[Federal Register Volume 88, Number 158 (Thursday, August 17, 2023)]
[Proposed Rules]
[Pages 56128-56390]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2023-16515]



[[Page 56127]]

Vol. 88

Thursday,

No. 158

August 17, 2023

Part II





Department of Transportation





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National Highway Traffic Safety Administration





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49 CFR Parts 531, 533, 535, and 537





Corporate Average Fuel Economy Standards for Passenger Cars and Light 
Trucks for Model Years 2027-2032 and Fuel Efficiency Standards for 
Heavy-Duty Pickup Trucks and Vans for Model Years 2030-2035; Proposed 
Rule

  Federal Register / Vol. 88, No. 158 / Thursday, August 17, 2023 / 
Proposed Rules  

[[Page 56128]]


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DEPARTMENT OF TRANSPORTATION

National Highway Traffic Safety Administration

49 CFR Parts 531, 533, 535, and 537

[NHTSA-2023-0022]
RIN 2127-AM55


Corporate Average Fuel Economy Standards for Passenger Cars and 
Light Trucks for Model Years 2027-2032 and Fuel Efficiency Standards 
for Heavy-Duty Pickup Trucks and Vans for Model Years 2030-2035

AGENCY: National Highway Traffic Safety Administration (NHTSA).

ACTION: Notice of proposed rulemaking.

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SUMMARY: NHTSA, on behalf of the Department of Transportation (DOT), is 
proposing new fuel economy standards for passenger cars and light 
trucks and fuel efficiency standards for model years (MYs) 2027-31 that 
increase at a rate of 2 percent per year for passenger cars and 4 
percent per year for light trucks, and new fuel efficiency standards 
for heavy-duty pickup trucks and vans (HDPUVs) for MYs 2030-2035 that 
increase at a rate of 10 percent per year. NHTSA is also setting forth 
proposed augural standards for MY 2032 passenger cars and light trucks, 
that would increase at 2 percent and 4 percent year over year, 
respectively, as compared to the prior year's standards. NHTSA 
currently projects that the proposed standards would require an 
industry fleet-wide average for passenger cars and light trucks of 
roughly 58 miles per gallon (mpg) in MY 2032 and an industry fleet-wide 
average for HDPUVs of roughly 2.6 gallons per 100 miles in MY 2038. 
NHTSA further projects that the proposed standards would reduce average 
fuel outlays over the lifetimes of passenger cars and light trucks by 
$1,043 and of HDPUVs by $439. These proposed standards are directly 
responsive to the agency's statutory mandate to improve energy 
conservation and reduce the nation's energy dependence on foreign 
sources.

DATES: 
    Comments: Comments are requested on or before October 16, 2023. See 
the SUPPLEMENTARY INFORMATION section on ``Public Participation,'' 
below, for more information about written comments.
    Public Hearings: NHTSA will hold one virtual public hearing during 
the public comment period. The agency will announce the specific date 
and web address for the hearing in a supplemental Federal Register 
notice. The agency will accept oral and written comments on the 
rulemaking documents and will also accept comments on the Draft 
Environmental Impact Statement (DEIS) at this hearing. The hearing will 
start at 9 a.m. Eastern time and continue until everyone has had a 
chance to speak. See the SUPPLEMENTARY INFORMATION section on ``Public 
Participation,'' below, for more information about the public hearing.

ADDRESSES: You may send comments, identified by Docket No. NHTSA-2023-
0022, by any of the following methods:
     Federal eRulemaking Portal: https://www.regulations.gov. 
Follow the instructions for submitting comments.
     Fax: (202) 493-2251.
     Mail: Docket Management Facility, M-30, U.S. Department of 
Transportation, West Building, Ground Floor, Rm. W12-140, 1200 New 
Jersey Avenue SE, Washington, DC 20590.
     Hand Delivery: Docket Management Facility, M-30, U.S. 
Department of Transportation, West Building, Ground Floor, Rm. W12-140, 
1200 New Jersey Avenue SE, Washington, DC 20590, between 9 a.m. and 4 
p.m. Eastern time, Monday through Friday, except Federal holidays.
    Instructions: All submissions received must include the agency name 
and docket number or Regulatory Information Number (RIN) for this 
rulemaking. All comments received will be posted without change to 
https://www.regulations.gov, including any personal information 
provided. For detailed instructions on sending comments and additional 
information on the rulemaking process, see the ``Public Participation'' 
heading of the SUPPLEMENTARY INFORMATION section of this document.
    Docket: For access to the dockets or to read background documents 
or comments received, please visit https://www.regulations.gov, and/or 
Docket Management Facility, M-30, U.S. Department of Transportation, 
West Building, Ground Floor, Rm. W12-140, 1200 New Jersey Avenue SE, 
Washington, DC 20590. The Docket Management Facility is open between 9 
a.m. and 4 p.m. Eastern time, Monday through Friday, except Federal 
holidays.

FOR FURTHER INFORMATION CONTACT: For technical and policy issues, 
Joseph Bayer, CAFE Program Division Chief, Office of Rulemaking, 
National Highway Traffic Safety Administration, 1200 New Jersey Avenue 
SE, Washington, DC 20590; email: [email protected]. For legal 
issues, Rebecca Schade, NHTSA Office of Chief Counsel, National Highway 
Traffic Safety Administration, 1200 New Jersey Avenue SE, Washington, 
DC 20590; email: [email protected].

SUPPLEMENTARY INFORMATION: 

Table of Acronyms and Abbreviations

------------------------------------------------------------------------
           Abbreviation                             Term
------------------------------------------------------------------------
AAA...............................  American Automobile Association.
AALA..............................  American Automotive Labeling Act.
AC................................  Air Conditioning.
ACC...............................  Advanced Clean Cars.
ACC I.............................  Advanced Clean Cars I.
ACC II............................  Advanced Clean Cars II.
ACME..............................  Adaptive Cylinder Management Engine.
ACT...............................  Advanced Clean Trucks.
ADEAC.............................  Advanced cylinder deactivation.
ADEACD............................  advanced cylinder deactivation on a
                                     dual overhead camshaft engine.
ADEACS............................  advanced cylinder deactivation on a
                                     single overhead camshaft engine.
ADSL..............................  Advanced diesel engine.
AEO...............................  Annual Energy Outlook.
AER...............................  All-Electric Range.
AERO..............................  Aerodynamic improvements.
AFV...............................  Alternative fuel vehicle.
AHSS..............................  advanced high strength steel.
AIS...............................  Abbreviated Injury Scale.
AMPC..............................  Advanced Manufacturing Production
                                     Tax Credit.
AMTL..............................  Advanced Mobility Technology
                                     Laboratory.

[[Page 56129]]

 
ANL...............................  Argonne National Laboratory.
ANSI..............................  American National Standards
                                     Institute.
APA...............................  Administrative Procedure Act.
AT................................  traditional automatic transmissions.
AWD...............................  All-Wheel Drive.
BEA...............................  Bureau of Economic Analysis.
BEV...............................  Battery electric vehicle.
BGEPA.............................  Bald and Golden Eagle Protection
                                     Act.
BISG..............................  Belt Mounted integrated starter/
                                     generator.
BMEP..............................  Brake Mean Effective Pressure.
BNEF..............................  Bloomberg New Energy Finance.
BPT...............................  Benefit-Per-Ton.
BSFC..............................  Brake-Specific Fuel Consumption.
BTW...............................  Brake and Tire Wear.
CAA...............................  Clean Air Act.
CAFE..............................  Corporate Average Fuel Economy.
CARB..............................  California Air Resources Board.
CBI...............................  Confidential Business Information.
CEGR..............................  Cooled Exhaust Gas Recirculation.
CEQ...............................  Council on Environmental Quality.
CFR...............................  Code of Federal Regulations.
CH4...............................  Methane.
CI................................  Compression Ignition.
CNG...............................  Compressed Natural Gas.
CO................................  Carbon Monoxide.
CO2...............................  Carbon Dioxide.
COVID.............................  Coronavirus disease of 2019.
CPM...............................  Cost Per Mile.
CR................................  Compression Ratio.
CRSS..............................  Crash Report Sampling System.
CVC...............................  Clean Vehicle Credit.
CVT...............................  Continuously Variable Transmissions.
CY................................  Calendar year.
CZMA..............................  Coastal Zone Management Act.
DCT...............................  Dual Clutch Transmissions.
DD................................  Direct Drive.
DEAC..............................  Cylinder Deactivation.
DEIS..............................  Draft Environmental Impact
                                     Statement.
DFS...............................  Dynamic Fleet Share.
DMC...............................  Direct Manufacturing Cost.
DOE...............................  Department of Energy.
DOHC..............................  Dual Overhead Camshaft.
DOI...............................  Department of the Interior.
DOT...............................  Department of Transportation.
DPM...............................  Diesel Particulate Matter.
DR................................  Discount Rate.
DSLI..............................  Advanced diesel engine with
                                     improvements.
DSLIAD............................  Advanced diesel engine with
                                     improvements and advanced cylinder
                                     deactivation.
EETT..............................  Electrical and Electronics Technical
                                     Team.
EF................................  Emission Factor.
EFR...............................  Engine Friction Reduction.
EIA...............................  U.S. Energy Information
                                     Administration.
EIS...............................  Environmental Impact Statement.
EISA..............................  Energy Independence and Security
                                     Act.
EJ................................  Environmental Justice.
E.O...............................  Executive Order.
EPA...............................  U.S. Environmental Protection
                                     Agency.
EPCA..............................  Energy Policy and Conservation Act.
EPS...............................  Electric Power Steering.
EFR...............................  Engine Friction Reduction.
ESA...............................  Endangered Species Act.
ETDS..............................  Electric Traction Drive System.
EV................................  Electric Vehicle.
FCC...............................  Fuel Consumption Credits.
FCEV..............................  Fuel Cell Electric Vehicle.
FCIV..............................  Fuel Consumption Improvement Value.
FCV...............................  Fuel Cell Vehicle.
FE................................  Fuel Efficiency.
FHWA..............................  Federal Highway Administration.
FIP...............................  Federal Implementation Plan.
FMVSS.............................  Federal Motor Vehicle Safety
                                     Standards.
FMY...............................  Final Model Year.
FRIA..............................  Final Regulatory Impact Analysis.
FTP...............................  Federal Test Procedure.

[[Page 56130]]

 
FWCA..............................  Fish and Wildlife Conservation Act.
FWD...............................  Front-Wheel Drive.
FWS...............................  U.S. Fish and Wildlife Service.
GCWR..............................  Gross Combined Weight Rating.
GDP...............................  Gross Domestic Product.
GES...............................  General Estimates System.
GGE...............................  Gasoline Gallon Equivalents.
GHG...............................  Greenhouse Gas.
GM................................  General Motors.
gpm...............................  gallons per mile.
GREET.............................  Greenhouse gases, Regulated
                                     Emissions, and Energy use in
                                     Transportation.
GVWR..............................  Gross Vehicle Weight Rating.
GWh...............................  Gigawatt hours.
HD................................  Heavy-Duty.
HDPUV.............................  Heavy-Duty Pickups and Vans.
HEG...............................  High Efficiency Gearbox.
HEV...............................  Hybrid Electric Vehicle.
HFET..............................  Highway Fuel Economy Test.
HVAC..............................  Heating, Ventilation, and Air
                                     Conditioning.
IACC..............................  improved accessories.
IAV...............................  IAV Automotive Engineering, Inc.
ICCT..............................  The International Council on Clean
                                     Transportation.
ICE...............................  Internal Combustion Engine.
IIHS..............................  Insurance Institute for Highway
                                     Safety.
IPCC..............................  Intergovernmental Panel on Climate
                                     Change.
IQR...............................  Interquartile Range.
IRA...............................  Inflation Reduction Act.
IWG...............................  Interagency Working Group.
LD................................  Light-Duty.
LDB...............................  Low Drag Brakes.
LDV...............................  Light-Duty Vehicle.
LE................................  Learning Effects.
LEV...............................  Low-Emission Vehicle.
LFP...............................  Lithium Iron Phosphate.
LIB...............................  Lithium-Ion Batteries.
LIVC..............................  Late Intake Valve Closing.
LT................................  Light truck.
MAX...............................  maximum values.
MBTA..............................  Migratory Bird Treaty Act.
MD................................  Medium-Duty.
MDHD..............................  Medium-Duty Heavy-Duty.
MDPCS.............................  Minimum Domestic Passenger Car
                                     Standard.
MDPV..............................  Medium-Duty Passenger Vehicle.
MIN...............................  minimum values.
MMTCO2............................  Million Metric Tons of Carbon
                                     Dioxide.
MMY...............................  Mid-Model Year.
MOU...............................  Memorandum of Understanding.
MOVES.............................  Motor Vehicle Emission Simulator.
MOVES3............................  latest version of MOVES.
MPG...............................  Miles Per Gallon.
mph...............................  Miles Per Hour.
MR................................  Mass Reduction.
MSRP..............................  Manufacturer Suggested Retail Price.
MY................................  Model Year.
NAAQS.............................  National Ambient Air Quality
                                     Standards.
NADA..............................  National Automotive Dealers
                                     Association.
NAICS.............................  North American Industry
                                     Classification System.
NAS...............................  National Academy of Sciences.
NCA...............................  Nickel Cobalt Aluminum.
NEMS..............................  National Energy Modeling System.
NEPA..............................  National Environmental Policy Act.
NESCCAF...........................  Northeast States Center for a Clean
                                     Air Future.
NHPA..............................  National Historic Preservation Act.
NHTSA.............................  National Highway Traffic Safety
                                     Administration.
NMC...............................  Nickel Manganese Cobalt.
NOX...............................  Nitrogen Oxide.
NPRM..............................  Notice of Proposed Rulemaking.
NRC...............................  National Research Council.
NREL..............................  National Renewable Energy
                                     Laboratory.
NTTAA.............................  National Technology Transfer and
                                     Advancement Act.
NVH...............................  Noise-Vibration-Harshness.
NVPP..............................  National Vehicle Population Profile.
OCR...............................  Optical Character Recognition.
OEM...............................  Original Equipment Manufacturer.

[[Page 56131]]

 
OHV...............................  Overhead Valve.
OMB...............................  Office of Management and Budget.
OPEC..............................  Organization of the Petroleum
                                     Exporting Countries.
ORNL..............................  Oak Ridge National Laboratories.
PC................................  Passenger Car.
PEF...............................  Petroleum Equivalency Factor.
PHEV..............................  Plug-in Hybrid Electric Vehicle.
PM................................  Particulate Matter.
PM2.5.............................  fine particulate matter.
PMY...............................  Pre-Model Year.
PRA...............................  Paperwork Reduction Act of 1995.
PRIA..............................  Preliminary Regulatory Impact
                                     Analysis.
PS................................  Power Split.
RC................................  Reference Case.
REMI..............................  Regional Economic Models, Inc.
RIN...............................  Regulation identifier number.
ROLL..............................  Tire rolling resistance.
RPE...............................  Retail Price Equivalent.
RRC...............................  Rolling Resistance Coefficient.
SAE...............................  Society of Automotive Engineers.
SBREFA............................  Small Business Regulatory
                                     Enforcement Fairness Act.
SC................................  Social Cost.
SCC...............................  Social Cost of Carbon.
SEC...............................  Securities and Exchange Commission.
SGDI..............................  Stoichiometric Gasoline Direct
                                     Injection.
SHEV..............................  Strong Hybrid Electric Vehicle.
SI................................  Spark Ignition.
SIP...............................  State Implementation Plan.
SKIP..............................  refers to skip input in market data
                                     input file.
SO2...............................  Sulfur Dioxide.
SOC...............................  State of Charge.
SOHC..............................  Single Overhead Camshaft.
SOX...............................  Sulfur Oxide.
SPR...............................  Strategic Petroleum Reserve.
SULEV.............................  Super-Ultra Low Emission Vehicles.
SUV...............................  Sport Utility Vehicle.
SwRI..............................  Southwest Research Institute.
TAR...............................  Technical Assessment Report.
TSD...............................  Technical Support Document.
UAW...............................  United Automobile, Aerospace &
                                     Agricultural Implement Workers of
                                     America.
UMRA..............................  Unfunded Mandates Reform Act of
                                     1995.
VCR...............................  Variable Compression Ratio.
VMT...............................  Vehicle Miles Traveled.
VOC...............................  Volatile Organic Compounds.
VSL...............................  Value of a Statistical Life.
VTG...............................  Variable Turbo Geometry.
VTGE..............................  Variable Turbo Geometry (Electric).
VVL...............................  Variable Valve Lift.
VVT...............................  Variable Valve Timing.
WF................................  Work Factor.
ZEV...............................  Zero Emission Vehicle.
------------------------------------------------------------------------

Does this action apply to me?

    This proposal affects companies that manufacture or sell new 
passenger automobiles (passenger cars), non-passenger automobiles 
(light trucks), and HDPUV, as defined under NHTSA's Corporate Average 
Fuel Economy (CAFE) regulations.\1\ Regulated categories and entities 
include:
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    \1\ ``Passenger car,'' ``light truck,'' and ``heavy-duty pickup 
trucks and vans'' are defined in 49 CFR part 523.

------------------------------------------------------------------------
                                   NAICS codes   Examples of potentially
            Category                   \A\          regulated entities
------------------------------------------------------------------------
Industry.......................          335111  Motor Vehicle
                                                  Manufacturers.
                                         336112
Industry.......................          811111  Commercial Importers of
                                                  Vehicles and Vehicle
                                                  Components.
                                         811112
                                         811198
                                         423110
Industry.......................          335312  Alternative Fuel
                                                  Vehicle Converters.
                                         336312

[[Page 56132]]

 
                                         336399
                                         811198
------------------------------------------------------------------------
\A\ North American Industry Classification System (NAICS).

    This list is not intended to be exhaustive, but rather provides a 
guide regarding entities likely to be regulated by this action. To 
determine whether particular activities may be regulated by this 
action, you should carefully examine the regulations. You may direct 
questions regarding the applicability of this action to the persons 
listed in FOR FURTHER INFORMATION CONTACT.

Table of Contents

I. Executive Summary
II. Technical Foundation for NPRM Analysis
    A. Why is NHTSA conducting this analysis?
    B. What is NHTSA analyzing?
    C. What inputs does the compliance analysis require?
    D. Technology Pathways, Effectiveness, and Cost
    E. Consumer Responses to Manufacturer Compliance Strategies
    F. Simulating Emissions Impacts of Regulatory Alternatives
    G. Simulating Economic Impacts of Regulatory Alternatives
    H. Simulating Safety Effects of Regulatory Alternatives
III. Regulatory Alternatives Considered in This NPRM
    A. General Basis for Alternatives Considered
    B. Regulatory Alternatives Under Consideration in This Proposal
IV. Effects of the Regulatory Alternatives
    A. Effects on Vehicle Manufacturers
    B. Effects on Society
    C. Physical and Environmental Effects
    D. Sensitivity Analysis
V. Basis for NHTSA's Tentative Conclusion That the Proposed Standards 
Are Maximum Feasible
    A. EPCA, as Amended by EISA
    B. Administrative Procedure Act
    C. National Environmental Policy Act
    D. Evaluating the EPCA/EISA Factors and Other Considerations To 
Arrive at the Proposed Standards 482
VI. Compliance and Enforcement
    A. Background
    B. Overview of Enforcement
    C. Proposed Changes
    D. Decision Not To Propose Non-Fuel Saving Credits or Flexibilities
VII. Public Participation
VIII. Regulatory Notices and Analyses
    A. Executive Order 12866, Executive Order 13563
    B. DOT Regulatory Policies and Procedures
    C. Executive Order 13990
    D. Environmental Considerations
    E. Regulatory Flexibility Act
    F. Executive Order 13132 (Federalism)
    G. Executive Order 12988 (Civil Justice Reform)
    H. Executive Order 13175 (Consultation and Coordination With Indian 
Tribal Governments)
    I. Unfunded Mandates Reform Act
    J. Regulation Identifier Number
    K. National Technology Transfer and Advancement Act
    L. Department of Energy Review
    M. Paperwork Reduction Act
    N. Privacy Act
IX. Regulatory Text

I. Executive Summary

    NHTSA, on behalf of the DOT, is proposing new corporate average 
fuel economy (CAFE) standards for passenger cars and light trucks \2\ 
for MYs 2027-2032,\3\ and new fuel efficiency standards for heavy-duty 
pickup trucks and vans \4\ (HDPUVs) for MYs 2030-2035. This proposal 
responds to NHTSA's statutory obligation to set CAFE and HDPUV 
standards at the maximum feasible level that the agency determines 
vehicle manufacturers can achieve in each MY, in order to improve 
energy conservation.\5\ Improving energy conservation by raising CAFE 
and HDPUV standard stringency not only helps consumers save money on 
fuel, but also improves national energy security and reduces harmful 
emissions.
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    \2\ Passenger cars are generally sedans, station wagons, and 
two-wheel drive crossovers and sport utility vehicles (CUVs and 
SUVs), while light trucks are generally four-wheel drive sport 
utility vehicles, pickups, minivans, and passenger/cargo vans. 
``Passenger car'' and ``light truck'' are defined more precisely at 
49 CFR part 523.
    \3\ As discussed further below, NHTSA is proposing six MYs of 
standards for each fleet, and notes that the final year of standards 
proposed for passenger cars and light trucks, MY 2032, is 
``augural,'' as in the 2012 final rule that established CAFE 
standards for MYs 2017 and beyond.
    \4\ HDPUVs are generally Class 2b/3 work trucks, fleet SUVs, 
work vans, and cutaway chassis-cab vehicles. ``Heavy-duty pickup 
trucks and vans'' are more precisely defined at 49 CFR part 523.
    \5\ See 49 U.S.C. 32902.
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    Based on the information currently before us, NHTSA estimates that 
this proposal, if implemented, would reduce gasoline consumption by 88 
billion gallons relative to baseline levels for passenger cars and 
light trucks, and by approximately 2.6 billion gallons relative to 
baseline levels for HDPUVs through calendar year 2050. Reducing fuel 
consumption has multiple benefits--it improves our nation's energy 
security, it saves consumers money, and reduces harmful pollutant 
emissions that lead to adverse human and environmental health outcomes 
and climate change. NHTSA estimates that this proposal, if implemented, 
could reduce carbon dioxide (CO2) emissions by 885 million 
metric tons for passenger cars and light trucks, and by 22 million 
metric tons for HDPUVs through calendar year 2050. While consumers 
would pay more for new vehicles upfront, we estimate that they would 
save money on fuel costs over the lifetimes of those new vehicles--
lifetime fuel savings exceed modeled regulatory costs by roughly $100, 
on average, for passenger car and light truck buyers of MY 2032 
vehicles, and roughly $300, on average, for HDPUV buyers of MY 2038 
vehicles. Net benefits for the preferred alternative for passenger cars 
and light truck are estimated to be $16.8 billion at a 3 percent 
discount rate (DR), and $8.4 billion at a 7 percent DR, and for HDPUVs, 
net benefits are estimated to be $2.2 billion at a 3 percent DR, and 
$1.4 billion at a 7 percent DR.
    NHTSA's proposal is also consistent with Executive Order (E.O.) 
14037, ``Strengthening American Leadership in Clean Cars and Trucks,'' 
(August 5, 2021), which directs the Secretary of Transportation (by 
delegation, NHTSA) to develop rulemakings under Energy Independence and 
Security Act of 2007 (EISA) \6\ to consider beginning work on a 
rulemaking to establish new fuel economy standards for passenger cars 
and light trucks beginning with MY 2027 and extending through at least 
MY 2030, and to consider beginning work on a rulemaking to establish 
new fuel efficiency standards for HDPUVs beginning with MY 2028 and 
extending through at least MY 2030, consistent with applicable law.\7\
---------------------------------------------------------------------------

    \6\ See 49 U.S.C. Chapter 329, generally.
    \7\ Id, Sec. 2.
---------------------------------------------------------------------------

    The record for this proposal comprised this Notice of Proposed 
Rulemaking (NPRM), a Draft Technical

[[Page 56133]]

Support Document (Draft TSD), a Preliminary Regulatory Impact 
Assessment (PRIA), and a Draft EIS, along with extensive analytical 
documentation, supporting references, and many other resources. Most of 
these resources are available on NHTSA's website,\8\ and other 
references not available on NHTSA's website can be found in the 
rulemaking docket, the docket number of which is listed at the 
beginning of this preamble.
---------------------------------------------------------------------------

    \8\ See National Highway Traffic Safety Administration. 2023. 
Corporate Average Fuel Economy. Available at: https://www.nhtsa.gov/laws-regulations/corporate-average-fuel-economy. (Accessed: May 31, 
2023).
---------------------------------------------------------------------------

    The proposal considers a range of regulatory alternatives for each 
fleet, consistent with NHTSA's obligations under the Administrative 
Procedure Act (APA), National Environmental Policy Act (NEPA) and E.O. 
12866. Specifically, NHTSA considered four regulatory alternatives for 
passenger cars and light trucks, as well as the No-Action Alternative. 
Each alternative is labeled for the type of vehicle and the rate of 
increase in fuel economy stringency, for example, PC1LT3 represents a 1 
percent increase in Passenger Car standards and a 3 percent increase in 
Light Truck standards. We include three regulatory alternatives for 
HDPUVs, each representing different possible rates of year-over-year 
increase in the stringency of new fuel economy and fuel efficiency 
standards, as well as the No-Action Alternative. For example, HDPUV4 
represents a 4 percent increase in fuel efficiency standards applicable 
to HDPUVs. The regulatory alternatives are as follows: \9\
---------------------------------------------------------------------------

    \9\ In a departure from recent CAFE rulemaking trends, we have 
applied different rates of stringency increase to the passenger car 
and the light truck fleets. Rather than have both fleets increase 
their respective standards at the same rate, light truck standards 
will increase at a different rate than passenger car standards. Each 
action alternative evaluated for this proposal has a passenger car 
fleet rate-of-increase of fuel economy lower than the rate-of-
increase of fuel economy for the light truck fleet. As discussed in 
Section III below, this is primarily due to NHTSA's assessment that 
manufacturers have already made substantial progress in technology 
application to passenger cars, such that the possibility for further 
fuel economy improvements to Internal Combustion Engine- and hybrid-
based vehicles is relatively limited, while there appears to be much 
more room to improve in the light truck fleet. This is consistent 
with NHTSA's obligation to set maximum feasible CAFE standards 
separately for passenger cars and light trucks (see 49 U.S.C. 
32902), which gives NHTSA discretion, by law, to set CAFE standards 
that increase at different rates for cars and trucks. Again, the 
reasons for this approach are discussed in Section III of this 
preamble. Section V of this preamble also discusses in greater 
detail how this approach carries out NHTSA's responsibility under 
EPCA to set maximum feasible standards for both passenger cars and 
light trucks.

Table I-1--Regulatory Alternatives Under Consideration for MYs 2027-2032
            Passenger Car and Light Truck CAFE Standards \10\
------------------------------------------------------------------------
                                                 Passenger
                                                    car      Light truck
                                                 stringency   stringency
             Name of  alternative                increases,   increases,
                                                 year-over-   year-over-
                                                  year (%)     year (%)
------------------------------------------------------------------------
No-Action Alternative.........................          N/A          N/A
Alternative PC1LT3............................            1            3
Alternative PC2LT4 (Preferred Alternative)....            2            4
Alternative PC3LT5............................            3            5
Alternative PC6LT8............................            6            8
------------------------------------------------------------------------


Table I-2--Regulatory Alternatives Under Consideration for MYs 2030-2035
                  HDPUV Fuel Efficiency Standards \11\
------------------------------------------------------------------------
                                                                HDPUV
                                                              stringency
                    Name of alternative                       increases,
                                                              year-over-
                                                               year (%)
------------------------------------------------------------------------
No-Action Alternative......................................          N/A
Alternative HDPUV4.........................................            4
Alternative HDPUV10 (Preferred Alternative)................           10
Alternative HDPUV14........................................           14
------------------------------------------------------------------------

    NHTSA is proposing to increase stringency at 2 percent per year for 
passenger cars and at 4 percent per year for light trucks, year over 
year from MY 2027 through MY 2032, and at 10 percent per year for 
HDPUVs, year over year from MY 2030 through MY 2035. The regulatory 
alternatives representing these proposals are called ``PC2LT4'' for 
passenger cars and light trucks, and ``HDPUV10'' for HDPUVs. NHTSA 
tentatively concludes that these levels are the maximum feasible for 
these MYs as discussed in more detail in Section V of this preamble. 
NHTSA is proposing standards that rise at a more rapid rate for light 
trucks than for passenger cars. As explained in more detail below, the 
agency believes that there is more room to improve the fuel economy of 
light trucks, in a cost-effective way, and that the benefits of 
requiring more improvement from light trucks will be significant given 
their high usage and the fact that they make up an ever-larger 
percentage of the overall fleet. Passenger cars, on the other hand, 
have been improving at a rapid rate for many years in succession, and 
the available improvements for that fleet are fewer, particularly given 
the statutory constraints that prevent NHTSA from considering the fuel 
economy of battery electric vehicles (BEVs) in determining maximum 
feasible CAFE standards.\12\ NHTSA notes that due to the statutory 
constraints that prevent NHTSA from considering the fuel economy of 
dedicated alternative fueled vehicles, the full fuel economy of dual-
fueled alternative fueled vehicles, and the availability of over-
compliance credits when determining what standards are maximum 
feasible, many aspects of our analysis are different from what they 
would otherwise be without the statutory restrictions--in particular, 
the technologies chosen to model possible compliance options, the 
estimated costs, benefits, and achieved levels of fuel economy, as well 
as the current and projected adoption of alternative fueled vehicles. 
NHTSA evaluates the results of that constrained analysis by weighing 
the four enumerated statutory factors to determine which standards are 
maximum feasible.
---------------------------------------------------------------------------

    \10\ Percentages in the table represent the year of year 
reduction in gal/mile applied to the mpg values on the target curves 
shown in Figure 1-1. The reduction in gal/mile results in an incrase 
mpg.
    \11\ For HDPUVs, the different regulatory alternatives are also 
defined in terms of percent-increases in stringency from year to 
year, but in terms of fuel consumption reductions rather than fuel 
economy increases, so that increasing stringency appears to result 
in standards going down (representing a direct reduction in fuel 
consumed) over time rather than up. Also, unlike for the passenger 
car and light truck standards, because HDPUV standards are measured 
using a fuel consumption metric, year-over-year percent changes do 
actually represent gallon/mile differences across the work-factor 
range. Under each action alternative, the stringency changes at the 
same percentage rate in each model year in the rulemaking time 
frame.
    \12\ 49 U.S.C. 32902(h) states that when determining what levels 
of CAFE standards are maximum feasible, NHTSA ``(1) may not consider 
the fuel economy of dedicated automobiles [including battery-
electric vehicles]; (2) shall consider dual fueled automobiles to be 
operated only on gasoline or diesel fuel; and (3) may not consider, 
when prescribing a fuel economy standard, the trading, transferring, 
or availability of credits under section 32903.''
---------------------------------------------------------------------------

    In this action, NHTSA is proposing six MYs of standards for each 
fleet. For passenger cars and light trucks, NHTSA notes that the final 
year of standards proposed, MY 2032, is ``augural,'' as in the 2012 
final rule which established CAFE standards for MYs 2017 and beyond. 
Augural standards mean that they are NHTSA's best estimate of what the 
agency would propose, based on the information currently before it, if 
the

[[Page 56134]]

agency had authority to set CAFE standards for more than five MYs in 
one action. The augural standards do not, and will not, have any effect 
in themselves and will not be binding unless adopted in a subsequent 
rulemaking. Consistent with past practice, NHTSA is including augural 
standards for MY 2032 to give its best estimate of what those standards 
would be to provide as much predictability as possible to manufacturers 
and to be consistent with the time frame of the proposed Environmental 
Protection Agency (EPA) standards for greenhouse gas (GHG) emissions 
from motor vehicles. Due to statutory lead time constraints for HDPUV 
standards, NHTSA's proposal for HDPUV standards must begin with MY 
2030. There is no restriction on the number of MYs for which NHTSA may 
set HDPUV standards, so none of the HDPUV standards are augural. NHTSA 
also requests comment on a scenario where the regulatory alternatives 
would extend only through MY 2032, which coincides with the time frame 
of the EPA proposed GHG standards for this vehicle segment.
    NHTSA requests comment on the full range of standards encompassed 
between the No-Action Alternative and Alternative PC6LT8 for MYs 2027-
2032 Passenger Cars, as well as comments on the range of standards 
encompassed for light trucks, and on the full range of standards 
encompassed between the No-Action Alternative and Alternative HDPUV14 
for MYs 2030-2035 HDPUVs. NHTSA expressly asks for comment on 
combinations of standards that may not be explicitly identified in this 
proposal, including standards between the No-Action Alternative and 
PC1/LT3, as well as between PC3/LT5 and PC6/LT8. NHTSA also notes that 
passenger car and light truck stringency may move independently of one 
another, and that rates of increase may vary by model year.
    The proposed CAFE standards remain vehicle-footprint-based, like 
the current CAFE standards in effect since MY 2011, and the proposed 
HDPUV standards remain work-factor-based, like the HDPUV standards 
established in the 2011 ``Phase 1'' rulemaking and continued to be used 
in 2016 ``Phase 2'' rulemaking. The footprint of a vehicle is the area 
calculated by multiplying the wheelbase times the track width, 
essentially the rectangular area of a vehicle measured from tire to 
tire where the tires hit the ground. The work factor (WF) of a vehicle 
is a unit established to measure payload, towing capability, and 
whether or not a vehicle has four-wheel drive. This means that the 
proposed standards are defined by mathematical equations that represent 
linear functions relating vehicle footprint to fuel economy targets for 
passenger cars and light trucks,\13\ and relating WF to fuel 
consumption targets for HDPUVs.
---------------------------------------------------------------------------

    \13\ Generally, passenger cars have more stringent targets than 
light trucks regardless of footprint, and smaller vehicles will have 
more stringent targets than larger vehicles, because smaller 
vehicles are generally more fuel efficient No individual vehicle or 
vehicle model need meet its target exactly, but a manufacturer's 
compliance is determined by how its average fleet fuel economy 
compares to the average fuel economy of the targets of the vehicles 
it manufactures.
---------------------------------------------------------------------------

    The target curves for passenger cars, light trucks, and 
compression-ignition and spark-ignition HDPUVs are set forth below; 
curves for MYs prior to the years of the rulemaking time frame are 
included in the figures for context. NHTSA underscores that the 
equations and coefficients defining the curves are the CAFE and HDPUV 
standards, and not the mpg and gallon/100-mile estimates that the 
agency currently estimates could result from manufacturers complying 
with the proposed curves. We provide mpg and gallon/100-mile estimates 
for ease of understanding after we illustrate the footprint curves, but 
the equations and coefficients are the actual standards.
BILLING CODE 4910-59-P

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BILLING CODE 4910-59-C
    NHTSA is also proposing new minimum domestic passenger car CAFE 
standards (MDPCS) for MYs 2027-2032 as required by the Energy Policy 
and Conservation Act of 1975 (EPCA), as amended by the EISA, and 
applied to vehicles defined as manufactured in the United States. 
Section 32902(b)(4) of 49 U.S.C. requires NHTSA to project the minimum 
domestic standard when it promulgates passenger car standards for a MY, 
so the minimum standards are estimated as specific mpg values and will 
be finalized as specific mpg values when NHTSA sets final passenger car 
standards for MYs 2027-2032. NHTSA retains the 1.9 percent offset first 
used in the 2020 final rule, reflecting prior differences between 
passenger car footprints originally forecast by the agency and 
passenger car footprints as they occurred in the real world, such that 
the minimum domestic passenger car standard is as shown in the table 
below. NHTSA requests comment on this approach.

[[Page 56137]]



                     Table I-3--Proposed Minimum Domestic Passenger Car Standard With Offset
                                                      [mpg]
----------------------------------------------------------------------------------------------------------------
                  MY 2027                      MY 2028       MY 2029       MY 2030       MY 2031       MY 2032
----------------------------------------------------------------------------------------------------------------
54.1......................................         55.3          56.4          57.5          58.7          59.9
----------------------------------------------------------------------------------------------------------------

    Recognizing that many readers think about CAFE standards in terms 
of the mpg values that the standards are projected to eventually 
require, NHTSA currently estimates that the proposed standards would 
require roughly 57.8 mpg in MY 2032, on an average industry fleet-wide 
basis, for passenger cars and light trucks. NHTSA notes both that real-
world fuel economy is generally 20-30 percent lower than the estimated 
required CAFE level stated above,\14\ and also that the actual CAFE 
standards are the footprint target curves for passenger cars and light 
trucks. This last note is important, because it means that the ultimate 
fleet-wide levels will vary depending on the mix of vehicles that 
industry produces for sale in those MYs. NHTSA also calculates and 
presents ``estimated achieved'' fuel economy levels, which differ 
somewhat from the estimated required levels for each fleet, for each 
year.\15\ NHTSA estimates that the industry-wide average fuel economy 
achieved in MY 2032 for passenger cars and light trucks combined could 
increase from about 53.6 mpg under the No-Action Alternative to 57.6 
mpg under the proposed standards.
---------------------------------------------------------------------------

    \14\ CAFE compliance is evaluated per 49 U.S.C. 32904(c) Testing 
and Calculation Procedures, which states that the EPA Administrator 
(responsible under EPCA/EISA for measuring vehicle fuel economy) 
shall use the same procedures used for model year 1975 (weighted 55 
percent urban cycle and 45 percent highway cycle) or comparable 
procedures. Colloquially, this is known as the 2-cycle test. The 
``real-world'' or 5-cycle evaluation includes the 2-cycle tests, and 
three additional tests that are used to adjust the city and highway 
estimates to account for higher speeds, air conditioning use, and 
colder temperatures. In addition to calculating vehicle fuel 
economy, EPA is responsible for providing the fuel economy data that 
is used on the fuel economy label on all new cars and light trucks, 
which uses the ``real-world'' values. In 2006, EPA revised the test 
methods used to determine fuel economy estimates (city and highway) 
appearing on the fuel economy label of all new cars and light trucks 
sold in the U.S., effective with 2008 model year vehicles.
    \15\ NHTSA's analysis reflects that manufacturers nearly 
universally make the technological improvements prompted by CAFE 
standards at times that coincide with existing product ``refresh'' 
and ``redesign'' cycles, rather than applying new technology every 
year regardless of those cycles. It is significantly more cost-
effective to make fuel-economy-improving technology updates when a 
vehicle is being updated anyway. See TSD 2.2.1.7 for additional 
discussion about manfacturer refresh and redesign cycles.
    \16\ There is no actual legal requirement for combined passenger 
car and light truck fleets, but NHTSA presents information this way 
in recognition of the fact that many readers will be accustomed to 
seeing such a value.

               Table I-4--Estimated Required Average and Estimated Achieved Average of CAFE Levels
                     [mpg] for passenger cars and light trucks, preferred alternative PC2LT4
----------------------------------------------------------------------------------------------------------------
               Fleet                  MY 2027      MY 2028      MY 2029      MY 2030      MY 2031      MY 2032
----------------------------------------------------------------------------------------------------------------
Passenger Cars:
    Estimated Required............         60.0         61.2         62.5         63.7         65.1         66.4
    Estimated Achieved............         63.5         65.3         67.5         69.3         71.3         72.8
Light Trucks:
    Estimated Required............         44.4         46.2         48.2         50.2         52.2         54.4
    Estimated Achieved............         44.2         45.7         47.5         49.0         50.9         52.4
Combined:
    Estimated Required \16\.......         48.4         50.1         51.9         53.8         55.7         57.8
    Estimated Achieved............         49.0         50.5         52.3         54.0         56.0         57.6
----------------------------------------------------------------------------------------------------------------

    To the extent that manufacturers appear to be over-complying in our 
analysis with required fuel economy levels in the passenger car fleet, 
NHTSA notes that this is due to the inclusion of several all-electric 
manufacturers in the baseline analysis, which affects the overall 
average achieved levels. Manufacturers with more traditional fleets do 
not over-comply at such high levels in our analysis, and our analysis 
considers the compliance paths for both manufacturer groups. In 
contrast, while it looks like manufacturers are falling short of 
required fuel economy levels in the light truck fleet (and choosing 
instead to pay civil penalties), NHTSA notes that this appears to be 
the result of a relatively small number of companies, which affects the 
overall average achieved levels. The agency's overall assessment is 
that the light truck standards are maximum feasible even though they 
may be challenging for some individual companies to achieve. Please see 
Section V.D of this preamble for more discussion on these topics and 
how the agency has considered them in determining maximum feasible 
standards for this proposal.
    For HDPUVs, NHTSA currently projects that the standards would 
require, on an average industry fleet-wide basis for the HDPUV fleet, 
roughly 2.638 gallons per 100 miles \17\ in MY 2035. HDPUV standards 
are attribute-based like passenger car and light truck standards, so 
here, too, ultimate fleet-wide levels will vary depending on what 
industry produces for sale.
---------------------------------------------------------------------------

    \17\ The HDPUV standards measure compliance in direct fuel 
consumption and uses gallons consumed per 100 miles of operation as 
a metric. See 49 CFR 535.6.

[[Page 56138]]



Table I-5--Estimated Required Average and Estimated Achieved Average of Fuel Efficiency Levels (gal/100 miles for HDPUVs, preferred alternative HDPUV10)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                        MY 2030          MY 2031          MY 2032          MY 2033          MY 2034          MY 2035
--------------------------------------------------------------------------------------------------------------------------------------------------------
Estimated Required................................           4.427            4.051            3.646            3.255            2.930            2.638
Estimated Achieved................................           3.266            2.764            2.759            2.160            2.157            2.153
--------------------------------------------------------------------------------------------------------------------------------------------------------

    For all fleets, average requirements and average achieved CAFE and 
HDPUV fuel efficiency levels would ultimately depend on manufacturers' 
and consumers' responses to standards, technology developments, 
economic conditions, fuel prices, and other factors.
    NHTSA recognizes that the 2022 rule for MYs 2024-2026 involved 
higher rates of increase based on our assessment at the time of what 
technologies were available for deployment in that fleet. Our technical 
analysis for this proposal keeps that same general framework as the 
2022 final rule, but as applied to a more-recent fleet that includes 
the vehicles that will be subject to the 2024-2026 standards. Thus, 
since May 2022, NHTSA has updated technologies considered in our 
analysis (removing technologies which are already universal or nearly 
so and technologies which are exiting the fleet, adding certain 
advanced engine technologies; \18\) updated macroeconomic input 
assumptions, as with each round of rulemaking analysis; improved user 
control of various input parameters; updated our approach to modeling 
manufacturers' expected compliance with states' Zero Emission Vehicle 
(ZEV) programs; accounted for potential changes to DOE's Petroleum 
Equivalency Factor (PEF), which is proposed to be changed,\19\ for the 
baseline assumptions; expanded accounting for Federal incentives such 
as Inflation Reduction Act programs; expanded procedures for estimating 
new vehicle sales and fleet shares; updated inputs for projecting 
aggregate light-duty Vehicle Miles Traveled (VMT); and added various 
output values and options.\20\
---------------------------------------------------------------------------

    \18\ See Draft TSD Chapter 1.1 for a complete list of 
technologies added or removed from the analysis.
    \19\ For more information on DOE's proposal, see 88 FR 21525. 
For more information on how DOE's proposal affects NHTSA's results 
in this proposal, please see Chapter 9 of the PRIA.
    \20\ See TSD Chapter 1.1 for a detailed discussion of analysis 
updates.
---------------------------------------------------------------------------

    NHTSA tentatively concludes, as we explain in more detail below, 
that Alternative PC2LT4 is the maximum feasible alternative that 
manufacturers can achieve for MYs 2027-2032 passenger cars and light 
trucks, based on a variety of reasons. Energy conservation is still 
paramount, for the consumer benefits, energy security benefits, and 
environmental benefits that it provides. Moreover, although the vehicle 
fleet is undergoing a significant transformation now and in the coming 
years, for reasons other than the CAFE standards, NHTSA believes that a 
significant percentage of the on-road (and new) vehicle fleet may 
remain propelled by internal combustion engines (ICEs) through 2032. 
NHTSA believes that the alternative we are proposing will encourage 
manufacturers producing those ICE vehicles during the standard-setting 
time frame to achieve significant fuel economy, improve energy 
security, and reduce harmful pollution by a large amount. At the same 
time, NHTSA is proposing standards that our estimates suggest will 
continue to save consumers money and fuel over the lifetime of their 
vehicles, particularly light truck buyers, while being economically 
practicable and technologically feasible for manufacturers to achieve.
    Although Alternatives PC3LT5 and PC6LT8 would conserve more energy 
and provide greater fuel savings benefits and certain pollutant 
emissions reductions, NHTSA's statutorily-constrained analysis 
currently estimates that those alternatives may not be achievable for 
many manufacturers in the rulemaking time frame. Additionally, 
compliance with those more stringent alternatives would impose 
significant costs on individual consumers without corresponding fuel 
savings benefits large enough to, on average, offset those costs. 
Within that framework, NHTSA's analysis suggests that the more 
stringent alternatives could push more technology application than 
would be economically practicable, given anticipated baseline activity 
that will already be consuming manufacturer resources and capital. In 
contrast to Alternatives PC3LT5 and PC6LT8, Alternative PC2LT4 comes at 
a cost we believe the market can bear without creating consumer 
acceptance or sales issues, appears to be much more achievable, and 
will still result in consumer net benefits on average. The proposed 
alternative also achieves large fuel savings benefits and significant 
reductions in emissions. NHTSA tentatively concludes Alternative PC2LT4 
is the appropriate choice given this record.
    For HDPUVs, NHTSA tentatively concludes, as explained in more 
detail below, that Alternative HDPUV10 is the maximum feasible 
alternative that manufacturers can achieve for MYs 2030-2035 HDPUVs. It 
has been seven years since NHTSA revisited HDPUV standards, and our 
analysis suggests that there is much opportunity for cost-effective 
improvements in this segment, broadly speaking. At the same time, we 
recognize that these vehicles are primarily used to conduct work for a 
large number of businesses. Although Alternative HDPUV14 would conserve 
more energy and provide greater fuel savings benefits and 
CO2 emissions reductions, it is significantly more costly 
than HDPUV10, and NHTSA currently estimates that Alternative HDPUV10 is 
the most cost-effective under a variety of metrics and at either a 3 
percent or a 7 percent DR, while still being appropriate and 
technologically feasible. NHTSA is allowed to consider electrification 
in determining maximum feasible standards for HDPUVs. As a result, 
NHTSA tentatively concludes that HDPUV10 is the appropriate choice 
given the record discussed in more detail below, and we believe it 
balances EPCA's overarching objective of energy conservation while 
remaining cost-effective and technologically feasible.
    For passenger cars and light trucks, NHTSA estimates that this 
proposal would reduce average fuel outlays over the lifetimes of MY 
2032 vehicles by about $1,043 per vehicle, while increasing the average 
cost of those vehicles by about $932 over the baseline, at a 3 percent 
DR. With climate benefits and all other benefits and costs discounted 
at 3 percent, when considering the entire CAFE fleet for MYs 1983-2032, 
NHTSA estimates $58.6 billion in monetized costs and $75.5 billion in 
monetized benefits attributable to the proposed standards, such that 
the present value of aggregate net monetized benefits to society would 
be $16.8 billion.\21\
---------------------------------------------------------------------------

    \21\ These values are from our ``model year'' analysis, 
reflecting the entire fleet from MYs 1983-2032, consistent with past 
practice. Model year and calendar year perspectives are discussed in 
more detail below in this section.

---------------------------------------------------------------------------

[[Page 56139]]

    For HDPUVs, NHTSA estimates that this proposal could reduce average 
fuel outlays over the lifetimes of MY 2038 vehicles by about $439 per 
vehicle, while increasing the average cost of those vehicles by about 
$131 over the baseline, at a 3 percent DR. With climate benefits and 
all other benefits and costs discounted at 3 percent, when considering 
the entire on-road HDPUV fleet for CYs 2022-2050, NHTSA estimates $2.1 
billion in monetized costs and $4.3 billion in monetized benefits 
attributable to the proposed standards, such that the present value of 
aggregate net monetized benefits to society would be $2.2 billion.\22\
---------------------------------------------------------------------------

    \22\ These values are from our ``calender year'' analysis, 
reflecting the on-the-road fleet from CYs 2022-2050. Model year and 
calendar year perspectives are discussed in more detail below in 
this section.
---------------------------------------------------------------------------

    These assessments do not include important unquantified effects, 
such as energy security benefits, equity and distributional effects, 
and certain air quality benefits from the reduction of toxic air 
pollutants and other emissions, among other things, so that the net 
benefit estimate is a conservative one.\23\ In addition, the power 
sector emissions modeling reflected in this analysis does not 
incorporate the most up-to-date data on the future evolution of the 
power sector, and the emission projections are higher than analyses 
using more recent data indicate is likely to be the case. This modeling 
will be updated in the final rule.
---------------------------------------------------------------------------

    \23\ These cost and benefit estimates are based on many 
different and uncertain inputs, and NHTSA has conducted several 
dozen sensitivity analyses varying individual inputs to evaluate the 
effect of that uncertainty. For example, while NHTSA's reference 
case analysis constrains the application of high compression ratio 
engines to some vehicles based on performance and other 
considerations, we also conducted a sensitivity analysis that 
removed all of those constraints. Results of this and other 
sensitivity analyses are discussed in Section IV.D of this preamble, 
in Chapter 9 of the PRIA, and (if large or otherwise significant) in 
Section V.D of this preamble.
---------------------------------------------------------------------------

    Table I-6 presents aggregate benefits and costs for new vehicle 
buyers and for the average individual new vehicle buyer.

     Table I-6--Benefits and Costs for the Light Duty (LD) and HDPUV
                         Preferred Alternatives
            [2021$, 3 percent annual DR, 3 percent SC-GHG DR]
------------------------------------------------------------------------
                                              PC2LT4          HDPUV10
------------------------------------------------------------------------
Aggregate Buyer Benefits and Costs ($b):
    Costs...............................            43.3             1.4
    Benefits............................            59.4             3.2
    Net Benefits........................            16.1             1.7
Aggregate Societal Benefits and Costs
 (including buyer, $b):
    Costs...............................            58.6             2.1
    Benefits............................            75.5             4.3
    Net Benefits........................            16.8             2.2
Per-vehicle ($):
    Regulatory Costs....................             932             131
    Lifetime Fuel Savings...............           1,043             439
------------------------------------------------------------------------
Notes: Total buyer costs and benefits include those presented in more
  detail in Table V-6 and Table V-7. Societal costs and benefits include
  those presented in more detail in Table V-8 and Table V-9. Aggregate
  light-duty measures are computed for the lifetimes of the total light-
  duty fleet produced through MY 2032. Aggregate HDPUV measures are
  computed for the on-road HDPUV fleet for CYs 2022-2050. Per-vehicle
  costs are those for MY 2032 (LD) and MY 2038 (HDPUV).

    NHTSA recognizes that EPA has recently issued a proposal to set new 
multi-pollutant emissions standards for MYs 2027 and later light-duty 
(LD) and medium-duty (MD) vehicles.\24\ EPA describes its proposal as 
building upon EPA's final standards for Federal GHG emissions standards 
for passenger cars and light trucks for MYs 2023 through 2026 and 
leverages advances in clean car technology to unlock benefits to 
Americans ranging from reducing pollution, to improving public health, 
to saving drivers money through reduced fuel and maintenance costs.\25\ 
EPA's proposed standards would phase in over MYs 2027 through 2032.\26\
---------------------------------------------------------------------------

    \24\ See Enviromental Protection Agency. 2023. Proposed Rule: 
Multi-Pollutant Emissions Standards for Model Years 2027 and Later 
Light-Duty and Medium-Duty Vehicles. Last revised: May 25, 2023. 
Available at: https://www.epa.gov/regulations-emissions-vehicles-and-engines/proposed-rule-multi-pollutant-emissions-standards-model. 
(Accessed: May 31, 2023).
    \25\ Id.
    \26\ Id.
---------------------------------------------------------------------------

    NHTSA coordinated with EPA in developing our proposal to avoid 
inconsistencies and produce requirements that are consistent with 
NHTSA's statutory authority. The proposals nevertheless differ in 
important ways. First, NHTSA's proposal, consistent with its statutory 
authority and mandate under EPCA/EISA, focuses on improving vehicle 
fuel economy and not directly on reducing vehicle emissions--though 
reduced emissions are a follow-on effect of improved fuel economy. 
Second, the biggest difference between the two proposals is due to 
EPCA/EISA's statutory prohibition against NHTSA considering the fuel 
economy of dedicated alternative fueled vehicles, including BEVs, and 
including the full fuel economy of dual-fueled alternative fueled 
vehicles in determining the maximum feasible fuel economy level that 
manufacturers can achieve for passenger cars and light trucks, even 
though manufacturers may use BEVs and dual-fueled alternative fuel 
vehicles (AFV) to comply with CAFE standards. EPA is not prohibited 
from considering BEVs as a compliance option. EPA's proposal is 
informed by, among other considerations, trends in the automotive 
industry (including the proliferation of announced investments by 
automakers in electrifying their fleets), tax incentives under the 
Inflation Reduction Act (IRA), and other forces that are leading to a 
rapid transition in the automotive industry away from ICEs.\27\ NHTSA, 
in contrast, may not consider BEVs as a compliance option for the 
passenger car and light truck fleets even though manufacturers may, in 
fact, use BEVs to comply with CAFE standards. This constraint means 
that not only are NHTSA's stringency rates of increase different from 
EPA's but also the shapes

[[Page 56140]]

of our standards are different based upon the different scopes.
---------------------------------------------------------------------------

    \27\ Enviromental Protection Agency. 2023. Proposed Rule: Multi-
Pollutant Emissions Standards for Model Years 2027 and Later Light-
Duty and Medium-Duty Vehicles. EPA-420-F-23-009. Offce of 
Transportation and Air Quality. Available at: https://www.epa.gov/regulations-emissions-vehicles-and-engines/proposed-rule-multi-pollutant-emissions-standards-model. (Accessed: May 31, 2023).
---------------------------------------------------------------------------

    Recognizing that the agencies are implementing statutory mandates 
to set maximum feasible fuel economy standards and to address dangerous 
air pollution, and that both standards affect the same fleet of 
vehicles, we seek comment on how best to optimize the effectiveness of 
NHTSA's standards consistent with the statutory factors. Our 
statutorily constrained simulated industry response shows a reasonable 
path forward to compliance with CAFE standards, but we want to stress 
that our analysis simply shows feasibility and does not dictate a 
required path to compliance. Because the standards are performance-
based, manufacturers are always free to apply their expertise to find 
the appropriate technology path that best meets all desired outcomes. 
Indeed, as explained in greater detail later on in this proposal, it is 
entirely possible and reasonable that a vehicle manufacturer will use 
technology options to meet NHTSA's proposed standards that are 
significantly different from what NHTSA's analysis for this proposal 
suggests given the statutory constraints under which it operates. NHTSA 
will coordinate with EPA to ensure NHTSA's standards take account of 
statutory objectives and constraints while minimizing compliance costs. 
NHTSA seeks input to help inform these objectives.
    As discussed before, NHTSA does not face the same statutory 
limitations in setting standards for HDPUVs as it does in setting 
standards for passenger cars and light trucks. This allows NHTSA to 
consider a broader array of technologies in setting maximum feasible 
standards for HDPUVs. However, we are still considerate of factors that 
allow these vehicles to maintain utility and do work for the consumer 
when we set the standards.
    Additionally, NHTSA has considered and accounted for manufacturers' 
expected compliance with California's Advanced Clean Cars (ACC) and 
Advanced Clean Trucks (ACT) regulations in our analysis, as part of the 
analytical baseline.\28\ We find that manufacturers will comply with 
ZEV requirements in California and a number of other states in the 
absence of CAFE standards, and accounting for that expected compliance 
allows us to present a more realistic picture of the state of fuel 
economy even in the absence of changes to the CAFE standards. 
Reflecting expected compliance with the ZEV mandates in the analysis 
improves the accuracy of the baseline in reflecting the state of the 
world without the revised CAFE standards, and thus the information 
available to decision-makers in their decision as to what standards are 
maximum feasible and to the public in commenting on those standards.
---------------------------------------------------------------------------

    \28\ Specifically, we include the main provisions of the ACC I, 
ACC II, and ACT programs, as discussed further below in Section 
II.C.5.a.
---------------------------------------------------------------------------

    A number of other improvements and updates have been made to the 
analysis since the 2022 final rule based on NHTSA analysis, new data, 
and stakeholder meetings for this NPRM. Table I-7 summarizes these, and 
they are discussed in much more detail below and in the documents 
accompanying this preamble.

Table I-7--Key Analytical Updates From the 2022 Final Rule \29\
---------------------------------------------------------------------------

    \29\ For a detailed list of updates to the CAFE Analysis please 
see Draft TSD Chapter 1.1.
---------------------------------------------------------------------------

Key Updates

     Update analysis fleet from MY2020 to MY2022.
     Addition of HDPUV, and required updates across entire 
model.
     Update technologies considered in the analysis.
    [cir] Addition of HCRE, HCRD and updated Diesel technology models.
    [cir] Removal of EFR,\30\ DSLIAD,\31\ manual transmissions, AT6L2, 
EPS,\32\ IACC,\33\ LDB,\34\ SAX, and some P2 combinations.
---------------------------------------------------------------------------

    \30\ Engine Friction Reduction.
    \31\ Advanced Diesel Engine with Improvements and Advanced 
Cylinder Deactivation.
    \32\ Electric Power Steering.
    \33\ Improved Accessories.
    \34\ Low-drag Brakes.
---------------------------------------------------------------------------

     User control of additional input parameters.
     Updated modeling approach to manufacturers' expected 
compliance with states' ZEV programs.
     Expanded accounting for Federal Incentives, such as the 
Inflation Reduction Act.
     Expanded procedures for estimating new vehicle sales and 
fleet shares.
     VMT coefficient updates.
     Additional output values and options.
    NHTSA notes that while the current estimates of costs and benefits 
are important considerations and are directed by E.O. 12866, cost-
benefit analysis provides only one informative data point in addition 
to the host of considerations that NHTSA must balance by statute when 
determining maximum feasible standards. Specifically, for passenger 
cars and light trucks, NHTSA is required to consider four statutory 
factors--technological feasibility, economic practicability, the effect 
of other motor vehicle standards of the Government on fuel economy, and 
the need of the United States to conserve energy. For HDPUVs, NHTSA is 
required to consider three statutory factors--whether standards are 
appropriate, cost-effective, and technologically reasonable--to 
determine whether the standards it adopts are maximum feasible.\35\ As 
will be discussed further below, NHTSA tentatively concludes that 
Alternatives PC2LT4 and HDPUV10 are maximum feasible on the basis of 
these respective factors, and the cost-benefit analysis, while 
informative, is not one of the statutorily-required factors. NHTSA also 
considered several dozen sensitivity cases varying different inputs and 
concluded that even when varying inputs resulted in changes to net 
benefits or (on rare occasions) changed the relative order of 
regulatory alternatives in terms of their net benefits, those changes 
were not significant enough to outweigh our tentative conclusion that 
Alternatives PC2LT4 and HDPUV10 are maximum feasible.
---------------------------------------------------------------------------

    \35\ 49 U.S.C. 32902(k).
---------------------------------------------------------------------------

    NHTSA further notes that CAFE and HDPUV standards apply only to new 
vehicles, meaning that the costs attributable to new standards are 
``front-loaded'' because they result primarily from the application of 
fuel-saving technology to new vehicles. By contrast, the impact of new 
CAFE and HDPUV standards on fuel consumption and energy savings, air 
pollution, and GHGs--and the associated benefits to society--occur over 
an extended time, as drivers buy, use, and eventually scrap these new 
vehicles. By accounting for many MYs and extending well into the future 
to 2050, our analysis accounts for these differing patterns in impacts, 
benefits, and costs. Given the front-loaded costs versus longer-term 
benefits, it is likely that an analysis extending even further into the 
future would find additional net present benefits.
    The bulk of our analysis for passenger cars and light trucks 
presents a ``model year'' (MY) perspective rather than a ``calendar 
year'' (CY) perspective. The MY perspective considers the lifetime 
impacts attributable to all passenger cars and light trucks produced 
prior to MY 2033, accounting for the operation of these vehicles over 
their entire lives (with some MY 2032 vehicles estimated to be in 
service as late as 2050). This approach emphasizes the role of the MYs 
for which new standards are being proposed, while accounting for the 
potential light truck that the proposed standards could induce some 
changes in

[[Page 56141]]

the operation of vehicles produced prior to MY 2027 (for passenger cars 
and light trucks), and that, for example, some individuals might choose 
to keep older vehicles in operation, rather than purchase new ones.
    The CY perspective we present includes the annual impacts 
attributable to all vehicles estimated to be in service in each CY for 
which our analysis includes a representation of the entire registered 
passenger car, light truck, and HDPUV fleet. For this proposal, this CY 
perspective covers each of CYs 2022-2050, with differential impacts 
accruing as early as MY 2022.\36\ Compared to the MY perspective, the 
CY perspective emphasizes MYs of vehicles produced in the longer term, 
beyond those MYs for which standards are currently being proposed.
---------------------------------------------------------------------------

    \36\ For a presentation of effects by CY, please see Chapter 
8.2.4.6 of the PRIA.
---------------------------------------------------------------------------

    The tables below summarize estimates of selected impacts viewed 
from each of these two perspectives, for each of the regulatory 
alternatives considered in this proposal.
---------------------------------------------------------------------------

    \37\ PRIA Chapter 1, Figure 1-1 provides a graphical comparison 
of energy sources and their relative change over the standard 
setting years.
    \38\ The additional electricity use is attributed to an increase 
in the number of PHEVs; PHEV fuel economy is only considered in 
charge-sustaining (i.e., gasoline-only) mode in the compliance 
analysis, but electricity consumption is computed for the effects 
analysis.
    \39\ Total Gigawatt hours.
    \40\ Climate benefits are based on reductions in CO2, 
CH4, and N2O emissions and are calculated 
using four different estimates of the social cost of each greenhouse 
gas (SC-GHG model average at 2.5 percent, 3 percent, and 5 percent 
DRs; 95th percentile at 3 percent DR), which each increase over 
time. For the presentational purposes of this table and other 
similar summary tables, we show the benefits associated with the 
average global SC-GHG at a 3 percent DR, but the agency does not 
have a single central SC-GHG point estimate. We emphasize the 
importance and value of considering the benefits calculated using 
all four SC-GHG estimates. See Section II.G.2 of this preamble for 
more information. Where percent DR values are reported in this 
table, the social benefits of avoided climate damages are discounted 
at 3 percent. The climate benefits are discounted at the same DR as 
used in the underlying SC-GHG values for internal consistency.
    \41\ For this and similar tables in this section, net benefits 
may differ from benefits minus costs due to rounding.

      Table I-8--Selected Cumulative Effects--Passenger Cars and Light Trucks--MY and CY Perspectives \37\
----------------------------------------------------------------------------------------------------------------
                                                                             PC2LT4
                                                                PC1LT3     (preferred      PC3LT5       PC6LT8
                                                                          alternative)
----------------------------------------------------------------------------------------------------------------
                                 Avoided Gasoline Consumption (billion gallons)
----------------------------------------------------------------------------------------------------------------
MYs 1983-2032..............................................          -23           -30          -34          -47
CYs 2022-2050..............................................          -65           -88         -115         -207
----------------------------------------------------------------------------------------------------------------
                                   Additional Electricity Consumption (TWh) 38
----------------------------------------------------------------------------------------------------------------
MYs 1983-2032..............................................           79            99           91          139
CYs 2022-2050..............................................          218           312          408          975
----------------------------------------------------------------------------------------------------------------
                                           Reduced CO Emissions (mmt)
----------------------------------------------------------------------------------------------------------------
MYs 1983-2032..............................................         -236          -301         -346         -482
CYs 2022-2050..............................................         -654          -885       -1,155       -2,011
----------------------------------------------------------------------------------------------------------------


     Table I--9: Selected Cumulative Effects--HDPUVs--CY Perspective
------------------------------------------------------------------------
                                                  HDPUV10
                                     HDPUV4     (preferred     HDPUV14
                                               alternative)
------------------------------------------------------------------------
             Avoided Gasoline Consumption (billion gallons)
------------------------------------------------------------------------
CYs 2022-2050...................         -0.1          -2.6        -11.8
------------------------------------------------------------------------
               Additional Electricity Consumption (TWh) 39
------------------------------------------------------------------------
CYs 2022-2050...................          1.1          24.2        101.0
------------------------------------------------------------------------
                       Reduced CO Emissions (mmt)
------------------------------------------------------------------------
CYs 2022-2050...................         -0.9         -22.3       -101.3
------------------------------------------------------------------------


 Table I-10--Estimated Monetized Costs and Benefits--Passenger Cars and Light Trucks--MY and CY Perspectives by Alternative and Social DR, 3% SC-GHG DR
                                                                        \40\ \41\
--------------------------------------------------------------------------------------------------------------------------------------------------------
 
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                           PC1LT3
                                      PC2LT4 (preferred
                                         alternative)
                                           PC3LT5
                                           PC6LT8
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                              Monetized Benefits ($billion)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                               3% DR.........  7% DR.........  3% DR.........  7% DR........  3% DR........  7% DR........  3% DR........  7% DR
MYs 1983-2032................  59............  37............  75............  47...........  88...........  55...........  120..........  75
CYs 2022-2050................  150...........  88............  203...........  119..........  261..........  152..........  437..........  252
--------------------------------------------------------------------------------------------------------------------------------------------------------

[[Page 56142]]

 
                                                               Monetized Costs ($billion)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                               3% DR.........  7% DR.........  3% DR.........  7% DR........  3% DR........  7% DR........  3% DR........  7% DR
MYs 1983-2032................  47............  31............  59............  39...........  79...........  52...........  105..........  70
CYs 2022-2050................  116...........  65............  157...........  87...........  240..........  130..........  386..........  206
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                            Monetized Net Benefits ($billion)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                               3% DR.........  7% DR.........  3% DR.........  7% DR........  3% DR........  7% DR........  3% DR........  7% DR
MYs 1983-2032................  13............  6.............  17............  8............  9............  3............  16...........  5
CYs 2022-2050................  34............  23............  46............  32...........  21...........  21...........  51...........  46
--------------------------------------------------------------------------------------------------------------------------------------------------------


               Table I-11--Estimated Monetized Costs and Benefits--HDPUVs--CY Perspective by Alternative and Social DR, 3% SC-GHG DR \42\
--------------------------------------------------------------------------------------------------------------------------------------------------------
 
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                  HDPUV4
                                      HDPUV10 (preferred alternative)
                                                  HDPUV14
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                              Monetized Benefits ($billion)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                  3% DR               7% DR               3% DR               7% DR               3% DR               7% DR
CYs 2022-2050...................  0.11..............  0.07..............  4.32..............  2.43..............  17.43.............  10.12
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               Monetized Costs ($billion)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                  3% DR               7% DR               3% DR               7% DR               3% DR               7% DR
CYs 2022-2050...................  0.09..............  0.04..............  2.07..............  0.99..............  9.43..............  4.67
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                            Monetized Net Benefits ($billion)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                  3% DR               7% DR               3% DR               7% DR               3% DR               7% DR
CYs 2022-2050...................  0.03..............  0.03..............  2.25..............  1.44..............  8.00..............  5.45
--------------------------------------------------------------------------------------------------------------------------------------------------------

    Our net benefit estimates are likely to be conservative both 
because (as discussed above) our analysis only extends to MY 2032 and 
CY 2050 (LD) and CY 2050 (HDPUV), and because there are additional 
important health, environmental, and energy security benefits that 
could not be fully quantified or monetized. Finally, for purposes of 
comparing the benefits and costs of proposed CAFE and HDPUV standards 
to the benefits and costs of other Federal regulations, policies, and 
programs under the Regulatory Right-to-Know Act,\43\ we have computed 
``annualized'' benefits and costs, as follows:
---------------------------------------------------------------------------

    \42\ Climate benefits are based on reductions in CO2, 
CH4, and N2O emissions and are calculated 
using four different estimates of the social cost of each greenhouse 
gas (SC-GHG model average at 2.5 percent, 3 percent, and 5 percent 
DRs; 95th percentile at 3 percent DR), which each increase over 
time. For the presentational purposes of this table and other 
similar summary tables, we show the benefits associated with the 
average global SC-GHG at a 3 percent discount rate, but the agency 
does not have a single central SC-GHG point estimate. We emphasize 
the importance and value of considering the benefits calculated 
using all four SC-GHG estimates. See Section II.G.2 of this preamble 
for more information. Where percent DR values are reported in this 
table, the social benefits of avoided climate damages are discounted 
at 3 percent. The climate benefits are discounted at the same DR as 
used in the underlying SC-GHG values for internal consistency.
    \43\ See https://www.whitehouse.gov/omb/information-regulatory-affairs/reports/ for examples of how this reporting is used by the 
Federal Government.
    \44\ Climate benefits are based on reductions in CO2, 
CH4, and N2O emissions and are calculated 
using four different estimates of the social cost of each greenhouse 
gas (SC-GHG model average at 2.5 percent, 3 percent, and 5 percent 
DRs; 95th percentile at 3 percent DR), which each increase over 
time. For the presentational purposes of this table and other 
similar summary tables, we show the benefits associated with the 
average global SC-GHG at a 3 percent discount rate, but the agency 
does not have a single central SC-GHG point estimate. We emphasize 
the importance and value of considering the benefits calculated 
using all four SC-GHG estimates. See Section II.G.2 of this preamble 
for more information. Where percent DR values are reported in this 
table, the social benefits of avoided climate damages are discounted 
at 3 percent. The climate benefits are discounted at the same DR as 
used in the underlying SC-GHG values for internal consistency.
    \45\ For this and similar tables in this section, net benefits 
may differ from benefits minus costs due to rounding.

 Table I-12--Estimated Annualized Monetized Costs and Benefits--Passenger Cars and Light Trucks--MY and CY Perspectives by Alternative and Social DR, 3%
                                                                   SC-GHG DR \44\ \45\
--------------------------------------------------------------------------------------------------------------------------------------------------------
 
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                           PC1LT3
                                      PC2LT4 (preferred
                                         alternative)
                                           PC3LT5
                                           PC6LT8
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                              Monetized Benefits ($billion)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                               3% DR           7% DR           3% DR           7% DR          3% DR          7% DR          3% DR          7% DR
MYs 1983-2032................  2.3...........  2.7...........  2.9...........  3.4..........  3.4..........  4............  4.7..........  5.4
CYs 2022-2050................  7.8...........  7.2...........  10.6..........  9.7..........  13.6.........  12.4.........  22.8.........  20.6
--------------------------------------------------------------------------------------------------------------------------------------------------------

[[Page 56143]]

 
                                                               Monetized Costs ($billion)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                               3% DR           7% DR           3% DR           7% DR          3% DR          7% DR          3% DR          7% DR
MYs 1983-2032................  1.8...........  2.3...........  2.3...........  2.8..........  3.1..........  3.8..........  4.1..........  5.1
CYs 2022-2050................  6.1...........  5.3...........  8.2...........  7.1..........  12.5.........  10.6.........  20.1.........  16.8
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                            Monetized Net Benefits ($billion)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                               3% DR.........  7% DR.........  3% DR.........  7% DR........  3% DR........  7% DR........  3% DR........  7% DR
MYs 1983-2032................  0.5...........  0.5...........  0.7...........  0.6..........  0.3..........  0.2..........  0.6..........  0.3
CYs 2022-2050................  1.8...........  1.9...........  2.4...........  2.6..........  1.1..........  1.7..........  2.7..........  3.8
--------------------------------------------------------------------------------------------------------------------------------------------------------


          Table I-13--Estimated Annualized Monetized Costs and Benefits--HDPUVs by Alternative and Social DR, CY Perspective, 3% SC-GHG DR \46\
--------------------------------------------------------------------------------------------------------------------------------------------------------
 
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                  HDPUV4
                                      HDPUV10 (preferred alternative)
                                                  HDPUV14
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                              Monetized Benefits ($billion)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                  3% DR               7% DR               3% DR               7% DR               3% DR               7% DR
CYs 2022-2050...................  0.006.............  0.006.............  0.23..............  0.20..............  0.91..............  0.82
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               Monetized Costs ($billion)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                  3% DR               7% DR               3% DR               7% DR               3% DR               7% DR
CYs 2022-2050...................  0.005.............  0.003.............  0.11..............  0.08..............  0.49..............  0.38
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                            Monetized Net Benefits ($billion)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                  3% DR               7% DR               3% DR               7% DR               3% DR               7% DR
CYs 2022-2050...................  0.001.............  0.002.............  0.12..............  0.12..............  0.42..............  0.44
--------------------------------------------------------------------------------------------------------------------------------------------------------

    It is also worth emphasizing that, although NHTSA is prohibited 
from considering the availability of certain flexibilities in making 
our determination about the levels of CAFE standards that would be 
maximum feasible, manufacturers have a variety of flexibilities 
available to aid their compliance. Section VI of this preamble 
summarizes these flexibilities. NHTSA is proposing changes to some of 
these flexibilities as shown in Table I-14 and Table I-15.
---------------------------------------------------------------------------

    \46\ Climate benefits are based on reductions in CO2, 
CH4, and N2O emissions and are calculated 
using four different estimates of the social cost of each greenhouse 
gas (SC-GHG model average at 2.5 percent, 3 percent, and 5 percent 
DRs; 95th percentile at 3 percent DR), which each increase over 
time. For the presentational purposes of this table and other 
similar summary tables, we show the benefits associated with the 
average global SC-GHG at a 3 percent discount rate, but the agency 
does not have a single central SC-GHG point estimate. We emphasize 
the importance and value of considering the benefits calculated 
using all four SC-GHG estimates. See Section II.G.2 of this preamble 
for more information. Where percent DR values are reported in this 
table, the social benefits of avoided climate damages are discounted 
at 3 percent. The climate benefits are discounted at the same DR as 
used in the underlying SC-GHG values for internal consistency.

  Table I-14--Overview of Compliance Flexibility Changes for CAFE Program (Vehicles With a Gross Vehicle Weight
  Rating (GVWR) of 8,500 lbs. or Less and Medium-Duty Passenger Vehicles (MDPVs) With a GVWR Between 8,501 and
                                                  10,000 lbs.)
----------------------------------------------------------------------------------------------------------------
                                      Determining average fleet performance
-----------------------------------------------------------------------------------------------------------------
              Component                            General description               Proposed changes in NPRM?
----------------------------------------------------------------------------------------------------------------
AC efficiency Fuel Consumption         This adjustment to the results from the 2-  Yes: Proposed changes to 49
 Improvement Value (FCIV).              cycle testing accounts for fuel             CFR 531.6 and 533.6 to
                                        consumption improvement from technologies   eliminate AC efficiency
                                        that improve AC efficiency that are not     FCIVs for BEVs starting in
                                        accounted for in the 2-cycle testing. The   MY 2027.
                                        AC efficiency FCIV program began in MY
                                        2017.

[[Page 56144]]

 
Off-cycle FCIV.......................  This adjustment to the results from the 2-  Yes: Proposing changes to 49
                                        cycle testing accounts for fuel             CFR 531.6 and 533.6 to
                                        consumption improvement from technologies   eliminate off-cycle menu
                                        that are not accounted for or not fully     FCIVs for BEVs and to
                                        accounted for in the 2-cycle testing. The   eliminate the 5-cycle and
                                        off-cycle FCIV program began in MY 2017.    alternative approvals
                                                                                    starting in MY 2027. PHEVs
                                                                                    retain benefits. Proposing a
                                                                                    60-day response deadline for
                                                                                    requests for information
                                                                                    regarding off-cycle requests
                                                                                    for MY 2025-2026.
Advanced full-size pickup trucks FCIV  This adjustment increases a manufacturer's  No proposed changes. The
                                        average fuel economy for hybridized and     program is set to sunset in
                                        other performance-based technologies for    MY 2024 and NHTSA is not
                                        MY 2017 and 2024.                           proposing to extend it.
----------------------------------------------------------------------------------------------------------------

     
---------------------------------------------------------------------------

    \47\ Docket ID NHTSA-2020-0079-0001.

          Table I-15--Overview of Compliance for Heavy-Duty Fuel Efficiency Program for Pickup and Vans
                              [Vehicles with a GVWR between 8,500 and 14,000 lbs.]
----------------------------------------------------------------------------------------------------------------
                      Determining average fleet performance and certification flexibilities
-----------------------------------------------------------------------------------------------------------------
              Component                            General description               Proposed changes in NPRM?
----------------------------------------------------------------------------------------------------------------
Advanced technology credit multiplier  In the 2016 Phase 2 Final Rule, EPA and     Yes: Proposed technical
                                        NHTSA explained that manufacturers may      amendments to accurately
                                        increase advanced technology credits by a   reflect changes contemplated
                                        3.5 multiplier for plug-in hybrid           by 2016 final rule
                                        electric vehicles, 4.5 for all-electric     establishing requirements
                                        vehicles, and 5.5 for fuel cell vehicles    for Phase 2. The multiplier
                                        through My 2027                             for advanced technology
                                                                                    credits ends after MY 2027.
Innovative and off-cycle technology    Manufacturer may generate credits for       Yes: Proposed changes to
 credits.                               vehicle or engine families or               eliminate innovative and off-
                                        subconfigurations having fuel consumption   cycle technology credits for
                                        reductions resulting from technologies      heavy-duty pickup trucks and
                                        not reflected in the Greenhouse Gas         vans.
                                        Emissions Model (GEM) simulation tool or
                                        in the FTP chassis dynamometer.
Credit Transfers.....................  Manufacturers may transfer advanced         Yes: Proposed technical
                                        technology credits across averaging sets.   amendment to reflect, as
                                                                                    intended in the 2016 Phase 2
                                                                                    rule that advanced
                                                                                    technology credits may not
                                                                                    be transferred across
                                                                                    averaging sets for Phase 2
                                                                                    and beyond.\47\
----------------------------------------------------------------------------------------------------------------

    The following sections of this preamble discuss the technical 
foundation for the agency's analysis, the regulatory alternatives 
considered in this proposal, the estimated effects of the regulatory 
alternatives, the basis for NHTSA's tentative conclusion that the 
proposed standards are maximum feasible, and NHTSA's approach to 
compliance and enforcement. The extensive record supporting NHTSA's 
tentative conclusion is documented in this preamble, in the Draft TSD, 
the PRIA, the Draft EIS, and the additional materials on NHTSA's 
website and in the rulemaking docket. NHTSA seeks comment on all 
aspects of this proposal.

[[Page 56145]]

II. Technical Foundation for NPRM Analysis

A. Why is NHTSA conducting this analysis?

    When NHTSA proposes new regulations, it generally presents an 
analysis that estimates the impacts of those regulations, and the 
impacts of other regulatory alternatives. These analyses derive from 
statutes such as the Administrative Procedure Act (APA) and NEPA, from 
E.O.s (such as E.O. 12866 and 13563), and from other administrative 
guidance (e.g., Office of Management and Budget (OMB) Circular A-4). 
For CAFE and HDPUV standards, the EPCA, as amended by the EISA, 
contains a variety of provisions that NHTSA seeks to account for 
analytically. Capturing all of these requirements analytically means 
that NHTSA presents an analysis that spans a meaningful range of 
regulatory alternatives, that quantifies a range of technological, 
economic, and environmental impacts, and that does so in a manner that 
accounts for EPCA/EISA's various express requirements for the CAFE and 
HDPUV programs (e.g., passenger cars and light trucks must be regulated 
separately; the standard for each fleet must be set at the maximum 
feasible level in each MY; etc.).
    NHTSA's proposed standards are thus supported by extensive analysis 
of potential impacts of the regulatory alternatives under 
consideration. Along with this preamble, a Draft TSD, a Preliminary 
Regulatory Impact Analysis (PRIA), and a Draft EIS, together provide a 
detailed enumeration of related methods, estimates, assumptions, and 
results. These additional analyses can be found in the rulemaking 
docket for this proposal \48\ and on NHTSA's website.\49\
---------------------------------------------------------------------------

    \48\ Docket No. NHTSA-2023-0022, which can be accessed at 
https://www.regulations.gov.
    \49\ See National Highway Traffic Safety Administration. 2023. 
Corporate Average Fuel Economy. Available at: https://www.nhtsa.gov/laws-regulations/corporate-average-fuel-economy. (Accessed: May 31, 
2023).
---------------------------------------------------------------------------

    This section provides further detail on the key features and 
components of NHTSA's analysis. It also describes how NHTSA's analysis 
has been constructed specifically to reflect governing law applicable 
to CAFE and HDPUV standards (which may vary between programs). Finally, 
the discussion reviews how NHTSA's analysis has been expanded and 
improved in response to comments received on the 2021 proposal,\50\ as 
well as additional work conducted over the last year. Further 
improvements may be made in the future based on comments received to 
this proposal, on the 2021 National Academies of Sciences (NAS) 
Report,\51\ and on other work generally previewed in these rulemaking 
documents. The analysis for this proposal aided NHTSA in implementing 
its statutory obligations, including the weighing of various 
considerations, by reasonably informing decision-makers about the 
estimated effects of choosing different regulatory alternatives.
---------------------------------------------------------------------------

    \50\ 86 FR 49602 (Sept. 3, 2021).
    \51\ National Academies of Sciences, Engineering, and Medicine. 
2021. Assessment of Technologies for Improving Light-Duty Vehicle 
Fuel Economy--2025-2035. Washington, DC. The National Academies 
Press. Available at: https://nap.nationalacademies.org/catalog/26092/assessment-of-technologies-for-improving-light-duty-vehicle-fuel-economy-2025-2035 (Accessed: May 31, 2023) and for hard-copy 
review at DOT headquarters.
---------------------------------------------------------------------------

1. What are the key components of NHTSA's analysis?
    NHTSA's analysis makes use of a range of data (i.e., observations 
of things that have occurred), estimates (i.e., things that may occur 
in the future), and models (i.e., methods for making estimates). Two 
examples of data include (1) records of actual odometer readings used 
to estimate annual mileage accumulation at different vehicle ages and 
(2) CAFE compliance data used as the foundation for the ``analysis 
fleets'' containing, among other things, production volumes and fuel 
economy/fuel efficiency levels of specific configurations of specific 
vehicle models produced for sale in the U.S. Two examples of estimates 
include (1) forecasts of future Gross Domestic Product (GDP) growth 
used, with other estimates, to forecast future vehicle sales volumes 
and (2) technology cost estimates, which include estimates of the 
technologies' ``direct cost,'' marked up by a ``retail price 
equivalent'' (RPE) factor used to estimate the ultimate cost to 
consumers of a given fuel-saving technology, and an estimate of ``cost 
learning effects'' (i.e., the tendency that it will cost a manufacturer 
less to apply a technology as the manufacturer gains more experience 
doing so).
    NHTSA uses the CAFE Compliance and Effects Modeling System (usually 
shortened to the ``CAFE Model'') to estimate manufacturers' potential 
responses to new CAFE, HDPUV, and GHG standards and to estimate various 
impacts of those responses. DOT's Volpe National Transportation Systems 
Center (often simply referred to as the ``Volpe Center'') develops, 
maintains, and applies the model for NHTSA. NHTSA has used the CAFE 
Model to perform analyses supporting every CAFE rulemaking since 2001. 
The 2016 ``Phase 2'' rulemaking \52\ establishing the most recent HDPUV 
standards also used the CAFE Model for analysis.
---------------------------------------------------------------------------

    \52\ 81 FR 73478 (October 25, 2016).
---------------------------------------------------------------------------

    The basic design of the CAFE Model is as follows: The system first 
estimates how vehicle manufacturers might respond to a given regulatory 
scenario, and from that potential compliance solution, the system 
estimates what impact that response will have on fuel consumption, 
emissions, safety impacts, and economic externalities. In a highly 
summarized form, Figure II-1 shows the basic categories of CAFE Model 
procedures and the sequential flow between different stages of the 
modeling. The diagram does not present specific model inputs or 
outputs, as well as many specific procedures and model interactions. 
The model documentation accompanying this proposal presents these 
details, and Chapter 1 of the Draft TSD contains a more detailed 
version of this flow diagram for readers who are interested.
BILLING CODE 4910-59-P

[[Page 56146]]

[GRAPHIC] [TIFF OMITTED] TP17AU23.004

BILLING CODE 4910-59-C
    More specifically, the model may be characterized as an integrated 
system of models. For example, one model estimates manufacturers' 
responses, another estimates resultant changes in total vehicle sales, 
and still another estimates resultant changes in fleet turnover (i.e., 
scrappage). Additionally, and importantly, the model does not determine 
the form or stringency of the standards. Instead, the model applies 
inputs specifying the form and stringency of standards to be analyzed 
and produces outputs showing the impacts of manufacturers working to 
meet those standards, which become part of the basis for comparing 
different potential stringencies. A regulatory scenario, meanwhile, 
involves specification of the form, or shape, of the standards (e.g., 
flat standards, or linear or logistic attribute-based standards), scope 
of passenger car, light truck, and HDPUV regulatory classes, and 
stringency of the CAFE or HDPUV standards for each MY to be analyzed. 
For example, a regulatory scenario may define CAFE or HDPUV standards 
for a particular class of vehicles that increase in stringency by a 
given percent per year for a given number of consecutive years.
    Manufacturer compliance simulation and the ensuing effects 
estimation, collectively referred to as compliance modeling, encompass 
numerous subsidiary elements. Compliance simulation begins with a 
detailed user-provided initial forecast of the vehicle models offered 
for sale during the simulation period.\53\ The compliance simulation 
then attempts to bring each manufacturer into compliance with the 
standards defined by the regulatory scenario contained within an input 
file developed by the user.\54\
---------------------------------------------------------------------------

    \53\ Because the CAFE Model is publicly available, anyone can 
develop their own initial forecast (or other inputs) for the model 
to use. The DOT-developed Market Data Input file that contains the 
forecast for this proposal is available on NHTSA's website at 
https://www.nhtsa.gov/corporate-average-fuel-economy/cafe-compliance-and-effects-modeling-system.
    \54\ With appropriate inputs, the model can also be used to 
estimate impacts of manufacturers' potential responses to new 
CO2 standards and to California's ZEV program.
---------------------------------------------------------------------------

    Estimating impacts involves calculating resultant changes in new 
vehicle costs, estimating a variety of costs (e.g., for fuel) and 
effects (e.g., CO2 emissions from fuel combustion) occurring 
as vehicles are driven over their lifetimes before eventually being 
scrapped, and estimating the monetary value of these effects. 
Estimating impacts also involves consideration of consumer responses--
e.g., the impact of vehicle fuel economy/efficiency, operating costs, 
and vehicle price on consumer demand for passenger cars, light trucks, 
and HDPUVs. Both basic analytical elements involve the

[[Page 56147]]

application of many analytical inputs. Many of these inputs are 
developed outside of the model and not by the model. For example, the 
model applies fuel prices; it does not estimate fuel prices.
    NHTSA also uses EPA's Motor Vehicle Emission Simulator (MOVES) 
model to estimate ``vehicle'' or ``downstream'' emission factors (EF) 
for criteria pollutants,\55\ and uses four Department of Energy (DOE) 
and DOE-sponsored models to develop inputs to the CAFE Model, including 
three developed and maintained by DOE's Argonne National Laboratory 
(ANL). The agency uses the DOE Energy Information Administration's 
(EIA's) National Energy Modeling System (NEMS) to estimate fuel 
prices,\56\ and uses ANL's Greenhouse gases, Regulated Emissions, and 
Energy use in Transportation (GREET) model to estimate emissions rates 
from fuel production and distribution processes.\57\ DOT also sponsored 
DOE/ANL to use ANL's Autonomie full-vehicle modeling and simulation 
system to estimate the fuel economy/efficiency impacts for over a 
million combinations of technologies and vehicle types.\58\ The Draft 
TSD and PRIA describe details of our use of these models. In addition, 
as discussed in the Draft EIS accompanying this proposal, DOT relied on 
a range of climate models to estimate impacts on climate, air quality, 
and public health. The Draft EIS discusses and describes the use of 
these models.
---------------------------------------------------------------------------

    \55\ See https://www.epa.gov/moves. This proposal uses version 
MOVES3 (the latest version at the time of analysis), available at 
https://www.epa.gov/moves/latest-version-motor-vehicle-emission-simulator-moves.
    \56\ See https://www.eia.gov/outlooks/aeo/. This proposal uses 
fuel prices estimated using the Annual Energy Outlook (AEO) 2022 
version of NEMS (see https://www.eia.gov/outlooks/aeo/tables_ref.php.).
    \57\ Information regarding GREET is available at https://greet.es.anl.gov/. This proposal uses the 2022 version of GREET.
    \58\ As part of the ANL simulation effort, individual technology 
combinations simulated in Autonomie were paired with ANL's BatPaC 
model to estimate the battery cost associated with each technology 
combination based on characteristics of the simulated vehicle and 
its level of electrification. Information regarding ANL's BatPaC 
model is available at https://www.anl.gov/cse/batpac-model-software. 
In addition, the impact of engine technologies on fuel consumption, 
torque, and other metrics was characterized using GT-POWER 
simulation modeling in combination with other engine modeling that 
was conducted by IAV Automotive Engineering, Inc. (IAV). The engine 
characterization ``maps'' resulting from this analysis were used as 
inputs for the Autonomie full-vehicle simulation modeling. 
Information regarding GT-POWER is available at https://www.gtisoft.com/gt-power/.
---------------------------------------------------------------------------

    To prepare for analysis supporting this proposal, DOT has refined 
and expanded the CAFE Model through ongoing development. Examples of 
such changes, some informed by past external comment, made since 2022 
include: \59\
---------------------------------------------------------------------------

    \59\ A more detailed list can be found in Chapter 1.1 of the 
Draft TSD.

 Addition of HDPUV, and associated required updates across 
entire model
 Updated technologies considered in the analysis
    [cir] Addition of HCRE, HCRD and updated diesel technology models 
\60\
---------------------------------------------------------------------------

    \60\ See technologies descriptions in Draft TSD Chapter 3.
---------------------------------------------------------------------------

    [cir] Removal of EFR, DSLIAD, manual transmissions, AT6L2, EPS, 
IACC, LDB, SAX, and some P2 combinations \61\
---------------------------------------------------------------------------

    \61\ See technologies description in 87 FR 25710 (May 2, 2022).
---------------------------------------------------------------------------

 User control of additional input parameters
 Updated modeling approach to manufacturers' expected 
compliance with states' ZEV programs
 Expanded accounting for Federal incentives, such as the IRA
 Expanded procedures for estimating new vehicle sales and fleet 
shares
 VMT coefficient updates

    These changes reflect DOT's long-standing commitment to ongoing 
refinement of its approach to estimating the potential impacts of new 
CAFE and HDPUV standards. The Draft TSD elaborates on these changes to 
the CAFE Model, as well as changes to inputs to the model for this 
analysis.
    NHTSA underscores that this analysis uses the CAFE Model in a 
manner that explicitly accounts for the fact that in producing a single 
fleet of vehicles for sale in the United States, manufacturers make 
decisions that consider the combination of CAFE/HDPUV standards, EPA 
GHG standards, and various policies set at sub-national levels (e.g., 
ZEV sales mandates, set by California and adopted by many other 
states). These regulations have important structural and other 
differences that affect the strategy a manufacturer could pursue in 
designing a fleet that complies with each of the above. As explained, 
NHTSA's analysis reflects a number of statutory and regulatory 
requirements applicable to CAFE/HDPUV and EPA GHG standard-setting. As 
stated previously, NHTSA will coordinate with EPA to optimize the 
effectiveness of NHTSA's standards while minimizing compliance costs, 
informed by public comments from all stakeholders and consistent with 
the statutory factors. NHTSA seeks input to help inform these 
objectives.
2. How do requirements under EPCA/EISA shape NHTSA's analysis?
    EPCA contains multiple requirements governing the scope and nature 
of CAFE standard setting. Some of these have been in place since EPCA 
was first signed into law in 1975, and some were added in 2007, when 
Congress passed EISA and amended EPCA. EISA also gave NHTSA authority 
to set standards for HDPUVs, and that authority was generally less 
constrained than for CAFE standards. NHTSA's modeling and analysis to 
inform standard setting is guided and shaped by these statutory 
requirements. EPCA/EISA requirements regarding the technical 
characteristics of CAFE and HDPUV standards and the analysis thereof 
include, but are not limited to, the following:
    Corporate Average Standards: Section 32902 of 49 U.S.C. requires 
standards for passenger cars, light trucks, and HDPUVs to be corporate 
average standards, applying to the average fuel economy/efficiency 
levels achieved by each corporation's fleets of vehicles produced for 
sale in the U.S.\62\ The CAFE Model calculates the CAFE and 
CO2 levels of each manufacturer's fleets based on estimated 
production volumes and characteristics, including fuel economy/
efficiency levels, of distinct vehicle models that could be produced 
for sale in the U.S.
---------------------------------------------------------------------------

    \62\ This differs from certain other types of vehicle standards, 
such as safety standards. For example, every vehicle produced for 
sale in the U.S. must, on its own, meet all applicable Federal motor 
vehicle safety standards (FMVSS), but no vehicle produced for sale 
must, on its own, meet Federal fuel economy or efficiency standards. 
Rather, each manufacturer is required to produce a mix of vehicles 
that, taken together, achieve an average fuel economy/efficiency 
level no less than the applicable minimum level.
---------------------------------------------------------------------------

    Separate Standards for Passenger Cars, Light Trucks, and HDPUVs: 
Section 32902 of 49 U.S.C. requires the Secretary of Transportation to 
set CAFE standards separately for passenger cars and light trucks and 
allows the Secretary to prescribe separate standards for different 
classes of heavy-duty (HD) vehicles like HDPUVs. The CAFE Model 
accounts separately for differentiated standards and compliance 
pathways for passenger cars, light trucks, and HDPUVs when it analyzes 
CAFE/HDPUV or GHG standards.
    Attribute-Based Standards: Section 32902 of 49 U.S.C. requires the 
Secretary of Transportation to define CAFE standards as mathematical 
functions expressed in terms of one or more vehicle attributes related 
to fuel economy, and NHTSA has extended this approach to HDPUV 
standards as well through regulation. This means that for

[[Page 56148]]

a given manufacturer's fleet of vehicles produced for sale in the U.S. 
in a given regulatory class and MY, the applicable minimum CAFE 
requirement (or maximum HDPUV fuel consumption requirement) is computed 
based on the applicable mathematical function, and the mix and 
attributes of vehicles in the manufacturer's fleet. The CAFE Model 
accounts for such functions and vehicle attributes explicitly.
    Separately Defined Standards for Each Model Year: Section 32902 of 
49 U.S.C. requires the Secretary of Transportation (by delegation, 
NHTSA) to set CAFE standards (separately for passenger cars and light 
trucks) \63\ at the maximum feasible levels in each MY. Fuel efficiency 
levels for HDPUVs must also be set at the maximum feasible level, in 
tranches of (at least) 3 MYs at a time. The CAFE Model represents each 
MY explicitly, and accounts for the production relationships between 
MYs.\64\
---------------------------------------------------------------------------

    \63\ Chaper 329 of title 49 of the U.S. Code uses the term 
``non-passenger automobiles,'' while NHTSA uses the term ``light 
trucks'' in its CAFE regulations. The terms' meanings are identical.
    \64\ For example, a new engine first applied to a given mode/
configuration in MY 2027 will most likely persist in MY 2028 of that 
same vehicle model/configuration, in order to reflect the fact that 
manufacturers do not apply brand-new engines to a given vehicle 
model every single year. The CAFE Model is designed to account for 
these real-world factors.
---------------------------------------------------------------------------

    Separate Compliance for Domestic and Imported Passenger Car Fleets: 
Section 32904 of 49 U.S.C. requires the EPA Administrator to determine 
CAFE compliance separately for each manufacturer's fleets of domestic 
passenger cars and imported passenger cars, which manufacturers must 
consider as they decide how to improve the fuel economy of their 
passenger car fleets.\65\ The CAFE Model accounts explicitly for this 
requirement when simulating manufacturers' potential responses to CAFE 
standards, and combines any given manufacturer's domestic and imported 
cars into a single fleet when simulating that manufacturer's potential 
response to GHG standards (because EPA does not have separate standards 
for domestic and imported passenger cars).
---------------------------------------------------------------------------

    \65\ There is no such requirement for light trucks or HDPUVs.
---------------------------------------------------------------------------

    Minimum CAFE Standards for Domestic Passenger Car Fleets: Section 
32902 of 49 U.S.C. requires that domestic passenger car fleets meet a 
minimum standard, which is calculated as 92 percent of the industry-
wide average level required under the applicable attribute-based CAFE 
standard, as projected by the Secretary at the time the standard is 
promulgated. The CAFE Model accounts explicitly for this requirement 
when simulating manufacturer compliance with CAFE standards and sets 
this requirement aside when simulating manufacturer compliance with GHG 
standards.
    Civil Penalties for Noncompliance: Section 32912 of 49 U.S.C. (and 
implementing regulations) prescribes a rate (in dollars per tenth of a 
mpg) at which the Secretary is to levy civil penalties if a 
manufacturer fails to comply with a passenger car or light truck CAFE 
standard for a given fleet in a given MY, after considering available 
credits. Some manufacturers have historically demonstrated a 
willingness to pay civil penalties rather than achieving full numerical 
compliance across all fleets. The CAFE Model calculates civil penalties 
(adjusted for inflation) for CAFE shortfalls and provides means to 
estimate that a manufacturer might stop adding fuel-saving technologies 
once continuing to do so would effectively be more ``expensive'' (after 
accounting for fuel prices and buyers' willingness to pay for fuel 
economy) than paying civil penalties. The CAFE Model does not allow 
civil penalty payment as an option for EPA's GHG standards or NHTSA's 
HDPUV standards.\66\
---------------------------------------------------------------------------

    \66\ While civil penalties are an option in the HDPUV fleet, the 
penalties for noncompliance are significantly higher, and thus 
manufactures will try to avoid paying them. Setting the model to 
disallow civil penalties acts to best simulate this behavior. If the 
model does find no option other than ``paying a civil penalty'' in 
the HDPUV fleet, this cost should be considered a proxy for credit 
purchase. NHTSA seeks comment on whether and how to model civil 
penalties for HDPUVs for the final rule.
---------------------------------------------------------------------------

    Dual-Fueled and Dedicated Alternative Fuel Vehicles: For purposes 
of calculating passenger car and light truck CAFE levels used to 
determine compliance, 49 U.S.C. 32905 and 32906 specify methods for 
calculating the fuel economy levels of vehicles operating on 
alternative fuels to gasoline or diesel, such as electricity. In some 
cases, after MY 2020, methods for calculating AFV fuel economy are 
governed by regulation. The CAFE Model is able to account for these 
requirements explicitly for each vehicle model. However, 49 U.S.C. 
32902 prohibits consideration of the fuel economy of dedicated AFVs, 
and requires that dual-fueled AFVs' fuel economy, such as plug-in 
electric vehicle (EVs), be calculated as though they ran only on 
gasoline or diesel, when NHTSA determines the maximum feasible fuel 
economy level that manufacturers can achieve in a given year for which 
NHTSA is establishing CAFE standards. The CAFE Model therefore has an 
option to be run in a manner that excludes the additional application 
of dedicated AFVs and counts only the gasoline fuel economy of dual-
fueled AFVs, in MYs for which maximum feasible standards are under 
consideration. As allowed under NEPA for analysis appearing in 
Environmental Impact Statements (EIS) that help inform decision makers 
about the environmental impacts of CAFE standards, the CAFE Model can 
also be run without this analytical constraint. The CAFE Model does 
account for dedicated and dual-fueled AFVs when simulating 
manufacturers' potential responses to EPA's GHG standards because the 
Clean Air Act (CAA), under which the EPA derives its authority to set 
GHG standards for motor vehicles, contains no restrictions in using 
AFVs for compliance. There are no specific statutory directions in EISA 
with regard to dedicated and dual-fueled AFV fuel efficiency for 
HDPUVs, so the CAFE Model reflects relevant regulatory provisions by 
calculating fuel consumption directly per 49 U.S.C. 32905 and 32906 
specified methods.
    ZEV Mandates: The CAFE Model can simulate manufacturers' compliance 
with state-level ZEV mandates applicable in California and ``Section 
177'' \67\ states. This approach involves identifying specific vehicle 
model/configurations that could be replaced with BEVs and converting to 
BEVs only enough vehicle models to meet the manufacturer's compliance 
obligations under state-level ZEV mandates, before beginning to 
consider the potential that other technologies could be applied toward 
compliance with CAFE, HDPUV, or GHG standards.
---------------------------------------------------------------------------

    \67\ The term ``Section 177'' states refers to states which have 
elected to adopt California's standards in lieu of Federal 
requirements, as allowed under section 177 of the CAA.
---------------------------------------------------------------------------

    Creation and Use of Compliance Credits: Section 32903 of 49 U.S.C. 
provides that manufacturers may earn CAFE ``credits'' by achieving a 
CAFE level beyond that required of a given passenger car or light truck 
fleet in a given MY and specifies how these credits may be used to 
offset the amount by which a different fleet falls short of its 
corresponding requirement. These provisions allow credits to be 
``carried forward'' and ``carried back'' between MYs, transferred 
between regulated classes (domestic passenger cars, imported passenger 
cars, and light trucks), and traded between manufacturers. However, 
credit use for passenger car and light truck compliance is also subject 
to specific statutory limits. For example, CAFE compliance credits can 
be carried

[[Page 56149]]

forward a maximum of five MYs and carried back a maximum of three MYs. 
Also, EPCA/EISA caps the amount of credits that can be transferred 
between passenger car and light truck fleets and prohibits 
manufacturers from applying traded or transferred credits to offset a 
failure to achieve the applicable minimum standard for domestic 
passenger cars. The CAFE Model can simulate manufacturers' potential 
use of CAFE credits carried forward from prior MYs or transferred from 
other fleets.\68\ Section 32902 of 49 U.S.C. prohibits consideration of 
manufacturers' potential application of CAFE compliance credits when 
determining the maximum feasible fuel economy level that manufacturers 
can achieve for their fleets of passenger cars and light trucks. The 
CAFE Model can be operated in a manner that excludes the application of 
CAFE credits for a given MY under consideration for standard setting, 
and NHTSA operated the model with that constraint for the purpose of 
determining the appropriate CAFE standard for passenger cars and light 
trucks. No such statutory restrictions exist for setting HDPUV 
standards. For modeling EPA's GHG standards, the CAFE Model does not 
limit transfers because the CAA does not limit them. Insofar as the 
CAFE Model can be exercised in a manner that simulates trading of GHG 
compliance credits, such simulations treat trading as unlimited.\69\
---------------------------------------------------------------------------

    \68\ The CAFE Model does not explicitly simulate the potential 
that manufacturers would carry CAFE or GHG credits back (i.e., 
borrow) from future model years, or acquire and use CAFE compliance 
credits from other manufacturers. At the same time, because EPA has 
elected not to limit credit trading, the CAFE Model can be exercised 
(for purposes of evaluating GHG standards) in a manner that 
simulates unlimited (a.k.a. ``perfect'') GHG compliance credit 
trading throughout the industry (or, potentially, within discrete 
trading ``blocs''). For purposes of analyzing CAFE standards, NHTSA 
believes it is challenging to predict precisely how manufacturers 
may choose to use these particular flexibilities in the future: for 
example, while it is reasonably foreseeable that a manufacturer who 
over-complies in one year may ``coast'' through several subsequent 
years relying on that over-compliance rather than making further 
technology improvements, it is harder to know whether manufacturers 
will rely on future technology investments to offset prior-year 
shortfalls, or whether/how manufacturers will trade credits with 
market competitors rather than making their own technology 
investments. Historically, carry-back and trading have been much 
less utilized than carry-forward, for a variety of reasons including 
higher risk and preference not to `pay competitors to make fuel 
economy improvements we should be making' (to paraphrase one 
manufacturer), although NHTSA recognizes that carry-back and trading 
are used more frequently when standards increase in stringency more 
rapidly. Given these dynamics, and given also the fact that the 
agency has yet to resolve some of the analytical challenges 
associated with simulating use of these flexibilities, the agency 
has decided to support this proposal with a conservative analysis 
that sets aside the potential that manufactures would depend widely 
on borrowing and trading--not to mention that, for purposes of 
determining maximum feasible CAFE standards, statute prohibits NHTSA 
from considering the trading, transferring, or availability of 
credits (see 49 U.S.C. 32902(h)). While compliance costs in real 
life may be somewhat different from what is modeled in the 
rulemaking record as a result of this decision, that is broadly true 
no matter what, and the agency does not believe that the difference 
would be so great that it would change the policy outcome. 
Furthermore, a manufacturer employing a trading strategy would 
presumably do so because it represents a lower-cost compliance 
option. Thus, the estimates derived from this modeling approach are 
likely to be conservative in this respect, with real-world 
compliance costs likely being lower.
    \69\ To avoid making judgments about possible future trading 
activity, the model simulates trading by combining all manufacturers 
into a single entity, so that the most cost-effective choices are 
made for the fleet as a whole.
---------------------------------------------------------------------------

    Statutory Basis for Stringency: Section 32902 of 49 U.S.C. requires 
the Secretary of Transportation (by delegation, NHTSA) to set CAFE 
standards for passenger cars and light trucks at the maximum feasible 
levels that manufacturers can achieve in a given MY, considering 
technological feasibility, economic practicability, the need of the 
United States to conserve energy, and the impact of other motor vehicle 
standards of the Government on fuel economy. For HDPUV standards, which 
must also achieve the maximum feasible improvement, the similar yet 
distinct factors of appropriateness, cost-effectiveness, and 
technological feasibility must be considered. EPCA/EISA authorizes the 
Secretary of Transportation (by delegation, NHTSA) to interpret these 
factors, and as the Department's interpretation has evolved, NHTSA has 
continued to expand and refine its qualitative and quantitative 
analysis to account for these statutory factors. For example, one of 
the ways that economic practicability considerations are incorporated 
into the analysis is through the technology effectiveness 
determinations: the Autonomie simulations reflect the agency's judgment 
that it would not be economically practicable (nor, for HDPUVs, 
appropriate) for a manufacturer to ``split'' an engine shared among 
many vehicle model/configurations into myriad versions each optimized 
to a single vehicle model/configuration.
    National Environmental Policy Act: NEPA requires NHTSA to consider 
the environmental impacts of its actions in its decision-making 
processes, including for CAFE standards. The Draft EIS accompanying 
this proposal documents changes in emission inventories as estimated 
using the CAFE Model, but also documents corresponding estimates--based 
on the application of other models documented in the Draft EIS--of 
impacts on the global climate, on air quality, and on human health.
    Other Aspects of Compliance: Beyond these statutory requirements 
applicable to DOT, EPA, or both are a number of specific technical 
characteristics of CAFE, HDPUV, and/or GHG regulations that are also 
relevant to the construction of this analysis, like the ``off-cycle'' 
technologies fuel economy/emissions improvements that apply for both 
CAFE and GHG compliance. Although too little information is available 
to account for these provisions explicitly in the same way that NHTSA 
has accounted for other technologies, the CAFE Model includes and makes 
use of inputs reflecting NHTSA's expectations regarding the extent to 
which manufacturers may earn such credits, along with estimates of 
corresponding costs. Similarly, the CAFE Model includes and makes use 
of inputs regarding credits EPA has elected to allow manufacturers to 
earn toward GHG levels (not CAFE or HDPUV) based on the use of air 
conditioner refrigerants with lower global warming potential, or on the 
application of technologies to reduce refrigerant leakage. In addition, 
the CAFE Model accounts for EPA ``multipliers'' for certain AFVs, based 
on current regulatory provisions or on alternative approaches. Although 
these are examples of regulatory provisions that arise from the 
exercise of discretion rather than specific statutory mandate, they can 
materially impact outcomes.
3. What updated assumptions does the current model reflect as compared 
to the 2022 final rule?
    Besides the updates to the CAFE Model described above, any analysis 
of regulatory actions that will be implemented several years in the 
future, and whose benefits and costs accrue over decades, requires a 
large number of assumptions. Over such time horizons, many, if not 
most, of the relevant assumptions in such an analysis are inevitably 
uncertain. Each successive CAFE analysis seeks to update assumptions to 
better reflect the current state of the world and the best current 
estimates of future conditions.
    A number of assumptions have been updated since the 2022 final 
rule. As discussed below, NHTSA has updated its ``analysis fleet'' from 
a MY 2020 reference to a MY 2022 reference for passenger cars and light 
trucks and has built an updated HDPUV analysis fleet (the last HDPUV 
analysis fleet was built in 2016). NHTSA has also updated estimates of 
manufacturers' compliance credit ``holdings,'' updated fuel price 
projections to reflect the U.S. EIA's 2022 Annual Energy Outlook (AEO), 
updated

[[Page 56150]]

projections of GDP and related macroeconomic measures, and updated 
projections of future highway travel. While NHTSA would have made these 
updates as a matter of course, we note that the ongoing global economic 
recovery and the ongoing war in Ukraine have impacted major analytical 
inputs such as fuel prices, GDP, vehicle production and sales, and 
highway travel. Many inputs remain uncertain, and NHTSA has conducted 
sensitivity analyses around many inputs to attempt to capture some of 
that uncertainty. These and other updated analytical inputs are 
discussed in detail in the Draft TSD and PRIA.
    Additionally, E.O. 13990 required the formation of an Interagency 
Working Group (IWG) on the Social Cost (SC) of GHGs and charged this 
body with updating estimates of the SCs of carbon, nitrous oxide, and 
methane (CH4). As discussed in the TSD, NHTSA has followed 
DOT's determination that the values developed in the IWG's interim 
guidance are the most consistent with the best available science and 
economics and are the most appropriate estimates to use in the analysis 
of this proposal. Those estimates of costs per ton of emissions (or 
benefits per ton of emissions reductions) are considerably greater than 
those applied in the analysis supporting the 2020 final rule. Even 
still, the estimates NHTSA is now using are not able to fully quantify 
and monetize a number of important categories of climate damages; 
because of those omitted damages and other methodological limits, DOT 
believes its values for SC-GHG are conservative underestimates.

B. What is NHTSA analyzing?

    NHTSA is analyzing the effects of different potential CAFE and 
HDPUV standards on industry, consumers, society, and the world at 
large. These different potential standards are identified as regulatory 
alternatives, and amongst the regulatory alternatives, NHTSA identifies 
which ones the agency is proposing. As in the past several CAFE 
rulemakings and in the Phase 2 HDPUV rulemaking, NHTSA is proposing to 
establish attribute-based CAFE and HDPUV standards defined by a 
mathematical function of vehicle footprint (which has an observable 
correlation with fuel economy) and a towing-and-hauling-based WF 
respectively.\70\ EPCA, as amended by EISA, expressly requires that 
CAFE standards for passenger cars and light trucks be based on one or 
more vehicle attributes related to fuel economy, and be expressed in 
the form of a mathematical function.\71\ The statute gives NHTSA 
discretion as to how to structure standards for HDPUVs, and NHTSA 
continues to believe that attribute-based standards expressed as a 
mathematical function remain appropriate for those vehicles as well, 
given their similarity in many ways to light trucks. Thus, the proposed 
standards (and the regulatory alternatives) for passenger cars and 
light trucks take the form of fuel economy targets expressed as 
functions of vehicle footprint (the product of vehicle wheelbase and 
average track width) that are separate for passenger cars and light 
trucks, and the proposed standards and alternatives for HDPUVs take the 
form of fuel consumption targets expressed as functions of vehicle WF 
(which is in turn a function of towing and hauling capabilities).
---------------------------------------------------------------------------

    \70\ Vehicle footprint is the vehicle's wheelbase times average 
track width (or more simply, the length and width beween the 
vehicle's four wheels). The HDPUV FE towing-and-hauling-based ``WF'' 
metric is based on a vehicle's payload and towing capabilities, with 
an added adjustment for 4-wheel drive vehicles.
    \71\ 49 U.S.C. 32902(a)(3)(A).
---------------------------------------------------------------------------

    For passenger cars and light trucks, under the footprint-based 
standards, the function defines a fuel economy performance target for 
each unique footprint combination within a car or truck model type. 
Using the functions, each manufacturer thus will have a CAFE average 
standard for each year that is almost certainly unique to each of its 
fleets,\72\ based upon the footprint and production volumes of the 
vehicle models produced by that manufacturer. A manufacturer will have 
separate footprint-based standards for cars and for trucks, consistent 
with 49 U.S.C. 32902(b)'s direction that NHTSA must set separate 
standards for cars and for trucks. The functions are mostly sloped, so 
that generally, larger vehicles (i.e., vehicles with larger footprints) 
will be subject to lower mpg targets than smaller vehicles. This is 
because smaller vehicles are generally more capable of achieving higher 
levels of fuel economy, mostly because they tend not to have to work as 
hard (and therefore to require as much energy) to perform their driving 
task. Although a manufacturer's fleet average standard could be 
estimated throughout the MY based on the projected production volume of 
its vehicle fleet (and are estimated as part of EPA's certification 
process), the standards with which the manufacturer must comply are 
determined by its final model year (FMY) production figures. A 
manufacturer's calculation of its fleet average standards, as well as 
its fleets' average performance at the end of the MY, will thus be 
based on the production-weighted average target and performance of each 
model in its fleet.\73\
---------------------------------------------------------------------------

    \72\ EPCA/EISA requires NHTSA and EPA to separate passenger cars 
into domestic and import passenger car fleets for CAFE compliance 
purposes (49 U.S.C. 32904(b)), whereas EPA combines all passenger 
cars into one fleet for GHG compliance purposes.
    \73\ As discussed in prior rulemakings, a manufacturer may have 
some vehicle models that exceed their target and some that are below 
their target. Compliance with a fleet average standard is determined 
by comparing the fleet average standard (based on the production-
weighted average of the target levels for each model) with fleet 
average performance (based on the production-weighted average of the 
performance of each model). This is inherent in the statutory 
structure of CAFE, which requires NHTSA to set corporate average 
standards.
---------------------------------------------------------------------------

    For passenger cars, consistent with prior rulemakings, NHTSA is 
proposing to define fuel economy targets as shown in Equation II-1.
BILLING CODE 4910-59-P
[GRAPHIC] [TIFF OMITTED] TP17AU23.005

Where:

TARGETFE is the fuel economy target (in mpg) applicable 
to a specific vehicle model type with a unique footprint 
combination,
a is a minimum fuel economy target (in mpg),
b is a maximum fuel economy target (in mpg),
c is the slope (in gallons per mile (or gpm) per square foot) of a 
line relating fuel

[[Page 56151]]

consumption (the inverse of fuel economy) to footprint, and
d is an intercept (in gpm) of the same line.

    Here, MIN and MAX are functions that take the minimum and maximum 
values, respectively, of the set of included values. For example, 
MIN[40, 35] = 35 and MAX(40, 25) = 40, such that MIN[MAX(40, 25), 35] = 
35.
    For the Preferred Alternative, this equation is represented 
graphically as the curves in Figure II-2.
[GRAPHIC] [TIFF OMITTED] TP17AU23.006

    For light trucks, also consistent with prior rulemakings, NHTSA is 
proposing to define fuel economy targets as shown in Equation II-2.
[GRAPHIC] [TIFF OMITTED] TP17AU23.007

Where:

TARGETFE is the fuel economy target (in mpg) applicable 
to a specific vehicle model type with a unique footprint 
combination,
a, b, c, and d are as for passenger cars, but taking values specific 
to light trucks,
e is a second minimum fuel economy target (in mpg),
f is a second maximum fuel economy target (in mpg),
g is the slope (in gpm per square foot) of a second line relating 
fuel consumption (the inverse of fuel economy) to footprint, and
h is an intercept (in gpm) of the same second line.

    For the Preferred Alternative, this equation is represented 
graphically as the curves in Figure II-3.

[[Page 56152]]

[GRAPHIC] [TIFF OMITTED] TP17AU23.008

    Although the general model of the target function equation is the 
same for passenger cars and light trucks, and the same for each MY, the 
parameters of the function equation differ for cars and trucks. The 
actual parameters for both the Preferred Alternative and the other 
regulatory alternatives are presented in Section III.
    The required CAFE level applicable to a passenger car (either 
domestic or import) or light truck fleet in a given MY is determined by 
calculating the production-weighted harmonic average of fuel economy 
targets applicable to specific vehicle model configurations in the 
fleet, as shown in Equation II-3.
[GRAPHIC] [TIFF OMITTED] TP17AU23.009

Where:

CAFErequired is the CAFE level the fleet is required to 
achieve,
i refers to specific vehicle model/configurations in the fleet,
PRODUCTIONi is the number of model configuration i 
produced for sale in the U.S., and
TARGETFE, i is the fuel economy target (as defined above) 
for model configuration i.

    For HDPUVs, NHTSA has previously set attribute-based standards, but 
used a work-based metric as the attribute rather than footprint. Work-
based measurements such as payload and towing capability are key among 
the parameters that characterize differences in the design of these 
vehicles, as well as differences in how the vehicles will be used. 
Since NHTSA has been regulating HDPUVs, these standards have been based 
on a WF attribute that combines the vehicle's payload and towing 
capabilities, with an added adjustment for 4-wheel drive vehicles. 
Again, while NHTSA is not required by statute to set HDPUV standards 
that are attribute-based and that are described by a mathematical 
function, NHTSA continues to believe that doing so is reasonable and 
appropriate for this segment of vehicles, consistent with prior HDPUV 
standard-setting rulemakings. NHTSA proposes to continue using the 
work-based attribute and gradually increasing stringency (which for 
HDPUVs means that standards appear to decline, as compared to passenger 
car and light truck standards where increasing stringency means that 
standards appear to increase. This is because HDPUV standards are based 
on fuel consumption, which is the inverse of fuel economy,\74\ the 
metric that NHTSA

[[Page 56153]]

is statutorily required to use when setting standards for light-duty 
vehicle (LDV) fuel use). NHTSA proposes to define HDPUV fuel efficiency 
targets as shown in Equation II-4.
---------------------------------------------------------------------------

    \74\ For additional information, see the National Academies of 
Sciences, Engineering, and Medicine. 2011. Assessment of Fuel 
Economy Technologies for Light-Duty Vehicles. Washington, DC. The 
National Academies Press. Available at: https://nap.nationalacademies.org/catalog/12924/assessment-of-fuel-economy-technologies-for-light-duty-vehicles. (Accessed: May 31, 2023). Fuel 
economy is a measure of how far a vehicle will travel with a gallon 
(or unit) of fuel and is expressed in mpg. Fuel consumption is the 
inverse of fuel economy. It is the amount of fuel consumed in 
driving a given distance. Fuel consumption is a fundamental 
engineering measure that is directly related to fuel consumed per 
100 miles and is useful because it can be employed as a direct 
measure of volumetric fuel savings.
[GRAPHIC] [TIFF OMITTED] TP17AU23.010

---------------------------------------------------------------------------
Where:

WF = Work Factor = [0.75 x (Payload Capacity + Xwd)] + [0.25 x 
Towing Capacity]
Where:
Xwd = 4wd adjustment = 500 lbs. if the vehicle group is equipped 
with 4WD and all-wheel drive, otherwise equals 0 lbs. for 2wd
Payload Capacity = GVWR (lbs.) - Curb Weight (lbs.) (for each 
vehicle group)
Towing Capacity = GCWR \75\ (lbs.) - GVWR (lbs.) (for each vehicle 
group)
---------------------------------------------------------------------------

    \75\ Gross Combined Weight Rating.

    For the Preferred Alternative, this equation is represented 
graphically as the curves in Figure II-4 and Figure II-5.
[GRAPHIC] [TIFF OMITTED] TP17AU23.011


[[Page 56154]]


[GRAPHIC] [TIFF OMITTED] TP17AU23.012

    Similar to the standards for passenger cars and light trucks, NHTSA 
(and EPA) have historically set HDPUV standards such that each 
manufacturer's fleet average standard is based on production volume-
weighting of target standards for all vehicles, which are based on each 
vehicle's WF as explained above. Thus, for HDPUVs, the required fuel 
efficiency level applicable in a given MY is determined by calculating 
the production-weighted harmonic average of subconfiguration targets 
applicable to specific vehicle model configurations in the fleet, as 
shown in Equation II-5.
[GRAPHIC] [TIFF OMITTED] TP17AU23.013

BILLING CODE 4910-59-C
Where:

Subconfiguration Target Standardi = fuel consumption standard for 
each group of vehicles with the same payload, towing capacity, and 
drive configuration (gallons per 100 miles), and
Volumei = production volume of each unique subconfiguration of a 
model type based upon payload, towing capacity, and drive 
configuration.

    Chapter 1 of the Draft TSD contains a detailed description of the 
use of attribute-based standards, generally, for passenger cars, light 
trucks, and HDPUVs, and explains the specific decision, in past rules 
and for the current proposal, to continue to use vehicle footprint as 
the attribute over which to vary passenger car and light truck 
stringency, and WF as the attribute over which to vary HDPUV 
stringency. That chapter also discusses the policy and approach in 
selecting the specific mathematical functions. NHTSA refers readers to 
the Draft TSD for a full discussion of these topics and seeks comment 
on that discussion.

C. What inputs does the compliance analysis require?

    The first step in our analysis of the effects of different levels 
of fuel economy standards is the compliance simulation. When we say, 
``compliance simulation'' throughout this rulemaking, we mean the CAFE 
Model's simulation of how vehicle manufacturers could comply with 
different levels of CAFE standards by adding fuel-economy-improving 
technology to an existing fleet of vehicles.\76\ At the most basic 
level, a model is a set of equations, algorithms,\77\ or other 
calculations that are used to make predictions about a

[[Page 56155]]

complex system, such as the environmental impact of a particular 
industry or activity. A model may consider various inputs, such as 
emissions data, technology costs, or other relevant factors, and use 
those inputs to generate output predictions.
---------------------------------------------------------------------------

    \76\ When we use the phase ``the model'' throughout this 
section, we are referring to the CAFE Model. Any other model will be 
specifically named.
    \77\ See Merriam-websiter, ``algorithm.'' Broadly, an algorithm 
is a step-by-step procedure for solving a problem or accomplishing 
some end. More specifically, an algorithm is a procedure for solving 
a mathematical problem (as of finding the greatest common divisor) 
in a finite number of steps that frequently involves repetition of 
an operation.
---------------------------------------------------------------------------

    One important note about models is that a model is only as good as 
the data and assumptions that go into it. We attempt to ensure that the 
technology inputs and assumptions that go into the CAFE Model to 
project the effects of different levels of CAFE standards are based on 
sound science and reliable data, and that our reasons for using those 
inputs and assumptions are transparent and understandable to 
stakeholders. This section and the following section discuss at a high 
level how we generate the technology inputs and assumptions that the 
CAFE Model uses for the compliance simulation.\78\ The Draft Technical 
Support Document, CAFE Model Documentation, CAFE Analysis Autonomie 
Model Documentation,\79\ and other technical reports supporting this 
proposal discuss our technology inputs and assumptions in more detail.
---------------------------------------------------------------------------

    \78\ As explained throughout this section, our inputs are a 
specific number or datapoint used by the model, and our assumptions 
are based on judgment after careful consideration of available 
evidence. An assumption can be an underlying reason for the use of a 
specific datapoint, function, or modeling process. For example, an 
input might be the fuel economy value of the Ford Mustang, whereas 
the assumption is that the Ford Mustang's fuel economy value 
reported in Ford's CAFE compliance data should be used in our 
modeling.
    \79\ The ANL report is titled ``Vehicle Simulation Process to 
Support the Analysis for MY 2027 and Beyond CAFE and MY 2030 and 
Beyond HDPUV FE Standards;'' however, for ease of use and 
consistency with the Draft TSD, it is referred to as ``CAFE Analysis 
Autonomie Documentation.''
---------------------------------------------------------------------------

    We incorporate technology inputs and assumptions either directly in 
the CAFE Model or in the CAFE Model's various input files. The heart of 
the CAFE Model's decisions about how to apply technologies to 
manufacturer's vehicles to project how the manufacturer could meet CAFE 
standards is the compliance simulation algorithm. The compliance 
simulation algorithm is several equations that direct the model to 
apply fuel economy improving technologies to vehicles in a way that 
estimates how manufacturers might apply those technologies to their 
vehicles in the real world. The compliance simulation algorithm 
projects a cost-effective pathway for manufacturers to comply with 
different levels of CAFE standards, considering the technology present 
on manufacturer's vehicles now, and what technology could be applied to 
their vehicles in the future. Embedded directly in the CAFE Model is 
the universe of technology options that the model can consider and some 
rules about the order in which it can consider those options and 
estimates of how effective fuel economy improving technology is on 
different types of vehicles, like on a sedan or a pickup truck.
    Technology inputs and assumptions are also located in all four of 
the CAFE Model's input files. The Market Data Input file is a Microsoft 
Excel file that characterizes the baseline automotive fleet used as the 
starting point for the analysis. There is one Excel row describing each 
vehicle model and model configuration manufactured in the United States 
in a MY (or years), and input and assumption data that links that 
vehicle to technology, economic, environmental, and safety effects. 
Next, the Technologies Input File identifies approximately six dozen 
technologies we use in the analysis, uses phase-in caps to identify 
when and how widely each technology can be applied to specific types of 
vehicles, provides most of the technology costs (only battery costs for 
electrified vehicles are provided in a separate file), and provides 
some of the inputs involved in estimating impacts on vehicle fuel 
consumption and weight. The Scenarios Input File provides the 
coefficient values defining the standards for each regulatory 
alternative,\80\ and other relevant information applicable to modeling 
each regulatory scenario. This information includes, for example, the 
estimated value of select tax credits from the IRA, which provide 
Federal technology incentives for electrified vehicles, and the PEF, 
which is a value that the Secretary of Energy determines under EPCA 
that applies to EV fuel economy values.\81\ Finally, the Parameters 
Input File contains mainly economic and environmental data, as well as 
data about how fuel economy credits and California's Zero Emissions 
Vehicle program credits are simulated in the model.
---------------------------------------------------------------------------

    \80\ The coefficient values are defined in Draft TSD Chapter 
1.2.1 for both the CAFE and HDPUV FE standards.
    \81\ See 49 U.S.C. 32904(a)(2), 88 FR 21525 (April 11, 2023).
---------------------------------------------------------------------------

    We generate these technology inputs and assumptions in several 
ways, including by and through evaluating data submitted by vehicle 
manufacturers pursuant to their CAFE reporting obligations; 
consolidating public data on vehicle models from manufacturer websites, 
press materials, marketing brochures, and other publicly available 
information; collaborative research, testing, and modeling with other 
Federal agencies, like the DOE's ANL; research, testing, and modeling 
with independent organizations, like IAV GmbH Ingenieurgesellschaft 
Auto und Verkehr (IAV), Southwest Research Institute (SwRI), NAS and 
FEV North America; determining that work done for prior rules is still 
relevant and applicable; considering feedback from stakeholders on 
prior rules and in meetings conducted before the commencement of this 
rule; and using our own engineering judgment. When we say, 
``engineering judgment'' throughout this rulemaking, we are referring 
to decisions made by a team of engineers and analysts. This judgment is 
based on their experience working in the automotive industry and other 
relevant fields, and assessment of all the data sources described 
above. Most importantly, we use engineering judgment to assess how best 
to represent vehicle manufacturer's potential responses to different 
levels of CAFE standards within the boundaries of our modeling tools, 
as ``a model is meant to simplify reality in order to make it 
tractable.'' \82\ In other words, we use engineering judgment to 
concentrate potential technology inputs and assumptions from millions 
of discrete data points from hundreds of sources to three datasets 
integrated in the CAFE Model and four input files. How the CAFE Model 
decides to apply technology, i.e., the compliance simulation algorithm, 
has also been developed using engineering judgment, considering some of 
the same factors that manufacturers consider when they add technology 
to vehicles in the real world.
---------------------------------------------------------------------------

    \82\ Chem. Mfrs. Ass'n v. E.P.A., 28 F.3d 1259, 1264-65 (D.C. 
Cir. 1994) (citing Milton Friedman, The Methodology of Positive 
Economics, in Essays in Positive Economics 3, 14-15 (1953)).
---------------------------------------------------------------------------

    While upon first read this discussion may seem oversimplified, we 
believe that there is value in all stakeholders being able to 
understand how the analysis uses different sets of technology inputs 
and assumptions and how those inputs and assumptions are based on real-
world factors. This is so that all stakeholders have the appropriate 
context to better comment on the specific technology inputs and 
assumptions discussed later and in detail in all of the associated 
technical documentation.
1. Technology Options and Pathways
    We begin the compliance analysis by defining the range of fuel 
economy improving technologies that the CAFE Model could add to a 
manufacturer's vehicles in the United States

[[Page 56156]]

market.83 84 85 These are technologies that we believe are 
representative of what vehicle manufacturers currently use on their 
vehicles, and that vehicle manufacturers could use on their vehicles in 
the timeframe of the standards (MYs 2027 and beyond for the LD analysis 
and MYs 2030 and beyond for the HDPUV analysis). The technology options 
include basic and advanced engines, transmissions, electrification, and 
road load technologies, which include mass reduction (MR), aerodynamic 
improvement (AERO), and tire rolling resistance (ROLL) reduction 
technologies. Note that while EPCA/EISA constrains our ability to 
consider the possibility that manufacturers would comply with CAFE 
standards by implementing some electrification technologies when making 
decisions about the level of CAFE standards that is maximum feasible, 
there are several reasons why we must accurately model the range of 
available electrification technologies. These are discussed in more 
detail in Section II.D and in Section V.
---------------------------------------------------------------------------

    \83\ 40 CFR 86.1806-17--Onboard diagnostics.
    \84\ 40 CFR 86.1818-12--Greenhouse gas emission standards for 
light-duty vehicles, light-duty trucks, and medium-duty passenger 
vehicles.
    \85\ Commission Directive 2001/116/EC--European Union emission 
regulations for new LDVs--including passenger cars and light 
commercial vehicles (LCV).
---------------------------------------------------------------------------

    We require several data elements to add a technology to the range 
of options that the CAFE Model can consider; those elements include a 
broadly applicable technology definition, estimates of how effective 
that technology is at improving a vehicle's fuel economy value on a 
range of vehicles (e.g., sedan through pickup truck, or HD pickup truck 
and HD van), and the cost to apply that technology on a range of 
vehicles. Each technology we select is designed to be representative of 
a wide range of specific technology applications used in the automotive 
industry. For example, in MY 2022, eleven vehicle brands under five 
vehicle manufacturers \86\ used what we call a ``downsized turbocharged 
engine with cylinder deactivation.'' While we might expect brands owned 
by the same manufacturer to use similar technology on their engines, 
among those five manufacturers, the engine systems will be very 
different. Some manufacturers may also have been making those engines 
longer than others, meaning that they have had more time to make the 
system more efficient while also making it cheaper, as they make gains 
learning the development improvement and production process. If we 
chose to model the best performing, cheapest engine and applied that 
technology across vehicles made by all automotive manufacturers, we 
would likely be underestimating the cost and underestimating the 
technology required for the entire automotive industry to achieve 
higher levels of CAFE standards. The reverse would be true if we 
selected a system that was less efficient and more expensive. So, in 
reality, some vehicle manufacturers' systems will perform better and 
cost less than our modeled systems and some will perform worse and cost 
more. However, selecting representative technology definitions for our 
analysis will ensure that, on balance, we capture a reasonable level of 
costs and benefits that would result from any manufacturer applying the 
technology.
---------------------------------------------------------------------------

    \86\ Ford, General Motors (GM), Honda, Stellantis, and VWA 
represent the following 11 brands: Acura, Alfa Romeo, Audi, Bentley, 
Buick, Cadillac, Chevrolet, Ford, GMC, Lamborghini, and Porsche.
---------------------------------------------------------------------------

    We have been refining the LD technology options since first 
developing the CAFE Model in the early 2000s. ``Refining'' means both 
adding and removing technology options depending on technology 
availability now and projected future availability in the United States 
market, while balancing a reasonable amount of modeling and analysis 
complexity. Since the last analysis we have reduced the number of LD 
ICE technology options but have refined the options, so they better 
reflect the diversity of engines in the current fleet. Our technology 
options also reflect an increase in diversity for hybridization and 
electrification options, though we utilize these options in a manner 
that is consistent with statutory constraints. In addition to better 
representing the current fleet, this reflects consistent feedback from 
vehicle manufacturers who have told us that they will reduce investment 
in ICEs while increasing investment in hybrid and plug-in BEV 
options.\87\
---------------------------------------------------------------------------

    \87\ 87 FR 25781 (May 2, 2022); Docket Submission of Ex Parte 
Meetings Prior to Publication of the Corporate Average Fuel Economy 
Standards for Passenger Cars and Light Trucks for Model Years 2027-
2032 and Fuel Efficiency Standards for Heavy-Duty Pickup Trucks and 
Vans for Model Years 2030-2035 Notice of Proposed Rulemaking 
memorandum, which can be found under References and Supporting 
Material in the rulemaking Docket No. NHTSA-2023-0022.
---------------------------------------------------------------------------

    Feedback on the past several CAFE rules has also centered 
thematically on the expected scope of future electrified vehicle 
technologies. We have received feedback that we cannot consider BEV 
options and even so, our costs underestimate BEV costs when we do 
consider them in, for example, the baseline. We have also received 
comments that we should consider more electrified vehicle options and 
our costs overestimate future costs. Consistent with our interpretation 
of EPCA/EISA, discussed further in Section V.D.1, we include several LD 
electrified technologies to appropriately represent the diversity of 
current and anticipated future technology options while ensuring our 
analysis remains consistent with statutory limitations. In addition, 
this ensures that our analysis can appropriately capture manufacturer 
decision making about their vehicle fleets for reasons other than CAFE 
standards (e.g., other regulatory programs and manufacturing 
decisions).
    The technology options also include our judgment about which 
technologies will not be available in the rulemaking timeframe. There 
are several reasons why we may have concluded that it was reasonable to 
exclude a technology from the options we consider. As with past 
analyses, we did not include technologies unlikely to be feasible in 
the rulemaking timeframe, engines technologies designed for markets 
other than the United States market that are required to use unique 
gasoline,\88\ or technologies where there were not appropriate data 
available for the range of vehicles that we model in the analysis 
(i.e., technologies that are still in the research and development 
phase but are not ready for mass market production). Each technology 
section below and in chapter 3 of the Draft TSD discusses these 
decisions in detail.
---------------------------------------------------------------------------

    \88\ In general, most vehicles produced for sale in the United 
States have been designed to use ``Regular'' gasoline, or 87 octane. 
See EIA. What is Octane. Available at: https://www.eia.gov/energyexplained/gasoline/octane-in-depth.php. (Accessed: May 31, 
2023), for more information.
---------------------------------------------------------------------------

    The HDPUV technology options also represent a diverse range of both 
internal combustion and electrified powertrain technologies. We last 
used the CAFE Model for analyzing HDPUV standards in the Phase 2 
Medium- and Heavy-Duty Greenhouse Gas and Fuel Efficiency joint rules 
with EPA in 2016.\89\ Since issuing that rule, we refined the ICE 
technology options based on trends on vehicles in the fleet and updated 
technology cost and effectiveness data. The HDPUV options also reflect 
more electrification and hybridization options in that real-world 
fleet. However, the HDPUV technology options are also less diverse than 
the LD technology options, for several reasons.

[[Page 56157]]

The HDPUV fleet is significantly smaller than the LD fleet, with five 
manufacturers building a little over 30 nameplates in one thousand 
vehicle model configurations,\90\ compared with the almost 20 LDV 
manufacturers building 369 nameplates in the range of over two thousand 
configurations. Also, by definition, the HDPUV fleet only includes two 
vehicle types: HD pickup trucks and work vans.\91\ These vehicle types 
have focused applications, which includes transporting people and 
moving equipment and supplies. As discussed in more detail below, these 
vehicles are built with specific technology application, reliability, 
and durability requirements in order to do work.\92\ We believe the 
range of HDPUV technology options appropriately and reasonably 
represents the smaller range of technology options available currently 
and for application in future MYs for the United States market.
---------------------------------------------------------------------------

    \89\ 81 FR 73478 (Oct. 25, 2016); CAFE Compliance and Effects 
Modeling System. 2016 Final Rule for Model Years 2021-2027 Heavy-
Duty Pickups and Vans. Available at: https://www.nhtsa.gov/corporate-average-fuel-economy/cafe-compliance-and-effects-modeling-system. (Accessed: May 31, 2023).
    \90\ In this example, a HDPUV ``nameplate'' could be the 
``Sprinter 2500'', as in the Mercedes-Benz Sprinter 2500. The 
vehicle model configurations are each unique variants of the 
Sprinter 2500 that have an individual row in our Market Data Input 
File, which are divided generally based on compliance fuel 
consumption value and WF.
    \91\ For this proposal, vehicles were divided between the LD and 
HDPUV fleets solely on their gross vehicle weight rating (GVWR) 
being above or below 8,500 lbs. We will revisit the distribution of 
vehicles in the final rule to include the the distinction for MDPVs.
    \92\ ``Work'' includes hauling, towing, carrying cargo, or 
transporting people, animals, or equipment.
---------------------------------------------------------------------------

    Note, however, that for both the LD and HDPUV analyses, the CAFE 
Model does not dictate or predict the technologies manufacturers must 
use to comply; rather, the CAFE Model outlines a technology pathway 
that manufacturers could use to meet the standards cost-effectively. 
While we estimate the costs and benefits for different levels of CAFE 
standards estimating technology applications that manufacturers could 
use in the rulemaking timeframe, it is entirely possible and reasonable 
that a vehicle manufacturer will use different technology options to 
meet our standards than the CAFE Model estimates and may even use 
technologies that we do not include in our analysis. This is because 
our standards do not mandate the application of any particular 
technology. Rather, our standards are performance based: manufacturers 
can and do use a range of compliance solutions that include technology 
application, shifting sales from one vehicle model or trim level to 
another,\93\ and even paying civil penalties. That said, we are 
confident that the 75 LD technology options and 30 HDPUV technology 
options included in the analysis (in particular considering that for 
each technology option, the analysis includes distinct technology cost 
and effectiveness values for fourteen different types of vehicles, 
resulting in about a million different technology effectiveness and 
cost data points) strike a reasonable balance between the diversity of 
technology used by an entire industry and simplifying reality in order 
to make modeling tractable.
---------------------------------------------------------------------------

    \93\ Manufacturers could increase their production of one type 
of vehicle that has higher fuel economy level, like the hybrid 
version of a conventional vehicle model, to meet the standards. For 
example, Ford has conventional, hybrid, and electric versions of its 
F-150 pickup truck, and Toyota has conventional, hybrid, and plug-in 
hybrid versions of its RAV4 sport utility vehicle.
    \94\ A detailed discussion of all the technologies listed in the 
table can be found in TSD Chapter 3.
---------------------------------------------------------------------------

    Table II-1 and Table II-2 below list most of the technologies that 
we used for the LD and HDPUV analyses. Each technology has a name that 
loosely corresponds to its real-world technology equivalent. We 
abbreviate the name to a short easy signifier for the CAFE Model to 
read. We organize those technologies into groups based on technology 
type: basic and advanced engines, transmissions, electrification, and 
road load technologies, which include MR, aerodynamic improvement, and 
low rolling resistance tire technologies.

         Table II-1--Light Duty Vehicle Technology Options \94\
------------------------------------------------------------------------
         Technology name              Abbreviation      Technology group
------------------------------------------------------------------------
Single Overhead Camshaft Engine    SOHC..............  Basic Engines.
 with VVT.
Double Overhead Camshaft Engine    DOHC..............  Basic Engines.
 with VVT.
Variable Valve Lift..............  VVL...............  Basic Engines.
Stoichiometric Gasoline Direct     SGDI..............  Basic Engines.
 Injection.
Cylinder Deactivation............  DEAC..............  Basic Engines.
Turbocharged Engine..............  TURBO0............  Advanced Engines.
Turbocharged Engine with Cooled    TURBOE............  Advanced Engines.
 Exhaust Gas Recirculation.
Turbocharged Engine with Cylinder  TURBOD............  Advanced Engines.
 Deactivation.
Advanced Turbocharged Engine,      TURBO1............  Advanced Engines.
 Level 1.
Advanced Turbocharged Engine,      TURBO2............  Advanced Engines.
 Level 2.
DOHC Engine with Advanced          ADEACD............  Advanced Engines.
 Cylinder Deactivation.
SOHC Engine with Advanced          ADEACS............  Advanced Engines.
 Cylinder Deactivation.
High Compression Ratio Engine....  HCR...............  Advanced Engines.
High Compression Ratio Engine      HCRE..............  Advanced Engines.
 with Cooled Exhaust Gas
 Recirculation.
High Compression Ratio Engine      HCRD..............  Advanced Engines.
 with Cylinder Deactivation.
Variable Compression Ratio Engine  VCR...............  Advanced Engines.
Variable Turbo Geometry Engine...  VTG...............  Advanced Engines.
Variable Turbo Geometry Engine     VTGE..............  Advanced Engines.
 with eBoost.
Turbocharged Engine with Advanced  TURBOAD...........  Advanced Engines.
 Cylinder Deactivation.
Advanced Diesel Engine...........  ADSL..............  Advanced Engines.
Advanced Diesel Engine with        DSLI..............  Advanced Engines.
 Cylinder Deactivation.
Compressed Natural Gas Engine....  CNG...............  Advanced Engines.
5-Speed Automatic Transmission...  AT5...............  Transmissions.
6-Speed Automatic Transmission...  AT6...............  Transmissions.
7-Speed Automatic Transmission     AT7L2.............  Transmissions.
 with Level 2 high efficiency
 gearbox (HEG).
8-Speed Automatic Transmission...  AT8...............  Transmissions.
8-Speed Automatic Transmission     AT8L2.............  Transmissions.
 with Level 2 HEG.
8-Speed Automatic Transmission     AT8L3.............  Transmissions.
 with Level 3 HEG.
9-Speed Automatic Transmission     AT9L2.............  Transmissions.
 with Level 2 HEG.
10-Speed Automatic Transmission    AT10L2............  Transmissions.
 with Level 2 HEG.
10-Speed Automatic Transmission    AT10L3............  Transmissions.
 with Level 3 HEG.
6-Speed Dual Clutch Transmission.  DCT6..............  Transmissions.

[[Page 56158]]

 
8-Speed Dual Clutch Transmission.  DCT8..............  Transmissions.
Continuously Variable              CVT...............  Transmissions.
 Transmission.
Continuously Variable              CVTL2.............  Transmissions.
 Transmission with Level 2 HEG.
Conventional Powertrain (Non-      CONV..............  Electrification.
 Electric).
12V Micro-Hybrid Start-Stop        SS12V.............  Electrification.
 System.
48V Belt Mounted Integrated        BISG..............  Electrification.
 Starter/Generator.
Parallel Strong Hybrid/Electric    P2D...............  Electrification.
 Vehicle with DOHC Engine.
Parallel Strong Hybrid/Electric    P2SGDID...........  Electrification.
 Vehicle with DOHC+SGDI Engine.
Parallel Strong Hybrid/Electric    P2S...............  Electrification.
 Vehicle with SOHC Engine.
Parallel Strong Hybrid/Electric    P2SGDIS...........  Electrification.
 Vehicle with SOHC+SGDI Engine.
Parallel Strong Hybrid Electric    P2TRB0............  Electrification.
 Vehicle with TURBO0 Engine.
Parallel Strong Hybrid Electric    P2TRBE............  Electrification.
 Vehicle with TURBOE Engine.
Parallel Strong Hybrid Electric    P2TRB1............  Electrification.
 Vehicle with TURBO1 Engine.
Parallel Strong Hybrid Electric    P2TRB2............  Electrification.
 Vehicle with TURBO2 Engine.
Parallel Strong Hybrid Electric    P2HCR.............  Electrification.
 Vehicle with HCR Engine.
Parallel Strong Hybrid Electric    P2HCRE............  Electrification.
 Vehicle with HCRE Engine.
Power Split Strong Hybrid/         SHEVPS............  Electrification.
 Electric Vehicle with Full Time
 Atkinson Engine.
Plug-in Hybrid Vehicle with        PHEV20T...........  Electrification.
 TURBO1 Engine and 20 miles of
 electric range.
Plug-in Hybrid Vehicle with        PHEV50T...........  Electrification.
 TURBO1 Engine and 50 miles of
 electric range.
Plug-in Hybrid Vehicle with HCR    PHEV20H...........  Electrification.
 Engine and 20 miles of electric
 range.
Plug-in Hybrid Vehicle with HCR    PHEV50H...........  Electrification.
 Engine and 50 miles of electric
 range.
Plug-in Hybrid Vehicle with Full   PHEV20PS..........  Electrification.
 Time Atkinson Engine and 20
 miles of electric range.
Plug-in Hybrid Vehicle with Full   PHEV50PS..........  Electrification.
 Time Atkinson Engine and 50
 miles of electric range.
Battery Electric Vehicle with 200  BEV1..............  Electrification.
 miles of range.
Battery Electric Vehicle with 250  BEV2..............  Electrification.
 miles of range.
Battery Electric Vehicle with 300  BEV3..............  Electrification.
 miles of range.
Battery Electric Vehicle with 350  BEV4..............  Electrification.
 miles of range.
Fuel Cell Vehicle................  FCV...............  Electrification.
Baseline Tire Rolling Resistance.  ROLL0.............  Rolling
                                                        Resistance.
Tire Rolling Resistance, 10%       ROLL10............  Rolling
 Improvement.                                           Resistance.
Tire Rolling Resistance, 20%       ROLL20............  Rolling
 Improvement.                                           Resistance.
Tire Rolling Resistance, 30%       ROLL30............  Rolling
 Improvement.                                           Resistance.
Baseline Aerodynamic Drag          AERO0.............  Aerodynamic Drag.
 Technology.
Aerodynamic Drag, 5% Drag          AERO5.............  Aerodynamic Drag.
 Coefficient Reduction.
Aerodynamic Drag, 10% Drag         AERO10............  Aerodynamic Drag.
 Coefficient Reduction.
Aerodynamic Drag, 15% Drag         AERO15............  Aerodynamic Drag.
 Coefficient Reduction.
Aerodynamic Drag, 20% Drag         AERO20............  Aerodynamic Drag.
 Coefficient Reduction.
Baseline Mass Reduction            MR0...............  Mass Reduction.
 Technology.
Mass Reduction--5.0% of Glider...  MR1...............  Mass Reduction.
Mass Reduction--7.5% of Glider...  MR2...............  Mass Reduction.
Mass Reduction--10.0% of Glider..  MR3...............  Mass Reduction.
Mass Reduction--15.0% of Glider..  MR4...............  Mass Reduction.
Mass Reduction--20.0% of Glider..  MR5...............  Mass Reduction.
------------------------------------------------------------------------


   Table II-2--Heavy-Duty Pickup Truck and Van Technology Options \95\
------------------------------------------------------------------------
         Technology name              Abbreviation      Technology group
------------------------------------------------------------------------
Single Overhead Camshaft Engine    SOHC..............  Basic Engines.
 with VVT.
Double Overhead Camshaft Engine    DOHC..............  Basic Engines.
 with VVT.
Stoichiometric Gasoline Direct     SGDI..............  Basic Engines.
 Injection.
Cylinder Deactivation............  DEAC..............  Basic Engines.
Turbocharged Engine..............  TURBO0............  Advanced Engines.
Advanced Diesel Engine...........  ADSL..............  Advanced Engines.
Advanced Diesel Engine with        DSLI..............  Advanced Engines.
 Improvements.
5-Speed Automatic Transmission...  AT5...............  Transmissions.
6-Speed Automatic Transmission...  AT6...............  Transmissions.
8-Speed Automatic Transmission...  AT8...............  Transmissions.
9-Speed Automatic Transmission     AT9L2.............  Transmissions.
 with Level 2 HEG.
10-Speed Automatic Transmission    AT10L2............  Transmissions.
 with Level 2 HEG.
Conventional Powertrain (Non-      CONV..............  Electrification.
 Electric).
12V Micro-Hybrid Start-Stop        SS12V.............  Electrification.
 System.
Belt Mounted Integrated Starter/   BISG..............  Electrification.
 Generator.
Parallel Strong Hybrid/Electric    P2S...............  Electrification.
 Vehicle with SOHC Engine.         (P2D, P2TRB0).....
Plug-in Hybrid Vehicle with Basic  PHEV50H...........  Electrification.
 Engine and 50 miles of electric   (PHEV50T).........
 range.
Battery Electric Vehicle with 150  BEV1..............  Electrification.
 miles of range (for van classes)
 or 200 miles of range (for
 pickup classes).
Battery Electric Vehicle with 250  BEV2..............  Electrification.
 miles of range (for van classes)
 or 300 miles of range (for
 pickup classes).

[[Page 56159]]

 
Fuel Cell Vehicle................  FCV...............  Electrification.
Baseline Tire Rolling Resistance.  ROLL0.............  Rolling
                                                        Resistance.
Tire Rolling Resistance, 10%       ROLL10............  Rolling
 Improvement.                                           Resistance.
Tire Rolling Resistance, 20%       ROLL20............  Rolling
 Improvement.                                           Resistance.
Baseline Aerodynamic Drag          AERO0.............  Aerodynamic Drag.
 Technology.
Aerodynamic Drag, 10% Drag         AERO10............  Aerodynamic Drag.
 Coefficient Reduction.
Aerodynamic Drag, 20% Drag         AERO20............  Aerodynamic Drag.
 Coefficient Reduction.
Baseline Mass Reduction            MR0...............  Mass Reduction.
 Technology.
Mass Reduction--1.4% of Glider...  MR1...............  Mass Reduction.
Mass Reduction--13.0% of Glider..  MR2...............  Mass Reduction.
------------------------------------------------------------------------

    We then organize the groups into pathways. The pathways instruct 
the CAFE Model how and in what order to apply technology. In other 
words, the pathways define technologies that are mutually exclusive 
(i.e., that cannot be applied at the same time), and define the 
direction in which vehicles can advance as the model evaluates which 
technologies to apply. Figure II-6 shows the LD and HDPUV technology 
pathways used in this analysis. In general, the paths are tied to ease 
of implementation of additional technology and how closely related the 
technologies are.
---------------------------------------------------------------------------

    \95\ A detailed discussion of all the technologies listed in the 
table can be found in TSD Chapter 3.
---------------------------------------------------------------------------

BILLING CODE 4910-59-P

[[Page 56160]]

[GRAPHIC] [TIFF OMITTED] TP17AU23.014

BILLING CODE 4910-59-C
    As an example, our ``Turbo Engine Path'' consists of five different 
engine technologies that employ different levels of turbocharging 
technology. A

[[Page 56161]]

turbocharger is essentially a small turbine that is driven by exhaust 
gases produced by the engine. As these gases flow through the 
turbocharger, they spin the turbine, which in turn spins a compressor 
that pushes more air into an engine's cylinder. Having more air in the 
engine's cylinder allows the engine to burn more fuel, which then 
creates more power, without needing a physically larger engine. In our 
analysis, an engine that uses a turbocharger ``downsizes,'' or becomes 
smaller. The smaller engine can use less fuel to do the same amount of 
work as the engine did before it used a turbocharger and was downsized. 
Allowing basic engines to be downsized and turbocharged instead of just 
turbocharged keeps the vehicle's utility and performance constant so 
that we can measure the costs and benefits of different levels of fuel 
economy improvements, rather than the change in different vehicle 
attributes. This concept is discussed further, below.
    Grouping technologies on pathways also tells the model how to 
evaluate technologies; continuing this example, a vehicle can only have 
one engine, so if a vehicle has one of the Turbo engines the model will 
evaluate which more advanced Turbo technology to apply. Or, if it is 
more cost-effective to go beyond the Turbo pathway, the model will 
evaluate whether to apply more advanced engine technologies and 
hybridization path technology.
    Then, the arrows between technologies instruct the model on the 
order in which to evaluate technologies on a pathway. This ensures that 
a vehicle that uses a more fuel-efficient technology cannot downgrade 
to a less efficient option or that a vehicle would switch to technology 
that was significantly technically different. As an example, if a 
vehicle in the compliance simulation begins with a TURBOD engine--a 
turbocharged engine with cylinder deactivation--it cannot adopt a 
TURBO0 engine. Similarly, this vehicle with a TURBOD engine cannot 
adopt an ADEACD engine.\96\ The model follows instructions pursuant to 
the direction of arrows between technology groups and between 
technologies on the same pathway.
---------------------------------------------------------------------------

    \96\ An engine could potentially be changed from TURBO0 to 
TURBO2 without redesigning the engine block or requiring 
significantly different expertise to design and implement. A change 
to ADEACD would likely require a different engine block that might 
not be possible to fit in the engine bay of the vehicle without a 
complete redesign and different technical expertise requiring years 
of research and development. This consideration which would strand 
capital and break parts sharing is why the advanced engine paths 
restrict most movement between them.
---------------------------------------------------------------------------

    We also consider two categories of technology that we could not 
simulate as part of the CAFE Model's technology pathways. ``Off-cycle'' 
and air conditioning (AC) efficiency technologies improve vehicle fuel 
economy, but the benefit of those technologies cannot be captured using 
the fuel economy test methods that we must use under EPCA/EISA.\97\ As 
an example, manufacturers can claim a benefit for technology like 
active seat ventilation and solar reflective surface coatings that make 
the cabin of a vehicle more comfortable for the occupants, who then do 
not have to use other less efficient accessories like heat or AC. 
Instead of including off-cycle and AC efficiency technologies in the 
technology pathways, we include the improvement as a defined benefit 
that gets applied to a manufacturer's entire fleet instead of to 
individual vehicles. The defined benefit that each manufacturer 
receives in the analysis for using off-cycle and AC efficiency 
technology on their vehicles is located in the Market Data Input file. 
See Chapter 3.7 of the Draft TSD for more discussion in how off-cycle 
and AC efficiency technologies are developed and modeled.
---------------------------------------------------------------------------

    \97\ See 49 U.S.C. 32904(c) (``Testing and calculation 
procedures. . . . the Administrator shall use the same procedures 
for passenger automobiles the Administrator used for model year 1975 
(weighted 55 percent urban cycle and 45 percent highway cycle), or 
procedures that give comparable results.'').
---------------------------------------------------------------------------

    To illustrate, throughout this section we will follow the 
hypothetical vehicle mentioned above that begins the compliance 
simulation with a TURBOD engine. Our hypothetical vehicle, Generic 
Motors' Ravine Runner F Series, is a roomy, top of the line sport 
utility vehicle (SUV). The Ravine Runner F Series starts the compliance 
simulation with technologies from most technology pathways; 
specifically, after looking at Generic Motors' website and marketing 
materials, we determined that it has technology that loosely fits 
within the following technologies that we consider in the CAFE Model: 
it has a turbocharged engine with cylinder deactivation, a fairly 
advanced 10-speed automatic transmission, a 12V start-stop system, the 
least advanced tire technology, a fairly aerodynamic vehicle body, and 
it employs a fairly advanced level of MR. We track the technologies on 
each vehicle using a ``technology key'', which is the string of 
technology abbreviations for each vehicle. Again, the vehicle 
technologies and their abbreviations that we consider in this analysis 
are shown in Table II-1 and Table II-2 above. The technology key for 
the Ravine Runner F Series is ``TURBOD; AT10L2, SS12V; ROLL0; AERO5; 
MR3.''
2. Defining the Technology Baseline
    The Market Data Input File is one of four Excel input files that 
the CAFE Model uses for compliance and effects simulation. The Market 
Data Input file's ``Vehicles'' tab (or worksheet) houses one of the 
most significant compilations of technology inputs and assumptions in 
the analysis, which is a characterization of a baseline fleet of 
vehicles to which the CAFE Model adds fuel-economy-improving 
technology. We call this fleet the ``baseline fleet'' or the ``analysis 
fleet.'' The baseline fleet includes a number of inputs necessary for 
the model to add fuel economy improving technology to each vehicle for 
the compliance analysis and to calculate the resulting impacts for the 
effects analysis.
    There is one Microsoft Excel file row for each vehicle model, for 
LD with the same certification fuel economy value and vehicle 
footprint, and for HDPUV with the same certification fuel consumption 
and WF. This means that vehicle models with different configurations 
that affect the vehicle's certification fuel economy or fuel 
consumption value--for example, our Ravine Runner example vehicle comes 
in three different configurations, the Ravine Runner FWD, Ravine Runner 
AWD, and Ravine Runner F Series--will be separated into three rows in 
the Vehicles tab. In each row we also designate a vehicle's engine, 
transmission, and platform codes.\98\ Vehicles that have the same 
engine, transmission, or platform code are deemed to ``share'' that 
component in the CAFE Model. Parts sharing helps manufacturers achieve 
economies of scale, deploy capital efficiently, and make the most of 
shared research and development expenses, while still presenting a wide 
array of consumer choices to the market. The CAFE Model was developed 
to treat vehicles, platforms, engines, and transmissions as separate 
entities, which allows the modeling system to concurrently evaluate 
technology improvements on multiple vehicles that may share a

[[Page 56162]]

common component. Sharing also enables realistic propagation, or 
``inheriting,'' of previously applied technologies from an upgraded 
component down to the vehicle ``users'' of that component that have not 
yet realized the benefits of the upgrade. For additional information 
about the initial state of the fleet and technology evaluation and 
inheriting within the CAFE Model, please see Section 2.1 and Section 
4.4 of the Draft CAFE Model Documentation.
---------------------------------------------------------------------------

    \98\ Each numeric engine, transmission, or platform code 
designates important information about that vehicle's technology; 
for example, a vehicle's six-digit Transmission Code includes 
information about the manufacturer, the vehicle's drive 
configuration (i.e., front-wheel drive, all-wheel drive, four-wheel 
drive, or rear-wheel drive), transmission type, number of gears 
(e.g., a 6-speed transmission has six gears), and the transmission 
variant.
---------------------------------------------------------------------------

    Figure II-7 below shows how we separate the different 
configurations of the Ravine Runner. We can see by the Platform Codes 
that these Ravine Runners all share the same platform, but only the 
Ravine Runner FWD and Ravine Runner AWD share an engine. Even so, all 
three certification fuel economy values are different, which is common 
of vehicles that differ in drive type (drive type meaning whether the 
vehicle has all-wheel drive (AWD), four-wheel drive (4WD), front-wheel 
drive (FWD), or rear-wheel drive). While it would certainly be easier 
to aggregate vehicles by model, ensuring that we capture model variants 
with different fuel economy values improves the accuracy of our 
analysis and the potential that our estimated costs and benefits from 
different levels of standards are appropriate. We include information 
about other vehicle technologies at the farthest right side of the 
Vehicles tab, and in the ``Engines'', ``Transmissions'', and 
``Platforms'' worksheets, as discussed further below.
[GRAPHIC] [TIFF OMITTED] TP17AU23.015

    Moving from left to right on the Vehicles tab, after including 
general information about vehicles and their compliance fuel economy 
value, we include sales and manufacturer's suggested retail price 
(MSRP) data, regulatory class information (i.e., domestic passenger 
car, import passenger car, light truck, MDPV, HD pickup truck, or HD 
van), and information about how we classify vehicles for the 
effectiveness and safety analyses. Each of these data points is 
important to different parts of the compliance and effects analysis, so 
that the CAFE Model can accurately average the technologies required 
across a manufacturer's regulatory class for each class to meet its 
CAFE standard, or the impacts of higher fuel economy standards on 
vehicle sales. In addition, we include columns indicating if a vehicle 
is a ``ZEV Candidate,'' which means that the vehicle could be made into 
a zero emissions vehicle (ZEV) at its first redesign opportunity in 
order to simulate a manufacturer's compliance with California's ACC, 
ACC II, or ACT program, which is discussed further below. Next, we 
include vehicle information necessary for applying different types of 
technology; for example, designating a vehicle's body style means that 
we can appropriately apply aerodynamic technology, and designating 
starting curb weight values means that we can more accurately apply MR 
technology. Importantly, this section also includes vehicle footprint 
data (because we set footprint-based standards).
---------------------------------------------------------------------------

    \99\ Note that not all data columns are shown in this example 
for brevity.
---------------------------------------------------------------------------

    We also set product design cycles, which are the years when the 
CAFE Model can apply different technologies

[[Page 56163]]

to vehicles. Manufacturers often introduce fuel saving technologies at 
a ``redesign'' of their product or adopt technologies at ``refreshes'' 
in between product redesigns. As an example, the redesigned third 
generation Chevrolet Silverado was released for the 2019 MY, and 
featured a new platform, updated drivetrain, increased towing capacity, 
reduced weight, improved safety and expanded trim levels, to name a few 
improvements. For MY 2022, the Chevrolet Silverado received a refresh 
(or facelift as it is commonly called), with an updated interior, 
infotainment, and front-end appearance.\100\
---------------------------------------------------------------------------

    \100\ GM Authority. 2022 Chevy Silverado. Available at: https://gmauthority.com/blog/gm/chevrolet/silverado/2022-chevrolet-silverado/. (Accessed May 31, 2023).
---------------------------------------------------------------------------

    During modeling, all improvements from technology application are 
initially realized on a component and then propagated (or inherited) 
down to the vehicles that share that component. As such, new component-
level technologies are initially evaluated and applied to a platform, 
engine, or transmission during their respective redesign or refresh 
years. Any vehicles that share the same redesign and/or refresh 
schedule as the component apply these technology improvements during 
the same MY. The rest of the vehicles inherit technologies from the 
component during their refresh or redesign year (for engine- and 
transmission-level technologies), or during a redesign year only (for 
platform-level technologies). Please see Section 4.4 of the Draft CAFE 
Model Documentation for additional information about technology 
evaluation and inheriting within the CAFE Model.
    The CAFE Model also considers the potential safety effect of MR 
technologies and crash compatibility of different vehicle types. MR 
technologies lower the vehicle's curb weight, which may change crash 
compatibility and safety, depending on the type of vehicle. We assign 
each vehicle in the Market Data Input File a ``safety class'' that best 
aligns with the CAFE Model's analysis of vehicle mass, size, and 
safety, and include the vehicle's baseline curb weight.\101\
---------------------------------------------------------------------------

    \101\ Vehicle curb weight is the weight of the vehicle with all 
fluids and components but without the drivers, passengers, and 
cargo.
---------------------------------------------------------------------------

    The CAFE Model includes procedures to consider the direct labor 
impacts of manufacturers' response to CAFE regulations, considering the 
assembly location of vehicles, engines, and transmissions, the percent 
U.S. content (that reflects percent U.S. and Canada content), and the 
dealership employment associated with new vehicle sales. Baseline labor 
information, by vehicle, is included in the Market Data Input File. 
Sales volumes included in and adapted from the market data also 
influence total estimated direct labor projected in the analysis. See 
Chapter 6.2.5 of the Draft TSD for further discussion of the labor 
utilization analysis.
    Then we assign the CAFE Model's range of technologies to individual 
vehicles. This initial linkage of vehicle technologies is how the CAFE 
Model knows how to advance a vehicle down each technology pathway. 
Assigning CAFE Model technologies to individual vehicles is dependent 
on the mix of information we have about any particular vehicle and 
trends about how a manufacturer has added technology to that vehicle in 
the past, equations and models that translate real-world technologies 
to their counterparts in our analysis, and our engineering judgment.
    As discussed further below, we use information directly from 
manufacturers to populate some fields in the Market Data Input file, 
like vehicle horsepower ratings and vehicle weight. We also use 
manufacturer data as an input to various other models that calculate 
how a manufacturer's real-world technology equates to a technology 
level in our model. For example, we calculate MR, aerodynamic drag 
reduction, and ROLL baseline levels by looking at industry-wide trends 
and calculating--through models or equations--levels of improvement for 
each technology. The models and algorithms that we use are described 
further below and in detail in Chapter 3 of the Draft TSD. Other 
fields, like vehicle refresh and redesign years, are projected forward 
based on historic trends.
    Let us return to the Ravine Runner F Series with the technology key 
``TURBOD; AT10L2, SS12V; ROLL0; AERO5; MR3.'' Generic Motor's publicly 
available spec sheet for the Ravine Runner F Series says that the 
Ravine Runner F Series uses Generic Motor's Turbo V6 engine with 
proprietary Adaptive Cylinder Management Engine (ACME) technology. ACME 
improves fuel economy and lowers emissions by operating the engine 
using only three of the engine's cylinders in most conditions and using 
all six engine cylinders when more power is required. Generic Motors 
uses this engine in several of their vehicles, and the specifications 
of the engine can be found in the Engines Tab of the Market Data Input 
File, under a six-digit engine code.\102\
---------------------------------------------------------------------------

    \102\ Like the Transmission Codes discussed above, the Engine 
Codes include information identifying the manufacturer, engine 
displacement (i.e., how many liters the engine is), whether the 
engine is naturally aspirated or force inducted (e.g., 
turbocharged), and whether the engine has any other unique 
attributes.
---------------------------------------------------------------------------

    This is a relatively easy engine to assign based on publicly 
available specification sheets, but some technologies are much more 
difficult to assign. Manufacturers use different trade names or terms 
for different technology, and the way that we assign the technology in 
our analysis may not necessarily line up with how a manufacturer 
describes the technology. We must use some engineering judgment to 
determine how discrete technologies in the market best fit the 
technology options that we consider in our analysis. We discuss factors 
that we use to assign each vehicle technology in the individual 
technology subsections below.
    In addition to the Vehicles Tab that houses the baseline fleet, the 
Market Data input file includes information that affects how the CAFE 
Model might apply technology to vehicles in the compliance simulation. 
Specifically, the Market Data Input file's ``Manufacturers'' tab 
includes a list of vehicle manufacturers considered in the analysis and 
several pieces of information about their economic and compliance 
behavior. First, we determine if a manufacturer ``prefers fines,'' 
meaning that historically in the LD fleet, we have observed this 
manufacturer paying civil penalties for failure to meet CAFE 
standards.\103\ We might designate a manufacturer as not preferring 
fines if, for example, they have told us that paying civil penalties 
would be a violation of provisions in their corporate charter. For this 
analysis, we assume that all manufacturers are willing to pay fines in 
MYs 2022-2026, and that in MY 2027 and beyond, only the manufacturers 
that have historically paid fines would continue to pay fines. We seek 
comment on these fine payment preference assumptions. Note however 
that, as further discussed below in regard to the CAFE Model's 
compliance simulation algorithm, the model will still apply 
technologies for these manufacturers if it is cost-effective to do so, 
defined by several variables discussed below in Section II.C.6.
---------------------------------------------------------------------------

    \103\ See 49 U.S.C. 32912.
---------------------------------------------------------------------------

    Next, we designate a ``payback period'' for each manufacturer. The 
payback period represents an assumption that consumers are willing to 
buy vehicles with more fuel economy

[[Page 56164]]

technology because the fuel economy technology will save them money on 
gas in the long run. For the past several CAFE Model analyses we have 
assumed that in the absence of CAFE or other regulatory standards, 
manufacturers would apply technology that ``pays for itself''--by 
saving the consumer money on fuel--in 2.5 years. While the amount of 
technology that consumers are willing to pay for is subject to much 
debate, we assume a 2.5-year payback period based on what manufacturers 
have told us they do, and on estimates in the available literature. 
This is discussed in detail in Section II.E below, and in the Draft TSD 
and PRIA.
    We also designate in the Market Data Input file the percentage of 
each manufacturer's sales that must meet CAA section 177 requirements 
in certain states. Section 209(a) of the CAA generally preempts states 
from adopting emission control standards for new motor vehicles; 
however, Congress created an exemption program in section 209(b) that 
allows the State of California to seek a waiver of preemption. EPA must 
grant the waiver unless the Agency makes one of three statutory 
findings.\104\ Under CAA section 177, other States can adopt and 
enforce standards identical those approved under California's section 
209(b) waiver.
---------------------------------------------------------------------------

    \104\ See 87 FR 14332 (March 14, 2022). (``The CAA section 
209(b) waiver is limited ``to any State which has adopted standards 
. . . for the control of emissions from new motor vehicles or new 
motor vehicle engines prior to March 30, 1966,'' and California is 
the only State that had standards in place before that date.'').
---------------------------------------------------------------------------

    Finally, we include estimated CAFE compliance credit banks for each 
manufacturer in several years through 2021, which is the year before 
the compliance simulation begins. The CAFE Model does not explicitly 
simulate credit trading between and among vehicle manufacturers, but we 
estimate how manufacturers might use compliance credits in early MYs. 
This reflects manufacturers' tendency to use regulatory credits rather 
than to apply technology.\105\
---------------------------------------------------------------------------

    \105\ Note, this is just an observation about manufacturers' 
tendency to use regulatory credits rather than to apply technology; 
in accordance with 49 U.S.C. 32902(h), the CAFE Model does not 
simulate a manufacturer's potential credit use during the years for 
which we are setting new CAFE standards.
---------------------------------------------------------------------------

    Before we begin building the Market Data Input file for any 
analysis, we must consider what MY vehicles will comprise the baseline 
fleet. There is an inherent time delay in the data we can use for any 
particular analysis because we must set LD CAFE standards at least 18 
months in advance of a MY if the CAFE standards increase,\106\ and 
HDPUV fuel efficiency standards at least 4 full MYs in advance if the 
standards increase.\107\ In addition to the requirement to set 
standards at least 18 months in advance of a MY, we must propose 
standards with enough time to allow the public to comment on the 
proposed standards and meaningfully evaluate that feedback and 
incorporate it into the final rule in accordance with the APA.\108\ 
This means that the most recent data we have available to generate the 
baseline fleet necessarily falls behind the MY fleets of vehicles for 
which we generate standards. We have historically and intend again to 
update the data we use for the baseline fleet for the final rule if we 
receive more recent, high-quality data in time to use it for the final 
rule.
---------------------------------------------------------------------------

    \106\ 49 U.S.C. 32902(a).
    \107\ 49 U.S.C. 32902(k)(3)(A).
    \108\ 5 U.S.C. 553.
---------------------------------------------------------------------------

    Using recent data for the baseline is more likely to reflect the 
current vehicle fleet than older data. Recent data will inherently 
include manufacturer's decisions on what fuel-economy-improving 
technology to apply, mix shifts in response to consumer preferences 
(e.g., more recent data reflects manufacturer and consumer preference 
towards larger vehicles),\109\ and industry sales volumes that 
incorporate substantive macroeconomic events (e.g., the impact of the 
Coronavirus disease of 2019 (COVID) or microchip shortages). We 
considered that using a baseline fleet year that has been impacted by 
these transitory shocks may not represent trends in future years; 
however, on balance, we believe that updating to using the most 
complete set of available fleet data provides the most accurate 
baseline for the CAFE Model to calculate compliance and effects of 
different levels of future fuel economy standards. Also, using recent 
data decreases the likelihood that the CAFE Model selects compliance 
pathways for future standards that affect vehicles already built-in 
previous MYs.\110\
---------------------------------------------------------------------------

    \109\ See the 2022 EPA Automotive Trends Report at pg. 14-19.
    \110\ For example, in this analysis the CAFE Model must apply 
technology to the MY 2022 fleet from MYs 2023-2026 for the 
compliance simulation that begins in MY 2027 (for the light-duty 
fleet), and from MYs 2023-2029 for the compliance simulation that 
begins in MY 2030 (for the HDPUV fleet). While manufacturers have 
already built MY 2022 and later vehicles, the most current, complete 
dataset with regulatory fuel economy test results to build the 
analysis fleet at the time of writing remains MY 2022 data for the 
light-duty fleet, and a range of MYs between 2014 and 2022 for the 
HDPUV fleet.
---------------------------------------------------------------------------

    At the time we start building the baseline fleet, data that we 
receive from vehicle manufacturers in accordance with EPCA/EISA,\111\ 
and our CAFE compliance regulations \112\ in advance of or during an 
ongoing MY, offers the best snapshot of vehicles for sale in the US in 
a MY. These pre-model year (PMY) and mid-model year (MMY) reports 
include information about individual vehicles at the vehicle 
configuration level. We use the vehicle configuration, certification 
fuel economy, sales, regulatory class, and some additional technology 
data from these reports as the starting point to build a ``row'' (i.e., 
a vehicle configuration, with all necessary information about the 
vehicle) in the Market Data Input File's Vehicle's Tab. Additional 
technology data come from publicly available information, including 
vehicle specification sheets, manufacturer press releases, owner's 
manuals, and websites. We also generate some assumptions in the Market 
Data Input file for data fields where there is limited data, like 
refresh and redesign cycles for future MYs, and technology levels for 
certain road load reduction technologies like MR and aerodynamic drag 
reduction.
---------------------------------------------------------------------------

    \111\ 49 U.S.C. 32907(a)(2).
    \112\ 49 CFR part 537.
---------------------------------------------------------------------------

    For this analysis, the LD baseline fleet consists of every vehicle 
model in MY 2022 in mostly every configuration that has a different 
compliance fuel economy value, which results in a little over 2,000 
individual rows in the Vehicles Tab of the Market Data Input file. The 
HDPUV fleet consists of vehicles produced in between MYs 2014 and 2022, 
which results in a little over 1100 individual rows in the HDPUV Market 
Data Input file. We used a combination of MY data for that fleet 
because of data availability, but the resulting dataset is a robust 
amalgamation that provides a reasonable starting point for the much 
smaller fleet.
    The next section discusses how our analysis evaluates how adding 
additional fuel-economy-improving technology to a vehicle in the 
baseline fleet will improve that vehicle's fuel economy value. Put 
another way, the next section answers the question, how do we estimate 
how effective any given technology is at improving a vehicle's fuel 
economy value?
3. Technology Effectiveness Values
    How does the CAFE Model know how effective any particular 
technology is at improving a vehicle's fuel economy value? Accurate 
technology effectiveness estimates require information about: (1) the 
vehicle type and size; (2) the other technologies on the vehicle and/or 
being added to the

[[Page 56165]]

vehicle at the same time; and (3) and how the vehicle is driven. Any 
oversimplification of these complex factors could make the 
effectiveness estimates less accurate.
    To build a database of technology effectiveness estimates that 
includes these factors, we partner with the DOE's ANL. ANL has 
developed and maintains a physics-based full-vehicle modeling and 
simulation tool called Autonomie that generates technology 
effectiveness estimates for the CAFE Model.
    What is physics-based full-vehicle modeling and simulation? A model 
is a mathematical representation of a system, and simulation is the 
behavior of that mathematical representation over time. In Autonomie, 
the model is a mathematical representation of an entire vehicle, 
including its individual technologies such as the engine and 
transmission, overall vehicle characteristics such as mass and 
aerodynamic drag, and the environmental conditions, such as ambient 
temperature and barometric pressure.
    We simulate a vehicle model's behavior over the ``two-cycle'' tests 
that are used to measure vehicle fuel economy.\113\ For readers 
unfamiliar with this process, measuring a vehicle's fuel economy on the 
two-cycle tests is like running a car on a treadmill following a 
program--or more specifically, two programs. The ``programs'' are the 
``urban cycle,'' or Federal Test Procedure (abbreviated as ``FTP''), 
and the ``highway cycle,'' or Highway Fuel Economy Test (abbreviated as 
``HFET''). Figure II-8 below shows the FTP ``program''; the vehicle 
meets certain speeds at certain times during the test, or in technical 
terms, the vehicle must follow the designated ``speed trace.'' The FTP 
is meant roughly to simulate stop and go city driving, and the HFET is 
meant roughly to simulate steady flowing highway driving at about 50 
miles per hour (mph). We also use the Society of Automotive Engineers 
(SAE) recommended practices to simulate hybridized and EV drive 
cycles,\114\ which involves the test cycles mentioned above and 
additional test cycles to measure battery energy consumption and range.
---------------------------------------------------------------------------

    \113\ We are statutorily required to use the two-cycle tests to 
measure vehicle fuel economy in the CAFE program. See 49 U.S.C. 
32904(c) (``Testing and calculation procedures. . . . the 
Administrator shall use the same procedures for passenger 
automobiles the Administrator used for model year 1975 (weighted 55 
percent urban cycle and 45 percent highway cycle), or procedures 
that give comparable results.'').
    \114\ SAE. Recommended Practice for Measuring the Exhaust 
Emissions and Fuel Economy of Hybrid-Electric Vehicles, Including 
Plug-in Hybrid Vehicles. SAE Standard J1711. Rev. Feb 2023.; and 
SAE. Battery Electric Vehicle Energy Consumption and Range Test 
Procedure. SAE Standard J1634. Rev. April 2021.
[GRAPHIC] [TIFF OMITTED] TP17AU23.016

    Measuring every vehicle's fuel economy values using the same test 
cycles (and in the real world, using sophisticated test and measurement 
equipment including dynamometers, carefully controlled environmental 
conditions, and precise procedures) ensures that the fuel economy 
certification results are repeatable for

[[Page 56166]]

each vehicle model, and comparable among all of the different vehicle 
models.
---------------------------------------------------------------------------

    \115\ EPA. Emissions Standards Reference Guide. EPA FTP. 
Available at: https://www.epa.gov/emission-standards-reference-guide/epa-federal-test-procedure-ftp. (Accessed: May 31, 2023).
---------------------------------------------------------------------------

    Finally, ``physics-based'' simply refers to the mathematical 
equations underlying the modeling and simulation--the simulated vehicle 
models and all of the sub-models that make up specific vehicle 
components and the calculated fuel used on simulated test cycles are 
calculated mathematical equations that conform to the laws of physics.
    Full-vehicle modeling and simulation was initially developed to 
avoid the costs of designing and testing prototype parts for every new 
type of technology. For example, Generic Motors can use physics-based 
computer modeling to determine the fuel economy penalty for adding a 
4WD, rugged off-road tire trim level of the Ravine Runner to its 
lineup. The Ravine Runner, modeled with its new drivetrain and off-road 
tires, can be simulated on a defined test route and under defined test 
conditions and compared against the baseline Ravine Runner simulated 
without the change. Full-vehicle modeling and simulation allows Generic 
Motors to consider and evaluate different designs and concepts before 
building a single prototype for any potential technology change.
    Full vehicle modeling and simulation is also essential to measuring 
how all technologies on a vehicle interact. An analysis using single or 
limited point estimates may assume that, for example, one technology 
may improve the vehicle's fuel economy by 5% and a second technology 
may improve the vehicle's fuel economy by 10%, but when both 
technologies are added to the vehicle together, they achieve a 15% 
improvement. Single point estimates generally do not provide accurate 
effectiveness values because they do not capture complex relationships 
among technologies. Technology effectiveness often differs 
significantly depending on the vehicle type (e.g., sedan versus pickup 
truck) and the way in which the technology interacts with other 
technologies on the vehicle, as different technologies may provide 
different incremental levels of fuel economy improvement if implemented 
alone or in combination with other technologies. As stated above, any 
oversimplification of these complex factors could lead to less accurate 
technology effectiveness estimates.
    In addition, because manufacturers often add several fuel-saving 
technologies simultaneously when redesigning a vehicle, it is difficult 
to isolate the effect of adding any one individual technology to the 
full vehicle system. Modeling and simulation offer the opportunity to 
isolate the effects of individual technologies by using a single or 
small number of baseline vehicle configurations and incrementally 
adding technologies to those baseline configurations. This provides a 
consistent reference point for the incremental effectiveness estimates 
for each technology and for combinations of technologies for each 
vehicle type. Vehicle modeling also reduces the potential for 
overcounting or undercounting technology effectiveness.
    ANL does not build an individual vehicle model for every single 
vehicle configuration in our LD and HDPUV Market Data Input files. This 
would be nearly impossible, because Autonomie requires very detailed 
data on hundreds of different vehicle attributes (like the weight of 
the vehicle's fuel tank, the weight of the vehicle's transmission 
housing, the weight of the engine, the vehicle's 0-60 mph time, and so 
on) to build a vehicle model, and for practical reasons we cannot 
acquire 4000 vehicles and obtain these measurements every time we 
promulgate a new rule (and we cannot acquire vehicles that have not yet 
been built). Rather, ANL builds a discrete number of vehicle models 
that are representative of large portions of vehicles in the real 
world. We refer to the vehicle model's type and performance level as 
the vehicle's ``technology class.'' By assigning each vehicle in the 
Market Data Input file a ``technology class,'' we can connect it to the 
Autonomie effectiveness estimate that best represents how effective the 
technology would be on the vehicle, taking into account vehicle 
characteristics like type and performance metrics. Because each vehicle 
technology class has unique characteristics, the effectiveness of 
technologies and combinations of technologies is different for each 
technology class.
    There are ten technology classes for the LD analysis: small car 
(SmallCar), small performance car (SmallCarPerf), medium car (MedCar), 
medium performance car (MedCarPerf), small SUV (SmallSUV), small 
performance SUV (SmallSUVPerf), medium SUV (MedSUV), medium performance 
SUV (MedSUVPerf), pickup truck (Pickup), and high towing pickup truck 
(PickupHT). There are four technology classes for the HDPUV analysis, 
based on the vehicle's ``weight class.'' An HDPUV that weighs between 
8,501 and 10,000 pounds is in ``Class 2b,'' and an HDPUV that weighs 
between 10,001 and 14,000 pounds is in ``Class 3.'' Our four HDPUV 
technology classes are Pickup2b, Pickup3, Van2b, and Van3.
    We use a two-step process that involves two algorithms to give 
vehicles a ``fit score'' that determines which vehicles best fit into 
each technology class. At the first step we determine the vehicle's 
size, and at the second step we determine the vehicle's performance 
level. Both algorithms consider several metrics about the individual 
vehicle and compare that vehicle to other vehicles in the baseline 
fleet. This process is discussed in detail in Draft TSD Chapter 2.2.
    Consider our Ravine Runner F Series, which is a medium-sized 
performance SUV. The exact same combination of technologies on the 
Ravine Runner F Series, which is a medium-sized SUV, will operate 
differently in a compact car or pickup truck, two different vehicle 
sizes. Our Ravine Runner F Series also achieves slightly better 
performance metrics than other medium-sized SUVs in the baseline fleet. 
When we say, ``performance metrics,'' we mean power, acceleration, 
handing, braking, and so on, but for the performance fit score 
algorithm, we consider the vehicle's estimated 0-60 mph time compared 
to a baseline 0-60 mph time for the vehicle's technology class. 
Accordingly, the ``technology class'' for the Ravine Runner F Series in 
our analysis is ``MedSUVPerf''.
    Table II-3 shows how vehicles in different technology classes that 
use the exact same fuel economy technology have very different absolute 
fuel economy values. Note that, as discussed further below, the 
Autonomie absolute fuel economy values are not used directly in the 
CAFE Model; we calculate the ratio between two Autonomie absolute fuel 
economy values (one for each technology key for a specific technology 
class) and apply that ratio to a baseline fleet vehicle's starting fuel 
economy value.

[[Page 56167]]



          Table II-3--Examples of Technology Class Differences
------------------------------------------------------------------------
                                                             Autonomie
                                                          absolute  fuel
           Technology class and technology key             economy value
                                                               (mpg)
------------------------------------------------------------------------
MedSUVPerf TURBOD; AT10L2, SS12V; ROLL0; AERO5; MR3.....            30.8
MedSUV TURBOD; AT10L2, SS12V; ROLL0; AERO5; MR3.........            34.9
CompactPerf TURBOD; AT10L2, SS12V; ROLL0; AERO5; MR3....            42.2
Pickup TURBOD; AT10L2, SS12V; ROLL0; AERO5; MR3.........            29.7
------------------------------------------------------------------------

    Let us also return to the concept of what we call technology 
synergies. Again, depending on the technology, when two technologies 
are added to the vehicle together, they may not result in an additive 
fuel economy improvement. This is an important concept to understand 
because in Section II.D, below, we present technology effectiveness 
estimates for every single combination of technology that could be 
applied to a vehicle. In some cases, technology effectiveness estimates 
show that a combined technology has a different effectiveness estimate 
than if the individual technologies were added together individually. 
However, this is expected and not an error. Continuing our example from 
above, turbocharging technology and DEAC technology both improve fuel 
economy by reducing the engine displacement, and accordingly burning 
less fuel. Turbocharging allows a larger naturally aspirated engine to 
be reduced in size or displacement while still doing the same amount of 
work, and its fuel efficiency improvements are in part due to the 
reduced displacement. DEAC effectively makes a larger engine smaller by 
essentially turning off cylinders, but the engine is able to perform 
the same amount of work when needed. Therefore, a manufacturer 
upgrading to an engine that uses both a turbocharger and DEAC 
technology, like the TURBOD engine in our example above, may not see a 
significant fuel economy improvement from that specific combination of 
technologies. Table II-4 shows a vehicle's fuel economy value when 
using the baseline DEAC technology and when using the baseline 
turbocharging technology, compared to our vehicle that uses both of 
those technologies combined with a TURBOD engine.

               Table II-4--Example of Technology Synergies
------------------------------------------------------------------------
                                                             Autonomie
                                                           absolute fuel
                MedSUVPerf technology key                  economy value
                                                               (mpg)
------------------------------------------------------------------------
DOHC; SGDI; AT10L2; SS12V; ROLL0; AERO5; MR3............            28.6
DOHC; SGDI; DEAC; AT10L2; SS12V; ROLL0; AERO5; MR3......            29.1
TURBO0; AT10L2; SS12V; ROLL0; AERO5; MR3................            30.7
TURBOD; AT10L2; SS12V; ROLL0; AERO5; MR3................            30.8
------------------------------------------------------------------------

    As expected, the percent improvement in Table II-4 between the 
first and second rows is 1.7% and between the third and fourth rows is 
0.3%, even though the only difference within the two sets of technology 
keys is the DEAC technology (note that we only compare technology keys 
within the same technology class). This is because there are complex 
interactions between all fuel economy improving technologies. We model 
these individual technologies and groups of technologies to reduce the 
uncertainty and improve the accuracy of the CAFE Model outputs.
    Some technology synergies that we will discuss in Section II.D 
include advanced engine and hybrid powertrain technology synergies. As 
an example, we do not see a particularly high effectiveness improvement 
from applying advanced engines to existing parallel strong hybrid 
(i.e., P2) architectures.\116\ In this instance, the P2 powertrain 
improves fuel economy, in part, by allowing the engine to spend more 
time operating at efficient engine speed and load conditions. This 
reduces the advantage of adding advanced engine technologies, which 
also improve fuel economy, by broadening the range of speed and load 
conditions for the engine to operate at high efficiency. This 
redundancy in fuel savings mechanism results in a lower effectiveness 
when the technologies are added to each other. Again, we intend and 
expect that different combinations of technologies will provide 
different effectiveness improvements on different vehicle types. This 
is something we can only see using full vehicle modeling and 
simulation.
---------------------------------------------------------------------------

    \116\ A parallel strong hybrid powertrain is fundamentally 
similar to a conventional powertrain but adds one electric motor to 
improve efficiency. Section II.C.1, Technology Options and Pathways, 
shows all of the parallel strong hybrid powertrain options we model 
in this analysis.
---------------------------------------------------------------------------

    Just as our CAFE Model analysis requires a large set of technology 
inputs and assumptions, the Autonomie modeling uses a large set of 
technology inputs and assumptions. Figure II-9 below shows the suite of 
fuel consumption input data used in the Autonomie modeling to generate 
the fuel consumption input data we use in the CAFE Model.

[[Page 56168]]

[GRAPHIC] [TIFF OMITTED] TP17AU23.017

    What are each of these inputs? For full vehicle benchmarking, 
vehicles are instrumented with sensors and tested both on the road and 
on chassis dynamometers (i.e., the car treadmills used to calculate 
vehicle's fuel economy values) under different conditions and duty 
cycles. Some examples of full vehicle benchmarking we did in 
conjunction with our partners at ANL in anticipation of this rule 
include benchmarking a 2019 Chevy Silverado, a 2021 Toyota Rav4 Prime, 
a 2022 Hyundai Sonata Hybrid, a 2020 Tesla Model 3, and a 2020 Chevy 
Bolt. We produced a report for each vehicle benchmarked, and those are 
available in the docket and on our website. As discussed further below, 
that full vehicle benchmarking data is used as inputs to the engine 
modeling and Autonomie full vehicle simulation modeling. Component 
benchmarking is like full vehicle benchmarking, but instead of testing 
a full vehicle, we instrument a single production component or 
prototype component with sensors and test it on a similar duty cycle as 
a full vehicle. Examples of components we benchmark are engines, 
transmissions, axles, electric motors, and batteries. Component 
benchmarking data are used as an input to component modeling, where a 
production or prototype component is changed in fit, form and/or 
function and modeled in the same scenario. As an example, we might 
model a decrease in the size of holes in fuel injectors to see the fuel 
atomization impact or see how it affects the fuel spray angle.
    We use a range of models to do the component modeling for our 
analysis. As shown in Figure II-9, battery pack modeling using ANL's 
BatPaC Model and engine modeling are two of the most significant 
component models used to generate data for the Autonomie modeling. We 
discuss BatPaC in detail in Section II.D, but briefly, BatPaC is the 
battery pack modeling tool we use to estimate the cost of vehicle 
battery packs, based on the materials chemistry, battery design, and 
manufacturing design of the plants manufacturing the battery packs.
    Engine modeling is used to generate engine fuel map models that 
define the fuel consumption rate for an engine equipped with specific 
technologies when operating over a variety of engine load and engine 
speed conditions. Some performance metrics we capture in engine 
modeling include power, torque, airflow, volumetric efficiency, fuel 
consumption, turbocharger performance and matching, pumping losses, and 
more. Each engine map model has been developed ensuring the engine will 
still operate under real-world constraints using a suite of other 
models. Some examples of these models that ensure the engine map models 
capture real-world operating constraints include simulating heat 
release through a predictive combustion model, knock characteristics 
through a kinetic fit knock model,\117\ and using physics-based heat 
flow and friction models, among others. We simulate these constraints 
using data gathered from component benchmarking, engineering, and 
physics.
---------------------------------------------------------------------------

    \117\ Engine knock occurs when combustion of some of the air/
fuel mixture in the cylinder does not result from propagation of the 
flame front ignited by the spark plug, but one or more pockets of 
air/fuel mixture explodes outside of the envelope of the normal 
combustion front. Engine knock can result in unsteady operation and 
damage to the engine.
---------------------------------------------------------------------------

    The engine map models are developed by creating a base, or root, 
engine map and then modifying that root map, incrementally, to isolate 
the effects of the added technologies. The LD engine maps, developed by 
IAV using their GT-Power modeling tool and the HDPUV engine maps, 
developed by SwRI using their GT-Power modeling tool, are based on 
real-world engine designs. One important feature of both the LD and 
HDPUV engine maps is that they were both developed using a knock model. 
As noted above, a knock model ensures that any engine size or 
specification that we model in the analysis does not result in engine 
knock, which could damage engine components in a real-world vehicle. 
Although the same engine map models are used for all vehicle technology 
classes, the effectiveness varies based on the characteristics of each 
class. For example, as discussed above, a compact car with a 
turbocharged engine will

[[Page 56169]]

have a different effectiveness value than a pickup truck with the same 
engine technology type. The engine map model development and 
specifications are discussed further in Chapter 3 of the Draft TSD.
    ANL also compiles a database of vehicle attributes and 
characteristics that are reasonably representative of the vehicles in 
that technology class to build the vehicle models. Relevant vehicle 
attributes may include a vehicle's fuel efficiency, emissions, 
horsepower, 0-60 mph acceleration time, and stopping distance, among 
others, while vehicle characteristics may include whether the vehicle 
has all-wheel-drive, 18-inch wheels, summer tires, and so on. ANL 
identified representative vehicle attributes and characteristics for 
both the LD and HDPUV fleets from publicly available information and 
automotive benchmarking databases such as A2Mac1,\118\ ANL's 
Downloadable Dynamometer Database (D\3\),\119\ EPA compliance and fuel 
economy data,\120\ EPA's guidance on the cold start penalty on 2-cycle 
tests,\121\ the 21st Century Truck Partnership,122 123 124 
and industry partnerships.\125\ The resulting vehicle technology class 
baseline assumptions and characteristics database consists of over 100 
different attributes like vehicle height and width and weights for 
individual vehicle parts.
---------------------------------------------------------------------------

    \118\ A2Mac1: Automotive Benchmarking. (Proprietary data). 
Available at: https://www.a2mac1.com. (Accessed: May 31, 2023). 
A2Mac1 is subscription-based benchmarking service that conducts 
vehicle and component teardown analyses. Annually, A2Mac1 removes 
individual components from production vehicles such as oil pans, 
electric machines, engines, transmissions, among the many other 
components. These components are weighed and documented for key 
specifications which is then available to their subscribers.
    \119\ Downloadable Dynamometer Database (D\3\). Argonne National 
Laboratory, Energy Systems Division. Available at: https://www.anl.gov/es/downloadable-dynamometer-database. (Accessed: May 31, 
2023).
    \120\ Data on Cars used for Testing Fuel Economy. EPA Compliance 
and Fuel Economy Data. Available at: https://www.epa.gov/compliance-and-fuel-economy-data/data-cars-used-testing-fuel-economy. 
(Accessed: May 31, 2023).
    \121\ EPA PD TSD at 2-265-2-266.
    \122\ DOE. 2019. 21st Century Truck Partnership Research 
Blueprint. Available at: https://www.energy.gov/sites/default/files/2019/02/f59/21CTPResearchBlueprint2019_FINAL.pdf. (Accessed: May, 
31, 2023).
    \123\ Office of Energy Efficiency & Renewable Energy. 2023. 21st 
Century Truck Partnership. Available at: https://www.energy.gov/eere/vehicles/21st-century-truck-partnership. (Accessed: May 31, 
2023).
    \124\ National Academies of Sciences, Engineering, and Medicine. 
2015. Review of the 21st Century Truck Partnership, Third Report. 
Washington, DC: The National Academies Press. Available at: https://nap.nationalacademies.org/21784/. (Accessed: May 31, 2023).
    \125\ North American Council for Freight Efficiency. Research 
and analysis. https://www.nacfe.org/research/overview/. (Accessed: 
May 31, 2023).
---------------------------------------------------------------------------

    ANL then assigns ``reference'' technologies to each vehicle model. 
The reference technologies are the technologies on the first step of 
each CAFE Model technology pathway, and they closely (but do not 
exactly) correlate to the technology abbreviations that we use in the 
CAFE Model. As an example, the first Autonomie vehicle model in the 
``MedSUVPerf'' technology class starts out with the least advanced 
engine, which is ``DOHC'' (a dual overhead cam engine) in the CAFE 
Model, or ``eng01'' in the Autonomie modeling. The vehicle has the 
least advanced transmission, AT5, the least advanced MR level, MR0, the 
least advanced aerodynamic body style, AERO0, and the least advanced 
ROLL level, ROLL0. The first vehicle model is also defined by initial 
vehicle attributes and characteristics that consist of data from the 
suite of sources mentioned above. Again, these attributes are meant to 
reasonably represent the average of vehicle attributes found on 
vehicles in a certain technology class.
    Then, just as a vehicle manufacturer tests its vehicles to ensure 
they meet specific performance metrics, Autonomie ensures that the 
built vehicle model meets its performance metrics. We include 
quantitative performance metrics in our Autonomie modeling to ensure 
that the vehicle models can meet real-world performance metrics that 
consumers observe and that are important for vehicle utility and 
customer satisfaction. The four performance metrics that we use in the 
Autonomie modeling for light duty vehicles are low-speed acceleration 
(the time required to accelerate from 0-60 mph), high-speed passing 
acceleration (the time required to accelerate from 50-80 mph), 
gradeability (the ability of the vehicle to maintain constant 65 mph 
speed on a six percent upgrade), and towing capacity for light duty 
pickup trucks. We have been using these performance metrics for the 
last several CAFE Model analyses, and vehicle manufacturers have 
repeatedly agreed that these performance metrics are representative of 
the metrics considered in the automotive industry.\126\ ANL simulates 
the vehicle model driving the two-cycle tests (i.e., running its 
treadmill ``programs'') to ensure that it meets its applicable 
performance metrics (e.g., our MedSUVPerf does not have to meet the 
towing capacity performance metric because it is not a pickup truck). 
For HDPUVs, Autonomie examines sustainable maximum speed at 6 percent 
grade, start/launch capability on grade, and maximum sustainable grade 
at highway cruising speed, before examining towing capability to look 
for the maximum possible vehicle weight over 40 mph in gradeability. 
This process ensures that the vehicle can satisfy the gradeability 
requirement (over 40 mph) with additional payload mass to the curb 
weight. These metrics are based on commonly used metrics in the 
automotive industry, including SAE J2807 tow requirements.\127\ 
Additional details about how we size light duty and HDPUV powertrains 
in Autonomie to meet defined performance metrics can be found in the 
CAFE Analysis Autonomie Documentation.
---------------------------------------------------------------------------

    \126\ See, e.g., NHTSA-2021-0053-1492, at 134 (``Vehicle design 
parameters are never static. With each new generation of a vehicle, 
manufacturers seek to improve vehicle utility, performance, and 
other characteristics based on research of customer expectations and 
desires, and to add innovative features that improve the customer 
experience. The Agencies have historically sought to maintain the 
performance characteristics of vehicles modeled with fuel economy-
improving technologies. Auto Innovators encourages the Agencies to 
maintain a performance-neutral approach to the analysis, to the 
extent possible. Auto Innovators appreciates that the Agencies 
continue to consider highspeed acceleration, gradeability, towing, 
range, traction, and interior room (including headroom) in the 
analysis when sizing powertrains and evaluating pathways for road-
load reductions. All of these parameters should be considered 
separately, not just in combination. (For example, we do not support 
an approach where various acceleration times are added together to 
create a single ``performance'' statistic. Manufacturers must 
provide all types of performance, not just one or two to the 
detriment of others.)'').
    \127\ See SAE J2807, Performance Requirements for Determining 
Tow-Vehicle Gross Combination Weight Rating and Trailer Weight 
Rating, available at https://www.sae.org/standards/content/j2807_202002/.
---------------------------------------------------------------------------

    If the vehicle model does not initially meet one of the performance 
metrics, then Autonomie's powertrain sizing algorithm increases the 
vehicle's engine power. The increase in power is achieved by increasing 
engine displacement (which is the measure of the volume of all 
cylinders in an engine), which might involve an increase in the number 
of engine cylinders, which may lead to an increase in the engine 
weight. This iterative process then determines if the baseline vehicle 
with increased engine power and corresponding updated engine weight 
meets the required performance metrics. The powertrain sizing algorithm 
stops once all the baseline vehicle's performance requirements are met.
    Some technologies require extra steps for performance optimization 
before the

[[Page 56170]]

vehicle models are ready for simulation. Specifically, the sizing and 
optimization process is more complex for the electrified vehicles 
(e.g., hybrid electric vehicle (HEVs) and plug-in hybrid electric 
vehicles (PHEVs) compared to vehicles with only ICEs, as discussed 
further in the Draft TSD. As an example, a PHEV powertrain that can 
travel a certain number of miles on its battery energy alone (referred 
to as all-electric range (AER), or as performing in electric-only mode) 
is also sized to ensure that it can meet the performance requirements 
of the SAE standardized drive cycles mentioned above in electric-only 
mode.
    Every time a vehicle model in Autonomie adopts a new technology, 
the vehicle weight is updated to reflect the weight of the new 
technology. For some technologies, the direct weight change is easy to 
assess. For example, when a vehicle is updated to a higher geared 
transmission, the weight of the original transmission is replaced with 
the corresponding transmission weight (e.g., the weight of a vehicle 
moving from a 6-speed automatic (AT6) to an 8-speed automatic (AT8) 
transmission is updated based on the 8-speed transmission weight). For 
other technologies, like engine technologies, calculating the updated 
vehicle weight is more complex. As discussed earlier, modeling a change 
in engine technology involves both the new technology adoption and a 
change in power (because the reduction in vehicle weight leads to lower 
engine loads, and a resized engine). When a vehicle adopts new engine 
technology, the associated weight change to the vehicle is accounted 
for based on a regression analysis of engine weight versus power.\128\
---------------------------------------------------------------------------

    \128\ See Merriam-Webster, ``regression analysis'' is the use of 
mathematical and statistical techniques to estimate one variable 
from another especially by the application of regression 
coefficients, regression curves, regression equations, or regression 
lines to empirical data. In this case, we are estimating engine 
weight by looking at the relationship between engine weight and 
engine power.
---------------------------------------------------------------------------

    In addition to using performance metrics that are commonly used by 
automotive manufacturers, we instruct Autonomie to mimic real-world 
manufacturer decisions by only resizing engines at specific periods in 
the analysis and in specific ways. When a vehicle manufacturer is 
making decisions about how to change a vehicle model to add fuel 
economy improving technology, the manufacturer could entirely 
``redesign'' the vehicle, or the manufacturer could ``refresh'' the 
vehicle with relatively more minor technology changes. We discuss how 
our modeling captures vehicle refreshes and redesigns in more detail 
below, but for now there are some simple yet important concepts to 
understand. First, most changes to a vehicle's engine happen when the 
vehicle is redesigned and not refreshed, as incorporating a new engine 
in a vehicle is a 10- to 15-year endeavor at a cost of $750 million to 
$1 billion.\129\ But, manufacturers will use that same basic engine, 
with only minor changes, across multiple vehicle models. We model 
engine ``inheriting'' from one vehicle to another in both the Autonomie 
modeling and the CAFE Model. During a vehicle ``refresh'', one vehicle 
may inherit an already redesigned engine from another vehicle that 
shares the same platform. In the Autonomie modeling, when a new vehicle 
adopts fuel saving technologies that are inherited, the engine is not 
resized (i.e., the properties from the reference vehicle are used 
directly). While this may result in a small change in vehicle 
performance, manufacturers have repeatedly and consistently told us 
that the high costs for redesign and the increased manufacturing 
complexity that would result from resizing engines for small technology 
changes preclude them from doing so. In addition, when a manufacturer 
applies MR technology (i.e., makes the vehicle lighter), the vehicle 
can use a less powerful engine because there is less weight to move. 
However, Autonomie will only use a resized engine at certain MR 
application levels, as a representation of how manufacturers update 
their engine technologies. Again, this is intended to reflect 
manufacturer's comments that it would be unreasonable and unaffordable 
to resize powertrains for every unique combination of technologies. We 
have determined that our rules about performance neutrality and 
technology inheritance result in a fleet that is essentially 
performance neutral.
---------------------------------------------------------------------------

    \129\ 2015 NAS Report, at 256. It's likely that manufacturers 
have made improvements in the product lifetime and development 
cycles for engines since this NAS report and the report that the NAS 
relied on, but we do not have data on how much. We believe that it 
is still reasonable to conclude that generating an all new engine or 
transmission design with little to no carryover from the previous 
generation would be a notable investment.
---------------------------------------------------------------------------

    Why is it important to ensure that the vehicle models in our 
analysis maintain consistent performance levels? The answer involves 
how we measure the costs and benefits of different levels of fuel 
economy standards. In our analysis, we want to capture the costs and 
benefits of vehicle manufacturers applying fuel-economy-improving 
technologies to their vehicles. If we modeled increases or decreases in 
performance because of fuel economy improving technology--for example, 
say a manufacturer that adds a turbocharger to their engine without 
downsizing the engine, and then directs all of the additional engine 
work to additional vehicle horsepower instead of vehicle fuel economy 
improvements--that increase in performance has a monetized benefit 
attached to it that is not specifically due to our fuel economy 
standards. By ensuring that our vehicle modeling remains performance 
neutral, we can better ensure that we are reasonably capturing the 
costs and benefits due only to potential changes in the fuel economy 
standards.
    As with past rules, we have analyzed the change in low speed 
acceleration (0-60 mph) time for four scenarios: (1) MY 2022 under the 
no action scenario (i.e., No-Action Alternative), (2) MY 2022 under the 
Preferred Alternative, (3) MY 2032 under the no action scenario, and 
(4) MY 2032 under the Preferred Alternative.\130\ Using the MY 2022 
analysis fleet sales volumes as weights, we calculated the weighted 
average 0-60 mph acceleration time for the analysis fleet in each of 
the four above scenarios. We identified that the analysis fleet under 
no action standards in MY 2032 had a 0.5002 percent worse 0-60 mph 
acceleration time than under the Preferred Alternative, indicating 
there is minimal difference in performance between the alternatives.
---------------------------------------------------------------------------

    \130\ The baseline reference for both the No-Action Alternative 
and the Preferred Alternative is MY 2022 fleet performance.
---------------------------------------------------------------------------

    Autonomie then adopts one single fuel saving technology to the 
baseline vehicle model, keeping everything else the same except for 
that one technology and the attributes associated with it. Once one 
technology is assigned to the vehicle model and the new vehicle model 
meets its performance metrics, the vehicle model is used as an input to 
the full vehicle simulation. This means that Autonomie simulates the 
optimized vehicle models for each technology class driving the test 
cycles we described above. As an example, the Autonomie modeling could 
start with 14 initial vehicle models (one for each technology class in 
the LD and HDPUV analysis). Those 14 initial vehicle models use a 
baseline 5-speed automatic transmission.\131\ ANL then builds 14 new 
vehicle models; the only difference between the 14 new vehicle models 
and the first set of vehicle models is that the

[[Page 56171]]

new vehicle models have a 6-speed automatic transmission. Replacing the 
AT5 with an AT6 would lead either to an increase or decrease in the 
total weight of the vehicle because each technology class includes 
different assumptions about transmission weight. ANL then ensures that 
the new vehicle models with the 6-speed automatic transmission meet 
their performance metrics. Now we have 28 different vehicle models that 
can be simulated on the two-cycle tests. This process is repeated for 
each technology option and for each technology class. This results in 
fourteen separate datasets, each with over 100,000 results, that 
include information about a vehicle model made of specific fuel economy 
improving technology and the fuel economy value that the vehicle model 
achieved driving its simulated test cycles.
---------------------------------------------------------------------------

    \131\ Note that although both the LD and HDPUV analyses include 
a 5-speed automatic transmission, the characteristics of those 
transmissions differ between the two analyses.
---------------------------------------------------------------------------

    We condense the million or so datapoints from Autonomie into three 
datasets used in the CAFE Model. These three datasets include (1) the 
fuel economy value (converted into ``fuel consumption'', which is the 
inverse of fuel economy; fuel economy is mpg and fuel consumption is 
gallons per mile) that each modeled vehicle achieved while driving the 
test cycles, for every technology combination in every technology 
class; (2) the fuel economy value for PHEVs driving those test cycles, 
when those vehicles drive on gasoline-only in order to comply with 
statutory constraints; and (3) optimized battery costs for each vehicle 
that adopts some sort of electrified powertrain (this is discussed in 
more detail below).
    Now, how does this information translate into the technology 
effectiveness data that we use in the CAFE Model? An important feature 
of this analysis is that the fuel economy improvement from each 
technology and combinations of technologies should be accurate and 
relative to a consistent baseline vehicle. We use the absolute fuel 
economy values from the full vehicle simulations only to determine the 
relative fuel economy improvement from adding a set of technologies to 
a vehicle, but not to assign an absolute fuel economy value to any 
vehicle model or configuration. For this analysis, the baseline 
absolute fuel economy value for each vehicle in the analysis fleet is 
based on CAFE compliance data. For subsequent technology changes, we 
apply the incremental fuel economy improvement values from one or more 
technologies to the baseline fuel economy value to determine the 
absolute fuel economy achieved for applying the technology change. 
Accordingly, when the CAFE Model is assessing how to cost-effectively 
add technology to a vehicle in order to improve the vehicle's fuel 
economy value, the CAFE Model calculates the difference in the fuel 
economy value from an Autonomie modeled vehicle with less technology 
and an Autonomie modeled vehicle with more technology. The relative 
difference between the two Autonomie modeled vehicles' fuel economy 
values is applied to the actual fuel economy value of a vehicle in the 
CAFE Model's baseline fleet.
    Let's return to our Ravine Runner F Series, which has a starting 
fuel economy value of just over 26 mpg and a starting technology key 
``TURBOD; AT10L2; SS12V; ROLL0; AERO5; MR3.'' The equivalent Autonomie 
vehicle model has a starting fuel economy value of just over 30.8 mpg 
and is represented by the technology descriptors Midsize_SUV, Perfo, 
Micro Hybrid, eng38, AUp, 10, MR3, AERO1, ROLL0. In 2028, the CAFE 
Model determines that Generic Motors needs to redesign the Ravine 
Runner F Series to reach Generic Motors' new light truck CAFE standard. 
The Ravine Runner F Series now has lots of new fuel-economy-improving 
technology--it is a parallel strong HEV with a TURBOE engine, an 
integrated 8-speed automatic transmission, 30% improvement in ROLL, 20% 
aerodynamic drag reduction, and 10% lighter glider (i.e., mass 
reduction). Its new technology key is now P2TRBE, ROLL30, AERO20, MR3. 
Table II-5 shows how the incremental fuel economy improvement from the 
Autonomie simulations is applied to the Ravine Runner F Series' 
starting fuel economy value.

           Table II-5--Example Translation From the Autonomie Effectiveness Database to the CAFE Model
----------------------------------------------------------------------------------------------------------------
                                 Starting technology key/                 Ending technology key/
             Model                technology descriptors        MPG       technology descriptors        MPG
----------------------------------------------------------------------------------------------------------------
CAFE Model.....................  TURBOD; AT10L2; SS12V;             26.1  P2TRBE, ROLL30,                   36.3
                                  ROLL0; AERO5; MR3.                       AERO20, MR3.
Autonomie......................  Midsize_SUV, Perfo,                30.8  Midsize_SUV, Perfo,               42.9
                                  Micro Hybrid, eng38,                     Par HEV, eng37, AUp
                                  AUp, 10, MR3, AERO1,                     8, MR3, AERO4, ROLL3.
                                  ROLL0.
----------------------------------------------------------------------------------------------------------------

    Note that the fuel economy values we obtain from the Autonomie 
modeling are based on the city and highway test cycles (i.e., the two-
cycle test) described above. This is because we are statutorily 
required to measure vehicle fuel economy based on the two-cycle 
test.\132\ In 2008, EPA introduced three additional test cycles to 
bring fuel economy ``label'' values from two-cycle testing in line with 
the efficiency values consumers were experiencing in the real world, 
particularly for hybrids. This is known as 5-cycle testing. Generally, 
the revised 5-cycle testing values have proven to be a good 
approximation of what consumers will experience while driving, 
significantly better than the previous two-cycle test values. Although 
the compliance modeling uses two-cycle fuel economy values, we use the 
``on-road'' fuel economy values, which are the ratio of 5-cycle to 2-
cycle testing values (i.e., the CAFE compliance values to the ``label'' 
values) \133\ to calculate the value of fuel savings to the consumer in 
the effects analysis. This is because the 5-cycle test fuel economy 
values better represent fuel savings that consumers will experience 
from real-world driving. For more information about these calculations, 
please see Section 5.3.2 of the CAFE Model Documentation, and our 
discussion of the effects analysis later in this section.
---------------------------------------------------------------------------

    \132\ 49 U.S.C. 32904(c) (EPA ``shall measure fuel economy for 
each model and calculate average fuel economy for a manufacturer 
under testing and calculation procedures prescribed by the 
Administrator. However, except under section 32908 of this title, 
the Administrator shall use the same procedures for passenger 
automobiles the Administrator used for model year 1975 (weighted 55 
percent urban cycle and 45 percent highway cycle), or procedures 
that give comparable results.'').
    \133\ We apply a certain percent difference between the 2-cycle 
test value and 5-cycle test value to represent the gap in compliance 
fuel economy and real-world fuel economy.
---------------------------------------------------------------------------

    In sum, we use Autonomie to generate physics-based full vehicle 
modeling and simulation technology effectiveness estimates. These 
estimates ensure that

[[Page 56172]]

our modeling captures differences in technology effectiveness due to 
(1) vehicle size and performance relative to other vehicles in the 
baseline fleet; (2) other technologies on the vehicle and/or being 
added to the vehicle at the same time; and (3) and how the vehicle is 
driven. This modeling approach also comports with the NAS 2015 
recommendation to use full vehicle modeling supported by application of 
lumped improvements at the sub-model level.\134\ The approach allows 
the isolation of technology effects in the analysis supporting an 
accurate assessment.
---------------------------------------------------------------------------

    \134\ 2015 NAS report, at 292.
---------------------------------------------------------------------------

    In our analysis, ``technology effectiveness values'' are the 
relative difference between the fuel economy value for one Autonomie 
vehicle model driving the two-cycle tests, and a second Autonomie 
vehicle model that uses new technology driving the two-cycle tests. We 
add the difference between two Autonomie-generated fuel economy values 
to a vehicle in the Market Data Input file's CAFE compliance fuel 
economy value. We then calculate the costs and benefits of different 
levels of fuel economy standards using the incremental improvement 
required to bring a baseline vehicle model's fuel economy value to a 
level that contributes to a manufacturer's fleet meeting its CAFE 
standard.
    In the next section, Technology Costs, we describe the process of 
generating costs for the Technology Costs input file.
4. Technology Costs
    We estimate present and future costs for fuel-saving technologies 
based on a vehicle's technology class and engine size. In the 
Technologies Input file, there is a separate tab for each technology 
class that includes unique costs for that class (depending on the 
technology), and a separate tab for each engine size that also contains 
unique engine costs for each engine size. These technology cost 
estimates are based on three main inputs. First, we estimate direct 
manufacturing costs (DMCs), or the component and labor costs of 
producing and assembling a vehicle's physical parts and systems. DMCs 
generally do not include the indirect costs of tools, capital 
equipment, financing costs, engineering, sales, administrative support 
or return on investment. We account for these indirect costs via a 
scalar markup of DMCs, which is termed the RPE. Finally, costs for 
technologies may change over time as industry streamlines design and 
manufacturing processes. We estimate potential cost improvements from 
improvements in the manufacturing process with learning effects (LEs). 
The retail cost of technology in any future year is estimated to be 
equal to the product of the DMC, RPE, and LE. Considering the retail 
cost of equipment, instead of merely DMCs, is important to account for 
the real-world price effects of a technology, as well as market 
realities. Each of these technology cost components is described 
briefly below and in the following individual technology sections, and 
in detail in Chapters 2 and 3 of the Draft TSD.
    DMCs are the component and assembly costs of the physical parts and 
systems that make up a complete vehicle. We estimate DMCs for 
individual technologies in several ways. Broadly, we rely in large part 
on costs estimated by the NHTSA-sponsored 2015 NAS study on the Cost, 
Effectiveness, and Deployment of Fuel Economy Technologies for LDVs and 
other NAS studies on fuel economy technologies; BatPaC, a publicly 
available battery pack modeling software developed and maintained by 
the DOE's ANL, NHTSA-sponsored teardown studies, and our own analysis 
of how much advanced MR technology (i.e., carbon fiber) is available 
for vehicles now and in the future; confidential business information 
(CBI); and off-cycle and AC efficiency costs from the EPA Proposed 
Determination TSD.\135\ While DMCs for fuel-saving technologies reflect 
the best estimates available today, technology cost estimates will 
likely change in the future as technologies are deployed and as 
production is expanded. For emerging technologies, we use the best 
information available at the time of the analysis and will continue to 
update cost assumptions for any future analysis.
---------------------------------------------------------------------------

    \135\ Enviromental Protection Agency. 2016. Proposed 
Determination on the Appropriateness of the Model Year 2022-2025 
Light-Duty Vehicle Greenhouse Gas Emissions Standards under the 
Midterm Evaluation: Technical Support Document. Assessment and 
Standards Division, Office of Transportation and Air Quality. 
Available at: https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100Q3L4.pdf. (Accessed: May 31, 2023).
---------------------------------------------------------------------------

    Our direct costs include materials, labor, and variable energy 
costs required to produce and assemble the vehicle; however, direct 
costs do not include production overhead, corporate overhead, selling 
costs, or dealer costs, which all contribute to the price consumers 
ultimately pay for the vehicle. These components of retail prices are 
illustrated in Table II-6 below.

                   Table II-6--Retail Price Components
------------------------------------------------------------------------
 
------------------------------------------------------------------------
                              Direct Costs
------------------------------------------------------------------------
Manufacturing Cost................  Cost of materials, labor, and
                                     variable energy needed for
                                     production.
------------------------------------------------------------------------
                             Indirect Costs
------------------------------------------------------------------------
                           Production Overhead
    Warranty......................  Cost of providing product warranty.
    Research and Development......  Cost of developing and engineering
                                     the product.
    Depreciation and amortization.  Depreciation and amortization of
                                     manufacturing facilities and
                                     equipment.
    Maintenance, repair,            Cost of maintaining and operating
     operations.                     manufacturing facilities and
                                     equipment.
                           Corporate Overhead
    General and Administrative....  Salaries of nonmanufacturing labor,
                                     operations of corporate offices,
                                     etc.
    Retirement....................  Cost of pensions for
                                     nonmanufacturing labor.
    Health Care...................  Cost of health care for
                                     nonmanufacturing labor.
                              Selling Costs
    Transportation................  Cost of transporting manufactured
                                     goods.
    Marketing.....................  Manufacturer costs of advertising
                                     manufactured goods.
                              Dealer Costs
    Dealer selling expense........  Dealer selling and advertising
                                     expense.
    Dealer profit.................  Net Income to dealers from sales of
                                     new vehicles.

[[Page 56173]]

 
    Net income....................  Net income to manufacturers from
                                     production and sales of new
                                     vehicles.
------------------------------------------------------------------------

    To estimate total consumer costs (i.e., both direct and indirect 
costs), we multiply a technology's DMCs by an indirect cost factor to 
represent the average price for fuel-saving technologies at retail. The 
factor that we use is the RPE, and it is the most commonly used to 
estimate indirect costs of producing a motor vehicle. The RPE markup 
factor is based on an examination of historical financial data 
contained in 10-K reports filed by manufacturers with the Securities 
and Exchange Commission (SEC). It represents the ratio between the 
retail price of motor vehicles and the direct costs of all activities 
that manufacturers engage in.
    For more than three decades, the retail price of motor vehicles has 
been, on average, roughly 50 percent above the direct cost expenditures 
of manufacturers.\136\ This ratio has been remarkably consistent, 
averaging roughly 1.5 with minor variations from year to year over this 
period. At no point has the RPE markup based on 10-K reports exceeded 
1.6 or fallen below 1.4.\137\ During this time frame, the average 
annual increase in real direct costs was 2.5 percent, and the average 
annual increase in real indirect costs was also 2.5 percent. The RPE 
averages 1.5 across the lifetime of technologies of all ages, with a 
lower average in earlier years of a technology's life, and, because of 
LEs on direct costs, a higher average in later years. Many automotive 
industry stakeholders have either endorsed the 1.5 markup,\138\ or have 
estimated alternative RPE values. As seen in Table II-7, all estimates 
range between 1.4 and 2.0, and most are in the 1.4 to 1.7 range.
---------------------------------------------------------------------------

    \136\ Rogozhin, A. et al. 2009. Automobile Industry Retail Price 
Equivalent and Indirect Cost Multipliers. EPA. RTI Project Number 
0211577.002.004. Triangle Park, N.C.; Spinney, B.C. et al. 1999. 
Advanced Air Bag Systems Cost, Weight, and Lead Time analysis 
Summary Report. Contract NO. DTNH22-96-0-12003. Task Orders--001, 
003, and 005. Washington, DC.
    \137\ Based on data from 1972-1997 and 2007. Data were not 
available for intervening years, but results for 2007 seem to 
indicate no significant change in the historical trend.
    \138\ Comment submitted by Chris Nevers, Vice President, Energy 
& Environment, Alliance of Automobile Manufacturers via 
Regulations.gov. Docket ID No. EPA-HQ-OAR-2018-0283-6186, p. 143. 
Available at: https://www.regulations.gov/comment/EPA-HQ-OAR-2018-0283-6186.

            Table II-7--Alternate Estimates of the RPE \139\
------------------------------------------------------------------------
            Author and year                      Value, comments
------------------------------------------------------------------------
Jack Faucett Associates for EPA, 1985..  1.26 initial value, later
                                          corrected to 1.7+ by Sierra
                                          research.
Vyas et al., 2000......................  1.5 for outsourced, 2.0 for
                                          OEM, electric, and hybrid
                                          vehicles.
NRC, 2002..............................  1.4 (corrected to > by Duleep).
McKinsey and Company, 2003.............  1.7 based on European study.
CARB, 2004.............................  1.4 (derived using the JFA
                                          initial 1.26 value, not the
                                          corrected 1.7+ value).
Sierra Research for AAA, 2007..........  2.0 or >, based on Chrysler
                                          data.
Duleep, 2008...........................  1.4, 1.56, 1.7 based on
                                          integration complexity.
NRC, 2011..............................  1.5 for Tier 1 supplier, 2.0
                                          for OEM.
NRC, 2015..............................  1.5 for OEM.
------------------------------------------------------------------------

    An RPE of 1.5 does not imply that manufacturers automatically mark 
up each vehicle by exactly 50 percent. Rather, it means that, over 
time, the competitive marketplace has resulted in pricing structures 
that average out to this relationship across the entire industry. 
Prices for any individual model may be marked up at a higher or lower 
rate depending on market demand. The consumer who buys a popular 
vehicle may, in effect, subsidize the installation of a new technology 
in a less marketable vehicle. But, on average, over time and across the 
vehicle fleet, the retail price paid by consumers has risen by about 
$1.50 for each dollar of direct costs incurred by manufacturers. Based 
on our own evaluation and the widespread use and acceptance of the RPE 
by automotive industry stakeholders, we have determined that the RPE 
provides a reasonable indirect cost markup for use in our analysis. A 
detailed discussion of indirect cost methods and the basis for our use 
of the RPE to reflect these costs, rather than other indirect cost 
markup methods, is available in the Final Regulatory Impact Analysis 
(FRIA) for the 2020 final rule.\140\
---------------------------------------------------------------------------

    \139\ Duleep, K.G. 2008. Analysis of Technology Cost and Retail 
Price. Presentation to Committee on Assessment of Technologies for 
Improving LDV Fuel Economy. January 25, 2008, Detroit, MI.; Jack 
Faucett Associates. 1985. Update of EPA's Motor Vehicle Emission 
Control Equipment Retail Price Equivalent (RPE) Calculation Formula. 
September 4, 1985. Chevy Chase, MD; McKinsey & Company. 2003. 
Preface to the Auto Sector Cases. New Horizons--Multinational 
Company Investment in Developing Economies. San Francisco, CA.; NRC. 
2002. Effectiveness and Impact of Corporate Average Fuel Economy 
Standards. The National Academies Press. Washington, DC; NRC. 2011. 
Assessment of Fuel Economy Technologies for LDVs. The National 
Academies Press. Washington, DC; NRC. 2015. Cost, Effectiveness, and 
Deployment of Fuel Economy Technologies in LDVs. The National 
Academies Press. Washington, DC; Sierra Research, Inc. 2007. Study 
of Industry-Average Mark-Up Factors used to Estimate Changes in 
Retail Price Equivalent (RPE) for Automotive Fuel Economy and 
Emissions Control Systems. Sierra Research Inc. Sacramento, CA; 
Vyas, A. et al. 2000. Comparison of Indirect Cost Multipliers for 
Vehicle Manufacturing. Center for Transportation Research, ANL, 
April. Argonne, Ill.
    \140\ 2020 FRIA, at pp. 354-76. Available at https://www.nhtsa.gov/sites/nhtsa.gov/files/documents/final_safe_fria_web_version_200701.pdf. (Accessed: May 31, 2023).
---------------------------------------------------------------------------

    Finally, manufacturers make improvements to production processes 
over time, which often result in lower costs. ``Cost learning'' 
reflects the effect of experience and volume on the cost of production, 
which generally results in better utilization of resources, leading to 
higher and more efficient production. As manufacturers gain experience 
through production, they refine production techniques, raw material and 
component sources, and assembly methods to maximize efficiency and 
reduce production costs.
    We estimated cost learning by considering methods established by 
T.P. Wright and later expanded upon by J.R. Crawford. Wright, examining 
aircraft production, found that every doubling of cumulative production 
of airplanes resulted in decreasing labor hours at a fixed percentage. 
This fixed percentage is commonly referred to as the progress

[[Page 56174]]

rate or progress ratio, where a lower rate implies faster learning as 
cumulative production increases. J.R. Crawford expanded upon Wright's 
learning curve theory to develop a single unit cost model, which 
estimates the cost of the nth unit produced given the following 
information is known: (1) cost to produce the first unit; (2) 
cumulative production of n units; and (3) the progress ratio.
    Consistent with Wright's learning curve, most technologies in the 
CAFE Model use the basic approach by Wright, where we estimate 
technology cost reductions by applying a fixed percentage to the 
projected cumulative production of a given fuel economy technology in a 
given MY.\141\ We estimate the cost to produce the first unit of any 
given technology by identifying the DMC for a technology in a specific 
MY. As discussed above and in detail below and in Chapter 3 of the 
Draft TSD, our technology DMCs come from studies, teardown reports, 
other publicly available data, and feedback from manufacturers and 
suppliers. Because different studies or cost estimates are based on 
costs in specific MYs, we identify the ``base'' MYs for each technology 
where the learning factor is equal to 1.00. Then, we apply a progress 
ratio to back-calculate the cost of the first unit produced. The 
majority of technologies in the CAFE Model use a progress ratio (i.e., 
the slope of the learning curve, or the rate at which cost reductions 
occur with respect to cumulative production) of approximately 0.89, 
which is derived from average progress ratios researched in studies 
funded and/or identified by NHTSA and EPA.\142\ Figure II-10 shows how 
technologies on the MY 2022 Ravine Runner Type F decrease in cost over 
several years. TURBOD and MR3 are technologies that have existed in 
vehicles for some time, so they show a gradual sloping learning curve 
implying that cost reductions from learning is moderate and eventually 
becomes less steep toward MY2050. Conversely, newer technologies such 
as, AT10L2, SS12V, and AERO5 show an initial steep learning curve where 
cost reduction occurs at a high rate. Lastly, ROLL0 exhibits a mostly 
flat curve implying that this level of rolling resistance technology is 
very mature and does not incur much cost reduction, if at all, from 
learning.
---------------------------------------------------------------------------

    \141\ We use statically projected cumulative volume production 
estimates beause the CAFE Model does not support dynamic projections 
of cumulative volume at this time.
    \142\ Simons, J.F. 2017. Cost and weight added by the Federal 
Motor Vehicle Safety Standards for MY 1968-2012 passenger cars and 
LTVs. Report No. DOT HS 812 354. NHTSA: Washington, DC 30-33; 
Argote, L. et al. 1997. The Acquisition and Depreciation of 
Knowledge in a Manufacturing Organization--Turnover and Plant 
Productivity. Working Paper. Graduate School of Industrial 
Administration, Carnegie Mellon University; Benkard, C.L. 2000. 
Learning and Forgetting--The Dynamics of Aircraft Production. The 
American Economic Review, Vol. 90(4): pp. 1034-54; Epple, D. et al. 
1991. Organizational Learning Curves--A Method for Investigating 
Intra-Plant Transfer of Knowledge Acquired through Learning by 
Doing. Organization Science, Vol. 2(1): pp. 58-70; Epple, D. et al. 
1996. An Empirical Investigation of the Microstructure of Knowledge 
Acquisition and Transfer through Learning by Doing. Operations 
Research, Vol. 44(1): pp. 77-86; Levitt, S. D. et al. 2013. Toward 
an Understanding of Learning by Doing--Evidence from an Automobile 
Assembly Plant. Journal of Political Economy, Vol. 121 (4): pp. 643-
81.
---------------------------------------------------------------------------

BILLING CODE 4910-59-P

[[Page 56175]]

[GRAPHIC] [TIFF OMITTED] TP17AU23.018

BILLING CODE 4910-59-C
    We assign groups of similar technologies or technologies of similar 
complexity learning curves. While the grouped technologies differ in 
operating characteristics and design, we chose to group them based on 
market availability, complexity of technology integration, and 
production volume of the technologies that can be implemented by 
manufacturers and suppliers. In general, we consider most base and 
basic engine and transmission technologies to be mature technologies 
that will not experience any additional improvements in design or 
manufacturing. Other basic engine technologies, like VVL, SGDI, and 
DEAC, do decrease in costs through around MY 2036, because those were 
introduced into the market more recently. All advanced engine 
technologies follow the same general pattern of a gradual reduction in 
costs until MY 2036, when they plateau and remain flat. We expect the 
cost to decrease as production volumes increase, manufacturing 
processes are improved, and economies of scale are achieved. We also 
assigned advanced engine technologies that are based on a singular 
preceding technology to the same learning curve as that preceding 
technology. Similarly, the more advanced transmission technologies 
experience a gradual reduction in costs through MY 2031, when they 
plateau and remain flat. Lastly, we estimate that the learning curves 
for road load technologies, with the exception of the most advanced MR 
level (which decreases at a fairly steep rate through MY 2040, as 
discussed further below and in Chapter 3.4 of the Draft TSD), will 
decrease through MY 2036 and then remain flat.
    We use the same cost learning rates for both LD and HDPUV 
technologies. This approach was used in the HDPUV analysis in the Phase 
2 Heavy-Duty joint rule with EPA,\143\ and we believe that this is an 
appropriate assumption to continue to use for this analysis. While the 
powertrains in HDPUVs do have a higher power output than LD 
powertrains, the designs and technology used will be very similar. 
Although most HDPUV components will have higher operating loads and 
provide different effectiveness values than LD components, the overall 
designs are similar between the technologies. The individual technology 
design and effectiveness differences between LD and HDPUV technologies 
are discussed below and in Chapter 3 of the Draft TSD.
---------------------------------------------------------------------------

    \143\ See MDHD Phase 2 FRIA at 2-56, noting that gasoline 
engines used in Class 2b and Class 3 pickup trucks and vans include 
the engines offered in a manufacturer's light-duty truck 
counterparts, as well as engines specific to the Class 2b and Class 
3 segment, and describing that the the technology definitions are 
based on those described in the LD analysis, but the effectiveness 
values are different.
---------------------------------------------------------------------------

    For technologies that have been in production for many years, like 
some engine and transmission technologies, this approach produces 
reasonable estimates that we can compare against

[[Page 56176]]

other studies and publicly available data. Generating the learning 
curve for battery packs for BEVs in future MYs is significantly more 
complicated, and we discuss how we generated those learning curves in 
Section II.D and in detail in Chapter 3.3 of the Draft TSD. Our battery 
pack learning curves recognize that there are many factors that could 
potentially lower battery pack costs over time outside of the cost 
reductions due to improvements in manufacturing processes due to 
knowledge gained through experience in production.
    Table II-8 shows how some of the technologies on the MY 2022 Ravine 
Runner Type F decrease in cost over several years. Note that these 
costs are specifically applicable to the MedSUVPerf class, and other 
technology classes may have different costs for the same technologies. 
These costs are pulled directly from the Technology Costs Input file, 
meaning that they include the DMC, RPE, and learning.

                    Table II-8--Absolute Costs for Example Ravine Runner Type F Technologies
----------------------------------------------------------------------------------------------------------------
                     Technology (MedSUVPerf)                          CY 2022         CY 2027         CY 2032
----------------------------------------------------------------------------------------------------------------
TURBOD (8C2B)...................................................       $8,924.90       $8,877.31       $8,851.36
AT10L2..........................................................        2,848.19        2,806.64        2,790.92
SS12V...........................................................          215.47          191.01          180.28
AERO5...........................................................           55.30           50.91           48.70
----------------------------------------------------------------------------------------------------------------

5. Technology Incentives
    Similar to the regulations that we are proposing, other government 
actions have the ability to influence the technology manufacturers 
apply to their vehicles. For the purposes of this analysis, we 
incorporate two other government actions into our analysis: state ZEV 
requirements and Federal tax credits.
a. Simulating the Zero Emissions Vehicle Programs
    The California Air Resources Board (CARB) has developed various 
programs to control emissions of criteria pollutants and GHGs from 
vehicles sold in California. CARB does so in accordance with Federal 
CAA; CAA section 209(a) generally preempts states from adopting 
emission control standards for new motor vehicles,\144\ however, 
Congress created an exemption program in CAA section 209(b) that allows 
the State of California to seek a waiver of preemption related to 
adopting or enforcing motor vehicle emissions standards.\145\ EPA must 
grant the waiver unless the Agency makes one of three statutory 
findings.\146\ Under CAA section 177, other States can adopt and 
enforce standards identical to those approved under California's 
Section 209(b) waiver.\147\ States that do so are sometimes referred to 
as section 177 states, in reference to section 177 of the CAA Since 
1990, CARB has included a Zero-Emission Vehicle (ZEV) program as part 
of its package of standards that control smog-causing pollutants and 
GHG emissions from passenger vehicles sold in California,\148\ and 
several states have adopted those ZEV program requirements in 
accordance with CAA section 177.
---------------------------------------------------------------------------

    \144\ 42 U.S.C. 7543(a).
    \145\ 42 U.S.C. 7543(b).
    \146\ See 87 FR 14332 (March 14, 2022). (``The CAA section 
209(b) waiver is limited ``to any State which has adopted standards 
. . . for the control of emissions from new motor vehicles or new 
motor vehicle engines prior to March 30, 1966,'' and California is 
the only State that had standards in place before that date.''). 
NHTSA notes that EPA has not yet granted a waiver of preemption for 
the ACC II program, and NHTSA does not prejudge EPA's 
decisionmaking. Nonetheless, NHTSA believes it is reasonable, for 
reasons discussed in detail below, to consider ZEV sales volumes 
that manufacturers will produce in response to ACC II as part of our 
consideration of actions that occur in the absence of fuel economy 
standards.
    \147\ 42 U.S.C. 7507.
    \148\ CARB. Zero-Emission Vehicle Program. Available at: https://ww2.arb.ca.gov/our-work/programs/zero-emission-vehicle-program/about. (Accessed: May 31, 2023).
---------------------------------------------------------------------------

    There are currently three operative ZEV regulations: ACC I (LD ZEV 
requirements through MY 2025),\149\ ACC II (LD ZEV requirements from 
MYs 2026-2035),\150\ and Advanced Clean Trucks (ACT) (trucks in Classes 
2b through 8, for MYs 2024-2035).\151\ We include the main provisions 
of the ACC I, II, and ACT programs in the CAFE Model's analysis of 
compliance pathways. We are confident that manufacturers will comply 
with the ZEV programs because they have complied with state ZEV 
programs in the past and they have made announcements of new ZEVs 
demonstrating an intent to comply with the requirements going forward. 
NHTSA models manufacturers' compliance with these programs because 
accounting for technology improvements that manufacturers would make 
even in the absence of CAFE standards allows NHTSA to gain a more 
accurate understanding of the effects of the proposed rulemaking.
---------------------------------------------------------------------------

    \149\ 13 CCR 1962.2.
    \150\ 13 CCR 1962.4.
    \151\ CARB. Final Regulation Order: Advanced Clean Trucks 
Regulation. Available at: https://ww2.arb.ca.gov/sites/default/files/barcu/regact/2019/act2019/fro2.pdf. (Accessed: May 31, 2023).
---------------------------------------------------------------------------

    This is the third analysis where we have modeled compliance with 
the ACC program (and now the ACC II and ACT program) requirements in 
the CAFE Model. While we have in the past received feedback agreeing or 
disagreeing with the modeling inclusion of the ZEV programs at all, the 
only past substantive comments on the ZEV program modeling methodology 
have been requesting the inclusion of more states that have recently 
signed on to adopt California's standards in our analysis. As noted 
below, the inclusion or exclusion of states in the analysis depends on 
which states have signed on to the programs at the time of our 
analysis. While we are aware of legal challenges to some states' 
adoption of the ZEV programs, it is beyond the scope of this rulemaking 
to evaluate the likelihood of success of those challenges. For purposes 
of our analysis, what is important is predicting, using a reasonable 
assessment, how the fleet will evolve in the future. The following 
discussion provides updates to our modeling methodology for the ZEV 
programs in the analysis.
    The ACC I, II, and ACT programs require that increasing levels of 
manufacturers' sales in California and section 177 states in each MY be 
ZEVs, specifically BEVs, PHEVs, FCEVs.\152\ BEVs, PHEVs, and FCEVs each 
contribute a different ``value'' towards a manufacturer's annual ZEV 
requirement, which is a product of the manufacturer's production volume 
sold in a ZEV state, multiplied by a ``percentage requirement.'' The 
percentage requirements increase in

[[Page 56177]]

each year so that a greater portion of a manufacturer's fleet sold in 
ZEV states in a particular MY must be ZEVs. For example, a manufacturer 
selling 100,000 vehicles in California and 10,000 vehicles in 
Connecticut (both states that have ZEV programs) in MY 2028 must ensure 
that 51,000 of the California vehicles and 5,100 of the Connecticut 
vehicles are ZEVs.
---------------------------------------------------------------------------

    \152\ CARB. Final Regulation Order. Available at: https://ww2.arb.ca.gov/sites/default/files/barcu/regact/2022/accii/acciifro1962.2.pdf. (Accessed: May 31, 2023).
---------------------------------------------------------------------------

    At the time of our analysis, sixteen states in addition to 
California either formally signed on to the ACC II standards or were in 
the process of adopting them.\153\ Although a few states are adopting 
these requirements in future MYs, we include every state that 
officially committed to adopting the requirements by the start of 
December 2022 (regardless of MY start date),\154\ which was the time of 
analysis, as being part of the unified ACC II states group for ease of 
modeling. We consider all ACC II states together and do not model 
specific states' years of joining, as states that have recently joined 
the program have done so within a relatively short span of MYs and 
represent only a very small percentage of new LDV sales.\155\ 
Similarly, nine states including California have formally adopted the 
ACT standards at the time of analysis.\156\ As other states are 
currently considering adopting ACT standards, we plan to update this 
number in the final rule analysis if those states formally adopt it.
---------------------------------------------------------------------------

    \153\ California, Colorado, Connecticut, Delaware, Maine, 
Maryland, Massachusetts, Minnesota, Nevada, New York, New Jersey, 
New Mexico, Oregon, Rhode Island, Vermont, Virginia, and Washington. 
See California Air Resource Board. States that have Adopted 
California's Vehicle Standards under Section 1777 of the Federal 
Clean Air Act. Available at: https://ww2.arb.ca.gov/sites/default/files/2022-05/%C2%A7177_states_05132022_NADA_sales_r2_ac.pdf. 
(Accessed: May 31, 2023).
    \154\ See States that have Adopted California's Vehicle 
Standards under Section 177 of the Federal Clean Air Act, May 13, 
2022, https://ww2.arb.ca.gov/sites/default/files/2022-05/%C2%A7177_states_05132022_NADA_sales_r2_ac.pdf; https://governor.nc.gov/eo-faq/open. We consider these to be states that 
have passed laws or have progressed sufficiently in the process of 
adopting requirements. States indicating interest or that still need 
to vote on adopting these provisions are not counted in this group.
    \155\ Id.
    \156\ California, Connecticut, Massachusetts, New Jersey, New 
York, North Carolina, Oregon, Vermont and Washington. We include 
Connecticut as their House passed the legislation instructing their 
Department of Energy and Environmental Protection to adopt ACT. See 
https://www.electrictrucksnow.com/states; https://vermontbiz.com/news/2022/november/24/vermont-adopts-rules-cleaner-cars-and-trucks; 
https://deq.nc.gov/about/divisions/air-quality/motor-vehicles-and-air-quality/advanced-clean-trucks; https://www.cga.ct.gov/2022/fc/pdf/2022HB-05039-R000465-FC.pdf.
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    It is important to note that not all section 177 states have 
adopted the ACC II or ACT program components.\157\ Furthermore, more 
states have formally adopted the ACC II program than the ACT program, 
so the discussion in the following sections will call states that have 
opted in ``ACC II states'' or ``ACT states.'' Separately, many states 
signed a memorandum of understanding (MOU) in 2020 to indicate their 
intent to work collaboratively towards a goal of turning 100% of MD and 
HD vehicles into ZEVs in the future.\158\ For the purposes of CAFE 
analysis, we include only those states that have formally adopted the 
ACT in our modeling as ``ACT states''. States that have signed the MOU 
but not formally adopted the ACT program are referred to as ``MOU 
states'' and are not included in CAFE modeling. When the term ``ZEV 
programs'' is used hereafter, it refers to both the ACC II and ACT 
programs.
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    \157\ At the time of writing, Pennsylvania has adopted the Low-
emission Vehicle standards, but not the ZEV (now ACC II) portion. 
See Pennsylvania Department of Environmental Protection. Clean 
Vehicle Program. Available at: https://www.dep.pa.gov/Business/Air/BAQ/Automobiles/Pages/CleanVehicleProgram.aspx. (Accessed: May 31, 
2023).
    \158\ Northeast States for Coordinated Air Use Management 
(NESCAUM). Multi-State Medium and Heavy-Duty Zero Emission Vehicle 
Memorandum of Understanding. July 13, 2020. Available at: https://www.nescaum.org/documents/mhdv-zev-mou-20220329.pdf/. (Accessed: May 
31, 2023).
---------------------------------------------------------------------------

    Incorporating these programs into the model includes converting 
vehicles that have been identified as potential ZEV candidates into 
BEVs at the vehicle's ZEV application year so that a manufacturer's 
fleet meets its required ZEV credit requirements. We focused on BEVs as 
ZEV conversions, rather than PHEVs or FCEVs, because, as for 2026-2035, 
manufacturers cannot earn more than 20% of their ZEV credits through 
PHEV sales. Similarly, PHEVs receive a smaller number of credits than 
BEVs and FCEVs since their powertrain still incorporates use of an ICE. 
We determined that including PHEVs in the ZEV modeling would have 
introduced unnecessary complication to the modeling and would have 
provided manufacturers little benefit in the modeled program. In 
addition, although FCEVs can earn the same number of credits as BEVs, 
we chose to focus on BEV technology pathways since FCEVs are generally 
less cost-effective than BEVs and most manufacturers have not been 
producing them at high volumes.
    Total credits are calculated by multiplying the credit value each 
ZEV receives by the vehicle's volume. In the ACC II program, from 2026 
onwards, each full ZEV earns one credit value per vehicle, while 
partial ZEVs (PHEVs) earn credits based on their AER. In the context of 
this section, ``full ZEVs'' refers to BEVs and FCEVs, as a PHEV 
generally receives a smaller number of credits than other ZEVs, as 
discussed above. Credit targets in the ACT program (referred to as 
deficits) are calculated by multiplying sales by percentage requirement 
and weight class multiplier. Each HDPUV full ZEV in the 2b/3 class 
earns 0.8 credits and each NZEV (called PHEVs in the CAFE Model) earns 
0.75 credits.\159\
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    \159\ CARB. Final Regulation Order: Advanced Clean Trucks 
Regulation. Available at: https://www.cga.ct.gov/2022/fc/pdf/2022HB-05039-R000465-FC.pdf. (Accessed: May 31, 2023).
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    The CAFE Model is designed to present outcomes at a national scale, 
so the ZEV programs analysis considers the states as a group as opposed 
to estimating each state's ZEV credit requirements individually. To 
capture the appropriate volumes subject to the ACC II and ACT 
requirements, we calculated each manufacturer's total market share in 
ACC II or ACT states. We used Polk's National Vehicle Population 
Profile (NVPP) from January 2022 to calculate these percentages.\160\ 
These data include vehicle characteristics such as powertrain, fuel 
type, manufacturer, nameplate, and trim level, as well as the state in 
which each vehicle is sold. At the time of the data snapshot, MY 2021 
data from the NVPP contained the most current estimate of new vehicle 
market shares for most manufacturers, and best represented the 
registered vehicle population on January 1, 2022. We assumed that new 
registrations data best approximate new sales given the data options. 
For MY 2021 vehicles in the latest NVPP, the ACC II State group makes 
up approximately 38% of the total LD sales in the United States. The 
ACT state groups comprise approximately 19% of the new Class 2b and 3 
vehicle market in the U.S.\161\ We based the volumes used for the ZEV 
credit target calculation on each manufacturer's future assumed market 
share in ACC II and ACT states. We made this assumption after examining 
three past years of market share data and determining that the 
geographic

[[Page 56178]]

distribution of manufacturers' market shares remained fairly constant. 
We welcome comment on the assumptions described in this paragraph.
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    \160\ National Vehicle Population Profile (NVPP). 2022. Includes 
content supplied by IHS Markit. Copyright R.L. Polk & Co., 2022. All 
rights reserved. Available at: https://repository.duke.edu/catalog/caad9781-5438-4d65-b908-bf7d97a80b3a. (Accessed: May 31, 2023).
    \161\ We consulted with Polk and determined that their NVPP data 
set that included vehicles in the 2b/3 weight class provided the 
most fulsome dataset at the time of analysis, recognizing that the 
2b/3 weight class includes both 2b/3 HD pickups and vans and other 
classes within 2b/3 segment. While we determined that this dataset 
was the best option for the analysis, it does not contain all Class 
3 pickups and vans sold in the United States.
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    We calculated total credits required for ACC II and ACT compliance 
by multiplying the percentages from each program's ZEV requirement 
schedule by the ACC II or ACT state volumes.\162\ For the first set of 
ACC requirements covering 2022 (the first modeled year in our analysis) 
through 2025, the percentage requirements start at 14.5% and ramp up in 
increments to 22 percent by 2025.\163\ For ACC II, the percentage 
requirements start at 35% in MY 2026 and ramp up to 100% in MY 2035 and 
subsequent years.\164\ For ACT Class 2b-3 Group vehicles (equivalent to 
HDPUVs in our analysis), the percentage requirements start at 5% in MY 
2024 and increase to 55% in MYs 2035 and beyond.\165\ We then multiply 
the resulting national sales volume predictions by manufacturer by each 
manufacturer's total market share in the ACC II or ACT states to 
capture the appropriate volumes in the ZEV credits calculation. 
Required credits by manufacturer, per year, are determined within the 
CAFE Model by multiplying the ACC II state volumes by CARB's ZEV credit 
percentage requirement for each program respectively.
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    \162\ Note that the ACT credit target calculation differs 
slightly from the ACC II calculation because it includes a vehicle 
class-specific weight modifier.
    \163\ 13 CCR 1962.2(b).
    \164\ 13 CCR 1962.4(c)(1)(B).
    \165\ 13 CCR 1963.1(b).
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    To ensure that the ACC II and ACT credit requirements are met in 
the baseline in each modeling scenario, we add ZEV candidate vehicles 
to the baseline. We flag ZEV candidates in the `vehicles' worksheet in 
the Market Data Input File, which is described above and in detail in 
Draft TSD Chapter 2.2. Although we identify the ZEV candidates in the 
Market Data Input File, the actual conversion from non-ZEV to ZEV 
vehicles occurs within the CAFE Model. The CAFE Model converts a 
vehicle to a ZEV during the specified ZEV application year.
    We flag ZEV candidates in two ways: using reference vehicles with 
ICE powertrains or using PHEVs already in the existing fleet. When 
using ICE powertrains as reference vehicles, we create a duplicate row 
(which we refer to as the ZEV candidate row) in the Market Data Input 
File's Vehicles tab for the ZEV version of the original vehicle, 
designated with a unique vehicle code. The ZEV candidate row specifies 
the relevant electrification technology level of the ZEV candidate 
vehicle (e.g., BEV1, BEV2, and so on), the year that the 
electrification technology is applied,\166\ and zeroes out the 
candidate vehicle's sales volume. We identify all ICE vehicles with 
varying levels of technology up to and including strong hybrid electric 
vehicles (SHEVs) with rows that have 100 sales or more as ZEV 
candidates. The CAFE Model moves the sales volume from the reference 
vehicle row to the ZEV candidate row on an as-needed basis, considering 
the MY's ZEV credit requirements. When using existing PHEVs within the 
fleet as a starting point for identifying ZEV candidates, we base our 
determination of ZEV application years for each model based on 
expectations of manufacturers' future EV offerings. The entire sales 
volume for that PHEV model row is converted to BEV on the application 
year. This approach allows for only the needed additional sales volumes 
to flip to ZEVs, based on the ACC II and ACT targets, and keeps us from 
overestimating ZEVs in future years.
---------------------------------------------------------------------------

    \166\ The model turns all ZEV candidates into BEVs in 2023, so 
sales volumes can be shifted from the reference vehicle row to the 
ZEV candidate row as necessary.
---------------------------------------------------------------------------

    We identify LD ZEV candidates by duplicating every row with 100 or 
more sales that is not a PHEV, BEV, or FCEV. We refer to the original 
rows as `reference vehicles.' Although PHEVs are all ZEV candidates, we 
do not duplicate those rows as we focus the CAFE Model's simulation of 
the ACC II and ACT programs on BEVs. However, any PHEVs already in the 
analysis fleet or made by the model will still receive the appropriate 
ZEV credits. While flagging the ZEV candidates, we identified each one 
as a BEV1, BEV2, BEV3, and BEV4 (BEV technology types based on range), 
based partly on their price, market segment, and vehicle features. For 
instance, we assumed luxury cars would have longer ranges than economy 
cars. We also assigned AWD/4WD variants of vehicles shorter BEV ranges 
when appropriate. See Draft TSD Chapter 3.3 for more detailed 
information on electrification options for this analysis. The CAFE 
Model assigns credit values per vehicle depending on whether the 
vehicle is a ZEV in a MY prior to 2026 or after, due to the change in 
value after the update of the standards from ACC II.
    We follow a similar process in assigning HDPUV ZEV candidates as in 
assigning LD ZEV candidates. We duplicate every van row with 100 or 
more sales and duplicate every pickup truck row with 100 or more sales 
provided the vehicle model has a WF less than 7,500 and a diesel- or 
gasoline-based range lower than 500 miles based on their rated fuel 
economy and fuel tank size. This is consistent with our treatment of 
HDPUVs in the CAFE technology pathways, which is discussed below in 
Section II.D and in Draft TSD Chapter 3. Note that the model can still 
apply PHEV technology to HDPUVs. When identifying ZEV candidates, we 
assign each candidate as either a BEV1 or a BEV2 based on their price, 
market segment, and other vehicle attributes.
    The CAFE Model brings manufacturers into compliance with ACC II and 
ACT first in the baseline, solving for the technology compliance 
pathway used to meet increasing ZEV standards.
    We did not include two provisions of the ZEV regulations in our 
modeling. First, while the ACC II Program includes compliance options 
for providing reduced-price ZEVs to community mobility programs and for 
selling used ZEVs (known as ``environmental justice vehicle values''), 
these are focused on a more local level than we could reasonably 
represent in the CAFE Model. The data for this part of the program are 
also not available from real world application. Second, CARB allows for 
some banking of ZEV credits and credit pooling.\167\ We did not assume 
compliance with ZEV requirements through banking of credits when 
simulating the program in the CAFE Model and focus instead on 
simulating manufacturer's compliance fully through the production of 
new ZEVs. In past rules, we assumed 80% compliance through vehicle 
requirements and the remaining 20% with banked credits.\168\ Due to the 
complicated nature of accounting for the entire credit program, and 
after conversations with CARB, we have decided not to incorporate 
banked credits into the ZEV modeling at this time. Based on guidance 
from CARB and assessment of CARB's responses to manufacturer comments, 
we expect impacts of banked credit provisions on overall volumes to be 
small.\169\
---------------------------------------------------------------------------

    \167\ CARB. Final Regulation Order: Section 1962.4, Title 13, 
California Code of Regulations. Available at: https://ww2.arb.ca.gov/sites/default/files/barcu/regact/2022/accii/acciifro1962.2.pdf. (Acessed: May 31, 2023).
    \168\ CAFE TSD 2024-2026. Pg. 129.
    \169\ CARB. Final Statement of Resons for Rulemaking, Including 
Summary of Comments and Agency Response. Appendix C: Summary of 
Comments to ZEV Regulation and Agency Response. Available at: 
https://ww2.arb.ca.gov/sites/default/files/barcu/regact/2022/accii/fsorappc.pdf. (Accessed: May 31, 2023).
---------------------------------------------------------------------------

    Draft TSD Chapter 2.3 includes more information about the process 
we use to

[[Page 56179]]

simulate ACC II and ACT program compliance in this analysis.
b. IRA Tax Credits
    The IRA included several new and expanded tax credits intended to 
encourage the adoption of clean vehicles.\170\ NHTSA models two of the 
IRA provisions in this analysis. The first is the Advanced 
Manufacturing Production Tax Credit (AMPC). This provision provides a 
$35 per kWh tax credit for manufacturers of battery cells and an 
additional $10 per kWh for manufacturers of battery modules (all 
applicable to manufacture in the United States).\171\ The second 
provision modeled is the Clean Vehicle Tax Credit (CVC),\172\ which 
provides up to $7,500 toward the purchase of clean vehicles with 
critical minerals and battery components manufactured in North 
America.\173\ The credits are currently in effect and are scheduled to 
sunset by 2032.\174\ Since the CAFE Model forecasts by model years, and 
MYs typically are released in the preceding CYs, NHTSA applies the 
credits to MYs 2024-2033 in the analysis for both LDVs and HDPUVs.
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    \170\ Public Law No: 117-169.
    \171\ 26 U.S.C. 45X. If a manufacturer produces a battery module 
without battery cells, they are eligible to claim up to $45 per kWh 
for the battery module. Two other provisions of the AMPC are not 
modeled at this time; (i) a credit equal to 10 percent of the 
manufacturing cost of electrode active materials, (ii) a credit 
equal to 10 percent of the manufacturing cost of critical minerals 
for battery production. We are not modeling these credits directly 
because of how we estimate battery costs and to avoid the potential 
to double count the tax credits if they are included into other 
analyses that feed into our inputs.
    \172\ 26 U.S.C 30D.
    \173\ There are vehicle price and consumer income limitations on 
the CVC, as well. See Congressional Research Service. 2022. Tax 
Provisions in the Inflation Reduction Act of 2022 (H.R. 5376). 
Available at: https://crsreports.congress.gov/product/pdf/R/R47202/6. (Accessed: May 31, 2023).
    \174\ The AMPC has a phase-out beginning in CY 2030.
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    Interactions between producers and consumers in the marketplace 
tend to ensure that subsidies like the AMPC and the CVC, regardless of 
whether they are initially paid to producers or consumers, are 
ultimately shared between the two groups. For this analysis, the agency 
assumes that manufacturers and consumers will each capture half of the 
dollar value of the AMPC and CVC. The agency assumes that 
manufacturers' shares of both credits will offset part of the cost to 
supply models that are eligible for the credits--PHEVs, BEVs, and FCVs. 
The subsidies reduce the costs of eligible vehicles and increase their 
attractiveness to buyers (however, in the LD fleet, the tax credits do 
not alter the penetration rate of BEVs in the regulatory 
alternatives).\175\ Because the AMPC credit scales with battery 
capacity, NHTSA staff determined average battery energy capacity by 
powertrain (e.g., PHEV, BEV, FCV) for passenger cars, light trucks, and 
HDPUVs based on ANL simulation outputs. For a more detailed discussion 
of these assumptions, see Draft TSD Chapter 2.3.2.
---------------------------------------------------------------------------

    \175\ In Table 9-4 of the PRIA, both the reference case (labeled 
``RC'') and the no tax credit case (``No EV tax credits'') show a 
32.3% penetration rate for BEVs in the baseline and preferred 
alternative.
---------------------------------------------------------------------------

    The CAFE Model's approach to analyzing the effects of the CVC 
includes another restriction. The CAFE Model accounts for the MSRP 
restrictions of the CVC by assuming that it cannot be applied to cars 
with an MSRP above $55,000 or other vehicles with an MSRP above 
$80,000, since these are ineligible for the incentive. NHTSA recognizes 
that manufacturers may be unable to comply immediately with the CVC's 
domestic component and critical mineral sourcing requirements, and that 
domestic production may ramp-up over the coming years. To reflect this 
ramp-up, the model phases-in the tax credit. See Chapter 2.5.2 of the 
Draft TSD for details.
    NHTSA is unable to explicitly represent all of the requirements of 
the CVC. For example, NHTSA cannot capture the income restrictions of 
the CVC in its analysis because the CAFE Model does not account for 
purchasers' income. We do not have reliable data on the income levels 
of consumers purchasing specific models. However, the agency's 
procedure for modeling MSRP restrictions partially captures the CVC 
income thresholds indirectly, insofar as high-income buyers are more 
likely to purchase luxury vehicles that exceed the CVC's MSRP caps.
    Nor does NHTSA's analysis explicitly represent the tax credits' 
accompanying restrictions on the location of final assembly and battery 
production or the origin of critical minerals. While it is unlikely 
that all PHEVs, BEVs and FCEVs sold in the United States at any point 
will meet both the critical mineral and battery component requirements, 
we do not have a reliable method or source to estimate where production 
is likely to occur during future MYs, particularly as manufacturers 
respond to the provisions of the IRA.\176\ Instead, we make the 
simplifying assumption for modeling purposes that all PHEVs, BEVs, and 
FCEVs produced and sold during the time frame that tax credits are 
offered will be eligible for those credits subject to the MSRP 
restrictions discussed above.
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    \176\ Note that the labor component of this analysis makes 
certain assumptions about the location of vehicle production. 
However, we do not make assumptions about how our standards will 
alter the origination of components and vehicles. Instead, we assume 
the porportion of hours spent in the United States to produce a 
component or assemble a vehicle remains constant, but the quantity 
of components and vehicles assembled will alter.
---------------------------------------------------------------------------

    To account for these limitations, we assume that the average credit 
value for the CVC across all PHEV, BEV, and FCEV sales in a given year 
will never reach its full $7,500 value for all vehicles, and instead 
assume a maximum average credit value of $5,000. We believe this 
assumption is also supported by the fact that some manufacturers may 
have optimized their supply chains and relocating component production 
to the United States could increase their costs of production, the 
price to the consumer, or both; and the CVC is a non-refundable tax 
credit, which means if the credit is claimed by the consumer, their tax 
liability must be at least $7,500 for the credit to reach its full 
value.
    We seek comment on our methodology for modeling the CVC and AMPC. 
The agency has also included several sensitivity cases testing 
different passthrough amounts and maximum credit values. If commenters 
believe the agency should be modeling additional components of either 
of the tax credits, the agency requests commenters identify both 
potential data sources and methodologies.
    There are several other provisions of the IRA related to clean 
vehicles that are excluded from the analysis. The Previously-owned 
Clean Vehicle credit provides a tax credit for the first resale of a 
clean vehicle by a qualified dealership.\177\ The agency excluded this 
tax credit because we do not track resale prices in the model, nor do 
we have a method of distinguishing between dealership and person-to-
person sales. Furthermore, this credit is only relevant to our analysis 
to the extent it may reduce scrappage rates of eligible vehicles, which 
is outside the capabilities of the model to forecast at this time.
---------------------------------------------------------------------------

    \177\ 26 U.S.C. 25E.
---------------------------------------------------------------------------

    The Commercial Clean Vehicle credit (Commercial Credit) provides 
commercial entities an alternative to the CVC.\178\ The value of the 
Commercial Credit for vehicles covered by this proposal is the cost 
differential between a qualified vehicle and a comparable non-qualified 
vehicle but is capped at $7,500. The Commercial Credit has

[[Page 56180]]

none of the origination and MSRP requirements of the CVC. At the time 
NHTSA was developing its approach to modeling the IRA tax credits and 
coordinating with EPA, the Treasury Department had yet to release its 
guidance on the Commercial Credit and NHTSA was uncertain if vehicles 
leased to consumers would qualify for the credit or how the incremental 
value of commercial clean vehicles would be calculated. As such, NHTSA 
felt that if leased vehicles were ineligible for the Commercial Credit 
or that the incremental approach could lead to a significant amount of 
vehicles receiving less than the maximum credit, that the value of the 
Commercial Credit would be subsumed by our approach to modeling the CVC 
given we allow all vehicles to qualify for the CVC.
---------------------------------------------------------------------------

    \178\ 26 U.S.C. 45W.
---------------------------------------------------------------------------

    Since then, the Treasury Department has clarified that leased 
vehicles qualify for the Commercial Credit and that the credit will be 
calculated based off of the DOE's Incremental Purchase Cost Methodology 
and Results for Clean Vehicles report for at least CY 2023 rather than 
having the taxpayer estimate the actual cost differential.\179\ To the 
extent that our modeling of the CVC misses vehicles that may qualify 
for a higher credit through the Commercial Credit, our decision to not 
model the Commercial Credit may understate the impacts of the IRA.
---------------------------------------------------------------------------

    \179\ See responses to Q2-Q4 of Internal Revenue Service Fact 
Sheet Topic G-Frequently Asked Questions About Qualified Commercial 
Clean Vehicles Credits. Avaliable at: https://www.irs.gov/newsroom/topic-g-frequently-asked-questions-about-qualified-commercial-clean-vehicles-credit. (Accessed: May 31, 2023).
---------------------------------------------------------------------------

    Given these updates, EPA modified their approach to modeling the 
IRA tax credits prior to finalizing their Multi-Pollutant Emissions 
Standards for Model Years 2027 and Later Light-Duty and Medium-Duty 
Vehicles proposal.\180\ EPA elected to model the CVC and Commercial 
Credit jointly, which resulted in a quicker phase-in schedule with a 
higher maximum average credit value than that used in NHTSA's analysis.
---------------------------------------------------------------------------

    \180\ See U.S. EPA. Multi-Pollutant Emissions Standards for 
Model Years 2027 and Later Light-Duty and Medium-Duty Vehicles Draft 
Regulatory Impact Analysis., EPA-420-D-23-003 (April 2023), Chapter 
2.6.8 and 2.5.2.1.4. Federal Register, Vol. 88, No. 87, Friday, May 
5, 2023.
---------------------------------------------------------------------------

    NHTSA is considering incorporating EPA's revised approach for 
modeling the CVC and Commercial Credit jointly for the final rule to 
account for the guidance issued by the Treasury Department. Under this 
approach, NHTSA could retain the same basic mechanisms employed to 
model the CVC but would modify the phase-in and maximum average credit 
to account for the possibility that the Commercial Credit is available 
and offers a higher tax benefit than the CVC. NHTSA seeks comment on 
whether it should adopt this approach, and, if so, specifically 
requests commenters help identify what would be an appropriate maximum 
average credit, phase-in schedule, and elasticity share between 
producers and consumers for this approach. EPA and NHTSA will continue 
to monitor developments with the IRA tax credits and consult with each 
other on how best to implement the credits for the analyses supporting 
their respective final rules.
    Finally, the Qualifying Advanced Energy Project credit (48C) 
provides manufacturers an amount equal to 30 percent of the qualified 
investment, including building or retooling plants for BEVs, PHEVs, or 
FCEVs.\181\ The agency excluded this tax credit for several reasons. 
The credit requires Treasury's pre-approval and the total amount of 
credits awarded under this provision may not exceed $10 billion.\182\ 
Furthermore, the AMPC cannot be claimed for any battery cell or module 
produced from a project that claimed a Qualifying Advanced Energy 
Project credit. For the sake of simplicity, we assume that 
manufacturers will chose the AMPC over the Qualified Advanced Energy 
Project credit. We also do not model other Federal programs that 
incentivize the production or purchase of clean vehicles and their 
infrastructure, such as the IRA Sec.  50142 Advanced Technology Vehicle 
Manufacturing Loan Program, IRA Sec.  50143 Domestic Manufacturing 
Conversion Grants, IRA Sec.  70002 USPS Clean Fleets, or IRA Sec.  
13404 Alternative Fuel Vehicle Refueling Property Credit. These credits 
and grants incentivize clean vehicles through avenues the CAFE Model is 
currently unable to consider as they typically affect a smaller subset 
of the vehicle market and may influence purchasing decisions through 
means other than price, e.g., through expanded charging networks.
---------------------------------------------------------------------------

    \181\ 26 U.S.C. 48C.
    \182\ Public Law 117-169, section 13502.
---------------------------------------------------------------------------

    We do not model individual state tax credit or rebate programs. 
Unlike ZEV requirements which are uniform across states that adopt 
them, state clean vehicle tax credits and rebates vary from 
jurisdiction to jurisdiction and are subject to more uncertainty than 
their Federal counterparts.\183\ Tracking sales by jurisdiction and 
modeling each program's individual compliance program would require 
significant revisions to the CAFE Model and likely provide minimal 
changes in the net outputs of the analysis.
---------------------------------------------------------------------------

    \183\ States have additional mechanisms to amend or remove tax 
incentives or rebates. Sometimes, even after these programs are 
enacted, uncertainty persists, see e.g. Farah, N. 2023. The Untimely 
Death of America's `Most Equitable' EV Rebate. Last Revised: 01/30/
2023. Available at: https://www.eenews.net/articles/the-untimely-death-of-americas-most-equitable-ev-rebate/. (Accessed: May 31, 
2023)
---------------------------------------------------------------------------

    We seek comment on our decision to exclude these credits. Excluding 
these credits may overstate the projected cost to consumers of certain 
vehicles. If commenters feel that we should include any of these 
credits in the final rule, the agency requests commenters address the 
limitations noted above and provide data sources to assist with 
modeling the credit.
6. Technology Applicability Equations and Rules
    How does the CAFE Model decide how to apply technology to the 
baseline fleet of vehicles? We described above that the CAFE Model 
projects cost-effective ways that vehicle manufacturers could comply 
with CAFE standards, subject to limits that ensure that the model 
reasonably replicates manufacturer's decisions in the real-world. This 
section describes the equations the CAFE Model uses to determine how to 
apply technology to vehicles, including whether technologies are cost-
effective, and why we believe the CAFE Model's calculation of potential 
compliance pathways reasonably represents manufacturers' decision-
making. This section also gives a high-level overview of real-world 
limitations that vehicle manufacturers face when designing and 
manufacturing vehicles, and how we include those in the technology 
inputs and assumptions in the analysis.
    The CAFE Model begins by looking at a manufacturer's fleet in a 
given MY and determining whether the fleet meets its CAFE standard. If 
the fleet does not meet its standard, the model begins the process of 
applying technology to vehicles. We described above how vehicle 
manufacturers use the same or similar engines, transmissions, and 
platforms across multiple vehicle models, and we track vehicle models 
that share technology by assigning Engine, Transmission, and Platform 
Codes to vehicles in the analysis fleet. As an example, the Ford 10R80 
10-speed transmission is currently used in the following Ford Motor 
Company vehicles: 2017-present Ford F-150, 2018-present Ford Mustang, 
2018-present Ford Expedition/Lincoln Navigator, 2019-present Ford 
Ranger,

[[Page 56181]]

2020-present Ford Explorer/Lincoln Aviator, and the 2020-present Ford 
Transit.\184\ The CAFE Model first determines whether any technology 
should be ``inherited'' from an engine, transmission, or platform that 
currently uses the technology to a vehicle that is due for a refresh or 
redesign. Using the Ford 10R80 10-speed transmission analysis as 
applied to the CAFE Model, the above models would be linked using the 
same Transmission Code. Even though the vehicles might be eligible for 
technology applications in different years because each vehicle model 
is on a different refresh or redesign cycle, each vehicle could 
potentially inherit the 10R80 10-speed transmission. The model then 
again evaluates whether the manufacturer's fleet complies with its CAFE 
standard. If it does not, the model begins the process of evaluating 
what from our universe of technologies could be applied to the 
manufacturer's vehicles.
---------------------------------------------------------------------------

    \184\ DOE. 2013. Light-Duty Vehicles Technical Requirements and 
Gaps for Lightweight and Propulsion Materials. Final Report. 
Available at: https://www.energy.gov/eere/vehicles/articles/workshop-reportlight-duty-vehicles-technical-requirements-and-gaps. 
(Accessed: May 31, 2023).
---------------------------------------------------------------------------

    The CAFE Model applies the most cost-effective technology out of 
all technology options that could potentially be applied. To determine 
whether a particular technology is cost-effective, the model will 
calculate the ``effective cost'' of multiple technology options and 
choose the option that results in the lowest ``effective cost.'' The 
``effective cost'' calculation is actually multiple calculations, but 
we only describe the highest levels of that logic here; interested 
readers can consult the CAFE Model Documentation for additional 
information on the calculation of effective cost. Equation II-6 shows 
the CAFE Model's effective cost calculation for this analysis.
[GRAPHIC] [TIFF OMITTED] TP17AU23.019

Where:

TechCostTotal: the total cost of a candidate technology evaluated on 
a group of selected vehicles;
TaxCreditsTotal: the cumulative value of additional vehicle and 
battery tax credits (or, Federal Incentives) resulting from 
application of a candidate technology evaluated on a group of 
selected vehicles;
FuelSavingsTotal: the value of the reduction in fuel consumption 
(or, fuel savings) resulting from application of a candidate 
technology evaluated on a group of selected vehicles;
[Delta]Fines: the change in manufacturer's fines in the analysis 
year if the CAFE compliance program is being evaluated, or zero if 
evaluating compliance with CO2 standards;
[Delta]ComplianceCredits: the change in manufacturer's compliance 
credits in the analysis year, which depending on the compliance 
program being evaluated, corresponds to the change in CAFE credits 
(denominated in thousands of gallons) or the change in 
CO2 credits (denominated in metric tons); and
EffCost: the calculated effective cost attributed to application of 
a candidate technology evaluated on a group of selected vehicles.

    For the effective cost calculation, the CAFE Model considers the 
total cost of a technology that could be applied to a group of 
connected vehicles, just as a vehicle manufacturer might consider what 
new technologies it has that are ready for the market, and which 
vehicles should and could receive the upgrade. Next, like the 
technology costs, the CAFE Model calculates the total value of Federal 
incentives (for this analysis, Federal tax credits) available for a 
technology that could be applied to a group of vehicles and subtracts 
that total incentive from the total technology costs. For example, even 
though we do not consider the fuel economy of LD BEVs in our standard-
setting analysis, we do account for the costs of vehicles that 
manufacturers may build in response to California's ACC I and ACC II 
program (and in the HDPUV analysis, the ACT program) as part of our 
evaluation of how the world would look without our regulation, or more 
simply, the regulatory baseline. If the CAFE Model is evaluating 
whether to build a BEV outside of the MYs for which NHTSA is setting 
standards (if the applicable in the modeling scenario), it starts with 
the total technology cost for a group of BEVs and subtracts the total 
value of the tax credits that could be applied to that group of 
vehicles.
    The total fuel savings calculation is slightly more complicated. 
Broadly, when considering total fuel savings from switching from one 
technology to another, the CAFE Model must calculate the total fuel 
cost for the vehicle before application of a technology and subtract 
the total fuel cost for the vehicle after calculation of that 
technology. The total fuel cost for a given vehicle depends on both the 
price of gas (or gasoline equivalent fuel) and the number of miles that 
a vehicle is driven, among other factors. As technology is applied to 
vehicles in groups, the total fuel cost is then multiplied by the sales 
volume of a vehicle in a MY to equal total fuel savings. This equation 
also includes an assumption that consumers are likely to buy vehicles 
with fuel economy improving technology that pays for itself within 2.5 
years, or 30 months. Finally, in the numerator, we subtract the change 
in a manufacturer's expected fines before and after application of a 
specific technology. Then, the result from the sequence above is 
divided by the change in compliance credits, which means a 
manufacturer's credits earned (expressed as thousands of gallons for 
the purposes of effective cost calculation) in a compliance category 
before and after the application of a technology to a group of 
vehicles.
    The effective cost calculation has evolved over successive CAFE 
Model iterations to become increasingly more complex; however, 
manufacturers' decision-making regarding what fuel economy improving 
technology to add to vehicles has also become increasingly more 
complex. We believe this calculation appropriately captures a number of 
manufacturers implicit or explicit considerations.
    The model accounts explicitly for each MY, applying technologies 
when vehicles are scheduled to be redesigned or freshened and carrying 
forward technologies between MYs once they are applied. The CAFE Model 
accounts explicitly for each MY because manufacturers actually ``carry 
forward'' most technologies between MYs, tending to concentrate the 
application of new technology to vehicle redesigns or mid-cycle 
``freshenings,'' and design cycles vary widely among manufacturers and 
specific products. Comments by manufacturers and model peer reviewers 
strongly support explicit year-by-year simulation. The multi-year 
planning capability, simulation of ``market-driven overcompliance,'' 
and

[[Page 56182]]

EPCA credit mechanisms increase the model's ability to simulate 
manufacturers' real-world behavior, accounting for the fact that 
manufacturers will seek out compliance paths for several MYs at a time, 
while accommodating the year-by-year requirement. This same multi-year 
planning structure is used to simulate responses to standards defined 
in grams CO2/mile and utilizing the set of specific credit 
provisions defined under EPA's program.
    In addition to the model's technology application decisions 
pursuant to the compliance simulation algorithm, there are also several 
technology inputs and assumptions that work together to determine which 
technologies the CAFE Model can apply. The technology pathways, 
discussed in detail above, are one significant way that we instruct the 
CAFE Model to apply technology. Again, the pathways define technologies 
that are mutually exclusive (i.e., that cannot be applied at the same 
time), and define the direction in which vehicles can advance as the 
modeling system evaluates specific technologies for application. Then, 
the arrows between technologies instruct the model on the order in 
which to evaluate technologies on a pathway, to ensure that a vehicle 
that uses a more fuel-efficient technology cannot downgrade to a less 
efficient option.
    In addition to technology pathway logic, we have several technology 
applicability rules that we use to better replicate manufacturers' 
decision-making. The ``skip'' input--represented in the Market Data 
Input File as ``SKIP'' in the appropriate technology column 
corresponding to a specific vehicle model--is particularly important 
for accurately representing how a manufacturer applies technologies to 
their vehicles in the real world. This tells the model not to apply a 
specific technology to a specific vehicle model. SKIP inputs are used 
to simulate manufacturer decisions with cost-benefit in mind, including 
(1) parts and process sharing; (2) stranded capital; and (3) 
performance neutrality.
    First, parts sharing includes the concepts of platform, engine, and 
transmission sharing, which are discussed in detail in Section II.C.2 
and Section II.C.3, above. A ``platform'' refers to engineered 
underpinnings shared on several differentiated vehicle models and 
configurations. Manufacturers share and standardize components, 
systems, tooling, and assembly processes within their products (and 
occasionally with the products of another manufacturer) to manage 
complexity and costs for development, manufacturing, and assembly. 
Detailed discussion for this type of SKIP is provided in the ``adoption 
features'' section for different technologies, if applicable, in 
Chapter 3 of the Draft TSD.
    Similar to vehicle platforms, manufacturers create engines that 
share parts. For instance, manufacturers may use different piston 
strokes on a common engine block or bore out common engine block 
castings with different diameters to create engines with an array of 
displacements. Head assemblies for different displacement engines may 
share many components and manufacturing processes across the engine 
family. Manufacturers may finish crankshafts with the same tools to 
similar tolerances. Engines on the same architecture may share pistons, 
connecting rods, and the same engine architecture may include both six- 
and eight-cylinder engines. One engine family may appear on many 
vehicles on a platform, and changes to that engine may or may not carry 
through to all the vehicles. Some engines are shared across a range of 
different vehicle platforms. Vehicle model/configurations in the 
analysis fleet that share engines belonging to the same platform are 
identified as such, and we also may apply a SKIP to a particular engine 
technology where we know that a manufacturer shares an engine 
throughout several of their vehicle models, and the engine technology 
is not appropriate for any of the platforms that share the same engine.
    It is important to note that manufacturers define common engines 
differently. Some manufacturers consider engines as ``common'' if the 
engines share an architecture, components, or manufacturing processes. 
Other manufacturers take a narrower definition, and only assume 
``common'' engines if the parts in the engine assembly are the same. In 
some cases, manufacturers designate each engine in each application as 
a unique powertrain. For example, a manufacturer may have listed two 
engines separately for a pair that share designs for the engine block, 
the crank shaft, and the head because the accessory drive components, 
oil pans, and engine calibrations differ between the two. In practice, 
many engines share parts, tooling, and assembly resources, and 
manufacturers often coordinate design updates between two similar 
engines. We consider engines together (for purposes of coding, 
discussed in Section II.C.2 above, and for SKIP application) if the 
engines share a common cylinder count and configuration, displacement, 
valvetrain, and fuel type, or if the engines only differed slightly in 
compression ratio (CR), horsepower, and displacement.
    Parts sharing also includes the concept of sharing manufacturing 
lines (the systems, tooling, and assembly processes discussed above), 
since manufacturers are unlikely to build a new manufacturing line to 
build a completely new engine. A new engine that is designed to be mass 
manufactured on an existing production line will have limits in number 
of parts used, type of parts used, weight, and packaging size due to 
the weight limits of the pallets, material handling interaction points, 
and conveyance line design to produce one unit of a product. The 
restrictions will be reflected in the usage of a SKIP of engine 
technology that the manufacturing line would not accommodate.
    SKIPs also relate to instances of stranded capital when 
manufacturers amortize research, development, and tooling expenses over 
many years, especially for engines and transmissions. The traditional 
production life cycles for transmissions and engines have been a decade 
or longer. If a manufacturer launches or updates a product with fuel-
saving technology, and then later replaces that technology with an 
unrelated or different fuel-saving technology before the equipment and 
research and development investments have been fully paid off, there 
will be unrecouped, or stranded, capital costs. Quantifying stranded 
capital costs accounts for such lost investments. One design where 
manufacturers take an iterative redesign approach, as described in a 
recent SAE paper,\185\ is the MacPherson strut suspension. It is a 
popular low-cost suspension design and manufacturers use it across 
their fleet.
---------------------------------------------------------------------------

    \185\ Pilla, S. et al. 2021. Parametric Design Study of 
McPherson Strut to Stabilizer Bar Link Bracket Weld Fatigue Using 
Design for Six Sigma and Taguchi Approach. SAE Technical Paper 2021-
01-0235. Available at: https://doi.org/10.4271/2021-01-0235. 
(Accessed: May 31, 2023).
---------------------------------------------------------------------------

    As we observed previously, manufacturers may be shifting their 
investment strategies in ways that may alter how stranded capital could 
be considered. For example, some suppliers sell similar transmissions 
to multiple manufacturers. Such arrangements allow manufacturers to 
share in capital expenditures or amortize expenses more quickly. 
Manufacturers share parts on vehicles around the globe, achieving 
greater scale and greatly affecting tooling strategies and costs.
    As a proxy for stranded capital in recent CAFE analyses, the CAFE 
Model

[[Page 56183]]

has accounted for platform and engine sharing and includes redesign and 
refresh cycles for significant and less significant vehicle updates. 
This analysis continues to rely on the CAFE Model's explicit year-by-
year accounting for estimated refresh and redesign cycles, and shared 
vehicle platforms and engines, to moderate the cadence of technology 
adoption and thereby limit the implied occurrence of stranded capital 
and the need to account for it explicitly. In addition, confining some 
manufacturers to specific advanced technology pathways through 
technology adoption features acts as a proxy to indirectly account for 
stranded capital. Adoption features specific to each technology, if 
applied on a manufacturer-by-manufacturer basis, are discussed in each 
technology section. We will monitor these trends to assess the role of 
stranded capital moving forward.
    Finally, we ensure that our analysis is performance neutral because 
the goal is to capture the costs and benefits of vehicle manufacturers 
adding fuel economy improving technology because of CAFE 
standards,\186\ and not to inappropriately capture costs and benefits 
for changing other vehicle attributes that may have a monetary value 
associated with them.\187\ This means that we ``SKIP'' some 
technologies where we can reasonably assume that the technology would 
not be able to maintain a performance attribute for the vehicle, and 
where our simulation over test cycles may not capture the technology 
limitation.
---------------------------------------------------------------------------

    \186\ One example is GM's 2nd generation High Feature V6 engine 
manufactured at their Romulus, MI plant (https://www.gm.com/company/facilities/romulusaccessed2/24/2023). These engines are represented 
by engine codes 113601, 113602, 113603 and should all be skipped for 
HCR due to 113603 being a pickup engine on the GMC Canyon and 
Chevrolet Colorado. DOT staff will add these skips for the final 
rule.
    \187\ See, e.g., 87 FR 25887, citing EPA, Consumer Willingness 
to Pay for Vehicle Attributes: What is the Current State of 
Knowledge? (2018) (``The agency has previously attempted to model 
the potential opportunity cost associated with changes in other 
vehicle attributes in sensitivity analyses. In those other 
rulemakings, the agency acknowledged that it is extremely difficult 
to quantify the potential changes to other vehicle attributes. To 
accurately do so requires extensive projections about which and how 
much of other attributes will be altered and a detailed accounting 
of how much value consumers assigned to those attributes. The agency 
modeled the opportunity cost associated with changes in other 
vehicle attributes using published empirical estimates of tradeoffs 
between higher fuel economy and improvements to other attributes, 
together with estimates of the values buyers attach to those 
attributes. The agency does not believe this is an appropriate 
methodology since there is considerable uncertainty in the 
literature about how much fuel economy consumers are willing to pay 
for and how consumers value other vehicle attributes. We note, for 
example, a recent EPA-commissioned study that `found very little 
useful consensus' regarding `estimates of the values of various 
vehicle attributes,' which ultimately were `of little use for 
informing policy decisions.' '').
---------------------------------------------------------------------------

    For example, prior to the development of SAE J2807, manufacturers 
used internal rating methods for their vehicle towing capacity. 
Manufacturers switched to the SAE tow rating standard at the next 
redesign of their respective vehicles so that they could mitigate costs 
via parts sharing and remain competitive in performance. Usually, the 
most capable powertrain configuration will also have the highest towing 
capacity and can be reflected in using this input feature. Separately, 
we also ensure that the analysis is performance neutral through other 
inputs and assumptions, like developing our engine maps assuming use 
with a fuel grade most commonly available to 
consumers.188 189 Those assumptions are discussed throughout 
this section, and in Chapters 2 and 3 of the Draft TSD. Technology 
``phase-in caps'' and the ``phase-in start years'' are defined in the 
Technology Cost Input file and offer a way to gradually ``phase-in'' 
technology that is not yet fully mature to the analysis. They apply to 
the manufacturer's entire estimated production and, for each 
technology, define a share of production in each MY that, once 
exceeded, will stop the model from further applying that technology to 
that manufacturer's fleet in that MY.
---------------------------------------------------------------------------

    \188\ See, e.g., 85 FR 24386 (``Vehicle manufacturers typically 
develop their engines and engine control system calibrations based 
on the fuel available to consumers. In many cases, manufacturers may 
recommend a fuel grade for best performance and to prevent potential 
damage. In some cases, manufacturers may require a specific fuel 
grade for both best performance, to achieve advertised power 
ratings, and/or to prevent potential engine damage. Consumers, 
though, may or may not choose to follow the manufacturer's 
recommendation or requirement for a specific fuel grade for their 
vehicle. As such, vehicle manufacturers often choose to employ 
engine control strategies for scenarios where the consumer uses a 
lower than recommended, or required, fuel octane level, as a way to 
mitigate potential engine damage over the life of a vehicle. These 
strategies limit the extent to which some efficiency improving 
engine technologies can be implemented, such as increased 
compression ratio and intake system and combustion chamber designs 
that increase burn rates and rate of in-cylinder pressure rise. If 
the minimum octane level available in the market were higher 
(especially the current sub-octane regular grade in the mountain 
states), vehicle manufacturers might not feel compelled to design 
vehicles sub-optimally to accommodate such blends.'').
    \189\ Id. at 24390 (``As described in the NPRM and PRIA, the 
agencies developed engine maps for technologies that are in 
production today or that are expected to be available in the 
rulemaking timeframe. The agencies recognize that engines with the 
same combination of technologies produced by different manufacturers 
will have differences in Brake-specific fuel consumption and other 
performance measures, due to differences in the design of engine 
hardware (e.g., intake runners and head ports, valves, combustion 
chambers, piston profile, compression ratios, exhaust runners and 
ports, turbochargers, etc.), control software, and emission 
calibration. Therefore, the engine maps are intended to represent 
the levels of performance that can be achieved on average across the 
industry in the rulemaking timeframe.'').
---------------------------------------------------------------------------

    The influence of these inputs varies with regulatory stringency and 
other model inputs. For example, setting the inputs to allow immediate 
100 percent penetration of a technology will not guarantee any 
application of the technology if stringency increases are low and the 
technology is not at all cost effective. Also, even if these are set to 
allow only very slow adoption of a technology, other model aspects and 
inputs may nevertheless force more rapid application than these inputs, 
alone, would suggest (e.g., because an engine technology propagates 
quickly due to sharing across multiple vehicles, or because BEV 
application must increase quickly in response to ZEV requirements). For 
this analysis, nearly all of these inputs are set at levels that do not 
limit the simulation at all.
    This analysis also applies phase-in caps and corresponding start 
years to prevent the simulation from showing unlikely rates of applying 
battery-electric vehicles (BEVs), such as showing that a manufacturer 
producing very few BEVs in MY 2022 could plausibly replace every 
product with a 300- or 400-mile BEV by MY 2026. Also, this analysis 
applies phase-in caps and corresponding start years intended to ensure 
that the simulation's plausible application of the highest included 
levels of MR (20 percent reductions of vehicle ``glider'' weight) do 
not, for example, outpace plausible supply of raw materials and 
development of entirely new manufacturing facilities.
    These model logical structures and inputs act together to produce 
estimates of ways each manufacturer could potentially shift to new 
fuel-saving technologies over time, reflecting some measure of 
protection against rates of change not reflected in, for example, 
technology cost inputs. This does not mean that every modeled solution 
would necessarily be economically practicable. Using technology 
adoption features like phase-in caps and phase-in start years is one 
mechanism that can be used so that the analysis better represents the 
potential costs and benefits of technology application in the 
rulemaking timeframe.

D. Technology Pathways, Effectiveness, and Cost

    The previous section discussed, at a high level, how we generate 
the technology inputs and assumptions used in the CAFE Model. We do 
this in several ways: by evaluating data

[[Page 56184]]

submitted by vehicle manufacturers; consolidating publicly available 
data, press materials, marketing brochures, and other information; 
collaborative research, testing, and modeling with other Federal 
agencies; research, testing, and modeling with independent 
organizations; determining that work done for prior rules is still 
relevant and applicable; considering feedback from stakeholders on 
prior rules and meetings conducted prior to the commencement of this 
rulemaking; and using our own engineering judgment.
    This section discusses the specific technology pathways, 
effectiveness, and cost inputs and assumptions used in the compliance 
analysis. As an example, interested readers learned in the previous 
section that the starting point for estimating technology costs is an 
estimate of the DMC--the component and assembly costs of the physical 
parts and systems that make up a complete vehicle--for any particular 
technology; in this section, readers will learn that our transmission 
technology DMCs are based on estimates from the NAS.
    After spending over a decade refining the technology pathways, 
effectiveness, and cost inputs and assumptions used in successive CAFE 
Model analyses, we have developed guiding principles to ensure that the 
CAFE Model's compliance analysis results in impacts that we would 
reasonably expect to see in the real world. These guiding principles 
are as follows:
    Technologies will have complementary or non-complementary 
interactions with the full vehicle technology system. The fuel economy 
improvement from any individual technology must be considered in 
conjunction with the other fuel-economy-improving technologies applied 
to the vehicle, because technologies added to a vehicle will not result 
in a simple additive fuel economy improvement from each individual 
technology. We expect this result in particular from engine and other 
powertrain technologies that improve fuel economy by allowing the ICE 
to spend more time operating at efficient engine speed and load 
conditions, or from engine technologies that both work to reduce the 
effective displacement of the engine.
    The effectiveness of a technology depends on the type of vehicle 
the technology is being applied to. When we talk about ``vehicle type'' 
in our analysis, we're referring to our vehicle technology classes--
e.g., a small car, a medium performance SUV, or a pickup truck, among 
other classes. A small car and a medium performance SUV that use the 
exact same technology will start with very different fuel economy 
values; so, when the exact same technology is added to both of those 
vehicles, the technology will provide a different effectiveness 
improvement on both of those vehicles.
    The cost and effectiveness values for each technology should be 
reasonably representative of what can be achieved across the entire 
industry. Each technology model employed in the analysis is designed to 
be representative of a wide range of specific technology applications 
used in industry. Some vehicle manufacturers' systems may perform 
better and cost less than our modeled systems and some may perform 
worse and cost more. However, employing this approach will ensure that, 
on balance, the analysis captures a reasonable level of costs and 
benefits that would result from any manufacturer applying the 
technology.
    The baseline for cost and effectiveness values must be identified 
before assuming that a cost or effectiveness value could be employed 
for any individual technology. For example, as discussed below, this 
analysis uses a set of engine map models that were developed by 
starting with a small number of baseline engine configurations, and 
then, in a very systematic and controlled process, adding specific 
well-defined technologies to create a new map for each unique 
technology combination. Again, providing a consistent reference point 
to measure incremental technology effectiveness values ensures that we 
are capturing accurate effectiveness values for each technology 
combination.
    The following sections discuss the engine, transmission, 
electrification, MR, aerodynamic, ROLL, and other vehicle technologies 
considered in this analysis. The following sections discuss:
     How we define the technology in the CAFE Model,\190\
---------------------------------------------------------------------------

    \190\ Note, due to the diversity of definitions industry 
sometimes employs for technology terms, or in describing the 
specific application of technology, the terms defined here may 
differ from how the technology is defined in the industry.
---------------------------------------------------------------------------

     How we assigned the technology to vehicles in the analysis 
fleet used as a starting point for this analysis,
     Any adoption features applied to the technology, so the 
analysis better represents manufacturers' real-world decisions,
     The technology effectiveness values, and
     Technology cost.
    Please note that the following technology effectiveness sections 
provide examples of the range of effectiveness values that a technology 
could achieve when applied to the entire vehicle system, in conjunction 
with the other fuel-economy-improving technologies already in use on 
the vehicle. To see the incremental effectiveness values for any 
particular vehicle moving from one technology key to a more advanced 
technology key, see the CAFE Model Fuel Economy Adjustment Files that 
are installed as part of the CAFE Model Executable File, and not in the 
input/output folders. Similarly, the technology costs provided in each 
section are examples of absolute costs seen in specific MYs, for 
specific vehicle classes. Please refer to the Technologies Input File 
to see all absolute technology costs used in the analysis across all 
MYs.
    For the LD analysis we show two sets of technology effectiveness 
charts for each technology type, titled ``Unconstrained'' and 
``Standard Setting.'' For the Standard Setting charts, effectiveness 
values reflect the application of 49 U.S.C. 32902(h) considerations to 
the technologies; for example, PHEV technologies only show the 
effectiveness achieved when operating in a gasoline only mode (charge 
sustaining mode). The Unconstrained charts show the effectiveness 
values modeled for the technologies without the 49 U.S.C; 32902(h) 
constraints; for example, PHEV technologies show effectiveness for 
their full dual fuel use functionality. The standard setting values are 
used during the standard setting years being assessed in this analysis, 
and the unconstrained values are used for all other years.
1. Engine Paths
    ICEs convert chemical energy in fuel to useful mechanical power. 
The chemical energy is converted to mechanical power by being burned or 
oxidized inside the engine. The air/fuel mixture entering the engine 
and burned fuel/exhaust by-products leaving the engine are the working 
fluids in the engine. The engine power output is a direct result of the 
work interaction between these fluids and the mechanical components of 
the engine.\191\ The generated mechanical power is used to perform 
useful work, such as vehicle propulsion. For a complete discussion on 
fundamentals of engine characteristics, such as torque, torque maps, 
engine load, power density, brake mean effective pressure (BMEP), 
combustion cycles, and

[[Page 56185]]

components, please refer to Heywood 2018.\192\
---------------------------------------------------------------------------

    \191\ Heywood, John B. Internal Combustion Engine Fundamentals. 
McGraw-Hill Education, 2018. Chapter 1.
    \192\ Heywood, John B. Internal Combustion Engine Fundamentals. 
McGraw-Hill Education, 2018.
---------------------------------------------------------------------------

    We classify the extensive variety of both LD and HDPUV vehicle IC 
engine technologies into discrete Engine Paths. These paths are used to 
model the most representative characteristics, costs, and performance 
of the fuel-economy improving engine technologies most likely available 
during the rulemaking time frame. The paths are intended to be 
representative of the range of potential performance levels for each 
engine technology. In general, the paths are tied to ease of 
implementation of additional technology and how closely related the 
technologies are. The technology paths for LD and HDPUV can be seen in 
Figure II-11 and Figure II-12 respectively.
BILLING CODE 4910-59-P
[GRAPHIC] [TIFF OMITTED] TP17AU23.020


[[Page 56186]]


[GRAPHIC] [TIFF OMITTED] TP17AU23.021

BILLING CODE 4910-59-C
    The LD Engine Paths have been selected and refined over a period of 
more than ten years, based on engines in the market, stakeholder 
comments, and our engineering judgment, subject to the following 
factors: we included technologies most likely available during the 
rulemaking time frame and the range of potential performance levels for 
each technology, and excluded technologies unlikely to be feasible in 
the rulemaking timeframe, technologies unlikely to be compatible with 
U.S. fuels, or technologies for which there was not appropriate data 
available to allow the simulation of effectiveness across all vehicle 
technology classes in this analysis.
    For technologies on the HDPUV Engine Paths, we revisited work done 
for the HDPUV analysis in the Phase 2 rulemaking. We have updated our 
HDPUV Engine Paths based on that work, the availability of technology 
in the HDPUV baseline fleet, and technologies we believe will be 
available in the rulemaking timeframe. The HDPUV fleet is significantly 
smaller than the LD fleet with the majority of vehicles being produced 
by only three manufacturers. These vehicles include work trucks and 
vans that are focused on transporting people, moving equipment and 
supplies, and tend to be more focused on a common need than that of 
vehicles in the LD fleet, which includes everything from sports cars to 
commuter cars and pickup trucks. The engines options between the two 
fleets are different in the real world and are accordingly different in 
the analysis. HDPUVs are work vehicles and their engines must be able 
to handle the additional work such as higher payloads, towing, and 
additional stop and go demands. This results in HDPUVs often requiring 
larger, more robust, and more powerful engines. As a result of the 
HDPUV's smaller fleet size and narrowed focus, fewer engines and engine 
technologies are developed or used in this fleet. That said, we believe 
that the range of technologies between the HDPUV Engine Paths and 
Electrification/Hybrid/Electrics Path presents a reasonable 
representation of powertrain options available for HDPUVs now and in 
the rulemaking time frame.
    We begin defining engine technology options by defining potential 
engine configurations: dual over-head camshaft (DOHC) engines have two 
camshafts per cylinder head (one operating the intake valves and one 
operating the exhaust valves), single over-head camshaft (SOHC) engines 
have a single camshaft, and over-head valve (OHV) engines also have a 
single camshaft located inside of the engine (south of the valves 
rather than over-head) connected to a rocker arm that actuates the 
valves. DOHC and SOHC engine configurations are common in the LD fleet, 
while OHV engine configurations are more common in the HDPUV fleet.
    The next step along the Engine Paths is at the Basic Engine Path 
technologies. These include variable valve lift (VVL), stoichiometric 
gasoline direct injection (SGDI), and a basic level of cylinder 
deactivation (DEAC). VVL dynamically adjusts how far the valve opens 
and reduces fuel consumption by reducing pumping losses and optimizing 
airflow over broader range of engine operating conditions. Instead of 
injecting fuel at lower pressures and before the intake valve, SGDI 
injects fuel directly into the cylinder at high pressures allowing for 
more precise fuel delivery while providing a cooling effect and 
allowing for an increase in the CR and/or more optimal spark timing for 
improved efficiency. DEAC disables the intake and exhaust valves and 
turns off fuel injection on select cylinders which effectively, allows 
the engine to operate temporarily as if it were smaller while

[[Page 56187]]

also reducing pumping losses to improve efficiency. New for this 
analysis is that variable valve timing (VVT) technology is integrated 
in all non-diesel engines, so we do not have a separate box for it on 
the Basic Engine Path. For the LD analysis, VVL, SGDI, and DEAC can be 
applied to an engine individually or in combination with each other, 
and for the HDPUV analysis, SGDI and DEAC can be applied individually 
or in combination.
    Moving beyond the Basic Engine Path technologies are the 
``advanced'' engine technologies, which means that applying the 
technology--both in our analysis and in the real world--would require 
significant changes to the structure of the engine or an entirely new 
engine architecture. The advanced engine technologies represent the 
application of alternate combustion cycles, various applications of 
forced induction technologies, or advances in cylinder deactivation.
    Advanced cylinder deactivation (ADEAC) systems, also known as 
rolling or dynamic cylinder deactivation systems, allow the engine to 
vary the percentage of cylinders deactivated and the sequence in which 
cylinders are deactivated. Depending on the engine's speed and 
associated torque requirements, an engine might have most cylinders 
deactivated (e.g., low torque conditions as with slower speed driving) 
or it might have all cylinders activated (e.g., high torque conditions 
as with merging onto a highway).\193\ An engine operating at low speed/
low torque conditions can then save fuel by operating as if it is only 
a fraction of its total displacement. We model two ADEAC technologies, 
advanced cylinder deactivation on a single overhead camshaft engine 
(ADEACS), and advanced cylinder deactivation on a dual overhead 
camshaft engine (ADEACD).
---------------------------------------------------------------------------

    \193\ See for example, Dynamic Skip Fire, Tula Technology, DSF 
in real world situations, https://www.tulatech.com/combustion-engine/. Our modeled ADEAC system is not based on this specific 
system, and therefore the effectiveness improvement will be 
different in our analysis than with this system, however, the theory 
still applies.
---------------------------------------------------------------------------

    Forced induction gasoline engines include both supercharged and 
turbocharged downsized engines, which can pressurize or force more air 
into an engine's intake manifold when higher power output is needed. 
The raised pressure results in an increased amount of airflow into the 
cylinder supporting combustion, increasing the specific power of the 
engine. The baseline turbocharged downsized technology (TURBO0) engine 
represents a basic level of forced air induction technology being 
applied to a DOHC engine. Cooled exhaust gas recirculation (CEGR) 
systems take engine exhaust gasses and passes them through a heat 
exchanger to reduce their temperature, and then mixes them with 
incoming air in the intake manifold. We model the base TURBO0 
turbocharged engine with cooled exhausted recirculation (TURBOE), basic 
cylinder deactivation (TURBOD), and advanced cylinder deactivation 
(TURBOAD). Walking down the Turbo Engine Path leads to engines that 
have higher BMEP, which is a function of displacement and power. The 
higher the BMEP, the higher the engine performance. We model two levels 
of advanced turbocharging technology (TURBO1 and TURBO2) that run 
increasingly higher turbocharger boost levels, burning more fuel, and 
making more power for a given displacement. As discussed above, we pair 
turbocharging with engine downsizing, meaning that the turbocharged 
downsized engines in our analysis improve vehicle fuel economy by using 
less fuel to power the smaller engine while maintaining vehicle 
performance.
    In this analysis, high compression ratio (HCR) engines represent a 
class of engines that achieve a higher level of fuel efficiency by 
implementing a high geometric CR with varying degrees of late intake 
valve closing (LIVC) (i.e., closing the intake valve later than usual) 
using VVT, and without the use of an electric drive 
motor.194 195 These engines operate on a modified Atkinson 
cycle allowing for improved fuel efficiency under certain engine load 
conditions but still offering enough power to not require an electric 
motor; however, there are limitations on how HCR engines can apply LIVC 
and the types of vehicles that can use this technology. The way that 
each individual manufacturer implements a modified Atkinson cycle will 
be unique, as each manufacturer must balance not only fuel efficiency 
considerations, but emissions, on-board diagnostics, and safety 
considerations that includes the vehicle being able to operate 
responsively to the driver's demand.
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    \194\ Late intake valve closing (LIVC) is a method manufacturers 
use to reduce the effective compression ratio and allow the 
expansion ratio to be greater than the compression ratio resulting 
in improved fuel economy but reduced power density. Further 
technical discussion on HCR and Atkinson Engines are discussed in 
Draft TSD Chapter 3.1.1.2.3.
    \195\ See the 2015 NAS report, Appendix D, for a short 
discussion on thermodynamic engine cycles.
---------------------------------------------------------------------------

    We define HCR engines as being naturally aspirated, gasoline, SI, 
using a geometric CR of 12.5:1 or greater,\196\ and able to dynamically 
apply various levels of LIVC based on load demand. An HCR engine uses 
less fuel for each engine cycle, which increases fuel economy, but 
decreases power density (or torque). Generally, during high loads--when 
more power is needed--the engine will use variable valve actuation to 
reduce the level of LIVC by closing the intake valve earlier in the 
compression stroke (leaving more fuel in the compression chamber), 
increasing the effective CR, reducing over-expansion, and sacrificing 
efficiency for increased power density.\197\ However, there is a limit 
to how much fuel can remain in the compression chamber of an HCR engine 
because over-compression of the air-fuel mixture can lead to engine 
knock.\198\ Conversely, at low loads the engine will typically increase 
the level of LIVC by closing the intake valve later in the compression 
stroke, reducing the effective CR, increasing the over-expansion, and 
sacrificing power density for improved efficiency. By closing the 
intake valve later in the compression stroke (i.e., applying more 
LIVC), the engine's displacement is effectively reduced, which results 
in less air and fuel for combustion and a lower power output.\199\ 
Varying LIVC can be used to mitigate, but not eliminate, the low power 
density issues that can constrain the application of an Atkinson-only 
engine.
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    \196\ Note that even if an engine has a compression ratio of 
12.5:1 or greater, it does not necessarily mean it is an HCR engine 
in our analysis, as discussed below. We look at a number of factors 
to perform baseline engine assignments.
    \197\ Variable valve actuation is a general term used to 
describe any single or combination of VVT, VVL, and variable valve 
duration used to dynamically alter an engines valvetrain during 
operation.
    \198\ Engine knock in spark ignition engines occurs when 
combustion of some of the air/fuel mixture in the cylinder does not 
result from propagation of the flame front ignited by the spark 
plug, but one or more pockets of air/fuel mixture explodes outside 
of the envelope of the normal combustion front.
    \199\ Power = (force x displacement)/time.
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    When we say, ``lower power density issues,'' this translates to a 
low torque density,\200\ meaning that the engine cannot create the 
torque required at necessary speeds to meet load demands. To the extent 
that a vehicle requires more power in a given condition than an engine 
with low power density can provide, that engine would experience issues 
like engine knock for the reasons discussed above, but more 
importantly, an engine designer would not allow an engine application 
where the engine has the potential to operate in unsafe conditions in 
the first place. Instead, a manufacturer could significantly

[[Page 56188]]

increase an engine's displacement (i.e., size) to overcome those low 
power density issues,\201\ or could add an electric motor and battery 
pack to provide the engine with more power, but a far more effective 
pathway would be to apply a different type of engine technology, like a 
downsized, turbocharged engine.\202\
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    \200\ Torque = radius x force.
    \201\ But see the 2022 EPA Trends Report at 46 (``As vehicles 
have moved towards engines with a lower number of cylinders, the 
total engine size, or displacement, is also at an all-time low.''), 
and the discussion below about why we do not believe manufacturers 
will increase the displacement of HCR engines to make the necessary 
power.
    \202\ See, e.g., Toyota Newsroom. 2024 Toyota Tacoma Makes Debut 
on the Big Island, Hawaii. May 19, 2023. Available at: https://pressroom.toyota.com/2024-toyota-tacoma-makes-debut-on-the-big-island-hawaii/. (Accessed: May 31, 2023). The 2024 Toyota Tacoma 
comes in 8 ``grades,'' all of which use a turbocharged engine.
---------------------------------------------------------------------------

    Vehicle manufacturers' intended performance attributes for a 
vehicle--like payload and towing capability, intention for off-road 
use, and other attributes that affect frontal area and rolling 
resistance--dictate whether an HCR engine can be a suitable technology 
choice for that vehicle.203 204 As vehicles require higher 
payloads and towing capacities,\205\ or experience road load increases 
from larger all-terrain tires or a larger frontal area and less 
aerodynamic design, or experience driveline losses for AWD and 4WD 
configurations, more engine torque is required at all engine speeds. 
Any time more engine torque is required the application of this 
technology becomes less effective and more limited.\206\ For these 
reasons, to maintain a performance-neutral analysis, and as discussed 
further below, we limit non-hybrid and non-plug-in-hybrid HCR engine 
application to certain categories of vehicles.\207\ Also for these 
reasons, HCR engines are not found in the HDPUV baseline fleet nor are 
they available as an engine option in the HDPUV analysis.
---------------------------------------------------------------------------

    \203\ Supplemental Comments of Toyota Motor North America, Inc., 
Notice of Proposed Rulemaking: Safer Affordable Fuel-Efficient 
Vehicles Rule, Docket ID Numbers: NHTSA-2018-0067 and EPA-HQ-OAR-
2018-0283. p.6.
    \204\ Feng, R. et al. 2016. Investigations of Atkinson Cycle 
Converted from Conventional Otto Cycle Gasoline Engine. SAE 
Technical Paper. Available at: https://www.sae.org/publications/technical-papers/content/2016-01-0680/. (Accessed: May 31, 2023).
    \205\ See Tucker, S. 2023. What Is Payload: A Complete Guide, 
Kelly Blue Book. Last revised: Feb. 2, 2023. Availale at: https://www.kbb.com/car-advice/payload-guide/#link3. (Accessed: May 31, 
2023). (``Roughly speaking, payload capacity is the amount of weight 
a vehicle can carry, and towing capacity is the amount of weight it 
can pull. Automakers often refer to carrying weight in the bed of a 
truck as hauling to distinguish it from carrying weight in a trailer 
or towing.'').
    \206\ Supplemental Comments of Toyota Motor North America, Inc., 
Notice of Proposed Rulemaking: Safer Affordable Fuel-Efficient 
Vehicles Rule, Docket ID Numbers: NHTSA-2018-0067 and EPA-HQ-OAR-
2018-0283. (``Tacoma has a greater coefficient of drag from a larger 
frontal area, greater tire rolling resistance from larger tires with 
a more aggressive tread, and higher driveline losses from 4WD. 
Similarly, the towing, payload, and off road capability of pick-up 
trucks necessitate greater emphasis on engine torque and horsepower 
over fuel economy.
     This translates into engine specifications such as a larger 
displacement and a higher stroke-to-bore ratio. . . . Tacoma's 
higher road load and more severe utility requirements push engine 
operation more frequently to the less efficient regions of the 
engine map and limit the level of Atkinson operation . . . This 
endeavor is not a simple substitution where the performance of a 
shared technology is universal. Consideration of specific vehicle 
requirements during the vehicle design and engineering process 
determine the best applicable powertrain.'').
    \207\ To maintain performance neutrality when sizing powertrains 
and selecting technologies we perform a series of simulations in 
Automime which are further discussed in the TSD Chapter 2.3.4 and in 
the CAFE Analysis Autonomie Documentation. The concept of 
performance neutrality is discussed in detail above in Section 
II.C.3, Technology Effectiveness Values, and additional reasons why 
we maintain a performance neutral analysis are discussed in Section 
II.C.6, Technology Applicability Equations and Rules.
---------------------------------------------------------------------------

    For this analysis, our HCR Engine Path includes three technology 
options: (1) a baseline Atkinson-enabled engine (HCR) with VVT and 
SGDI, (2) an Atkinson enabled engine with cooled exhaust gas 
recirculation (HCRE), and finally, (3) the Atkinson enabled engine with 
DEAC (HCRD). This updated family of HCR engine map models also reflects 
our statement in NHTSA's May 2, 2022 final rule that a single engine 
that employs an HCR, CEGR, and DEAC ``is unlikely to be utilized in the 
rulemaking timeframe based on comments received from the industry 
leaders in HCR technology application.'' \208\
---------------------------------------------------------------------------

    \208\ 87 FR 25796 (May 2, 2022).
---------------------------------------------------------------------------

    These three HCR Engine Path technology options (HCR, HCRE, HCRD) 
should not be confused with the hybrid and plug-in hybrid electric 
pathway options that also utilize HCR engines in combination with an 
electrified powertrain (i.e., P2HCR, P2HCRE, PHEV20H, and PHEV50H); 
those hybridization path options are discussed in Section II.D.3, 
below. In contrast, Atkinson engines in this analysis (SHEVPS, 
PHEV20PS, and PHEV50PS) run the Atkinson Cycle full time, but are 
connected to an electric motor. The full-time Atkinson engines are 
discussed in Section II.D.3 below.
    The Miller cycle is another alternative combustion cycle that uses 
an extended expansion stroke, similar to the Atkinson cycle, to improve 
fuel efficiency. Miller cycle-enabled engines have a similar trade-off 
in power density as Atkinson engines; the lower power density requires 
a larger volume engine in comparison to an Otto cycle-based 
turbocharged system for similar applications.\209\ To address the 
impacts of the extended expansion stroke on power density during high 
load operating conditions, the Miller cycle operates in combination 
with a forced induction system. In our analysis, the baseline Miller 
cycle-enabled engine includes the application of variable turbo 
geometry technology (VTG), or what is also known as a variable-geometry 
turbocharger. VTG technology allows the turbocharger to adjust key 
geometric characteristics of the system, thus allowing adjustment of 
boost profiles and response based on the engine's operating needs. The 
adjustment of boost profile during operation increases the engine's 
power density over a broader range of operating conditions and 
increases the functionality of a Miller cycle-based engine. The use of 
a variable geometry turbocharger also supports the use of CEGR. The 
second level of VTG Engine technology in our analysis (VTGE) is an 
advanced Miller cycle-enabled system that includes the application of 
at least a 40V-based electronic boost system. An electronic boost 
system has an electric motor added to assist the turbocharger; the 
motor assist mitigates turbocharger lag and low boost pressure by 
providing the extra boost needed to overcome the torque deficit at low 
engine speeds.
---------------------------------------------------------------------------

    \209\ National Academies of Sciences, Engineering, and Medicine. 
2021. Assessment of Technologies for Improving Light-Duty Vehicle 
Fuel Economy 2025-2035.The National Academies Press: Washington, DC. 
Section 4. Available at: https://doi.org/10.17226/26092. (Accessed: 
May 31, 2023). [hereinafter 2021 NAS report].
---------------------------------------------------------------------------

    Variable compression ratio (VCR) engines work by changing the 
length of the piston stroke of the engine to optimize the CR and 
improve thermal efficiency over the full range of engine operating 
conditions. Engines that use VCR technology are currently in production 
as small displacement turbocharged in-line four-cylinder, high BMEP 
applications.
    Diesel engines have several characteristics that result in better 
fuel efficiency over traditional gasoline engines, including reduced 
pumping losses due to lack of (or greatly reduced) throttling, high 
pressure direct injection of fuel, a combustion cycle that operates at 
a higher CR, and a very lean air/fuel mixture relative to an 
equivalent-performance gasoline engine. However, diesel technologies 
require additional systems to control NOX emissions, such as 
a NOX adsorption catalyst system or a urea/ammonia selective 
catalytic reduction system. We included two

[[Page 56189]]

levels of diesel engine technology in both the LD and HDPUV analyses: 
the baseline diesel engine technology (ADSL) is a turbocharged diesel 
engine, and the more advanced diesel engine (DSLI) adds DEAC to the 
ADSL engine technology. The diesel engine maps are new for this 
analysis. The LD diesel engine maps and HD van engine maps are based on 
a modern 3.0L turbo-diesel engine, and the HDPUV pickup truck engine 
maps are based on a larger 6.7L turbo-diesel engine.
    Finally, compressed natural gas (CNG) systems are ICEs that run on 
natural gas as a fuel source. The fuel storage and supply systems for 
these engines differ tremendously from gasoline, diesel, and flex fuel 
vehicles.\210\ The CNG engine option has been included in past 
analyses; however, the LD and HDPUV baseline fleets do not include any 
dedicated CNG vehicles. As with the last analyses, CNG engines are 
included as a baseline-only technology and are not applied to any 
vehicle that did not already include a CNG engine.
---------------------------------------------------------------------------

    \210\ Flexible fuel vehicles (FLEX) are designed to run on 
gasoline or gasoline-ethanol blends of up to 85 percent ethanol.
---------------------------------------------------------------------------

    The first step in assigning engine technologies to vehicles in the 
LD and HDPUV baseline fleets is to use data for each manufacturer to 
determine which vehicle platforms share engines. Within each 
manufacturer's fleet, we develop and assign unique engine codes based 
on configuration, technologies applied, displacement, CR, and power 
output. While the process for engine assignments is the same between 
the LD and HDPUV analyses, engine codes are not shared between the two 
fleets, and engine technologies are not shared between the fleets, for 
the reasons discussed above. We also assign engine technology classes, 
which are codes that identify engine architecture (e.g., how many 
cylinders the engine has, whether it is a DOHC or SOHC, and so on) to 
accurately account for engine costs in the analysis.
    When we assign engine technologies to vehicles in the baseline 
fleets, we must consider the actual technologies on a manufacturer's 
engine and compare those technologies to the engine technologies in our 
analysis. We have just over 270 unique engine codes in the LD baseline 
fleet and just over 20 unique engine codes in the HDPUV fleet, meaning 
that for both analysis fleets, we must identify the technologies 
present on those almost 300 unique engines in the real world, and make 
decisions about which of our approximately 40 engine map models (and 
therefore engine technology on the technology tree) \211\ best 
represents those real-world engines. When we consider how to best fit 
each of those 300 engines to our 40 engine technologies and engine map 
models, we use specific technical elements contained in manufacturer 
publications, press releases, vehicle benchmarking studies, technical 
publications, manufacturer's specification sheets, and occasionally CBI 
(like the specific technologies, displacement, CR, and power mentioned 
above), and engineering judgment. For example, in the LD analysis, an 
engine with a 13.0:1 CR is a good indication that an engine would be 
considered an HCR engine in our analysis, and some engines that achieve 
a slightly lower CR, e.g., 12.5, may be considered an HCR engine 
depending on other technology on the engine, like inclusion of SGDI, 
increased engine displacement compared to other competitors, a high 
energy spark system, and/or reduction of engine parasitic losses 
through variable or electric oil and water pumps. Importantly, we never 
assign engine technologies based on one factor alone; we use data and 
engineering judgment to assign complex real-world engines to their 
corresponding engine technologies in the analysis. We believe that our 
initial characterization of the fleet's engine technologies reasonably 
captures the current state of the market while maintaining a reasonable 
amount of analytical complexity. Also, as a reminder, in addition to 
the 40 engine map models used in the Engine Paths Collection, we have 
over 20 additional potential powertrain technology assignments 
available in the Hybrid/Electric Paths Collection.
---------------------------------------------------------------------------

    \211\ We assign each engine code technology that most closely 
corresponds to an engine map; for most technologies, one box on the 
technology tree corresponds to one engine map that corresponds to 
one engine code.
---------------------------------------------------------------------------

    Engine technology adoption in the model is defined through a 
combination of technology path logic, refresh and redesign cycles, 
phase-in capacity limits,\212\ and SKIP logic. How does technology path 
logic define technology adoption? Once an engine design moves to the 
advanced engine tree it is not allowed to move to alternate advanced 
engine trees. For example, any LD basic engine can adopt one of the 
TURBO engine technologies, but vehicles that have turbocharged engines 
in the baseline fleet will stay on the Turbo Engine Path to prevent 
unrealistic engine technology change in the short timeframe considered 
in the rulemaking analysis. This represents the concept of stranded 
capital, which as discussed above, is when manufacturers amortize 
research, development, and tooling expenses over many years. Besides 
technology path logic, which applies to all manufacturers and 
technologies, we place additional constraints on the adoption of VCR 
and HCR technologies.
---------------------------------------------------------------------------

    \212\ Although we did apply phase-in caps for this analysis, as 
discussed in Chapter 3.1.1 of the Draft TSD, those phase-in caps are 
not binding because the model has several other less advanced 
technologies available to apply first at a lower cost, as well as 
the redesign schedules. As discussed in Draft TSD Chapter 2.2, 100 
percent of the analysis fleet will not redesign by 2023, which is 
the last year that phase-in caps could apply to the engine 
technologies discussed in this section. Please see the Draft TSD for 
more information on engine phase-in caps.
---------------------------------------------------------------------------

    Basic and turbocharged engines in the LD analysis can adopt a VCR 
engine if the engine is currently manufactured by a manufacturer or 
partnered manufacturer that has already implemented the technology. VCR 
technology requires a complete redesign of the engine, and in the 
analysis fleet, only two models have incorporated this technology. VCR 
engines are complex, costly by design, and address many of the same 
efficiency losses as mainstream technologies like turbocharged 
downsized engines, making it unlikely that a manufacturer that has 
already started down an incongruent technology path would adopt VCR 
technology. Because of these issues, we limited adoption of the VCR 
engine technology to original equipment manufacturers (OEMs) that have 
already employed the technology and their partners. We do not believe 
any other manufacturers will invest to develop and market this 
technology in their fleet in the rulemaking time frame.
    HCR engines are subject to three limitations. This is because, as 
we have recognized in past analyses,\213\ HCR engines excel in lower 
power applications for lower load conditions, such as driving around a 
city or steady state highway driving without large payloads. Thus, 
their adoption is more limited than some other technologies.
---------------------------------------------------------------------------

    \213\ The discussions at 83 FR 43038 (Aug. 24, 2018), 85 FR 
24383 (April 30, 2020), 86 FR 49568 and 49661 (September 3, 2021), 
and 87 FR 25786 and 25790 (May 2, 2022) are incorporated herein by 
reference.
---------------------------------------------------------------------------

    First, we do not allow vehicles with 405 or more horsepower, and 
(to simulate parts sharing) vehicles that share engines with vehicles 
with 405 or more horsepower, to adopt HCR engines due to their 
prescribed power needs being more demanding and likely not supported by 
the lower power density found in HCR-based engines.\214\ Because

[[Page 56190]]

LIVC essentially reduces the engine's displacement, to make more power 
and keep the same levels of LIVC, manufacturers would need to increase 
the displacement of the engine to make the necessary power. We do not 
believe manufacturers will increase the displacement of their engines 
to accommodate HCR technology adoption. This bears out in industry 
trends: total engine size (or displacement) is at an all-time low, and 
trends show that industry focus on turbocharged downsized engine 
packages are leading to their much higher market penetration.\215\ 
Separately, as seen in the baseline fleet, manufacturers generally use 
HCR engines in applications where the vehicle's power requirements fall 
significantly below our horsepower threshold. In fact, the horsepower 
average for the sales weighted average of vehicles in the baseline 
analysis fleet that use HCR Engine Path technologies is 179 hp, 
demonstrating that HCR engine use has indeed been limited to lower-hp 
applications, and well below our 405 hp threshold. In fringe cases 
where a vehicle classified as having higher load requirements does have 
an HCR engine, it is coupled to a hybrid system.\216\
---------------------------------------------------------------------------

    \214\ Heywood, John B. Internal Combustion Engine Fundamentals. 
McGraw-Hill Education, 2018. Chapter 5.
    \215\ See 2022 EPA Trends Report at 46, 72.
    \216\ See the Market Data Input File. As an example, the 
reported total system horsepower for the Ford Maverick HEV is also 
191hp, well below our 405hp threshold. See also the Lexus LC/LS 
500h: the Lexus LC/LS 500h also uses premium fuel to reach this 
performance level.
---------------------------------------------------------------------------

    Secondly, to maintain a performance-neutral analysis,\217\ we 
exclude pickup trucks and (to simulate parts sharing) \218\ vehicles 
that share engines with pickup trucks from receiving HCR engines that 
are not accompanied by an electrified powertrain. In other words, 
pickup trucks and vehicles that share engines with pickup trucks can 
receive HCR-based engine technologies in the Hybridization Paths 
Collection of technologies. We exclude pickup trucks and vehicles that 
share engines with pickup trucks from receiving HCR engines that are 
not accompanied by an electrified powertrain because these often-
heavier vehicles have higher low speed torque needs, higher base road 
loads, increased payload and towing requirements,\219\ and have 
powertrains that are sized and tuned to perform this additional work 
above what passenger cars are required to conduct. Again, vehicle 
manufacturers' intended performance attributes for a vehicle--like 
payload and towing capability, intention for off-road use, and other 
attributes that affect frontal area and rolling resistance--dictate 
whether an HCR engine can be a suitable technology choice for that 
vehicle.220 221 For example, road loads are comprised of 
aerodynamic loads which include frontal area vehicle design along with 
rolling resistance that attribute to higher engine loads as vehicle 
speed increases.\222\ We assume that a manufacturer intending to apply 
HCR technology to their pickup truck or vehicle that shares an engine 
with a pickup truck would do so in combination with an electric system 
to assist with the vehicle's load needs, and indeed the only 
manufacturer that has an HCR-like engine (in terms of how we model HCR 
engines in this analysis) in its pickup truck in the baseline fleet has 
done so.
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    \217\ As discussed in detail in Section II.C.3 and II.C.6 above, 
we maintain a performance-neutral analysis to capture only the costs 
and benefits of manufacturers adding fuel-economy-improving 
technology to their vehicles in response to CAFE standards.
    \218\ See Section II.C.6.
    \219\ See Society of Automotive Engineers Surface Vehicle 
Recommended Practice J2807. Performance Requirements for Determining 
Tow-Vehicle Gross Combination Weight Rating and Trailer Weight 
Rating (issued April 2008, revised February 2020); Trevor Reed. SAE 
J207 Tow Tests--The Standard, Motortrend (Jan 16, 2015). Available 
at https://www.motortrend.com/how-to/1502-sae-j2807-tow-tests-the-standard/. (Accessed: May 31, 2023). When we say ``increased payload 
and towing requirements,'' we are referring to a literal defined set 
of requirements that manufacturers follow to ensure the 
manufacturer's vehicle can meet a set of performance measurements 
when building a tow-vehicle in order to give consumers the ability 
to ``cross-shop'' between different manufacturer's vehicles. As 
discussed in detail above in Section II.C.3 and II.C.6, we maintain 
a performance neutral analysis to ensure that we are only accounting 
for the costs and benefits of manufacturers adding technology in 
response to CAFE standards. This means that we will apply adoption 
features, like the HCR application restriction, to a vehicle that 
begins the analysis with specific performance measurements, like a 
pickup truck, where application of the specific technology would 
likely not allow the vehicle to meet the manufacturer's baseline 
performance measurements.
    \220\ See, e.g., Supplemental Comments of Toyota Motor North 
America, Inc., Notice of Proposed Rulemaking: Safer Affordable Fuel-
Efficient Vehicles Rule, Docket ID Numbers: NHTSA-2018-0067 and EPA-
HQ-OAR-2018-0283. p.6.
    \221\ Supplemental Comments of Toyota Motor North America, Inc., 
Notice of Proposed Rulemaking: Safer Affordable Fuel-Efficient 
Vehicles Rule, Docket ID Numbers: NHTSA-2018-0067 and EPA-HQ-OAR-
2018-0283. ``Tacoma has a greater coefficient of drag from a larger 
frontal area, greater tire rolling resistance from larger tires with 
a more aggressive tread, and higher driveline losses from 4WD. 
Similarly, the towing, payload, and off road capability of pick-up 
trucks necessitate greater emphasis on engine torque and horsepower 
over fuel economy.
    This translates into engine specifications such as a larger 
displacement and a higher stroke-to-bore ratio. . . . Tacoma's 
higher road load and more severe utility requirements push engine 
operation more frequently to the less efficient regions of the 
engine map and limit the level of Atkinson operation . . . This 
endeavor is not a simple substitution where the performance of a 
shared technology is universal. Consideration of specific vehicle 
requirements during the vehicle design and engineering process 
determine the best applicable powertrain.''
    \222\ 2015 NAS Report, Chapter 6, p. 207-242.
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    Finally, we restrict HCR engine application for some manufacturers 
that are heavily performance-focused and have demonstrated a 
significant commitment to power dense technologies such as turbocharged 
downsizing.\223\ When we say, ``significant commitment to power dense 
technologies,'' we mean that their fleets use near 100% turbocharged 
downsized engines. This means that no vehicle manufactured by these 
manufacturers can receive an HCR engine. Again, we implement this 
adoption feature to avoid an unquantified amount of stranded capital 
that would be realized if these manufacturers switched from one 
technology to another.
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    \223\ There are three manufacturers that met the criteria (near 
100 percent turbo downsized fleet, and future hybrid systems are 
based on turbo-downsized engines) described and were excluded: BMW 
of North America, LLC, Daimler, and Jaguar Land Rover.
---------------------------------------------------------------------------

    Note, however, that these adoption features only apply to vehicles 
that receive HCR engines that are not accompanied by an electrified 
powertrain. A P2 hybrid system that uses an HCR engine overcomes the 
low-speed torque needs using the electric motor and thus has no 
restrictions or SKIPs applied.
    How effective an engine technology is at improving a vehicle's fuel 
economy depends on several factors such as the vehicle's technology 
class and any additional technology that is being added or removed from 
the vehicle in conjunction with the new engine technology, as discussed 
in Section II.C, above. The Autonomie model's full vehicle simulation 
results provide most of the effectiveness values that we use as inputs 
to the CAFE Model. For a full discussion of the Autonomie modeling see 
Chapter 2.4 of the Draft TSD and the CAFE Analysis Autonomie 
Documentation. The Autonomie modeling uses engine map models as the 
primary inputs for simulating the effects of different engine 
technologies.
    Engine maps provide a three-dimensional representation of engine 
performance characteristics at each engine speed and load point across 
the operating range of the engine. Engine maps have the appearance of 
topographical maps, typically with engine speed on the horizontal axis 
and engine torque, power, or BMEP on the vertical axis. A third engine 
characteristic, such as brake-specific fuel consumption (BSFC), is 
displayed

[[Page 56191]]

using contours overlaid across the speed and load map. The contours 
provide the values for the third characteristic in the regions of 
operation covered on the map. Other characteristics typically overlaid 
on an engine map include engine emissions, engine efficiency, and 
engine power. We refer to the engine maps developed to model the 
behavior of the engines in this analysis as engine map models.
    The engine map models we use in this analysis are representative of 
technologies that are currently in production or are expected to be 
available in the rulemaking timeframe. We develop the engine map models 
to be representative of the performance achievable across industry for 
a given technology, and they are not intended to represent the 
performance of a single manufacturer's specific engine. We target a 
broadly representative performance level because the same combination 
of technologies produced by different manufacturers will have 
differences in performance, due to manufacturer-specific designs for 
engine hardware, control software, and emissions calibration. 
Accordingly, we expect that the engine maps developed for this analysis 
will differ from engine maps for manufacturers' specific engines. 
However, we intend and expect that the incremental changes in 
performance modeled for this analysis, due to changes in technologies 
or technology combinations, will be similar to the incremental changes 
in performance observed in manufacturers' engines for the same changes 
in technologies or technology combinations.
    IAV developed most of the LD engine map models we use in this 
analysis. IAV is one of the world's leading automotive industry 
engineering service partners with an over 35-year history of performing 
research and development for powertrain components, electronics, and 
vehicle design.\224\ Southwest Research Institute (SwRI) developed the 
LD diesel and HDPUV engine maps for this analysis. SwRI has been 
providing automotive science, technology, and engineering services for 
over 70 years.\225\ Both IAV and SwRI developed our engine maps using 
the GT-POWER(copyright) Modeling tool (GT-POWER). GT-POWER is a 
commercially available, industry standard, engine performance 
simulation tool. GT-POWER can be used to predict detailed engine 
performance characteristics such as power, torque, airflow, volumetric 
efficiency, fuel consumption, turbocharger performance and matching, 
and pumping losses.\226\
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    \224\ IAV Automotive Engineering. Available at: https://www.iav.com/en. (Accessed: May 31, 2023).
    \225\ Southwest Research Institite. Available at: https://www.swri.org. (Accessed: May 31, 2023).
    \226\ For additional information on the GT-POWER tool please see 
https://www.gtisoft.com/gt-suite-applications/propulsion-systems/gt-power-engine-simulation-software.
---------------------------------------------------------------------------

    Just like ANL optimizes a single vehicle model in Autonomie 
following the addition of a singular technology to the vehicle model, 
our engine map models were built in GT-POWER by incrementally adding 
engine technology to a baseline engine--built using engine test data, 
component test data, and manufacturers' and suppliers' technical 
publications--and then optimizing the engine to consider real-world 
constraints like heat, friction, and knock. We use a small number of 
baseline engine configurations with well-defined BSFC maps, and then, 
in a very systematic and controlled process, add specific well-defined 
technologies to create a BSFC map for each unique technology 
combination. This could theoretically be done through engine or vehicle 
testing, but we would need to conduct tests on a single engine, and 
each configuration would require physical parts and associated engine 
calibrations to assess the impact of each technology configuration, 
which is impractical for the rulemaking analysis because of the 
extensive design, prototype part fabrication, development, and 
laboratory resources that are required to evaluate each unique 
configuration. We and the automotive industry use modeling as an 
approach to assess an array of technologies with more limited testing. 
Modeling offers the opportunity to isolate the effects of individual 
technologies by using a single or small number of baseline engine 
configurations and incrementally adding technologies to those baseline 
configurations. This provides a consistent reference point for the BSFC 
maps for each technology and for combinations of technologies that 
enables us to carefully identify and quantify the differences in 
effectiveness among technologies.
    Before use in the Autonomie analysis, both IAV and SwRI validated 
the generated engine maps against a global database of benchmarked 
data, engine test data, single cylinder test data, prior modeling 
studies, technical studies, and information presented at 
conferences.\227\ IAV and SwRI also validated the effectiveness values 
from the simulation results against detailed engine maps produced from 
the ANL engine benchmarking programs, as well as published information 
from industry and academia.228 229 This ensures reasonable 
representation of simulated engine technologies. Additional details and 
assumptions that we use in the engine map modeling are described in 
detail in Chapter 3.1 of the Draft TSD and the CAFE Analysis Autonomie 
Model Documentation chapter titled ``Autonomie--Engine Model.''
---------------------------------------------------------------------------

    \227\ Friedrich, I. et al. 2006. Automatic Model Calibration for 
Engine-Process Simulation with Heat-Release Prediction. SAE 
Technical Paper. Available at: https://doi.org/10.4271/2006-01-0655. 
(Accessed: May 31, 2023); Rezaei, R. et al. 2012. Zero-Dimensional 
Modeling of Combustion and Heat Release Rate in DI Diesel Engines. 
SAE International Journal Of Engines 5(3): pp. 874-885. Available 
at: https://doi.org/10.4271/2012-01-1065. (Accessed: May 31, 2023); 
Multistage Supercharging for Downsizing with Reduced Compression 
Ratio. 2015. MTZ Rene Berndt, Rene Pohlke, Christopher Severin, and 
Matthias Diezemann IAV GmbH.; Symbiosis of Energy Recovery and 
Downsizing. 2014. September 2014 MTZ Publication Heiko Neukirchner, 
Torsten Semper, Daniel Luederitz and Oliver Dingel IAV GmbH.
    \228\ Bottcher, L., & Grigoriadis, P. 2019. ANL--BSFC Map 
Prediction Engines 22-26. IAV.
    \229\ Reinhart, T. 2022. Engine Efficiency Technology Study. 
Final Report. SwRI Project No. 03.26457.
---------------------------------------------------------------------------

    Note that we never apply absolute BSFC levels from the engine maps 
to any vehicle model or configuration for the rulemaking analysis. We 
only use the absolute fuel economy values from the full vehicle 
Autonomie simulations to determine incremental effectiveness for 
switching from one technology to another technology. The incremental 
effectiveness is then applied to the absolute fuel economy or fuel 
consumption value of vehicles in the analysis fleet, which are based on 
CAFE or FE compliance data. For subsequent technology changes, we apply 
incremental effectiveness changes to the absolute fuel economy level of 
the previous technology configuration. Therefore, for a technically 
sound analysis, it is most important that the differences in BSFC among 
the engine maps be accurate, and not the absolute values of the 
individual engine maps.
    While the fuel economy improvements for most engine technologies in 
the analysis are derived from the database of Autonomie full-vehicle 
simulation results, the analysis incorporates a handful of what we 
refer to as analogous effectiveness values. We use these when we do not 
have an engine map model for a particular technology combination. To 
generate an analogous effectiveness value, we use data from analogous 
technology combinations for which we do have engine map models and 
conduct a pairwise comparison to generate a data set of emulated 
performance values for adding technology to a baseline application. We 
only use analogous

[[Page 56192]]

effectiveness values for four technologies that are all SOHC 
technologies. We determined that the effectiveness results using these 
analogous effectiveness values provided reasonable results. This 
process is discussed further in Chapter 3.1.4.2 of the Draft TSD.
    Figure II-13, Figure II-14, and Figure II-15 show the engine 
technology effectiveness values for all vehicle technology classes. 
These values show the calculated improvement for upgrading only the 
listed engine technology for a given combination of other technologies. 
In other words, the range of effectiveness values seen for each 
specific technology (e.g., TURBO1) represents the addition of the 
TURBO1 technology to every technology combination that could select the 
addition of TURBO1.
    These values are derived from the ANL Autonomie simulation dataset 
and the righthand side Y-axis shows the number of Autonomie simulations 
that achieve each percentage effectiveness improvement point. The 
dashed line and grey shading indicate the median and 1.5X interquartile 
range (IQR), which is a helpful metric to use to identify outliers. 
Comparing these histograms to the box and whisker plots presented in 
prior CAFE program rule documents, it is much easier to see that the 
number of effectiveness outliers is extremely small.
    Some advanced engine technologies have values that indicate low 
effectiveness. We determined the low effectiveness resulted from the 
application of advanced engines to existing P2 architectures. This 
effect is expected and illustrates the importance of using the full 
vehicle modeling to capture interactions between technologies, and 
capture instances of both complimentary technologies and non-
complimentary technologies. In this instance, the P2 powertrain 
improves fuel economy, in part, by allowing the engine to spend more 
time operating at efficient engine speed and load conditions. This 
reduces the advantage of adding advanced engine technologies, which 
also improve fuel economy, by broadening the range of speed and load 
conditions for the engine to operate at high efficiency. This 
redundancy in fuel savings mechanism results in a lower effectiveness 
when the technologies are added to each other.
BILLING CODE 4910-59-P

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    The engine costs in our analysis are the product of engine DMCs, 
RPE, the LE, and updating to a consistent dollar year. We sourced 
engine DMCs from multiple sources, but primarily from the 2015 NAS 
report.\230\ For VTG and VTGE technologies (i.e., Miller Cycle), we 
used cost data from a FEV technology cost assessment performed for 
ICCT,\231\ aggregated using individual component and system costs from 
the 2015 NAS report. We considered costs from the 2015 NAS report that 
referenced a Northeast States Center for a Clean Air Future (NESCCAF) 
2004 report,\232\ but believe the reference material from the FEV 
report provides more updated cost estimates for the VTG technology.
---------------------------------------------------------------------------

    \230\ 2015 NAS Report, Table S.2, p. 7-8.
    \231\ Isenstadt, A. et al. 2016. Downsized, Boosted Gasoline 
Engines. Working Paper. ICCT 2016-22: p. 28.
    \232\ NESCCAF. 2004. Reducing Greenhouse Gas Emissions from 
Light-Duty Motor Vehicles. Available at: http://www.nesccaf.org/documents/rpt040923ghglightduty.pdf. (Accessed: May 31, 2023).
---------------------------------------------------------------------------

    All engine technology costs start with a base engine cost, and then 
additional technology costs are based on cylinder and bank count and 
configuration; the DMC for each engine technology is a function of unit 
cost times either the number of cylinders or number of banks, based on 
how the technology is applied to the system. The total costs for all 
engine technologies in all MYs across all vehicle classes can be found 
in the Technologies Input file.
2. Transmission Paths
    Transmissions transmit torque generated by the engine from the 
engine to the wheels. Transmissions primarily use two mechanisms to 
improve fuel efficiency: (1) a wider gear range, which allows the 
engine to operate longer at higher efficiency speed-load points; and 
(2) improvements in friction or shifting efficiency (e.g., improved 
gears, bearings, seals, and other components), which reduce parasitic 
losses.
    We only model automatic transmissions in both the LD and HDPUV 
analyses. The four subcategories of automatic transmissions that we 
model in the LD analysis include traditional automatic transmissions 
(AT), dual clutch transmissions (DCT), continuously variable 
transmissions (CVT and eCVT), and direct drive (DD) transmissions.\233\ 
We also include high efficiency gearbox (HEG) technology improvements 
as options to the transmission technologies (designated as L2 or L3 in 
our analysis to indicate level of technology improvement).\234\ There 
has been a significant reduction in manual transmissions over the years 
and they made up less than 1% of the vehicles produced in MY 2021.\235\ 
Due to the trending decline of manual transmissions and their current 
low production volumes, we have removed

[[Page 56196]]

manual transmissions from this analysis.
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    \233\ Note that eCVT and DD transmissions are only coupled with 
electrified drivetrains and are therefore not included as a 
standalone transmission option on the CAFE Model's technology 
pathways.
    \234\ See 2015 NAS Report, at 191. HEG improvements for 
transmissions represent incremental advancements in technology that 
improve efficiency, such as reduced friction seals, bearings and 
clutches, super finishing of gearbox parts, and improved 
lubrication. These advancements are all aimed at reducing frictional 
and other parasitic loads in transmissions to improve efficiency. We 
consider three levels of HEG improvements in this analysis based on 
the National Academy of Sciences (NAS) 2015 recommendations, and CBI 
data.
    \235\ 2022 EPA Automotive Trends Report.
---------------------------------------------------------------------------

    We only model ATs in the HDPUV analysis because, except for DD 
transmissions that are only included as part of an electrified 
drivetrain, all HDPUV fleet baseline vehicles use ATs. In addition, 
from an engineering standpoint, DCTs and CVTs are not suited for HDPUV 
work requirements, as discussed further below. The HDPUV automatic 
transmissions work in the same way as the LD ATs and are labeled the 
same, but they are sized and mapped, in the Autonomie effectiveness 
modeling,\236\ to account for the additional work, durability, and 
payload these vehicles are designed to conduct. The HDPUV transmissions 
are sized with larger clutch packs, higher hydraulic line pressures, 
different shift schedules, larger torque converter and different lock 
up logic, and stronger components when compared to their LD 
counterparts. Chapter 3.2.1 of the Draft TSD discusses the technical 
specifications of the four different AT subtypes in more detail. Figure 
II-16 and Figure II-17 show the LD and HDPUV transmission technology 
paths.
---------------------------------------------------------------------------

    \236\ ANL--All Assumptions_Summary_NPRM_2206.xlsx, ANL--Data 
Dictionary_NPRM_2206.xlsx, ANL--Summary of Main Component 
Performance, Assumptions_NPRM_2206.xlsx. ANL--All Assumptions 
Summary--(2b-3) FY22 NHTSA--220811.xlsx, ANL--Data Dictionary--(2b-
3) FY22 NHTSA--2200811.xlsx, ANL--Summary of Main Component 
Performance Assumptions--(2b-3) FY22 NHTSA--220811.xlsx.
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[[Page 56197]]


[GRAPHIC] [TIFF OMITTED] TP17AU23.026

    To assign transmission technologies to vehicles in the baseline 
fleets, we identify which Autonomie transmission model is most like a 
vehicle's real-world transmission, considering the transmission's 
configuration, costs, and effectiveness. Like with engines, we use 
manufacturer CAFE compliance submissions and publicly available 
information to assign transmissions to vehicles and determine which 
platforms share transmissions. To link shared transmissions in a 
manufacturer's fleet, we use transmission codes that include 
information about the manufacturer, drive configuration, transmission 
type, and number of gears. Just like manufacturers share transmissions 
in multiple vehicles, the CAFE Model will treat transmissions as 
``shared'' if they share a transmission code and transmission 
technologies will be adopted together.
    While identifying an ATs gear count is fairly easy, identifying HEG 
levels for ATs and CVTs is more difficult. We reviewed the age of the 
transmission design, relative performance versus previous designs, and 
technologies incorporated to assign an HEG level. There are no HEG 
Level 3 automatic transmissions in either the LD or the HDPUV baseline 
fleets. For the LD analysis we found all 7-speed, all 9-speed, all 10-
speed, and some 8-speed automatic transmissions to be advanced 
transmissions operating at HEG Level 2 equivalence. We assigned eight-
speed automatic transmissions and CVTs newly introduced for the LD 
market in MY 2016 and later as HEG Level 2. All other automatic 
transmissions are assigned to their respective transmissions baseline 
level (i.e., AT6, AT8, and CVT). For DCTs, the number of gears in the 
assignments for DCTs usually match the number of gears listed by the 
data sources, with some exceptions (we assign dual-clutch transmissions 
with seven and nine gears to DCT6 and DCT8 respectively). We assigned 
vehicles in either the LD or HDPUV analyses fleets with a fully 
electric powertrain a DD transmission. We assigned any vehicle in the 
LD analysis fleet with a power-split hybrid (SHEVPS) powertrain an 
electronic continuously variable transmission (eCVT). Finally, we 
assigned the limited number of manual transmissions in the LD fleet as 
DCTs, as we did not model manual transmissions in Autonomie for this 
analysis.
    Most transmission adoption features are instituted through 
technology path logic (i.e., decisions about how less advanced 
transmissions of the same type can advance to more advanced 
transmissions of the same type). Technology pathways are designed to 
prevent ``branch hopping''--changes in transmission type that would 
correspond to significant changes in transmission architecture--for 
vehicles that are relatively advanced on a given pathway. For example, 
any automatic transmission with more than five gears cannot move to a 
dual-clutch transmission. We also prevent ``branch hopping'' as a proxy 
for stranded capital, which is discussed in more detail in Section II.C 
and Chapter 2.5 of the Draft TSD. The LD and HDPUV transmission paths 
are shown above in Figure II-16 and Figure II-17.
    For the LD analysis, the automatic transmission path precludes 
adoption of other transmission types once a platform progresses past an 
AT8. We use this restriction to avoid the significant level of stranded 
capital loss that could result from adopting a completely different 
transmission type shortly after adopting an advanced transmission, 
which would occur if a different transmission type were adopted after 
AT8 in the rulemaking timeframe. Vehicles that did not start out with 
AT7L2 transmissions cannot adopt that technology in the model. It is 
likely that other vehicles will not adopt the AT7L2 technology, as 
vehicles that have moved to more advanced automatic transmissions have 
overwhelmingly moved to 8-speed and 10-speed transmissions.\237\
---------------------------------------------------------------------------

    \237\ 2022 EPA Automotive Trends Report, at p. 66, Figure 4.21.
---------------------------------------------------------------------------

    CVT adoption is limited by technology path logic and is only 
available in the LD fleet analysis and therefore, not in the technology 
path for the HDPUV analysis. Vehicles that do not originate with a CVT 
or vehicles

[[Page 56198]]

with multispeed transmissions beyond AT8 in the baseline fleet cannot 
adopt CVTs. Vehicles with multispeed transmissions greater than AT8 
demonstrate increased ability to operate the engine at a highly 
efficient speed and load. Once on the CVT path, the platform is only 
allowed to apply improved CVT technologies. Due to the limitations of 
current CVTs, discussed in Draft TSD Chapter 3.2, this analysis 
restricts the application of CVT technology on LDVs with greater than 
300 lb.-ft of engine torque. This is because of the higher torque 
(load) demands of those vehicles and CVT torque limitations based on 
durability constraints. We believe the 300 lb.-ft restriction 
represents an increase over current levels of torque capacity that is 
likely to be achieved during the rule making timeframe. This 
restriction aligns with CVT application in the baseline fleet, in that 
CVTs are only witnessed on vehicles with under 280 lb.-ft of 
torque.\238\ Additionally, this restriction is used to avoid stranded 
capital. Finally, the analysis allows vehicles in the baseline fleet 
that have DCTs to apply an improved DCT and allows vehicles with an AT5 
to consider DCTs. Drivability and durability issues with some DCTs have 
resulted in a low relative adoption rate over the last decade. This is 
also broadly consistent with manufacturers' technology choices.\239\ 
DCTs are not a selectable technology for the HDPUV analysis.
---------------------------------------------------------------------------

    \238\ Market Data Input File.
    \239\ 2022 EPA Automotive Trends Report, at p. 66, Figure 4.21.
---------------------------------------------------------------------------

    Autonomie models transmissions as a sequence of mechanical torque 
gains. The torque and speed are multiplied and divided, respectively, 
by the current ratio for the selected operating condition. Furthermore, 
torque losses corresponding to the torque/speed operating point are 
subtracted from the torque input. Torque losses are defined based on a 
three-dimensional efficiency lookup table that has the following 
inputs: input shaft rotational speed, input shaft torque, and operating 
condition. We populate transmission template models in Autonomie with 
characteristics data to model specific transmissions.\240\ 
Characteristics data are typically tabulated data for transmission gear 
ratios, maps for transmission efficiency, and maps for torque converter 
performance, as applicable. Different transmission types require 
different quantities of data. The characteristics data for these models 
come from peer-reviewed sources, transmission and vehicle testing 
programs, results from simulating current and future transmission 
configurations, and confidential data obtained from OEMs and 
suppliers.\241\ We model HEG improvements by modeling improvements to 
the efficiency map of the transmission. As an example, the baseline AT8 
model data comes from a transmission characterization study.\242\ The 
AT8L2 has the same gear ratios as the AT8, however, we improve the gear 
efficiency map to represent application of the HEG level 2 
technologies. The AT8L3 models the application of HEG level 3 
technologies using the same principle, further improving the gear 
efficiency map over the AT8L2 improvements. Each transmission (15 for 
the LD analysis and 6 for the HDPUV analysis) is modeled in Autonomie 
with defined gear ratios, gear efficiencies, gear spans, and unique 
shift logic for the technology configuration the transmission is 
applied to. These transmission maps are developed to represent the gear 
counts and span, shift and torque converter lockup logic, and 
efficiencies that can be seen in the fleet, along with upcoming 
technology improvements, all while balancing key attributes such as 
drivability, fuel economy, and performance neutrality. This modeling is 
discussed in detail in Chapter 3.2 of the Draft TSD and the CAFE 
Analysis Autonomie Documentation chapter titled ``Autonomie--
Transmission Model.''
---------------------------------------------------------------------------

    \240\ ANL--All Assumptions_Summary_NPRM_2206.xlsx, ANL--Data 
Dictionary_NPRM_2206.xlsx, ANL--Summary of Main Component 
Performance, Assumptions_NPRM_2206.xlsx. ANL--All Assumptions 
Summary--(2b-3) FY22 NHTSA--220811.xlsx, ANL--Data Dictionary--(2b-
3) FY22 NHTSA--2200811.xlsx, ANL--Summary of Main Component 
Performance Assumptions--(2b-3) FY22 NHTSA--220811.xlsx.
    \241\ Downloadable Dynamometer Database.: https://www.anl.gov/energy-systems/group/downloadable-dynamometer-database. (Accessed: 
May 31, 2023); Kim, N. et al. 2014. Advanced Automatic Transmission 
Model Validation Using Dynamometer Test Data. SAE 2014-01-1778. SAE 
World Congress: Detroit, MI.; Kim, N. et al. 2014. Development of a 
Model of the Dual Clutch Transmission in Autonomie and Validation 
With Dynamometer Test Data. International Journal of Automotive 
Technologies Volume 15, Issue 2: pp 263-71.
    \242\ CAFE Analysis Autonomie Documentation chapter titled 
``Autonomie--Transmission Model.''
---------------------------------------------------------------------------

    The effectiveness values for the transmission technologies, for all 
LD and HDPUV technology classes, are shown in Figure II-18, Figure II-
19, and Figure II-20. Note that the effectiveness for the AT5, eCVT and 
DD technologies is not shown. The DD and eCVT transmissions do not have 
standalone effectiveness values because those technologies are only 
implemented as part of electrified powertrains. The AT5 has no 
effectiveness values because it is a baseline technology against which 
all other transmission technologies are compared.

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[[Page 56201]]


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BILLING CODE 4910-59-C
    Our transmission DMCs come from the 2015 NAS report and studies 
cited therein. The LD costs are taken almost directly from the 2015 NAS 
report adjusted to the current dollar year or for the appropriate 
number of gears. We applied a 20% cost increase for HDPUV transmissions 
based on comparing the additional weight, torque capacity, and 
durability required in the HDPUV segment. Chapter 3.2 of the Draft TSD 
discusses the specific 2015 NAS report costs used to generate our 
transmission cost estimates, and all transmission costs across all MYs 
can be found in CAFE Model's Technologies Input file. We have used the 
2015 NAS report transmission costs for the last several LD CAFE Model 
analyses (since reevaluating all transmission costs for the 2020 final 
rule) and have received no comments or feedback on these costs. We seek 
comment on our approach to estimating all transmission costs, but in 
particular on HDPUV transmission costs for this analysis, in addition 
to any publicly available data from manufacturers or reports on the 
cost of HDPUV transmissions.
3. Electrification Paths
    The electrification paths include a set of technologies that share 
common electric powertrain components, like batteries and electric 
motors, for certain vehicle functions that were traditionally powered 
by combustion engines. While all vehicles (including conventional ICE 
vehicles) use batteries and electric motors in some form, some 
component designs and powertrain architectures contribute to greater 
levels of electrification than others--allowing the vehicle to be less 
reliant on gasoline or other fuel.
    Unlike other technologies in the analysis, including other 
electrification technologies, Congress placed specific limitations on 
how we consider the fuel economy of PHEVs and BEVs when setting CAFE 
standards.\243\ We implement these restrictions in the CAFE Model by 
using fuel economy values that assume ``charge sustaining'' (gasoline-
only) PHEV operation,\244\ and by restricting technologies that convert 
a vehicle to a BEV or a FCEV from being applied during ``standard-
setting'' years.\245\ However, there are several reasons why we must 
still accurately model PHEVs and BEVs in the analysis; these reasons 
are discussed in detail throughout this preamble and, in particular, in 
Sections III and V. In brief: we must consider the existing fleet fuel 
economy level in calculating the maximum feasible fuel economy level 
that manufacturers can achieve in future years. Accurately calculating 
the pre-existing fleet fuel economy level is crucial because it marks 
the starting point for determining what further efficiency gains will 
be feasible during the rulemaking timeframe. As discussed in detail 
above and in Chapter 2.2 of the Draft TSD, PHEVs, BEVs, and FCEVs 
currently exist in manufacturer's fleets

[[Page 56202]]

and count towards manufacturer's compliance fuel economy values.
---------------------------------------------------------------------------

    \243\ 49 U.S.C. 32902(h)(1), (2). In determining maximum 
feasible fuel economy levels, ``the Secretary of Transportation--(1) 
may not consider the fuel economy of dedicated automobiles; [and] 
(2) shall consider dual fueled automobiles to be operated only on 
gasoline or diesel fuel.''
    \244\ We have two sets of fuel consumption improvement data from 
ANL: one that does not include charge depleting and charge 
sustaining for PHEVS, and one with both.
    \245\ CAFE Model Documentation at S4.6 Technology Fuel Economy 
Improvements.
---------------------------------------------------------------------------

    In addition to accurately capturing the ``baseline fleet'' of 
vehicles in a given MY, we must capture a regulatory ``no action'' 
baseline in each MY; that is, the regulatory baseline captures what the 
world will be like if our rule is not adopted, to accurately capture 
the costs and benefits of CAFE standards. The ``no-action'' baseline 
includes our representation of the existing fleet of vehicles (i.e., 
the LD and HDPUV baseline fleets) and (with some restrictions) our 
representation of manufacturer's fleets in the absence of our 
standards. Specifically, we assume that in the absence of CAFE and 
HDPUV FE standards, manufacturers will produce certain BEVs to comply 
with California's ACCs and ACT program. Accounting for electrified 
vehicles that manufacturers produced in response to state regulatory 
requirements improves the accuracy of the analysis of the costs and 
benefits of additional technology added to vehicles in response to CAFE 
standards, while adhering to the statutory prohibition against 
considering the fuel economy gains that could be achieved if 
manufacturers create new dedicated automobiles to comply with the CAFE 
standards.
    Next, the costs and benefits of CAFE standards do not end in the 
MYs for which we are setting standards. Vehicles produced in standard-
setting years, e.g., MYs 2027 and beyond in this analysis, will 
continue to have effects for years after they are produced as the 
vehicles are sold and driven. To accurately capture the costs and 
benefits of vehicles subject to the standards in future years, the CAFE 
Model projects compliance through MY 2050. Outside of the standard-
setting years, we model the extent to which manufacturers could produce 
electrified vehicles, in order to improve the accuracy and realism of 
our analysis in situations where statute does not prevent us from doing 
so. Finally, we do consider the effects of electrified vehicle adoption 
in the CAFE Model under a ``real-world'' scenario where we lift EPCA/
EISA's restrictions on our decision-making. This ``real-world'' 
analysis forms the basis of our NEPA analysis, so that we can consider 
the actual environmental impacts of our actions in the decision-making 
process.\246\
---------------------------------------------------------------------------

    \246\ 40 CFR 1500.1(a).
---------------------------------------------------------------------------

    For those reasons, we must still accurately model electrified 
vehicles. That said, PHEVs, BEVs, and FCEVs only represent a portion of 
the electrified technologies that we include in the analysis. We 
discuss the range of modeled electrified technologies below and in 
detail in Chapter 3.3.1 of the Draft TSD.
    Among the simpler configurations with the fewest electrification 
components, micro HEV technology (SS12V) uses a 12-volt system that 
simply restarts the engine from a stop. Mild HEVs use a 48-volt belt 
integrated starter generator (BISG) system that restarts the vehicle 
from a stop and provides some regenerative braking functionality.\247\ 
Mild HEVs are often also capable of minimal electric assist to the 
engine on take-off.
---------------------------------------------------------------------------

    \247\ See 2015 NAS Report, at 130. (``During braking, the 
kinetic energy of a conventional vehicle is converted into heat in 
the brakes and is thus lost. An electric motor/generator connected 
to the drivetrain can act as a generator and return a portion of the 
braking energy to the battery for reuse. This is called regenerative 
braking. Regenerative braking is most effective in urban driving and 
in the urban dynamometer driving schedule (UDDS) cycle, in which 
about 50 percent of the propulsion energy ends up in the brakes (NRC 
2011, 18).'').
---------------------------------------------------------------------------

    Strong hybrid-electric vehicles (SHEVs) have higher system 
voltages, compared to mild hybrids with BISG systems, and are capable 
of engine start/stop and regenerative braking, electric motor assist of 
the engine at higher speeds and power demands, and can provide limited 
all-electric propulsion. Common SHEV powertrain architectures, 
classified by the interconnectivity of common electrified vehicle 
components, include both a series-parallel architecture by power-split 
device (SHEVPS) as well as a parallel architecture (P2 \248\). P2s--
although enhanced by the electrification components, including just one 
electric motor--remains fundamentally similar to a conventional 
powertrain.\249\ In contrast, SHEVPS is considerably different than a 
conventional powertrain; SHEVPSs use two electric motors, which allows 
the use of a lower-power-density engine. This results in a higher 
potential for fuel economy improvement compared to a P2, although the 
SHEVPS' engine power density is lower.\250\ Or, put another way, ``[a] 
disadvantage of the power split architecture is that when towing or 
driving under other real-world conditions, performance is not 
optimum.'' \251\ In contrast, ``[o]ne of the main reasons for using 
parallel hybrid architecture is to enable towing and meet maximum 
vehicle speed targets.'' \252\ This is an important distinction to 
comprehend to understand why we allow certain types of vehicles to 
adopt P2 powertrains and not SHEVPS powertrains, and to understand why 
we include only P2 architectures in the HDPUV analysis. Both concepts 
are discussed further below.
---------------------------------------------------------------------------

    \248\ Readers familiar with the last CAFE Model analysis may 
remember this category of powertrains referred to as ``SHEVP2s.'' 
Now that the SHEVP2 pathway has been split into three pathways based 
on the paired ICE technology, we refer to this broad category of 
technologies as ``P2s.''
    \249\ Kapadia, J. et al. 2017. Powersplit or Parallel--Selecting 
the Right Hybrid Architecture. SAE International Journal of 
Alternative Power 6(1). Available at: https://doi.org/10.4271/2017-01-1154. (Accessed: May 31, 2023) (Parallel hybrids architecture 
typically adds the electrical system components to an existing 
conventional powertrain).
    \250\ Kapadia, J. et al. 2017. Powersplit or Parallel--Selecting 
the Right Hybrid Architecture. SAE International Journal of 
Alternative Power 6(1). Available at: https://doi.org/10.4271/2017-01-1154. (Accessed: May 31, 2023).
    \251\ 2015 NAS report, at 134.
    \252\ Kapadia, J. et al. 2017. Powersplit or Parallel--Selecting 
the Right Hybrid Architecture. SAE International Journal of 
Alternative Power 6(1). Available at: https://doi.org/10.4271/2017-01-1154. (Accessed: May 31, 2023).
---------------------------------------------------------------------------

    PHEVs utilize a combination gasoline-electric powertrain, like that 
of a SHEV, but have the ability to plug into the electric grid to 
recharge the battery, like that of a BEV; this contributes to all-
electric mode capability in both blended and non-blended PHEVs.\253\ 
The analysis includes PHEVs with an AER of 20 and 50 miles to encompass 
the range of PHEV AER in the market today. BEVs have an all-electric 
powertrain and use only batteries for the source of propulsion energy. 
BEVs with ranges of 200 to more than 350 miles are used in the 
analysis. Finally, FCEVs are another form of electrified vehicle that 
have a fully electric powertrain that uses a fuel cell system to 
convert hydrogen fuel into electrical energy. Table II-9 and Table II-
10 list every electrification technology considered in the analysis, 
including its acronym and a brief description. For brevity, we refer to 
technologies by their acronyms in this section.
---------------------------------------------------------------------------

    \253\ Some PHEVs operate in charge-depleting mode (i.e., 
``electric-only'' operation--depleting the high-voltage battery's 
charge) before operating in charge-sustaining mode (similar to 
strong hybrid operation, the gasoline and electric powertrains work 
together), while other (blended) PHEVs switch between charge-
depleting mode and charge-sustaining mode during operation.

[[Page 56203]]



        Table II-9--Light-Duty Electrification Path Technologies
------------------------------------------------------------------------
            Technology                           Description
------------------------------------------------------------------------
SS12V.............................  12-Volt Stop-Start (Micro Hybrid-
                                     Electric Vehicle).
BISG..............................  48V Belt Mounted Integrated Starter/
                                     Generator (Mild Hybrid-Electric
                                     Vehicle).
SHEV-P2SGDID......................  P2 Strong Hybrid-Electric Vehicle
                                     with a Dual Over-Head Cam Engine
                                     and Gasoline Direct Injection.
SHEV-P2SGDIS......................  P2 Strong Hybrid-Electric Vehicle
                                     with a Single Over-Head Cam Engine
                                     and Gasoline Direct Injection.
SHEV-P2TRB1.......................  P2 Strong Hybrid-Electric Vehicle
                                     with a TURBO1 Powertrain.
SHEV-P2TRB2.......................  P2 Strong Hybrid-Electric Vehicle
                                     with a TURBO2 Powertrain.
SHEV-P2TRBE.......................  P2 Strong Hybrid-Electric Vehicle
                                     with a TURBOE Powertrain.
SHEV-P2HCR........................  P2 Strong Hybrid-Electric Vehicle
                                     with a High Compression Ratio
                                     Powertrain.
SHEV-P2HCRE.......................  P2 Strong Hybrid-Electric Vehicle
                                     with an E-High Compression Ratio
                                     Powertrain.
SHEV-PS...........................  Power Split (PS) Strong Hybrid/
                                     Electric Vehicle.
PHEV20PS..........................  Plug-In Hybrid with Power-Split
                                     device and 20-mile All Electric
                                     Range.
PHEV50PS..........................  Plug-In Hybrid with Power-Split
                                     device and 50-mile All Electric
                                     Range.
PHEV20T...........................  PHEV20 with Turbo Engine and 20-mile
                                     All Electric Range.
PHEV50T...........................  PHEV50 with Turbo Engine and 50-mile
                                     All Electric Range.
PHEV20H...........................  PHEV20 with High Compression Ratio
                                     Engine and 20-mile All Electric
                                     Range.
PHEV50H...........................  PHEV50 with High Compression Ratio
                                     Engine and 50-mile All Electric
                                     Range.
BEV1..............................  ~200-mile Battery Electric Vehicle
                                     BEV1LD <= 250 miles.
BEV2..............................  ~250-mile Battery Electric Vehicle
                                     225 miles < BEV2LD <= 275 miles.
BEV3..............................  ~300-mile Battery Electric Vehicle
                                     275 miles < BEV3LD <= 350 miles.
BEV4..............................  ~400-mile Battery Electric Vehicle
                                     350 miles < BEV3LD.
FCEV..............................  Fuel Cell Electric Vehicle.
------------------------------------------------------------------------


          Table II-10--HDPUV Electrification Path Technologies
------------------------------------------------------------------------
            Technology                           Description
------------------------------------------------------------------------
SS12V.............................  12-Volt Stop-Start (Micro Hybrid-
                                     Electric Vehicle).
BISG..............................  48V Belt Mounted Integrated Starter/
                                     Generator (Mild Hybrid-Electric
                                     Vehicle).
SHEV-P2SGDIS......................  P2 Strong Hybrid-Electric Vehicle
                                     with a Single Over-Head Cam Engine
                                     and Gasoline Direct Injection.
PHEV50H \254\.....................  PHEV50 with a Single Over-Head Cam
                                     Engine and Gasoline Direct
                                     Injection and 50-mile All Electric
                                     Range.
BEV1..............................  Battery Electric Vehicle: 150-mile
                                     Range for Vans and 200-mile Range
                                     for Pickups.
BEV2..............................  Battery Electric Vehicle: 250-mile
                                     Range for Vans and 300-mile Range
                                     for Pickups.
FCEV..............................  Fuel Cell Electric Vehicle.
------------------------------------------------------------------------

    Readers familiar with previous LD CAFE analyses will notice that we 
have increased the number of engine options available for strong 
hybrid-electric vehicles and plug-in hybrid-electric vehicles. As 
discussed above, this better represents the diversity of different 
hybrid architectures and engine options available in the real world for 
strong and PHEVs, while still maintaining a reasonable level of 
analytical complexity. In addition, we now refer to the BEV options as 
BEV1, 2, 3, and 4, rather than by their range assignments as in the 
previous analysis, to accommodate using the same model code for the LD 
and HDPUV analyses. Note that BEV1 and BEV2 have different range 
assignments in the LD and HDPUV analyses; further, within the HDPUV 
fleet, different range assignments exist for HD pickups and HD vans.
---------------------------------------------------------------------------

    \254\ Note that the HDPUV PHEV is labeled ``PHEV50H'' but that 
is only so it can use the designated PHEV50H ``box'' on the 
technology tree. The HDPUV PHEV engine is a basic single overhead 
cam engine with GDI, as described in the table.
---------------------------------------------------------------------------

    In the CAFE Model, HDPUVs only have one strong hybrid engine/
powertrain option, and one PHEV option.\255\ The P2 architecture 
supports high payload and high towing requirements versus other types 
of hybrid architecture,\256\ which are important considerations for 
HDPUV commercial operations. The mechanical connection between the 
engine, transmission, and P2 hybrid systems enables continuous power 
flow to be able to meet high towing weights and loads at the cost of 
system efficiency. We do not allow engine downsizing in this setup in 
so that when the battery storage system is depleted, the vehicle is 
still able to operate. We picked the P2 strong hybrid architecture for 
HDPUV PHEVs because although there are currently no PHEV HDPUVs in the 
market to base a technology choice, we believe that the P2 strong 
hybrid architecture would more likely be picked than other architecture 
options. This is because, as discussed above, the P2 architecture ``can 
be integrated with existing conventional powertrain systems that 
already meet the additional attribute requirements of these large 
vehicle segments.'' \257\
---------------------------------------------------------------------------

    \255\ Note that while the HDPUV PHEV option is labeled 
``PHEV50H'' in the technology pathway, it actually uses a basic 
engine. This is so the same technology pathway can be used in the LD 
and HDPUV CAFE Model analyses.
    \256\ Kapadia, J. et al. 2017. Powersplit or Parallel--Selecting 
the Right Hybrid Architecture. SAE International Journal of 
Alternative Power 6(1): pp. 68-76. Available at: https://doi.org/10.4271/2017-01-1154. (Accessed: May 31, 2023) (Using current 
powersplit design approaches, critical attribute requirements of 
larger vehicle segments, including towing capability, performance 
and higher maximum vehicle speeds, can be difficult and in some 
cases impossible to meet. Further work is needed to resolve the 
unique challenges of adapting powersplit systems to these larger 
vehicle applications. Parallel architectures provide a viable 
alternative to powersplit for larger vehicle applications because 
they can be integrated with existing conventional powertrain systems 
that already meet the additional attribute requirements of these 
large vehicle segments).
    \257\ Kapadia, J. et al. 2017. Powersplit or Parallel--Selecting 
the Right Hybrid Architecture. SAE International Journal of 
Alternative Power 6(1): pp. 68-76. Available at: https://doi.org/10.4271/2017-01-1154. (Accessed: May 31, 2023).

---------------------------------------------------------------------------

[[Page 56204]]

    We only include one HDPUV PHEV option as there are no PHEVs in the 
baseline HDPUV fleet, and there are no announcements from major 
manufacturers that indicate this a pathway that they will pursue in the 
short term.\258\ We believe this is in part because PHEVs, which are 
essentially two separate powertrains combined, can decrease HDPUV 
capability by increasing the curb weight of the vehicle and reducing 
cargo capacity. A manufacturer's ability to use PHEVs in the HDPUV 
segment is highly dependent on the load requirements and the duty cycle 
of the vehicle. However, in the right operation, HDPUV PHEVs can have a 
cost-effective advantage over their conventional 
counterparts.259 260 261 More specifically, there would be a 
larger fuel economy benefit the more the vehicle could rely on its 
electric operation, with partial help from the ICE; examples of duty 
cycles where this would be the case include short delivery applications 
or construction trucks that drive between work sites in the same city. 
Accordingly, we do think that PHEVs can be a technology option for 
adoption in the rulemaking timeframe. We picked a 50-mile AER for this 
segment based on discussions with experts at ANL, who were also 
involved in DOE projects and provided guidance for this 
segment.262 263
---------------------------------------------------------------------------

    \258\ We recognize that there are some third-party companies 
that have converted HDPUVs into PHEVs, however, HDPUV incomplete 
vehicles that are retrofitted with electrification technology in the 
aftermarket are not regulated under this rulemaking unless the 
manufacturer optionally chooses to certify them as a complete 
vehicle. See 49 CFR 523.7.
    \259\ National Renewable Energy Laboratory. 2023. Electric and 
Plug-in Hybrid Electric Vehicle Publications. Available at: https://www.nrel.gov/transportation/fleettest-publications-electric.html. 
(Accessed: May 31, 2023).
    \260\ For the purpose of the Fuel Efficiency regulation, HDPUVs 
are assessed on the 2-cycle test procedure similar to the LDVs. The 
GVWR does not exceed 14,000 lbs in this segment.
    \261\ Birky, A. et al. 2017. Electrification Beyond Light Duty: 
Class 2b-3 Commercial Vehicles. Final Report. ORNL/TM-2017/744. 
Available at: https://doi.org/10.2172/1427632. (Accessed: May 31, 
2023).
    \262\ DOE, Vehicle Technologies Office. 2023. 21st Century Truck 
Partnership. Available at: https://www.energy.gov/eere/vehicles/21st-century-truck-partnership. (Accessed: May 31, 2023).
    \263\ Islam, E. et al. 2022. A Comprehensive Simulation Study to 
Evaluate Future Vehicle Energy and Cost Reduction Potential. Final 
Report. ANL/ESD-22/6.
---------------------------------------------------------------------------

    Additional information about each technology we considered is 
located in Chapter 3.3.1 of the Draft TSD. We seek comment on the range 
of HDPUV electrification path technologies.
    The full set of LD and HDPUV Electrification Path and Hybrid/
Electric Paths Collection technologies are shown in Figure II-21 and 
Figure II-22 below, respectively.
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    We assigned electrification technologies to vehicles in the 
baseline LD and HDPUV fleets using manufacturer-submitted CAFE 
compliance information, publicly available technical specifications, 
marketing brochures, articles from reputable media outlets, and data 
from Wards Intelligence.\264\ Table II-11 and Table II-12 below show 
the baseline penetration rates of electrification technologies in the 
LD and HDPUV fleets, respectively. Over half the LD fleet has some 
level of electrification, with the vast majority--over 50 percent of 
the fleet--being micro hybrids; BEV3 (>275 miles; <=350 miles) is the 
most common LD BEV technology. The HDPUV fleet has 6.22 percent level 
of electrification with BEV2s (>150 miles; <=250 miles) representing 
all of the electrified vehicles in that fleet, with the remaining 
having a conventional non-electrified powertrain.
---------------------------------------------------------------------------

    \264\ Wards Intelligence. 2022. U.S. Car and Light Truck 
Specifications and Prices, '22 Model Year. Available at: https://wardsintelligence.informa.com/WI966023/US-Car-and-Light-Truck-Specifications-and-Prices-22-Model-Year. (Accessed: May 31, 2023).

                Table II-11--Electrification Technology Penetration Rates in the MY 2022 LD Fleet
----------------------------------------------------------------------------------------------------------------
                                                         Sales volume  with this      Penetration rate  in 2022
             Electrification technology                        technology                baseline fleet (%)
----------------------------------------------------------------------------------------------------------------
None................................................                     4,244,826                         29.52
SS12V...............................................                     7,569,293                         52.63
BISG................................................                       521,786                          3.63
P2..................................................                       245,778                          1.71
SHEVPS..............................................                       745,535                          5.18
PHEV20PS............................................                        31,966                          0.22
PHEV20H.............................................                        50,643                          0.35
PHEV20T.............................................                       132,181                          0.92
PHEV50PS............................................                             0                         0.000
PHEV50H.............................................                        27,776                          0.19
PHEV50T.............................................                           200                         0.001
BEV1................................................                        45,754                          0.32
BEV2................................................                       233,631                          1.62
BEV3................................................                       335,244                          2.33
BEV4................................................                       129,860                          0.90
FCEV................................................                         4,419                          0.03
                                                     -----------------------------------------------------------
    Total...........................................                    14,380,891                           100
----------------------------------------------------------------------------------------------------------------


[[Page 56207]]


              Table II-12--Electrification Technology Penetration Rates in the Baseline HDPUV Fleet
----------------------------------------------------------------------------------------------------------------
                                                         Sales volume  with this        Penetration rate  in
             Electrification technology                        technology                baseline fleet  (%)
----------------------------------------------------------------------------------------------------------------
None................................................                       822,409                         93.78
SS12V...............................................                             0                          0.00
BISG................................................                             0                          0.00
P2..................................................                             0                          0.00
PHEV50H.............................................                             0                          0.00
BEV1................................................                             0                          0.00
BEV2................................................                        54,508                          6.22
FCEV................................................                             0                          0.00
                                                     -----------------------------------------------------------
    Total...........................................                       876,917                           100
----------------------------------------------------------------------------------------------------------------

    Like the other technology pathways, as the CAFE Model adopts 
electrification technologies for vehicles, more advanced levels of 
hybridization or electrification technologies will supersede all prior 
levels, while certain technologies within each level are mutually 
exclusive. The only adoption feature applicable to micro (SS12V) and 
mild (BISG) hybrid technology is path logic; vehicles can only adopt 
micro and mild hybrid technology if the vehicle did not already have a 
more advanced level of electrification.
    The adoption features that we apply to strong hybrid technologies 
include path logic, powertrain substitution, and vehicle class 
restrictions. Per the defined (applicable) technology pathways, SHEVPS, 
P2x, P2TRBx, and the P2HCRx technologies are considered mutually 
exclusive. In other words, when the model applies one of these 
technologies, the others are immediately disabled from future 
application. However, all vehicles on the strong hybrid pathways can 
still advance to one or more of the plug-in technologies, when 
applicable in the modeling scenario (i.e., allowed in the model).
    When the model applies any strong hybrid technology to a vehicle, 
the transmission technology on the vehicle is superseded; regardless of 
the transmission originally present, P2 hybrids adopt an advanced 8-
speed automatic transmission (AT8L2), and PS hybrids adopt a 
continuously variable transmission via power-split device (eCVT). When 
the model applies the P2 technology, the model can consider various 
engine options to pair with the P2 architecture according to existing 
engine path constraints--taking into account relative cost 
effectiveness. For SHEVPS technology, the existing engine is replaced 
with a full time Atkinson cycle engine.\265\ For P2s, we picked the 8-
speed automatic transmission to supersede the vehicle's incoming 
transmission technology. This is because most P2s in the market use an 
8-speed automatic transmission,\266\ therefore it is representative of 
the fleet now. We also think that 8-speed transmissions are 
representative of the transmissions that will continue to be used in 
these hybrid vehicles, as we anticipate manufacturers will continue to 
use these ``off the shelf'' transmissions based on availability and 
ease of incorporation in the powertrain. The eCVT (power-split device) 
is the transmission for SHEVPSs and is therefore the technology we 
picked to supersede the vehicle's prior transmission when adopting the 
SHEVPS powertrain.
---------------------------------------------------------------------------

    \265\ Designated Eng26 in the list of engine map models used in 
the analysis. See Draft TSD Chapter 3.1.1.2.3 for more information.
    \266\ We are aware that some Hyundai vehicles use a 6-speed 
transmission and some Ford vehicles use a 10-speed transmission, but 
on balance we have observed that the majority of P2s use an 8-speed 
transmission.
---------------------------------------------------------------------------

    SKIP logic is also used to constrain adoption for SHEVPS and 
PHEV20/50PS technologies. These technologies are ``skipped'' for 
vehicles with engines \267\ that meet one of the following conditions: 
the engine belongs to an excluded manufacturer; \268\ the engine 
belongs to a pickup truck (i.e., the engine is on a vehicle assigned 
the ``pickup'' body style); the engine's peak horsepower is more than 
405 hp; or if the engine is on a non-pickup vehicle but is shared with 
a pickup. The reasons for these conditions are similar to those for the 
SKIP logic that we apply to HCR engine technologies, discussed in more 
detail in Section II.D.1. In the real world, performance vehicles with 
certain powertrain configurations cannot adopt the technologies listed 
above and maintain vehicle performance without redesigning the entire 
powertrain. It may be helpful to understand why we do not apply SKIP 
logic to P2s and to understand why we do apply SKIP logic to SHEVPSs. 
Remember the difference between P2 and SHEVPS architectures: P2 
architectures are better for ``larger vehicle applications because they 
can be integrated with existing conventional powertrain systems that 
already meet the additional attribute requirements'' of large vehicle 
segments.\269\ No SKIP logic applies to P2s because we believe that 
this type of electrified powertrain is sufficient to meet all of the 
performance requirements for all types of vehicles. Manufacturers have 
proven this now with vehicles like the Ford F-150 Hybrid and Toyota 
Tundra Hybrid.270 271 In contrast, ``[a] disadvantage of the 
power split architecture is that when towing or driving under other 
real-world conditions, performance is not optimum.'' \272\ If we were 
to size (in the Autonomie simulations) the PS motors and engines to 
achieve not ``not optimum'' performance, the electric motors would be 
unrealistically large (on both a size and cost basis), and the 
accompanying engine would also have to be a very large displacement 
engine, which is not characteristic of how vehicle manufacturers apply 
PS IC engines in the real-world. Instead, for vehicle applications that 
have particular performance requirements--defined in our analysis as 
vehicles with engines that belong to an excluded

[[Page 56208]]

manufacturer, engines belonging to a pickup truck or shared with a 
pickup truck, or the engine's peak horsepower is more than 405hp--those 
vehicles can adopt P2 architectures that should be able to handle the 
vehicle's performance requirements.
---------------------------------------------------------------------------

    \267\ This refers to the engine assigned to the vehicle in the 
2022 baseline fleet.
    \268\ Excluded manufacturers included BMW, Daimler, and Jaguar 
Land Rover.
    \269\ Kapadia, J. et al. 2017. Powersplit or Parallel--Selecting 
the Right Hybrid Architecture. SAE International Journal of 
Alternative Power 6(1). Available at: https://doi.org/10.4271/2017-01-1154. (Accessed: May 31, 2023).
    \270\ SAE International. 2021. 2022 Toyota Tundra: V8 Out, Twin-
Turbo Hybrid Takes Over. Last revised: September 22, 2021. Available 
at: https://www.sae.org/news/2021/09/2022-toyota-tundra-gains-twin-turbo-hybrid-power. (Accessed: May 30, 2023).
    \271\ SAE International. 2020. Hybridization the Highlight of 
Ford's All-New 2021 F-150. Last revised: June 30, 2020. Available 
at: https://www.sae.org/news/2020/06/2021-ford-f-150-reveal. 
(Accessed: May 30, 2023).
    \272\ 2015 NAS report, at 134.
---------------------------------------------------------------------------

    LD PHEV adoption is limited only by technology path logic; however, 
in the HDPUV analysis, PHEV technology is not available in the model 
until MY 2025 for HD vans and MY 2027 for HD pickups. As discussed 
above, there are no PHEVs in the baseline HDPUV fleet and there are no 
announcements from major manufacturers that indicate this a pathway 
that they will pursue in the short term; that said, we do believe this 
is a technology that could be beneficial for very specific HDPUV 
applications. However, the technology is fully available for adoption 
by HDPUVs in the rulemaking timeframe (i.e., MYs 2030 and beyond). Note 
that we also conducted two sensitivity cases varying the year that 
HDPUV PHEVs are available in the model, allowing them to be introduced 
in MYs 2025 and 2030. PRIA Chapter 9 shows that under the ``PHEV 
available in MY 2025'' sensitivity case, there are approximately double 
(19.6 percent versus 9.1%) the number of PHEVs in the no-action 
sensitivity case compared to the no-action central case and no-action 
``PHEV available in MY 2030'' case by MY 2038. However, in response to 
CAFE standards, PHEVs increase in all three cases by 1.5 percent. This 
results in functionally no difference in total SCs, total social 
benefits, and accordingly net social benefits from varying the HDPUV 
PHEV availability year, in addition to functionally no difference in 
gasoline consumption, CO2 emissions, and other economic and 
environmental parameters. We seek comment on this assumption, and any 
other information available from manufacturers or other stakeholders on 
the potential that original equipment manufacturers will implement PHEV 
technology prior to MY 2025 for HD vans, and prior to MY 2027 for HD 
pickups.
    The engine and transmission technologies on a vehicle are 
superseded when PHEV technologies are applied. For example, the model 
applies an AT8L2 transmission with all PHEV20T/50T plug-in 
technologies, and the model applies an eCVT transmission for all 
PHEV20PS/50PS and PHEV20H/50H plug-in technologies. A vehicle adopting 
PHEV20PS/50PS receives a hybrid full Atkinson cycle engine, and a 
vehicle adopting PHEV20H/PHEV50H receives an HCR engine. For PHEV20T/
50T, the vehicle receives a TURBO1 engine.
    Adoption of BEVs and FCEVs is limited by both path logic and phase-
in caps. They are applied as end-of-path technologies that supersede 
previous levels of electrification. Phase-in caps, which are defined in 
the CAFE Model Input Files, are percentages that represent the maximum 
rate of increase in penetration rate for a given technology. They are 
accompanied by a phase-in start year, which determines the first year 
the phase-in cap applies. Together, the phase-in cap and start year 
determine the maximum penetration rate for a given technology in a 
given year; the maximum penetration rate equals the phase-in cap times 
the number of years elapsed since the phase-in start year. Note that 
phase-in caps do not inherently dictate how much a technology is 
applied by the model. Rather, they represent how much of the fleet 
could have a given technology by a given year.
    Because BEV1 costs less and has slightly higher effectiveness 
values than other advanced electrification technologies,\273\ the model 
will have vehicles adopt it first, until it is restricted by the phase-
in cap. Table II-13 shows the phase-in caps, phase-in year, and maximum 
penetration rate through 2050 for BEV and FCEV technologies. For 
comparison, we also list the actual penetration rate of each technology 
in the 2022 baseline fleet in the fourth column from the left.
---------------------------------------------------------------------------

    \273\ This is because BEV1 uses fewer batteries and weighs less 
than BEVs with greater ranges.
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[[Page 56209]]


    The LD BEV1 phase-in cap is informed by manufacturers' tendency to 
move away from low-range passenger vehicle offerings in part because of 
potential consumer concern with range anxiety.274 275 276 In 
some cases, the advertised range on EVs may not reflect the actual 
real-world range in cold and hot ambient temperatures and real-world 
driving conditions, affecting the utility of these lower range 
vehicles.\277\ Many manufacturers have told us that the portion of 
consumers willing to accept a vehicle with the lowest modeled range is 
small, with manufacturers targeting range values above BEV1 range.
---------------------------------------------------------------------------

    \274\ Pratt, D. 2021. How Much Do Cold Temperatures Affect an 
Electric Vehicle's Driving Range? Last Revised: Dec. 19, 2021. 
Available at: https://www.consumerreports.org/hybrids-evs/how-much-do-cold-temperatures-affect-an-evs-driving-range-a5751769461. 
(Accessed: May 31, 2023).
    \275\ 2022 EPA Trends Report at page 60.
    \276\ IEA. 2022. Trends in Electric Light-Duty Vehicles. 
Available at: https://www.iea.org/reports/global-ev-outlook-2022/trends-in-electric-light-duty-vehicles. (Accessed: May 31, 2023).
    \277\ AAA. 2019. AAA Electric Vehicle Range Testing. Last 
Revised: Feb. 2019. Available at: https://www.aaa.com/AAA/common/AAR/files/AAA-Electric-Vehicle-Range-Testing-Report.pdf. (Accessed: 
May 31, 2023).
---------------------------------------------------------------------------

    Furthermore, the average BEV range has steadily increased over the 
past decade,\278\ due to battery technological progress increasing 
energy density as well as batteries becoming more cost effective. EPA 
observed in its 2022 Automotive Trends Report that ``the average range 
of new EVs has climbed substantially. In MY 2021, the average new EV is 
projected to have a 298-mile range, or about four times the range of an 
average EV in 2011.'' \279\ Based on the cited examples and basis 
described in this section, the maximum growth rate for LD BEV1s in the 
model is set accordingly low to less than 0.1 percent per year. While 
this rate is significantly lower than that of the other BEV 
technologies, the BEV1 phase-in cap allows the penetration rate of low-
range BEVs to grow by a multiple of what is currently observed in the 
market.
---------------------------------------------------------------------------

    \278\ 2022 EPA Automotive Trends Report, at p. 62, Figure 4.17. 
See also United States DOE Vehicle Technologies Office Fact of the 
Week (FOTW) #1290, In Model Year 2022, the Longest-Range EV Reached 
520 Miles on a Single Charge (May 15, 2023). Available at https://www.energy.gov/eere/vehicles/articles/fotw-1290-may-15-2023-model-year-2022-longest-range-ev-reached-520-miles. (Accessed: May 31, 
2023).
    \279\ 2021 EPA Automotive Trends Report, at p. 58 (citing DOE, 
Vehicle Technologies Office. FOTW #1234, April 18, 2022: Volumetric 
Energy Density of Lithium-ion Batteries Increased by More than Eight 
Times Between 2008 and 2020. Available at: https://www.energy.gov/eere/vehicles/articles/fotw-1234-april-18-2022-volumetric-energy-density-lithium-ion-batteries. (Accessed: May 31, 2023).
---------------------------------------------------------------------------

    For higher BEV ranges (such as that for BEV2 for both LD and 
HDPUVs), phase-in caps are intended to conservatively reflect potential 
challenges in the scalability of BEV manufacturing and implementing BEV 
technology on many vehicle configurations, including larger vehicles. 
In the short term, the penetration of BEVs is largely limited by 
battery material acquisition and manufacturing.\280\ Incorporating 
battery packs with the capacity to provide greater electric range also 
poses its own engineering challenges. Heavy batteries and large packs 
may be difficult to integrate for many vehicle configurations and 
require vehicle structure modifications. Pickup trucks and large SUVs, 
in particular, require higher levels of energy as the number of 
passengers and/or payload increases, for towing and other high-torque 
applications. In the LD analysis, we use the LD BEV3 and BEV4 phase-in 
caps to reflect these transitional challenges and use similar phase-in 
caps for the HDPUV analysis.
---------------------------------------------------------------------------

    \280\ See, e.g., Henze, V. 2022. China's Battery Supply Chain 
Tops BNEF Ranking for Third Consecutive Time, with Canada a Close 
Second. Bloomberg New Energy Finance. Last Revised: Nov. 12, 2022. 
Available at: https://about.bnef.com/blog/chinas-battery-supply-chain-tops-bnef-ranking-for-third-consecutive-time-with-canada-a-close-second/. (Accessed: May 31, 2023).
---------------------------------------------------------------------------

    We seek comment on the BEV phase-in caps for the LD and HDPUV 
analyses. Remember when submitting comments that BEV phase-in caps are 
a tool that we use in the model to allow the model to build higher-
range BEVs (when the modeling scenario allows, as in outside of 
standard-setting years), because if we did not, the model would only 
build BEV1s, as they are the most cost-effective BEV technology. Based 
on the analysis provided above, we believe there is a reasonable 
justification for different BEV phase-in caps based on expected BEV 
ranges in the future.
    The phase-in cap for FCEVs is assigned based on existing market 
share as well as historical trends in FCEV production for LD and HDPUV. 
FCEV production share in the past five years has been extremely low and 
the lack of fueling infrastructure remains a limiting factor \281\--we 
set the phase-in cap accordingly.\282\ As with BEV1, however, the 
phase-in cap still allows for the market share of FCEVs to grow several 
times over.
---------------------------------------------------------------------------

    \281\ DOE, Alternative Fuels Data Center. Hydrogen Refueling 
Infrastructure Development. Available at: https://afdc.energy.gov/fuels/hydrogen_infrastructure.html. (Accessed: May 31, 2023).
    \282\ 2022 EPA Automotive Trends Report, at p. 60, Figure 4.14.
---------------------------------------------------------------------------

    Autonomie determines the effectiveness of each electrified 
powertrain type by modeling the basic components, or building blocks, 
for each powertrain, and then combining the components modularly to 
determine the overall efficiency of the entire powertrain. The 
components, or building blocks, that contribute to the effectiveness of 
an electrified powertrain in the analysis include the vehicle's 
battery, electric motors, power electronics, and accessory loads. 
Autonomie identifies components for each electrified powertrain type 
and then interlinks those components to create a powertrain 
architecture. Autonomie then models each electrified powertrain 
architecture and provides an effectiveness value for each architecture. 
For example, Autonomie determines a BEV's overall efficiency by 
considering the efficiencies of the battery (including charging 
efficiency), the electric traction drive system (the electric machine 
and power electronics), and mechanical power transmission devices.\283\ 
Or, for a PHEV, Autonomie combines a very similar set of components to 
model the electric portion of the hybrid powertrain and then also 
includes the ICE and related power for transmission components.\284\ 
ANL uses data from their Advanced Mobility Technology Laboratory (AMTL) 
to develop Autonomie's electrified powertrain models. The modeled 
powertrains are not intended to represent any specific manufacturer's 
architecture but act as surrogates predicting representative levels of 
effectiveness for each electrification technology. We discuss the 
procedures for modeling each of these sub-systems in detail in the 
Draft TSD and in the CAFE Analysis Autonomie Documentation and include 
a brief summary below.
---------------------------------------------------------------------------

    \283\ Iliev, S. et al. 2023. Vehicle Technology Assessment, 
Model Development, and Validation of a 2021 Toyota RAV4 Prime. 
Report No. DOT HS 813 356. National Highway Traffic Safety 
Administration.
    \284\ See the CAFE Analysis Autonomie Documentation.
---------------------------------------------------------------------------

    The fundamental components of an electrified powertrain's 
propulsion system--the electric motor and inverter--ultimately 
determine the vehicle's performance and efficiency. For this analysis, 
Autonomie employed a set of electric motor efficiency maps created by 
Oak Ridge National Laboratory (ORNL), one for a traction motor and an 
inverter, the other for a motor/generator and inverter.\285\ Autonomie 
also uses test data validations from technical publications to 
determine the peak efficiency of BEVs

[[Page 56210]]

and FCEVs. The electric motor efficiency maps, created from production 
vehicles like the 2007 Toyota Camry hybrid, 2011 Hyundai Sonata hybrid, 
and 2016 Chevrolet Bolt, represent electric motor efficiency as a 
function of torque and motor Rotations Per Minute (RPM). These 
efficiency maps provide nominal and maximum speeds, as well as a 
maximum torque curve. ANL uses the maps to determine the efficiency 
characteristics of the motors, which includes some of the losses due to 
power transfer through the electric machine.\286\ Specifically, ANL 
scales the efficiency maps, specific to powertrain type, to have total 
system peak efficiencies ranging from 96-98 percent \287\--such that 
their peak efficiency value corresponds to the latest state-of-the-art 
technologies, opposed to retaining dated system efficiencies (90-93 
percent).\288\
---------------------------------------------------------------------------

    \285\ Oak Ridge National Laboratory. 2008. Evaluation of the 
2007 Toyota Camry Hybrid Synergy Drive System; Oak Ridge National 
Laboratory. 2011. Annual Progress Report for the Power Electronics 
and Electric Machinery Program.
    \286\ CAFE Analysis Autonomie Documentation chapter titled 
``Vehicle and Component Assumptions--Electric Machines--Electric 
Machine Efficiency Maps.''
    \287\ CAFE Analysis Autonomie Documentation chapter titled 
``Vehicle and Component Assumptions--Electric Machines--Electric 
Machine Peak Efficiency Scaling.''
    \288\ Oak Ridge National Laboratory. 2008. Evaluation of the 
2007 Toyota Camry Hybrid Synergy Drive System; Oak Ridge National 
Laboratory. 2011. Annual Progress Report for the Power Electronics 
and Electric Machinery Program.
---------------------------------------------------------------------------

    Beyond the powertrain components, Autonomie also considers electric 
accessory devices that consume energy and affect overall vehicle 
effectiveness, such as headlights, radiator fans, wiper motors, engine 
control units, transmission control units, cooling systems, and safety 
systems. In real-world driving and operation, the electrical accessory 
load on the powertrain varies depending on how the driver uses certain 
features and the condition in which the vehicle is operating, such as 
for night driving or hot weather driving. However, for regulatory test 
cycles related to fuel economy, the electrical load is repeatable 
because the fuel economy regulations control for these factors. 
Accessory loads during test cycles do vary by powertrain type and 
vehicle technology class, since distinctly different powertrain 
components and vehicle masses will consume different amounts of energy.
    The baseline fleet consists of different vehicle types with varying 
accessory electrical power demand. For instance, vehicles with 
different motor and battery sizes will require different sizes of 
electric cooling pumps and fans to optimally manage component 
temperatures. Autonomie has built-in models that can simulate these 
varying sub-system electrical loads. However, for this analysis, we use 
a fixed (by vehicle technology class and powertrain type), constant 
power draw to represent the effect of these accessory loads on the 
powertrain on the 2-cycle test. We intend and expect that fixed 
accessory load values will, on average, have similar impacts on 
effectiveness as found on actual manufacturers' systems. This process 
is in line with the past analyses.289 290 For this analysis, 
we aggregate electrical accessory load modeling assumptions for the 
different powertrain types (electrified and conventional) and 
technology classes (both LD and HDPUV) from data from the Draft TAR, 
EPA Proposed Determination,\291\ data from manufacturers,\292\ research 
and development data from DOE's Vehicle Technologies 
Office,293 294 295 and DOT-sponsored vehicle benchmarking 
studies completed by ANL's AMTL.
---------------------------------------------------------------------------

    \289\ Technical Assessment Report (July 2016), Chapter 5.
    \290\ EPA Proposed Determination TSD (November 2016), at pp. 2-
270.
    \291\ EPA Proposed Determination TSD (November 2016), at pp. 2-
270.
    \292\ Alliance of Automobile Manufacturers (now Alliance for 
Automotive Innovation) Comments on Draft TAR, at p. 30.
    \293\ DOE, Vehicle Technologies Office. Electric Drive Systems 
Research and Development. Available at: https://www.energy.gov/eere/vehicles/vehicle-technologies-office-electric-drive-systems. 
(Accessed: May 31, 2023).
    \294\ ANL. 2023. Advanced Mobility Technology Laboratory (AMTL). 
Available at: https://www.anl.gov/es/advanced-mobility-technology-laboratory. (Accessed: May 31, 2023).
    \295\ DOE's lab years are ten years ahead of manufacturers' 
potential production intent (e.g., 2020 Lab Year is MY 2030).
---------------------------------------------------------------------------

    Certain technologies' effectiveness for reducing fuel consumption 
requires optimization through the appropriate sizing of the powertrain. 
Autonomie uses sizing control algorithms based on data collected from 
vehicle benchmarking,296 297 and the modeled electrification 
components are sized based on performance neutrality considerations. 
This analysis iteratively minimizes the size of the powertrain 
components to maximize efficiency while enabling the vehicle to meet 
multiple performance criteria. The Autonomie simulations use a series 
of resizing algorithms that contain ``loops,'' such as the acceleration 
performance loop (0-60 mph), which automatically adjusts the size of 
certain powertrain components until a criterion, like the 0-60 mph 
acceleration time, is met. As the algorithms examine different 
performance or operational criteria that must be met, no single 
criterion can degrade; once a resizing algorithm completes, all 
criteria will be met, and some may be exceeded as a necessary 
consequence of meeting others.
---------------------------------------------------------------------------

    \296\ CAFE Analysis Autonomie Documentation chapter titled 
``Vehicle Sizing Process--Vehicle Powertrain Sizing Algorithms--
Light-Duty Vehicles--Conventional Vehicle Sizings Algorithm.''
    \297\ CAFE Analysis Autonomie Documentation chapter titled 
``Vehicle Sizing Process--Vehicle Powertrain Sizing Algorithms--
Heavy-Duty Pickups and Vans--Conventional Vehicle Sizings 
Algorithm.''
    \298\ Enviromental Protection Agency. 2023. How Vehicles are 
Tested. Available at: https://www.fueleconomy.gov/feg/how_tested.shtml. (Accessed: May 31, 2023).
    \299\ CAFE Analysis Autonomie Documentation, Chapter titled 
`Test Procedure and Energy Consumption Calculations'.
    \300\ EPA. 2017. EPA Test Procedures for Electric Vehicles and 
Plug-in Hybrids. Draft Summary. Available at: https://www.fueleconomy.gov/feg/pdfs/EPA%20test%20procedure%20for%20EVs-PHEVs-11-14-2017.pdf. (Accessed: May 31, 2023).
    \301\ 40 CFR part 600.
---------------------------------------------------------------------------

    Autonomie applies different powertrain sizing algorithms depending 
on the type of vehicle considered because different types of vehicles 
not only contain different powertrain components to be optimized, but 
they must also operate in different driving modes. While the 
conventional powertrain sizing algorithm must consider only the power 
of the engine, the more complex algorithm for electrified powertrains 
must simultaneously consider multiple factors, which could include the 
engine power, electric machine power, battery power, and battery 
capacity. Also, while the resizing algorithm for all vehicles must 
satisfy the same performance criteria, the algorithm for some electric 
powertrains must also allow those electrified vehicles to operate in 
certain driving cycles, like the US06 cycle, without assistance of the 
combustion engine and ensure the electric motor/generator and battery 
can handle the vehicle's regenerative braking power, all-electric mode 
operation, and intended range of travel.
    To establish the effectiveness of the technology packages, 
Autonomie simulates the vehicles' performance on compliance test 
cycles.298 299 300 For vehicles with conventional 
powertrains and micro hybrid powertrains, Autonomie simulates the 
vehicles using the 2-cycle test procedures and guidelines.\301\ For 
mild HEVs, strong HEVs, and FCEVs, Autonomie simulates the same 2-cycle 
test, with the addition of repeating the drive cycles until the final 
State of charge (SOC) is approximately the same as the initial SOC, a 
process described in SAE J1711. For PHEVs, Autonomie simulates vehicles 
performing the test cycles per

[[Page 56211]]

guidance provided in SAE J1711.\302\ PHEVs have a different range of 
modeled effectiveness during ``standard setting'' CAFE Model runs, in 
which the PHEV operates under a ``charge sustaining'' mode (similar to 
how SHEVs function) compared to ``EIS'' runs, in which the same PHEV 
operates under a ``charge depleting'' mode (similar to how BEVs 
function). For BEVs and FCEVs, Autonomie simulates vehicles performing 
the test cycles per guidance provided in SAE J1634.\303\
---------------------------------------------------------------------------

    \302\ PHEV testing is broken into several phases based on SAE 
J1711: charge-sustaining on the city and HWFET cycle, and charge-
depleting on the city and HWFET cycles.
    \303\ SAE J1634. Battery Electric Vehicle Energy Consumption and 
Range Test Procedure. July 12, 2017.
---------------------------------------------------------------------------

    Chapters 2.4 and 3.3 of the Draft TSD and the CAFE Analysis 
Autonomie Documentation chapter titled ``Test Procedure and Energy 
Consumption Calculations'' discuss the components and test cycles used 
to model each electrified powertrain type; please refer to those 
chapters for more technical details on each of the modeled technologies 
discussed in this section.
    The range of effectiveness for the electrification technologies in 
this analysis is a result of the interactions between the components 
listed above and how the modeled vehicle operates on its respective 
test cycle. This range of values will result in some modeled 
effectiveness values being close to real-world measured values, and 
some modeled values that will depart from measured values, depending on 
the level of similarity between the modeled hardware configuration and 
the real-world hardware and software configurations. The range of 
effectiveness values for the electrification technologies applied in 
the LD fleets are shown in Figure II-23 and Figure II-24. Effectiveness 
values for electrification technologies in the HDPUV fleet are shown in 
Figure II-25.
BILLING CODE 4910-59-P

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[[Page 56213]]


[GRAPHIC] [TIFF OMITTED] TP17AU23.034


[[Page 56214]]


[GRAPHIC] [TIFF OMITTED] TP17AU23.035

BILLING CODE 4910-59-C
    When the CAFE Model turns a vehicle powered by an ICE into an 
electrified vehicle, it must remove the parts and costs associated with 
the ICE (and, potentially, the transmission) and add the costs of a 
battery pack and other non-battery electrification components, such as 
the electric motor and power inverter. To estimate battery pack costs 
for this analysis, we need an estimate of how much battery packs cost 
now (i.e., a ``base year'' cost), and estimates of how that cost could 
reduce over time (i.e., the ``learning effect.''). The general concept 
of learning effects is discussed in detail in Section II.C and in 
Chapter 2 of the Draft TSD, while the specific LE we applied to battery 
pack costs in this analysis is discussed below. We estimate base year 
battery pack costs for most electrification technologies using BatPaC, 
which is an ANL model designed to calculate the cost of EV battery 
packs.
    Traditionally, a user would use BatPaC to cost a battery pack for a 
single vehicle, and the user would vary factors such as battery cell 
chemistry, battery power and energy, battery pack interconnectivity 
configurations, battery pack production volumes, and/or charging 
constraints, just to name a few, to see how those factors would 
increase or decrease the cost of the battery pack. However, several 
hundreds of thousands of simulated vehicles in our analysis have 
electrified powertrains, meaning that we would have to run individual 
BatPaC simulations for each full vehicle simulation that requires a 
battery pack. This would have been computationally intensive and 
impractical. Instead, ANL staff builds ``lookup tables'' with BatPaC 
that provide battery pack manufacturing costs, battery pack weights, 
and battery pack cell capacities for vehicles with varying power 
requirements modeled in our large-scale simulation runs.
    Just like with other vehicle technologies, the specifications of 
different vehicle manufacturer's battery packs are extremely diverse. 
We, therefore, endeavored to develop battery pack costs that reasonably 
encompass the cost of battery packs for vehicles in each technology 
class. Two BatPaC assumptions are of note when generating base year 
battery costs: (1)

[[Page 56215]]

battery cell chemistry and (2) battery plant production volume.
    In conjunction with our partners at ANL working on the CAFE 
analysis Autonomie modeling, we referenced EV outlook 
reports,304 305 306 vehicle teardown 
reports,307 308 and stakeholder discussions \309\ to 
determine common battery pack chemistries for each modeled 
electrification technology. The CAFE Analysis Autonomie Documentation 
chapter titled ``Battery Performance and Cost Model--BatPac Examples 
from Existing Vehicles in the Market'' includes more detail about the 
reports referenced for this analysis.\310\ For mild hybrids, we used 
the LFP-G \311\ chemistry because power and energy requirements for 
mild hybrids are very low, the charge and discharge cycles (or need for 
increased battery cycle life) are high, and the battery raw materials 
are much less expensive than a nickel manganese cobalt (NMC)-based cell 
chemistry. We used NMC622-G \312\ for all other electrified vehicle 
technology initial battery pack cost calculations. While we made this 
decision at the time of modeling based on the best available 
information, while also considering feedback on prior rules,\313\ more 
recent data affirms that EV batteries using NMC622 cathode chemistries 
are still a significant part of the market.\314\ We recognize there is 
ongoing research and development with battery cathode chemistries that 
may have the potential to reduce costs and increase battery 
capacity.315 316 317 318 In particular, we are aware of a 
recent shift by manufacturers to transition to lithium iron phosphate 
(LFP) chemistry-based battery packs as prices for materials used in 
battery cells fluctuate (see additional discussion below); however, we 
believe that based on available data,\319\ NMC622 is more 
representative for our MY 2022 base year battery costs than LFP, and 
any additional cost reductions from manufacturers switching to LFP 
chemistry-based battery packs in years beyond 2022 are accounted for 
through LEs. As a reminder, in this analysis, we account for the 
potential cost savings for future battery cell chemistries using a 
learning rate applied to the battery pack DMC. As discussed above, the 
battery chemistry we use is intended to reasonably represent what is 
used in U.S. battery manufacturing in MY 2022, the DMC base year for 
our BatPaC calculations.
---------------------------------------------------------------------------

    \304\ RhoMotion. 2023. Emerging Battery Technology Forum. 
Available at: https://rhomotion.com/rho-motion-seminar-series-live-q1-2023-seminar-recordings. (Accessed: May 31, 2023).
    \305\ Bibra, E. et al. 2022. Global EV Outlook 2022--Securing 
Supplies For an Electric Future. International Energy Agency. 
Available at: https://iea.blob.core.windows.net/assets/ad8fb04c-4f75-42fc-973a-6e54c8a4449a/GlobalElectricVehicleOutlook2022.pdf. 
(Accessed: May 31, 2023).
    \306\ Bloomberg New Energy Finance. 2023. Electric Vehicle 
Outlook 2023. Available at: https://about.bnef.com/electric-vehicle-outlook/. (Accessed: May 31, 2023).
    \307\ Hummel, P. et al. 2017. UBS Evidence Lab Electric Car 
Teardown--Disruption Ahead?. UBS. Available at: https://neo.ubs.com/shared/d1ZTxnvF2k. (Accessed: May 31, 2023).
    \308\ A2Mac1: Automotive Benchmarking. (Proprietary data). 
Available at: https://portal.a2mac1.com/. (Accessed: May 31, 2023).
    \309\ See Docket Submission of Ex Parte Meetings Prior to 
Publication of the Corporate Average Fuel Economy Standards for 
Passenger Cars and Light Trucks for Model Years 2027-2032 and Fuel 
Efficiency Standards for Heavy-Duty Pickup Trucks and Vans for Model 
Years 2030-2035 Notice of Proposed Rulemaking memorandum, which can 
be found under References and Supporting Material in the rulemaking 
Docket No. NHTSA-2023-0022.
    \310\ CAFE Analysis Autonomie Documentation chapter titled 
``Battery Performance and Cost Model--BatPac Examples from Existing 
Vehicles in the Market.''
    \311\ Lithium Iron Phosphate (LiFePO4) cathode and 
Graphite anode.
    \312\ Lithium Nickel Manganese Cobalt Oxide 
(LiNiMnCoO2) cathode and Graphite anode.
    \313\ Stakeholders had commented on both the 2020 and 2022 final 
rules that batteries using NMC811 chemistry had either recently come 
into or were imminently coming into the market, and therefore we 
should have selected NMC811 as the appropriate chemistry for 
modeling battery pack costs.
    \314\ Rho Motion. Seminar Series Live, Q1 2023--Seminar 
Recordings. ``Emerging Battery Technology Forum'' February 7, 2023. 
Available at: https://rhomotion.com/rho-motion-seminar-series-live-q1-2023-seminar-recordings. (Accessed: May 31, 2023). More 
specifically, the monthly weighted average global EV battery cathode 
chemistry across all vehicle classes shows that 19% use NMC622 and 
20% use NMC811+, representing a fairly even split. Even though we 
considered domestic battery production rather than global battery 
production for the analysis supporting this proposal, NMC622 is 
still prevalent even at a global level. Note that this seminar video 
is no longer publicly available to non-subscribers.
    \315\ Slowik, P. et. al. 2022. Assessment of Light-Duty Electric 
Vehicle Costs and Consumer Benefits in the United States in the 
2022-2035 Time Frame. International Council on Clean Transportation. 
Available at: https://theicct.org/wp-content/uploads/2022/10/ev-cost-benefits-2035-oct22.pdf. (Accessed: May 31, 2023).
    \316\ Batteries News. 2022. ``Solid-State NASA Battery Beats The 
Model Y 4680 Pack at Energy Density by Stacking all Cells in One 
Case.'' October 20, 2022. Available at: https://batteriesnews.com/solid-state-nasa-battery-beats-model-y-4680-pack-energy-density-stacking-cells-one-case/. (Accessed: February 1, 2023).
    \317\ Sagoff, J. 2023. Scientists develop more humane, 
environmentally friendly battery material. ANL. Available at: 
https://www.anl.gov/article/scientists-develop-more-humane-environmentally-friendly-battery-material. (Accessed: May 31, 2023).
    \318\ International Energy Agency. Global EV Outlook 2023. April 
2023. Available at https://www.iea.org/reports/global-ev-outlook-2023. (Accessed: May 31, 2023).
    \319\ International Energy Agency. Global EV Outlook 2023. April 
2023. Available at https://www.iea.org/reports/global-ev-outlook-2023. (Accessed: May 31, 2023). As of IEA's 2023 Global EV Outlook 
report, ``around 95% of the LFP batteries for electric LDVs went to 
vehicles produced in China, and BYD [a Chinese EV manufacturer] 
alone represents 50% of demand. Tesla accounted for 15%, and the 
share of LFP batteries used by Tesla increased from 20% in 2021 to 
30% in 2022. Around 85% of the cars with LFP batteries manufactured 
by Tesla were manufactured in China, with the remainder being 
manufactured in the United States with cells imported from China. In 
total, only around 3% of electric cars with LFP batteries were 
manufactured in the United States in 2022.'' This is not to say that 
as of 2022 there were no current production or use of vehicle 
battery packs with LFP-based chemistries in the U.S., but rather 
that based on available data, we are more certain that NMC622 was a 
reasonable chemistry selection for our 2022 base year battery costs.
---------------------------------------------------------------------------

    We also looked at vehicle sales volumes in MY 2022 to determine a 
reasonable base production volume assumption.\320\ In practice, a 
single battery plant can produce packs using different cell chemistries 
with different power and energy specifications, as well as battery pack 
constructions with varying battery pack designs--different cell 
interconnectivities (to alter overall pack power end energy) and 
thermal management strategies--for the same base chemistry. However, in 
BatPaC, a battery plant is assumed to manufacture and assemble a 
specific battery pack design, and all cost estimates are based on one 
single battery plant manufacturing only that specific battery pack. For 
example, if a manufacturer has more than one BEV and each uses a 
specific battery pack design, a BatPaC user would include manufacturing 
volume assumptions for each design separately to represent each plant 
producing each specific battery pack. As a consequence, we examined 
battery pack designs for vehicles sold in MY 2022 to determine a 
reasonable manufacturing plant production volume assumption. We 
considered each assembly line designed for a specific battery pack and 
for a specific BEV as an individual battery plant. Since battery 
technologies are still evolving, it is likely to be some time before 
battery cells can be treated as commodity where the specific numbers of 
cells are used for varying battery pack applications and all other 
metrics remain the same.
---------------------------------------------------------------------------

    \320\ See Chapter 2.2.1.1 of the Draft TSD for more information 
on data we use for MY 2022 sales volumes.
---------------------------------------------------------------------------

    Similar to previous rulemakings, we used BEV sales as a starting 
point to analyze potential base modeled battery manufacturing plant 
production volume assumptions. Since actual production data for 
specific battery manufacturing plants are extremely hard to obtain and 
the battery cell manufacturer is not always the battery pack 
manufacturer,\321\ we calculated an

[[Page 56216]]

average production volume per manufacturer metric to approximate BEV 
production volumes for this analysis. This metric was calculated by 
taking an average of all manufacturer's battery energy across all BEVs 
reported in vehicle manufacturer's PMY 2022 reports \322\ and dividing 
by the averaged sales-weighted energy per-vehicle; the resulting volume 
was then rounded to the nearest 5,000. Manufacturers are not required 
to report gross battery pack sizes for the PMY report, so we estimated 
pack size for each vehicle based on publicly available data, like 
manufacturer's announcements. This process was repeated for all other 
electrified vehicle technologies. We believe this gave us a reasonable 
base year plant production volume--especially in the absence of actual 
production data--since the PMY data from manufacturers already includes 
accurate related data, such as vehicle model and sales information 
metrics.\323\ An example calculation below, in Table II-14 and Equation 
II-7 and Equation II-8, outline how the sales-weighted energy per 
vehicle production volume estimates are calculated with Table II-14 
showing several example BEV models, their production volumes, and pack 
energy that are representative of industry today.
---------------------------------------------------------------------------

    \321\ Lithium-Ion Battery Supply Chain for E-Drive Vehicles in 
the United States: 2010-2020, ANL/ESD-21/3.
    \322\ 49 CFR 537.7.
    \323\ NHTSA used publicly available range and pack size 
information and linked the information to vehicle models.

                                  Table II-14--Example BEV Model Battery Packs
----------------------------------------------------------------------------------------------------------------
                                                                                       Production      Battery
      Electrification level              Vehicle make            Vehicle model           volume      pack energy
----------------------------------------------------------------------------------------------------------------
BEV..............................  Make A.................  Model A1...............          70,000        80kWh
BEV..............................  Make A.................  Model A2...............           3,000       100kWh
BEV..............................  Make B.................  Model B1...............           4,000        90kWh
BEV..............................  Make C.................  Model C1...............          18,000        70kWh
----------------------------------------------------------------------------------------------------------------

    The average energy (Eavg) across all BEVs in the fleet 
is initially found. In this example, the average energy is calculated 
as the sum of the pack energy divided by the number of vehicle models:
[GRAPHIC] [TIFF OMITTED] TP17AU23.036

    Next, the average production volume (Pavg) for this 
example was found via the sales weighted energy per vehicle by taking 
the product of a model's pack energy (EModel xn) and 
production volume (PModel xn) across all example vehicle 
models--with the sum of all models then divided by the average pack 
energy (Eavg), found from the previous equation:

[[Page 56217]]

[GRAPHIC] [TIFF OMITTED] TP17AU23.037

    Once the average BEV production (Pavg) was found, it is 
rounded to the nearest 5,000; for this example, the production volume 
is rounded up from 104,235.3 to 105,000 vehicles. This process was used 
to determine production volumes for each of the electrified powertrain 
technologies in the fleet. Our final battery manufacturing plant 
production volume assumptions for different electrification 
technologies are as follows: mild hybrid and strong hybrids are 
manufactured assuming 200,000 packs, PHEVs are manufactured assuming 
20,000 packs, and BEVs are manufactured assuming 60,000 packs.
    We believe it was reasonable to consider U.S. sales for purposes of 
this calculation rather than global sales based on the best available 
data we had at the time of modeling and based on our understanding of 
how manufacturers design BEVs for particular markets.\324\ That said, 
we are interested in comments from manufacturers and other stakeholders 
on how vehicle and battery manufacturers take advantage of design 
overlap across markets to maintain cost reduction progress in battery 
technology. A manufacturer may have previously sold the same vehicle 
with different battery packs in two different markets, but as the 
outlook for battery materials and global economic events dynamically 
shift, manufacturers could take advantage of significant design overlap 
and other synergies like from vertical integration to introduce lower-
cost battery packs in markets that it previously perceived had 
different design requirements.\325\ To the extent that manufacturers' 
costs are based more closely on global volumes of battery packs 
produced, our base year battery pack production volume assumption could 
potentially be conservative; however, as discussed further below, our 
base year MY 2022 battery pack costs fall well within the range of 
reasonable estimates based on 2023 data. Again, we seek comment on this 
approach and the resulting base year cost estimates.
---------------------------------------------------------------------------

    \324\ As an example, a manufacturer might design a BEV to suit 
local or regional duty cycles (i.e., how the vehicle is driven day-
to-day) due to local geography and climate, customer preferences, 
affordability, supply constraints, and local laws. This is one 
factor that goes into chemistry selection, as different battery 
chemistries affect a vehicle's range capability, rate of 
degradation, and overall vehicle mass.
    \325\ As an example, some U.S. Tesla Model 3 and Model Y battery 
packs use a nickel cobalt aluminum (Lithium Nickel Manganese Cobalt 
Aluminum Oxide cathode with Graphite anode, commonly abbreviated as 
NCA)-based cell, while the same vehicles for sale in China use LFP-
based packs. However, Tesla has introduced LFP-based battery packs 
to some Model 3 vehicles sold in the U.S., showing how manufacturers 
can take advantage of experience in other markets to introduce 
different battery technology in the United States. See Electric 
Vehicle Database. Tesla Model 3 Standard Range Plus LFP. Available 
at: https://ev-database.uk/car/1320/Tesla-Model-3-Standard-Range-Plus-LFP. (Accessed: May 31, 2023). See the Tesla Model 3 Owner's 
Manual for additional considerations regarding LFP-based batteries, 
at https://www.tesla.com/ownersmanual/model3/en_jo/GUID-7FE78D73-0A17-47C4-B21B-54F641FFAEF4.html.
---------------------------------------------------------------------------

    As mentioned above, our BatPaC lookup tables provide $/kWh battery 
pack costs based on vehicle power and energy requirements. As an 
example, a midsized SUV with mid-level road load reduction technologies 
(MASS, ROLL, and AERO), like the vehicle in the example in Section 
II.C, might require a 110-120kWh energy and 200-210kW power battery 
pack. From our base year BatPaC cost estimates, that vehicle might have 
a battery pack that costs around $123/kWh. Note that the total cost of 
a battery pack goes up the higher the power/energy requirements, 
however the cost per kWh goes down. This represents the cost of 
hardware that is needed in all battery packs but is deferred across 
more kW/kWh in larger packs, which reduces the per kW/kWh cost. Table 
II-15 shows an example of the BatPaC-based lookup tables for the BEV3 
SUV through pickup technology classes.

[[Page 56218]]

[GRAPHIC] [TIFF OMITTED] TP17AU23.038

    Note that the values in the table above should not be considered 
the total battery $/kWh costs that are used for vehicles in the 
analysis in future MYs. As detailed below, battery costs are also 
projected to decrease over time as manufacturers improve production 
processes, shift battery chemistries, or make other technological 
advancements. In addition, select modeled tax credits further reduce 
our estimated costs; additional discussion of those tax credits is 
located throughout this preamble, the Draft TSD, and PRIA.
    The CAFE Analysis Autonomie Documentation details other specific 
assumptions that ANL used to simulate battery packs and their 
associated base year costs for the full vehicle simulation modeling, 
including updates to the battery management unit costs, and the range 
of power and energy requirements used to bound the lookup tables.\326\ 
Please refer to the CAFE Analysis Autonomie Documentation and Chapter 
3.3 of the Draft TSD for further information about how we used BatPaC 
to estimate base year battery costs. The full range of BatPaC-generated 
battery DMCs is located in ANL--Summary of Main Component Performance 
Assumptions_NPRM_2206. Note again that these charts represent the DMC 
using a dollar per kW/kWh metric; battery absolute costs used in the 
analysis by technology key can be found in the CAFE Model Battery Costs 
File.
---------------------------------------------------------------------------

    \326\ CAFE Analysis Autonomie Documentation chapter titled 
``Battery Performance and Cost Model--Use of BatPac in Autonomie.''
---------------------------------------------------------------------------

    For this analysis, our method of estimating future battery costs 
has three fundamental components: (1) an estimate of MY 2022 battery 
pack costs (i.e., our base year costs generated in the BatPaC 5.0 model 
to estimate battery pack costs for specific vehicles, depending on 
factors such as pack size and power requirements, discussed above), and 
(2) future learning rates through 2050, and (3) the effect of changes 
in the cost of key minerals on battery pack costs, which are discussed 
below.
    The concept of a learning curve was initially developed to describe 
cost reduction due to improvements in manufacturing processes from 
knowledge gained through experience in production; however, it has 
since been recognized that other factors make important contributions 
to cost reductions associated with cumulative production.\327\ We 
discuss this concept further, in Section II.C.
---------------------------------------------------------------------------

    \327\ Wene, C. 2000. Experience Curves for Energy Technology 
Policy. International Energy Agency. Paris.
---------------------------------------------------------------------------

    For the last CAFE Model analysis, we estimated potential future 
reductions in battery pack costs,\328\ based on an assessment of cost 
reductions due to battery pack production volume increases.\329\ This 
production-volume-based learning rate clearly fell within the meaning 
of a ``learning curve'' because the cost reductions were based on 
improvements in manufacturing processes due to knowledge gained through 
experience in production. We also used BatPaC to examine how battery 
pack costs might change due to factors other than production volume 
increases, including chemistry changes and changes in manufacturing 
plant efficiency, while recognizing that BatPaC does include some cost 
reductions due to improvements in manufacturing processes, in 
particular

[[Page 56219]]

through assumed increases in the degree of plant automation.\330\ 
Recognizing that battery pack costs for future years are inherently 
uncertain, we sought comment on our learning rates and also provided 
cost estimates from other sources against which to compare our 
estimates.331 332 Our conclusion after considering comments 
and publicly available information was that our estimates of how 
battery pack costs could reduce over time fell reasonably within the 
estimates of potential future battery pack cost estimates from other 
sources. However, we also received valuable information and feedback 
from commenters on sources of information about future battery costs 
estimates,\333\ and concerns about factors that could potentially drive 
the future cost of battery packs up or down.\334\
---------------------------------------------------------------------------

    \328\ Note that we use cost in the CAFE Model, however many 
sources also report price. We have tried to use the accurate term 
throughout this section, however, note that even within the same 
data source, cost and price may be used interchangeably. See Mauler, 
L., F. Duffner, W. Zeier and J. Leker. 2021. Battery cost 
forecasting: a review of methods and results with an outlook to 
2050. Energy and Environmental Science, 4712-4739 (``However, 
details on company-specific prices, costs and profit margins are not 
publicly available and differences are difficult to assess.[] In 
battery literature both terms are frequently used interchangeable, a 
phenomenon reported earlier,[ ] which may be explained by different 
perspectives on the same value, since the price paid to a battery 
manufacturer represents the cost to the manufacturer of the final 
product.'').
    \329\ 87 FR 25819.
    \330\ See 24-26 TSD at 286-7 (citing Nelson, Paul A., Ahmed, 
Shabbir, Gallagher, Kevin G., and Dees, Dennis W. Modeling the 
Performance and Cost of Lithium-Ion Batteries for Electric-Drive 
Vehicles, Third Edition (ANL/CSE-19/2). Available at https://publications.anl.gov/anlpubs/2019/03/150624.pdf. (Accessed: May 31, 
2023).) (``As detailed in the BatPaC model documentation, the costs 
of materials, labor, and capital equipment in the model are based 
upon ANL's estimates of 2018 values, `[t]hus, if BatPaC is used to 
calculate the current costs of batteries at current production 
levels (say 30,000 all-electric (BEV) packs per year) we expect it 
to provide good estimates of current battery prices to OEMs. 
Estimates done for ten years in the future should be at production 
levels of 100,000 to 500,000 units per year, which will result in 
lower pack prices because of the assumed increase in the degree of 
plant automation.' '').
    \331\ 87 FR 25818.
    \332\ 24-26 TSD at 313.
    \333\ See, e.g., Mauler, L. et al. 2021. Battery Cost 
Forecasting: A Review of Methods and Results With an Outlook to 
2050. Energy and Environmental Science: pp. 4712-4739.
    \334\ 87 FR 25819-20.
---------------------------------------------------------------------------

    In particular, a 2021 study by Mauler et al., ``Battery cost 
forecasting: a review of methods and results with an outlook to 2050,'' 
referenced above and by commenters during the last rule provided one of 
the most far-reaching examinations of battery cost literature to date. 
This comprehensive survey of 53 forecasts of battery pack and cell 
costs included studies based on four forecasting methods: learning, 
literature-based projections, expert elicitation, and bottom-up battery 
pack models.\335\ Each study focused on a unique set of assumptions 
that may include battery plant size and location, the plant's 
production processes and overall cumulative production, battery cell 
and electrode designs, and material prices. The paper identifies and 
discusses these important considerations--making correlations between 
resulting cost differences across battery technology considerations and 
varying forecast periods between studies--and appropriately 
encapsulates the battery market within technological scope. 
Importantly, as discussed further below, the authors appropriately note 
the uncertainty associated with predicting lithium-ion battery (LIB) 
costs out through 2050.
---------------------------------------------------------------------------

    \335\ Mauler, L. et al.. Battery Cost Forecasting: A Review Of 
Methods And Results With An Outlook To 2050. Energy and 
Environmental Science: pp. 4712-4739. Many of these selected studies 
focus on common-place LIB cathode chemistries for BEVs--such as 
lithium nickel manganese cobalt oxide (NMC), lithium nickel cobalt 
aluminum oxide (NCA), and lithium iron phosphate (LFP); however, 
some studies investigate the future-use of battery technologies such 
as solid-state (SSB) and lithium-sulfur (LSB), while other studies 
examine battery applications that more broadly coincide with HEVs, 
energy stationary storage (ESS), consumer electronics, and medical 
devices. Thirty of the forecasts were based on bottom-up battery 
models and sixteen used estimated learning curves.
---------------------------------------------------------------------------

    The authors extracted 237 estimates from the 22 studies published 
over the previous 10 years that focused on LIB packs. They fitted a 
central tendency curve to the estimates as a function of time up to 
2050.\336\ The central tendency curve shows battery pack costs 
declining from $1,014/kWh in 2010 to $234/kWh in 2020. Costs in the 
fitted curve decline to $132/kWh in 2030, and progress lower to $109/
kWh in 2035, and $92/kWh in 2040. The paper's authors present the fit 
curve with reference to survey battery prices from Bloomberg New Energy 
Finance (BNEF), one source of battery pack prices based on survey data. 
In the two articles referenced by Mauler et al. to provide comparison 
data for their fitted curve, BNEF cites battery pack prices at $176/kWh 
in 2018 declining to $94/kWh by 2024 (using observed historical values 
to calculate a ``learning rate of around 18%. This means that for every 
doubling of cumulative volume, we observe an 18% reduction in 
price.''),\337\ and a more recent estimate of $137/kWh in 2020 
declining to $101/kWh by 2023.\338\ Mauler et al. note that ``in the 
time period between 2015 and 2020, 90% of forecasted values are more 
pessimistic than observed prices. This indicates that forecasts in the 
examined literature have been on the pessimistic end in the past. 
Further, the persistent span of estimates above [$130/kWh, in the 
surveyed literature] throughout 2050 underlines the uncertainty 
associated with the prediction of LIB cost that will remain a key 
challenge in the future for researchers and companies in the field.'' 
\339\
---------------------------------------------------------------------------

    \336\ Figure 9 of Mauler et al., 2021, at 4715. The authors 
note: ``Whenever values for multiple applications are reported, the 
forecast dedicated to electric vehicle batteries is preferred.'' 
Costs appear to be in 2020 dollars, although this is not clearly 
stated in the text. The authors also ``emphasize that this should 
not be considered as a literature-based forecast to 2050, but merely 
as a comprehensive picture of forecasted values from the past 
decade.''
    \337\ BNEF. 2019. A Behind the Scenes Take on Lithium-ion 
Battery Prices. Last revised: March 5, 2019. Available at: https://about.bnef.com/blog/behind-scenes-take-lithium-ion-battery-prices/. 
(Accessed: May 31, 2023).
    \338\ BNEF. 2020. Battery Pack Prices Cited Below $100/kWh for 
the First Time in 2020, While Market Average Sits at $137/kWh. Last 
revised: December 16, 2020. Available at: https://about.bnef.com/blog/battery-pack-prices-cited-below-100-kwh-for-the-first-time-in-2020-while-market-average-sits-at-137-kwh/. (Accessed: May 31, 
2023). Note that at the time of writing (2020), BNEF was of the 
opinion that ``The path to achieving $101/kWh by 2023 looks clear, 
even if there will undoubtedly be hiccups, such as commodity price 
increases, along the way.'').
    \339\ Mauler et al., at 4733.
---------------------------------------------------------------------------

    Much has happened since the last CAFE Model analysis and the 
battery cost forecasting paper summarized above. BNEF summarized that 
``[a]s demand continues to grow, battery producers and automakers are 
scrambling to secure access to key metals such as lithium and nickel, 
battling high prices and tight supply.'' \340\ Since the articles cited 
in the Mauler paper discussed above, BNEF has revised their battery 
pack price estimates for 2022 to $135/kWh,\341\ and then revised their 
2022 estimate again to $138/kWh.\342\ BNEF attributed the increase in 
pack costs in part to the increase in mineral costs--specifically 
lithium carbonate--in addition to inflation and component cost 
increases.\343\ However, BNEF also

[[Page 56220]]

noted that ``[t]he average battery price would have been even higher if 
not for the shift to lower-cost LFP batteries, which contain no nickel 
or cobalt.'' \344\ The International Energy Agency's Global EV Outlook 
2023 also used estimates from BNEF, citing a value of $150 for all LIB 
packs.\345\
---------------------------------------------------------------------------

    \340\ BNEF. 2022. The Race to Net Zero: The Pressures of the 
Battery Boom in Five Charts. Last revised: July 21, 2022. Available 
at: https://about.bnef.com/blog/race-to-net-zero-the-pressures-of-the-battery-boom-in-five-charts/. (Accessed: May 31, 2023).
    \341\ BNEF. 2022. The Race to Net Zero: The Pressures of the 
Battery Boom in Five Charts. Last revised: July 21, 2022. Available 
at: https://about.bnef.com/blog/race-to-net-zero-the-pressures-of-the-battery-boom-in-five-charts/. (Accessed: May 31, 2023).
    \342\ BNEF. 2022. Lithium-ion Battery Pack Prices Rise for First 
Time to an Average of $151/kWh. Last revised: Dec. 6, 2022. 
Available at: https://about.bnef.com/blog/lithium-ion-battery-pack-prices-rise-for-first-time-to-an-average-of-151-kwh/. (Accessed: May 
31, 2023); McKerracher, C. 2022. Rising Battery Prices Threaten to 
Derail the Arrival of Affordable Evs. Available at: https://www.bloomberg.com/news/articles/2022-12-06/rising-battery-prices-threaten-to-derail-the-arrival-of-affordable-evs. (Accessed: May 31, 
2023). (``To arrive at the average price, BNEF gathered almost 200 
survey data points from buyers and sellers of lithium-ion batteries 
going into passenger Evs, commercial vehicles, buses and stationary 
storage applications. The headline figure is a volume-weighted 
average, so it hides a lot of variation by region and application. 
The lowest prices recorded were for electric buses and commercial 
vehicles in China at $131 per kWh. Average pack prices for fully 
electric passenger vehicles were $138 per kWh.'').
    \343\ BNEF. 2022. Lithium-ion Battery Pack Prices Rise for First 
Time to an Average of $151/kWh. Last revised: Dec. 6, 2022. 
Available at: https://about.bnef.com/blog/lithium-ion-battery-pack-prices-rise-for-first-time-to-an-average-of-151-kwh/. (Accessed: May 
31, 2023).
    \344\ Id.
    \345\ International Energy Agency, Global EV Outlook 2023, 
available at https://www.iea.org/reports/global-ev-outlook-2023 
(citing BloombergNEF, Lithium-ion Battery Prices Rise for First Time 
to an Average of $151/kWh, available at https://about.bnef.com/blog/lithium-ion-battery-pack-prices-rise-for-first-time-to-an-average-of-151-kwh/). Note that $151/kWh represents an average across 
multiple battery end-uses, while BNEF's estimates for battery 
electric vehicle packs in particular are $138/kWh on a volume-
weighted average basis in 2022.
---------------------------------------------------------------------------

    In addition, the U.S. DOE updated modeling-based estimates of 
battery pack costs from using ANL's BatPaC model. Their updated 
estimates show 2022 values at $130/kWh of rated energy.\346\ 
Separately, a 2022 analysis of future vehicle costs sponsored by the 
U.S. DOE with co-authors from ANL, Ford, GM, Electric Power Research 
Institute, the National Renewable Energy Laboratory, and Chevron 
compared predictions of future EV battery pack costs from 9 studies 
with 3 R&D targets set by DOE and US DRIVE.\347\ They concluded that 
``recent assessments of future BEV battery costs by governmental 
agencies, national laboratories, the NAS, academia, consulting firms, 
and automakers show this [dramatic decline in the costs of high-energy 
Li-ion batteries] trend is expected to continue in the future.'' \348\
---------------------------------------------------------------------------

    \346\ ANL. 2022. BatPaC--A Spreadsheet Tool to Design a Lithium 
Ion Battery and Estimate Its Production Cost. Last revised: Mar. 8, 
2022. Available at: https://www.anl.gov/cse/batpac-model-software. 
(Accessed: May 31, 2023). This estimate assumes a production scale 
of 100,000 units per year, however as discussed further below, our 
BatPaC-derived costs align extremely well with these DOE-estimated 
costs. See also, Cunningham, B. U.S. Department of Energy Vehicle 
Technologies Office 2023 Annual Merit Review. Overview: Batteries 
R&D, DOE Modeled Battery Pack Cost. June 12, 2023; VTO Fact of the 
Week #1272, Electric Vehicle Battery Pack Costs, which shows that 
2022 costs are nearly 90% lower than in 2008, according to DOE 
Estimates (Jan. 9, 2023). Available at https://www.energy.gov/eere/vehicles/articles/fotw-1272-january-9-2023-electric-vehicle-battery-pack-costs-2022-are-nearly. (Accessed: May 31, 2023).
    \347\ Kelly, J. et al. 2022. Cradle-to-Grave Lifecycle Analysis 
of U.S. Light-Duty Vehicle-Fuel Pathways: A Greenhouse Gas Emissions 
and Economic Assessment of Current (2020) and Future (2030-2035) 
Technologies. ANL-22/27. ANL: Argonne, IL. p. 56.
    \348\ Id.
---------------------------------------------------------------------------

    For this analysis, instead of relying on our previous methodology 
of using the BatPaC model to estimate volume-based cost reductions for 
battery packs, we extracted estimated learning rates from the Mauler et 
al. study discussed above. Our learning rates are based on the year-
over-year cost decreases shown in the Mauler et al. study; however, we 
modified the learning rate in two ways, discussed in turn.
    First, we began Mauler's 2030-2035 estimated learning rate in MY 
2022, as it better aligns with our MY 2022 BatPaC-based base year cost 
estimates and is reflected in the most recent BNEF survey data. To the 
extent that global EV battery production has grown more rapidly than 
the studies anticipated, it is reasonable to expect that learning in 
manufacturing processes, economies of scale, and technological progress 
have also been realized sooner than the projections anticipated. 
Assuming this is the case, future learning rates will be lower than the 
studies anticipated because battery manufacturing has moved farther 
down the learning curve than they anticipated.
    Second, to reflect the combination of fluctuating mineral costs and 
an increase in demand, we hold the battery pack cost learning curve 
constant between MYs 2022 and 2025. This is a conservative assumption 
that is also employed by EPA in their proposal for light duty vehicles 
and medium duty vehicles beginning in MY 2027 at Section IV.C.2 and 
Draft Regulatory Impact Analysis Section 2.5.2.1.3. The assumption 
reflects increased lithium costs since 2020 that are not expected to 
decline appreciably to circa 2020 levels until additional capacity 
(mining, materials processing, and cell production) comes on-line,\349\ 
although prices have already fallen from 2022 highs at the time of 
writing. We believe that a continuation of high prices for a few years 
followed by a decrease to near previous levels is reasonable because 
world lithium resources are more than sufficient to supply a global EV 
market and higher prices should continue to induce investment in 
lithium mining and refining.350 351 That said, we recognize 
the uncertainty in critical minerals prices into the near future. We 
seek comment on this representation of mineral costs in the learning 
curve, and any other feedback relevant to incorporating these 
considerations into our modeling framework.
---------------------------------------------------------------------------

    \349\ Trading Economics. 2023. Lithium. Available at: https://tradingeconomics.com/commodity/lithium (Accessed: May 31, 2023).
    \350\ U.S. Geological Survey. 2023. Lithium Statistics and 
Information. Available at: https://www.usgs.gov/centers/national-minerals-information-center/lithium-statistics-and-information. 
(Accessed: May 31, 2023).
    \351\ Global lithium resources (``resources defined by U.S.G.S. 
as ``[a] concentration of naturally occurring solid, liquid, or 
gaseous material in or on the Earth's crust in such form and amount 
that economic extraction of a commodity from the concentration is 
currently or potentially feasible.'') are currently four times as 
large as global reserves (``reserves'' defined by U.S.G.S. as 
``[t]hat part of the reserve base that could be economically 
extracted or produced at the time of determination.''), and both 
have grown over time as production has increased (Figure 3). Lithium 
resources are not evenly distributed geographically (Figure 4). 
According to 2021 USGS estimates, Bolivia (24%), Argentina (22%), 
Chile (11%), the United States (10%), Australia (8%) and China (6%) 
together hold four-fifths of the world's lithium resources.
---------------------------------------------------------------------------

    Unlike our past production-based estimates for a battery learning 
curve, this learning curve methodology does not explicitly assume any 
particular battery chemistry is used, because the learning curve we use 
aggregates assumptions from several studies and uses some assumptions 
of our own. That said, we anticipate cell chemistry improvements will 
happen sometime during the middle or later part of this decade. We 
believe that during the rulemaking time frame, based on on-going 
research and discussions with stakeholders,\352\ the industry will 
continue to employ lithium-ion NMC as the predominant battery cell 
chemistry for the near-term but will transition more fully to advanced 
high-nickel battery chemistries \353\ like NMC811 or less-costly cell 
chemistries like LFP-G during the middle or end of the decade--i.e., 
during the rulemaking timeframe. We acknowledge there are other battery 
cell chemistries currently being researched that reduce the use of 
cobalt, use solid opposed to liquid electrolyte, use of high silicone 
content anodes or lithium-metal anodes, or even eliminate use of 
lithium in the cell altogether; 354 355 however, at this 
time, we do not have sufficient data to estimate cost for those 
advanced battery cell chemistries. Assuming lithium-ion NMC will 
continue to be used for the

[[Page 56221]]

near and mid-term results in reasonable estimates that are comparable 
to other sources' cost projections, although we note that the outcome 
of a model should not be used to justify the input assumptions.
---------------------------------------------------------------------------

    \352\ Docket Submission of Ex Parte Meetings Prior to 
Publication of the Corporate Average Fuel Economy Standards for 
Passenger Cars and Light Trucks for Model Years 2027-2032 and Fuel 
Efficiency Standards for Heavy-Duty Pickup Trucks and Vans for Model 
Years 2030-2035 Notice of Proposed Rulemaking memorandum, which can 
be found under References and Supporting Material in the rulemaking 
Docket No. NHTSA-2023-0022.
    \353\ Panayi, A. 2023. Into the Next Phase, the EV Market 
Towards 2030--The TWh year: The Outlook for the EV & Battery Markets 
in 2023. RhoMotion. Available at: https://rhomotion.com/rho-motion-seminar-series-live-q1-2023-seminar-recordings. (Accessed: May 31, 
2023).
    \354\ Slowik, P. et. al. 2022. Assessment of Light-Duty Electric 
Vehicle Costs and Consumer Benefits in the United States in the 
2022-2035 Time Frame. International Council on Clean Transportation. 
Available at: https://theicct.org/wp-content/uploads/2022/10/ev-cost-benefits-2035-oct22.pdf. (Accessed: May 31, 2023).
    \355\ Batteries News. 2022. Solid-State NASA Battery Beats The 
Model Y 4680 Pack at Energy Density by Stacking all Cells in One 
Case. Last revised: October 20, 2022. Available at: https://batteriesnews.com/solid-state-nasa-battery-beats-model-y-4680-pack-energy-density-stacking-cells-one-case/. (Accessed: May 31, 2023).
---------------------------------------------------------------------------

    As there are inherent uncertainties in projecting future battery 
pack costs due to several factors, including the timing of the analysis 
used to support this proposal, we performed several battery-related 
cost sensitivity analyses. These include cases increasing and 
decreasing battery pack DMCs by 20%, cases increasing and decreasing 
the learning rate by 20%, and a case using the learning curve 
development methodology we used for the 2022 final rule for MYs 2024-
2026 standards. These results are presented in Chapter 9 of the PRIA. 
One important point that these sensitivity case results emphasize is 
that because of NHTSA's inability to consider manufacturers building 
EVs in response to CAFE standards during standard-setting years (i.e., 
MYs 2027-2032 for this proposal), net SCs and benefits do not change 
significantly between battery cost sensitivity cases, and similarly 
would not change significantly if much lower battery costs were used. 
We will continue to follow Federal and international reports on battery 
pack costs and seek additional comment on our battery cost estimates; 
we will update these costs for the final rule analysis if better data 
becomes available.
    Additional discussion in Draft TSD Chapter 3 shows that our 
projected costs fall fairly well in the middle of the range of other 
costs projected by various studies and organizations for future years. 
Using the same approach as the rest of our analysis--that our costs 
should represent an average achievable performance across the 
industry--we believe that the battery DMCs with the learning curve 
applied provide a reasonable representation of potential future costs 
across the industry, based on the information available to us at the 
time of the analysis for this proposal was completed. Figure II-26 
below shows how our reference and sensitivity case cost projections 
(for a 300-mile range BEV with a 70.1kWh battery pack) change over time 
using different base year and learning assumptions.
[GRAPHIC] [TIFF OMITTED] TP17AU23.039

    NHTSA also continues to coordinate with DOE and EPA on assumptions 
and methodology related to battery cost. During the interagency review 
process for EPA's Multi-Pollutant Emissions Standards for Model Years 
2027 and Later Light-Duty and Medium-Duty Vehicles proposal, which 
shortly preceded the process for this proposal, EPA consulted with DOE 
to incorporate battery cost learning effects that reflect the effect of 
cumulative learning by considering the battery production required for 
a given projected BEV penetration. In its analysis, upon recommendation 
from DOE, EPA applied battery cost learning effects dependent on the 
cumulative GWh of battery pack production projected in each individual 
policy scenario, as described in Chapter 2.5.2.1.3 of the

[[Page 56222]]

EPA Draft Regulatory Impact Analysis (DRIA).\356\ In other words, 
learning effects were more pronounced in policy scenarios resulting in 
higher rates of BEV penetration and, conversely, were less pronounced 
in policy scenarios resulting in lower rates of BEV penetration. 
Similar to the NHTSA analysis, the EPA cost/kWh also varies by pack 
size, with larger packs having a lower cost/kWh (see Chapter 2.5.2.1.2 
of the EPA DRIA).\357\ Because of the way in which EPA has thus 
parameterized its battery cost, which is dependent on cumulative volume 
production in a given policy scenario, a direct comparison to the NHTSA 
cost sensitivities shown in Figure II-27 is not straightforward. The 
cost/kWh of several different pack sizes, as implemented in the EPA 
analysis supporting the recent EPA proposal, are shown in Figure 30.
---------------------------------------------------------------------------

    \356\ See U.S. EPA, Multi-Pollutant Emissions Standards for 
Model Years 2027 and Later Light-Duty and Medium-Duty Vehicles Draft 
Regulatory Impact Analysis., EPA-420-D-23-003 (April 2023), Chapter 
2.5.2.1.3.
    \357\ See U.S. EPA, Multi-Pollutant Emissions Standards for 
Model Years 2027 and Later Light-Duty and Medium-Duty Vehicles Draft 
Regulatory Impact Analysis., EPA-420-D-23-003 (April 2023), Chapter 
2.5.2.1.2.
[GRAPHIC] [TIFF OMITTED] TP17AU23.040

    In light of the timing of EPA's analysis relative to NHTSA's 
analysis, NHTSA was unable to consider the EPA approach for possible 
use in the current analysis. The costs developed by EPA as depicted in 
Figure II-27 above show the potential to reach significantly lower 
levels than most of the costs in NHTSA's battery sensitivity cases of 
Figure II-26, depending on the volume production associated with a 
given policy scenario and year. As previously noted, NHTSA continues to 
coordinate with DOE and EPA on battery cost assumptions and 
methodology, and in light of the battery costs and methodology 
published in the EPA LMDV proposal, NHTSA will consider this approach 
to estimating learning effects for use in the final rule analysis. 
Further analysis of battery costs similar to that proposed in EPA's 
LMDV proposal, including the possible adoption of EPA's cumulative 
volume-based learning approach, could result in significantly lower 
battery costs than assumed in this proposed rule analysis. NHTSA 
requests comment on the possibility of implementing for its final rule 
analysis EPA's cumulative volume-based learning approach, and on the 
methodology outlined in EPA's DRIA that EPA used to generate and 
validate the cumulative GWh battery pack production-based battery pack 
costs.
---------------------------------------------------------------------------

    \358\ Chart generated using EPA data, see https://www3.epa.gov/otaq/ld/2023-03-14-22-42-30-ld-central-run-to2055.zip.
---------------------------------------------------------------------------

    Recognizing that there is no way to validate costs for years that 
have not yet happened, we seek comment in particular from vehicle and 
battery manufacturers on any additional data they can submit 
(preferably publicly) to further the conversation about battery pack 
costs in the later part of this decade through the early 2030s. In 
addition, we seek comment on all aspects of our methodology for 
modeling base year and future year battery pack costs, and welcome data 
or other information that could inform our approach for the final 
rulemaking. We specifically seek comment on how the performance metrics 
may change in response to shifts in chemistries used in vehicle models 
driven by global policies affecting battery supply chain development, 
total global production and associated learning rates, and related 
sensitivity analyses.
    While batteries and relative battery components are the biggest 
cost driver of electrification, non-battery electrification components, 
such as electric motors, power electronics, and wiring harnesses, also 
add to the total cost required to electrify a vehicle. Different 
electrified vehicles have

[[Page 56223]]

variants of non-battery electrification components and configurations 
to accommodate different vehicle classes and applications with 
respective designs; for instance, some BEVs may be engineered with only 
one electric motor and some BEVs may be engineered with two or even 
four electric motors within their powertrain to provide all wheel drive 
function. In addition, some electrified vehicle types still include 
conventional powertrain components, like an ICE and traditional 
transmission.
    For all electrified vehicle powertrain types, we group non-battery 
electrification components into four major categories: electric motors 
(or e-motors), power electronics (generally including the DC-DC 
converter, inverter, and power distribution module), charging 
components (charger, charging cable, and high voltage cables), and 
thermal management system(s). We further group the components into 
those comprising the electric traction drive system (ETDS), and all 
other components. Although each manufacturer's ETDS and power 
electronics vary between the same electrified vehicle types and between 
different electrified vehicle types, we consider the ETDS for this 
analysis to be comprised of the e-motor and inverter, power 
electronics, and thermal system.
    When researching costs for different non-battery electrification 
components, we found that different reports vary in components 
considered and cost breakdown. This is not surprising, as vehicle 
manufacturers use different non-battery electrification components in 
different vehicles systems, or even in the same vehicle type, depending 
on the application. In order of the component categories discussed 
above, we examined the following cost teardown studies, as shown in 
Table II-16.

             Table II-16--Cost Estimates for Different Electrified Vehicle Components, by Powertrain
----------------------------------------------------------------------------------------------------------------
                                                        UBS MY 2016 chevy                         EPA-sponsored
     Non-battery electrical        EETT \359\ roadmap     bolt teardown                            FEV report
           components              report  (2017$ in    (2017$ in DMC year      Assumptions      (updated 2021$
                                     DMC year 2017)           2017)                               for analysis)
----------------------------------------------------------------------------------------------------------------
ETDS............................  $18/kW.............  $17.76/kW..........  Based on e-motor           $19.80/kW
                                                                             peak power.
On-Board Charger................  no information       85/kW..............  Based on vehicle            93.54/kW
                                   provided..                                requirement (7 kW
                                                                             for BEVs, 2 kW
                                                                             for PHEVs).
DC to DC Converter..............  no information       90/kW..............  Based on converter         100.94/kW
                                   provided.                                 rated power (2
                                                                             kW).
High Voltage Cables and Charging  no information       450................  Fixed cost rated              495.21
 Cords for BEVs and PHEVs.         provided.                                 for 360V.
High Voltage Cables for Strong    no information       no information       Fixed cost........            100.44
 Hybrids.                          provided.            provided.
----------------------------------------------------------------------------------------------------------------

    Using the best available estimate for each component from the 
different reports captures components in most manufacturer's systems 
but not all; we believe, however, that this is a reasonable metric and 
approach for this analysis, given the non-standardization of 
electrified powertrain designs and subsequent component specifications. 
Other sources we used for non-battery electrification component costs 
include an EPA-sponsored FEV teardown of a 2013 Chevrolet Malibu ECO 
with eAssist for some BISG component costs,\360\ which we validated 
against a 2019 Dodge Ram eTorque system's publicly available retail 
price,\361\ and the 2015 NAS report.\362\ Broadly, our total BISG 
system cost, including the battery, fairly matches these other cost 
estimates.
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    \359\ Electrical and Electronics Technical Team.
    \360\ Light Duty Vehicle Technology Cost Analysis 2013 Chevrolet 
Malibu ECO with eAssist BAS Technology Study, FEV P311264 (Contract 
no. EP-C-12-014, WA 1-9).
    \361\ Colwell, K.C. 2019. The 2019 Ram 1500 eTorque Brings Some 
Hybrid Tech, If Little Performance Gain, to Pickups. Last revised: 
Mar. 14, 2019. Available at: https://www.caranddriver.com/reviews/a22815325/2019-ram-1500-etorque-hybrid-pickup-drive. (Accessed: May 
31, 2023).
    \362\ 2015 NAS report, at p. 305.
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    As discussed in Section II.C, our technology costs account for 
three variables: retail price equivalence (RPE), which is 1.5 times the 
DMC, the technology learning curve, and the adjustment of the dollar 
value to 2021$ for this analysis. While HDPUVs have larger non-battery 
electrification componentry than LDVs, the cost calculation methodology 
is identical, in that the $/kW metric is the same, but the absolute 
costs are higher. As a result, HDPUVs and LDVs share the same non-
battery electrification DMCs.
    For the non-battery electrification component learning curves, in 
both the LD and HDPUV fleets, we used cost information from ANL's 2016 
Assessment of Vehicle Sizing, Energy Consumption, and Cost through 
Large-Scale Simulation of Advanced Vehicle Technologies report.\363\ 
The report provides estimated cost projections from the 2010 lab year 
to the 2045 lab year for individual vehicle 
components.364 365 We considered the component costs used in 
electrified vehicles, and determined the learning curve by evaluating 
the year over year cost change for those components. ANL published a 
2020 and a 2022 version of the same report; however, those versions did 
not include a discussion of the high and low-cost estimates for the 
same components.366 367 Our learning estimates generated 
using the 2016 report align in the middle of these two ranges, and 
therefore we continue to apply the learning curve estimates based on 
the 2016 report. There are many sources that we could have picked to 
develop learning curves for non-battery electrification component 
costs, however given the uncertainty surrounding extrapolating costs 
out to

[[Page 56224]]

MY 2050, we believe these learning curves provide a reasonable 
estimate.
---------------------------------------------------------------------------

    \363\ Moawad, A. et al. 2016. Assessment of Vehicle Sizing, 
Energy Consumption and Cost Through Large Scale Simulation of 
Advanced Vehicle Technologies. ANL/ESD-15/28. Available at: https://www.osti.gov/biblio/1245199. (Accessed: May 31, 2023).
    \364\ ANL/ESD-15/28 at p. 116.
    \365\ DOE's lab year equates to five years after a model year, 
e.g., DOE's 2010 lab year equates to MY 2015.
    \366\ Islam, E. et al. 2020. Energy Consumption and Cost 
Reduction of Future Light-Duty Vehicles through Advanced Vehicle 
Technologies: A Modeling Simulation Study Through 2050. ANL/ESD-19/
10.
    \367\ Islam, E. et al. 2022. A Comprehensive Simulation Study to 
Evaluate Future Vehicle Energy and Cost Reduction Potential. ANL/
ESD-22/6.
---------------------------------------------------------------------------

    In summary, we calculate total electrified powertrain costs by 
summing individual component costs, which ensures that all technologies 
in an electrified powertrain appropriately contribute to the total 
system cost. We combine the costs associated with the ICE (if 
applicable) and transmission, non-battery electrification components 
like the electric machine, and battery pack to create a full-system 
cost. Chapter 3.3.5.4 of the Draft TSD presents the total costs for 
each electrified powertrain option, broken out by the components we 
discussed throughout this section. In addition, the chapter discusses 
where to find each of the component costs in the CAFE Model's various 
input files.
4. Road Load Reduction Paths
    No car or truck uses energy (whether gas or otherwise) 100% 
efficiently when it is driven down the road. If the energy in a gallon 
of gas is thought of as a pie, the amount of energy ultimately 
available from that gallon to propel a car or truck down the road would 
only be a small slice. So where does the lost energy go? Most of it is 
lost due to thermal and frictional loses in the engine and drivetrain 
and drag from ancillary systems (like the air conditioner, alternator 
generator, various pumps, etc.). The rest is lost to what engineers 
call road loads. For the most part, road loads include wind resistance 
(or aerodynamics), drag in the braking system, and rolling resistance 
from the tires. At low speeds, aerodynamic losses are very small, but 
as speeds increases these loses rapidly become dramatically higher than 
any other road load. Drag from the brakes in most cars is practically 
negligible. ROLL losses can be significant: at low speeds ROLL losses 
can be more than aerodynamic losses. Whatever energy is left after 
these road loads are spent on accelerating the vehicle anytime a its 
speed increases. This is where reducing the mass of a vehicle is 
important to efficiency because the amount of energy to accelerate the 
vehicle is always directly proportional to a vehicle's mass. All else 
being equal, reduce a car's mass and better fuel economy is guaranteed. 
However, keep in mind that at freeway speeds, aerodynamics plays a more 
dominant role in determining fuel economy than any other road load or 
than vehicle mass.
    We include three road load reducing technology paths in this 
analysis: the MR Path, Aerodynamic Improvements (AERO) Path, and ROLL 
Path. For all three vehicle technologies, we assign baseline fleet 
technologies and identify adoption features based on the vehicle's body 
style. The LD fleet body styles we include in the analysis are 
convertible, coupe, sedan, hatchback, wagon, SUV, pickup, minivan, and 
van. The HDPUV fleet body styles include chassis cab, cutaway, fleet 
SUV, work truck, and work van. Figure II-28 and Figure II-29 show the 
LD and HDPUV fleet body styles used in the analysis.
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    As expected, the road load forces described above operate 
differently based on a vehicle's body style, and the technology 
adoption features and effectiveness values reflect this. The following 
sections discuss the three Road Load Reduction Paths.
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    \368\ For this proposal, vehicles were divided between the LD 
and HDPUV fleets solely on their gross vehicle weight rating (GVWR) 
being above or below 8,500 lbs. We will revisit the distribution of 
vehicles in the final rule to include the distinction for MDPVs.

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[[Page 56226]]

a. Mass Reduction
    MR is a relatively cost-effective means of improving fuel economy, 
and vehicle manufacturers are expected to apply various MR technologies 
to meet fuel economy standards. Vehicle manufacturers can reduce 
vehicle mass through several different techniques, such as modifying 
and optimizing vehicle component and system designs, part 
consolidation, and adopting materials that are conducive to MR 
(advanced high strength steel (AHSS), aluminum, magnesium, and plastics 
including carbon fiber reinforced plastics).
    For the LD fleet portion of this analysis, we considered five 
levels of MR technology (MR1-MR5) that include increasing amounts of 
advanced materials and MR techniques applied to the vehicle's 
glider.\369\ The subsystems that may make up a vehicle glider include 
the vehicle body, chassis, interior, steering, electrical accessory, 
brake, and wheels systems. We accounted for mass changes associated 
with powertrain changes separately.\370\ We considered two levels of MR 
(MR1--MR2) and a baseline (MR0) for the HDPUV fleet. We use fewer 
levels because vehicles within the HD fleets are built for a very 
different duty cycle \371\ and tend to be larger and heavier. Moreover, 
there are different vehicle parameters, like towing capacity, that 
drive vehicle mass in the HD fleet rather than, for example, NVH 
(noise, vibration and harshness) performance in the LD fleet. 
Similarly, HDPUV MR is assumed to come from the glider,\372\ and 
powertrain MR occurs during the Autonomie modeling. Our estimates of 
how manufacturers could reach each level of MR technology in the LD and 
HDPUV analyses, including a discussion of advanced materials and MR 
techniques, can be found in Chapter 3.4 of the Draft TSD.
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    \369\ Note that in the previous analysis, there was a sixth 
level of mass reduction available as a pathway to compliance. For 
this analysis, this pathway was removed because it relied on 
extensive use of carbon fiber composite technology to an extent that 
is only found in purpose-built racing cars and a few hundred road 
legal sports cars costing hundreds of thousands of dollars. Draft 
TSD Chapter 3.4 provides additional discussion on the decision to 
include five mass reduction levels in this analysis.
    \370\ Glider mass reduction can sometimes enable a smaller 
engine while maintaining performance neutrality. Smaller engines 
typically weigh less than bigger ones. We captured any changes in 
the resultant fuel savings associated with powertrain mass reduction 
and downsizing via the Autonomie simulation. Autonomie calculates a 
hypothetical vehicle's theoretical fuel mileage using a mass 
reduction to the vehicle curb weight equal to the sum of mass 
savings to the glider plus the mass savings associated with the 
downsized powertrain.
    \371\ HD vans that are used for package delivery purposes are 
frequently loaded to GVWR. However, LD passenger cars are never 
loaded to GVWR. Operators of HD vans have an economic motivation to 
load their vehicles to GVWR. In contrast studies show that between 
38% and 82% of passenger cars are used soley to transport their 
drivers. (Bureau of Transportation Studies, 2011, FHWA Publication 
No. FHWA-PL-18-020, 2019).
    \372\ We also assumed that an HDPUV glider comprises 71 percent 
of a vehicle's curb weight, based on a review of mass reduction 
technologies in the 2010 Transportation Research Board and National 
Research Council's ``Technologies and Approaches to Reducing the 
Fuel Consumption of Medium- and Heavy-Duty Vehicles.'' See 
Transportation Research Board and National Research Council. 2010. 
Technologies and Approaches to Reducing the Fuel Consumption of 
Medium- and Heavy-Duty Vehicles. Washington, DC: The National 
Academies Press. At page 120-121. Available at: https://nap.nationalacademies.org/12845/. (Accessed: May 31, 2023).
---------------------------------------------------------------------------

    We assigned baseline MR levels to vehicles in both the LD and HDPUV 
analysis fleets by using regression analyses that consider a vehicle's 
body design \373\ and body style, in addition to several variables 
about the vehicle, like footprint, power, bed length (for pickup 
trucks), and battery pack size (if applicable), among other factors. We 
have been improving on the LD regression analysis since the 2016 Draft 
Technical Assessment Report (TAR) and continue to find that it 
reasonably estimates MR technology levels of vehicles in the analysis 
fleet. We developed a similar regression for the HDPUV fleet for this 
analysis using the factors described above and other applicable HDPUV 
attributes and found that it similarly appropriately assigns baseline 
MR technology levels. Chapter 3.4 of the Draft TSD contains a full 
description of the regression analyses used for each fleet and examples 
of results of the regression analysis for select vehicles.
---------------------------------------------------------------------------

    \373\ The body design categories we used are 3-box, 2-box, HD 
pickup, and HD van. A 3-box can be explained as having a box in the 
middle for the passenger compartment, a box in the front for the 
engine and a box in the rear for the luggage compartment. A 2-box 
has a box in front for the engine and then the passenger and luggage 
box are combined into a single box.
---------------------------------------------------------------------------

    There are several ways we ensure that the CAFE Model considers MR 
technologies like manufacturers might apply them in the real world. 
Given the degree of commonality among the vehicle models built on a 
single platform, manufacturers do not have complete freedom to apply 
unique technologies to each vehicle that shares the platform. While 
some technologies (e.g., low rolling resistance tires) are very nearly 
``bolt-on'' technologies, others involve substantial changes to the 
structure and design of the vehicle, and therefore often necessarily 
affect all vehicle models that share that platform. In most cases, MR 
technologies are applied to platform level components and therefore the 
same design and components are used on all vehicle models that share 
the platform. Each vehicle in the analysis fleet is associated with a 
specific platform. A platform ``leader'' in the analysis fleet is a 
vehicle variant of a given platform that has the highest level of MR 
technology in the analysis fleet. As the model applies technologies, it 
will ``level up'' all variants on a platform to the highest level of MR 
technology on the platform. For example, if a platform leader is 
already at MR3 in MY 2022, and a ``follower'' starts at MR0 in MY 2022, 
the follower will get MR3 at its next redesign (unless the leader is 
redesigned again before that time, and further increases the MR level 
associated with that platform, then the follower would receive the new 
MR level).
    In addition to leader-follower logic for vehicles that share the 
same platform, we also restrict MR5 technology to platforms that 
represent 80,000 vehicles or fewer. The CAFE Model will not apply MR5 
technology to platforms representing high volume sales, like a 
Chevrolet Traverse, for example, where hundreds of thousands of units 
are sold per year. We use this particular adoption feature and the 
80,000-unit threshold in particular, to model several relevant 
considerations. First, we assume that MR5 would require a significant 
amount of carbon fiber technology.\374\ There is high global demand 
from a variety of industries for a limited supply of carbon fibers; 
specifically, aerospace, military/defense, and industrial applications 
demand most of the carbon fiber currently produced. Today, only roughly 
10 percent of the global dry fiber supply goes to the automotive 
industry, which translates to the global supply base only being able to 
support approximately 70,000 cars.\375\ In addition, the production 
process for carbon fiber is significantly different than for 
traditional vehicle materials. We use this adoption feature as a proxy 
for stranded capital (i.e., when manufacturers amortize research, 
development, and tooling expenses over many years) from leaving the 
traditional processes, and to represent the significant paradigm change 
to tooling

[[Page 56227]]

and equipment that would be required to support molding carbon fiber 
panels. There are no other adoption features for MR in the LD analysis, 
and no adoption features for MR in the HDPUV analysis.
---------------------------------------------------------------------------

    \374\ See the Final TSD for CAFE Standards for MYs 2024-2026, 
and Chapter 3.4 of the Draft TSD accompanying this rulemaking for 
more information about carbon fiber.
    \375\ Sloan, J. 2020. Carbon Fiber Suppliers Gear up for Next 
Generation Growth. Available at: https://www.compositesworld.com/articles/carbon-fiber-suppliers-gear-up-for-next-gen-growth. 
(Accessed: May 31, 2023).
---------------------------------------------------------------------------

    In the Autonomie simulations, MR technology is simulated as a 
percentage of mass removed from the specific subsystems that make up 
the glider. The mass of subsystems that make up the vehicle's glider is 
different for every technology class, based on glider weight data from 
the A2Mac1 database \376\ and two NHTSA-sponsored studies that examined 
light-weighting a passenger car and light truck. We account for MR from 
powertrain improvements separately from glider MR. Autonomie considers 
several components for powertrain MR, including engine downsizing, and, 
fuel tank, exhaust systems, and cooling system light-weighting.\377\ 
With regard to the LDV fleet, the 2015 NAS report suggested an engine 
downsizing opportunity exists when the glider mass is light-weighted by 
at least 10 percent. The 2015 NAS report also suggested that 10 percent 
light-weighting of the glider mass alone would boost fuel economy by 3 
percent and any engine downsizing following the 10 percent glider MR 
would provide an additional 3 percent increase in fuel economy.\378\ 
The NHTSA light-weighting studies applied engine downsizing (for some 
vehicle types but not all) when the glider weight was reduced by 10 
percent. Accordingly, the analysis limits engine resizing to several 
specific incremental technology steps; important for this discussion, 
engines in the analysis are only resized when MR of 10 percent or 
greater is applied to the glider mass, or when one powertrain 
architecture replaces another architecture. For the HDPUV analysis, we 
do not allow engine downsizing at any MR level. This is because HDPUV 
designs are sized with the maximum GVWR and GCWR in mind, as discussed 
earlier in this section. We are objectively controlling the vehicles' 
utility and performance by this method in Autonomie. For example, if 
more MR technology is applied to a HD van, the payload capacity 
increases while maintaining the same maximum GVWR and GCWR.\379\ The 
lower laden weight enables these vehicles to improve fuel efficiency by 
increased capacity. A summary of how the different MR technology levels 
improve fuel consumption is shown in Figure II-30, Figure II-31, and 
Figure II-32 below.
---------------------------------------------------------------------------

    \376\ A2Mac1: Automotive Benchmarking. Available at: https://portal.a2mac1.com/. (Accessed: May 31, 2023). The A2Mac1 database 
tool is widely used by industry and academia to determine the bill 
of materials (a list of the raw materials, sub-assemblies, parts, 
and quantities needed to manufacture an end-product) and mass of 
each component in the vehicle system.
    \377\ Although we do not acount for mass reduction in 
transmissions, we do reflect design improvements as part of mass 
reduction when going from, for example, an older AT6 to a newer AT8 
that has similar if not lower mass.
    \378\ National Research Council. 2015. Cost, Effectiveness, and 
Deployment of Fuel Economy Technologies for Light-Duty Vehicles. The 
National Academies Press: Washington DC. Available at: https://doi.org/10.17226/21744. (Accessed: May 31, 2023).
    \379\ Transportation Research Board and National Research 
Council. 2010. Technologies and Approaches to Reducing the Fuel 
Consumption of Medium- and Heavy-Duty Vehicles. The National 
Academies Press: Washington, DC. p. 116. Available at: https://nap.nationalacademies.org/12845/. (Accessed: May 31, 2023).
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    Our MR costs are based on two NHTSA light-weighting studies--the 
teardown of a MY 2011 Honda Accord and a MY 2014 Chevrolet Silverado 
pickup truck \380\--and the 2021 NAS report.\381\ The costs for MR1-MR4 
rely on the light-weighting studies, while the cost of MR5 references 
the carbon fiber costs provided in the 2021 NAS report. The same cost 
curves are used for the HDPUV analysis, however, we used linear 
interpolation to shift the HDPUV MR2 curve (by roughly a factor of 20) 
to account for the fact that MR2 in the HDPUV analysis represents a 
different level than MR2 in the LD analysis. Unlike the other 
technologies in our analysis that have a fixed technology cost (for 
example, it costs about $3,000 to add a AT10L3 transmission to a LD SUV 
or pickup truck in MY 2027), the cost of MR is calculated on a dollar 
per pound saved basis based on a vehicle's starting weight. Put another 
way, for a given vehicle platform, a baseline mass is assigned using 
the aforementioned regression model. The amount of mass to reach each 
of the five levels of MR is calculated by the CAFE Model based on this 
baseline number and then multiplied by the dollar per pound saved 
figure for each of the five MR levels. The dollar per pound saved 
figure increases at a nearly linear rate going from MR0 to M4. However, 
this figure increases steeply going from MR4 to MR5 because the 
technology cost to realize the associated mass savings level is an 
order of magnitude larger. This dramatic increase is reflected by all 
three studies we relied on for MR costing, and we believe that it 
reasonably represents what manufacturers would expect to pay for 
including increasing amounts of carbon fiber on their vehicles. For the 
HDPUV analysis, there is also a significant cost increase from MR1 to 
MR2. This is because the MR going from MR1 to MR2 in the HDPUV fleet 
analysis is a larger step than going from MR1 to MR2 for the LD fleet 
analysis--5% to 7.5% off the glider compared to 1.4% to 13%. More MR 
demands higher costs.
---------------------------------------------------------------------------

    \380\ DOT HS 811 666, Singh, H., Final Report, Mass Reduction 
for Light-Duty Vehicles for Model Years 2017-2025, 2012; DOT HS 812 
487, Singh, H., Davies, J., Kramer, D. Fisher, A., Paramasuwom, M., 
Mogal, V., . . . and Ganesan, V., Mass Reduction for Light-Duty 
Vehicles for Model Years 2017-2025, 2018.
    \381\ This analysis applied the cost estimates per pound derived 
from passenger cars to all passenger car segments, and the cost 
estimates per pound derived from full-size pickup trucks to all 
light-duty truck and SUV segments. The cost estimates per pound for 
carbon fiber (MR5) were the same for all segments.
---------------------------------------------------------------------------

    Like past analyses, we considered several options for MR technology 
costs. Again, we determined that the NHTSA-sponsored studies accounted 
for significant factors that we believe are important to include our 
analysis, including materials considerations (material type and gauge, 
while considering real-world constraints such as manufacturing and 
assembly methods and complexity), safety (including the Insurance 
Institute for Highway Safety's (IIHS) small overlap tests), and 
functional performance (including towing and payload capacity, noise, 
vibration, and harshness (NVH)+, and gradeability in the pickup truck 
study).
b. Aerodynamic Improvements
    The energy required for a vehicle to overcome wind resistance, or 
more formally what is known as aerodynamic drag, ranges from minimal at 
low speeds to incredibly significant at highway speeds.\382\ Reducing a 
vehicle's aerodynamic drag is, therefore, an effective way to reduce 
the vehicle's fuel consumption. Aerodynamic drag is characterized as 
proportional to the frontal area (A) of the vehicle and a factor called 
the coefficient of drag (Cd). The coefficient of drag 
(Cd) is a dimensionless value that represents a moving 
object's resistance against air, which depends on the shape of the 
object and flow conditions. The frontal area (A) is the cross-sectional 
area of the vehicle as viewed from the front. Aerodynamic drag of a 
vehicles is often expressed as the product of the two values, 
CdA, which is also known as the drag area of a vehicle. The 
force imposed by aerodynamic drag increases with the square of vehicle 
velocity, accounting for the largest contribution to road loads at 
higher speeds.\383\
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    \382\ 2015 NAS Report, at 207.
    \383\ See, e.g., Pannone, G. 2015. Technical Analysis of Vehicle 
Load Reduction Potential for Advanced Clean Cars, Final Report. 
April 2015. Available at: https://ww2.arb.ca.gov/sites/default/files/2020-04/13_313_ac.pdf (Accessed: May 31, 2023). The graph on 
page 20 shows how at higher speeds the aerodyanmic force becomes the 
dominant load force.
---------------------------------------------------------------------------

    Manufacturers can reduce aerodynamic drag either by reducing the 
drag coefficient or reducing vehicle frontal area, which can be 
achieved by passive or active aerodynamic technologies. Passive 
aerodynamics refers to aerodynamic attributes that are inherent to the 
shape and size of the vehicle. Passive attributes can include the shape 
of the hood, the angle of the windscreen, or even overall vehicle ride 
height. Active aerodynamics refers to technologies that variably deploy 
in response to driving conditions. Example of active aerodynamic 
technologies are grille shutters, active air dams, and

[[Page 56230]]

active ride height adjustment. Manufacturers may employ both passive 
and active aerodynamic technologies to improve aerodynamic drag values.
    There are four levels of aerodynamic improvement (over the baseline 
AERO0) available in the LD analysis (AERO5, AERO10, AERO15, AERO20), 
and two levels of improvements available for the HDPUV analysis 
(AERO10, AERO20). There are fewer levels available for the HDPUV 
analysis because HDPUVs have less diversity in overall vehicle shape; 
prioritization of vehicle functionality forces a boxy shape and limits 
incorporation of many of the ``shaping''--based aerodynamic 
technologies, such as smaller rear-view mirrors, body air flow, rear 
diffusers, and so on. Refer back to Figure II-28 and Figure II-29 for a 
visual of each body style considered in the LD and HDPUV analyses.
    Each AERO level associates with 5, 10, 15, or 20 percent 
aerodynamic drag improvement values over a baseline computed for each 
vehicle body style. These levels, or bins, respectively correspond to 
the level of aerodynamic drag reduction over the baseline, e.g., 
``AERO5'' corresponds to the 5 percent aerodynamic drag improvement 
value over the baseline, and so on. While each level of aerodynamic 
drag improvement is technology agnostic--that is, manufacturers can 
ultimately choose how to reach each level by using whatever 
technologies work for the vehicle--we estimated a pathway to each 
technology level based on data from a NRC of Canada-sponsored wind 
tunnel testing program. The program included an extensive review of 
production vehicles utilizing aerodynamic drag improvement 
technologies, and industry comments.384 385 Our example 
pathways for achieving each level of aerodynamic drag improvements is 
discussed in Chapter 3.5 of the Draft TSD.
---------------------------------------------------------------------------

    \384\ Larose, G. et al. 2016. Evaluation of the Aerodynamics of 
Drag Reduction Technologies for Light-duty Vehicles--a Comprehensive 
Wind Tunnel Study. SAE International Journal of Passenger Cars--
Mechanical Systems 9(2): pp. 772-784. Available at: https://doi.org/10.4271/2016-01-1613. (Accessed: May 31, 2023).
    \385\ Larose, G. et al. 2016. Evaluation of the Aerodynamics of 
Drag Reduction Technologies for Light-duty Vehicles--a Comprehensive 
Wind Tunnel Study. SAE International Journal of Passenger Cars--
Mechanical Systems 9(2): pp. 772-784. Available at: https://doi.org/10.4271/2016-01-1613. (Accessed: May 31, 2023).
---------------------------------------------------------------------------

    We assigned baseline aerodynamic drag reduction technology levels 
based on vehicle body styles.\386\ We computed an average coefficient 
of drag based on vehicle body styles, using coefficient of drag data 
from the MY 2015 analysis fleet for the LD analysis, and data from the 
MY 2019 Chevy Silverado and MY 2020 Ford Transit and the MY 2022 Ford 
e-Transit for cargo vans for the HDPUV analysis. Different body styles 
offer different utility and have varying levels of baseline form drag. 
This analysis considers both frontal area and body style as 
unchangeable utility factors affecting aerodynamic forces; therefore, 
the analysis assumes all reduction in aerodynamic drag forces come from 
improvement in the drag coefficient. Then we used drag coefficients for 
each vehicle in the baseline fleet to establish a baseline aerodynamic 
technology level for each vehicle. We compared the vehicle's drag 
coefficient to the calculated drag coefficient by body style mentioned 
above, to assign baseline levels of aerodynamic drag reduction 
technology. We were able to find most vehicles' drag coefficients in 
manufacturer's publicly available specification sheets, however in 
cases where we could not find that information, we used engineering 
judgment to assign the baseline technology level.
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    \386\ These assignments do not necessarily match the body styles 
that manufacturers use for marketing purposes. Instead, we make 
these assignments based on engineering judgment and the categories 
used in our modeling, considering how this affects a vehicle's AERO 
and vehicle technology class assignments.
---------------------------------------------------------------------------

    We also look at vehicle body style and vehicle horsepower to 
determine which types of vehicles can adopt different aerodynamic 
technology levels. For the LD analysis, AERO15 and AERO20 cannot be 
applied to minivans, and AERO20 cannot be applied to convertibles, 
pickup trucks, and wagons. We also do not allow application of AERO15 
and AERO20 technology to vehicles with more than 780 horsepower. There 
are two main types of vehicles that inform this threshold: performance 
ICE vehicles and high-power BEVs. In the case of the former, we 
recognize that manufacturers tune aerodynamic features on these 
vehicles to provide desirable downforce at high speeds and to provide 
sufficient cooling for the powertrain, rather than reducing drag, 
resulting in middling drag coefficients despite advanced aerodynamic 
features. Therefore, manufacturers may have limited ability to improve 
aerodynamic drag coefficients for high performance vehicles with ICEs 
without reducing horsepower. Only 4,047 units of sales volume in the 
baseline fleet include limited application of aerodynamic technologies 
due to ICE vehicle performance.\387\
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    \387\ See the Market Data Input File.
---------------------------------------------------------------------------

    In the case of high-power BEVs, the 780-horsepower threshold is set 
above the highest peak system horsepower present on a BEV in the 2020 
fleet. We originally set this threshold based on vehicles in the MY 
2020 fleet in parallel with the 780-horsepower ICE limitation. For this 
analysis, the restriction does not have any functional effect because 
the only BEVs that have above 780-horsepower in the MY 2022 analysis 
fleet--the Tesla Model S and X Plaid, and variants of the Lucid Air--
are already assigned AERO20 as a baseline technology state and there 
are no additional levels of AERO technology left for those vehicles to 
adopt. Note that these high horsepower BEVs have extremely large 
battery packs to meet both performance and range requirements. These 
bigger battery packs make the vehicles heavier, which means they do not 
have the same downforce requirements as a similarly situated high-
horsepower ICE vehicle. Broadly speaking, BEVs have different 
aerodynamic behavior and considerations than ICE vehicles, allowing for 
features such as flat underbodies that significantly reduce drag.\388\ 
BEVs are therefore more likely to achieve higher AERO levels, so the 
horsepower threshold is set high enough that it does not restrict 
AERO15 and AERO20 application. BEVs that do not currently use high AERO 
technology levels are generally bulkier (e.g., SUVs or trucks) or lower 
budget vehicles.
---------------------------------------------------------------------------

    \388\ 2020 EPA Automotive Trends Report, at p. 227.
---------------------------------------------------------------------------

    There are no additional adoption features for aerodynamic 
improvement technologies in the HDPUV analysis. We limited the range of 
technology options for reasons discussed above, but both AERO 
technology levels are available to all HDPUV body styles.
    Figure II-33, Figure II-34, and Figure II-35 show the potential 
fuel consumption improvement from the baseline AERO0 technology. For 
example, the AERO20 values shown represent the range of potential fuel 
consumption improvement values that could be achieved through the 
replacement of AERO0 technology with AERO20 technology for every 
technology key that is not restricted from using AERO20. We use the 
change in fuel consumption values between entire technology keys, and 
not the individual technology effectiveness values. Using the change 
between whole technology keys captures the

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complementary or non-complementary interactions among technologies.
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    We carried forward the established AERO technology costs previously 
used in the 2020 final rule and again into the MY 2024-2026 standards 
analysis,\389\ and updated those costs to the dollar-year used in this 
analysis. For LD AERO improvements, the cost to achieve AERO5 is 
relatively low, as manufacturers can make most of the improvements 
through body styling changes. The cost to achieve AERO10 is higher than 
AERO5, due to the addition of several passive aerodynamic technologies, 
and consecutively the cost to achieve AERO15 and AERO20 are much higher 
than AERO10 due to use of both passive and active aerodynamic 
technologies. The two AERO technology levels available for HDPUVs are 
similar in technology type and application to LDVs in the same 
technology categories, specifically light trucks. Because of this 
similarity, and unlike other technology areas that are required to 
handle higher loads or greater wear, aerodynamics technologies can be 
almost directly ported between fleets. As a result, there is no 
difference in technology cost between LD and HDPUV fleets for this 
analysis. The cost estimates are based on CBI submitted by the 
automotive industry in advance of the 2018 CAFE NPRM, and on our 
assessment of manufacturing costs for specific aerodynamic 
technologies. See the 2018 PRIA for discussion of the cost 
estimates.\390\ We received no additional comments from stakeholders 
regarding the costs established in the 2018 PRIA during the MY 2024-
2026 standards analysis and continued to use the established costs for 
this analysis. Draft TSD Chapter 3.5 contains additional discussion of 
aerodynamic improvement technology costs, and costs for all technology 
classes across all MYs are in the CAFE Model's Technologies Input File.
---------------------------------------------------------------------------

    \389\ See the FRIA accompanying the 2020 final rule, Chapter 
VI.C.5.e.
    \390\ See the PRIA accompanying the 2018 NPRM, Chapter 
6.3.10.1.2.1.2 for a discussion of these cost estimates.
---------------------------------------------------------------------------

c. Low Rolling Resistance Tires
    Tire rolling resistance burns additional fuel when driving. As a 
car or truck tire rolls, at the point the tread touches the pavement, 
the tire flattens-out to create what tire engineers call the contact 
patch. The rubber in the contact patch deforms to mold to the tiny 
peaks and valleys of the payment. The interlock between the rubber and 
these tiny peaks and valleys creates grip. Every time the contact patch 
leaves the road surface as the tire rotates, it must recover to its 
original shape and then as the tire goes all the way around it must 
create a new contact patch that molds to a new piece of road surface. 
However, this molding and repeated re-molding action takes energy. Just 
like when a person stretches a rubber band it takes work, so does 
deforming the rubber and the tire to form the contact patch. When 
thinking about the efficiency of driving a car down the road, this 
means that not all the energy produced by a vehicle's engine can go 
into propelling the vehicle forward. Instead, some small, but 
appreciable, amount goes into deforming the tire and creating the 
contact patch repeatedly. This also explains why tires with low 
pressure have higher rolling resistance than properly inflated tires. 
When the tire pressure is low, the tire deforms more to create the 
contact patch which is the same as stretching the rubber farther in the 
analogy above. The larger deformations burn up even more energy and 
results in worse fuel mileage. Lower-rolling-resistance tires have 
characteristics that reduce frictional losses associated with the 
energy dissipated mainly in the deformation of the tires under load, 
thereby improving fuel economy.
    We use three levels of low rolling resistance tire technology for 
LDVs and two levels for HDPUVs. Each level of low rolling resistance 
tire technology reduces rolling resistance by 10 percent from an 
industry-average baseline rolling resistance coefficient (RRC) value of 
0.009.\391\ While the industry-average baseline RRC is based on 
information from LDVs, we also determined that baseline is appropriate 
for HDPUVs. RRC data from a NHTSA-sponsored study shows that similar 
vehicles across the LD and HDPUV categories have been able to achieve 
similar RRC improvements. See Chapter 3.6 of the Draft TSD for more 
information on this comparison. Table II-17 shows the LD and HDPUV low 
rolling resistance technology options and their associated RRC.
---------------------------------------------------------------------------

    \391\ See Technical Analysis of Vehicle Load Reduction by 
CONTROLTEC for California Air Resources Board (April 29, 2015). We 
determined the industry-average baseline RRC using a CONTROLTEC 
study prepared for the CARB, in addition to considering CBI 
submitted by vehicle manufacturers prior to the 2018 LD NPRM 
analysis. The RRC values used in this study were a combination of 
manufacturer information, estimates from coast down tests for some 
vehicles, and application of tire RRC values across other vehicles 
on the same platform. The average RRC from surveying 1,358 vehicle 
models by the CONTROLTEC study is 0.009. The CONTROLTEC study 
compared the findings of their survey with values provided by the 
U.S. Tire Manufacturers Association for original equipment tires. 
The average RRC from the data provided by the U.S. Tire 
Manufacturers Association is 0.0092, compared to the average of 
0.009 from CONTROLTEC.

 Table II-17--Tire Rolling Resistance Technologies and Their Associated
                  Rolling Resistance Coefficient (RRC)
------------------------------------------------------------------------
                                                              Rolling
                                                            resistance
                       Technology                           coefficient
                                                           (RRC)  (N/N)
------------------------------------------------------------------------
ROLL0...................................................          0.0090
ROLL10..................................................          0.0081
ROLL20..................................................          0.0072
ROLL30..................................................          0.0063
------------------------------------------------------------------------

    We have been using ROLL10 and ROLL20 in the last several CAFE Model 
analyses. New for this analysis is ROLL30 for the LD fleet. In past 
rulemakings, we did not consider ROLL30 due to lack of widespread 
commercial adoption of ROLL30 tires in the fleet within the rulemaking 
timeframe, despite commenters' argument on availability of the 
technology on current vehicle models and possibility that there would 
be additional tire improvements over the next decade.\392\ Comments we 
received during the comment period for the last CAFE rule also 
reflected the application of ROLL30 by OEMs, although they discouraged 
considering the technology due to high cost and possible wet traction 
reduction. With increasing use of ROLL30 application by 
OEMs,393 394 395 and material selection making it possible 
to design low rolling resistance independent of tire wet grip 
(discussed in detail in Chapter 3.6 of the Draft TSD), we now consider 
ROLL30 as a viable future technology during this rulemaking period. We 
believe that the tire industry is in the process of moving automotive 
manufacturers towards higher levels of rolling resistance technology in 
the vehicle fleet. We believe that at this time, the emerging tire 
technologies that would achieve 30 percent improvement in rolling 
resistance, like changing tire profile, stiffening tire walls, or 
adopting improved tires along with active chassis control, among other 
technologies, will be available for commercial adoption in

[[Page 56234]]

the fleet during this rulemaking timeframe.
---------------------------------------------------------------------------

    \392\ NHTSA-2018-0067-11985.
    \393\ Docket No. NHTSA-2021-0053-0010, Evaluation of Rolling 
Resistance and Wet Grip Performance of OEM Stock Tires Obtained from 
NCAP Crash Tested Vehicles Phase One and Two, Memo to Docket--
Rolling Resistance Phase One and Two.
    \394\ Technical Analysis of Vehicle Load Reduction by CONTROLTEC 
for California Air Resources Board (April 29, 2015).
    \395\ NHTSA DOT HS 811 154.
---------------------------------------------------------------------------

    However, we did not consider ROLL30 for the HDPUV fleet, for 
several reasons. We do not believe that HDPUV manufacturers will use 
ROLL30 tires because of the significant added cost for the technology 
while they would see more fuel efficiency benefits from powertrain 
improvements. As discussed further below, our cost estimates for ROLL30 
technology--which incorporate both technology and materials costs--are 
approximately double the costs of ROLL20. In addition, a significant 
majority of the HDPUV fleet currently employs no low rolling resistance 
tire technology. We believe that HDPUV manufacturers will still move 
through ROLL10 and ROLL20 technology in the rulemaking timeframe. That 
said, we welcome any data or feedback from stakeholders showing a 
pathway to ROLL30 (i.e., vehicles that can achieve a RRC value of 
0.0063) for HDPUVs.
    Assigning low rolling resistance tire technology to the baseline 
fleet is difficult because RRC data is not part of tire manufacturers' 
publicly released specifications, and because vehicle manufacturers 
often offer multiple wheel and tire packages for the same nameplate. 
Consistent with previous rules, we used a combination of CBI data, data 
from a NHTSA-sponsored ROLL study, and assumptions about parts-sharing 
to assign tire technology in the baseline fleet. A slight majority of 
vehicles (52.9%) in the baseline LD fleet do not use any ROLL 
improvement technology, while 16.2% of baseline vehicles use ROLL10 and 
24.9% of baseline vehicles use ROLL20. Only 6% of vehicles in the 
baseline LD fleet use ROLL30. Most (74.5%) vehicles in the HDPUV fleet 
do not use any ROLL improvement technology, and 3.0% and 22.5% use 
ROLL10 and ROLL20, respectively.
    The CAFE Model can apply ROLL technology at either a vehicle 
refresh or redesign. We recognize that some vehicle manufacturers 
prefer to use higher RRC tires on some performance cars and SUVs. Since 
most of performance cars have higher torque, to avoid tire slip, OEMs 
prefer to use higher RRC tires for these vehicles. Like the aerodynamic 
technology improvements discussed above, we applied ROLL technology 
adoption features based on vehicle horsepower and body style. All 
vehicles in the LD and HDPUV fleets that have below 350hp can adopt all 
levels of ROLL technology.
    Table II-18 shows that all LDVs under 350hp can adopt ROLL 
technology, and as vehicle hp increases, fewer vehicles can adopt the 
highest levels of ROLL technology. Note that ROLL30 is not available 
for vehicles in the HDPUV fleet not because of an adoption feature, but 
because it is not included in the ROLL technology pathway.

                                                    Table II-18--When Can ROLL Technology Be Applied?
--------------------------------------------------------------------------------------------------------------------------------------------------------
          Technology                                     Light Duty                                                      HDPUV
--------------------------------------------------------------------------------------------------------------------------------------------------------
    Engine horsepower (hp)          <350            >=350           >=405          >=500           <350          >=350          >=405          >=500
--------------------------------------------------------------------------------------------------------------------------------------------------------
ROLL0........................  All body        All body        All body        All body       All body       All body       All body       All body
                                styles.         styles.         styles.         styles.        styles.        styles.        styles.        styles.
ROLL10.......................  All body        All body        All body        --Pickup       All body       All body       All body       --Work truck.
                                styles.         styles.         styles.         truck.         styles.        styles.        styles.
ROLL20.......................  All body        All body        --Pickup truck  No body        All body       All body       --Work truck.  No body
                                styles.         styles.        --SUV.........   styles.        styles.        styles.       --Work van...   styles.
                                                               --Van.........                                               --Fleet SUV..
                                                               --Minivan.....                                               --Chassis Cab
                                                                                                                            --Cutaway....
ROLL30.......................  All body        --Pickup truck  No body styles  No body        All body       N/A..........  N/A..........  N/A.
                                styles.        --Sport                          styles.        styles.
                                                Utility.
                                               --Van.........
                                               --Minivan.....
--------------------------------------------------------------------------------------------------------------------------------------------------------

    Figure II-36, Figure II-37, and Figure II-38 show how effective the 
different levels of ROLL technology are at improving vehicle fuel 
consumption.
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    DMCs and learning rates for ROLL10 and ROLL20 are the same as prior 
analyses,\396\ but are updated to the dollar-year used in this 
analysis. In the absence of ROLL30 DMCs from tire manufacturers, 
vehicle manufacturers, or studies, to develop the DMC for ROLL30 we 
extrapolated the DMCs for ROLL10 and ROLL20. We seek comment on this 
approach, and if we receive updated information from tire or vehicle 
manufacturers, or other studies, we will update it for future analyses. 
In addition, we used the same DMCs for the LD and HDPUV analyses. This 
is because the original cost of a potentially heaver or sturdier HDPUV 
tire is already accounted for in the baseline MSRP of a HDPUV in our 
baseline, and the DMC represents the added cost of the improved tire 
technology. In addition, as discussed above, LD and HDPUV tires are 
often interchangeable. We believe that the added cost of each tire 
technology accurately represents the price difference that would be 
experienced by the different fleets. ROLL technology costs are 
discussed in detail in Chapter 3.6 of the Draft TSD, and ROLL 
technology costs for all vehicle technology classes can be found in the 
CAFE Model's Technologies Input File.
---------------------------------------------------------------------------

    \396\ See NRC/NAS Special Report 286, Tires and Passenger 
Vehicle Fuel Economy: Informing Consumers, Improving Performance 
(2006); Corporate Average Fuel Economy for MY 2011 Passenger Cars 
and Light Trucks, Final Regulatory Impact Analysis (March 2009), at 
V-137; Joint Technical Support Document: Rulemaking to Establish 
Light-Duty Vehicle Greenhouse Gas Emission Standards and Corporate 
Average Fuel Economy Standards (April 2010), at 3-77; Draft 
Technical Assessment Report: Midterm Evaluation of Light-Duty 
Vehicle Greenhouse Gas Emission Standards and Corporate Average Fuel 
Economy Standards for Model Years 2022-2025 (July 2016), at 5-153 
and 154, 5-419. In brief, the estimates for ROLL10 are based on the 
incremental $5 value for four tires and a spare tire in the NAS/NRC 
Special Report and confidential manufacturer comments that provided 
a wide range of cost estimates. The estimates for ROLL20 are based 
on incremental interpolated ROLL10 costs for four tires (as NHTSA 
and EPA believed that ROLL20 technology would not be used for the 
spare tire), and were seen to be generally fairly consistent with 
CBI suggestions by tire suppliers.
---------------------------------------------------------------------------

5. Simulating AC Efficiency and Off-Cycle Technologies
    Off-cycle and AC efficiency technologies can provide fuel economy 
benefits in real-world vehicle operation, but the traditional 2-cycle 
test procedures (i.e., FTP and HFET) used to measure fuel economy 
cannot fully capture those benefits.\397\ Off-cycle technologies can 
include, but are not limited to, thermal control technologies, high-
efficiency alternators, and high-efficiency exterior lighting. As an 
example, manufacturers can claim a benefit for thermal control 
technologies like active seat ventilation and solar reflective surface 
coating, which help to regulate the temperature within the vehicle's 
cabin--making it more comfortable for the occupants and reducing the 
use of low-efficiency heating, ventilation, and air-conditioning (HVAC) 
systems. AC efficiency technologies are technologies that reduce the 
operation of or the loads on the compressor, which pressurizes AC 
refrigerant. The less the compressor operates or the more efficiently 
it operates, the less load the compressor places on the engine or 
battery storage system, resulting in better fuel efficiency. AC 
efficiency technologies can include, but are not limited to, blower 
motor controls, internal heat exchangers, and improved condensers/
evaporators.
---------------------------------------------------------------------------

    \397\ See 49 U.S.C 32904(c) (``The Administrator shall measure 
fuel economy for each model and calculate average fuel economy for a 
manufacturer under testing and calculation procedures prescribed by 
the Administrator. The Administrator shall use the same procedures 
for passenger automobiles the Administrator used for model year 1975 
(weighted 55 percent urban cycle and 45 percent highway cycle), or 
procedures that give comparable results.'').
---------------------------------------------------------------------------

    Vehicle manufacturers have the option to generate credits for off-
cycle technologies and improved AC systems under the EPA's 
CO2 program and receive a fuel consumption improvement value 
(FCIV) equal to the value of the benefit not captured on the 2-cycle 
test under NHTSA's CAFE program. The FCIV is not a ``credit'' in the 
NHTSA CAFE program--unlike, for example, the statutory overcompliance 
credits prescribed in 49 U.S.C. 32903--but FCIVs increase the reported 
fuel economy of a manufacturer's fleet, which is used to determine 
compliance. EPA applies FCIVs during determination of a fleet's final 
average

[[Page 56237]]

fuel economy reported to NHTSA.\398\ We only calculate and apply FCIVs 
at a manufacturer's fleet level, and the improvement is based on the 
volume of the manufacturer's fleet that contains qualifying 
technologies.
---------------------------------------------------------------------------

    \398\ 49 U.S.C. 32904. Under EPCA, the Administrator of the EPA 
is responsible for calculating and measuring vehicle fuel economy.
---------------------------------------------------------------------------

    We currently do not model AC efficiency and off-cycle technologies 
in the CAFE Model like we model other vehicle technologies, for several 
reasons. Each time we add a technology option to the CAFE Model's 
technology pathways we increase the number of Autonomie simulations by 
approximately a hundred thousand. This means that to add just five AC 
efficiency and five off-cycle technology options would double our 
Autonomie simulations to around two million total simulations. In 
addition, 40 CFR 600.512-12 does not require manufacturers to submit 
information regarding AC efficiency and off-cycle technologies on 
individual vehicle models in their FMY reports to EPA and NHTSA.\399\ 
In their FMY reports, manufacturers are only required to provide 
information about AC efficiency and off-cycle technology application at 
the fleet level. However, starting with MY 2023, manufacturers are 
required to submit AC efficiency and off-cycle technology data to NHTSA 
in the new CAFE Projections Reporting Template for PMY, MMY and 
supplementary reports. Once we begin evaluating manufacturer 
submissions in the CAFE Projections Reporting Template we may 
reconsider in future analyses how off-cycle and AC efficiency 
technologies are evaluated in the analysis. However, developing a 
robust methodology for including off-cycle and AC efficiency 
technologies in the analysis depends on manufacturers giving us robust 
data.
---------------------------------------------------------------------------

    \399\ 40 CFR 600.512-12.
---------------------------------------------------------------------------

    Instead, the CAFE Model applies predetermined AC efficiency and 
off-cycle benefits to each manufacturer's fleet after the CAFE Model 
applies traditional technology pathway options. The CAFE Model attempts 
to apply pathway technologies and AC efficiency and off-cycle 
technologies in a way that both minimizes cost and allows the 
manufacturer to meet a given level of CAFE standard without over or 
under complying. The predetermined benefits that the CAFE Model applies 
for AC efficiency and off-cycle technologies are based on EPA's 2022 
Trends Report and CBI compliance data from vehicle manufacturers. We 
started with each manufacturer's latest reported values and 
extrapolated the values to the regulatory cap on benefits that 
manufacturers are allowed to claim, considering each manufacturer's 
fleet composition (i.e., passenger cars versus light trucks) and 
historic AC efficiency and off-cycle technology use. In general, data 
shows that manufacturers apply less off-cycle technology to passenger 
cars than pickup trucks, and our input assumptions reflect that. 
Additional details about how we determined AC efficiency and off-cycle 
technology application rates are discussed Chapter 3.7 of the Draft 
TSD.
    New for this analysis, we also developed a methodology for 
considering BEV AC efficiency and off-cycle technology application. We 
did this because the analytical ``no-action'' baseline against which we 
measure the costs and benefits of our standards includes an appreciable 
number of BEVs. Because BEVs are not equipped with a traditional engine 
or transmission, they cannot benefit from off-cycle technologies like 
engine idle start-stop, active transmission and engine warm-up, and 
high efficiency alternator technologies. However, BEVs still benefit 
from technologies like high efficiency lighting, solar panels, active 
aerodynamic improvement technologies, and thermal control technologies. 
We calculated the maximum off-cycle benefit that the model could apply 
for each manufacturer and each MY based on off-cycle technologies that 
could be applied to BEVs and the percentage of BEVs in each 
manufacturer's fleet. Note that we do not include PHEVs in this 
calculation, because they still use a conventional engine and 
transmission. We discuss additional details and assumptions for this 
calculation in Chapter 3.7 of the Draft TSD.
    Note that we do not model AC efficiency and off-cycle technology 
benefits for HDPUVs. We have received petitions for off-cycle benefits 
for HDPUVs from manufacturers, but to date, none have been approved.
    Because the CAFE Model applies AC efficiency and off-cycle 
technology benefits independent of the technology pathways, we must 
account for the costs of those technologies independently as well. We 
generated costs for these technologies on a dollars per gram of 
CO2 per mile ($ per g/mi) basis, as AC efficiency and off-
cycle technology benefits are applied in the CAFE Model on a gram per 
mile basis (as in the regulations). Like the last CAFE analysis, we 
used data from EPA's Proposed Determination TSD and the 2012 Joint 
NHTSA/EPA TSD, updated to 2018$ with an indirect cost markup and 
relatively flat learning rate applied. We did not have time to update 
these costs to 2021$, but will do so for the final rule, and we expect 
the impact to be minimal. Additional details and assumptions used for 
A/C Efficiency and off-cycle costs is discussed in Chapter 3.7 of the 
Draft TSD.

E. Consumer Responses to Manufacturer Compliance Strategies

    The previous subsections in Section II have so far discussed how 
manufacturers might respond to changes to the standards. While the 
technology analysis is informative of the different compliance 
strategies available to manufactures, the tangible costs and benefits 
that accrue because of the standards are dependent on how consumers 
respond to the decisions made by manufacturers. Many, if not most, of 
the benefits and costs resulting from changes to standards are private 
benefits that accrue to the buyers of new vehicles, produced in the MYs 
under consideration. These benefits and costs largely flow from the 
changes to vehicle ownership and operating costs that result from 
improved fuel economy, and the cost of the technology required to 
achieve those improvements. The remaining benefits are also derived 
from how consumers use--or do not use--vehicles. Since they are not 
borne directly by the consumer who purchases or operates the new 
vehicle, we categorize these as ``external'' benefits, even if they do 
not necessarily meet the economic definition of an externality. The 
next few subsections walk through how the analysis models how consumers 
respond to changes to vehicles implemented by manufacturers to respond 
to the CAFE and HDPUV FE standards. NHTSA seeks comment on the 
following discussion.
1. Macroeconomic and Consumer Behavior Assumptions
    This proposal includes a comprehensive economic analysis of the 
impacts of the proposed standards. Most of the effects measured are 
influenced by macroeconomic conditions that are exogenous to the 
agency's influence. For example, fuel prices are mainly determined by 
global supply and demand, and yet they partially determine how much 
fuel efficiency technology manufacturers will apply to U.S. vehicles, 
how much consumers are willing to pay for a new vehicle, the amount of 
travel in which all users engage, and the value of each gallon saved 
from higher standards. Constructing these forecasts requires robust 
projections of macroeconomic variables that span the timeframe of the 
analysis, including real GDP, consumer

[[Page 56238]]

confidence, U.S. population, and real disposable personal income.
    The analysis presented along with this proposal employs fuel price 
forecasts developed by the EIA's NEMS. EIA is an agency within the U.S. 
DOE which collects, analyzes, and disseminates independent and 
impartial energy information to promote sound policymaking, efficient 
markets, and public understanding of energy and its interaction with 
the economy and the environment. EIA uses NEMS to produce its AEO, 
which presents forecasts of future fuel prices, among many other 
energy-related variables. The analysis uses the 2022 EIA forecasts of 
fuel prices and electricity prices.
    The analysis also uses IHS Markit Global Insight forecasts of U.S. 
population, GDP, total number of households, and disposable personal 
income. We chose to use these estimates as they are the same estimates 
employed by EIA to construct their AEO projections. The agency uses a 
forecast of consumer confidence to project sales from the IHS Markit 
Global Insight long-term macroeconomic model.
    While these macroeconomic assumptions are important inputs to the 
analysis, they are also subject to the most uncertainty--particularly 
over the full lifetimes of the vehicles affected by this proposed rule. 
The agency uses low and high cases from the AEO as bounding cases for 
fuel price sensitivity analyses. The purpose of the sensitivity 
analyses, discussed in greater detail in Chapter 9 of the PRIA, is not 
to posit a more credible future state of the world than the central 
case assumes--we assume the central case is the most likely future 
state of the world--but rather to measure the degree to which important 
outcomes can change under different assumptions about fuel prices.
    The first year simulated in this analysis is 2022, though it is 
based on observational data (rather than forecasts) to the greatest 
extent possible. The elements of the analysis that rely most heavily on 
the macroeconomic inputs--aggregate demand for VMT, new vehicle sales, 
used vehicle retirement rates--all reflect the continued return to pre-
pandemic growth rates (in all the regulatory alternatives). See Chapter 
4.1 of the Draft TSD for a more complete discussion of the 
macroeconomic assumptions made for the analysis.
    Another key assumption that permeates throughout the analysis is 
how much consumers are willing to pay for fuel economy. Increased fuel 
economy offers vehicle owners savings through reduced fuel expenditures 
throughout the lifetime of a vehicle. If buyers fully value the savings 
in fuel costs that result from driving (and potentially re-selling) 
vehicles with higher fuel economy and manufacturers supply all 
improvements in fuel economy that buyers demand, market-determined 
levels of fuel economy would reflect both the cost of improving it and 
the private benefits from doing so. In that case, regulations on fuel 
economy would only be necessary to reflect environmental or other 
benefits other than to buyers themselves. But if consumers instead 
undervalue future fuel savings or are otherwise unable to purchase 
their optimal levels of fuel economy due to market failures, they will 
underinvest in fuel economy and manufacturers would spend too little on 
fuel-saving technology (or deploy its energy-saving benefits to improve 
vehicles' other attributes). In that case, more stringent fuel economy 
standards could lead manufacturers to adopt improvements in fuel 
economy that not only reduce external costs from producing and 
consuming fuel to appropriate levels but also improve consumer welfare.
    Increased fuel economy offers vehicle owners significant potential 
savings. The analysis shows that the value of prospective fuel savings 
exceeds manufacturers' technology costs to comply with the preferred 
alternatives for HDPUVs and light trucks discounted at 3 percent, and 
the fuel savings for passenger automobiles pays back a significant 
portion of the upfront costs. It would seem reasonable to assume that 
well-informed vehicle shoppers, if without time constraints or other 
barriers to rational decision-making, will recognize the full value of 
fuel savings from purchasing a model that offers higher fuel economy, 
since they would enjoy an equivalent increase in their disposable 
income and the other consumption opportunities it affords them; or for 
commercial operators, higher fuel efficiency would free up additional 
capital for either higher profits or additional business ventures. If 
consumers did value the full amount of fuel savings, more fuel-
efficient vehicles would functionally be less costly for consumers to 
own when considering both their initial purchase prices and subsequent 
operating costs, thus making the models that manufacturers are likely 
to offer under stricter alternatives more attractive than those 
available under the No-Action Alternative.
    Recent econometric research is divided between studies concluding 
that consumers value most or all of the potential savings in fuel costs 
from driving higher-mpg vehicles, and those concluding that consumers 
significantly undervalue expected fuel savings. More circumstantial 
evidence appears to show that consumers do not fully value the expected 
lifetime fuel savings from purchasing higher-mpg models. Although the 
average fuel economy of new light vehicles reached an all-time high in 
MY 2021 of 25.4 mpg,\400\ this is still significantly below the fuel 
economy of the fleet's most efficient vehicles that are readily 
available to consumers.\401\ Manufacturers have repeatedly informed the 
agency that consumers only value between 2 to 3 years-worth of fuel 
savings when making purchasing decisions. And in the last CAFE 
rulemaking, the Environmental Defense Fund commented with a Consumer 
Reports article indicating that 64 percent of consumers ranked fuel 
economy as extremely or very important, and viewed fuel economy as the 
attribute that has the most room for improvement, but only 29% of those 
same respondents would be willing to pay for technology that paid back 
over a period in excess of 3 years with the average consumer willing to 
pay for fuel economy that recouped the upfront costs between 2 and 3 
years.\402\
---------------------------------------------------------------------------

    \400\ See EPA 2022 Automotive Trends Report at 5. Available at 
https://www.epa.gov/system/files/documents/2022-12/420r22029.pdf. 
(Accessed: May 31, 2023).
    \401\ Id. At 9.
    \402\ 87 FR 25856.
---------------------------------------------------------------------------

    The potential for buyers to voluntarily forego improvements in fuel 
economy that offer savings exceeding their initial costs is one example 
of what is often termed the ``energy-efficiency gap.'' This appearance 
of such a gap, between the level of energy efficiency that would 
minimize consumers' overall expenses and what they actually purchase, 
is typically based on engineering calculations that compare the initial 
cost for providing higher energy efficiency to the discounted present 
value of the resulting savings in future energy costs. There has long 
been an active debate about why such a gap might arise and whether it 
actually exists. Economic theory predicts that economically rational 
individuals will purchase more energy-efficient products only if the 
savings in future energy costs they offer promise to offset their 
higher initial costs.
    On the other hand, behavioral economics has documented numerous 
situations in which the decision-making of consumers differs in 
important ways from the from the predictions of the standard model of 
rational consumer behavior, especially for choices under

[[Page 56239]]

uncertainty.\403\ The future value of purchasing a model that offers 
higher fuel economy is uncertain for several reasons, but particularly 
because the mileage any particular consumer experiences will generally 
differ from that shown on fuel economy labels, potential buyers may be 
uncertain how much they will actually drive a new vehicle, future 
resale prices may be uncertain, and future fuel prices are highly 
uncertain. Recent research indicates that typical consumers exhibit 
several behavioral departures from the rational economic model, some of 
which could explain undervaluing of fuel economy to an extent roughly 
consistent with the agency's assumed 30-month payback rule. These 
include loss aversion (valuing potential losses more than potential 
gains when faced with an uncertain choice), present bias (the tendency 
to use DRs that decrease over time, also known as hyperbolic 
discounting), certainty bias (a preference for certain over uncertain 
options) and inattention or satisficing.\404\ Behavioral economic 
theory also differs from rational economic theory by recognizing that 
consumers' preferences may change depending on the context of a choice. 
In addition, behavioral economics recognizes that by conscious 
deliberation or learning by experience consumers can overrule behaviors 
that differ from the rational economic model. There are also a variety 
of classic externalities that could prevent consumers in an unregulated 
market from fully purchasing levels of fuel efficiency that will 
deliver net present savings, including informational asymmetries 
between consumers, dealerships, and manufacturers; market power; first-
mover disadvantages for both consumers and manufacturers; principal-
agent split incentives between vehicle purchasers and vehicle drivers; 
and positional externalities.\405\
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    \403\ e.g. Dellavigna, S. 2009. Psychology and economics: 
Evidence from the field. Journal of Economic Literature. 47(2): pp. 
315-372.
    \404\ Satisficing is when a consumer finds a solution that meets 
enough of their requirements instead of searching for a vehicle that 
optimizes their utility.
    \405\ For a discussion of these potential market failures, see 
Rothschild, R. and Schwartz, J. (2021) ``Tune Up: Fixing Market 
Failures to Cut Fuel Costs and Pollution from Cars and Trucks'' 
Institute for Policy Integrity. New York University School of Law.
---------------------------------------------------------------------------

    If the behavioral explanation for how potential new buyers choose 
fuel economy is more accurate than the rational economic model, there 
could be important implications for our cost-benefit analysis. Because 
preferences can be context dependent, some consumers may view the 
decision whether to buy a model offering increased fuel economy in a 
market without increasing fuel economy standards as a risky choice, 
because their return from the purchase will vary with their future 
travel activity and gasoline prices. In contrast, if the fuel economies 
of most new vehicles are increasing in response to higher standards, 
they may view the relative risk/reward of purchasing a vehicle with 
higher fuel economy more favorably. When fuel economy standards 
increase incrementally over several years, consumers' experience might 
lead them to conclude that the value of fuel savings was worth the 
higher cost to purchase more fuel-efficient models, even if that was 
not their initial view. Such differences from rational economic theory 
could affect NHTSA's estimates of the impacts of raising standards on 
new vehicle sales as well as the usage and retirement rates of used 
vehicles, with important implications for safety, emissions, and 
employment, as well as for the welfare of producers and consumers.
    The analysis assumes that potential buyers value only the 
undiscounted savings in fuel costs from purchasing a higher-mpg model 
they expect to realize over the first 30 months (i.e., 2.5 years) they 
own it. NHTSA feels that 30 months is supported by the totality of 
present literature and is consistent with manufacturer assumptions 
about consumer demand. Depending on the DR buyers are assumed to apply, 
this amounts to 25-30% of the expected savings in fuel costs over its 
entire lifetime. These savings would offset only a fraction of the 
expected increase in new vehicle prices that NHTSA estimates will be 
required for manufacturers to recover their increased costs for making 
required improvements to fuel economy. NHTSA seeks comment on whether 
30 months of undiscounted fuel savings is an appropriate measure for 
the analysis of consumer willingness to pay for fuel economy. The 
assumption also has important implications for other outcomes of the 
model, including for VMT, safety, and air pollution emissions 
projections, and NHTSA has included a handful of sensitivity cases to 
examine the impacts of higher and lower payback periods on the 
analysis. If commenters believe a different amount of time should be 
used for the payback assumption, it would be most helpful to NHTSA if 
commenters could define the amount of time, provide an explanation of 
why that amount of time is preferable, and provide any data or 
information on which the amount of time is based. These concepts are 
explored more thoroughly in Chapter 4.2.1.1 of the Draft TSD and 
Chapter 2.4 of the PRIA.
    It is possible that commercial operators, to the extent they act as 
profit-maximizing entities could value the tradeoff between long-term 
fuel savings and upfront capital differently than the average non-
commercial consumer. However, both commercial and non-commercial 
consumers may face their own set of market failures and other 
constraints that may prevent them from purchasing in an un-regulated 
market the level of fuel efficiency that may maximize their private net 
benefits. Additionally, the CAFE Model is unable to distinguish between 
these two types of purchasers. Given this constraint, NHTSA believes 
that using the same payback period for the HDPUV fleet as for the LD 
fleet made sense. Similar to the LD analysis, the agency is including 
several sensitivity cases testing alternative payback assumptions for 
HDPUVs.
2. Fleet Composition
    The composition of the on-road fleet--and how it changes in 
response to the standards--determines many of the costs and benefits of 
the proposal. For example, how much fuel the LD fleet consumes is 
dependent on the number and efficiency of new vehicles sold, older (and 
less efficient) vehicles retired, and how much those vehicles are 
driven.
    Until the 2020 final rule, all previous CAFE rulemaking analyses 
used static fleet forecasts that were based on a combination of 
manufacturer compliance data, public data sources, and proprietary 
forecasts (or product plans submitted by manufacturers). When 
simulating compliance with regulatory alternatives, those analyses 
projected identical sales and retirements across the alternatives, for 
each manufacturer down to the make/model level--where the exact same 
number of each model variant was assumed to be sold in a given MY under 
both the least stringent alternative (typically the baseline) and the 
most stringent alternative considered (intended to represent ``maximum 
technology'' scenarios in some cases).
    However, a fleet forecast is unlikely to be representative of a 
broad set of regulatory alternatives with significant variation in the 
cost of new vehicles. Several commenters on previous regulatory actions 
and peer reviewers of the CAFE Model encouraged consideration of the 
potential impact of fuel efficiency standards on new vehicle

[[Page 56240]]

prices and sales, the changes to compliance strategies that those 
shifts could necessitate, and the downstream impact on vehicle 
retirement rates. In particular, the continued growth of the utility 
vehicle segment causes changes within some manufacturers' fleets as 
sales volumes shift from one region of the footprint curve to another, 
or as mass is added to increase the ride height of a vehicle on a sedan 
platform to create a crossover utility vehicle, which exists on the 
same place of the footprint curve as the sedan upon which it might be 
based.
    The analysis accompanying this proposal, like the 2020 and 2022 
rulemakings, dynamically simulates changes in the vehicle fleet's size, 
composition, and usage as manufacturers and consumers respond to 
regulatory alternatives, fuel prices, and macroeconomic conditions. The 
analysis of fleet composition is comprised of two forces, how new 
vehicle sales--the flow of new vehicles into the registered 
population--change in response to regulatory alternatives, and the 
influence of economic and regulatory factors on vehicle retirement 
(otherwise known as scrappage). Below are brief descriptions of how the 
agency models sales and scrappage. For a full explanation, refer to 
Chapter 4.2 of the Draft TSD. Particularly given the broad uncertainty 
discussed in Chapter 4.2 of the Draft TSD, NHTSA seeks comment on the 
discussion below and the associated discussions in the TSD, on the 
internal structure of the sales and scrappage modules, and whether and 
how to change the sales and scrappage analyses for the final rule.
a. Sales
    For the purposes of regulatory evaluation, the relevant sales 
metric is the difference between alternatives rather than the absolute 
number of sales in any of the alternatives. As such, the sales response 
model currently contains three parts: a nominal forecast that provides 
the level of sales in the baseline (based upon macroeconomic inputs, 
exclusively), a price elasticity that creates sales differences 
relative to that No-Action alternative in each year, and a fleet share 
model that produces differences in the passenger car and light truck 
market share in each alternative. For a more detailed description of 
these three parts, see Chapter 4.2 of the Draft TSD.
    The current baseline sales module reflects the idea that total new 
vehicle sales are primarily driven by conditions in the economy that 
are exogenous to the automobile industry. Over time, new vehicle sales 
have been cyclical--rising when prevailing economic conditions are 
positive (periods of growth) and falling during periods of economic 
contraction. While the kinds of changes to vehicle offerings that occur 
as a result of manufacturers' compliance actions exert some influence 
on the total volume of new vehicle sales, they are not determinative. 
Instead, they drive the kinds of marginal differences between 
regulatory alternatives that the current sales module is designed to 
simulate--more expensive vehicles, generally, reduce total sales but 
only marginally.
    The first component of the sales response model is the nominal 
forecast, which is a function with a small set of macroeconomic inputs 
that determines the size of the new vehicle market in each CY in the 
analysis for the baseline. It is of some relevance that this 
statistical model is intended only as a means to project a baseline 
sales series for LDVs. The nominal forecast model does not include 
prices and is not intended for statistical inference around the 
question of price response in the new vehicle market. NHTSA's 
projection oscillates by MY at the beginning of the analysis before 
settling on a constant trend in the 2030s. This result seems consistent 
with the continued response to the pandemic and to supply chain 
challenges. NHTSA's projections for most MYs fall between AEO 2021 and 
2022 forecasts, which were run as sensitivity cases. NHTSA will 
continue to monitor macroeconomic data and new vehicle sales and update 
its baseline forecast as appropriate.
    The baseline HDPUV fleet is modeled differently. NHTSA considered 
using a statistical model drawn from the LD specification to project 
new HDPUV sales but reasoned that the mix of HDPUV buyers and vehicles 
was sufficiently different that an alternative approach was required. 
Due to a lack of historical and future data on the changing customer 
base in the HDPUV market (e.g., the composition of commercial and 
personal users) and uncertainty around vehicle classification at the 
LDV and HDPUV margin, NHTSA chose to rely on an exogenous forecast path 
from the AEO to project sales. To align with the technology used to 
create the model fleet, NHTSA used compliance data from multiple MYs to 
estimate aggregate sales for MY 2022 and then applied year-over-year 
growth rates taken from the AEO forecast to project aggregate sales for 
subsequent MYs. Since the first year of the analysis, MY 2022, was 
constructed using compliance data spanning nearly a decade, the 
aggregate number of sales for the simulated fleet in MY 2022 was lower 
than the MY 2022 AEO forecast. To align with the AEO projections, the 
agency applied an upward adjustment to the HDPUV growth rate of 2 
percent for MYs 2023-2025, and 2.5 percent for MYs 2026-2028. Instead 
of adjusting the fleet size to match AEO's in MY2022, the agency 
elected to phase-in the increase in growth rates over a span of years 
to reflect that HDPUV production may continue to face supply 
constraints resulting from the COVID pandemic in the near future but 
should return to normal sometime later in the decade. NHTSA seeks 
comment on this approach, and whether it should implement an approach 
similar to how NHTSA models LDV sales.
    The second component of the sales response model captures how price 
changes affect the number of vehicles sold. NHTSA applies a price 
elasticity to the percentage change in average price (in each year). 
The price change does not represent an increase/decrease over the last 
observed year, but rather the percentage change relative to the 
baseline for that year. In the baseline, the average price is defined 
as the observed new vehicle price in 2022 (the last historical year 
before the simulation begins) plus the average regulatory cost 
associated with the No-Action Alternative for each MY.\406\ The central 
analysis in this proposal simulates multiple programs simultaneously 
(CAFE and HDPUV FE final standards, EPA final GHG standards, ZEV, and 
the California Framework Agreement), and the regulatory cost includes 
both technology costs and civil penalties paid for non-compliance (with 
CAFE standards) in a MY. We also subtract any IRA tax credits that a 
vehicle may qualify for from the regulatory costs.\407\ Because the 
elasticity assumes no perceived change in the quality of the product, 
and the vehicles produced under different regulatory scenarios have 
inherently different operating costs, the price metric must account for 
this difference. The price to which the elasticity is applied in this 
analysis represents the residual price change between scenarios after 
accounting for

[[Page 56241]]

2.5 years' worth of fuel savings to the new vehicle buyer.
---------------------------------------------------------------------------

    \406\ The CAFE Model currently operates as if all costs incurred 
by the manufacturer as a consequence of meeting regulatory 
requirements, whether those are the cost of additional technology 
applied to vehicles in order to improve fleetwide fuel economy or 
civil penalties paid when fleets fail to achieve their standard, are 
``passed through'' to buyers of new vehicles in the form of price 
increases.
    \407\ For additional details about how we model tax credits, see 
Section II.C.5b above.
---------------------------------------------------------------------------

    The price elasticity is also specified as an input, and for this 
analysis the agency assumes an elastic response of -0.4--meaning that a 
five percent increase in the average price of a new vehicle produces a 
two percent decrease in total sales. As explained in Chapter 4.2.1.2 of 
the Draft TSD, NHTSA selected this elasticity because of the totality 
of present evidence. NHTSA seeks comment on this assumption and has 
included several sensitivity cases testing alternative values.
    The third and final component of the sales model, which only 
applies to the LD fleet, is the dynamic fleet share module (DFS). Some 
commenters to previous rules noted that the market share of SUVs 
continues to grow, while conventional passenger car body-styles 
continue to lose market share. For instance, in the 2012 final rule, 
the agencies projected fleet shares based on the continuation of the 
baseline standards (MYs 2012-2016) and a fuel price forecast that was 
much higher than the realized prices since that time. As a result, that 
analysis assumed passenger car body-styles comprising about 70 percent 
of the new vehicle market by 2025. The reality, however, has been quite 
different; in 2021, passenger cars represented only 22% of new vehicle 
sales.\408\ Since the 2020 rule, NHTSA has incorporated a DFS into the 
CAFE Model in an attempt to address these market realities.
---------------------------------------------------------------------------

    \408\ See Bureau of Transportation Statistics. 2023. National 
Transportation Statics. Table 1-17. Avaliable at: https://www.bts.gov/content/new-and-used-passenger-car-sales-and-leases-thousands-vehicles. (Accessed May 31, 2023).
---------------------------------------------------------------------------

    For the 2020 and 2022 rulemakings, NHTSA used a DFS model crafted 
from two functions from the NEMS used for the 2017 AEO to independently 
estimate the share of passenger cars and light trucks, respectively, 
given average new market attributes (fuel economy, horsepower, and curb 
weight) for each group and current fuel prices, as well as the prior 
year's market share and prior year's attributes. The two independently 
estimated shares are then normalized to ensure that they sum to one. 
However, as the agency explained in the 2022 final rulemaking, that 
approach had several drawbacks including the model having 
counterintuitive signs, the exclusion a variable for price, and an 
overestimation of the fleet share of passenger automobile as currently 
observed.\409\
---------------------------------------------------------------------------

    \409\ 84 FR 25861 (May 2, 2022).
---------------------------------------------------------------------------

    For this proposal, NHTSA has revised its approach to modeling the 
DFS. The baseline fleet share projection is derived from the agency's 
own compliance data for the 2022 fleet, and the 2022 AEO projections 
for later MYs. To reconcile differences in the initial 2022 shares, 
NHTSA projected the fleet share forward using the annual changes from 
2022 predicted by AEO and applied these to the agency's own compliance 
fleet shares for MY 2022.\410\ The fleet is distributed across two 
different body-types: ``cars'' and ``light trucks.'' While there are 
specific definitions of ``passenger cars'' and ``light trucks'' that 
determine a vehicle's regulatory class, the distinction used in this 
phase of the analysis is more simplistic. All body-styles that are 
commonly considered a car--sedans, coupes, convertibles, hatchbacks, 
and station wagons--are defined as ``cars'' for the purpose of 
determining fleet share. Everything else--SUVs, smaller SUVs 
(crossovers), vans, and pickup trucks--are defined as ``light 
trucks''--even though they may not be treated as such for compliance 
purposes.
---------------------------------------------------------------------------

    \410\ For example if AEO PC share grows from 40 percent in one 
year to 50 percent in the next (25 percent growth), and our 
compliance PC share in that year is 44 percent then the predicted 
share in the next year would be 55 percent (11 points or 25 percent 
higher).
---------------------------------------------------------------------------

    These shares are applied to the total industry sales derived in the 
first stage of the sales response. This produces total industry volumes 
of car and light truck body styles. Individual model sales are then 
determined from there based on the following sequence: (1) individual 
manufacturer shares of each body style (either car or light truck) 
times the total industry sales of that body style, then (2) each 
vehicle within a manufacturer's volume of that body-style is given the 
same percentage of sales as appear in the 2022 fleet. This implicitly 
assumes that consumer preferences for particular styles of vehicles are 
determined in the aggregate (at the industry level), but that 
manufacturers' sales shares of those body styles are consistent with MY 
2022 sales. Within a given body style, a manufacturer's sales shares of 
individual models are also assumed to be constant over time. This 
approach implicitly assumes that manufacturers are currently pricing 
individual vehicle models within market segments in a way that 
maximizes their profit. Without more information about each OEM's true 
cost of production and operation, fixed and variables costs, and both 
desired and achievable profit margins on individual vehicle models, 
there is no basis to assume that strategic shifts within a 
manufacturer's portfolio will occur in response to standards.
    Similar to the second component of the sales module, the DFS then 
applies an elasticity to the change in price between alternatives and 
the No-Action Alternative to determine the change in fleet share. NHTSA 
uses the net regulatory cost differential (costs minus fuel savings) in 
a logistic model to capture the changes in fleet share between 
passenger cars and light trucks, with a price coefficient of -0.000042. 
NHTSA selected this methodology and price coefficient based on academic 
literature.\411\ When the total regulatory costs of passenger 
automobiles minus fuel savings exceeds that of light-trucks, the market 
share of light-trucks will rise relative to passenger automobiles. For 
example, a $100 net regulatory cost increase in passenger automobiles 
relative to light trucks would produce a ~.1% shift in market share 
towards light trucks assuming light trucks initially represented 60% of 
the fleet. NHTSA seeks comment on how it is modeling the DFS in this 
proposal, and more specifically seeks input to the elasticity NHTSA is 
using.
---------------------------------------------------------------------------

    \411\ The agency describes this literature review and the 
calibrated logit model in more detail in the accompanying docket 
memo ``Calibrated Estimates for Projecting Light-Duty Fleet Share in 
the CAFE Model''.
---------------------------------------------------------------------------

    The approach for this proposal to modeling changes in fleet share 
addresses several key concerns raised by NHTSA in its prior rulemaking. 
There are no longer any counterintuitive signs, and the model now 
directly considers the impacts of changes in price. While the model 
applies fuel savings in determining the relative changes in prices 
between passenger cars and light-trucks, the current approach does not 
explicitly consider the utility of fuel economy when determining the 
respective market share of passenger automobiles and light trucks. In 
prior rules, NHTSA has speculated that the rise in light-truck market 
share may be attributable to the increased utility that light-trucks 
provide their operators, and as the fuel economy between the different 
body-styles diminished, light-trucks have become an even more 
attractive option. As explained in a docket memo, NHTSA has been unable 
to create a comprehensive model that includes the variables in NEMS, 
price, and fuel economy that behaves appropriately. NHTSA is 
considering applying an elasticity to the changes in fuel economy 
directly to capture this change in utility. NHTSA seeks comment on 
whether this alternative approach is appropriate.

[[Page 56242]]

b. Scrappage
    New and used vehicles are substitutes. When the price of a good's 
substitute increases/decreases, the demand curve for that good shifts 
upwards/downwards and the equilibrium price and quantity supplied also 
increases/decreases. Thus, increasing the quality-adjusted price of new 
vehicles will result in an increase in equilibrium price and quantity 
of used vehicles. Since, by definition, used vehicles are not being 
``produced'' but rather ``supplied'' from the existing fleet, the 
increase in quantity must come via a reduction in their scrappage 
rates. Practically, when new vehicles become more expensive, demand for 
used vehicles increases (and they become more expensive). Because used 
vehicles are more valuable in such circumstances, they are scrapped at 
a lower rate, and just as rising new vehicle prices push marginal 
prospective buyers into the used vehicle market, rising used vehicle 
prices force marginal prospective buyers of used vehicles to acquire 
older vehicles or vehicles with fewer desired attributes. The effect of 
fuel economy standards on scrappage is partially dependent on how 
consumers value future fuel savings and our assumption that consumers 
value only the first 30 months of fuel savings when making a purchasing 
decision.
    Many competing factors influence the decision to scrap a vehicle, 
including the cost to maintain and operate it, the household's demand 
for VMT, the cost of alternative means of transportation, and the value 
that can be attained through reselling or scrapping the vehicle for 
parts. A car owner will decide to scrap a vehicle when the value of the 
vehicle minus the cost to maintain or repair the vehicle is less than 
the value as scrap metal. In other words, the owner gets more value 
from scrapping the vehicle than continuing to drive it, or from selling 
it. Typically, the owner that scraps the vehicle is not the original 
vehicle owner.
    While scrappage decisions are made at the household level, NHTSA is 
unaware of sufficient household data to sufficiently capture scrappage 
at that level. Instead, NHTSA uses aggregate data measures that capture 
broader market trends. Additionally, the aggregate results are 
consistent with the rest of the CAFE Model as the model does not 
attempt to model how manufacturers will price new vehicles; the model 
instead assumes that all regulatory costs to make a particular vehicle 
compliant are passed onto the purchaser who buys the vehicle.
    The most predictive element of vehicle scrappage is ``engineering 
scrappage.'' This source of scrappage is largely determined by the age 
of a vehicle and the durability of a specific MY vintage. NHTSA uses 
proprietary vehicle registration data from IHS/Polk to estimate vehicle 
age and durability. Other factors include fuel economy and new vehicle 
prices. For historical data on new vehicle transaction prices, NHTSA 
uses National Automobile Dealers Association (NADA) Data.\412\ The data 
consist of the average transaction price of all LDVs; since the 
transaction prices are not broken-down by body style, the model may 
miss unique trends within a particular vehicle body style. The 
transaction prices are the amount consumers paid for new vehicles and 
exclude any trade-in value credited towards the purchase. This may be 
particularly relevant for pickup trucks, which have experienced 
considerable changes in average price as luxury and high-end options 
entered the market over the past decade. Future models will further 
consider incorporating price series that consider the price trends for 
cars, SUVs and vans, and pickups separately. The other source of 
vehicle scrappage is from cyclical effects, which the model captures 
using forecasts of GDP and fuel prices.
---------------------------------------------------------------------------

    \412\ The data can be obtained from NADA. For reference, the 
data for MY 2020 may be found at https://www.nada.org/nadadata/.
---------------------------------------------------------------------------

    Vehicle scrappage follows a roughly logistic function with age--
that is, when a vintage is young, few vehicles in the cohort are 
scrapped, as they age, more and more of the cohort are retired and the 
instantaneous scrappage (the rate at which vehicles are scrapped) 
reaches a peak, and then scrappage declines as vehicles enter their 
later years as fewer and fewer of the cohort remains on the road. The 
analysis uses a logistic function to capture this trend of vehicle 
scrappage with age. The data show that the durability of successive MYs 
generally increases over time, or put another way, historically newer 
vehicles last longer than older vintages. However, this trend is not 
constant across all vehicle ages--the instantaneous scrappage rate of 
vehicles is generally lower for later vintages up to a certain age, but 
increases thereafter so that the final share of vehicles remaining 
converges to a similar share remaining for historically observed 
vintages.\413\ NHTSA uses fixed effects to capture potential changes in 
durability across MYs, and to ensure that vehicles approaching the end 
of their life are scrapped in the analysis, NHTSA applies a decay 
function to vehicles after they reach age 30. The macroeconomic 
conditions variables discussed above are included in the logistic model 
to capture cyclical effects. Finally, the change in new vehicle prices 
projected in the model (technology costs minus 30 months of fuel 
savings and any tax credits passed through to the consumer) are 
included, which generates differing scrappage rates across the 
alternatives.
---------------------------------------------------------------------------

    \413\ Examples of why durability may have changed are new 
automakers entering the market or general changes to manufacturing 
practices like switching some models from a car chassis to a truck 
chassis.
---------------------------------------------------------------------------

    For this proposal, NHTSA modeled the retirement of HDPUVs similarly 
to pick-up trucks. The amount of data for HDPUVs is significantly 
smaller than for the LD fleet and drawing meaningful conclusions from 
the small sample size is difficult. Furthermore, the two regulatory 
classes share similar vehicle characteristics and are likely used in 
similar fashions, hence NHTSA believes that the vehicles will follow a 
similar scrappage schedule. Commercial HDPUVs may endure harsher 
conditions during their useful life such as more miles in tough 
operating conditions, which may impact their retirement schedules. We 
believe that many light-trucks likely endure the same rigor and are 
represented in the light-truck segment of the analysis; however, NHTSA 
recognizes that the intensity or proportionality of heavy use in the 
HDPUV fleet may exceed that of light trucks and seeks comment from the 
public on how to capture that use in a statistically-significant 
fashion either within the existing framework or an alternative 
approach.
    In addition to the variables included in the scrappage model, NHTSA 
considered several other variables that likely either directly or 
indirectly influence scrappage in the real world, including maintenance 
and repair costs, the value of scrapped metal, vehicle characteristics, 
the quantity of new vehicles purchased, higher interest rates, and 
unemployment. These variables were excluded from the model either 
because of a lack of underlying data or modeling constraints. Their 
exclusion from the model is not intended to diminish their importance, 
but rather highlights the practical constraints of modeling intricate 
decisions like scrappage.
    For additional details on how NHTSA modeled scrappage, see Chapter 
4.2.2 of the Draft TSD. NHTSA seeks comments on its approach to 
modeling scrappage.

[[Page 56243]]

3. Changes in Vehicle Miles Traveled (VMT)
    In the CAFE Model, VMT is the product of average usage per vehicle 
in the fleet and fleet composition, which is itself a function of new 
vehicle sales and vehicle retirement decisions. These three 
components--average vehicle usage, new vehicle sales, and older vehicle 
scrappage--jointly determine total VMT projections for each 
alternative. VMT directly influences many of the various effects of 
fuel economy standards that decision-makers consider in determining 
what levels of standards to set. For example, the value of fuel savings 
is a function of a vehicle's efficiency, miles driven, and fuel price. 
Similarly, factors like criteria pollutant emissions, congestion, and 
fatalities are direct functions of VMT. For a more detailed description 
of how NHTSA models VMT, see Chapter 4.3 of the Draft TSD.
    It is NHTSA's perspective that the total demand for VMT should not 
vary excessively across alternatives. The basic travel needs for an 
average household are unlikely to be influenced heavily by the 
stringency of the standards, as the daily need for a vehicle will 
remain the same. That said, it is reasonable to assume that fleets with 
differing age distributions and inherent cost of operation will have 
slightly different annual VMT (even without considering VMT associated 
with rebound miles). Based on the structure of the CAFE Model, the 
combined effect of the sales and scrappage responses could create small 
percentage differences in total VMT across the range of regulatory 
alternatives if steps are not taken to constrain VMT. Because VMT is 
related to many of the costs and benefits of the program, even small 
magnitude differences in VMT across alternatives can have meaningful 
impacts on the incremental net benefits. Furthermore, since decisions 
about alternative stringencies look at the incremental costs and 
benefits across alternatives, it is more important that the analysis 
capture the variation of VMT across alternatives than to accurately 
project total VMT within a scenario. NHTSA seeks comment on whether 
non-rebound VMT should be constrained across the LD fleet, or if it 
would be more appropriate to model VMT changing with fleet size.
    To ensure that travel demand remains consistent across the 
different regulatory scenarios for the LD fleet, the CAFE Model begins 
with a model of aggregate VMT developed by Federal Highway 
Administration (FHWA) that is used to produce their annual VMT 
forecasts. These estimates provide the aggregate VMT of all MYs and 
body styles for any given CY and are the same across regulatory 
alternatives for each year in the analysis. NHTSA seeks comment on 
whether it should continue to constrain aggregate, non-rebound VMT 
across alternatives. NHTSA is considering removing the constraint on 
VMT. While as noted above, this will produce some differences in non-
rebound VMT across the alternatives, we believe that the differences 
will be minor and will reflect households either reducing or dropping 
out of the personal vehicle market as they seek to reduce travel costs 
through alternative modes of transportation.
    Since vehicles of different ages and body styles carry different 
costs and benefits, to account properly for the average value of 
consumer and societal costs and benefits associated with vehicle usage 
under various alternatives, it is necessary to partition miles by age 
and body type. NHTSA created ``mileage accumulation schedules'' using 
IHS-Polk odometer data to construct mileage accumulation schedules as 
an initial estimate of how much a vehicle expected to drive at each age 
throughout its life.\414\ NHTSA uses simulated new vehicle sales, 
annual rates of retirement for used vehicles, and the mileage 
accumulation schedules to distribute VMT across the age distribution of 
registered vehicles in each CY to preserve the non-rebound VMT 
constraint.
---------------------------------------------------------------------------

    \414\ The mileage accumulations schedules are constructed with 
content supplied by IHS Markit; Copyright (copyright) R.L. Polk & 
Co., 2018. All rights reserved.
---------------------------------------------------------------------------

    FHWA does not produce an annual VMT forecast for HDPUVs. Without an 
annual forecast, NHTSA is unable to constrain VMT for HDPUVs similar to 
the LD fleet. Instead, VMT is built exclusively through the vehicle 
accumulation schedules. For the aforementioned reasons, we believe that 
the change in VMT that results from changes in fleet composition and 
size are reasonable. NHTSA seeks comment on this assumption, and 
alternatively asks commenters to identify an independent forecast of 
HDPUV VMT that may be used as a constraint.
    The fuel economy rebound effect--a specific example of the well-
documented energy efficiency rebound effect for energy-consuming 
capital goods--refers to the tendency of motor vehicles' use (as 
measured by VMT) to increase when their fuel economy is improved and, 
as a result, the cost per mile (CPM) of driving declines. Establishing 
more stringent standards than the baseline level will lead to 
comparatively higher fuel economy for new cars and light trucks, and 
increase fuel efficiency for HDPUVs, thus decreasing the amount of fuel 
consumed and increasing the amount of travel in which new vehicle 
owners engage. NHTSA recognizes that the value selected for the rebound 
effect influences overall costs and benefits associated with the 
regulatory alternatives under consideration as well as the estimates of 
lives saved under various regulatory alternatives, and that the rebound 
estimate, along with fuel prices, technology costs, and other 
analytical inputs, is part of the body of information that agency 
decision-makers have considered in determining the appropriate levels 
of the standards in this proposal. We also note that the rebound effect 
diminishes the economic and environmental benefits associated with 
increased fuel efficiency.
    NHTSA conducted a review of the literature related to the fuel 
economy rebound effect, which is extensive and covers multiple decades 
and geographic regions. The totality of evidence, without categorically 
excluding studies on grounds that fail to meet certain criteria, and 
evaluating individual studies based on their particular strengths, 
suggests that a plausible range for the rebound effect is 10-50 
percent. This range implies that, for example, a 10 percent reduction 
in vehicles' fuel CPM would lead to an increase of 1-5 percent in the 
number of miles they are driven annually. The central tendency of this 
range appears to be at or slightly above its midpoint, which is 30 
percent. Considering only those studies that NHTSA believes are derived 
from extremely robust and reliable data, employ identification 
strategies that are likely to prove effective at isolating the rebound 
effect, and apply rigorous estimation methods, suggests a range of 
approximately 10-45 percent, with most of the estimates falling in the 
15-30 percent range.
    That said, a case can also be made to support values of the rebound 
effect in the 5-15 percent range. Both economic theory and empirical 
evidence suggest that the rebound effect has been declining over time 
due to factors such as increasing income (which raises the value of 
travelers' time), progressive smaller reductions in fuel costs in 
response to continuing increases in fuel economy, and slower growth in 
car ownership and the number of license holders. Lower estimates of the 
rebound effect estimates are associated with recently published studies 
that rely on U.S. data, measure vehicle use using

[[Page 56244]]

actual odometer readings, control for the potential endogeneity of fuel 
economy, and estimate the response of vehicle use to variation in fuel 
economy itself rather than to fuel cost per distance driven or fuel 
prices. Accordingly, greater weight to these studies suggests that the 
rebound effect is more likely to be in the 5-15 percent range.
    NHTSA selected a rebound effect of 10% for its analysis of both LD 
and HDPUV fleets because it was well-supported by the totality of the 
evidence. It is rarely possible to identify whether estimates of the 
rebound effect in academic literature apply specifically to household 
vehicles, LDVs, or another category, and different nations classify 
trucks included in NHTSA's HDPUV category in varying ways, so NHTSA has 
assumed the same value for LDVs and HDPUVs.
    We also examine the sensitivity of estimated impacts to values of 
the rebound ranging from 5 percent to 15 percent to account for the 
uncertainty surrounding the rebound value. NHTSA seeks comment on the 
above discussion, and whether to consider a different value for the 
rebound effect for the final rule analysis for either the LD or HDPUV 
analyses.
    In order to calculate total VMT with rebound, the CAFE Model 
applies the price elasticity of VMT (taken from the FHWA forecasting 
model) to the full change in CPM and the initial VMT schedule but 
applies the (user defined) rebound parameter to the incremental 
percentage change in CPM between the non-rebound and full CPM 
calculations to the miles applied to each vehicle during the 
reallocation step that ensured adjusted non-rebound VMT matched the 
non-rebound VMT constraint.
    The approach in the model is a combination of top-down (relying on 
the FHWA forecasting model to determine total LD VMT in a given CY), 
and bottom-up (where the composition and utilization of the on-road 
fleet determines a base level of VMT in a CY, which is constrained to 
match the FHWA model). While a joint household consumer choice model--
if one could be developed adequately and reliably to capture the myriad 
circumstances under which families and individuals make decisions 
relating to vehicle purchase, use, and disposal--would reflect 
decisions that are made at the household level, it is not obvious, or 
necessarily appropriate, to model the national program at that scale in 
order to produce meaningful results that can be used to inform policy 
decisions.
    The most useful information for policymakers relates to national 
impacts of potential policy choices. No other element of the rulemaking 
analysis occurs at the household level, and the error associated with 
allocating specific vehicles to specific households over the course of 
three decades would easily dwarf any error associated with the 
estimation of these effects in aggregate. We have attempted to 
incorporate estimates of changes to the new and used vehicle markets at 
the highest practical levels of aggregation and worked to ensure that 
these effects produce fleetwide VMT estimates that are consistent with 
the best, current projections given our economic assumptions. While 
future work will always continue to explore approaches to improve the 
realism of CAFE and HDPUV FE policy simulations, there are important 
differences between small-scale econometric studies and the kind of 
flexibility that is required to assess the impacts of a broad range of 
regulatory alternatives over multiple decades. To assist with creating 
even more precise estimates of VMT, NHTSA requests comment on 
alternative approaches to simulate VMT demand. See Chapter 4.3 of the 
Draft TSD for a complete accounting of how NHTSA models VMT.
4. Changes to Fuel Consumption
    NHTSA uses the fuel economy and age and body-style VMT estimates to 
determine changes in fuel consumption. NHTSA divides the expected 
vehicle use by the anticipated mpg to calculate the gallons consumed by 
each simulated vehicle, and when aggregated, the total fuel consumed in 
each alternative.

F. Simulating Emissions Impacts of Regulatory Alternatives

    This proposal includes various fuel-saving technologies, which 
produce additional co-benefits. These co-benefits include reduced 
vehicle emissions during operation as well as reduced upstream 
emissions during petroleum extraction, transportation and refining, and 
finally fuel transportation, storage, and distribution. This section 
has a detailed discussion, particularly for the main standard-setting 
inputs and assumptions, on the development and evolution of input 
parameters for criteria pollutants, GHGs, and air toxics emissions and 
the resulting potential human health effects.
    The rule implements an emissions inventory methodology for 
estimating emissions impacts. Vehicle emissions inventories are often 
described as three-legged stools, comprised of vehicle activity (i.e., 
miles traveled, hours operated, or gallons of fuel burned), population 
(or number of vehicles), and EFs. An emissions factor is a 
representative rate that attempts to relate the quantity of a pollutant 
released to the atmosphere per unit of activity. For this rulemaking, 
like past rules, activity levels (both miles traveled and fuel 
consumption) are generated by the CAFE Model while the EFs have been 
incorporated from other Federal models.
    The following section briefly discusses the methodology the CAFE 
Model uses to track vehicle activity and populations, and how we 
generate the emissions factors that relate that vehicle activity to 
criteria pollutant, GHG, and air toxics emissions impacts. This section 
also details how we estimate these emissions could adversely affect 
human health, especially from criteria pollutants known to cause poor 
air quality. Further description of how the health impacts of criteria 
pollutant emissions can vary and how these emission damages have been 
monetized and incorporated into the rule can be found in Chapter 6.2.2 
of the Draft TSD and the Draft EIS accompanying this analysis.
    For transportation applications, upstream emissions are generated 
between the point of energy feedstock extraction to the vehicle's fuel 
tank or energy storage system; in lifecycle analysis this is often 
referred to as well-to-tank emissions. Downstream emissions are 
primarily comprised of what is emitted through the vehicle's exhaust 
but would also include other emissions generated during vehicle use and 
inactivity (called `soaking'), including hydrofluorocarbons leaked from 
AC systems. This would encompass, for example, particulate matter (PM) 
from brake and tire wear (BTW) as well as volatile organic compounds 
(VOCs) from evaporative emissions during refueling and as the vehicle's 
engine remains off and the fuel onboard permeates from its tank. 
Downstream emissions are commonly known as tank-to-wheel emissions and 
cumulative fuel cycle emissions are called well-to-wheel emissions in 
lifecycle analysis.
    The CAFE Model tracks vehicle populations and activity levels to 
produce estimates of the effects of different levels of CAFE standards. 
Tracking vehicle populations begins with the baseline fleet or analysis 
fleet, and estimates of each vehicle's fuel type (e.g., gasoline, 
diesel, electricity), fuel economy, and number of units sold in the 
U.S. As fuel-economy-improving technology is added to vehicles in the 
baseline fleet in each subsequent MY, the CAFE Model estimates annual 
rates at which new vehicles are purchased,

[[Page 56245]]

driven,\415\ and subsequently scrapped. The model uses estimates of 
vehicles remaining in service in each year and the amount those 
vehicles are driven (i.e., activity levels) to calculate the quantities 
of each type of fuel or energy, including gasoline, diesel, and 
electricity, that vehicles in the fleet consume in each year. The 
quantities of travel and fuel consumption estimated for the cross 
section of MYs and CYs constitutes a set of ``activity levels'' based 
on which the model calculates emissions. The model does so by 
multiplying activity levels by EFs.
---------------------------------------------------------------------------

    \415\ The procedures the CAFE Model uses to estimate annual VMT 
for individual car and light truck models produced during each model 
year over their lifetimes and to combine these into estimates of 
annual fleet-wide travel during each future CY, together with the 
sources of its estimates of their survival rates and average use at 
each age, are described in detail in Draft TSD Chapters 4.2 and 4.3. 
The data and procedures the CAFE Model employs to convert these 
estimates of VMT to fuel and energy consumption by individual model, 
and to aggregate the results to calculate total consumption and 
energy content of each fuel type during future CYs, are also 
described in detail in that same section.
---------------------------------------------------------------------------

    EFs measure the mass of each greenhouse or criteria pollutant 
emitted per vehicle-mile of travel, gallon of fuel consumed, or unit of 
fuel energy content. We generate EFs for the following regulated 
criteria pollutants and GHGs: carbon monoxide (CO), VOCs, nitrogen 
oxides (NOX), sulfur oxides (SOX), particulate 
matter with 2.5-micron ([mu]m) diameters or less (PM2.5); 
CO2, methane (CH4), and nitrous oxide 
(N2O).\416\ In this rulemaking, upstream EFs are on a fuel 
volume basis and downstream EFs are on a distance basis. Simply stated, 
the rulemaking's upstream emission inventory is the product of the per-
gallon EF and the corresponding number of gallons of gasoline or 
diesel, or amount of electricity, the vehicle consumes. Similarly, the 
downstream emission inventory is the product of the per-mile EF and the 
appropriate miles traveled estimate. The only exceptions are that 
tailpipe SOX and CO2 also use a per-gallon EF in 
the CAFE Model. EVs do not produce combustion-related emissions,\417\ 
however, EV upstream electricity emissions are also accounted for in 
the CAFE Model inputs. Upstream and downstream EFs and subsequent 
inventories were developed independently from separate data sources, as 
discussed further below.
---------------------------------------------------------------------------

    \416\ There is also HFC leakage from air conditioner systems, 
but these emissions are not captured in our analysis.
    \417\ BEVs do not produce any combustion-based emissions while 
PHEVs only produce combustion-based emissions during use of 
conventional fuels. Utilization factors typically define how much 
real-world operation occurs while using electricity versus 
conventional fuels.
---------------------------------------------------------------------------

    We estimated upstream EFs using the GREET 2022 Model,\418\ which is 
a lifecycle emissions model developed by the U.S. DOE's ANL. Like past 
CAFE analyses, we used GREET 2022 to calculate emissions factors for 
the following four upstream emission processes for gasoline, E85, and 
diesel: (1) petroleum extraction, (2) petroleum transportation, (3) 
petroleum refining, and (4) fuel transportation, storage, and 
distribution (TS&D), for the years 2022 through 2050 in five-year 
intervals. We consider conventional crude oil, oil sands, and shale 
oils in the gasoline and diesel EF calculations and follow assumptions 
consistent with the GREET Model for ethanol blending. Based on our 
assumption that any reduction in fuel consumption within the United 
States leads to an equal sized increase in gasoline exports, we 
currently do not project changes in upstream emissions resulting from 
feedstock extraction and fuel production outside the U.S. We realize 
that reduced domestic fuel consumption may to lead to some reduction in 
global fuel supply over the longer term even if U.S. fuel production 
remains unaffected in the near term (as we argue is likely to be the 
case), and we are considering if and how to incorporate this effect in 
our Final Rule. Doing so would involve projecting the long run effects 
of changes to domestic fuel economy and fuel efficiency standards on 
global demand, prices, and output of refined transportation fuels and 
feedstocks used to produce them. We seek comment on the most suitable 
methods for conducting this analysis, and on our underlying analysis 
and assumptions about the likely effects of changes in domestic 
gasoline consumption on U.S. gasoline imports and exports as well as 
the global supply and demand.
---------------------------------------------------------------------------

    \418\ U.S. DOE, Energy Systems and Infrastructure Analysis.2022. 
Greenhouse gases, Regulated Emissions, and Energy use in 
Transportation (GREET) Model. Last Revised: Oct. 11, 2022. Available 
at: https://greet.es.anl.gov/. (Accessed: May 31, 2023).
---------------------------------------------------------------------------

    We also used GREET 2022 to estimate upstream electricity EFs. GREET 
2022 projects a national default mix for electricity generation (often 
simply called the grid mix) for transportation from the latest AEO data 
available, in this case from 2022. The CAFE Model utilizes a single 
upstream electricity EF for transportation use and does not 
differentiate by process, based on GREET EFs for electricity as a 
transportation fuel. A detailed description of how we used GREET 2022 
to generate upstream EFs is located in Chapter 5 of the Draft TSD.
    We understand that AEO 2023 became available after NHTSA completed 
its analysis for this proposal, and that AEO 2023 projects a higher 
grid mix for renewable-based electricity generation, which would reduce 
upstream emissions associated with additional electricity generation as 
a potential result of more stringent CAFE standards. We intend to 
employ updated estimates of power sector emissions in our final rule, 
which could be based on the latest-available versions of AEO and GREET, 
and we seek comment on making these updates. Other grid mixes with 
higher penetrations of renewables are presented as sensitivity cases in 
the PRIA and do provide some context about what our analysis would look 
like using a grid mix with a higher penetration of renewables. We seek 
comment on these sensitivity cases and which national grid mix forecast 
may best represent the latest market conditions and policies, such as 
the Inflation Reduction Act. We also seek comments on other forecasts 
to consider, including EPA's Integrated Planning Model for the post-IRA 
2022 reference case for the final rulemaking,\419\ and the methodology 
used to generate alternate forecasts.
---------------------------------------------------------------------------

    \419\ See documentation of US EPA, Post-IRA 2022 Reference Case, 
https://www.epa.gov/power-sector-modeling/post-ira-2022-reference-case.
---------------------------------------------------------------------------

    We estimated non-CO2 downstream EFs for gasoline, E85, 
diesel, and CNG \420\ using the MOtor Vehicle Emission Simulator 
(MOVES3) model,\421\ which is a regulatory highway emissions inventory 
model developed by the EPA's National Vehicle and Fuel Emissions 
Laboratory. We generated downstream CO2 EFs based on the 
carbon content (i.e., the fraction of each fuel type's mass that is 
carbon) and mass density per unit of the specific type of fuel. The 
CAFE Model calculates CO2 vehicle-based emissions associated 
with vehicle operation of the surviving on-road fleet by multiplying 
the number of gallons of a specific fuel consumed by the CO2 
emissions factor for the associated fuel type. More specifically, the 
number of gallons of a particular fuel is multiplied by the carbon 
content

[[Page 56246]]

and the mass density per unit of that fuel type, and then the ratio of 
CO2 emissions generated per unit of carbon consumed during 
the combustion process is applied.\422\ Draft TSD Chapter 5.3 goes into 
detail about how we generated the downstream emissions factors used in 
this analysis.
---------------------------------------------------------------------------

    \420\ BEVs and FCEVs do not generate any combustion-related 
emissions.
    \421\ To ensure that the MOVES default database aligned with the 
most current CAFE standards, we removed assumptions associated with 
the Safer Affordable Fuel-Efficient (SAFE) Vehicles Rule from 2020 
that was withdrawn, and replaced those assumptions with changes from 
the MY 2024-2026 Rule finalized in 2022. We modified parameters 
related to future fleet increases in stringency and rebound effects 
of vehicle miles traveled.
    \422\ Chapter 3, Section 4 of the CAFE Model Documentation 
provides additional description for calculation of CO2 
downstream emissions with the model.
---------------------------------------------------------------------------

    With stringent LDV standards already in place for PM from vehicle 
exhaust, particles from brake and tire wear (BTW) are becoming an 
increasingly important component of PM emission inventories. To put the 
impact of future BTW PM emissions in perspective, for a gasoline-fueled 
passenger car's PM2.5 emissions (from vehicle exhaust, brake 
wear, and tire wear),\423\ BTW will constitute a slight majority of 
PM2.5 emissions in 2020 and after. Similarly, for light 
trucks, BTW will become a majority of PM2.5 in 2035. In 
particular, brake wear from cars and light trucks will account for up 
to 40 percent of their PM2.5 inventories by 2050. Previous 
CAFE rulemakings have not modeled the indirect impacts to BTW emissions 
due to changes in fuel economy and VMT. This rulemaking considers 
PM2.5 from the vehicle's exhaust, brakes, and tires.
---------------------------------------------------------------------------

    \423\ PM2.5 is particulate matter of diameters less 
than 2.5 microns.
---------------------------------------------------------------------------

    As with downstream emissions factors, we generated BTW EFs using 
EPA's MOVES3 model.\424\ Due to limited BTW measurements, MOVES does 
not vary BTW factors by vehicle MY, fuel type, or powertrain. Instead, 
MOVES brake wear is dependent on vehicle weight-based regulatory 
classes and operating behavior derived primarily from vehicle speed and 
acceleration. On the other hand, tire wear is dependent on the weight-
based MOVES regulatory classes and operations strictly based on vehicle 
speed. Unlike the CAFE Model's downstream EFs, the BTW estimates were 
averaged over all vehicle MYs and ages for a single grams-per-mile 
value by regulatory class.
---------------------------------------------------------------------------

    \424\ US EPA, Office of Transportation and Air Quality. 2020. 
Brake and Tire Wear Emissions from Onroad Vehicles in MOVES3. 
Assessment and Standards Division. pp. 1-48. Available at: https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P1010M43.pdf. (Accessed May 31, 
2023).
---------------------------------------------------------------------------

    There is some evidence that average vehicle weight will differ by 
fuel type and powertrain, particularly EVs with extended-range battery 
packs, which are often heavier than a comparable gasoline- or diesel-
powered vehicle.\425\ These weight increases due to electrification are 
likely to result in additional tire wear. However, regenerative braking 
often extends their useful life and reduces associated brake wear,\426\ 
but the additional mass from heavier batteries might increase BTW 
emissions overall.427 428 Further BTW field studies are 
needed to better understand how differences in vehicle fuel and 
powertrain type are likely to impact PM2.5 emissions from 
BTW. For the time being, the CAFE Model's BTW inputs are differentiated 
by fuel type but have equivalent values across gasoline, diesel, and 
electricity. Given the degree to which PM2.5 inventories are 
expected to shift from vehicle exhaust to BTW in the near future, we 
assert that it is better to have some BTW estimates--even if 
imperfect--than not to include them at all, as was the case in prior 
CAFE rulemakings. We seek comment on this updated approach and 
additional data sources that could be used to update the BTW estimates.
---------------------------------------------------------------------------

    \425\ Cooley, B. 2022. America's New Weight Problem: Electric 
Vehicles. CNET. Published: Jan. 28, 2022. Available at: https://www.cnet.com/roadshow/news/americas-new-weight-problem-electric-cars. (Accessed: May 31, 2023).
    \426\ Bondorf, L. et al. 2023. Airborne Brake Wear Emissions 
from a Battery Electric Vehicle. Atmosphere 14(3): pp. 488. 
Available at: https://doi.org/10.3390/atmos14030488. (Accessed: May 
31, 2023).
    \427\ US EPA, Office of Transportation and Air Quality. 2022 
Brake Wear Particle Emission Rates and Characterization. Available 
at: https://nepis.epa.gov/Exe/ZyPURL.cgi?Dockey=P1013TSX.txt. 
(Accessed: May 31, 2023).
    \428\ McTurk, E. 2022. Do Electric Vehicles Produce More Tyre 
and Brake Pollution Than Their Petrol and Diesel Equivalents?. RAC. 
Available at: https://www.rac.co.uk/drive/electric-cars/running/do-electric-vehicles-produce-more-tyre-and-brake-pollution-than-petrol-and/. (Accessed: May 31, 2023).
---------------------------------------------------------------------------

    The CAFE Model computes select health impacts resulting from three 
criteria pollutants: NOX, SOX, and 
PM2.5. Out of the six criteria pollutants currently 
regulated, NOX, SOX, and PM2.5 are 
known to be emitted regularly from mobile sources and have the most 
adverse effects to human health. These health impacts include several 
different morbidity measures, as well as a mortality estimate, and are 
measured by the number of instances predicted to occur per ton of 
emitted pollutant. The CAFE Model reports total health impacts by 
multiplying the estimated tons of each criteria pollutant--generated 
using the process described above--by the corresponding health 
incidence per ton value. Broadly speaking, a health incidence per ton 
value is the morbidity and mortality estimates linked to an additional 
ton of an emitted pollutant; these can also be referred to as benefit 
per ton values where there are monetized reduced health incidences 
related to a reduced ton of emissions (discussed further in Section 
II.G).
    The health incidence per ton values in this analysis reflect the 
differences in health impacts arising from the five upstream emission 
source sectors that we use to generate upstream emissions (petroleum 
extraction, petroleum transportation, refineries, fuel transportation, 
storage and distribution, and electricity generation). We carefully 
examined how each upstream source sector is defined in GREET 2022 (the 
model we use to generate upstream EFs, as described above) to 
appropriately map the emissions estimates to data on health incidences 
from criteria pollutant emissions. As the health incidences for the 
different source sectors are all based on the emission of one ton of 
the same pollutants, NOX, SOX, and 
PM2.5, the differences in the incidence per ton values arise 
from differences in the geographic distribution of the pollutants, a 
factor which affects the number of people impacted by the 
pollutants.\429\
---------------------------------------------------------------------------

    \429\ EPA. 2018. Estimating the Benefit per Ton of Reducing 
PM2.5 Precursors from 17 Sectors. Office of Air and 
Radiation and Office of Air Quality Planning and Standards. Research 
Triangle Park, NC. pp. 1-108. Available at: https://www.epa.gov/sites/production/files/2018-02/documents/sourceapportionmentbpttsd_2018.pdf. (Accessed: May 31, 2023).
---------------------------------------------------------------------------

    Like past CAFE analyses, we relied on publicly available reports 
from EPA to estimate health incidence per ton values for each upstream 
source. We used several EPA reports to generate the upstream health 
incidence per ton values, as different EPA reports provided more up-to-
date estimates for different sectors based on newer air quality 
modeling. These EPA reports use a reduced-form benefit-per-ton (BPT) 
approach to inform the assessment of health impacts. In this approach, 
the PM2.5-related BPT values are the total monetized human 
health benefits (the sum of the economic value of the reduced risk of 
premature death and illness) that are expected from reducing one ton of 
directly-emitted PM2.5 or PM2.5 precursor such as 
NOX or Sulfur Dioxide (SO2). We note, however, 
that the complex, non-linear photochemical processes that govern ozone 
formation prevent us from developing reduced-form ozone, ambient 
NOX, or other air toxic BPT values. This is an important 
limitation to recognize when using the BPT approach. We include 
additional discussion of uncertainties in the BPT approach in Chapter 
5.4.3 of the Draft TSD. That said, we believe that the BPT approach 
provides a reasonable estimate

[[Page 56247]]

of how different CAFE stringencies may impact public health. The BPT 
methodology and data sources are unchanged from the 2022 CAFE rule, and 
stakeholders generally agreed that estimates of the benefits of 
PM2.5 reductions were improved from prior analyses based on 
our emissions-related health impacts methodology updated for that 
rule.\430\
---------------------------------------------------------------------------

    \430\ CBD et al., Docket No. NHTSA-2021-0053-1572, at 5.
---------------------------------------------------------------------------

    The reports we relied on for health incidences and BPT estimates 
include EPA's 2018 technical support document, Estimating the Benefit 
per Ton of Reducing PM2.5 Precursors from 17 Sectors 
(referred to here as the 2018 EPA source apportionment TSD),\431\ a 
2018 oil and natural gas sector paper written by EPA staff (Fann et 
al.), which estimates health impacts for this sector in the year 
2025,\432\ and a 2019 paper from EPA (Wolfe et al.) that computes 
monetized per ton damage costs for mobile sources in several 
categories, based on vehicle type and fuel type.\433\ Some CAFE Model 
upstream emissions components do not correspond to any one EPA source 
sector in available literature, so we used a weighted average of 
different source sectors to generate those values. Data we used from 
each paper for each upstream source sector are discussed in detail in 
Chapter 5.4 of the Draft TSD.
---------------------------------------------------------------------------

    \431\ EPA. 2018. Estimating the Benefit per Ton of Reducing 
PM2.5 Precursors from 17 Sectors. Office of Air and 
Radiation and Office of Air Quality Planning and Standards. Research 
Triangle Park, NC. pp. 1-108. Available at: https://19january2017snapshot.epa.gov/benmap/estimating-benefit-ton-reducing-pm25-precursors-17-sectors_.html. (Accessed: May 31, 2023).
    \432\ Fann, N. et al. 2018. Assessing Human Health 
PM2.5 and Ozone Impacts from U.S. Oil and Natural Gas 
Sector Emissions in 2025. Environmental Science & Technology, 
52(15): pp. 8095-8103. (hereinafter Fann et al.).
    \433\ Wolfe, P. et al. 2019.). Monetized Health Benefits 
Attributable To Mobile Source Emission Reductions Across The United 
States In 2025. The Science of the Total Environment, 650(Pt 2). pp. 
2490-2498. (hereinafter Wolfe et al.). Health incidence per ton 
values corresponding to this paper were sent by EPA staff.
---------------------------------------------------------------------------

    The CAFE Model follows a similar process for computing health 
impacts resulting from downstream emissions as it does for calculating 
health impacts from upstream emissions. We used the Wolfe et al. paper 
to compute monetized damage costs per ton values for several on-road 
mobile sources categories based on vehicle type and fuel type. Wolfe et 
al. did not report incidences per ton, but that information was 
obtained through communications with EPA staff. Additional information 
about how we generated downstream health estimates is discussed in 
Chapter 5.4 of the Draft TSD.
    We are aware that EPA recently updated its estimated benefits for 
reducing PM2.5 from several sources,\434\ but those sources 
do not include mobile sources. After discussion with EPA staff, we 
retained the PM2.5 incidence per ton values from the last 
CAFE analysis for consistency with the current mobile source emissions 
estimates. If any additional information becomes available before the 
final rule analysis, we will consult with EPA staff and may update 
values where applicable.
---------------------------------------------------------------------------

    \434\ U.S. EPA. 2023. Estimating the Benefit per Ton of Reducing 
Directly-Emitted PM2.5, PM2.5 Precursors and 
Ozone Precursors from 21 Sectors. Last updated: Jan. 2023. Available 
at: https://www.epa.gov/benmap/estimating-benefit-ton-reducing-directly-emitted-pm25-pm25-precursors-and-ozone-precursors. 
(Accessed: May 31, 2023).
---------------------------------------------------------------------------

G. Simulating Economic Impacts of Regulatory Alternatives

    The following sections describe NHTSA's approach for measuring the 
economic costs and benefits that would result from establishing 
alternative standards for future MYs. The measures that NHTSA uses are 
important considerations, because as OMB Circular A-4 states, benefits 
and costs reported in regulatory analyses must be defined and measured 
consistently with economic theory and should also reflect how 
alternative regulations are anticipated to change the behavior of 
producers and consumers from a baseline scenario. For CAFE and fuel 
efficiency standards, those include vehicle manufacturers, buyers of 
new vehicles, owners of used vehicles, and suppliers of fuel, all of 
whose behavior is likely to respond in complex ways to the level of 
standards that DOT establishes for future MYs.
    It is also important to report the benefits and costs of this 
proposed action in a format that conveys useful information about how 
those impacts are generated, while also distinguishing the economic 
consequences for private businesses and households from the action's 
effects on the remainder of the U.S. economy. A reporting format will 
accomplish this objective to the extent that it clarifies who incurs 
the benefits and costs of the proposed action, while also showing how 
the economy-wide or ``social'' benefits and costs of the proposed 
action are composed of direct effects on vehicle producers, buyers, and 
users, plus the indirect or ``external'' benefits and costs it creates 
for the general public.
    Table II-19 lists the economic benefits and costs analyzed in 
conjunction with this proposal, and where to find explanations for what 
we measure, why we include it, how we estimate it, and the estimated 
value for that specific line item. The table also shows how the 
different elements of the analysis piece together to inform NHTSA's 
estimates of private and external costs and benefits.\435\
---------------------------------------------------------------------------

    \435\ Changes in tax revenues are a transfer and not an economic 
externality as traditionally defined, but we group these with 
external costs instead of private costs since that loss in revenue 
affects society as a whole as opposed to impacting only consumers or 
manufacturers.

             Table II-19--Benefits and Costs Resulting From NHTSA's Proposed Regulatory Action \436\
----------------------------------------------------------------------------------------------------------------
                                      Section of       Chapter of  draft
              Entry                    preamble          TSD modeling       Chapter of PRIA     Chapter of PRIA
                                      discussion          explanation         discussion            results
----------------------------------------------------------------------------------------------------------------
                                                  Private Costs
----------------------------------------------------------------------------------------------------------------
Technology Costs to Increase      II.G.1.a(1).......  Chapter 6.1.......  Chapter 7.1.1.....  Chapters 8.2.3.1
 Fuel Economy.                                                                                 and 8.3.3.1.
Increased Maintenance and Repair  II.G.3............  ..................  Chapter 7.1.1
 Costs.
Sacrifice in Other Vehicle        II.G.3............  ..................  Chapters 7.1.1 and  Chapters 9.2.3.9
 Attributes.                                                               9.2.3.10.           and 9.2.3.10.
Consumer Surplus Loss from        II.G.1.a(2).......  Chapter 6.1.2.....  Chapter 7.1.4.....  Chapters 8.2.2.3,
 Reduced New Vehicle Sales.                                                                    8.2.3.2, 8.3.2.3
                                                                                               and 8.3.3.2.
Safety Costs Internalized by      II.H.3............  Chapter 7.4.......  Chapters 7.1.5,     Chapters 8.2.4.5
 Drivers.                                                                  8.5.5.              and 8.3.4.5.
Subtotal--Internal Costs........  ..................  ..................  ..................  Sum of above
                                                                                               entries.
----------------------------------------------------------------------------------------------------------------

[[Page 56248]]

 
                                          External and Government Costs
----------------------------------------------------------------------------------------------------------------
Congestion and Noise Costs from   II.G.2.a(1).......  Chapter 6.2.3.....  Chapter 7.2.2.....  Chapters 8.2.4.3
 Rebound-Effect Driving.                                                                       and 8.3.4.3.
Safety Costs Not Internalized by  II.H.1 and II.H.2.  Chapter 7.........  Chapters 7.1.5,     Chapters 8.2.4.5
 Drivers.                                                                  8.5.5.              and 8.3.4.5.
Loss in Fuel Tax Revenue........  II.G.2.a(2).......  Chapters 6.1.3,     Chapter 7.3.1.....  Chapters 8.2.4.6
                                                       6.2.                                    and 8.3.4.6.
Subtotal--External Costs........  ..................  ..................  ..................  Sum of above
                                                                                               entries.
Social Costs....................  ..................  ..................  ..................  Sum of private and
                                                                                               external costs.
----------------------------------------------------------------------------------------------------------------
                                                Private Benefits
----------------------------------------------------------------------------------------------------------------
Savings in Retail Fuel Costs      II.G.1.b(1).......  Chapter 6.1.3.....  Chapter 7.3.1.....  Chapters 8.2.2.2,
 \437\.                                                                                        8.2.2.3, and
                                                                                               8.3.2.2, 8.3.2.3.
Benefits from Additional Driving  II.G.1.b(3).......  Chapter 6.1.5.....  Chapter 7.2.1.....  Chapters 8.2.3.2
                                                                                               and 8.3.3.2.
Less Frequent Refueling.........  II.G.1.b(2).......  Chapter 6.1.4.....  Chapter 8.4.2.....  Chapters 8.2.2.3
                                                                                               and 8.3.2.3.
Subtotal--Private Benefits......  ..................  ..................  ..................  Sum of above
                                                                                               entries.
----------------------------------------------------------------------------------------------------------------
                                        External and Government Benefits
----------------------------------------------------------------------------------------------------------------
Reduction in Petroleum Market     II.G.2.b(3).......  Chapter 6.2.4.....  Chapter 7.3.2.....  Chapters 8.2.4.4
 Externality.                                                                                  and 8.3.4.4.
Climate Benefits................  II.G.2.b(1).......  Chapter 6.2.1.....  Chapters 8.5.1....  Chapters 8.2.4.1
                                                                                               and 8.3.4.1.
Health Benefits.................  II.G.2.b(2).......  Chapter 6.2.2.....  Chapters 8.5.2....  Chapters 8.2.4.2
                                                                                               and 8.3.4.1.
Subtotal--External Benefits.....  ..................  ..................  ..................  Sum of above
                                                                                               entries.
Social Benefits.................  ..................  ..................  ..................  Sum of private and
                                                                                               external
                                                                                               benefits.
----------------------------------------------------------------------------------------------------------------
Net Private Benefits............  ..................  ..................  ..................  Private Benefits--
                                                                                               Private Costs.
Net External Benefits...........  ..................  ..................  ..................  External Costs--
                                                                                               External
                                                                                               Benefits.
Net Social Benefits.............  ..................  ..................  ..................  Social Benefits--
                                                                                               Social Costs.
----------------------------------------------------------------------------------------------------------------

    NHTSA reports the costs and benefits of proposed standards for LDVs 
and HDPUVs separately. While the effects are largely the same for the 
two fleets our fuel economy and fuel efficiency programs are separate, 
and NHTSA makes independent determinations of the maximum feasible 
standards for each fleet.
---------------------------------------------------------------------------

    \436\ This table presents the societal costs and benefits. Costs 
and benefits that affect only the consumer analysis, such as sales 
taxes, insurance costs, and reallocated VMT, are purposely ommited 
from this table. See Chapters 8.2.3 and 8.3.3 of the PRIA for 
consumer-specific costs and benefits.
    \437\ Since taxes are transfers from consumers to governments, a 
portion of the Savings in Retail Fuel Costs includes taxes avoided. 
The Loss in Fuel Tax Revenue is completely offset within the Savings 
in Retail Fuel Costs.
---------------------------------------------------------------------------

    A standard function of regulatory analysis is to evaluate tradeoffs 
between impacts that occur at different points in time. Many Federal 
regulations involve costly upfront investments that generate future 
benefits in the form of reductions in health, safety, or environmental 
damages. To evaluate these tradeoffs, the analysis must account for the 
social rate of time preference--the broadly observed social preference 
for benefits that occur sooner versus those that occur further in the 
future. This is accomplished by discounting impacts that occur further 
in the future more than impacts that occur sooner.
    OMB Circular A-4 affirms the appropriateness of accounting for the 
social rate of time preference in regulatory analyses and recommends 
DRs of 3 and 7 percent for doing so. The recommended 3 percent DR was 
chosen to represent the ``consumption rate of interest'' approach, 
which discounts future costs and benefits to their present values using 
the rate at which consumers appear to make tradeoffs between current 
consumption and equal consumption opportunities when deferred to the 
future. OMB Circular A-4 reports an inflation-adjusted or ``real'' rate 
of return on 10-year Treasury notes of 3.1 percent between 1973 and its 
2003 publication date and interprets this as approximating the rate at 
which society is indifferent between consumption today and in the 
future. The 7 percent rate reflects the opportunity cost of capital 
approach to discounting, where the DR approximates the forgone return 
on private investment if the regulation were to divert resources from 
capital formation. Fuel savings and most other benefits from tightening 
standards will be experienced directly by owners of vehicles that offer 
higher fuel economy and thus affect their future consumption 
opportunities, while benefits or costs that are experienced more widely 
throughout the economy will also primarily affect future consumption. 
Circular A-4 indicates that discounting at the consumption rate of 
interest is the ``analytically preferred method'' when effects are 
presented in consumption-equivalent units. Thus, applying OMB's 
guidance to NHTSA's proposed rule suggests the 3 percent rate is the 
appropriate rate. However, NHTSA reports both the 3 and 7 percent rates 
for transparency and completeness On April 6, 2023, OMB issued a 
request for comment on proposed updates to Circular A-4.\438\ OMB 
specifically sought comment on whether to change its guidance on 
DRs.\439\ DOT will consider modifying the DRs used in this analysis if 
OMB issues a revision to Circular A-4 ahead of the final rule.
---------------------------------------------------------------------------

    \438\ 88 FR 20915 (April 7, 2023).
    \439\ See Preamble: Proposed OMB Circular No. A-4. Regulatory 
Analysis. Page 17. Avaliable at: https://www.whitehouse.gov/wp-content/uploads/2023/04/DraftCircularA-4Preamble.pdf. (Accessed May 
31, 2023).
---------------------------------------------------------------------------

    For a complete discussion of the methodology employed and the 
results, see Chapter 6 of the Draft TSD and Chapter 8 of the PRIA, 
respectively. The safety implications of the proposal--including the 
monetary impacts--are

[[Page 56249]]

reserved for Section II.H. NHTSA seeks comment on the following 
discussion.
1. Private Costs and Benefits
a. Costs to Consumers
(1) Technology Costs
    The technology applied to meet the proposed standards would 
increase the cost to produce new cars, light trucks and HDPUVs. Within 
this analysis, manufacturers are assumed to transfer these costs to the 
consumers who purchase vehicles offering higher fuel economy. While 
NHTSA recognizes that some manufacturers may defray their regulatory 
costs for meeting increased CAFE and fuel efficiency standards through 
more complex pricing strategies or by accepting lower profits, NHTSA 
lacks sufficient insight into manufacturers' pricing strategies to 
confidently model alternative approaches. Thus, we simply assume that 
manufacturers raise the prices of models whose fuel economy they elect 
to improve sufficiently to recover their increased costs for doing so. 
The technology costs are incurred by manufacturers and then passed onto 
consumers. While we include the effects of IRA tax credits in our 
modeling of consumer responses to the standards, the effect of the tax 
credit is an economic transfer where the costs to one party are exactly 
offset by benefits to another and have no impact on the net benefits of 
the proposal. NHTSA could include IRA tax credits as a reduction in the 
technology costs for manufacturers and purchasing prices in our cost-
benefit accounting, tax credits are a transfer from the government to 
private parties, and as such have no net effect on the benefits or 
costs of the proposed rule. As such, the line item included in the 
tables summarizing the cost of technology throughout this proposal 
should be considered pre-tax unless otherwise noted.
    See Section III.C.6 of this preamble and Chapter 2.5 of the Draft 
TSD for more details.
(2) Consumer Sales Surplus
    Consumers who forgo purchasing a new vehicle because of the 
increase in the price of new vehicles' prices caused by more stringent 
standards will experience a decrease in welfare. The collective welfare 
loss to these ``potential'' new vehicle buyers is measured by their 
foregone consumer surplus.
    Consumer surplus is a fundamental economic concept and represents 
the net value (or net benefit) a good or service provides to consumers. 
It is measured as the difference between what a consumer is willing to 
pay for a good or service and its market price. OMB Circular A-4 
explicitly identifies consumer surplus as a benefit that should be 
accounted for in cost-benefit analysis. For instance, OMB Circular A-4 
states the ``net reduction in total surplus (consumer plus producer) is 
a real cost to society,'' and elsewhere recommends that consumer 
surplus values be monetized ``when they are significant.''
    Accounting for the limited portion of lifetime fuel savings that 
the average new vehicle buyer values, and holding all else equal, 
higher average prices should depress new vehicle sales and by extension 
reduce consumer surplus. The inclusion of the effects on the proposal 
on consumer surplus is not only consistent with OMB guidance, but with 
other parts of this regulatory analysis. For instance, we calculate the 
increase in consumer surplus associated with increased driving that 
results from the lower CPM of driving under more stringent regulatory 
alternatives, as discussed in Section II.G.1.b(3). The surpluses 
associated with sales and additional mobility are inextricably linked, 
as they capture the direct costs and benefits to purchasers of new 
vehicles. The sales surplus captures the welfare loss to consumers when 
they forego purchasing new vehicles because of higher prices, while the 
consumer surplus associated with additional driving measures the 
benefit of the increased mobility it provides.
    NHTSA estimates the loss of sales surplus based on the change in 
quantity of vehicles projected to be sold, after adjusting for quality 
improvements attributable to higher fuel economy or fuel efficiency. 
For additional information about consumer sales surplus, see Chapter 
6.1.2 of the Draft TSD. NHTSA seeks comment on our methodology for the 
consumer sales surplus.
(3) Ancillary Costs of Higher Vehicle Prices
    Some costs of purchasing and owning a new or used vehicle increase 
in proportion to its purchase price or market value. At the time of 
purchase, the price of the vehicle combined with the state-specific tax 
rate determine the sales tax paid. Throughout the lifetime of the 
vehicle, the residual value of the vehicle--which is determined by its 
initial purchase price, age, and accumulated usage--determine value-
related registration fees and insurance premiums. The analysis assumes 
that the transaction price is a fixed share of the MSRP, which allows 
calculation of these factors as shares of MSRP. As the standards 
influence the price of vehicles, these ancillary costs will also 
increase. For a detailed explanation of how NHTSA estimates these 
costs, see Chapter 6.1.1 of the Draft TSD.
    These costs are included in the consumer per-vehicle cost-benefit 
analysis but not in the societal cost-benefit analysis, because they 
are assumed to be transfers from consumers to government agencies or to 
reflect actuarially ``fair'' insurance premiums. We seek comment on 
this approach and our methodology for calculating these costs.
    In previous proposals and final rules, NHTSA also included the 
costs of financing vehicle purchases as an ancillary cost to consumers. 
However, as we noted in the 2022 final rule, the availability of 
vehicle financing offers a benefit to consumers by spreading out the 
costs of additional fuel economy technology over time. Thus, we no 
longer include financing as a cost to consumers. We seek comment on 
this assumption.
b. Benefits to Consumers
(1) Fuel Savings
    The primary benefit to consumers of increasing standards is the 
savings in future fuel costs that accrue to buyers and subsequent 
owners of new vehicles. The value of fuel savings is calculated by 
multiplying avoided fuel consumption by retail fuel prices. Each 
vehicle of a given body style is assumed to be driven the same amount 
in each year of its lifetime as all those of comparable age and body 
style. The ratio of that cohort's annual VMT to its fuel efficiency 
produces an estimate of its yearly fuel consumption. The difference 
between fuel consumption in the No-Action Alternative, and in each 
regulatory alternative, represents the gallons (or energy content) of 
fuel saved.
    Under this assumption, our estimates of fuel consumption from 
increasing the fuel economy or fuel efficiency of each individual model 
depend only on how much its fuel economy or efficiency is increased, 
and do not reflect whether its actual use differs from other models of 
the same body type. Neither do our estimates of fuel consumption 
account for variation in how much vehicles of the same body type and 
age are driven each year, which appears to be significant (see Chapter 
4.3.1.2 of the Draft TSD). Consumers save money on fuel expenditures at 
the average retail fuel price (fuel price assumptions are discussed in 
detail in Chapter 4.1.2 of the Draft TSD), which includes all taxes and 
represents an average across octane blends. For gasoline and diesel, 
the

[[Page 56250]]

included taxes reflect both the Federal tax and a calculated average 
state fuel tax. Expenditures on alternative fuels (E85 and electricity, 
primarily) are also included in the calculation of fuel expenditures, 
on which fuel savings are based. However, since alternative fuel 
technology is not applied to meet the proposed standards, the majority 
of the costs associated with operating alternative fuels net to zero. 
And while the included taxes net out of the social benefit cost 
analysis (as they are a transfer), consumers value each gallon saved at 
retail fuel prices including any additional fees or taxes they pay.
    Chapter 6.1.3 of the Draft TSD provides additional details. In the 
TSD, NHTSA considers the possibility that several of the assumptions 
made about vehicle use could lead to misstating the benefits of fuel 
savings. NHTSA notes that these assumptions are necessary to model fuel 
savings and likely have minimal impact to the accuracy of the analysis 
for this proposal.
(2) Refueling Benefit
    Increasing standards affects the amount of time drivers spend 
refueling their vehicles in several ways. First, higher standards 
increase the fuel efficiency of ICE vehicles produced in the future, 
which may increase their driving range and decrease the number of 
refueling events. Conversely, to the extent that more stringent 
standards increase the purchase price of new vehicles, they may reduce 
sales of new vehicles and scrappage of existing ones, causing more VMT 
to be driven by older and less efficient vehicles that require more 
refueling events for the same amount of driving. Finally, as the number 
of EVs in the fleet increases, some of the time spent previously 
refueling ICE vehicles at the pump will be replaced with recharging EVs 
at public charging stations. While the analysis does not allow 
electrification to be chosen as a compliance pathway with the proposed 
standards for LDVs, it is still important to model recharging since 
excluding these costs would underestimate scenarios with additional 
BEVs, such as our sensitivity cases that examine lower battery costs.
    NHTSA estimates these savings by calculating the amount of 
refueling time avoided--including the time it takes to locate a retail 
outlet, refuel one's vehicle, and pay--and multiplying it by DOT's 
estimated value of travel time. For a full description of the 
methodology, refer to Chapter 6.1.4 of the Draft TSD.
    We seek comment on this methodology. In particular, we seek comment 
on whether increasing fuel economy for LDVs and fuel efficiency for 
HDPUVs should be expected to reduce the amount of refueling benefits. 
An alternative hypothesis NHTSA is considering is whether manufacturers 
maintain vehicle range by lowering tank size as vehicle efficiency 
improves without, therefore, reducing refueling time.
(3) Additional Mobility
    Any increase in travel demand provides benefits that reflect the 
value to drivers and passengers of the added--or more desirable--social 
and economic opportunities that additional travel makes available. 
Under each of the alternatives considered in this analysis, the fuel 
CPM of driving would decrease as a consequence of higher fuel economy 
and efficiency levels, thus increasing the number of miles that buyers 
of new cars, light trucks, and HDPUVs would drive as a consequence of 
the well-documented fuel economy rebound effect.
    In theory, the decision by drivers and their passengers to make 
more frequent or longer trips when the cost of driving declines 
demonstrates that the benefits that they gain by doing so must exceed 
the costs they incur. At a minimum, one would expect the benefits of 
additional travel to equal the cost of the fuel consumed to travel 
additional miles (or they would not have occurred). Because the cost of 
that additional fuel is reflected in the simulated fuel expenditures, 
it is also necessary to account for the benefits associated with those 
extra miles traveled. But those benefits arguably should also offset 
the economic value of their (and their passengers') travel time, other 
vehicle operating costs, and the economic cost of safety risks due to 
the increase in exposure to crash risks that occurs with additional 
travel. The amount by which the benefit of this additional travel 
exceeds its economic costs measures the net benefits drivers and their 
passengers experience, usually referred to as increased consumer 
surplus.
    Chapter 6.1.5 of the Draft TSD explains NHTSA's methodology for 
calculating benefits from additional mobility. The benefit of 
additional mobility over and above its costs is measured by the change 
in consumers' surplus, which NHTSA approximates as one-half of the 
change in fuel CPM times the increase in VMT due to the rebound effect. 
NHTSA seeks comment on both the assumption and methodology employed to 
capture the value of additional mobility.
    When the size of the vehicle stock decreases in the LD alternative 
cases, VMT and fuel cost per-vehicle increase. Because maintaining 
constant non-rebound VMT assumes consumers are willing to pay the full 
cost of the reallocated vehicle miles, we offset the increase in fuel 
cost per-vehicle in the LD analysis by adding the product of the 
reallocated VMT and fuel CPM to the mobility value in the per-vehicle 
consumer analysis. Because we do not estimate other changes in cost 
per-vehicle that could result from the reallocated miles (e.g., 
maintenance, depreciation, etc.) we do not estimate the portion of the 
transferred mobility benefits that would correspond to consumers' 
willingness to pay for those costs. We do not estimate the consumers' 
surplus associated with the reallocated miles because there is no 
change in total non-rebound VMT and thus no change in consumers' 
surplus per consumer. Chapter 6.1.5 of the Draft TSD explains NHTSA's 
methodology for calculating the benefits of reallocated miles. We seek 
comment on this assumption and methodology.
2. External Costs and Benefits
a. Costs
(1) Congestion and Noise
    Increased vehicle use associated with the rebound effect also 
contributes to increased traffic congestion and highway noise. Although 
drivers obviously experience these impacts, they do not fully value 
their effects on other travelers or bystanders, just as they do not 
fully value the emissions impacts of their own driving. Congestion and 
noise costs are thus ``external'' to the vehicle owners whose decisions 
about how much, where, and when to drive more in response to changes in 
fuel economy result in these costs. Thus, unlike changes in the costs 
incurred by drivers for fuel consumption or safety risks they willingly 
assume, changes in congestion and noise costs are not offset by 
corresponding changes in the travel benefits drivers experience.
    Congestion costs are limited to road users; however, since road 
users include a significant fraction of the U.S. population, changes in 
congestion costs are treated as part of the proposal's external 
economic impact on society as a whole instead of as a cost to private 
parties. Costs resulting from road and highway noise are even more 
widely dispersed because they are borne partly by surrounding 
residents, pedestrians, and other non-road users, and for this reason 
are also considered as costs that drivers impose on society as a whole.
    To estimate the economic costs associated with changes in 
congestion and noise caused by increases in

[[Page 56251]]

driving, NHTSA updated the estimates of per-mile congestion and noise 
costs from increased automobile and light truck use reported in FHWA's 
1997 Highway Cost Allocation Study to account for changes in travel 
activity and economic conditions since they were originally developed, 
as well as to express them in 2021 dollars for consistency with other 
economic inputs. NHTSA employed a similar approach for the 2022 final 
rule. Because HDPUVs and light-trucks share similar operating 
characteristics, we also apply the noise and congestion cost estimates 
for light-trucks to HDPUVs.
    See Chapter 6.2 of the Draft TSD for details on how NHTSA 
calculated estimates of the economic costs associated with changes in 
congestion and noise caused by differences in miles driven. NHTSA 
specifically seeks comment on the congestion costs employed in this 
analysis, and whether and how to change them for the analysis for the 
final rule.
(2) Fuel Tax Revenue
    As mentioned in Section II.G.1.b(1), a portion of the fuel savings 
experienced by consumers includes avoided fuel taxes. While fuel taxes 
are a transfer and do not affect net benefits, NHTSA reports an 
estimate of changes in fuel tax revenues together with external costs 
to show the potential impact on state and local government finances.
b. Benefits
(1) Climate Benefits
    The combustion of petroleum-based fuels to power cars, light 
trucks, and HDPUVs generates emissions of various GHGs, which 
contribute to changes in the global climate and resulting economic 
damages. Extracting and transporting crude petroleum, refining it to 
produce transportation fuels, and distributing fuel all generate 
additional emissions of GHGs and criteria air pollutants beyond those 
from vehicle usage. By reducing the volume of petroleum-based fuel 
produced and consumed, adopting standards will thus mitigate global 
climate-related economic damages caused by accumulation of GHGs in the 
atmosphere, as well as the more immediate and localized health damages 
caused by exposure to criteria pollutants. Because they fall broadly on 
the U.S. population, and on the global population as a whole in the 
case of climate damages, population, reducing GHG emissions and 
criteria pollutants represents an external benefit from requiring 
higher fuel economy.
(a) Valuation of the Social Cost of Greenhouse Gases
    NHTSA estimates the climate benefits of CO2, 
CH4, and N2O emission reductions expected from 
this proposed rule using the SC-GHG estimates presented in the 
Technical Support Document: SC of Carbon (SCC), Methane, and Nitrous 
Oxide Interim Estimates under E.O. 13990 (``February 2021 TSD''). These 
estimates are interim values developed under E.O. 13990 for use in 
benefit-cost analyses until updated estimates of the impacts of climate 
change can be developed. NHTSA uses the SC-GHG interim values to 
estimate the climate benefits of decreased fuel consumption stemming 
from this proposal.
    The SC-GHG estimates used in our analysis were developed over many 
years, using a transparent process, peer-reviewed methodologies, the 
best science available at the time, and with input from the public. 
Specifically, in 2009, an IWG that included the DOT and other executive 
branch agencies and offices was established to ensure that agencies 
were using the best available science and to promote consistency in the 
SC-CO2 values used across agencies. The IWG published its 
initial SC-CO2 estimates in 2010. These estimates were 
updated in 2013 using new versions of the various models initially used 
to derive them. In August 2016, the IWG published estimates of the SC 
of methane (SC-CH4) and nitrous oxide (SC-N2O) 
using methodologies that are consistent with the methodology underlying 
the SC-CO2 estimates.
    E.O. 13990 (issued on January 20, 2021) re-established the IWG and 
directed it to publish interim SC-GHG values for CO2, 
CH4, and N2O within thirty days. Furthermore, the 
E.O. tasked the IWG with devising long-term recommendations to update 
the methodologies used in calculating these SC-GHG values, based on 
``the best available economics and science,'' and incorporating 
principles of ``climate risk, environmental justice (EJ), and 
intergenerational equity''. The E.O. also instructed the IWG to take 
into account recommendations from the NAS committee convened on this 
topic, which were published in 2017. The February 2021 TSD provides a 
complete discussion of the IWG's initial review conducted under E.O. 
13990.
    NHTSA is using the IWG's interim values, published in the February 
2021 TSD, for the analysis accompanying this NPRM. This approach is the 
same as that taken in DOT regulatory analyses extending from 2009 
through 2022. If updated estimates of the social cost of greenhouse gas 
emissions are available before the final rule, NHTSA will consider 
revising the estimates within the CAFE Model, time permitting. We 
request comment on this approach to estimating social benefits of 
reducing GHG emissions in this rulemaking in light of the ongoing 
interagency process. For additional details, see Chapter 6.2.1.1 of the 
Draft TSD.
    The United States cannot address the domestic consequences of 
climate change by itself; instead, we need other nations to take action 
to reduce their own domestic emissions and to consider the benefits 
that doing so will have for the United States. In order to ensure that 
other nations take action to reduce their GHG emissions, the United 
States is actively involved in developing and implementing 
international commitments to secure those reductions. Concrete actions 
to reduce domestic emissions such as increasing fuel efficiency and 
fuel economy standards may help the United States secure reductions 
from other nations. As such, NHTSA agrees with the global focus of the 
IWG's interim guidance.
    Furthermore, the IWG found that domestic SC-GHG estimates fail to 
reflect the full impact of GHG emissions to the United States in 
multiple ways. The IWG concluded that those estimates fail to capture 
many climate impacts that can affect the welfare of U.S. citizens and 
residents. Examples of affected interests include direct effects on 
U.S. citizens and assets located abroad, international trade, and 
tourism, and spillover pathways such as economic and political 
destabilization and global migration that can lead to adverse impacts 
on U.S. national security, public health, and humanitarian concerns. 
Those impacts are better captured within global measures of the social 
cost of greenhouse gases.
    NHTSA is mindful that our understanding of the SC-GHG is still 
evolving. In addition to participating in the IWG process, DOT 
continues to track developments in the economic and environmental 
sciences literature regarding the SC of GHG emissions, including 
research from Federal sources like the EPA.\440\ NHTSA seeks comment on 
whether an alternative approach should be considered for the final 
rule.
---------------------------------------------------------------------------

    \440\ For more information on EPA's proposed estimates and 
process, including the final external peer review report on EPA's 
draft methodology, see EPA. 2022. EPA External Review Draft of 
Report on the Social Cost of Greenhouse Gases: Estimates 
Incorporating Recent Scientific Advances. Avaliable at https://www.epa.gov/environmental-economics/scghg. (Accessed: May 31, 2023).

---------------------------------------------------------------------------

[[Page 56252]]

(b) Discount Rates for Climate Related Benefits
    As mentioned earlier, NHTSA discounts costs and benefits at both 
the 3% consumption rate of interest and the 7% opportunity cost of 
capital, in accordance with OMB Circular A-4. The IWG rejected the use 
of the opportunity cost of capital approach to discounting reductions 
in climate-related damages (currently set at 7%), concluding that the 
``consumption rate of interest is the correct discounting concept to 
use when future damages from elevated temperatures are estimated in 
consumption-equivalent units as is done in the Integrated Assessment 
Models used to estimate the SC-GHG (NAS 2017).'' In fact, Circular A-4 
indicates that discounting at the consumption rate of interest is the 
``analytically preferred method'' when effects are presented in 
consumption-equivalent units. DOT concurs that in light of Circular A-
4's guidance on discount rates spanning displacement of investments 
and/or consumption, and considering that climate damages are modeled in 
consumption equivalent units and heightened concerns over 
intergenerational equity, the use of consumption-based discount rates 
is superior for estimating SC-GHG.
    As the IWG states, ``GHG emissions are stock pollutants, where 
damages are associated with what has accumulated in the atmosphere over 
time, and they are long lived such that subsequent damages resulting 
from emissions today occur over many decades or centuries depending on 
the specific [GHG] under consideration.'' OMB Circular A-4 states that 
impacts occurring over such intergenerational time horizons require 
special treatment:

    Special ethical considerations arise when comparing benefits and 
costs across generations. Although most people demonstrate time 
preference in their own consumption behavior, it may not be 
appropriate for society to demonstrate a similar preference when 
deciding between the well-being of current and future generations. 
Future citizens who are affected by such choices cannot take part in 
making them, and today's society must act with some consideration of 
their interest.

    Furthermore, NHTSA notes that in 2015, OMB--along with the rest of 
the IWG--articulated that ``Circular A-4 is a living document, which 
may be updated as appropriate to reflect new developments and 
unforeseen issues,'' and that ``the use of 7 percent is not considered 
appropriate for intergenerational discounting. There is wide support 
for this view in the academic literature, and it is recognized in 
Circular A-4 itself.'' Following this statement from OMB, and 
recognizing the need to balance welfare improvements to current and 
future generations, it would be inappropriate to apply an opportunity 
cost of capital rate to estimate SC-GHG.
    In addition to the ethical considerations, Circular A-4 also 
identifies uncertainty in long-run interest rates as another reason why 
it is appropriate to use lower rates to discount intergenerational 
impacts, since recognizing such uncertainty causes the appropriate 
discount rate to decline gradually over progressively longer time 
horizons. Circular A-4 also acknowledges the difficulty in estimating 
appropriate discount rates for ``intergenerational'' time horizons, 
noting that ``[p]rivate market rates provide a reliable reference for 
determining how society values time within a generation, but for 
extremely long time periods no comparable private rates exist.'' The 
social costs of distant future climate damages--and by implication, the 
value of reducing them by lowering emissions of GHGs--are highly 
sensitive to the discount rate, and the present value of reducing 
future climate damages grows at an increasing rate as the discount rate 
used in the analysis declines.
    This ``non-linearity'' means that even if uncertainty about the 
exact value of the long-run interest rate is equally distributed 
between values above and below the 3 percent consumption rate of 
interest, the probability-weighted (or ``expected'') present value of a 
unit reduction in climate damages will be higher than the value 
calculated using a 3 percent discount rate. The effect of such 
uncertainty about the correct discount rate can be accounted for by 
using a lower ``certainty-equivalent'' rate to discount distant future 
damages, defined as the rate that produces the same expected present 
value of a reduction in future damages implied by the distribution of 
possible discount rates around what is believed to be the most likely 
single value.
    The IWG identifies ``a plausible range of certainty-equivalent 
constant consumption discount rates: 2.5, 3, and 5 percent per year,'' 
each intended to reflect the effect of uncertainty surrounding 
alternative estimates of the correct discount rate. The IWG TSD does 
not address the question of how agencies should combine its estimates 
of benefits from reducing GHG emissions that reflect these alternative 
discount rates with the discount rates for nearer-term benefits and 
costs prescribed in OMB Circular A-4.
    NHTSA has not selected a primary discount rate for the SC of GHGs. 
This approach was selected because the IWG does not specify which of 
the discount rates it recommends should be considered the agency's 
primary estimate. The agency's analysis showing our primary non-GHG 
impacts at 3 and 7 percent alongside climate-related benefits 
discounted at each rate recommended by the IWG may be found in Chapter 
8 of the PRIA for both LDVs and HDPUVs. For the sake of simplicity, 
most tables throughout this analysis pair both the 3 percent and the 7 
percent discount rates for other costs and benefits with the SCs of 
GHGs discounted at a 3 percent rate. We believe that this approach 
provides policymakers with a range of costs and benefits associated 
with the rule using a reasonable range of discounting approaches and 
associated climate benefits, while also reporting that the 95th 
percentile value illustrates the potential for climate change to cause 
damages that are much higher than the ``best guess'' damage estimates.
    For additional details, see Chapter 6.2.1.2 of the Draft TSD. We 
seek comment on our choice to consider a broad range of discount rates 
for SC-GHGs, and we will consider modifying our approach to discounting 
SC-GHGs based on such comments and any updated guidance.
(2) Reduced Health Damages
    The CAFE Model estimates monetized health effects associated with 
emissions from three criteria pollutants: NOX, 
SOX, and PM2.5. As discussed in Section II.F 
above, although other criteria pollutants are currently regulated, only 
impacts from these three pollutants are calculated since they are known 
to be emitted regularly from mobile sources, have the most adverse 
effects on human health, and have been the subject of extensive 
research by EPA to estimate the benefits of reducing these pollutants. 
Other pollutants, especially those that are precursors to ozone, are 
more difficult to model due to the complexity of their formation in the 
atmosphere, and EPA does not calculate BPT estimates for these. The 
CAFE Model computes the monetized health damages from each of the three 
pollutants by multiplying the monetized health impact per ton by the 
total tons of each pollutant emitted, including from both upstream and 
downstream sources. Reductions in these costs from their level under 
the baseline alternative that are projected to result from adopting 
alternative standards are treated as external benefits of those 
alternatives. Chapter 5 of the Draft TSD accompanying this proposal 
includes a detailed description of the EFs that

[[Page 56253]]

inform the CAFE Model's calculation of the total tons of each pollutant 
associated with upstream and downstream emissions.
    These monetized health impacts per ton values are closely related 
to the health incidence per ton values described above in Section II.F 
and in detail in Chapter 5.4 of the Draft TSD. We use the same EPA 
sources that provided health incidence values to determine which 
monetized health impacts per ton values to use as inputs in the CAFE 
Model. Like the estimates associated with health incidences per ton of 
criteria pollutant emissions, we used multiple EPA papers and 
conversations with EPA staff to appropriately account for monetized 
damages for each pollutant associated with the source sectors included 
in the CAFE Model and based our final estimates on the most up-to-date 
data. The various emission source sectors included in the EPA papers do 
not always correspond exactly to the emission source categories used in 
the CAFE Model. In those cases, we mapped multiple EPA sectors to a 
single source category and computed a weighted average of the health 
impact per ton values.
    The EPA uses the value of a statistical life (VSL) to estimate 
premature mortality impacts, and a combination of willingness to pay 
estimates and costs of treating the health impact for estimating the 
morbidity impacts. EPA's 2018 technical support document, ``Estimating 
the Benefit per Ton of Reducing PM2.5 Precursors from 17 
Sectors,'' (referred to here as the 2018 EPA source apportionment TSD) 
contains a more detailed account of how health incidences are 
monetized. It is important to note that the EPA sources cited 
frequently refer to these monetized health impacts per ton as 
``benefits per ton,'' since they describe these estimates in terms of 
emissions avoided. In the CAFE Model input structure, these are 
generally referred to as monetized health impacts or damage costs 
associated with pollutants emitted (rather than avoided), unless the 
context states otherwise.
    The CAFE Model health impacts inputs are based partially on the 
structure of the 2018 EPA source apportionment TSD, which reported 
benefits per ton values for the years 2020, 2025, and 2030. For the 
years in between the source years used in the input structure, the CAFE 
Model applies values from the closest source year. For example, the 
model applies 2020 monetized health impact per ton values for calendar 
years 2020-2022 and applies 2025 values for calendar years 2023-2027. 
In order for some of the monetized health damage values to match the 
structure of other impacts costs, DOT staff developed proxies for 7% 
discounted values for specific source sectors by using the ratio 
between a comparable sector's 3% and 7% discounted values. In addition, 
we used implicit price deflators from the Bureau of Economic Analysis 
(BEA) to convert different monetized estimates to 2021 dollars, in 
order to be consistent with the rest of the CAFE Model inputs.
    This process is described in more detail in Chapter 6.2.2 of the 
Draft TSD accompanying this proposal. In addition, the CAFE Model 
documentation contains more details of the model's computation of 
monetized health impacts. We seek comment on this approach. All 
resulting emissions damage costs for criteria pollutants are located in 
the Criteria Emissions Cost worksheet of the Parameters file.
(3) Reduction in Petroleum Market Externalities
    The proposed standards would decrease domestic consumption of 
gasoline, producing a corresponding decrease in the Nation's demand for 
crude petroleum, a commodity that is traded actively in a worldwide 
market. Because the U.S. accounts for a significant (albeit 
diminishing) share of global oil consumption, the resulting decrease in 
global petroleum demand will exert some downward pressure on worldwide 
prices.
    U.S. consumption and imports of petroleum products have three 
potential effects on the domestic economy that are often referred to 
collectively as ``energy security externalities,'' and increases in 
their magnitude are sometimes cited as possible SCs of increased U.S. 
demand for petroleum. Symmetrically, reducing U.S. petroleum 
consumption and imports can reduce these costs, and by doing so provide 
additional external benefits from establishing higher CAFE and fuel 
efficiency standards.
    First, any increase in global petroleum prices that results from 
higher U.S. gasoline demand will cause a transfer of revenue to oil 
producers worldwide from consumers of petroleum, because consumers 
throughout the world are ultimately subject to the higher global price 
that results. Under competitive market assumptions, this transfer is 
simply a shift of resources that produces no change in global economic 
output or welfare. Since the financial drain it produces on the U.S. 
economy may not be considered by individual consumers of petroleum 
products, it is sometimes cited as an external cost of increased U.S. 
petroleum consumption.
    As the U.S. has transitioned towards self-sufficiency in petroleum 
production (the nation became a net exporter of petroleum in 2020), 
this transfer is increasingly from U.S. consumers of refined petroleum 
products to U.S. petroleum producers, so it not only leaves welfare 
unaffected but even ceases to be a financial burden on the U.S. 
economy. In fact, to the extent that the U.S. becomes a larger net 
petroleum exporter, any transfer from global consumers to petroleum 
producers becomes a financial benefit to the U.S. economy. 
Nevertheless, uncertainty in the nation's long-term import-export 
balance makes it difficult to project precisely how these effects might 
change in response to increased consumption.
    The loss of potential GDP from this externality will depend on the 
degree that global petroleum suppliers like the Organization of 
Petroleum Exporting Countries (OPEC) and Russia exercise market power 
which raise oil market prices above competitive market levels. In that 
situation, increases in U.S. gasoline demand will drive petroleum 
prices further above competitive levels, thus exacerbating this 
deadweight loss. More stringent standards lower gasoline demand and 
hence reduce these losses.
    Over most of the period spanned by NHTSA's analysis, any decrease 
in domestic spending for petroleum caused by the effect of lower U.S. 
fuel consumption and petroleum demand on world oil prices is expected 
to remain entirely a transfer within the U.S. economy. In the case in 
which large producers are able to exercise market power to keep global 
prices for petroleum above competitive levels, this reduction in price 
should also increase potential GDP in the U.S. However, the degree to 
which OPEC and other producers like Russia are able to act as a cartel 
depends on a variety of economic and political factors and has varied 
widely over recent history, so there is significant uncertainty over 
how this will evolve over the horizon that NHTSA models. For these 
reasons, lower U.S. spending on petroleum products that results from 
raising standards, reducing U.S. gasoline demand, and the downward 
pressure it places on global petroleum prices is not included among the 
economic benefits accounted for in the agency's evaluation of this 
proposed rule. We seek comment on this assumption.
    Second, higher U.S. petroleum consumption can also increase 
domestic consumers' exposure to oil price shocks and thus increase 
potential costs to all

[[Page 56254]]

U.S. petroleum users (including those outside the LDV and HDPUV 
sectors, whose consumption would be unaffected by this proposed rule) 
from possible interruptions in the global supply of petroleum or rapid 
increases in global oil prices. Because users of petroleum products are 
unlikely to consider the effect of their increased purchases on these 
risks, their economic value is often cited as an external cost of 
increased U.S. consumption. Decreased consumption, which we expect as a 
result of the proposed standards, decreases this cost. We include an 
estimate of this impact of the standards, and an explanation of our 
methodology can be found in Chapter 6.2.4.4 of the Draft TSD.
    Finally, some analysts argue that domestic demand for imported 
petroleum may also influence U.S. military spending; because the 
increased cost of military activities would not be reflected in the 
price paid at the gas pump, this is often suggested as a third category 
of external costs from increased U.S. petroleum consumption. For 
example, NHTSA has received extensive comments about exactly this 
effect on its past actions from the group Securing America's Energy 
Future. Most recent studies of military-related costs to protect U.S. 
oil imports conclude that significant savings in military spending are 
unlikely to result from incremental reductions in U.S. consumption of 
petroleum products on the scale that would result from adopting higher 
standards. While the cumulative effects of increasing fuel economy over 
the long-term likely have reduced the amount the U.S. has to spend to 
protect its interest in energy sources globally--avoid being beholden 
to geo-political forces that could disrupt oil supplies--it is 
extremely difficult to quantify the impacts and even further to 
identify how much a single fuel economy rule contributes. As such NHTSA 
does not estimate the impact of the proposed standards on military 
spending. See Chapter 6.2.4.5 of the Draft TSD for additional details.
    Each of these three factors would be expected to decrease 
incrementally as a consequence of a decrease in U.S. petroleum 
consumption resulting from the proposed standards. Chapter 6.2.4 of the 
Draft TSD provides a comprehensive explanation of NHTSA's analysis of 
these three impacts. NHTSA seeks comment on its accounting of energy 
security.
    NHTSA is also monitoring the availability of critical minerals used 
in electrified powertrains and whether any shortage of such materials 
could emerge as an additional energy security concern. While nearly all 
electricity in the United States is generated through the conversion of 
domestic energy sources and thus its supply does not raise security 
concerns, EVs also require sophisticated batteries to store and deliver 
that electricity. Currently, the most commonly used vehicle battery 
chemistries include materials that are either scarce or expensive, are 
sourced from potentially insecure or unstable overseas sites, and can 
pose environmental challenges during extraction and conversion to 
usable material. Known supplies of some of these critical minerals are 
also highly concentrated in a few countries and therefore face the same 
market power concerns as petroleum products.
    NHTSA is restricted from considering the fuel economy of 
alternative fuel sources in determining CAFE standards, and as such, 
the CAFE Model restricts the application of BEV pathways and PHEV 
electric efficiency in simulating compliance with the regulatory 
alternatives. However, the cost of critical minerals may affect the 
cost to supply both plug-in and non-plug-in hybrids that require larger 
batteries. Further, as manufacturers choose to produce more electrified 
vehicles, they will also become more susceptible to disruptions to 
critical mineral markets, which may make it harder for them to comply 
with CAFE standards if their voluntary compliance strategy relies on 
electrification rather than other technologies. NHTSA does not include 
costs or benefits related to these emerging energy security 
considerations in its analysis for this proposed rule but seeks comment 
on whether it is appropriate to include an estimate in the analysis 
and, if so, which data sources and methodologies it should employ.
(4) Changes in Labor Use and Employment
    As vehicle prices rise, we expect consumers to purchase fewer 
vehicles than they would have at lower prices. If manufacturers produce 
fewer vehicles as a consequence of lower demand, they may need less 
labor to produce and assemble vehicles, while dealers may need less 
labor to sell the vehicles. Conversely, as manufacturers add equipment 
to each new vehicle, the industry will require labor resources to 
develop, sell, and produce additional fuel-saving technologies. We also 
account for the possibility that new standards could shift the relative 
shares of passenger cars and light trucks in the overall fleet. Since 
the production of different vehicles involves different amounts of 
labor, this shift affects the required quantity of labor.
    The analysis considers the direct labor effects that the standards 
have across the automotive sector. The effects include (1) dealership 
labor related to new LDV and HDPUV unit sales; (2) assembly labor for 
vehicles, engines, and transmissions related to new vehicle unit sales; 
and (3) labor related to mandated additional fuel savings technologies, 
accounting for new vehicle unit sales. NHTSA has now used this 
methodology across several rulemakings but has generally not emphasized 
its results, largely because NHTSA found that attempting to quantify 
the overall labor or economic effects was too uncertain and difficult. 
We have also excluded any analysis of how changes in direct labor 
requirements could change employment in adjacent industries.
    NHTSA still believes that such an expanded analysis may be outside 
the effects that are reasonably traceable to the proposal; however, 
NHTSA has identified an exogenous model that can capture both the labor 
impacts contained in the CAFE Model and the secondary macroeconomic 
impacts due to changes in sales, vehicle prices, and fuel savings. 
Accompanying this proposal is a docket memo explaining how the CAFE 
Model's outputs may be used within Regional Economic Models, Inc. 
(REMI)'s PI + employment model to quantify the impacts of this 
proposal. We seek comment on the practicability of expanding the scope 
of the proposal's labor analysis for the final rule and whether the 
REMI model is appropriate.
    All labor effects are estimated and reported at a national 
aggregate level, in person-years, assuming 2,000 hours of labor per 
person-year. These labor hours are not converted to monetized values 
because we assume that the labor costs are included into a new 
vehicle's purchasing price. The analysis estimates labor effects from 
the forecasted CAFE Model technology costs and from review of 
automotive labor for the MY 2022 fleet. NHTSA uses information about 
the locations of vehicle assembly, engine assembly, and transmission 
assembly, and the percent of U.S. content of vehicles collected from 
American Automotive Labeling Act (AALA) submissions for each vehicle in 
the reference fleet. The analysis assumes that the fractions of parts 
that are currently made in the U.S. will remain constant for each 
vehicle as manufacturers add fuel-savings technologies. This should not 
be construed as a prediction that the percentage of U.S.-made parts--
and by extension U.S. labor--will remain

[[Page 56255]]

constant, but rather as an acknowledgement that NHTSA does not have a 
clear basis to project where future production may shift. The analysis 
also uses data from the NADA annual report to derive dealership labor 
estimates.
    We seek comment on these assumptions, and whether there are any 
data sources or methodologies the agency could employ to dynamically 
model parts content across different regulatory alternatives. While the 
IRA tax credit eligibility is not dependent on our labor assumptions 
here, if NHTSA were able to dynamically model changes in parts content 
with enough confidence in its precision, NHTSA could potentially employ 
those results to dynamically model a portion of tax credit eligibility.
    In sum, the analysis shows that the increased labor from producing 
additional technology necessary to meet the preferred alternative will 
outweigh any decreases attributable to the change in new vehicle sales. 
For a full description of the process NHTSA uses to estimate labor 
impacts, see Chapter 6.2.5 of the Draft TSD.
3. Costs and Benefits Not Quantified
    In addition to the costs and benefits described above, Table II-19 
includes two-line items without values. The first is maintenance and 
repair costs. Many of the technologies manufacturers apply to vehicles 
to meet the standards are sophisticated and costly. The technology 
costs capture only the initial or ``upfront'' costs to incorporate this 
equipment into new vehicles; however, if the equipment is costlier to 
maintain or repair--as seems likely because the materials used to 
produce the equipment are more expensive and the equipment itself is 
significantly more complex and requires more time and labor to maintain 
or repair--then consumers will also experience increased costs 
throughout the lifetime of the vehicle to keep it operational. 
Conversely, electrification technologies offer the potential to lower 
repair and maintenance costs. For example, BEVs do not have engines 
that are costly to maintain, and all electric pathways with 
regenerative braking may reduce the strain on braking equipment and 
consequential extend the useful life of braking equipment. However, 
NHTSA notes that due to statutory constraints on considering the fuel 
economy of BEVs and the full fuel economy of PHEVs in determining 
maximum feasible CAFE standards, any reduction in maintenance and 
repair costs due to electrification would have a limited impact on 
NHTSA's analysis comparing alternatives. NHTSA seeks comment on methods 
for estimating these costs.
    The second empty line item in the table is the value of potential 
sacrifices in other vehicle attributes. Some technologies that could be 
used to improve fuel economy can also be used to increase other vehicle 
attributes, especially performance, carrying capacity, comfort, and 
energy-using accessories, though some technologies can also increase 
both fuel economy and performance simultaneously. While this is most 
obvious for technologies that improve the efficiency of engines and 
transmissions, it may also be true of technologies that reduce mass, 
aerodynamic drag, rolling resistance or any road or accessory load. The 
exact nature of the potential to trade-off attributes for fuel economy 
varies with specific technologies, but at a minimum, increasing vehicle 
efficiency or reducing loads allows a more powerful engine to be used 
while achieving the same level of fuel economy. It is also possible if 
consumers are unable to access financing to cover the purchase price of 
the attributes they value as well as additional fuel economy that will 
more than pay for itself that the additional cost of the new technology 
leads consumers to purchase vehicles that are smaller or lack features 
such as heated seats, advanced entertainment systems, or panoramic 
sunroofs, which are amenities consumers value but are unrelated to the 
performance of the drivetrain.\441\ How consumers value increased fuel 
economy and how fuel economy regulations affect manufacturers' 
decisions about using efficiency improving technologies can have 
important effects on the estimated costs, benefits, and indirect 
impacts of fuel economy standards. Nevertheless, any sacrifice in 
potential improvements to vehicles' other attributes could represent a 
net opportunity cost to their buyers (though performance-efficiency 
tradeoffs could also lower compliance costs, and some additional 
attributes, like acceleration, could come with their own countervailing 
social costs).
---------------------------------------------------------------------------

    \441\ NHTSA notes that if consumers simply take out a larger 
loan, then some future consumption is replaced by higher principle 
and interest payments in the future.
---------------------------------------------------------------------------

    NHTSA has previously attempted to model the potential sacrifice in 
other vehicle attributes in sensitivity analyses by assuming the 
opportunity cost must be greater than some percentage of the fuel 
savings they voluntarily forego. In those previous rulemakings, NHTSA 
acknowledged that it is extremely difficult to quantify the potential 
loss of other vehicle attributes, and therefore included the value of 
other vehicle attributes only in sensitivity analyses. This approach is 
used in a sensitivity analysis for this proposed rule. NHTSA seeks 
comment on alternative methods for estimating the potential sacrifice 
in other vehicle attributes.
    The results of NHTSA's analysis of the proposed HDPUV standards 
suggest that buyer's perceived reluctance to purchasing higher-mpg 
models is due to undervaluation of the expected fuel savings due to 
market failures, including short-termism, principal-agent split 
incentives, uncertainty about the performance and service needs of new 
technologies and first-mover disadvantages for consumers, uncertainty 
about the resale market, and market power and first-mover disadvantages 
among manufacturers. This result is the same for vehicles purchased by 
individual consumers and those bought for commercial purposes. NHTSA 
tested the sensitivity of the analysis to the potential that the market 
failures listed do not apply to the commercial side of the HDPUV 
market. In this sensitivity analysis, commercial operators are modeled 
as profit maximizers who would not be made more or less profitable by 
more stringent standards by offsetting the estimated net private 
benefit to commercial operators.\442\ NHTSA decided against including 
this alternative in the primary analysis to align with its approach to 
market failures in the light-duty analysis. Furthermore, there is 
insufficient data on the size and composition of the commercial share 
of the HDPUV market to develop a precise estimate of a commercial 
operator opportunity cost. For additional details, see Chapter 9.2.3.10 
of the Draft RIA. We seek comment on this sensitivity analysis, and in 
particular, comments on market failures that are relevant to commercial 
operators and sources to help identify the market share of commercial 
operators.
---------------------------------------------------------------------------

    \442\ Relevant sensitivity cases are labeled ``Commercial 
Operator Sales Share'' and denote the percent of the fleet assumed 
owned by commercial operators. NHTSA calculates net private benefits 
as the sum of technology costs, lost consumer surplus from reduced 
new vehicle sales, and safety costs internalized by drivers minus 
fuel savings, benefits from additional driving, and savings from 
less frequent refueling.
---------------------------------------------------------------------------

H. Simulating Safety Effects of Regulatory Alternatives
    The primary objective of the standards is to achieve maximum 
feasible fuel economy and fuel efficiency, thereby reducing fuel 
consumption. In setting standards to achieve this intended effect, the

[[Page 56256]]

potential of the standards to affect vehicle safety is also considered. 
As a safety agency, NHTSA has long considered the potential for adverse 
or positive safety consequences when establishing CAFE and fuel 
efficiency standards.
    This safety analysis includes the comprehensive measure of safety 
impacts of the proposed LD and HDPUV standards from three sources:

 Changes in Vehicle Mass

    Similar to previous analyses, NHTSA calculates the safety impact of 
changes in vehicle mass made to reduce fuel consumption to comply with 
the standards. Statistical analysis of historical crash data indicates 
reducing mass in heavier vehicles generally improves safety for 
occupants in lighter vehicles and other road users like pedestrians and 
cyclists, while reducing mass in lighter vehicles generally reduces 
safety. NHTSA's crash simulation modeling of vehicle design concepts 
for reducing mass revealed similar effects. These observations align 
with the role of mass disparity in crashes; when vehicles of different 
masses collide, the smaller vehicle will experience a larger change in 
velocity (and, by extension, force), which increases the risk to its 
occupants. NHTSA believes the most recent analysis represents the best 
estimate of the impacts of MR that results in changes in mass 
disparities on crash fatalities, although it is important to note that 
these best estimates are not significantly different from zero and are 
not significant at the 5th confidence level. NHTSA seeks comments on 
its approach to estimating the effects of the standards on mass-safety.
 Impacts of Vehicle Prices on Fleet Turnover
    Vehicles have become safer over time through a combination of new 
safety regulations and voluntary safety improvements. NHTSA expects 
this trend to continue as emerging technologies, such as advanced 
driver assistance systems, are incorporated into new vehicles. Safety 
improvements will likely continue regardless of changes in the 
standards.
    As discussed in Section III.E.2, technologies added to comply with 
fuel economy and efficiency standards have an impact on vehicle prices, 
therefore slowing the acquisition of newer vehicles and retirement of 
older ones. The delay in fleet turnover caused by the effect of new 
vehicle prices affect safety by slowing the penetration of new safety 
technologies into the fleet.
    The standards also influence the composition of the LD fleet. As 
the safety provided by light trucks, SUVs and passenger cars responds 
differently to technology that manufacturers employ to meet the 
standards--particularly MR--fleets with different compositions of body 
styles will have varying numbers of fatalities, so changing the share 
of each type of LDV in the projected future fleet impacts safety 
outcomes.
    However, any fatalities associated with changes in sales and fleet 
share represent a small fraction of the total number of expected 
fatalities in the No-Action Alternative.
 Increased Driving Because of Better Fuel Economy
    The ``rebound effect'' predicts consumers will drive more when the 
cost of driving declines. More stringent standards reduce vehicle 
operating costs, and in response, some consumers may choose to drive 
more. Additional driving increases exposure to risks associated with 
motor vehicle travel, and this added exposure translates into higher 
fatalities and injuries. However, any fatalities associated with 
rebound driving represent a small fraction of the total number of 
fatalities that are expected in the No-Action Alternative.
    The contributions of the three factors described above generate the 
differences in safety outcomes among regulatory alternatives. NHTSA's 
analysis makes extensive efforts to allocate the differences in safety 
outcomes between the three factors. Fatalities expected during future 
years under each alternative are projected by deriving a fleet-wide 
fatality rate (fatalities per vehicle mile of travel) that incorporates 
the effects of differences in each of the three factors from baseline 
conditions and multiplying it by that alternative's expected VMT. 
Fatalities are converted into a societal cost by multiplying fatalities 
with the DOT-recommended VSL supplemented by economic impacts that are 
external to VSL measurements. Traffic injuries and property damage are 
also modeled directly using the same process and valued using costs 
that are specific to each injury severity level.
    All three factors influence predicted fatalities, but only two of 
them--changes in vehicle mass and in the composition of the LD fleet in 
response to changes in vehicle prices--impose increased risks on 
drivers and passengers that are not compensated for by accompanying 
benefits. In contrast, increased driving associated with the rebound 
effect is a consumer choice that reveals the benefits of additional 
travel. Consumers who choose to drive more have apparently concluded 
that the utility of additional driving exceeds the additional costs for 
doing so, including the crash risk that they perceive additional 
driving involves. As discussed in Chapter 7 of the Draft TSD, the 
benefits of rebound driving are accounted for by offsetting a portion 
of the added safety costs.
    For the safety component of the analysis for this proposal, NHTSA 
assumed that HDPUVs have the same risk exposure as light trucks. Given 
that the HDPUV fleet is significantly smaller than the LD fleet, the 
sample size to derive safety coefficients separately for HDPUVs is 
challenging. We believe that HDPUVs share many physical commonalities 
with light trucks and the incidence and crash severity are likely to be 
similar. As such, we concluded it was appropriate to use the light 
truck safety coefficients for HDPUVs. We seek comment on this 
assumption.
    NHTSA is also expanding its safety analysis to include non-
occupants to the analysis. The agency categorizes safety outcome 
through three measures of LD and HDPUV vehicle safety: fatalities 
occurring in crashes, serious injuries, and the amount of property 
damage incurred in crashes with no injuries. Counts of fatalities to 
occupants of automobiles and non-occupants are obtained from NHTSA's 
Fatal Accident Reporting System. Estimates of the number of serious 
injuries to drivers and passengers of LD and HDPUV vehicles are 
tabulated from NHTSA's General Estimates System (GES) for 1990-2015, 
and from its Crash Report Sampling System (CRSS) for 2016-2019. Both 
GES and CRSS include annual samples of motor vehicle crashes occurring 
throughout the United States. Weights for different types of crashes 
were used to expand the samples of each type to estimates of the total 
number of crashes occurring during each year. Finally, estimates of the 
number of automobiles involved in property damage-only crashes each 
year were also developed using GES.
    NHTSA seeks comment on its safety assumptions and methodology, 
which is described in detail in Chapter 7 of the Draft TSD.
1. Mass Reduction Impacts
    Vehicle mass reduction can be one of the more cost-effective means 
of improving efficiency, particularly for makes and models not already 
built with much high-strength steel or aluminum closures or low-mass 
components. Manufacturers have stated that they will continue to reduce 
mass of some of their models to meet more stringent standards, and 
therefore, this expectation is incorporated into the modeling analysis 
supporting the

[[Page 56257]]

standards. Safety trade-offs associated with mass-reduction have 
occurred in the past, particularly before standards were attribute-
based because manufacturers chose, in response to standards, to build 
smaller and lighter vehicles; these smaller, lighter vehicles did not 
fare as well in crashes as larger, heavier vehicles, on average. 
Although NHTSA now uses attribute-based standards, in part to reduce or 
eliminate the incentive to downsize vehicles to comply with the 
standards, NHTSA must be mindful of the possibility of related safety 
trade-offs. For this reason, NHTSA accounts for how MR applied to meet 
the standards would affect the safety of a specific vehicle given its 
starting and ending GVWR.
    For this proposed rule, the agency employed the modeling technique 
developed in the 2016 Puckett and Kindelberger report to analyze the 
updated crash and exposure data by examining the cross sections of the 
societal fatality rate per billion vehicle miles of travel (VMT) by 
mass and footprint, while controlling for driver age, gender, and other 
factors, in separate logistic regressions for five vehicle groups and 
nine crash types. NHTSA utilized the relationships between weight and 
safety from this analysis, expressed as percentage increases in 
fatalities per 100-pound weight reduction (which is how MR is applied 
in the technology analysis; see Section III.D.4), to examine the weight 
impacts applied in this analysis. The effects of MR on safety were 
estimated relative to (incremental to) the regulatory baseline in the 
analysis, across all vehicles for MY 2021 and beyond. NHTSA agency is 
faced with competing challenges. Research has consistently shown that 
MR affects ``lighter'' and ``heavier'' vehicles differently across 
crash types. The 2016 Puckett and Kindelberger report found MR 
concentrated among the heaviest vehicles is likely to have a beneficial 
effect on overall societal fatalities, while MR concentrated among the 
lightest vehicles is likely to have a detrimental effect on occupant 
fatalities but a slight benefit to pedestrians and cyclists. This 
represents a relationship between the dispersion of mass across 
vehicles in the fleet and societal fatalities: decreasing dispersion is 
associated with a decrease in fatalities. MR in heavier vehicles is 
more beneficial to the occupants of lighter vehicles than it is harmful 
to the occupants of the heavier vehicles. MR in lighter vehicles is 
more harmful to the occupants of lighter vehicles than it is beneficial 
to the occupants of the heavier vehicles.
    To accurately capture the differing effect on lighter and heavier 
vehicles, NHTSA splits vehicles into lighter and heavier vehicle 
classifications in the analysis. However, this poses a challenge of 
creating statistically meaningful results. There is limited relevant 
crash data to use for the analysis. Each partition of the data reduces 
the number of observations per vehicle classification and crash type, 
and thus reduces the statistical robustness of the results. The 
methodology employed by NHTSA was designed to balance these competing 
forces as an optimal trade-off to accurately capture the impact of 
mass-reduction across vehicle curb weights and crash types while 
preserving the potential to identify robust estimates.
    A more detailed description of the mass-safety analysis can be 
found in Chapter 7.2 of the Draft TSD.
2. Sales/Scrappage Impacts
    The sales and scrappage responses to higher vehicle prices 
discussed in Section III.E.2 have important safety consequences and 
influence safety through the same basic mechanism, fleet turnover. In 
the case of the scrappage response, delaying fleet turnover keeps 
drivers in older vehicles which tend to be less safe than newer 
vehicles. Similarly, the sales response slows the rate at which newer 
vehicles, and their associated safety improvements, enter the on-road 
population. The sales response also influences the mix of vehicles on 
the road-with more stringent CAFE standards leading to a higher share 
of light trucks sold in the new vehicle market, assuming all else is 
equal. Light trucks have higher rates of fatal crashes when interacting 
with passenger cars and, as earlier discussed, different directional 
responses to MR technology based on the existing mass and body style of 
the vehicle.
    Any effect on fleet turnover (either from delayed vehicle 
retirement or deferred sales of new vehicles) will affect the 
distribution of both ages and MYs present in the on-road LD and HDPUV 
fleets. Because each of these vintages carries with it inherent rates 
of fatal crashes, and newer vintages are generally safer than older 
ones, changing that distribution will change the total number of on-
road fatalities under each regulatory alternative. Similarly, the DFS 
model captures the changes in the LD fleet's composition of cars and 
trucks. As cars and trucks have different fatality rates, differences 
in fleet composition across the alternatives will affect fatalities.
    At the highest level, NHTSA calculates the impact of the sales and 
scrappage effects by multiplying the VMT of a vehicle by the fatality 
risk of that vehicle. For this analysis, calculating VMT is rather 
simple: NHTSA uses the distribution of miles calculated in Chapter 4.3 
of the Draft TSD. The trickier aspect of the analysis is creating 
fatality rate coefficients. The fatality risk measures the likelihood 
that a vehicle will be involved in a fatal accident per mile driven. 
NHTSA calculates the fatality risk of a vehicle based on the vehicle's 
MY, age, and style, while controlling for factors that are independent 
of the intrinsic nature of the vehicle, such as behavioral 
characteristics. Using this same approach, NHTSA designed separate 
models for fatalities, non-fatal injuries, and property damaged 
vehicles. We seek comment on the fatality models in Chapter 7.1 of the 
Draft TSD.
    The vehicle fatality risk described above captures the historical 
evolution of safety. Given that modern technologies are proliferating 
faster than ever and offer greater safety benefits than traditional 
safety improvements, NHTSA augmented the fatality risk projections with 
knowledge about forthcoming safety improvements. NHTSA applied 
estimates of the market uptake and improving effectiveness of crash 
avoidance technologies to estimate their effect on the fleet-wide 
fatality rate, including explicitly incorporating both the direct 
effect of those technologies on the crash involvement rates of new 
vehicles equipped with them, as well as the ``spillover'' effect of 
those technologies on improving the safety of occupants of vehicles 
that are not equipped with these technologies.
    NHTSA's approach to measuring these impacts is to derive 
effectiveness rates for these advanced crash-avoidance technologies 
from safety technology literature. NHTSA then applies these 
effectiveness rates to specific crash target populations for which the 
crash avoidance technology is designed to mitigate and adjusted to 
reflect the current pace of adoption of the technology, including the 
public commitment by manufactures to install these technologies. The 
products of these factors, combined across all 7 advanced technologies, 
produce a fatality rate reduction percentage that is applied to the 
fatality rate trend model discussed above, which projects both vehicle 
and non-vehicle safety trends. The combined model produces a projection 
of impacts of changes in vehicle safety technology as well as 
behavioral and infrastructural trends. A much more detailed discussion 
of the methods and inputs used to make these

[[Page 56258]]

projections of safety impacts from advanced technologies is included in 
Chapter 7.1 of the Draft TSD. We seek comment on our general approach 
to modeling the impact of advance crash avoidance systems on safety and 
invite commenters to provide any additional empirical data and research 
that we can use to augment the analysis.
3. Rebound Effect Impacts
    The additional VMT demanded due to the rebound effect is 
accompanied by more exposure to risk, however, rebound miles are not 
imposed on consumers by regulation. They are a freely chosen activity 
resulting from reduced vehicle operational costs. As such, NHTSA 
believes a large portion of the safety risks associated with additional 
driving are offset by the benefits drivers gain from added driving. The 
level of risk internalized by drivers is uncertain. This analysis 
assumes that drivers of both HDPUV and LDVs internalize 90 percent of 
this risk, which mostly offsets the societal impact of any added 
fatalities from this voluntary consumer choice. Additional discussion 
of internalized risk is contained in Chapter 7.4 of the Draft TSD. 
NHTSA seeks comment on this assumption and asks commenters to provide 
any academic literature that may attempt to further illuminate this 
topic.
4. Value of Safety Impacts
    Fatalities, nonfatal injuries, and property damage crashes are 
valued as a societal cost within the CAFE Model's cost and benefit 
accounting. Their value is based on the comprehensive value of a 
fatality, which includes lost quality of life and is quantified in the 
VSL as well as economic consequences such as medical and emergency 
care, insurance administrative costs, legal costs, and other economic 
impacts not captured in the VSL alone. These values were derived from 
data in Blincoe et al. (2015), adjusted to 2021 dollars, and updated to 
reflect the official DOT guidance on the VSL.
    Nonfatal injury costs, which differ by severity, were weighted 
according to the relative incidence of injuries across the Abbreviated 
Injury Scale (AIS). To determine this incidence, NHTSA applied a KABCO/
MAIS translator to CRSS KABCO based injury counts from 2017 through 
2019. This produced the MAIS-based injury profile. This profile was 
used to weight nonfatal injury unit costs derived from Blincoe et al., 
adjusted to 2021 economics and updated to reflect the official DOT 
guidance on the VSL. Property-damaged vehicle costs were also taken 
from Blincoe et al. and adjusted to 2021 economics.
    For the analysis, NHTSA assigns a societal value of $12.2 million 
for each fatality, $153,000 for each nonfatal injury, and $7,700 for 
each property damaged vehicle.
    As discussed in the previous section, NHTSA discounts 90% of the 
safety costs associated with the rebound effect. The remaining 10% of 
those safety costs are not considered to be internalized by drivers and 
appear as a cost of the standards that influence net benefits. 
Similarly, the effects on safety attributable to changes in mass and 
fleet turnover are not considered costs internalized by drivers since 
manufacturers are responsible for deciding how to design and price 
vehicles. The costs not internalized by drivers is therefore the 
summation of the mass-safety effects, fleet turnover effects, and the 
remaining 10% of rebound-related safety effects.

III. Regulatory Alternatives Considered in This NPRM

A. General Basis for Alternatives Considered

    Agencies typically consider regulatory alternatives in order to 
evaluate the comparative effects of different potential ways of 
implementing their statutory authority to achieve their intended policy 
goals. NEPA requires agencies to compare the potential environmental 
impacts of their actions to a reasonable range of alternatives. E.O. 
12866 and 13563, as well as OMB Circular A-4, also request that 
agencies evaluate regulatory alternatives in their rulemaking analyses.
    Alternatives analysis begins with a ``No-Action'' Alternative, 
typically described as what would occur in the absence of any further 
regulatory action by the agency. OMB Circular A-4 states that the 
``baseline should be the best assessment of the way the world would 
look absent the regulatory action. The choice of an appropriate 
baseline may require consideration of a wide range of potential 
factors, including:
     Evolution of the market,
     Changes in external factors affecting expected benefits 
and costs,
     Changes in regulations promulgated by the agency or other 
government entities, and
     The degree of compliance by regulated entities with other 
regulations.'' \443\
---------------------------------------------------------------------------

    \443\ OMB Circular A-4. General Issues, 2. Developing a 
Baseline. Available at: https://obamawhitehouse.archives.gov/omb/circulars_a004_a-4/. (Accessed: May 31, 2023).
---------------------------------------------------------------------------

    This proposal includes a No-Action Alternative for passenger cars 
and light trucks and a No-Action alternative for HDPUVs, both described 
below; four ``action alternatives'' for passenger cars and light 
trucks; and three action alternatives for HDPUVs. The proposed 
standards may, in places, be referred to as the ``Preferred 
Alternative,'' which is NEPA parlance, but NHTSA intends ``proposed 
standards'' and ``Preferred Alternative'' to be used interchangeably 
for purposes of this proposal. NHTSA believes this appropriately 
comports with the Council on Environmental Quality's (CEQ) directive 
that ``agencies shall . . . limit their consideration to a reasonable 
number of alternatives.'' \444\
---------------------------------------------------------------------------

    \444\ 40 CFR 1502.14(f).
---------------------------------------------------------------------------

    The different regulatory alternatives for passenger cars and light 
trucks are defined in terms of percent-increases in CAFE stringency 
from year to year. Readers should recognize that those year-over-year 
changes in stringency are not measured in terms of mile per gallon 
differences (as in, 1 percent more stringent than 30 mpg in one year 
equals 30.3 mpg in the following year), but rather in terms of shifts 
in the footprint functions that form the basis for the actual CAFE 
standards (as in, on a gallon per mile basis, the CAFE standards change 
by a given percentage from one MY to the next). One action alternative 
is less stringent than the Preferred Alternative for passenger cars and 
light trucks and two action alternatives are more stringent. The 
alternatives considered in this proposal for passenger cars and light 
trucks represent a reasonable range of possible agency actions.\445\
---------------------------------------------------------------------------

    \445\ See Draft TSD Chapter 1.2.1 for a complete discussion 
about the footprint curve functions and how they are calculated.
---------------------------------------------------------------------------

    In a departure from recent CAFE rulemaking trends, we have applied 
different rates of increase to the passenger car and the light truck 
fleets. Rather than have both fleets increase their respective 
standards at the same rate, light truck standards will increase at a 
faster rate than passenger car standards. Each action alternative 
evaluated for this proposal has a passenger car fleet rate-of-increase 
of fuel economy lower than the rate-of-increase of fuel economy for the 
light truck fleet. NHTSA has discretion, by law, to set CAFE standards 
that increase at different rates for cars and trucks, because NHTSA 
must set maximum feasible CAFE standards separately for cars and 
trucks.\446\ We have selected

[[Page 56259]]

this approach for the current proposal for several reasons.
---------------------------------------------------------------------------

    \446\ See, e.g., the 2012 final rule establishing CAFE standards 
for MYs 2017 and beyond, in which rates of stringency increase for 
passenger cars and light trucks were different. 77 FR 62623, 62638-
39 (Oct. 15, 2012).
---------------------------------------------------------------------------

    First, NHTSA believes that manufacturers will deploy considerable 
amounts of technology to reach the existing passenger car fuel economy 
standards adopted for MYs 2024-26. This is not to say that NHTSA now 
concludes those standards set in 2022 are beyond maximum feasible, but 
simply to note that as manufacturers continue to improve fuel economy 
in response to those standards, in the absence of further technological 
innovation, less technology will remain on the table to be used for 
additional stringent increases in subsequent years, particularly for 
passenger cars. Because the CAFE statute prohibits us from considering 
BEVs and full PHEVs' combined fuel economy, we believe manufacturers 
will find it difficult to improve fuel economy with ICE engine 
technologies beyond what we are proposing for passenger cars and 
maintain a reasonable cost. This is supported by feedback we have 
received from industry stakeholders, suggesting that consumers are less 
willing and able to absorb significant additional regulatory costs for 
passenger cars than they are for light trucks. This phenomenon is more 
pronounced for smaller cars, where manufacturers have already 
significantly increased fuel economy in response to existing standards, 
leaving only the most expensive fuel saving technology options and 
where additional regulatory costs may represent a larger percentage of 
the overall vehicle cost. Our (statutorily constrained) analysis also 
suggests that costs for improvements in fuel economy for passenger cars 
are increasingly no longer offset by the value of the fuel saved (or 
other benefits to the purchaser), which makes ongoing rapid increases 
less feasible.\447\ We do not believe this is a trend that is in the 
best interests of American consumers, particularly those who are 
seeking affordable new cars.
---------------------------------------------------------------------------

    \447\ This is true specifically because of the statutory 
restrictions on considering the fuel economy of BEVs and the full 
fuel economy of PHEVs for new CAFE standards, and especially for 
passenger cars given their technology levels.
---------------------------------------------------------------------------

    Second, as discussed in Draft TSD Chapter 1.2.4, NHTSA carefully 
considered the existing curve shapes in light of ongoing trends in the 
fleet, and determined, as in the 2022 TSD, that changing our approach 
to standard stringency made more sense for CAFE standards than changing 
the curve shapes at this point. We believe the ongoing trend \448\ to 
also be driven by new types of vehicles classified as light trucks 
simply on the basis of having AWD that would otherwise be subject to 
the generally-more-stringent passenger car curve. Consumers appear 
receptive to these offerings, but they may end up with less fuel 
savings than if the vehicles had been classified as passenger cars 
instead, which appears to run counter to EPCA's overarching purpose of 
energy conservation. Attribute-based standards and separate standards 
for cars and trucks are statutorily required and are designed to 
accommodate these market trends but have resulted in less fuel savings 
which would otherwise accrue to American consumers. Additionally, we 
believe light trucks have significantly more opportunity for fuel 
economy improvements due to lower baseline technology levels, and 
greater average VMT values. Our analysis shows that for light truck 
stringency increases, the value of fuel savings alone outweighs the 
increased regulatory cost. In short, there appears to be more room to 
improve the light truck fleet, and thus NHTSA has considered larger 
ongoing increases in stringency for this fleet compared to passenger 
cars, though still generally smaller increases than those finalized for 
MYs 2024-2026.
---------------------------------------------------------------------------

    \448\ See trends discussion in TSD Chapter 1.2.3.1.
---------------------------------------------------------------------------

    For HDPUVs, the different regulatory alternatives are also defined 
in terms of percent-increases in stringency from year to year, but in 
terms of fuel consumption reductions rather than fuel economy 
increases, so that increasing stringency appears to result in standards 
going down (representing a direct reduction in fuel consumed) over time 
rather than up. Also, unlike for the passenger car and light truck 
standards, because HDPUV standards are in fuel consumption space, year-
over-year percent changes actually do represent gallon/mile differences 
across the work-factor range. Under each action alternative, the 
stringency changes at the same percentage rate in each MY in the 
rulemaking time frame. One action alternative is less stringent than 
the Preferred Alternative for HDPUVs, and one action alternative is 
more stringent. The alternatives considered in this proposal for HDPUVs 
represent a reasonable range of possible agency actions.

B. Regulatory Alternatives Under Consideration in This Proposal

    The regulatory alternatives considered by the agency in this 
proposal are presented here as the percent-increases-per-year that they 
represent. The sections that follow will present the alternatives as 
the literal coefficients that define standards curves increasing at the 
given percentage rates. NHTSA requests comment on the full range of 
standards encompassed between the No-Action Alternative and Alternative 
PC6LT8 for MYs 2027-2032 passenger cars and light trucks, including the 
possibility of setting standards in between the considered 
alternatives. NHTSA also requests comment on the full range of 
standards encompassed between the No-Action Alternative and Alternative 
HDPUV14 for MYs 2030-2035 HDPUVs, including the possibility of setting 
standards in between the considered alternatives.

 Table III-1--Regulatory Alternatives Under Consideration for MYs 2027-
                  2032 Passenger Cars and Light Trucks
------------------------------------------------------------------------
                                        Passenger car      Light truck
                                         stringency        stringency
         Name of alternative          increases,  year- increases,  year-
                                        over-year (%)     over-year (%)
------------------------------------------------------------------------
No-Action Alternative...............               N/A               N/A
Alternative PC1LT3..................                 1                 3
Alternative PC2LT4 (Preferred                        2                 4
 Alternative).......................
Alternative PC3LT5..................                 3                 5
Alternative PC6LT8..................                 6                 8
------------------------------------------------------------------------


[[Page 56260]]


 Table III-2--Regulatory Alternatives Under Consideration for MYs 2030-
                               2035 HDPUVs
------------------------------------------------------------------------
                                                              HDPUV
                                                           stringency
                  Name of alternative                   increases,  year-
                                                          over-year (%)
------------------------------------------------------------------------
No-Action Alternative.................................               N/A
Alternative HDPUV4....................................                 4
Alternative HDPUV10 (Preferred Alternative)...........                10
Alternative HDPUV14...................................                14
------------------------------------------------------------------------

    A variety of factors will be at play simultaneously as 
manufacturers seek to comply with the eventual standards that NHTSA 
promulgates. Foreseeably, NHTSA, EPA, and CARB will all be regulating 
simultaneously; manufacturers will be responding to those regulations 
as well as to foreseeable shifts in market demand during the rulemaking 
time frame (both due to cost/price changes for different types of 
vehicles over time, fuel price changes, and the recently-passed tax 
credits for BEVs and PHEVs). Many costs and benefits that will accrue 
as a result of manufacturer actions during the rulemaking time frame 
will be occurring for reasons other than CAFE standards, and NHTSA 
believes it is important to try to reflect many of those factors in 
order to present a more accurate picture of the effects of different 
potential CAFE and HDPUV standards to decision-makers and to the 
public.
    The following sections define each regulatory alternative, 
including the No-Action Alternative, for each program, and explain 
their derivation.
1. No-Action Alternative
    As with the 2022 final rule, our No-Action Alternative is fairly 
nuanced. In this analysis, the No-Action Alternative assumes:
     The existing national CAFE and GHG standards are met, and 
that the CAFE and GHG standards for MY 2026 finalized in 2022 continue 
in perpetuity.
     Manufacturers who committed to the California Framework 
Agreements met their contractual obligations for MY 2022.
     The HDPUV MY 2027 standards finalized in the Phase 2 
program continue in perpetuity.
     Manufacturers will comply with the ZEV/ACC2/ACT standards 
that California has adopted, and other states have agreed to follow 
through 2035.
     Manufacturers will make production decisions in response 
to estimated market demand for fuel economy or fuel efficiency, 
considering estimated fuel prices, estimated product development 
cadence, the estimated availability, applicability, cost, and 
effectiveness of fuel-saving technologies, and available tax credits.
    NHTSA continues to believe that to properly estimate fuel 
economies/efficiencies (and achieved CO2 emissions) in the 
No-Action Alternative, it is necessary to simulate all of these legal 
requirements (extant and foreseeable) affecting automakers and vehicle 
design simultaneously.\449\ Consequently, the CAFE Model evaluates each 
requirement in each MY, for each manufacturer/fleet. Differences among 
fleets and compliance provisions often creates over-compliance in one 
program, even if a manufacturer is able to exactly comply (or under-
comply) in another program. This is similar to how manufacturers 
approach the question of concurrent compliance in the real world--when 
faced with multiple regulatory programs, the most cost-effective path 
may be to focus efforts on meeting one or two sets of requirements, 
even if that results in ``more effort'' than would be necessary for 
another set of requirements, in order to ensure that all regulatory 
obligations are met. We elaborate on those model capabilities below. 
Generally speaking, the model treats each manufacturer as applying the 
following logic when making technology decisions, both for simulating 
passenger car and light truck compliance, and HDPUV compliance, with a 
given regulatory alternative:
---------------------------------------------------------------------------

    \449\ To be clear, this is for purposes of properly estimating 
the No-Action Alternative, which represents what NHTSA believes is 
likely to happen in the world in the absence of future NHTSA 
regulatory action. NHTSA does not attempt to simulate further 
application of BEVs, for example, in determining amongst the action 
alternatives for passenger cars and light trucks which one would be 
maximum feasible, because the statute prohibits NHTSA from 
considering the fuel economy of BEVs in determining maximum feasible 
CAFE standards.
---------------------------------------------------------------------------

    1. What do I need to carry over from last year?
    2. What should I apply more widely in order to continue sharing 
(of, e.g., engines) across different vehicle models?
    3. What new BEVs do I need to build in order to satisfy anticipated 
manufacturer compliance with state ZEV mandates?
    4. What further technology, if any, could I apply that would enable 
buyers to recoup additional costs within 30 months after buying new 
vehicles?
    5. What additional technology, if any, should I apply to respond to 
potential new CAFE and CO2 standards for passenger cars and 
light trucks, or to potential new HDPUV standards?
    Additionally, within the context of 4 and 5, the CAFE Model may 
consider, as appropriate and allowed by statutory restrictions on 
technology application for a given MY, the applicability of recently-
passed tax credits for battery-based vehicle technologies, which 
improve the attractiveness of those technologies to consumers and thus 
the model's likelihood of choosing them as part of a compliance 
solution. The model can also apply over-compliance credits if 
applicable and not legally prohibited. The CAFE Model simulates all of 
these simultaneously. As mentioned above, this means that when 
manufacturers make production decisions in response to actions other 
than CAFE or HDPUV standards, those costs and benefits are not 
attributable to possible future CAFE or HDPUV standards. This approach 
allows the analysis to isolate the effects of the decision being made 
on the appropriate CAFE standards, as opposed to the effects of many 
things that will be occurring simultaneously.
    Existing NHTSA standards during the rulemaking time frame are 
modeled as follows:
    To account for the existing CAFE standards finalized in MY 2026 for 
passenger cars and light trucks, the No-Action Alternative includes the 
following coefficients defining those standards, which (for purposes of 
this analysis) are assumed to persist without change in subsequent MYs:

                              Table III-3--Passenger Car CAFE Target Function Coefficients for No-Action Alternative \450\
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               2027            2028            2029            2030            2031            2032
--------------------------------------------------------------------------------------------------------------------------------------------------------
a (mpg).................................................           66.95           66.95           66.95           66.95           66.95           66.95
b (mpg).................................................           50.09           50.09           50.09           50.09           50.09           50.09
c (gpm per s.f).........................................         0.00034         0.00034         0.00034         0.00034         0.00034         0.00034
d (gpm).................................................         0.00120         0.00120         0.00120         0.00120         0.00120         0.00120
--------------------------------------------------------------------------------------------------------------------------------------------------------


[[Page 56261]]


                               Table III-4--Light Truck CAFE Target Function Coefficients for No-Action Alternative \451\
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               2027            2028            2029            2030            2031            2032
--------------------------------------------------------------------------------------------------------------------------------------------------------
a (mpg).................................................           53.73           53.73           53.73           53.73           53.73           53.73
b (mpg).................................................           32.30           32.30           32.30           32.30           32.30           32.30
c (gpm per s.f).........................................         0.00037         0.00037         0.00037         0.00037         0.00037         0.00037
d (gpm).................................................         0.00327         0.00327         0.00327         0.00327         0.00327         0.00327
--------------------------------------------------------------------------------------------------------------------------------------------------------

    These coefficients are used to create the graphic below, where the 
x-axis represents vehicle footprint and the y-axis represents fuel 
economy, showing that in ``CAFE space,'' targets are higher in fuel 
economy for smaller footprint vehicles and lower for larger footprint 
vehicles.
---------------------------------------------------------------------------

    \450\ The Passenger Car Function Coefficients `a', `b', `c', and 
`d' are defined in Draft TSD Chapter 1.2.1, Equation 1-1.
    \451\ The Light Truck Function Coefficients `a', `b', `c', and 
`d' are defined in Draft TSD Chapter 1.2.1, Equation 1-1.
---------------------------------------------------------------------------

BILLING CODE 4910-59-P
[GRAPHIC] [TIFF OMITTED] TP17AU23.051

    Additionally, EPCA, as amended by EISA, requires that any 
manufacturer's domestically-manufactured passenger car fleet must meet 
the greater of either 27.5 mpg on average, or 92 percent of the average 
fuel economy projected by the Secretary for the combined domestic and 
non-domestic passenger automobile fleets manufactured for sale in the 
United States by all manufacturers in the MY. NHTSA retains the 1.9 
percent offset to the Minimum Domestic Passenger Car Standard (MDPCS), 
first used in the 2020 final rule, to account for recent projection 
errors as part of estimating the total passenger car fleet fuel 
economy, and used in rulemakings since.452 453 The 
projection shall be published in the Federal Register when the standard 
for that MY is promulgated in accordance with 49 U.S.C. 
32902(b).454 455 For purposes of the No-Action Alternative, 
the MDPCS is as it was established in the 2022 final rule for MY 2026, 
as shown in Table III-5 below:
---------------------------------------------------------------------------

    \452\ Section V.A.2 (titled ``Separate Standards for Passenger 
Cars, Light Trucks, and Heavy-Duty Pickups and Vans, and Minimum 
Standards for Domestic Passenger Cars'') of the NPRM discusses the 
basis for the offset.
    \453\ 87 FR 25710 (May 2, 2022).
    \454\ 49 U.S.C. 32902(b)(4).
    \455\ The offset will be applied to the final regulation 
numbers, but was not used in this analysis. The values for the MDPCS 
for the proposed action alternatives are nonadjusted values.

[[Page 56262]]



                                   Table III-5--No-Action Alternative--Minimum Domestic Passenger Car Standard (MDPCS)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                2027                                       2028             2029             2030             2031             2032
--------------------------------------------------------------------------------------------------------------------------------------------------------
53.5...............................................................            53.5             53.5             53.5             53.5             53.5
--------------------------------------------------------------------------------------------------------------------------------------------------------

    To account for the existing HDPUV standards finalized in the Phase 
2 rule, the No-Action Alternative for HDPUVs includes the following 
coefficients defining those standards, which (for purposes of this 
analysis) are assumed to persist without change in subsequent MYs:
---------------------------------------------------------------------------

    \456\ In the CAFE Model, these are Linear work-factor-based 
function where coefficients e and f are for diesels, BEVs and FCEVs, 
see TSD Chapter 1.2.1.
    \457\ In the CAFE Model, these are Linear work-factor-based 
function where coefficients c and d are for gasoline, CNG, strong 
hybrid vehicles and PHEVs, see TSD Chapter 1.2.1.

                               Table III-6--HDPUV CI Vehicle Target Function Coefficients for No-Action Alternative \456\
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               2030            2031            2032            2033            2034            2035
--------------------------------------------------------------------------------------------------------------------------------------------------------
e (gal/100 miles per WF)................................       0.0003418       0.0003418       0.0003418       0.0003418       0.0003418       0.0003418
f (gal/100 miles per WF)................................           2.633           2.633           2.633           2.633           2.633           2.633
--------------------------------------------------------------------------------------------------------------------------------------------------------


                               Table III-7--HDPUV SI Vehicle Target Function Coefficients for No-Action Alternative \457\
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               2030            2031            2032            2033            2034            2035
--------------------------------------------------------------------------------------------------------------------------------------------------------
c (gal/100 miles per WF)................................       0.0004152       0.0004152       0.0004152       0.0004152       0.0004152       0.0004152
d (gal/100 miles per WF)................................           3.196           3.196           3.196           3.196           3.196           3.196
--------------------------------------------------------------------------------------------------------------------------------------------------------

    These equations are represented graphically below:
    [GRAPHIC] [TIFF OMITTED] TP17AU23.052
    

[[Page 56263]]


[GRAPHIC] [TIFF OMITTED] TP17AU23.053

BILLING CODE 4910-59-C
    As the baseline scenario, the No-Action Alternative also includes 
the following additional actions that NHTSA believes will occur in the 
absence of further regulatory action by NHTSA:
    To account for the existing national GHG emissions standards, the 
No-Action Alternative for passenger cars and light trucks includes the 
following coefficients defining the GHG standards set by EPA in 2022 
for MY 2026, which (for purposes of this analysis) are assumed to 
persist without change in subsequent MYs:

                                  Table III-8--Passenger Car CO2 Target Function Coefficients for No-Action Alternative
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               2027            2028            2029            2030            2031            2032
--------------------------------------------------------------------------------------------------------------------------------------------------------
a (g/mi)................................................           114.3           114.3           114.3           114.3           114.3           114.3
b (g/mi)................................................           160.9           160.9           160.9           160.9           160.9           160.9
c (g/mi per s.f)........................................            3.11            3.11            3.11            3.11            3.11            3.11
d (g/mi)................................................          -13.10          -13.10          -13.10          -13.10          -13.10          -13.10
e (s.f.)................................................            41.0            41.0            41.0            41.0            41.0            41.0
f (s.f.)................................................            56.0            56.0            56.0            56.0            56.0            56.0
--------------------------------------------------------------------------------------------------------------------------------------------------------


                                   Table III-9--Light Truck CO2 Target Function Coefficients for No-Action Alternative
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               2027            2028            2029            2030            2031            2032
--------------------------------------------------------------------------------------------------------------------------------------------------------
a (g/mi)................................................           141.8           141.8           141.8           141.8           141.8           141.8
b (g/mi)................................................           254.4           254.4           254.4           254.4           254.4           254.4
c (g/mi per s.f)........................................            3.41            3.41            3.41            3.41            3.41            3.41
d (g/mi)................................................            1.90            1.90            1.90            1.90            1.90            1.90
e (s.f.)................................................            41.0            41.0            41.0            41.0            41.0            41.0
f (s.f.)................................................            74.0            74.0            74.0            74.0            74.0            74.0
--------------------------------------------------------------------------------------------------------------------------------------------------------

    Coefficients a, b, c, d, e, and f define the existing MY 2026 
Federal CO2 standards for passenger cars and light trucks, 
respectively, in Table III-8 and Table III-9 above. Analogous to 
coefficients defining CAFE standards, coefficients a and b specify 
minimum and maximum CO2 targets in each MY. Coefficients c 
and d specify the slope and intercept of the linear portion of the 
CO2 target function, and coefficients e and f bound the 
region within which CO2 targets are defined by this linear 
form.
    To account for the existing national GHG emission standards, the 
No-Action Alternative for HDPUVs includes the following coefficients 
defining the WF based standards set by EPA for MY 2027 and beyond. The 
four-wheel drive coefficient is maintained at 500 (coefficient `a') and 
the weighting multiplier coefficient is maintained at 0.75 (coefficient 
`b'). The CI and SI coefficients are in the tables below:

[[Page 56264]]



   Table III-10--HDPUV CI Vehicle Target Function Coefficients for No-
                           Action Alternative
------------------------------------------------------------------------
                                                          2027 and later
------------------------------------------------------------------------
e.......................................................          0.0348
f.......................................................             268
------------------------------------------------------------------------


   Table III-11--HDPUV SI Vehicle Target Function Coefficients for All
                              Alternatives
------------------------------------------------------------------------
                                                          2027 and later
------------------------------------------------------------------------
C.......................................................          0.0369
D.......................................................             284
------------------------------------------------------------------------

    Coefficients c, d, e, and f define the existing MY2027 and beyond 
CO2 standards from Phase 2 rule for HDPUVs, in Table III-10 
and Table III-11 above. The coefficients are linear work-factor based 
function with c and d representing gasoline, CNG vehicles, SHEVs and 
PHEVS and e and f representing diesels, BEVS and FCEVs. For this 
rulemaking, this is identical to the NHTSA's fuel efficiency standards 
No Action alternative.
    The No-Action Alternative also includes NHTSA's estimates of ways 
that each manufacturer could introduce new PHEVs and BEVs in response 
to state ZEV mandates. To account for the ZEV programs, NHTSA has 
included the main provisions of the ACC II and ACT programs in the CAFE 
Model's analysis of compliance pathways. Incorporating these programs 
into the model includes converting vehicles that have been identified 
as potential ZEV candidates into battery-electric vehicles (BEVs) so 
that a manufacturer's fleet meets the calculated ZEV credit 
requirements.\458\ The two programs have different requirements per MY, 
so they are modeled separately in the CAFE analysis. Chapter 2.3 of the 
Draft TSD discusses, in detail, how NHTSA developed these estimates.
---------------------------------------------------------------------------

    \458\ NHTSA made the decision to focus on BEVs for ZEV 
compliance based on several factors: first, because CARB only allows 
partial compliance with PHEVs; second, because NHTSA had 
conversations with manufacturers that indicated an interest in 
focusing on BEV development over developments of PHEV systems in the 
rulemaking time frame; and third, because including PHEVs in the ZEV 
modeling would have introduced unnecessary complication. See Docket 
Submission of Ex Parte Meetings Prior to Publication of the 
Corporate Average Fuel Economy Standards for Passenger Cars and 
Light Trucks for Model Years 2027-2032 and Fuel Efficiency Standards 
for Heavy-Duty Pickup Trucks and Vans for Model Years 2030-2035 
Notice of Proposed Rulemaking memorandum, which can be found under 
References and Supporting Material in the rulemaking Docket No. 
NHTSA-2023-0022.
---------------------------------------------------------------------------

    The No-Action Alternative also includes NHTSA estimates of ways 
that manufacturers could take advantage of recently-passed tax credits 
for battery-based vehicle technologies. NHTSA explicitly models 
portions of two provisions of the IRA when simulating the behavior of 
manufacturers and consumers. The first is the Advanced Manufacturing 
Production Tax Credit (AMPC). This provision of the IRA provides a $35 
per kWh tax credit for manufacturers of battery cells and an additional 
$10 per kWh for manufacturers of battery modules (all applicable to 
manufacture in the United States).\459\ These credits, with the 
exception of the critical minerals credit, phase out from 2030 to 2032. 
The second provision explicitly modeled is the CVC,\460\ which provides 
up to $7,500 toward the purchase of clean vehicles with critical 
minerals and battery components manufactured in North America.\461\ The 
AMPC and CVC provide tax credits for PHEVs, BEVs, and FCVs. Chapter 2.2 
in the Draft TSD discusses, in detail, how NHTSA has modeled these tax 
credits. These credits likely make the use of BEVs and PHEVs more 
attractive in complying with the California ZEV mandate and EPA's GHG 
standards.
---------------------------------------------------------------------------

    \459\ 26 U.S.C. 45X. If a manufacturer produces a battery module 
without battery cells, they are eligible to claim up to $45 per kWh 
for the battery module. The provision includes other provisions 
related to vehicles such as a credit equal to 10 percent of the 
manufacturing cost of electrode active materials, and another 10 
percent for the manufacturing cost of critical minerals. We are not 
modeling these credits directly because of how we estimate battery 
costs and to avoid the potential to double count the tax credits if 
they are included into other analyses that feed into our inputs.
    \460\ 26 U.S.C. 30D.
    \461\ There are vehicle price and consumer income limitations on 
the CVC as well, see Congressional Research Service. Tax Provisions 
in the Inflation Reduction Act of 2002 (H.R. 5376). Aug. 10, 2022.
---------------------------------------------------------------------------

    The No-Action Alternative for the passenger car, light truck and 
HDPUV fleets also includes NHTSA's assumption, for purposes of 
compliance simulations, that manufacturers will add fuel economy- or 
fuel efficiency-improving technology voluntarily, if the value of 
future undiscounted fuel savings fully offsets the cost of the 
technology within 30 months. This assumption is often called the ``30-
month payback'' assumption, and NHTSA has used it for many years and in 
many CAFE rulemakings.\462\ It is used to represent consumer demand for 
fuel economy. It can be a source of apparent ``over-compliance'' in the 
No-Action Alternative, especially when technology is estimated to be 
extremely cost-effective, as occurs later in the analysis time frame 
when learning has significant effects on some technology costs.
---------------------------------------------------------------------------

    \462\ Even though NHTSA uses the 30-month payback assumption to 
assess how much technology manufacturers would add voluntarily in 
the absence of new standards, the benefit-cost analysis accounts for 
the full lifetime fuel savings that would accrue to vehicles 
affected by the proposed standards.
---------------------------------------------------------------------------

    NHTSA staff believe that manufacturers do at times improve fuel 
economy even in the absence of new standards, for several reasons. 
First, overcompliance is not uncommon in the historical data, both in 
the absence of new standards, and with new standards--NHTSA's analysis 
in the 2022 TSD included CAFE compliance data showing that from 2004-
2017, while not all manufacturers consistently over-complied, a number 
did. Of the manufacturers who did over-comply, some did so by 20 
percent or more, in some fleets, over multiple MYs.\463\ Others have 
similarly observed the auto industry's secular march toward higher fuel 
economy over time, even in the absence of standards.\464\
---------------------------------------------------------------------------

    \463\ See 2022 TSD, at 68.
    \464\ Meyer, R. 2020. Trump's New Auto Rollback Is an Economic 
Disaster. Last revised: Apr. 13, 2020. Available at: https://www.theatlantic.com/science/archive/2020/04/trumps-auto-rollback-will-eliminate-13500-jobs-cafe/609748. (Accessed: May 31, 2023).
---------------------------------------------------------------------------

    Second, manufacturers have consistently told NHTSA that they do 
make fuel economy improvements where the cost can be fully recovered in 
the first 2-3 years of ownership. The 2015 NAS report discussed this 
assumption explicitly, stating: ``There is also empirical evidence 
supporting loss aversion as a possible cause of the energy paradox. 
Greene (2011) showed that if consumers accurately perceived the upfront 
cost of fuel economy improvements and the uncertainty of fuel economy 
estimates, the future price of fuel, and other factors affecting the 
present value of fuel savings, the loss-averse consumers among them 
would appear to act as if they had very high DRs or required payback 
periods of about 3 years.'' \465\ Furthermore, the 2020 NAS HD report 
states: ''The
---------------------------------------------------------------------------

    \465\ National Research Council. 2015. Cost, Effectiveness, and 
Deployment of Fuel Economy Technologies for Light-Duty Vehicles. The 
National Academies Press: Washington, DC. Page 31. Available at: 
https://doi.org/10.17226/21744. (Accessed: May 31, 2023) and 
available for review in hard copy at DOT headquarters). (hereinafter 
``2015 NAS report'').

---------------------------------------------------------------------------

[[Page 56265]]

committee has heard from manufacturers and purchasers that they look 
for 1.5- to 2-year paybacks or, in other cases, for a payback period 
that is half the expected ownership period of the first owner of the 
vehicle.'' \466\ Naturally, there are heterogenous preferences for 
vehicle attributes in the marketplace: at the same time that we are 
observing record sales of electrified vehicles, we are also seeing 
sustained demand for pickup trucks with higher payloads and towing 
capacity and hence lower fuel economy. This analysis, like all the CAFE 
analyses preceding it, uses an average value to represent these 
preferences for the CAFE fleet and the HDPUV fleet. The analysis 
balances the risks of estimating too low of a payback period, which 
would preclude most technologies from consideration regardless of 
potential cost reductions due to learning, against the risk of allowing 
too high of a payback period, which would allow an unrealistic cost 
increase from technology addition in the baseline fleet.
---------------------------------------------------------------------------

    \466\ National Academies of Sciences, Engineering, and Medicine. 
2020. Reducing Fuel Consumption and Greenhouse Gas Emissions of 
Medium- and Heavy-Duty Vehicles, Phase Two: Final Report. The 
National Academies Press: Washington, DC. p. 296. Available at: 
https://doi.org/10.17226/25542. (Accessed: May 31, 2023).
---------------------------------------------------------------------------

    Third, as in previous CAFE analyses, our fuel price projections 
assume sustained increases in real fuel prices over the course of the 
rule (and beyond). As readers are certainly aware, fuel prices have 
changed over time--sometimes quickly, sometimes slowly, generally 
upward:
[GRAPHIC] [TIFF OMITTED] TP17AU23.054

    In the 1990s, when fuel prices were historically low (as shown 
above), manufacturers did not tend to improve their fuel economy, 
likely in part because there simply was very little consumer demand for 
improved fuel economy and CAFE standards remained flat. In subsequent 
decades, when fuel prices were higher, many of them have exceeded their 
standards in multiple fleets, and for multiple years. Our current fuel 
price projections look more like the last two decades, where prices 
have been more volatile, but also closer to $3/gallon on average. In 
recent years, when fuel prices have generally declined on average and 
CAFE standards have continued to increase, fewer manufacturers have 
exceeded their standards. However, our compliance data show that at 
least some manufacturers do improve their fuel economy if fuel prices 
are high enough, even if they are not able to respond perfectly to 
fluctuations precisely when they happen. This highlights the importance 
of fuel price assumptions both in the analysis and in the real world on 
the future of fuel economy improvements.
2. Action Alternatives for MYs 2027-2032 Passenger Cars and Light 
Trucks
    In addition to the No-Action Alternative, NHTSA has considered four 
``action'' alternatives for passenger cars and light trucks, each of 
which is more stringent than the No-Action Alternative during the 
rulemaking time frame. These action alternatives are specified below 
and demonstrate different possible approaches to balancing the 
statutory factors applicable for passenger cars, light trucks, and 
HDPUVs. Section V discusses in more detail how the different 
alternatives reflect different possible balancing approaches.

[[Page 56266]]

a. Alternative PC1LT3

    Alternative PC1LT3 would increase CAFE stringency by 1 percent per 
year, year over year, for MYs 2027-2032 passenger cars, and by 3 
percent per year, year over year, for MYs 2027-2032 light trucks.
---------------------------------------------------------------------------

    \467\ The Passenger Car Function Coefficients `a', `b', `c', and 
`d' are defined in Draft TSD Chapter 1.2.1.
    \468\ The Light Truck Function Coefficients `a', `b', `c', and 
`d' are defined in Draft TSD Chapter 1.2.1.

                               Table III-12--Passenger Car CAFE Target Function Coefficients for Alternative PC1LT3 \467\
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               2027            2028            2029            2030            2031            2032
--------------------------------------------------------------------------------------------------------------------------------------------------------
a (mpg).................................................           67.63           68.31           69.00           69.70           70.40           71.11
b (mpg).................................................           50.60           51.11           51.63           52.15           52.68           53.21
c (gpm per s.f).........................................         0.00033         0.00033         0.00033         0.00032         0.00032         0.00032
d (gpm).................................................         0.00118         0.00117         0.00116         0.00115         0.00114         0.00113
--------------------------------------------------------------------------------------------------------------------------------------------------------


                                Table III-13--Light Truck CAFE Target Function Coefficients for Alternative PC1LT3 \468\
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               2027            2028            2029            2030            2031            2032
--------------------------------------------------------------------------------------------------------------------------------------------------------
a (mpg).................................................           55.39           57.10           58.87           60.69           62.56           64.50
b (mpg).................................................           33.30           34.33           35.39           36.48           37.61           38.78
c (gpm per s.f).........................................         0.00036         0.00035         0.00034         0.00033         0.00032         0.00031
d (gpm).................................................         0.00317         0.00308         0.00299         0.00290         0.00281         0.00273
--------------------------------------------------------------------------------------------------------------------------------------------------------

    These equations are represented graphically below:
BILLING CODE 4910-59-P
[GRAPHIC] [TIFF OMITTED] TP17AU23.055


[[Page 56267]]


[GRAPHIC] [TIFF OMITTED] TP17AU23.056

    Under this alternative, the MDPCS is as follows:

                Table III-14--Alternative PC1LT3--Minimum Domestic Passenger Car Standard (MDPCS)
----------------------------------------------------------------------------------------------------------------
       2027               2028               2029               2030               2031               2032
----------------------------------------------------------------------------------------------------------------
           54.6               55.2               55.7               56.3               56.9               57.4
----------------------------------------------------------------------------------------------------------------


b. Alternative PC2LT4--Preferred Alternative
---------------------------------------------------------------------------

    \469\ The Passenger Car Function Coefficients `a', `b', `c', and 
`d' are defined in Draft TSD Chapter 1.2.1.
    \470\ The Light Truck Function Coefficients `a', `b', `c', and 
`d' are defined in Draft TSD Chapter 1.2.1.

    Alternative PC2LT4 would increase CAFE stringency by 2 percent per 
year, year over year, for MYs 2027-2032 passenger cars, and by 4 
percent per year, year over year, for MYs 2027-2032 light trucks.

                               Table III-15--Passenger Car CAFE Target Function Coefficients for Alternative PC2LT4 \469\
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               2027            2028            2029            2030            2031            2032
--------------------------------------------------------------------------------------------------------------------------------------------------------
a (mpg).................................................           68.32           69.71           71.14           72.59           74.07           75.58
b (mpg).................................................           51.12           52.16           53.22           54.31           55.42           56.55
c (gpm per s.f).........................................         0.00033         0.00032         0.00032         0.00031         0.00030         0.00030
d (gpm).................................................         0.00117         0.00115         0.00113         0.00110         0.00108         0.00106
--------------------------------------------------------------------------------------------------------------------------------------------------------


                                Table III-16--Light Truck CAFE Target Function Coefficients for Alternative PC2LT4 \470\
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               2027            2028            2029            2030            2031            2032
--------------------------------------------------------------------------------------------------------------------------------------------------------
a (mpg).................................................           55.96           58.30           60.73           63.26           65.89           68.64
b (mpg).................................................           33.64           35.05           36.51           38.03           39.61           41.26
c (gpm per s.f).........................................         0.00036         0.00034         0.00033         0.00032         0.00031         0.00029
d (gpm).................................................         0.00314         0.00302         0.00289         0.00287         0.00267         0.00256
--------------------------------------------------------------------------------------------------------------------------------------------------------


[[Page 56268]]

    These equations are represented graphically below:
    [GRAPHIC] [TIFF OMITTED] TP17AU23.057
    
    [GRAPHIC] [TIFF OMITTED] TP17AU23.058
    

[[Page 56269]]


    Under this alternative, the MDPCS is as follows:

                 Table III-17--Alternative PC2LT4--Minimum Domestic Passenger Car Standard (MPG)
----------------------------------------------------------------------------------------------------------------
       2027               2028               2029               2030               2031               2032
----------------------------------------------------------------------------------------------------------------
           55.2               56.3               57.5               58.6               59.8               61.1
----------------------------------------------------------------------------------------------------------------


c. Alternative PC3LT5

    Alternative PC3LT5 would increase CAFE stringency by 3 percent per 
year, year over year, for MYs 2027-2032 passenger cars, and by 5 
percent per year, year over year, for MYs 2027-2032 light trucks.
---------------------------------------------------------------------------

    \471\ The Passenger Car Function Coefficients `a',`b',`c',and 
`d' are defined in Draft TSD Chapter 1.2.1.
    \472\ The Light Truck Function Coefficients 
``a'',``b'',``c'',and ``d'' are defined in Draft TSD Chapter 1.2.1.

                               Table III-18--Passenger Car CAFE Target Function Coefficients for Alternative PC3LT5 \471\
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               2027            2028            2029            2030            2031            2032
--------------------------------------------------------------------------------------------------------------------------------------------------------
a (mpg).................................................           69.02           71.16           73.36           75.63           77.97           80.38
b (mpg).................................................           51.64           53.24           54.89           56.58           58.33           60.14
c (gpm per s.f).........................................         0.00033         0.00032         0.00031         0.00030         0.00029         0.00028
d (gpm).................................................         0.00116         0.00113         0.00109         0.00106         0.00103         0.00100
--------------------------------------------------------------------------------------------------------------------------------------------------------


                                Table III-19--Light Truck CAFE Target Function Coefficients for Alternative PC3LT5 \472\
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               2027            2028            2029            2030            2031            2032
--------------------------------------------------------------------------------------------------------------------------------------------------------
a (mpg).................................................           56.55           59.53           62.66           65.96           69.43           73.09
b (mpg).................................................           34.00           35.79           37.67           39.65           41.74           43.94
c (gpm per s.f).........................................         0.00036         0.00034         0.00032         0.00030         0.00029         0.00028
d (gpm).................................................         0.00311         0.00295         0.00280         0.00266         0.00253         0.00240
--------------------------------------------------------------------------------------------------------------------------------------------------------

    These equations are represented graphically below:
    [GRAPHIC] [TIFF OMITTED] TP17AU23.059
    

[[Page 56270]]


[GRAPHIC] [TIFF OMITTED] TP17AU23.060

    Under this alternative, the MDPCS is as follows:

                 Table III-20--Alternative PC3LT5--Minimum Domestic Passenger Car Standard (MPG)
----------------------------------------------------------------------------------------------------------------
       2027               2028               2029               2030               2031               2032
----------------------------------------------------------------------------------------------------------------
           55.8               57.5               59.3               61.1               63.0               64.9
----------------------------------------------------------------------------------------------------------------


d. Alternative PC6LT8

    Alternative PC6LT8 would increase CAFE stringency by 6 percent per 
year, year over year, for MYs 2027-2032 passenger cars, and by 8 
percent per year, year over year, for MYs 2027-2032 light trucks.

                               Table III-21--Passenger Car CAFE Target Function Coefficients for Alternative PC6LT8 \473\
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               2027            2028            2029            2030            2031            2032
--------------------------------------------------------------------------------------------------------------------------------------------------------
a (mpg).................................................           71.23           75.77           80.61           85.75           91.23           97.05
b (mpg).................................................           53.29           56.69           60.31           64.16           68.26           72.61
c (gpm per s.f).........................................         0.00032         0.00030         0.00028         0.00026         0.00025         0.00023
d (gpm).................................................         0.00112         0.00106         0.00099         0.00093         0.00088         0.00083
--------------------------------------------------------------------------------------------------------------------------------------------------------


                                Table III-22--Light Truck CAFE Target Function Coefficients for Alternative PC6LT8 \474\
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               2027            2028            2029            2030            2031            2032
--------------------------------------------------------------------------------------------------------------------------------------------------------
a (mpg).................................................           58.40           63.48           69.00           74.99           81.52           88.60
b (mpg).................................................           35.11           38.16           41.48           45.09           49.01           53.27
c (gpm per s.f).........................................         0.00034         0.00032         0.00029         0.00027         0.00025         0.00023
d (gpm).................................................         0.00301         0.00277         0.00255         0.00234         0.00216         0.00198
--------------------------------------------------------------------------------------------------------------------------------------------------------

    These equations are represented graphically below:
---------------------------------------------------------------------------

    \473\ The Passenger Car Function Coefficients `a',`b',`c',and 
`d' are defined in Draft TSD Chapter 1.2.1.
    \474\ The Light Truck Function Coefficients `a',`b',`c',and `d' 
are defined in Draft TSD Chapter 1.2.1.

---------------------------------------------------------------------------

[[Page 56271]]

[GRAPHIC] [TIFF OMITTED] TP17AU23.061

[GRAPHIC] [TIFF OMITTED] TP17AU23.062


[[Page 56272]]


    Under this alternative, the MDPCS is as follows:

                 Table III-23--Alternative PC6LT8--Minimum Domestic Passenger Car Standard (MPG)
----------------------------------------------------------------------------------------------------------------
       2027               2028               2029               2030               2031               2032
----------------------------------------------------------------------------------------------------------------
           57.5               61.2               65.1               69.3               73.7               78.4
----------------------------------------------------------------------------------------------------------------

3. Action Alternatives for MYs 2030-2035 Heavy-Duty Pickups and Vans
    In addition to the No-Action Alternative, NHTSA has considered 
three action alternatives for HDPUVs, each of which is more stringent 
than the No-Action Alternative during the rulemaking time frame. While 
each of the Action Alternatives described below would establish 
increases in stringency from MY 2030 through MY 2035, NHTSA also 
requests comment on a scenario where these Action Alternatives would 
extend only through MY 2032, which coincides with the timeframe of the 
EPA proposed GHG standards for this vehicle segment.\475\ These action 
alternatives are specified below.
---------------------------------------------------------------------------

    \475\ See 87 FR 29242-29243 (May 5, 2023). NHTSA recognizes that 
the Draft EIS accompanying this proposal examines only regulatory 
alternatives for HDPUVs in which standards cover MYs 2030-2035.
---------------------------------------------------------------------------

a. Alternative HDPUV4
    Alternative HDPUV4 would increase HDPUV standard stringency by 4 
percent per year for MYs 2030-2035 HDPUVs. NHTSA included this 
alternative in order to evaluate a possible balancing of statutory 
factors in which cost-effectiveness outweighed all other factors. The 
four-wheel drive coefficient is maintained at 500 (coefficient `a') and 
the weighting multiplier coefficient is maintained at 0.75 (coefficient 
`b').
---------------------------------------------------------------------------

    \476\ In the CAFE Model, these are linear work-factor-based 
functions where coefficients e and f are for diesels, BEVs and 
FCEVs. See Draft TSD Chapter 1.2.1.

                               Table III-24--HDPUV (CI Vehicle) Target Function Coefficients for Alternative HDPUV4 \476\
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               2030            2031            2032            2033            2034            2035
--------------------------------------------------------------------------------------------------------------------------------------------------------
e.......................................................       0.0003281       0.0003150       0.0003024       0.0002903       0.0002787       0.0002675
f.......................................................           2.528           2.427           2.330           2.236           2.147           2.061
--------------------------------------------------------------------------------------------------------------------------------------------------------


                               Table III-25--HDPUV (SI Vehicle) Target Function Coefficients for Alternative HDPUV4 \477\
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               2030            2031            2032            2033            2034            2035
--------------------------------------------------------------------------------------------------------------------------------------------------------
c.......................................................       0.0003986       0.0003826       0.0003673       0.0003526       0.0003385       0.0003250
d.......................................................           3.068           2.945           2.828           2.715           2.606           2.502
--------------------------------------------------------------------------------------------------------------------------------------------------------

    These equations are represented graphically below:
---------------------------------------------------------------------------

    \477\ In the CAFE Model, these are linear work-factor-based 
functions where coefficients c and d are for gasoline, CNG, strong 
hybrid vehicles and PHEVs. See Draft TSD Chapter 1.2.1.

---------------------------------------------------------------------------

[[Page 56273]]

[GRAPHIC] [TIFF OMITTED] TP17AU23.063

[GRAPHIC] [TIFF OMITTED] TP17AU23.064

b. Alternative HDPUV10--Preferred Alternative
    Alternative HDPUV10 would increase HDPUV standard stringency by 10 
percent per year for MYs 2030-2035 HDPUVs. The four-wheel drive 
coefficient is maintained at 500 (coefficient `a') and the weighting 
multiplier coefficient is maintained at 0.75 (coefficient `b').

[[Page 56274]]



                               Table III-26--HDPUV (CI Vehicle) Target Function Coefficients for Alternative HDPUV10 \478\
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               2030            2031            2032            2033            2034            2035
--------------------------------------------------------------------------------------------------------------------------------------------------------
e.......................................................       0.0003076       0.0002769       0.0002492       0.0002243       0.0002018       0.0001816
f.......................................................           2.370           2.133           1.919           1.728           1.555           1.399
--------------------------------------------------------------------------------------------------------------------------------------------------------


                               Table III-27--HDPUV (SI Vehicle) Target Function Coefficients for Alternative HDPUV10 \479\
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               2030            2031            2032            2033            2034            2035
--------------------------------------------------------------------------------------------------------------------------------------------------------
c.......................................................       0.0003737       0.0003363       0.0003027       0.0002724       0.0002452       0.0002207
d.......................................................           2.876           2.589           2.330           2.097           1.887           1.698
--------------------------------------------------------------------------------------------------------------------------------------------------------

    These equations are represented graphically below:
---------------------------------------------------------------------------

    \478\ In the CAFE Model, these are linear work-factor-based 
functions where coefficients e and f are for diesels, BEVs and 
FCEVs. See Draft TSD Chapter 1.2.1.
    \479\ In the CAFE Model, these are linear work-factor-based 
functions where coefficients c and d are for gasoline, CNG, strong 
hybrid vehicles and PHEVs. See Draft TSD Chapter 1.2.1.
[GRAPHIC] [TIFF OMITTED] TP17AU23.065

[GRAPHIC] [TIFF OMITTED] TP17AU23.066


[[Page 56275]]


c. Alternative HDPUV14
    Alternative HDPUV14 would increase HDPUV standard stringency by 14 
percent per year for MYs 2030-2035 HDPUVs. The four-wheel drive 
coefficient is maintained at 500 (coefficient `a') and the weighting 
multiplier coefficient is maintained at 0.75 (coefficient `b').
---------------------------------------------------------------------------

    \480\ In the CAFE Model, these are linear work-factor-based 
functions where coefficients e and f are for diesels, BEVs and 
FCEVs. See Draft TSD Chapter 1.2.1.
    \481\ In the CAFE Model, these are linear work-factor-based 
functions where coefficients c and d are for gasoline, CNG, strong 
hybrid vehicles and PHEVs. See Draft TSD Chapter 1.2.1.

                               Table III-28--HDPUV (CI Vehicle) Target Function Coefficients for Alternative HDPUV14 \480\
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               2030            2031            2032            2033            2034            2035
--------------------------------------------------------------------------------------------------------------------------------------------------------
e.......................................................       0.0002939       0.0002528       0.0002174       0.0001870       0.0001608       0.0001383
f.......................................................           2.264           1.947           1.675           1.440           1.239           1.065
--------------------------------------------------------------------------------------------------------------------------------------------------------


                               Table III-29--HDPUV (SI Vehicle) Target Function Coefficients for Alternative HDPUV14 \481\
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                               2030            2031            2032            2033            2034            2035
--------------------------------------------------------------------------------------------------------------------------------------------------------
c.......................................................       0.0003571       0.0003071       0.0002641       0.0002271       0.0001953       0.0001680
d.......................................................           2.749           2.364           2.033           1.748           1.503           1.293
--------------------------------------------------------------------------------------------------------------------------------------------------------

    These equations are represented graphically below:
    [GRAPHIC] [TIFF OMITTED] TP17AU23.067
    

[[Page 56276]]


[GRAPHIC] [TIFF OMITTED] TP17AU23.068

BILLING CODE 4910-59-C

IV. Effects of the Regulatory Alternatives

A. Effects on Vehicle Manufacturers

1. Passenger Cars and Light Trucks
    Each regulatory alternative considered in this proposal, aside from 
the No-Action Alternative, would increase the stringency of both 
passenger car and light truck CAFE standards during MYs 2027-2032 (with 
MY 2032 being an augural standard). To estimate the potential effects 
of each of these alternatives, NHTSA has, as with all recent 
rulemakings, assumed that standards would continue unchanged after the 
last model year to be covered by proposed CAFE targets (in this case an 
augural MY, 2032). NHTSA recognizes that it is possible that the size 
and composition of the fleet (i.e., in terms of distribution across the 
range of vehicle footprints) could change over time, affecting the 
average fuel economy requirements under both the passenger car and 
light truck standards, and for the overall fleet. If fleet changes 
ultimately differ from NHTSA's projections, average requirements would 
differ from NHTSA's projections.
    Following are the estimated required average fuel economy values 
for the passenger car, light truck, and total fleets for each action 
alternative that NHTSA considered alongside values for the No-Action 
alternative.

                                     Table IV-1--Estimated Required Average Fuel Economy (MPG), by Regulatory Fleet
--------------------------------------------------------------------------------------------------------------------------------------------------------
               Model year                      2022            2027            2028            2029            2030            2031            2032
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                      Passenger Car
--------------------------------------------------------------------------------------------------------------------------------------------------------
No Action...............................            44.1            58.8            58.8            58.8            58.8            58.8            58.8
PC1LT3..................................            44.1            59.4            60.0            60.6            61.2            61.8            62.4
PC2LT4..................................            44.1            60.0            61.2            62.5            63.7            65.1            66.4
PC3LT5..................................            44.1            60.6            62.5            64.4            66.4            68.5            70.6
PC6LT8..................................            44.1            62.5            66.5            70.8            75.3            80.1            85.2
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                       Light Truck
--------------------------------------------------------------------------------------------------------------------------------------------------------
No Action...............................            32.1            42.6            42.6            42.6            42.6            42.6            42.6
PC1LT3..................................            32.1            43.9            45.3            46.7            48.1            49.6            51.2
PC2LT4..................................            32.1            44.4            46.2            48.2            50.2            52.2            54.4
PC3LT5..................................            32.1            44.9            47.2            49.7            52.3            55.1            58.0
PC6LT8..................................            32.1            46.3            50.3            54.7            59.5            64.6            70.3
--------------------------------------------------------------------------------------------------------------------------------------------------------


                                    Table IV-2--Estimated Required Average Fuel Economy (MPG), Total Light-Duty Fleet
--------------------------------------------------------------------------------------------------------------------------------------------------------
               Model year                      2022            2027            2028            2029            2030            2031            2032
--------------------------------------------------------------------------------------------------------------------------------------------------------
No Action...............................            35.8            46.7            46.7            46.7            46.7            46.7            46.7
PC1LT3..................................            35.8            47.9            49.1            50.3            51.6            53.0            54.3
PC2LT4..................................            35.8            48.4            50.1            51.9            53.8            55.7            57.8
PC3LT5..................................            35.8            48.9            51.2            53.5            56.1            58.7            61.5
PC6LT8..................................            35.8            50.5            54.5            58.9            63.7            68.9            74.5
--------------------------------------------------------------------------------------------------------------------------------------------------------


[[Page 56277]]

    Manufacturers do not always comply exactly with each CAFE standard 
in each MY. To date, some manufacturers have tended to regularly exceed 
one or both requirements.\482\ Many manufacturers make use of EPCA's 
provisions allowing CAFE compliance credits to be applied when a 
fleet's CAFE level falls short of the corresponding requirement in a 
given MY.\483\ Some manufacturers have paid civil penalties (i.e., 
fines) required under EPCA when a fleet falls short of a standard in a 
given MY and the manufacturer lacks compliance credits sufficient to 
address the compliance shortfall. As discussed in the accompanying PRIA 
and Draft TSD, NHTSA simulates manufacturers' responses to each 
alternative given a wide range of input estimates (e.g., technology 
cost and efficacy, fuel prices), and, per EPCA requirements, setting 
aside the potential that any manufacturer would respond to CAFE 
standards in MYs 2027-2032 by applying CAFE compliance credits or 
considering the fuel economy attributable to alternative fuel 
sources.\484\ Many of these inputs are subject to uncertainty, and, in 
any event, as in all CAFE rulemakings, NHTSA's analysis simply 
illustrates one set of ways manufacturers could potentially respond to 
each regulatory alternative. For this proposal, NHTSA estimates that 
manufacturers' responses to standards defining each alternative could 
lead average fuel economy levels to increase through MY 2032, as shown 
in the following tables.
---------------------------------------------------------------------------

    \482\ Overcompliance can be the result of multiple factors 
including projected ``inheritance'' of technologies (e.g., changes 
to engines shared across multiple vehicle model/configurations) 
applied in earlier MYs, future technology cost reductions (e.g., 
decreased techology costs due to learning), and changes in fuel 
prices that affect technology cost effectiveness. As in all past 
rulemakings over the last decade, NHTSA assumes that beyond fuel 
economy improvements necessitated by CAFE standards, EPA-GHG 
standards, and ZEV mandates, manufacturers may also improve fuel 
economy via technologies that would pay for themselves within the 
first 30 months of vehicle operation.
    \483\ For additional detail on the creation and use of 
compliance credits, see Chapters 1.1 and 2.2.2.3 of the accompanying 
Draft TSD.
    \484\ In the case of battery-electric vehicles, this means BEVs 
will not be built in response to the proposed standards. For plug-in 
hybrid vehicles, this means only the gasoline-powered operation 
(i.e., non-electric fuel economy, or charge sustaining mode 
operation only) is considered when selecting technology to meet the 
proposed standards.

                                     Table IV-3--Estimated Achieved Average Fuel Economy (MPG), by Regulatory Fleet
--------------------------------------------------------------------------------------------------------------------------------------------------------
               Model year                      2022            2027            2028            2029            2030            2031            2032
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                      Passenger Car
--------------------------------------------------------------------------------------------------------------------------------------------------------
No Action...............................            47.1            63.0            64.4            65.8            67.5            69.1            70.3
PC1LT3..................................            47.1            63.2            64.8            66.7            68.4            70.3            71.5
PC2LT4..................................            47.1            63.5            65.3            67.5            69.3            71.3            72.8
PC3LT5..................................            47.1            63.5            65.8            68.1            70.5            73.0            74.8
PC6LT8..................................            47.1            63.6            67.5            71.1            74.8            78.9            83.6
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                       Light Truck
--------------------------------------------------------------------------------------------------------------------------------------------------------
No Action...............................            31.9            43.4            44.1            45.2            46.2            47.3            48.1
PC1LT3..................................            31.9            44.2            45.5            47.2            48.4            50.2            51.5
PC2LT4..................................            31.9            44.2            45.7            47.5            49.0            50.9            52.4
PC3LT5..................................            31.9            44.3            46.0            47.9            49.6            51.7            53.5
PC6LT8..................................            31.9            44.3            46.1            48.3            50.3            52.6            55.2
--------------------------------------------------------------------------------------------------------------------------------------------------------


                                    Table IV-4--Estimated Achieved Average Fuel Economy (MPG), Total Light-Duty Fleet
--------------------------------------------------------------------------------------------------------------------------------------------------------
               Model year                      2022            2027            2028            2029            2030            2031            2032
--------------------------------------------------------------------------------------------------------------------------------------------------------
No Action...............................            36.4            48.2            49.0            50.2            51.3            52.6            53.6
PC1LT3..................................            36.4            48.9            50.2            51.9            53.3            55.2            56.5
PC2LT4..................................            36.4            49.0            50.5            52.4            54.0            56.0            57.6
PC3LT5..................................            36.4            49.0            50.8            52.8            54.7            57.0            58.9
PC6LT8..................................            36.4            49.0            51.2            53.7            56.1            58.9            62.0
--------------------------------------------------------------------------------------------------------------------------------------------------------

    While these increases in average fuel economy reflect currently 
estimated changes in the composition of the fleet (i.e., the relative 
shares of passenger cars and light trucks), they result almost wholly 
from the projected application of fuel-saving technology. As mentioned 
above, NHTSA's analysis merely illustrates one set of ways 
manufacturers could potentially respond to each regulatory alternative. 
Manufacturers' actual responses will almost assuredly differ from 
NHTSA's current simulations.
    The SHEV share of the LD fleet initially (i.e., in MY 2022) is 
relatively low, but increases to approximately 25 percent by the 
beginning of the proposed regulatory period. Across action 
alternatives, SHEV penetration rates increase as alternatives become 
more stringent, in both the passenger car and light truck fleets. SHEVs 
are estimated to make up a larger portion of light truck fleet than 
passenger car fleet across MYs 2027-2032. While their market shares do 
not increase to the

[[Page 56278]]

levels of SHEVs, PHEVs make up approximately 10 percent of the 
estimated light truck fleet in the three most stringent action 
alternatives.

                            Table IV-5--Estimated Strong Hybrid Electric Vehicle (SHEV) Penetration Rate, by Regulatory Fleet
--------------------------------------------------------------------------------------------------------------------------------------------------------
               Model year                      2022            2027            2028            2029            2030            2031            2032
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                      Passenger Car
--------------------------------------------------------------------------------------------------------------------------------------------------------
No Action...............................             5.4            13.0            13.5            13.5            13.0            12.7            12.8
PC1LT3..................................             5.4            14.3            15.7            16.0            15.4            16.1            16.1
PC2LT4..................................             5.4            15.5            17.5            20.7            20.6            20.6            20.6
PC3LT5..................................             5.4            15.5            18.6            22.1            23.2            24.8            25.1
PC6LT8..................................             5.4            15.5            27.0            33.2            37.8            44.1            49.8
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                       Light Truck
--------------------------------------------------------------------------------------------------------------------------------------------------------
No Action...............................             7.8            30.1            30.8            31.6            30.8            26.9            26.2
PC1LT3..................................             7.8            33.3            39.3            41.4            41.4            40.0            40.7
PC2LT4..................................             7.8            33.1            39.5            42.2            43.4            42.6            44.6
PC3LT5..................................             7.8            33.1            41.3            44.1            46.6            45.9            48.2
PC6LT8..................................             7.8            33.4            41.4            46.0            47.1            46.8            51.6
--------------------------------------------------------------------------------------------------------------------------------------------------------


                          Table IV-6--Estimated Strong Hybrid Electric Vehicle (SHEV) Penetration Rate, Total Light-Duty Fleet
--------------------------------------------------------------------------------------------------------------------------------------------------------
               Model year                      2022            2027            2028            2029            2030            2031            2032
--------------------------------------------------------------------------------------------------------------------------------------------------------
No Action...............................             6.9            24.6            25.3            25.9            25.1            22.3            21.9
PC1LT3..................................             6.9            27.3            31.9            33.5            33.2            32.3            32.8
PC2LT4..................................             6.9            27.5            32.6            35.5            36.2            35.6            36.9
PC3LT5..................................             6.9            27.5            34.1            37.2            39.2            39.2            40.7
PC6LT8..................................             6.9            27.7            36.9            42.0            44.2            45.9            51.0
--------------------------------------------------------------------------------------------------------------------------------------------------------


                           Table IV-7--Estimated Plug-in Hybrid-Electric Vehicle (PHEV) Penetration Rate, by Regulatory Fleet
--------------------------------------------------------------------------------------------------------------------------------------------------------
               Model year                      2022            2027            2028            2029            2030            2031            2032
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                      Passenger Car
--------------------------------------------------------------------------------------------------------------------------------------------------------
No Action...............................             1.2             0.0             0.0             0.0             0.0             0.0             0.0
PC1LT3..................................             1.2             0.0             0.0             0.0             0.0             0.0             0.0
PC2LT4..................................             1.2             0.0             0.0             0.0             0.0             0.0             0.0
PC3LT5..................................             1.2             0.0             0.0             0.0             0.1             0.1             0.1
PC6LT8..................................             1.2             0.0             0.0             0.2             0.9             1.1             1.4
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                       Light Truck
--------------------------------------------------------------------------------------------------------------------------------------------------------
No Action...............................             2.0             0.6             0.6             1.1             1.1             4.3             4.3
PC1LT3..................................             2.0             2.6             2.9             4.3             4.6             7.7             9.1
PC2LT4..................................             2.0             2.9             3.6             5.7             6.1             9.4            11.0
PC3LT5..................................             2.0             2.9             2.9             5.3             5.6             9.3            11.6
PC6LT8..................................             2.0             2.9             3.0             6.4             9.4            13.6            16.8
--------------------------------------------------------------------------------------------------------------------------------------------------------


                          Table IV-8--Estimated Plug-in Hybrid-Electric Vehicle (PHEV) Penetration Rate, Total Light-Duty Fleet
--------------------------------------------------------------------------------------------------------------------------------------------------------
               Model year                      2022            2027            2028            2029            2030            2031            2032
--------------------------------------------------------------------------------------------------------------------------------------------------------
No Action...............................             1.7             0.4             0.4             0.8             0.8             2.9             2.9
PC1LT3..................................             1.7             1.8             2.0             2.9             3.1             5.2             6.2
PC2LT4..................................             1.7             2.0             2.5             3.9             4.1             6.4             7.5
PC3LT5..................................             1.7             2.0             2.0             3.6             3.9             6.3             7.9
PC6LT8..................................             1.7             2.0             2.1             4.5             6.8             9.6            11.8
--------------------------------------------------------------------------------------------------------------------------------------------------------

    Due to the statutory constraints imposed on the analysis by EPCA 
that exclude consideration of AFVs, BEVs are not a compliance option 
during the standard setting years. As seen in Table IV-9 and Table IV-
10, BEV penetration increases across MYs in the No-Action Alternative. 
During the standard setting years, BEVs are only added to account for 
manufacturers' expected response to state ZEV mandates. In MYs outside 
of the standard setting years, BEVs may be added to the No-Action 
Alternative if they are profit-maximizing for manufacturers to produce 
for reasons other than the CAFE standards; however, the number of 
vehicles added in the non-standard-setting years on this basis are very 
minimal and expected compliance with state ZEV mandates remains 
responsible for the majority of

[[Page 56279]]

BEVs produced during those years. The action alternatives show nearly 
the same BEV penetration rates as the No-Action Alternative, although 
in some cases there is a slight deviation, despite no new BEVs entering 
the fleet, due to rounding in some MYs where fewer vehicles are being 
sold in response to the proposed standards and altering fleet shares.

                               Table IV-9--Estimated Battery Electric Vehicle (BEV) Penetration Rate, by Regulatory Fleet
--------------------------------------------------------------------------------------------------------------------------------------------------------
               Model year                      2022            2027            2028            2029            2030            2031            2032
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                      Passenger Car
--------------------------------------------------------------------------------------------------------------------------------------------------------
No Action...............................            12.4            32.0            33.4            35.5            38.1            40.4            42.2
PC1LT3..................................            12.4            32.0            33.4            35.6            38.1            40.5            42.2
PC2LT4..................................            12.4            32.0            33.4            35.6            38.1            40.5            42.2
PC3LT5..................................            12.4            32.0            33.4            35.6            38.1            40.5            42.2
PC6LT8..................................            12.4            32.0            33.4            35.6            38.1            40.5            42.2
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                       Light Truck
--------------------------------------------------------------------------------------------------------------------------------------------------------
No Action...............................             0.7            17.1            18.5            20.4            22.9            25.5            27.5
PC1LT3..................................             0.7            17.2            18.5            20.4            23.0            25.5            27.5
PC2LT4..................................             0.7            17.2            18.5            20.4            23.0            25.5            27.5
PC3LT5..................................             0.7            17.2            18.5            20.5            23.0            25.5            27.5
PC6LT8..................................             0.7            17.2            18.5            20.5            23.0            25.5            27.5
--------------------------------------------------------------------------------------------------------------------------------------------------------


                             Table IV-10--Estimated Battery Electric Vehicle (BEV) Penetration Rate, Total Light-Duty Fleet
--------------------------------------------------------------------------------------------------------------------------------------------------------
               Model year                      2022            2027            2028            2029            2030            2031            2032
--------------------------------------------------------------------------------------------------------------------------------------------------------
No Action...............................             5.2            21.9            23.2            25.2            27.7            30.3            32.3
PC1LT3..................................             5.2            21.9            23.2            25.2            27.8            30.3            32.3
PC2LT4..................................             5.2            21.9            23.2            25.2            27.8            30.3            32.3
PC3LT5..................................             5.2            21.9            23.2            25.2            27.8            30.3            32.3
PC6LT8..................................             5.2            21.9            23.2            25.2            27.7            30.3            32.3
--------------------------------------------------------------------------------------------------------------------------------------------------------

    The PRIA provides a longer summary of NHTSA's estimates of 
manufacturers' potential application of fuel-saving technologies 
(including other types of technologies, such as advanced transmissions, 
aerodynamic improvements, and reduced vehicle mass) in response to each 
regulatory alternative. Appendices I and II of the accompanying PRIA 
provide more detailed and comprehensive results, and the underlying 
CAFE Model output files provide all the information used to construct 
these estimates, including the specific combination of technologies 
estimated to be applied to every vehicle model/configuration in each of 
MYs 2022-2050.
    NHTSA's analysis shows manufacturers' regulatory costs for 
compliance with the proposed CAFE standards, combined with existing EPA 
GHG standards \485\ and state ZEV mandates,\486\ not surprisingly 
increasing more under the more stringent alternatives as more fuel-
saving technologies would be required. NHTSA estimates manufacturers' 
cumulative regulatory costs across MYs 2027-2032 could total $187b 
under the No-Action Alternative, and an additional $45b, $63b, $91b, 
and $177b under alternatives PC1LT3, PC2LT4, PC3LT5, and PC6LT8, 
respectively, when accounting for fuel-saving technologies added under 
the simulation for each regulatory alternative (including AC 
improvements and other off-cycle technologies), and also accounting for 
CAFE civil penalties that NHTSA estimates some manufacturers could 
elect to pay rather than achieving full compliance with the proposed 
CAFE targets in some MYs in some fleets. The table below shows how 
these costs are estimated to vary among manufacturers, accounting for 
differences in the quantities of vehicles produced for sale in the U.S. 
Appendices I and II of the accompanying PRIA present results separately 
for each manufacturer's passenger car and light truck fleets in each MY 
under each regulatory alternative, and the underlying CAFE Model output 
files also show results specific to manufacturers' domestic and 
imported car fleets.
---------------------------------------------------------------------------

    \485\ EPA's proposed MY 2027-2032 CO2 standards were 
not modeled for this NPRM combined with CAFE and FE new standards.
    \486\ NHTSA does not model state GHG programs outside of ZEV. 
See Chapter 2.2.2.6 of the accompanying Draft TSD for details about 
how NHTSA models anticipated manufacturer compliance with 
California's ZEV program.

                        Table IV-11--Estimated Cumulative Costs ($b) During MYs 2027-2032
----------------------------------------------------------------------------------------------------------------
                                                                       Relative to no action
          Manufacturer               No action   ---------------------------------------------------------------
                                                      PC1LT3          PC2LT4          PC3LT5          PC6LT8
----------------------------------------------------------------------------------------------------------------
BMW.............................             4.2             0.2             0.5             0.9             2.9
Ford............................            28.3             8.2            11.1            13.0            24.3
General Motors..................            26.7            15.1            17.5            22.3            33.3
Honda...........................            13.5             1.1             1.7             4.9            12.8
Hyundai.........................             9.5             8.6            10.4            11.8            17.5

[[Page 56280]]

 
Kia.............................             4.2             3.3             6.3             8.6            12.9
Jaguar--Land Rover..............             0.9             0.3             0.5             0.6             1.1
Karma...........................             0.0             0.0             0.0             0.0             0.0
Lucid...........................             0.0             0.0             0.0             0.0             0.0
Mazda...........................             2.6             0.0             0.1             5.7             8.7
Mercedes-Benz...................             3.8             0.3             0.6             1.0             2.7
Mitsubishi......................             1.2             0.3             0.4             0.8             1.5
Nissan..........................            14.8             1.2             2.7             3.9             9.2
Stellantis......................            31.5             4.8             8.5            11.3            25.0
Subaru..........................            11.3             0.0             0.0             0.0             2.9
Tesla...........................             0.0             0.0             0.0             0.0             0.0
Toyota..........................            25.3            -0.1             0.1             2.6            14.6
Volvo...........................             0.8             0.3             0.4             0.6             1.5
VWA.............................             8.6             1.2             2.0             2.9             6.7
                                 -------------------------------------------------------------------------------
    Industry Total..............           187.3            44.9            62.9            90.8           177.4
----------------------------------------------------------------------------------------------------------------

    As discussed in the TSD, these estimates reflect technology cost 
inputs that, in turn, reflect a ``markup'' factor that includes 
manufacturers' profits. In other words, if costs to manufacturers are 
reflected in vehicle price increases, NHTSA estimates that the average 
costs to new vehicle purchasers could increase through MY 2032 as 
summarized in Table IV-12 and Table IV-13.

                                   Table IV-12--Estimated Average Per-Vehicle Regulatory Cost ($), by Regulatory Fleet
--------------------------------------------------------------------------------------------------------------------------------------------------------
               Model year                      2022            2027            2028            2029            2030            2031            2032
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                      Passenger Car
--------------------------------------------------------------------------------------------------------------------------------------------------------
No Action...............................             159           1,462           1,412           1,389           1,386           1,383           1,312
PC1LT3..................................             159           1,782           1,861           1,867           1,847           1,817           1,731
PC2LT4..................................             159           1,847           1,966           2,087           2,069           2,033           1,966
PC3LT5..................................             159           1,964           2,136           2,373           2,391           2,441           2,517
PC6LT8..................................             159           2,166           2,616           3,175           3,671           4,039           4,393
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                       Light Truck
--------------------------------------------------------------------------------------------------------------------------------------------------------
No Action...............................             125           2,248           2,239           2,270           2,302           2,484           2,438
PC1LT3..................................             125           2,555           2,696           2,805           2,886           3,078           3,125
PC2LT4..................................             125           2,609           2,826           2,992           3,122           3,369           3,502
PC3LT5..................................             125           2,732           2,990           3,213           3,441           3,740           4,232
PC6LT8..................................             125           2,896           3,360           3,922           4,628           5,281           6,118
--------------------------------------------------------------------------------------------------------------------------------------------------------


                                 Table IV-13--Estimated Average Per-Vehicle Regulatory Cost ($), Total Light-Duty Fleet
--------------------------------------------------------------------------------------------------------------------------------------------------------
               Model year                      2022            2027            2028            2029            2030            2031            2032
--------------------------------------------------------------------------------------------------------------------------------------------------------
No Action...............................             138           1,998           1,977           1,993           2,012           2,132           2,077
PC1LT3..................................             138           2,309           2,432           2,510           2,558           2,676           2,678
PC2LT4..................................             138           2,367           2,555           2,708           2,790           2,942           3,008
PC3LT5..................................             138           2,488           2,720           2,950           3,110           3,326           3,679
PC6LT8..................................             138           2,664           3,126           3,689           4,328           4,886           5,562
--------------------------------------------------------------------------------------------------------------------------------------------------------

    Table IV-14 shows how these costs could vary among manufacturers, 
suggesting that disparities could increase as the stringency of 
standards increases.

       Table IV-14--Average Manufacturer Per-Vehicle Costs by Alternative, Total Light-Duty Fleet, MY 2032
                                                       [$]
----------------------------------------------------------------------------------------------------------------
          Manufacturer               No action        PC1LT3          PC2LT4          PC3LT5          PC6LT8
----------------------------------------------------------------------------------------------------------------
BMW.............................           2,066           2,150           2,357           2,646           4,529
Ford............................           2,384           3,165           3,720           4,183           6,327
General Motors..................           2,422           4,095           4,469           5,528           7,398

[[Page 56281]]

 
Honda...........................           1,467           1,565           1,701           2,069           3,967
Hyundai.........................           1,786           3,312           3,703           5,390           7,632
Kia.............................           1,151           2,165           3,387           5,888           7,856
Jaguar--Land Rover..............           1,819           2,657           3,189           3,741           5,697
Karma...........................          -3,543          -3,543          -3,543          -3,543          -3,543
Lucid...........................             -62             -62             -62             -62             -62
Mazda...........................           2,303           2,330           2,366           7,266          11,798
Mercedes-Benz...................           2,470           2,653           2,836           3,247           5,262
Mitsubishi......................           1,421           1,969           2,057           3,201           5,088
Nissan..........................           2,363           2,558           2,902           3,203           5,010
Stellantis......................           2,956           3,807           4,388           4,892           7,459
Subaru..........................           2,384           2,384           2,384           2,389           3,292
Tesla...........................              13              13              13              13              13
Toyota..........................           1,794           1,794           1,867           2,166           3,679
Volvo...........................           1,202           1,517           1,768           2,172           4,068
VWA.............................           2,249           2,635           2,913           3,360           5,346
                                 -------------------------------------------------------------------------------
    Industry Average............           2,077           2,678           3,008           3,679           5,562
----------------------------------------------------------------------------------------------------------------

    NHTSA estimates that although projected fuel savings under the more 
stringent regulatory alternatives could tend to increase new vehicle 
sales, this tendency could be outweighed by the opposing response to 
higher prices, such that new vehicle sales could decline slightly under 
the more stringent alternatives. The magnitude of these fuel savings 
and vehicle price increases depends on manufacturer compliance 
decisions, especially technology application. In the event that 
manufacturers select technologies with lower prices and/or higher fuel 
economy improvements, vehicle sales effects could differ. Draft TSD 
Chapter 4.2.1.2 discusses NHTSA's approach to estimating new vehicle 
sales, including NHTSA's estimate that new vehicle sales could recover 
from 2020's aberrantly low levels.
[GRAPHIC] [TIFF OMITTED] TP17AU23.069

    While these slight reductions in new vehicle sales tend to reduce 
projected automobile industry labor by small margins, NHTSA estimates 
that the cost increases could reflect an underlying increase in 
employment to produce additional fuel-saving technology, such that 
automobile industry labor could remain about the same under each of the 
four regulatory alternatives.

[[Page 56282]]

[GRAPHIC] [TIFF OMITTED] TP17AU23.070

    The accompanying TSD discusses NHTSA's approach to estimating 
automobile industry employment, and the accompanying PRIA Chapter 8.2 
(and its Appendices I and II) and CAFE Model output files provide more 
detailed results of NHTSA's LD analysis.
2. Heavy-Duty Pickups and Vans
    NHTSA is proposing an increase in HDPUV fuel efficiency standards 
for MYs 2030-2035 relative to the existing standards set in 2016. 
Unlike the LD CAFE program, NHTSA may consider AFVs when setting 
maximum feasible average standards for HDPUVs. Additionally, for 
purposes of calculating average fuel efficiency for HDPUVs, NHTSA 
considers EVs, fuel cell vehicles, and the proportion of electric 
operation of EVs and PHEVs that is derived from electricity that is 
generated from sources that are not onboard the vehicle to have a fuel 
efficiency value of 0 grams/mile. Each of the regulatory alternatives 
that NHTSA is considering in this proposal would increase the 
stringency of fuel efficiency standards for HDPUVs starting in MY 2030, 
with increases each year through MY 2035.
    NHTSA recognizes that it is possible that the size and composition 
of the fleet (i.e., in terms of vehicle attributes that impact 
calculation of standards for averaging sets) could change over time, 
affecting the currently-estimated average fuel efficiency requirements. 
If fleet changes ultimately differ from NHTSA's projections, average 
requirements could, therefore, also differ from NHTSA's projections. 
The table below includes the estimated required average fuel efficiency 
values for the HDPUV fleet in each of the regulatory alternatives 
considered in this proposal.

                                 Table IV-15--Estimated Required Average Fuel Efficiency (gal/100mi), Total HDPUV Fleet
--------------------------------------------------------------------------------------------------------------------------------------------------------
               Model year                      2022            2030            2031            2032            2033            2034            2035
--------------------------------------------------------------------------------------------------------------------------------------------------------
No Action...............................           5.497           4.920           5.003           5.002           4.962           4.962           4.965
HDPUV4..................................           5.497           4.723           4.610           4.425           4.214           4.046           3.886
HDPUV10.................................           5.497           4.427           4.051           3.646           3.255           2.930           2.638
HDPUV14.................................           5.497           4.231           3.684           3.167           2.702           2.324           1.999
--------------------------------------------------------------------------------------------------------------------------------------------------------

    As with the LD program, manufacturers do not always comply exactly 
with each fuel efficiency standard in each MY. Manufacturers may bank 
credits from overcompliance in one year that may be used to cover 
shortfalls in up to five future MYs. Manufacturers may also carry 
forward credit deficits for up to three MYs. If a manufacturer is still 
unable to address the shortfall, NHTSA may assess civil penalties. As 
discussed in the accompanying PRIA and Draft TSD, NHTSA simulates 
manufacturers' responses to each alternative given a wide range of 
input estimates (e.g., technology cost and effectiveness, fuel prices, 
electrification technologies). For this proposed rule, NHTSA estimates 
that manufacturers' responses to standards defining each alternative 
could lead average fuel efficiency levels to improve through MY 2035, 
as shown in the following tables.

[[Page 56283]]



                                 Table IV-16--Estimated Achieved Average Fuel Efficiency (gal/100mi), Total HDPUV Fleet
--------------------------------------------------------------------------------------------------------------------------------------------------------
               Model year                      2022            2030            2031            2032            2033            2034            2035
--------------------------------------------------------------------------------------------------------------------------------------------------------
No Action...............................           5.528           3.270           2.771           2.766           2.229           2.229           2.225
HDPUV4..................................           5.528           3.269           2.769           2.764           2.227           2.227           2.223
HDPUV10.................................           5.528           3.266           2.764           2.759           2.160           2.157           2.153
HDPUV14.................................           5.528           3.265           2.632           2.627           1.972           1.972           1.878
--------------------------------------------------------------------------------------------------------------------------------------------------------

    Table IV-16 displays the projected achieved FE levels for the HDPUV 
fleet through MY 2035. Estimates of achieved levels are very similar 
between the No-Action Alternative and the least stringent Action 
Alternative. The narrow band of estimated average achieved levels in 
Table IV-16 is primarily due to several factors. Relative to the LD 
fleet, the HDPUV fleet (i) represents a smaller number of vehicles, 
(ii) includes fewer manufacturers, and (iii) is composed of a smaller 
number of manufacturer product lines. Technology choices for an 
individual manufacturer or individual product line can therefore have a 
large effect on fleet-wide average fuel efficiency. Second, Table IV-17 
shows that in the No-Action Alternative a substantial portion of the 
fleet converts to an electrified powertrain (e.g., SHEV, PHEV, BEV) 
between MY 2022 and MY 2030. This reduces the availability of, and need 
for,\487\ additional fuel efficiency improvement to meet more stringent 
standards.
---------------------------------------------------------------------------

    \487\ The need for further improvements in response to more 
stringent HDPUV standards is further reduced by the fact that NHTSA 
regulations currently grant BEVs (and the electric-only operation of 
PHEVs) an HDPUV compliance value of 0 gallons/100 miles, a 
significant adjustment on which NHTSA seeks comment elsewhere in 
this document.

                                 Table IV-17: Application Levels of Selected Technologies by Model Year for HDPUV Fleet
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                  2022     2030     2031     2032     2033     2034     2035     2036     2037     2038
                                                                  (%)      (%)      (%)      (%)      (%)      (%)      (%)      (%)      (%)      (%)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                               Technology Application Levels in the No-Action Alternative
--------------------------------------------------------------------------------------------------------------------------------------------------------
Strong Hybrid (all types).....................................        0       26       36       36       26       26       26       26       26       26
PHEV (all types)..............................................        0        0        4        4       13       13       13       13        9        9
BEV (all types)...............................................        6       31       35       35       41       41       41       41       45       45
Advanced Engines..............................................       40       21        7        6        3        3        3        3        3        3
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                           Technology Application Levels Relative to the No-Action Alternative
--------------------------------------------------------------------------------------------------------------------------------------------------------
HDPUV4:
Strong Hybrid (all types).....................................  .......        0        0        0        0        0        0        0        0        0
PHEV (all types)..............................................  .......        0        0        0        0        0        0        0        0        0
BEV (all types)...............................................  .......        0        0        0        0        0        0        0        0        0
Advanced Engines..............................................  .......        0        0        0        0        0        0        0        0        0
HDPUV10:
Strong Hybrid (all types).....................................  .......        0        0        0        0        0        0        0        0        0
PHEV (all types)..............................................  .......        0        0        0        1        1        1        1        1        1
BEV (all types)...............................................  .......        0        0        0        0        0        0        0        0        0
Advanced Engines..............................................  .......        0        0        0        1        2        2        2        2        2
HDPUV14:
Strong Hybrid (all types).....................................  .......        0        0        0        0        0        0        0        0        0
PHEV (all types)..............................................  .......        0        0        0        2        2        4        4        4        4
BEV (all types)...............................................  .......        0        3        3        3        3        3        3        3        3
Advanced Engines..............................................  .......        0       -2       -2        4        4       10       10       10       10
--------------------------------------------------------------------------------------------------------------------------------------------------------
Note: ``advanced engines'' represents the combined penetration of advanced cylinder deactivation, advanced turbo, variable compression ratio, high
  compression ratio, and diesel engines.\488\

    In line with the technology application trends above, regulatory 
costs do not differ by large amounts between the No-Action Alternative 
and the proposed action alternatives. Most of the differences in 
regulatory costs occur in the HDPUV14 alternative and are concentrated 
in a few manufacturers (e.g., Ford, GM), where the compliance modeling 
projects increases in PHEV, BEV, and advanced engine technologies.
---------------------------------------------------------------------------

    \488\ Specifically, this includes technologies with the 
following codes in the CAFE Model: TURBO0, TURBOE, TURBOD, TURBO1, 
TURBO2, ADEACD, ADEACS, HCR, HRCE, HCRD, VCR, VTG, VTGE, TURBOAD, 
ADSL, DSLI.

                 Table IV-18--Total Regulatory Cost by Manufacturer, MY 2022-2038 (in billions)
----------------------------------------------------------------------------------------------------------------
                                                                               Relative to no action
                  Manufacturer                       No action   -----------------------------------------------
                                                                      HDPUV4          HDPUV10         HDPUV14
----------------------------------------------------------------------------------------------------------------
Ford............................................           11.99            0.03            0.07            0.71
GM..............................................            0.66            0.00            0.86            4.02
Mercedes-Benz...................................            0.67            0.00            0.00            0.00

[[Page 56284]]

 
Nissan..........................................            1.17            0.00            0.00            0.00
Rivian..........................................            0.00            0.00            0.00            0.00
Stellantis......................................            4.61            0.00            0.00            0.00
                                                 ---------------------------------------------------------------
    Total.......................................           19.11            0.03            0.93            4.72
----------------------------------------------------------------------------------------------------------------

    On a per-vehicle basis, costs are minimal in HDPUV4 and increase 
with stringency and across MYs in HDPUV10 and HDPUV14.

                Table IV-19--Estimated Average Per-Vehicle Regulatory Cost ($), Total HDPUV Fleet
----------------------------------------------------------------------------------------------------------------
                                                     2022     2030     2031     2032     2033     2034     2035
----------------------------------------------------------------------------------------------------------------
No Action........................................        0    1,760    1,797    1,604    2,459    2,222    1,999
HDPUV4...........................................        0        3        3        3        4        4        4
HDPUV10..........................................        0        8       14       14      148      148      142
HDPUV14..........................................        0       33      352      334      563      540      697
----------------------------------------------------------------------------------------------------------------

    The relatively similar responses across action alternatives carry 
over to the analysis of the sales and labor market as well. The 
increase in sales in the No Action Alternative carries over to each of 
the action alternatives as well. The vehicle-level price increases 
noted above produces very small declines in overall sales.
[GRAPHIC] [TIFF OMITTED] TP17AU23.071

    These sales declines and limited additional technology application 
produce small decreases in labor utilization, as the sales effect 
ultimately outweighs job gains due to development and application of 
advanced technology. In aggregate, the alternatives represent less than 
half of a percentage point deviation from the No-Action Alternative.

[[Page 56285]]

[GRAPHIC] [TIFF OMITTED] TP17AU23.072

    The accompanying Draft TSD Chapter 6.2.5 discusses NHTSA's approach 
to estimating automobile industry employment, and the accompanying PRIA 
Chapter 8.3 (and its Appendix III) and CAFE Model output files provide 
more detailed results of NHTSA's HDPUV analysis.
B. Effects on Society
    NHTSA accounts for the effects on society of the standards by using 
a benefit/cost categories framework. These categories include private 
costs borne by manufacturers and consumers, SCs to society, which 
include external and Government costs, pertaining to emissions, 
congestion, noise, energy security, and safety, and all the benefits 
resulting from related categories in the form of savings, however they 
may occur across the presented alternatives. In this accounting 
framework, the CAFE Model records costs and benefits for particular MYs 
in the LD fleet but also reports these measures over the lifetime of 
the vehicle and allows for the accounting of costs and benefits across 
calendar years. Examining program effects through this lens illustrates 
the temporal differences in major cost and benefit components. In the 
HDPUV FE analysis, where the proposed standard would continue until 
otherwise amended, we report only the costs and benefits across 
calendar years.
1. Passenger Cars and Light Trucks
    We split effects on society into private costs, SCs, private 
benefits, and external benefits. Table IV-20 describes the costs and 
benefits of increasing CAFE standards in each alternative, as well as 
the party to which they accrue. Manufacturers are directly regulated 
under the program and incur additional production costs when they apply 
technology to their vehicle offerings in order to improve their fuel 
economy. We assume that those costs are fully passed through to new car 
and truck buyers in the form of higher prices. We also assume that any 
civil penalties paid by manufacturers for failing to comply with their 
CAFE standards are passed through to new car and truck buyers and are 
included in the sales price. However, those civil penalties are paid to 
the U.S. Treasury, where they currently fund the general business of 
government. As such, they are a transfer from new vehicle buyers to all 
U.S. citizens, who then benefit from the additional Federal revenue. 
While they are calculated in the analysis, and do influence consumer 
decisions in the marketplace, they do not directly contribute to the 
calculation of net benefits (and are omitted from the tables below).
    While incremental maintenance and repair costs and benefits would 
accrue to buyers of new cars and trucks affected by more stringent CAFE 
standards, we do not carry these impacts in the analysis. They are 
difficult to estimate but represent real costs (and potential benefits 
in the case of AFVs that require less frequent maintenance events). 
They may be included in future analyses as data become available to 
evaluate lifetime maintenance impacts. This analysis assumes that 
drivers of new vehicles internalize 90 percent of the risk associated 
with increased exposure to crashes when they engage in additional 
travel (as a consequence of the rebound effect).
    Private benefits are dominated by the value of fuel savings, which 
accrue to new car and truck buyers at retail fuel prices (inclusive of 
Federal and state taxes). In addition to saving money on fuel 
purchases, new vehicle buyers also benefit from the increased mobility 
that results from a lower cost of driving their vehicle (higher fuel 
economy reduces the per-mile cost of travel) and fewer refueling 
events. The additional travel occurs as drivers take advantage of lower 
operating costs to increase mobility, and this generates benefits to 
those drivers--equivalent to the cost of operating their vehicles to 
travel those miles, the consumer surplus, and the offsetting benefit 
that represents 90 percent of the additional safety risk from travel.

[[Page 56286]]

    In addition to private benefits and costs--those borne by 
manufacturers, buyers, and owners of cars and light trucks--there are 
other benefits and costs from increasing CAFE standards that are borne 
more broadly throughout the economy or society, which NHTSA refers to 
as SCs.\489\ The additional driving that occurs as new vehicle buyers 
take advantage of lower per-mile fuel costs is a benefit to those 
drivers, but the congestion (and road noise) created by the additional 
travel also imposes a small additional SC to all road users. We also 
include transfers from one party to another other than those directly 
incurred by manufacturers or new vehicle buyers, the largest of which 
is the loss in fuel tax revenue that occurs as a result of falling fuel 
consumption.\490\ Buyers of new cars and light trucks produced in MYs 
subject to increasing CAFE standards save on fuel purchases that 
include Federal, state, and sometimes local taxes, so revenues from 
these taxes decline; because that revenue funds maintenance of roads 
and bridges as well as other government activities, the loss in fuel 
tax revenue represents a SC, but is offset by the benefits gained by 
drivers who spend less at the pump.\491\
---------------------------------------------------------------------------

    \489\ Some of these external benefits and costs result from 
changes in economic and environmental externalities from supplying 
or consuming fuel, while others do not involve changes in such 
externalities but are similar in that they are borne by parties 
other than those whose actions impose them.
    \490\ Changes in tax revenues are a transfer and not an economic 
externality as traditionally defined, but we group these with social 
costs instead of private costs since that loss in revenue affects 
society as a whole as opposed to impacting only consumers or 
manufacturers.
    \491\ It may subsequently be replaced by another source of 
revenue, but that is beyond the scope of this proposal to examine.
---------------------------------------------------------------------------

    Among the purely external benefits created when CAFE standards are 
increased, the largest is the reduction in damages resulting from GHG 
emissions. Table IV-20 shows the different SC results that correspond 
to each GHG DR. The associated benefits related to reduced health 
damages from criteria pollutants and the benefit of improved energy 
security are both significantly smaller than the associated change in 
GHG damages across alternatives. As the tables also illustrate, the 
majority of both costs and benefits are private costs and benefits that 
accrue to buyers of new cars and trucks, rather than external welfare 
changes that affect society more generally (with the exception of the 
95th percentile SC-GHG case). This has been consistently true in CAFE 
rulemakings.
    Table IV-20 shows that the social and SCC-GHG DRs have a 
significant impact on the estimated costs and benefits. With the 
exception of the highest SCC-GHG DR, net social benefits are positive 
for all alternatives at both the 3 percent and 7 percent social DRs. 
Net benefits are higher when assessed at a 3 percent social DR since 
the largest benefit--fuel savings--are accrued over a prolonged period, 
while the largest cost--technology costs--are accrued predominantly in 
earlier years. In the cases with the highest SCC-GHG DR (5%), net 
benefits are still positive in the lower stringent alternatives (PC1LT3 
and PC2LT4) at a 3 percent social DR. Totals in the following table may 
not sum perfectly due to rounding.

         Table IV-20--Incremental Benefits and Costs Over the Lifetimes of Total Fleet Produced Through MY 2032 (2021$ Billions), by Alternative
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                               3% Discount rate                            7% Discount rate
                                                                 ---------------------------------------------------------------------------------------
                                                                    PC1LT3     PC2LT4     PC3LT5     PC6LT8     PC1LT3     PC2LT4     PC3LT5     PC6LT8
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                      Private Costs
--------------------------------------------------------------------------------------------------------------------------------------------------------
Technology Costs to Increase Fuel Economy.......................       29.9       37.8       50.7       68.8       21.5       27.1       36.1       48.5
Increased Maintenance and Repair Costs..........................        0.0        0.0        0.0        0.0        0.0        0.0        0.0        0.0
Sacrifice in Other Vehicle Attributes...........................        0.0        0.0        0.0        0.0        0.0        0.0        0.0        0.0
Consumer Surplus Loss from Reduced New Vehicle Sales............        0.0        0.1        0.2        1.1        0.0        0.1        0.2        0.8
Safety Costs Internalized by Drivers............................        4.3        5.3        6.6        8.7        2.3        2.9        3.6        4.7
                                                                 ---------------------------------------------------------------------------------------
    Subtotal--Private Costs.....................................       34.2       43.3       57.5       78.6       23.8       30.0       39.8       54.0
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                      Social Costs
--------------------------------------------------------------------------------------------------------------------------------------------------------
Congestion and Noise Costs from Rebound-Effect Driving..........        3.0        3.6        5.3        5.3        1.7        2.1        3.1        3.4
Safety Costs Not Internalized by Drivers........................        1.7        1.7        4.6        5.0        1.2        1.4        3.1        4.3
Loss in Fuel Tax Revenue........................................        7.9       10.0       11.3       15.6        4.4        5.6        6.2        8.5
                                                                 ---------------------------------------------------------------------------------------
    Subtotal--Social Costs......................................       12.6       15.4       21.2       26.0        7.4        9.1       12.4       16.3
        Total Societal Costs (incl. Private)....................       46.8       58.6       78.7      104.5       31.2       39.1       52.2       70.3
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                    Private Benefits
--------------------------------------------------------------------------------------------------------------------------------------------------------
Reduced Fuel Costs..............................................       37.6       47.7       55.1       75.9       20.6       26.0       30.0       40.7
Benefits from Additional Driving................................        7.3        9.0       11.0       14.1        4.0        4.9        6.0        7.6
Less Frequent Refueling.........................................        2.0        2.7        3.1        4.6        1.1        1.5        1.7        2.5
                                                                 ---------------------------------------------------------------------------------------
    Subtotal--Private Benefits..................................       46.9       59.4       69.1       94.6       25.6       32.4       37.6       50.9
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                    External Benefits
--------------------------------------------------------------------------------------------------------------------------------------------------------
Reduction in Petroleum Market Externality.......................        1.5        1.9        2.1        2.9        0.8        1.0        1.1        1.6
Reduced Health Damages..........................................        0.2        0.3        0.2        0.4        0.1        0.1        0.1        0.1
--------------------------------------------------------------------------------------------------------------------------------------------------------

[[Page 56287]]

 
                                                                 Reduced Climate Damages
--------------------------------------------------------------------------------------------------------------------------------------------------------
SC-GHG @5% DR...................................................        2.7        3.5        4.0        5.5        2.7        3.5        4.0        5.5
SC-GHG @3% DR...................................................       11.0       14.0       16.0       22.2       11.0       14.0       16.0       22.2
SC-GHG @2.5% DR.................................................       16.8       21.4       24.6       34.1       16.8       21.4       24.6       34.1
SC-GHG @95th pctile at 3% DR....................................       33.3       42.4       48.7       67.5       33.3       42.4       48.7       67.5
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                         Total Societal Benefits (incl. Private)
--------------------------------------------------------------------------------------------------------------------------------------------------------
SC-GHG @5% DR...................................................       51.2       65.0       75.5      103.4       29.2       37.0       42.8       58.1
SC-GHG @3% DR...................................................       59.5       75.5       87.5      120.1       37.5       47.5       54.9       74.8
SC-GHG @2.5% DR.................................................       65.3       82.9       96.1      132.0       43.3       54.9       63.5       86.7
SC-GHG @95th pctile at 3% DR....................................       81.8      103.9      120.2      165.4       59.8       75.9       87.6      120.1
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                  Net Societal Benefits
--------------------------------------------------------------------------------------------------------------------------------------------------------
SC-GHG @5% DR...................................................        4.4        6.3       -3.2       -1.2       -2.0       -2.1       -9.4      -12.2
SC-GHG @3% DR...................................................       12.7       16.8        8.8       15.6        6.3        8.4        2.7        4.5
SC-GHG @2.5% DR.................................................       18.5       24.3       17.4       27.5       12.1       15.8       11.3       16.4
SC-GHG @95th pctile at 3% DR....................................       35.0       45.2       41.5       60.9       28.7       36.8       35.4       49.8
--------------------------------------------------------------------------------------------------------------------------------------------------------

2. Heavy-Duty Pickups and Vans
    Our categorizations of benefits and costs in the HDPUV space 
mirrors the approach taken above for the LD passenger trucks and vans. 
Table IV-21 describes the costs and benefits of increasing CAFE 
standards in each alternative, as well as the party to which they 
accrue. Manufacturers are directly regulated under the program and 
incur additional production costs when they apply technology to their 
vehicle offerings in order to improve their fuel efficiency. We assume 
that those costs are fully passed through to new HDPUV buyers, in the 
form of higher prices.
    The choice of GHG DR also affects the resulting benefits and costs. 
As the tables show, net social benefits are positive for all 
alternatives, and are greatest when SC-GHG DRs of 2.5 or 3 percent are 
used. Totals in the following table may not sum perfectly due to 
rounding.

                                        Table IV-21--Incremental Benefits and Costs From Calendar Years 2022-2050
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                         3% Discount rate                                7% Discount Rate
--------------------------------------------------------------------------------------------------------------------------------------------------------
                       Alternative                            HDPUV4          HDPUV10         HDPUV14         HDPUV4          HDPUV10         HDPUV14
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                      Private Costs
--------------------------------------------------------------------------------------------------------------------------------------------------------
Technology Costs to Increase Fuel Economy...............            0.05            1.28            5.81            0.02            0.64            3.02
Increased Maintenance and Repair Costs..................               0               0               0               0               0               0
Sacrifice in Other Vehicle Attributes...................               0               0               0               0               0               0
Consumer Surplus Loss from Reduced New Vehicle Sales....               0               0               0               0               0               0
Safety Costs Internalized by Drivers....................               0            0.12            0.64               0            0.05            0.28
    Subtotal--Private Costs.............................            0.05            1.41            6.45            0.03            0.69            3.30
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                      Social Costs
--------------------------------------------------------------------------------------------------------------------------------------------------------
Congestion and Noise Costs from Rebound-Effect Driving..               0            0.01            0.07               0            0.01            0.04
Safety Costs Not Internalized by Drivers................               0           -0.10           -0.50               0           -0.04           -0.21
Loss in Fuel Tax Revenue................................            0.03            0.75            3.41            0.01            0.33            1.54
    Subtotal--Social Costs..............................            0.04            0.67            2.98            0.02             0.3            1.37
        Total Social Costs..............................            0.09            2.07            9.43            0.04            0.99            4.67
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                    Private Benefits
--------------------------------------------------------------------------------------------------------------------------------------------------------
Reduced Fuel Costs......................................            0.12            2.98           13.79            0.05             1.3            6.15
Benefits from Additional Driving........................            0.01            0.26            1.36               0            0.11            0.60
Less Frequent Refueling.................................           -0.06           -0.09           -3.06           -0.03           -0.04           -1.45
    Subtotal--Private Benefits..........................            0.07            3.15           12.09            0.03            1.38            5.30
--------------------------------------------------------------------------------------------------------------------------------------------------------

[[Page 56288]]

 
                                                                    External Benefits
--------------------------------------------------------------------------------------------------------------------------------------------------------
Reduction in Petroleum Market Externality...............            0.01            0.15            0.67               0            0.07            0.30
Reduced Health Damages..................................               0            0.05            0.22               0            0.02            0.08
Reduced Climate Damages.................................
SC-GHG @5% DR...........................................            0.01            0.23            1.05            0.01            0.23            1.05
SC-GHG @3% DR...........................................            0.04            0.97            4.45            0.04            0.97            4.45
SC-GHG @2.5% DR.........................................            0.06            1.51            6.89            0.06            1.51            6.89
SC-GHG @95th pctile at 3% DR............................            0.12            2.96           13.55            0.12            2.96           13.55
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                  Total Social Benefits
--------------------------------------------------------------------------------------------------------------------------------------------------------
SC-GHG @5% DR...........................................            0.08            3.58           14.03            0.04            1.69            6.73
SC-GHG @3% DR...........................................            0.11            4.32           17.43            0.07            2.43           10.12
SC-GHG @2.5% DR.........................................            0.14            4.85           19.87            0.09            2.97           12.56
SC-GHG @95th pctile at 3% DR............................            0.19            6.31           26.53            0.15            4.42           19.23
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                   Net Social Benefits
--------------------------------------------------------------------------------------------------------------------------------------------------------
SC-GHG @5% DR...........................................          -0.005            1.50            4.61          -0.001            0.69            2.05
SC-GHG @3% DR...........................................            0.03            2.25            8.00            0.03            1.44            5.45
SC-GHG @2.5% DR.........................................            0.05            2.78           10.44            0.05            1.97            7.89
SC-GHG @95th pctile at 3% DR............................            0.11            4.24           17.10            0.11            3.43           14.55
--------------------------------------------------------------------------------------------------------------------------------------------------------

C. Physical and Environmental Effects

1. Passenger Cars and Light Trucks
    NHTSA estimates various physical and environmental effects 
associated with the proposed standards. These include quantities of 
fuel and electricity consumed, GHGs and criteria pollutants reduced, 
and health and safety impacts. Table IV-22 shows the cumulative impacts 
grouped by decade, including the on-road fleet sizes, VMT, fuel 
consumption, and CO2 emissions, across alternatives. The 
size of the on-road fleet increases in later decades regardless of 
alternative, but the greatest on-road fleet size projection is seen in 
the baseline, with fleet sizes declining as the alternatives become 
increasingly more stringent.
    VMT increases occur in the two later decades, with the highest 
miles occurring from 2041-2050. Fuel consumption (measured in gallons 
or gasoline gallon equivalents) declines across both decades and 
alternatives as the alternatives become more stringent, as do GHG 
emissions.
---------------------------------------------------------------------------

    \492\ These rows report total vehicle units observed during the 
period. For example, 2,393 million units are modeled in the on-road 
fleet for CYs 2022-2030. On average, this represents approximately 
266 million vehicles in the on-road fleet for each calendar year in 
this CY cohort.
    \493\ These rows report total miles traveled during the period. 
For example, 28,057 billion miles traveled in CYs 2022-2030. On 
average, this represents approximately 3,117 billion annual miles 
traveled in this CY cohort.

                  Table IV-22--Cumulative Effects for All Alternatives by Calendar Year Cohort
----------------------------------------------------------------------------------------------------------------
                                     No action        PC1LT3          PC2LT4          PC3LT5          PC6LT8
----------------------------------------------------------------------------------------------------------------
                                        On-Road Fleet (Million Units) 492
----------------------------------------------------------------------------------------------------------------
2022-2030.......................           2,393           2,394           2,394           2,394           2,394
2031-2040.......................           2,606           2,603           2,602           2,600           2,594
2041-2050.......................           2,645           2,640           2,638           2,631           2,619
----------------------------------------------------------------------------------------------------------------
                                   Vehicle Miles Traveled (Billion Miles) 493
----------------------------------------------------------------------------------------------------------------
2022-2030.......................          28,057          28,061          28,061          28,062          28,063
2031-2040.......................          33,745          33,795          33,811          33,829          33,869
2041-2050.......................          34,490          34,556          34,578          34,607          34,670
----------------------------------------------------------------------------------------------------------------
                                     Fuel Consumption (Billion Gallons/GGE)
----------------------------------------------------------------------------------------------------------------
2022-2030.......................           1,115           1,114           1,113           1,113           1,113
2031-2040.......................             997             974             966             959             935
2041-2050.......................             709             675             663             646             596
----------------------------------------------------------------------------------------------------------------
                                               CO2 Emissions (mmT)
----------------------------------------------------------------------------------------------------------------
2022-2030.......................          12,362          12,342          12,338          12,335          12,330
2031-2040.......................          10,988          10,735          10,644          10,562          10,290

[[Page 56289]]

 
2041-2050.......................           7,633           7,252           7,116           6,931           6,352
----------------------------------------------------------------------------------------------------------------

    From a calendar year perspective, NHTSA's analysis estimates total 
annual consumption of fuel by the entire on-road fleet from calendar 
year 2022 through calendar year 2050. On this basis, gasoline and 
electricity consumption by the U.S. LDV fleet evolves as shown in 
Figure IV-5 and Figure IV-6, each of which shows projections for the 
No-Action Alternative (Alternative 0, i.e., the baseline), Alternative 
PC1LT3, Alternative PC2LT4, Alternative PC3LT5, and Alternative PC6LT8. 
Gasoline consumption decreases over time, with the largest decreases 
occurring in more stringent alternatives. Electricity consumption 
increases over time, with the same pattern of Alternative PC6LT8 
experiencing the highest magnitude of change.
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    NHTSA estimates the GHGs attributable to the LD on-road fleet, from 
both vehicles and upstream energy sector processes (e.g., petroleum 
refining, fuel transportation and distribution, electricity 
generation). Figure IV-7, Figure IV-8, and Figure IV-9 present NHTSA's 
estimate of how emissions from these three GHGs across all fuel types 
could evolve over the years. Note that these graphs include emissions 
from both downstream (powertrain and BTW) and upstream processes. All 
three GHG emissions follow similar trends of decline in the years 
between 2022-2050. Note that CO2 emissions are expressed in 
units of million metric tons (mmt) while emissions from other 
pollutants are expressed in metric tons.

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BILLING CODE 4910-59-C
    The figures presented here are not the only estimates NHTSA 
calculates regarding projected GHG emissions in future years. The 
accompanying Draft EIS uses an ``unconstrained'' analysis as opposed to 
the ``standard setting'' analysis presented in this proposal. For more 
information regarding projected GHG emissions, as well as model-based 
estimates of corresponding impacts on several measures of global 
climate change, see the Draft EIS.
    NHTSA also estimates criteria pollutant emissions resulting from 
downstream (powertrain and BTW) and upstream processes attributable to 
the LD on-road fleet. Under each regulatory alternative, NHTSA projects 
a dramatic decline in annual emissions of NOX, and 
PM2.5 attributable to the LD on-road fleet between 2022 and 
2050. As exemplified in Figure IV-10, NOX emissions in any 
given year could be very nearly the same under each regulatory 
alternative.
    On the other hand, as discussed in the PRIA Chapter 8.2 and Chapter 
4 of the Draft EIS accompanying this document, NHTSA projects that 
annual SO2 emissions attributable to the LD on-road fleet 
could increase by 2050 in all of the alternatives, including the 
baseline, due to greater use of electricity for PHEVs and BEVs (See 
Figure IV-6). Differences between the action alternatives are modest. 
However, we also note that the adoption of actions that result in a 
cleaner electricity grid that reduces electricity generation emission 
rates below the projected levels underlying NHTSA's analysis (discussed 
in the Draft TSD) could dramatically reduce SO2 emissions 
under all regulatory alternatives considered here.\494\ We note that 
recent projections available since NHTSA finished modeling for this 
proposal show notable decreases in power sector emissions that would 
likely affect the CAFE Model emissions results. NHTSA intends to 
analyze these projections and update them for the final rule. Moreover, 
NHTSA notes that the projected increase in SO2 emissions is 
not observed in analyses using more up-to-date data.
---------------------------------------------------------------------------

    \494\ Other actions, such as President Biden's E.O.s regarding 
Federal clean electricity, vehicle procurement, and sustainability, 
may significantly alter the emissions pattern of the electrical 
grid. See, e.g. https://www.whitehouse.gov/briefing-room/presidential-actions/2021/01/27/executive-order-on-tackling-the-climate-crisis-at-home-and-abroad/. See also, https://www.whitehouse.gov/briefing-room/presidential-actions/2021/12/08/executive-order-on-catalyzing-clean-energy-industries-and-jobs-through-federal-sustainability/. AEO 2023 forecasts show that 
America's grid is likely to get cleaner in the forthcoming years, 
significantly reducing anticipated emissions as compared to today.
---------------------------------------------------------------------------

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BILLING CODE 4910-59-C
    Health impacts quantified by the CAFE Model include various 
instances of hospital visits due to respiratory problems, minor 
restricted activity days, non-fatal heart attacks, acute bronchitis, 
premature mortality, and other effects of criteria pollutant emissions 
on health. Table IV-23 shows the split in select health impacts 
relative to the No-Action Alternative, across all action alternatives. 
The magnitude of the differences relates directly to the changes in 
tons of criteria pollutants emitted. The magnitudes differ across 
health impact types because of variation in the baseline totals; for 
example, the total Minor Restricted Activity Days are much higher than 
the Respiratory Hospital Admissions. See Chapter 5.4 of the Draft TSD 
for information regarding how the CAFE Model calculates these health 
impacts.

         Table IV-23--Emission Health Impacts Across Alternatives Relative to the No-Action Alternative
                                                 [CY 2022-2050]
----------------------------------------------------------------------------------------------------------------
               Measure (Incidents)                    PC1LT3          PC2LT4          PC3LT5          PC6LT8
----------------------------------------------------------------------------------------------------------------
Premature Deaths................................            -279            -367            -499          -1,037
Respiratory Emergency Room Visits...............            -184            -245            -330            -697
Acute Bronchitis................................            -458            -609            -823          -1,771
Lower Respiratory Symptoms......................          -5,806          -7,729         -10,444         -22,464
Upper Respiratory Symptoms......................          -8,307         -11,068         -14,949         -32,232
Minor Restricted Activity Days..................        -265,774        -355,489        -478,650      -1,038,111
Work Loss Days..................................         -45,040         -60,215         -81,093        -175,702
Asthma Exacerbation.............................          -9,804         -13,064         -17,644         -38,030
Cardiovascular Hospital Admissions..............             -73             -96            -130            -271
Respiratory Hospital Admissions.................             -69             -91            -124            -257
Non-Fatal Heart Attacks (Peters)................            -291            -383            -520          -1,083
Non-Fatal Heart Attacks (All Others)............             -31             -41             -55            -115
----------------------------------------------------------------------------------------------------------------

    Lastly, NHTSA also quantifies safety impacts in its analysis. These 
include estimated counts of fatalities, non-fatal injuries, and 
property damage crashes occurring over the lifetimes of the LD on-road 
vehicles considered in the analysis. The following table shows the 
changes in these counts projected in action alternatives relative to 
the baseline.

[[Page 56295]]



        Table IV-24--Change in Safety Outcomes Across Alternatives Relative to the No-Action Alternative
                                                 [CY 2022-2050]
----------------------------------------------------------------------------------------------------------------
                   Alternative                        PC1LT3          PC2LT4          PC3LT5          PC6LT8
----------------------------------------------------------------------------------------------------------------
                                                   Fatalities
----------------------------------------------------------------------------------------------------------------
Fatalities from Mass Changes....................             -53             -46              -8              27
Fatalities from Rebound Effect..................             516             673             879           1,317
Fatalities from Sales/Scrappage.................              43              63             118             202
                                                 ---------------------------------------------------------------
    Total.......................................             506             690             989           1,546
----------------------------------------------------------------------------------------------------------------
                                                Non-Fatal Crashes
----------------------------------------------------------------------------------------------------------------
Non-Fatal Crash from Mass Changes...............          -8,223          -7,387          -1,464           4,849
Non-Fatal Crash from Rebound Effect.............          81,814         107,786         139,933         210,233
Non-Fatal Crash from Sales/Scrappage............           3,086           4,658           9,302          14,419
                                                 ---------------------------------------------------------------
    Total.......................................          76,677         105,057         147,771         229,501
----------------------------------------------------------------------------------------------------------------
                                            Property Damaged Vehicles
----------------------------------------------------------------------------------------------------------------
Property Damage Vehicles from Mass Changes......         -28,533         -24,894          -4,321          18,241
Property Damage Vehicles from Rebound Effect....         274,761         362,513         471,861         712,423
Property Damage Vehicles from Sales/Scrappage...         -16,149         -22,096         -47,046         -82,251
                                                 ---------------------------------------------------------------
    Total.......................................         230,079         315,523         420,494         648,413
----------------------------------------------------------------------------------------------------------------

    Chapter 7.1.5 of the PRIA accompanying this document contains an 
in-depth discussion on the effects of the various alternatives on these 
safety measures, and Chapter 7 of the Draft TSD contains information 
regarding the construction of the safety estimates.
2. Heavy-Duty Pickups and Vans
    NHTSA estimates the same physical and environmental effects for 
HDPUVs as it does for LDVs, including: quantities of fuel and 
electricity consumption; tons of GHG emissions and criteria pollutants 
reduced; and health and safety impacts. Table IV-22 shows the 
cumulative impacts grouped by decade, including the on-road fleet 
sizes, VMT, fuel consumption, and CO2 emissions, across 
alternatives. The size of the on-road fleet increases in later decades 
regardless of the alternative, but the greatest on-road fleet size 
projection is seen in the baseline, with fleet sizes declining in the 
most stringent scenario, Alternative HDPUV14. The other differences 
between the alternatives are not visible in the Table IV-25 due to 
rounding.
    VMT increases occur in the two later decades, with the highest 
numbers occurring from 2041-2050. Across alternatives, the VMT 
increases remain around approximately the same magnitude. Fuel 
consumption (measured in gallons or gasoline gallon equivalents) 
declines across decades, as do GHG emissions. Differences between the 
alternatives are minor but fuel consumption and GHG emissions also 
decrease as alternatives become more stringent.
---------------------------------------------------------------------------

    \495\ These rows report total vehicle units observed during the 
period. For example, 152 million units are modeled in the on-road 
fleet for CYs 2022-2030. On average, this represents approximately 
17 million vehicles in the on-road fleet for each calendar year in 
this CY cohort.
    \496\ These rows report total miles traveled during the period. 
For example, 2,040 billion miles traveled in CYs 2022-2030. On 
average, this represents approximately 227 billion annual miles 
traveled in this CY cohort.

                  Table IV-25--Cumulative Impacts for All Alternatives by Calendar Year Cohort
----------------------------------------------------------------------------------------------------------------
                                                     No action        HDPUV4          HDPUV10         HDPUV14
----------------------------------------------------------------------------------------------------------------
                                        On-Road Fleet (Million Units) 495
----------------------------------------------------------------------------------------------------------------
2022-2030.......................................             152             152             152             152
2031-2040.......................................             187             187             187             187
2041-2050.......................................             208             208             208             207
----------------------------------------------------------------------------------------------------------------
                                   Vehicle Miles Traveled (Billion Miles) 496
----------------------------------------------------------------------------------------------------------------
2022-2030.......................................           2,040           2,040           2,040           2,040
2031-2040.......................................           2,629           2,629           2,630           2,630
2041-2050.......................................           2,922           2,922           2,922           2,922
----------------------------------------------------------------------------------------------------------------
                                     Fuel Consumption (Billion Gallons/GGE)
----------------------------------------------------------------------------------------------------------------
2022-2030.......................................             146             146             146             146
2031-2040.......................................             143             143             143             141

[[Page 56296]]

 
2041-2050.......................................             123             123             122             117
----------------------------------------------------------------------------------------------------------------
                                              CO2  Emissions (mmT)
----------------------------------------------------------------------------------------------------------------
2022-2030.......................................           1,652           1,652           1,652           1,652
2031-2040.......................................           1,599           1,598           1,593           1,569
2041-2050.......................................           1,335           1,335           1,319           1,264
----------------------------------------------------------------------------------------------------------------

    Figure IV-13 and Figure IV-14 show the estimates of gasoline and 
electricity consumption of the on-road HDPUV fleet for all fuel types 
over time on a calendar year basis, from 2022-2050. The three action 
alternatives, HDPUV4, HDPUV10, and HDPUV14, are compared to the 
baseline changes over time.
    Gasoline consumption decreases over time, with the largest 
decreases occurring in more stringent alternatives. Electricity 
consumption increases over time, with the same pattern of Alternative 
HDPUV14 experiencing the highest magnitude of change. In both charts, 
the differences in magnitudes across alternatives do not vary 
drastically.
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    NHTSA estimates the GHGs attributable to the HD on-road fleet, from 
both downstream and upstream energy sector processes (e.g., petroleum 
refining, fuel transportation and distribution, electricity 
generation). These estimates mirror those discussed in the LD section 
above. Figure IV-15, Figure IV-16, and Figure IV-17 present NHTSA's 
estimate of how emissions from these three GHGs could evolve over the 
years (CY 2022-2050). Emissions from all three GHG types tracked follow 
similar trends of decline in the years between 2022-2050. Note that 
these graphs include emissions from both vehicle and upstream processes 
and scales vary by figure (CO2 emissions are expressed in 
units of million metric tons (mmt) while emissions from other 
pollutants are expressed in metric tons).
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    For more information regarding projected GHG emissions, as well as 
model-based estimates of corresponding impacts on several measures of 
global climate change, see the Draft EIS.
    NHTSA also estimates criteria pollutant emissions resulting from 
vehicle and upstream processes attributable to the HDPUV on-road fleet. 
Under each regulatory alternative, NHTSA projects a significant decline 
in annual emissions of NOX, and PM2.5 
attributable to the HDPUV on-road fleet between 2022 and 2050. As 
exemplified in Figure IV-18, the magnitude of emissions in any given 
year could be very similar under each regulatory alternative.
    On the other hand, as discussed in the PRIA Chapter 8.3 and the 
Draft EIS, NHTSA projects that annual SO2 emissions 
attributable to the HDPUV on-road fleet could increase modestly under 
the action alternatives, because, as discussed above, NHTSA projects 
that each of the action alternatives could lead to greater use of 
electricity (for PHEVs and BEVs) in later calendar years. However, as 
for the LD analysis, we note that the adoption of actions that result 
in a cleaner electricity grid that reduces electricity generation 
emission rates below the projected levels underlying NHTSA's analysis 
(discussed in the TSD) could dramatically reduce SO2 
emissions under all regulatory alternatives considered here.\497\
---------------------------------------------------------------------------

    \497\ Other actions, such as President Biden's E.O.s regarding 
Federal clean electricity, vehicle procurement, and sustainability, 
may significantly alter the emissions pattern of the electrical 
grid. See, e.g. https://www.whitehouse.gov/briefing-room/presidential-actions/2021/01/27/executive-order-on-tackling-the-climate-crisis-at-home-and-abroad/. See also https://www.whitehouse.gov/briefing-room/presidential-actions/2021/12/08/executive-order-on-catalyzing-clean-energy-industries-and-jobs-through-federal-sustainability/. AEO 2023 forecasts show that 
America's grid is likely to get cleaner in the forthcoming years 
significantly reducing anticipaited emissions as compared to today.

---------------------------------------------------------------------------

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BILLING CODE 4910-59-C
    Health impacts quantified by the CAFE Model include various 
instances of hospital visits due to respiratory problems, minor 
restricted activity days, non-fatal heart attacks, acute bronchitis, 
premature mortality, and other effects of criteria pollutant emissions 
on health. Table IV-26 shows select health impacts relative to the 
baseline, across all action alternatives. The magnitude of the 
differences relates directly to the changes in tons of criteria 
pollutants emitted. The magnitudes differ across health impact types 
because of variation in the totals; for example, the total Minor 
Restricted Activity Days are much higher than the Respiratory Hospital 
Admissions. See Chapter 5.4 of the Draft TSD for information regarding 
how the CAFE Model calculates these health impacts.

         Table IV-26--Emission Health Impacts Across Alternatives Relative to the No-Action Alternative
                                                 [CY 2022-2050]
----------------------------------------------------------------------------------------------------------------
                      Measures (incidents)                            HDPUV4          HDPUV10         HDPUV14
----------------------------------------------------------------------------------------------------------------
Premature Deaths................................................            -0.4           -10.8           -40.2
Respiratory Emergency Room Visits...............................            -0.4            -8.6           -31.1
Acute Bronchitis................................................            -0.9           -21.9           -79.0
Lower Respiratory Symptoms......................................           -11.9          -277.0          -998.9
Upper Respiratory Symptoms......................................           -17.3          -401.8        -1,446.3
Minor Restricted Activity Days..................................          -623.4       -14,190.9       -50,583.5
Work Loss Days..................................................           -99.9        -2,286.6        -8,182.8
Asthma Exacerbation.............................................           -20.5          -474.9        -1,709.1
Cardiovascular Hospital Admissions..............................            -0.1            -2.7           -10.2
Respiratory Hospital Admissions.................................            -0.1            -2.6            -9.6
Non-Fatal Heart Attacks (Peters)................................            -0.5           -11.2           -41.8
Non-Fatal Heart Attacks (All Others)............................             0.0            -1.2            -4.3
----------------------------------------------------------------------------------------------------------------

    Lastly, NHTSA also quantifies safety impacts in its analysis. These 
include estimated counts of fatalities, non-fatal injuries, and 
property damage crashes occurring over the lifetimes of the HD on-road 
vehicles considered in the analysis. The following table shows 
projections of these counts in action alternatives relative to the 
baseline.

 Table IV-27--Change in Safety Outcomes Across Alternatives Relative to
                        the No-Action Alternative
                             [CY 2022-2050]
------------------------------------------------------------------------
           Alternative                HDPUV4      HDPUV10      HDPUV14
------------------------------------------------------------------------
                               Fatalities
------------------------------------------------------------------------
Fatalities from Mass Changes.....            0            0            0
Fatalities from Rebound Effect...            0            6           33
Fatalities from Sales/Scrappage..            0           -5          -27
                                  --------------------------------------
    Total........................            0            1            6
------------------------------------------------------------------------

[[Page 56301]]

 
                            Non-Fatal Crashes
------------------------------------------------------------------------
Non-Fatal Crash from Mass Changes            0            0            0
Non-Fatal Crash from Rebound                42        1,033        5,360
 Effect..........................
Non-Fatal Crash from Sales/                 10         -878       -4,493
 Scrappage.......................
                                  --------------------------------------
    Total........................           52          155          867
------------------------------------------------------------------------
                        Property Damaged Vehicles
------------------------------------------------------------------------
Property Damage Vehicles from                0            0            0
 Mass Changes....................
Property Damage Vehicles from              147        3,609       18,609
 Rebound Effect..................
Property Damage Vehicles from               28       -3,155      -15,845
 Sales/Scrappage.................
                                  --------------------------------------
    Total........................          175          454        2,764
------------------------------------------------------------------------

    Chapter 7.1.5 of the PRIA accompanying this document contains an 
in-depth discussion on the effects of the various alternatives on these 
safety measures, and Draft TSD Chapter 7 contains information regarding 
the construction of the safety estimates.

D. Sensitivity Analysis

    The analysis conducted to support this rulemaking consists of data, 
estimates, and assumptions, all applied within an analytical framework, 
the CAFE Model. Just as with all past CAFE and HDPUV FE rulemakings, 
NHTSA recognizes that many analytical inputs are uncertain, and some 
inputs are very uncertain. Of those uncertain inputs, some are likely 
to exert considerable influence over specific types of estimated 
impacts, and some are likely to do so for the bulk of the analysis. Yet 
making assumptions in the face of that uncertainty is necessary when 
analyzing possible future events (e.g., consumer and industry responses 
to fuel economy/efficiency regulation). In other cases, we made 
assumptions in how we modeled the effects of other existing regulations 
that affected the costs and benefits of the action alternatives (e.g., 
state ZEV mandates were included in the No-Action Alternative). To 
better understand the effect that these assumptions have on the 
analytical findings, we conducted additional model runs with 
alternative assumptions. These additional runs were specified in an 
effort to explore a range of potential inputs and the sensitivity of 
estimated impacts to changes in these model inputs. Sensitivity cases 
in this analysis span assumptions related to technology applicability 
and cost, economic conditions, consumer preferences, externality 
values, and safety assumptions, among others.\498\ A sensitivity 
analysis can identify two critical pieces of information: how big of an 
influence does each parameter exert on the analysis, and how sensitive 
are the model results to that assumption?
---------------------------------------------------------------------------

    \498\ In contrast to an uncertainty analysis, where many 
assumptions are varied simultaneously, the sensitivity analyses 
included here vary a single assumption and provide information about 
the influence of each individual factor, rather than suggesting that 
an alternative assumption would have justified a different Preferred 
Alternative.
---------------------------------------------------------------------------

    That said, influence is different from likelihood. NHTSA does not 
mean to suggest that any one of the sensitivity cases presented here is 
inherently more likely than the collection of assumptions that 
represent the reference case (RC) in the figures and tables that 
follow. Nor is this sensitivity analysis intended to suggest that only 
one of the many assumptions made is likely to prove off-base with the 
passage of time or new observations. It is more likely that, when 
assumptions are eventually contradicted by future observation (e.g., 
deviations in observed and predicted fuel prices are nearly a given), 
there will be collections of assumptions, rather than individual 
parameters, that simultaneously require updating. For this reason, we 
do not interpret the sensitivity analysis as necessarily providing 
justification for alternative regulatory scenarios to be preferred. 
Rather, the analysis simply provides an indication of which assumptions 
are most critical, and the extent to which future deviations from 
central analysis assumptions could affect costs and benefits of the 
rule. For a full discussion of how this information relates to NHTSA's 
tentative determination of which regulatory alternatives would be 
maximum feasible, please see Section V.D.
    Table IV-28 lists and briefly describes the cases that we examined 
in the sensitivity analysis. Note that some cases only apply to the LD 
fleet (e.g., scenarios altering assumptions about fleet share modeling) 
and others only affect the HDPUV FE analysis (e.g., initial PHEV 
availability).

         Table IV-28--Cases Included in the Sensitivity Analysis
------------------------------------------------------------------------
            Sensitivity case                       Description
------------------------------------------------------------------------
RC.....................................  Reference case.
EIS-RC.................................  Reference case for
                                          Environmental Impact Statement
                                          (EIS).
Battery DMC +20%.......................  Battery direct manufacturing
                                          cost (DMC) increased by 20
                                          percent.
Battery DMC -20%.......................  Battery direct manufacturing
                                          cost (DMC) decreased by 20
                                          percent.
Battery learning rate + 20%............  Year-over-year percentage rate
                                          of learning increased by 20
                                          percent.
Battery learning rate - 20%............  Year-over-year percentage rate
                                          of learning decreased by 20
                                          percent.
BatPaC 90% cell yield..................  BatPaC model runs assume 90
                                          percent cell yield.

[[Page 56302]]

 
Annual vehicle redesigns...............  Vehicles redesigned every model
                                          year.
Limited HCR skips......................  Removes all HCR skips.
PHEV available MY 2025.................  Shifts initial HDPUV PHEV
                                          availability to MY 2025.
PHEV available MY 2030.................  Shifts initial HDPUV PHEV
                                          availability to MY 2030.
Oil price (AEO high)...................  Fuel prices from AEO 2022 High
                                          Oil Price case.
Oil price (AEO low)....................  Fuel prices from AEO 2022 Low
                                          Oil Price case.
Oil price (GI reference)...............  Fuel prices from Global
                                          Insights (GI) May 2022
                                          Reference Case.
High GDP + fuel (GI optimistic)........  GDP and fuel prices from GI
                                          optimistic case.
Low GDP + fuel (GI pessimistic)........  GDP and fuel prices from GI
                                          pessimistic case.
High GDP + fuel (AEO high).............  GDP and fuel prices from AEO
                                          2022 High Economic Growth
                                          case.
Low GDP + fuel (AEO low)...............  GDP and fuel prices from AEO
                                          2022 Low Economic Growth case.
High GDP (GI optimistic)...............  GDP from GI optimistic case.
Low GDP (GI pessimistic)...............  GDP from GI pessimistic case.
Oil market externalities (low).........  Price shock component set to
                                          10th percentile of estimates.
Oil market externalities (high)........  Price shock component set to
                                          90th percentile of estimates.
No payback period......................  Payback period set to 0 months.
24-month payback period................  Payback period set to 24
                                          months.
30-month/70k miles payback.............  Valuation of fuel savings at 30
                                          months for technology
                                          application, 70,000 miles for
                                          sales and scrappage models.
36-month payback period................  Payback period set to 36
                                          months.
60-month payback period................  Payback period set to 60
                                          months.
Implicit opportunity cost..............  Includes a measure that
                                          estimates possible opportunity
                                          cost of forgone vehicle
                                          attribute improvements that
                                          exceed the central case 30-
                                          month payback period.
Rebound (5%)...........................  Rebound effect set at 5
                                          percent.
Rebound (15%)..........................  Rebound effect set at 15
                                          percent.
Sales-scrappage response (-0.1)........  Sales-scrappage model with
                                          price elasticity multiplier of
                                          -0.1.
Sales-scrappage response (-0.5)........  Sales-scrappage model with
                                          price elasticity multiplier of
                                          -0.5.
LDV sales (unadjusted).................  No LD sales multiplier.
LDV sales (2022 FR)....................  LD sales model coefficients
                                          equal to those used in the
                                          2022 CAFE Final Rule.
LDV sales (AEO 2022)...................  LD sales rate of change
                                          consistent with AEO 2022
                                          Reference case.
No fleet share price response..........  Fleet share elasticity estimate
                                          set to 0 (i.e., no fleet share
                                          response across alternatives).
Fixed fleet share, no price response...  Fixed fleet share at AEO 2022
                                          levels, fleet share elasticity
                                          set to zero.
Fixed fleet share......................  Fleet share level fixed at 2022
                                          value.
HDPUV sales (AEO reference)............  HDPUV sales based on AEO 2022
                                          Reference Case (i.e., no
                                          initial sales ramp).
HDPUV sales (AEO low economic growth)..  HDPUV sales based on AEO 2022
                                          Low Economic Growth Case
                                          without initial sales ramp.
HDPUV sales (AEO high economic growth).  HDPUV sales based on AEO 2022
                                          High Economic Growth Case with
                                          initial sales ramp.
Commercial operator sales share 100%...  Assume all HDPUV vehicles are
                                          purchased by commercial
                                          operators. Applies commercial
                                          operator private net benefit
                                          offset.
Commercial operator sales share 50%....  Assume half of all HDPUV
                                          vehicles are purchased by
                                          commercial operators. Applies
                                          commercial operator private
                                          net benefit offset.
Mass-size-safety (low).................  The lower bound of the 95
                                          percent confidence interval
                                          for all mass-size-safety model
                                          coefficients.
Mass-size-safety (high)................  The upper bound of the 95
                                          percent confidence interval
                                          for all mass-size-safety model
                                          coefficients.
Crash avoidance (low)..................  Lower-bound estimate of
                                          effectiveness of six current
                                          crash avoidance technologies
                                          at avoiding fatalities,
                                          injuries, and property damage.
Crash avoidance (high).................  Upper-bound estimate of
                                          effectiveness of six current
                                          crash avoidance technologies
                                          at avoiding fatalities,
                                          injuries, and property damage.
2022 FR fatality rates.................  Fatality rates at 2022 CAFE
                                          Final Rule levels.
Clean grid (low).......................  Upstream emissions factors
                                          based on AEO 2022 Low
                                          Renewables Costs projection of
                                          grid composition.
Clean grid (high)......................  Upstream emissions factors
                                          based on NREL 95%
                                          Electrification by 2050-2021
                                          Standard Scenario projection
                                          of grid composition.
Adjusted MDPCS.........................  Adjusted Minimum Domestic
                                          Passenger Car Standard (MDPCS)
                                          based on historical trends.
2023 revised civil penalty rate........  Civil penalty set to values
                                          prescribed in 2023 Adjustment
                                          to Civil Penalties rule, 88 FR
                                          6971(Feb. 2, 2023).
Standard-setting conditions to 2035....  Applies standard-setting
                                          conditions to MY 2027-2035.
Standard-setting conditions to 2050....  Applies standard-setting
                                          conditions to MY 2027-2050.
Standard-setting conditions all years..  Applies standard-setting
                                          conditions to MY 2022-2050.
No augural.............................  No augural standards for MY
                                          2032.
No ZEV.................................  Excludes modeling of ZEV
                                          program.
EPA AC/OC approach.....................  AC Leakage set to 0 for all
                                          vehicles for MY2027-MY2050; AC
                                          Efficiency Credits for BEVs
                                          set to 0 in MY2027-MY2050; AC/
                                          OC Credits for BEVs set to 0
                                          in MY2027-2050; All Non-BEV
                                          vehicles have AC/OC credits
                                          gradually decline to 0 by MY
                                          2031.

[[Page 56303]]

 
AC efficiency/OC BEV zero..............  Off-Cycle Credits and AC
                                          Efficiency Credits for BEVs
                                          set to 0 in MY2027-MY2050; AC
                                          Leakage is unchanged for all
                                          manufacturers.
Original PEF value.....................  PEF value used in prior CAFE
                                          rulemakings (82,049 Wh/gal).
No EV tax credits......................  All IRA EV tax credits removed.
No AMPC................................  IRA Advanced Manufacturing
                                          Production tax credit (AMPC)
                                          removed.
Consumer tax credit share 75%..........  Consumer tax credit share set
                                          to 75 percent (25 percent
                                          captured by manufacturers).
Consumer tax credit share 25%..........  Consumer tax credit share set
                                          to 25 percent (75 percent
                                          captured by manufacturers).
Maximum vehicle tax credit.............  Maximum value of IRA vehicle
                                          tax credit.
Oil price (AEO 2023 high)..............  Fuel prices from the AEO 2023
                                          High Oil Price Case.
Oil price (AEO 2023 low)...............  Fuel prices from the AEO 2023
                                          Low Oil Price Case.
Oil price (AEO 2023 ref)...............  Fuel prices from the AEO 2023
                                          Reference Case.
High GDP (AEO 2023)....................  GDP from the AEO 2023 High
                                          Economic Growth case.
Low GDP (AEO 2023).....................  GDP from the AEO 2023 Low
                                          Economic Growth case.
Reference GDP (AEO 2023)...............  GDP from the AEO 2023 Reference
                                          case.
Reference GDP (AEO 2022)...............  GDP from the AEO 2022 Reference
                                          case.
High GDP + fuel (AEO 2023).............  GDP and fuel prices from the
                                          AEO 2023 High Economic Growth
                                          case.
Low GDP + fuel (AEO 2023)..............  GDP and fuel prices from the
                                          AEO 2023 Low Economic Growth
                                          case.
Reference GDP + fuel (AEO 2023)........  GDP and fuel prices from the
                                          AEO 2023 Reference case.
Oil Market Externalities (AEO 2023)....  Price shock component estimated
                                          using AEO 2023 oil market
                                          projections.
LD Fleet Share (AEO 2023)..............  Fleet share based on AEO 2023
                                          light-duty sales projection.
Fixed fleet share (AEO 2023), no price   Fleet share based on AEO 2023
 response.                                light-duty sales projection,
                                          fleet share elasticity set to
                                          0.
HDPUV sales (AEO 2023).................  HDPUV sales based on AEO 2023
                                          Reference case projection
                                          (including sales ramp).
HDPUV sales (AEO 2023 reference).......  HDPUV sales based on AEO 2023
                                          Reference case projection (not
                                          including sales ramp).
HDPUV sales (AEO 2023 low economic       HDPUV sales based on AEO 2023
 growth).                                 Low Economic Growth case
                                          (including sales ramp).
HDPUV sales (AEO 2023 high economic      HDPUV sales based on AEO 2023
 growth).                                 High Economic Growth case
                                          (including sales ramp).
------------------------------------------------------------------------

    Complete results for the sensitivity cases are summarized in 
Chapter 9 of the accompanying PRIA, and detailed model inputs and 
outputs for curious readers are available on NHTSA's website.\499\ For 
purposes of this preamble, the figures in Section IV.D.1 illustrate the 
relative change of the sensitivity effect of selected inputs on the 
costs and benefits estimated for this proposed rule for LDVs, while the 
figures in Section IV.D.2 present the same data for the HDPUV analysis. 
Each collection of figures groups sensitivity cases by the category of 
input assumption (e.g., macroeconomic assumptions, technology 
assumptions, and so on).
---------------------------------------------------------------------------

    \499\ National Highway Traffic Association. 2023. Corporate 
Average Fuel Economy. Available at: https://www.nhtsa.gov/laws-regulations/corporate-average-fuel-economy. (Accessed: May 31, 
2023).
---------------------------------------------------------------------------

    While the figures in this section do not show precise values, they 
give us a sense of which inputs are ones for which a different 
assumption would have a much different effect on analytical findings, 
and which ones would not have much effect. For example, assuming a 
different oil price trajectory would have a relatively large effect, as 
would doubling, or eliminating the assumed ``payback period.'' The 
relative magnitude of the effect varies by fleet. Making alternative 
assumptions about the future costs of battery technology has a 
relatively large effect on the HDPUV results. Adjusting assumptions 
related to the tax credits included in the IRA has a significant impact 
on results for both LDVs and HDPUVs. On the other hand, assumptions 
about which there has been significant disagreement in the past, like 
the rebound effect or the sales-scrappage response to changes in 
vehicle price, appear to cause only relatively small changes in net 
benefits across the range of analyzed input values. Chapter 9 of the 
PRIA provides an extended discussion of these findings, and presents 
net benefits estimated under each of the cases included in the 
sensitivity analysis.
    The results presented in the earlier subsections of Section IV and 
discussed in Section V reflect NHTSA's best judgments regarding many 
different factors, and the sensitivity analysis discussed here is 
simply to illustrate the obvious, that differences in assumptions can 
lead to differences in analytical outcomes, some of which can be large 
and some of which may be smaller than expected. Policymaking in the 
face of future uncertainty is inherently complex. Section V explains 
how NHTSA balances the statutory factors in light of the analytical 
findings, the uncertainty that we know exists, and our nation's policy 
goals, to propose CAFE standards for MYs 2027-2032, and HDPUV fuel 
efficiency standards for MY 2030 and beyond that NHTSA concludes are 
maximum feasible.
    1. Passenger Cars and Light Trucks
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BILLING CODE 4910-59-C

V. Basis for NHTSA's Tentative Conclusion That the Proposed Standards 
Are Maximum Feasible

A. EPCA, as Amended by EISA

    EPCA, as amended by EISA, contains provisions establishing how 
NHTSA must set CAFE standards and fuel efficiency standards for HDPUVs. 
DOT (by delegation, NHTSA) \500\ must establish separate CAFE standards 
for passenger cars and light trucks \501\ for each MY,\502\ and each 
standard must be the maximum feasible that the Secretary (again, by 
delegation, NHTSA) determines manufacturers can achieve in that 
MY.\503\ In determining the maximum feasible levels of CAFE standards, 
EPCA requires that NHTSA consider four statutory factors: technological 
feasibility, economic practicability, the effect of other motor vehicle 
standards of the Government on fuel economy, and the need of the United 
States to conserve energy.\504\ NHTSA must also set separate standards 
for HDPUVs, and while those standards must also ``achieve the maximum 
feasible improvement,'' they must be ``appropriate, cost-effective, and 
technologically feasible'' \505\--factors slightly different from those 
required to be considered for passenger car and light truck standards. 
NHTSA has broad discretion to balance the statutory factors in 
developing fuel consumption standards to achieve the maximum feasible 
improvement.
---------------------------------------------------------------------------

    \500\ EPCA and EISA direct the Secretary of Transportation to 
develop, implement, and enforce fuel economy standards (see 49 
U.S.C. 32901 et seq.), which authority the Secretary has delegated 
to NHTSA at 49 FR 1.95(a).
    \501\ 49 U.S.C. 32902(b)(1) (2007).
    \502\ 49 U.S.C. 32902(a) (2007).
    \503\ Id.
    \504\ 49 U.S.C. 32902(f).
    \505\ 49 U.S.C. 32902(k)(2).
---------------------------------------------------------------------------

    In addition, NHTSA has the authority to consider (and typically 
does consider) other relevant factors, such as the effect of CAFE 
standards on motor vehicle safety. The ultimate determination of what 
standards can be considered maximum feasible involves a weighing and 
balancing of factors, and the balance may shift depending on the 
information NHTSA has available about the expected circumstances in the 
MYs covered by the rulemaking. NHTSA's decision must also be guided by 
the overarching purpose of EPCA, energy conservation, while balancing 
these factors.\506\
---------------------------------------------------------------------------

    \506\ Center for Biological Diversity v. NHTSA, 538 F.3d 1172, 
1197 (9th Cir. 2008) (``Whatever method it uses, NHTSA cannot set 
fuel economy standards that are contrary to Congress's purpose in 
enacting the EPCA--energy conservation.''). While this decision 
applied only to standards for passenger cars and light trucks, NHTSA 
interprets the admonition as broadly applicable to its actions under 
section 32902.
---------------------------------------------------------------------------

    EPCA/EISA also contain several other requirements, as follow.
1. Lead Time
a. Passenger Cars and Light Trucks
    EPCA requires that NHTSA prescribe new CAFE standards at least 18 
months before the beginning of each MY.\507\ Thus, if the first year 
for which NHTSA is proposing to set CAFE standards is MY 2027, NHTSA 
interprets this provision as requiring us to issue a final rule 
covering MY 2027 standards no later than April 2025. Given the aim in 
E.O. 14037 to issue a final rule by July 2024, NHTSA expects the lead 
time requirement to be met.
---------------------------------------------------------------------------

    \507\ 49 U.S.C. 32902(a) (2007).
---------------------------------------------------------------------------

b. Heavy-Duty Pickups and Vans
    EISA requires that standards for commercial medium- and HD on-
highway vehicles and work trucks (of which HDPUVs are part) provide not 
less than four full MYs of regulatory lead time.\508\ Thus, if the 
first year for which NHTSA is proposing to set fuel efficiency 
standards for HDPUVs is MY 2030, NHTSA interprets this provision as 
requiring us to issue a final rule covering MY 2030 standards no later 
than October 2025.\509\ NHTSA expects this lead time requirement to be 
met.
---------------------------------------------------------------------------

    \508\ 49 U.S.C. 32902(k)(3)(A) (2007).
    \509\ As with passenger cars and light trucks, NHTSA interprets 
the MY for HDPUVs as beginning with October of the calendar year 
prior. Therefore, HDPUV MY 2029 would begin in October 2028; 
therefore, four full MYs prior to October 2028 would be October 
2024.
---------------------------------------------------------------------------

    EISA contains a related requirement for HDPUVs that the standards 
provide not only four full MYs of regulatory lead time, but also three 
full MYs of regulatory stability.\510\ As discussed in the Phase 2 
final rule, Congress has not spoken directly to the meaning of the 
words ``regulatory stability.'' NHTSA interprets the ``regulatory 
stability'' requirement as ensuring that manufacturers will not be 
subject to new standards in repeated rulemakings too rapidly, given 
that Congress did not include a minimum duration period for the MD/HD 
standards.\511\ NHTSA further interprets the statutory meaning as 
reasonably encompassing standards which provide for increasing 
stringency during the rulemaking time frame to be the maximum feasible. 
In this statutory context, NHTSA thus interprets the phrase 
``regulatory stability'' in section 32902(k)(3)(B) as requiring that 
the standards remain in effect for three years before they may be 
increased by amendment. It does not prohibit standards that contain 
predetermined stringency increases.
---------------------------------------------------------------------------

    \510\ 49 U.S.C. 32902(k)(3)(B) (2007).
    \511\ In contrast, as discussed below, passenger car and 
standards must remain in place for ``at least 1, but not more than 
5, MYs.'' 49 U.S.C. 32902(b)(3)(B).
---------------------------------------------------------------------------

2. Separate Standards for Passenger Cars, Light Trucks, and Heavy-Duty 
Pickups and Vans, and Minimum Standards for Domestic Passenger Cars
    EPCA requires NHTSA to set separate standards for passenger cars 
and light trucks for each MY.\512\ Based on the plain language of the 
statute, NHTSA has long interpreted this requirement as preventing 
NHTSA from setting a single combined CAFE standard for cars and trucks 
together. Congress originally required separate CAFE standards for cars 
and trucks to reflect the different fuel economy capabilities of those 
different types of vehicles, and over the history of the CAFE program, 
has never revised this requirement. Even as many cars and trucks have 
come to resemble each other more closely over time--many crossover and 
sport-utility models, for example, come in versions today that may be 
subject to either the car standards or the truck standards depending on 
their characteristics--it is still accurate to say that vehicles with 
truck-like characteristics such as 4-wheel drive, cargo-carrying 
capability, etc., currently consume more fuel per mile than vehicles 
without these components. While there have been instances in recent 
rulemakings where NHTSA raised passenger car and light truck standard 
stringency at the same numerical rate year over year, NHTSA also has 
precedent for setting passenger car and light truck standards that 
increase at different numerical rates year over year, as in the 2012 
final rule. This underscores that NHTSA's obligation is to set maximum 
feasible standards separately for each fleet, based on our assessment 
of each fleet's circumstances as seen through the lens of the four 
statutory factors that NHTSA must consider.
---------------------------------------------------------------------------

    \512\ 49 U.S.C. 32902(b)(1) (2007).
---------------------------------------------------------------------------

    EPCA, as amended by EISA, also requires another separate standard 
to be set for domestically manufactured \513\ passenger cars. Unlike 
the generally applicable standards for passenger cars

[[Page 56312]]

and light trucks described above, the compliance obligation of the 
MDPCS is identical for all manufacturers. The statute clearly states 
that any manufacturer's domestically manufactured passenger car fleet 
must meet the greater of either 27.5 mpg on average, or ``92 percent of 
the average fuel economy projected by the Secretary for the combined 
domestic and non-domestic passenger automobile fleets manufactured for 
sale in the United States by all manufacturers in the MY, which 
projection shall be published in the Federal Register when the standard 
for that MY is promulgated in accordance with [49 U.S.C. 32902(b)].'' 
\514\ Since that statutory requirement was established, the ``92 
percent'' has always been greater than 27.5 mpg, and foreseeably will 
continue to be so in the future. As in the 2020 and 2022 final rules, 
NHTSA continues to recognize industry concerns that actual total 
passenger car fleet standards have differed significantly from past 
projections, perhaps more so when NHTSA has projected significantly 
into the future. In the 2020 final rule, the compliance data showed 
that standards projected in 2012 were consistently more stringent than 
the actual standards, by an average of 1.9 percent. NHTSA has stated 
that this difference indicates that in rulemakings conducted in 2009 
through 2012, NHTSA's and EPA's projections of passenger car vehicle 
footprints and production volumes, in retrospect, underestimated the 
production of larger passenger cars over the MYs 2011 to 2018 
period.\515\
---------------------------------------------------------------------------

    \513\ In the CAFE program, ``domestically manufactured'' is 
defined by Congress in 49 U.S.C. 32904(b). The definition roughly 
provides that a passenger car is ``domestically manufactured'' as 
long as at least 75 percent of the cost to the manufacturer is 
attributable to value added in thie United States, Canada, or 
Mexico, unless the assembly of the vehicle is completed in Canada or 
Mexico and the vehicle is imported into the United States more than 
30 days after the end of the MY.
    \514\ 49 U.S.C. 32902(b)(4) (2007).
    \515\ See 85 FR 25127 (Apr. 30, 2020).
---------------------------------------------------------------------------

    Unlike the passenger car standards and light truck standards which 
are vehicle-attribute-based and automatically adjust with changes in 
consumer demand, the MDPCS are not attribute-based, and therefore do 
not adjust with changes in consumer demand and production. They are, 
instead, fixed standards that are established at the time of the 
rulemaking. As a result, by assuming a smaller-footprint fleet, on 
average, than what ended up being produced, the MY 2011-2018 MDPCS 
ended up being more stringent and placing a greater burden on 
manufacturers of domestic passenger cars than was projected and 
expected at the time of the rulemakings that established those 
standards. In the 2020 final rule, therefore, NHTSA agreed with 
industry concerns over the impact of changes in consumer demand (as 
compared to what was assumed in 2012 about future consumer demand for 
greater fuel economy) on manufacturers' ability to comply with the 
MDPCS and in particular, manufacturers that produce larger passenger 
cars domestically. Some of the largest civil penalties for 
noncompliance in the history of the CAFE program have been paid for 
noncompliance with the MDPCS. NHTSA also expressed concern at that time 
that consumer demand may shift even more in the direction of larger 
passenger cars if fuel prices continue to remain low. Sustained low oil 
prices can be expected to have real effects on consumer demand for 
additional fuel economy, and if that occurs, consumers may foreseeably 
be even more interested in 2WD crossovers and passenger-car-fleet SUVs 
(and less interested in smaller passenger cars) than they are at 
present.
    Therefore, in the 2020 final rule, to help avoid similar outcomes 
in the 2021 to 2026 time frame to what had happened with the MDPCS over 
the preceding MYs, NHTSA determined that it was reasonable and 
appropriate to consider the recent projection errors as part of 
estimating the total passenger car fleet fuel economy for MYs 2021-
2026. NHTSA therefore projected the total passenger car fleet fuel 
economy using the central analysis value in each MY, and applied an 
offset based on the historical 1.9 percent difference identified for 
MYs 2011-2018.
    For the 2022 final rule, NHTSA retained the 1.9 percent offset, 
concluding that it is difficult to predict passenger car footprint 
trends in advance, which means that, as various stakeholders have 
consistently noted, the MDPCS may turn out quite different from 92 
percent of the ultimate average passenger car standard once a MY is 
complete. NHTSA also expressed concern, as suggested by the United 
Automobile, Aerospace, and Agricultural Implement Workers of America 
(UAW), that automakers struggling to meet the unadjusted MDPCS may 
choose to import their passenger cars rather than producing them 
domestically.
    NHTSA is proposing to continue employing the 1.9 percent offset for 
MYs 2027-2032, because NHTSA continues to believe that the reasons 
presented previously for the offset still apply, and that therefore the 
offset is appropriate, reasonable, and consistent with Congress' 
intent. We seek comment on this aspect of the proposal.
    For HDPUVs, Congress gave DOT (by delegation, NHTSA) broad 
discretion to ``prescribe separate standards for different classes of 
vehicles'' under 49 U.S.C. 32902(k). HDPUVs are defined by regulation 
as ``pickup trucks and vans with a gross vehicle weight rating between 
8,501 pounds and 14,000 pounds (Class 2b through 3 vehicles) 
manufactured as complete vehicles by a single or final stage 
manufacturer or manufactured as incomplete vehicles as designated by a 
manufacturer.'' \516\ NHTSA also allows HD vehicles above 14,000 pounds 
GVWR to be optionally certified as HDPUVs and comply with HDPUV 
standards ``if properly included in a test group with similar vehicles 
at or below 14,000 pounds GVWR,'' and ``The work factor for these 
vehicles may not be greater than the largest work factor that applies 
for vehicles in the test group that are at or below 14,000 pounds 
GVWR.'' \517\ Incomplete HD vehicles at or below 14,000 pounds GVWR may 
also be optionally certified as HDPUVs and comply with the HDPUV 
standards.\518\ NHTSA is proposing to set separate standards for 
``spark ignition'' (SI, or, gasoline-fueled) and ``compression 
ignition'' (CI, or, diesel-fueled) HDPUVs, consistent with the existing 
Phase 2 standards. Each class of vehicles has its own work-factor based 
target curve; alternative fueled vehicles are subject to the standard 
for CI vehicles and HEVs and PHEVs are subject to the standard for SI 
vehicles. We understand that EPA has proposed a single curve for all 
HDPUVs regardless of fuel type; NHTSA is not proposing to take this 
approach, for several reasons. First, EPA is proposing to modify the MY 
2027 standards set in the 2016 ``Phase 2'' rulemaking, and NHTSA cannot 
follow suit due to statutory lead time requirements. Second, the 
stability of the curve designs should allow manufacturers enough lead 
time to develop technologies not yet fully implemented in the market 
for this segment that we expect will be needed to meet the standards. 
And finally, NHTSA is more confident that, given the lead time concerns 
and the technologies anticipated to be required, retaining separate CI 
and SI curves will better balance NHTSA's statutory factors for HDPUVs 
of cost-effectiveness and technological feasibility. We seek comment on 
this aspect of the proposal.
---------------------------------------------------------------------------

    \516\ 49 CFR 523.7(a).
    \517\ 49 CFR 523.7(b).
    \518\ 49 CFR 523.7(c).
---------------------------------------------------------------------------

3. Attribute-Based and Defined by a Mathematical Function
    For passenger cars and light trucks, EISA requires NHTSA to set 
CAFE standards that are ``based on 1 or more attributes related to fuel 
economy and express[ed] . . . in the form of a mathematical function.'' 
\519\ Historically, NHTSA has based standards on vehicle

[[Page 56313]]

footprint, and proposes to continue to do so for MYs 2027-2032. As in 
previous rulemakings, NHTSA proposes to define the standards in the 
form of a constrained linear function that generally sets higher (more 
stringent) targets for smaller-footprint vehicles and lower (less 
stringent) targets for larger-footprint vehicles. As discussed above in 
Section II.B, NHTSA seeks comment on these aspects of the proposal.
---------------------------------------------------------------------------

    \519\ 49 U.S.C. 32902(b)(3)(A) (2007).
---------------------------------------------------------------------------

    In the 2022 final rule, NHTSA discussed the concept of ``backstop'' 
standards in response to broad industry-wide growth in vehicle size and 
mix shifts from cars to trucks and SUVs over time. A number of 
commenters requested that NHTSA set additional backstop standards to 
ensure that those vehicles achieve certain minimum fuel economy levels. 
While NHTSA continues to believe that we do have authority to set such 
standards, we propose to address the concerns by setting light truck 
standards that increase at a more rapid rate, 4 percent year over year, 
than the 2-percent-per-year passenger car standards over the same 
timeframe. We believe that this will minimize regulatory complexity, as 
compared to creating entire new standards with which manufacturers 
would have to comply simultaneously, and it should achieve a similar 
aim of requiring the fleet that consumes more fuel--light trucks--to 
continue improving rather than backsliding. We seek comment on this 
approach.
    For HDPUVs, NHTSA also sets attribute-based standards defined by a 
mathematical function. HDPUV standards have historically been set in 
units of gallons per 100 miles, rather than in mpg,\520\ and the 
attribute for HDPUVs has historically been ``work factor,'' which is a 
function of a vehicle's payload capacity and towing capacity.\521\ 
While NHTSA does not interpret EISA as requiring NHTSA to set 
attribute-based standards defined by a mathematical function for 
HDPUVs, given that 49 U.S.C. 32902(b)(3)(A) refers specifically to fuel 
economy standards for passenger and non-passenger automobiles, NHTSA 
has still previously concluded that following that approach for HDPUVs 
is reasonable and appropriate, as long as the work performed by HDPUVs 
is accounted for. NHTSA proposes to continue to set work-factor based 
gallons-per-100-miles standards for HDPUVs for MYs 2027-2032.
---------------------------------------------------------------------------

    \520\ NHTSA has long interpreted ``fuel economy standards'' in 
the context of 49 U.S.C. 32902(k) as referring not specifically to 
mpg, as in the LDV context, but instead more broadly to account as 
accurately as possible for MD/HD fuel efficiency. NHTSA considered 
setting standards for HDPUVs (and other MD/HD vehicles) in mpg, but 
concluded that that would not be an appropriate metric given the 
work that MD/HD vehicles are manufactured to do. See 76 FR 57106, 
57112, fn. 19 (Sep. 15, 2011).
    \521\ See 49 CFR 535.5(a)(2).
---------------------------------------------------------------------------

4. Number of Model Years for Which Standards May Be Set at a Time
    For passenger cars and light trucks, EISA also states that NHTSA 
shall ``issue regulations under this title prescribing average fuel 
economy standards for at least 1, but not more than 5, MYs.'' \522\ For 
this proposal, NHTSA is proposing CAFE standards for passenger cars and 
light trucks for MYs 2027-2031, and to facilitate longer-term product 
planning by industry and in the interest of harmonization, NHTSA is 
also presenting proposed augural standards for MY 2032 as 
representative of what levels of stringency NHTSA currently believes 
could be appropriate in that MY, based on the information before us 
today. We emphasize that the augural standards are informational, and 
we recognize that they cannot be finalized as part of an action to 
finalize standards for MYs 2027-2031, and that a future rulemaking 
consistent with all applicable law will be necessary in order for NHTSA 
to establish final CAFE standards for MY 2032 passenger cars and light 
trucks. Nevertheless, for brevity, information about the impacts of the 
standards will be provided throughout the documents without 
distinguishing between the proposed standards and the augural 
standards. We seek comment on the value of presenting augural standards 
for MY 2032 as part of this action and including their presentation in 
the final rule. NHTSA notes that it also conducted a sensitivity 
analysis removing the augural year, MY 2032. The results of that 
sensitivity analysis showed slightly lower costs, benefits, and net 
benefits for each regulatory alternative, and no change in the relative 
ordering of net benefits amongst the alternatives.\523\ NHTSA 
tentatively concludes that the presentation of MY 2032 throughout these 
documents would not change our decision as to which alternative is 
maximum feasible.
---------------------------------------------------------------------------

    \522\ 49 U.S.C. 32902(b)(3)(B) (2007).
    \523\ See Chapter 9 of the PRIA for more information.
---------------------------------------------------------------------------

    The five-year statutory limit on average fuel economy standards 
that applies to passenger cars and light trucks does not apply to the 
HD pickup and van standards. NHTSA has previously stated that ``it is 
reasonable to assume that if Congress intended for the [MD/HD] 
regulatory program to be limited by the timeline prescribed in [49 
U.S.C. 32902(b)(3)(B)], it would have either mentioned [MD/HD] vehicles 
in that subsection or included the same timeline in [49 U.S.C. 
32902(k)].'' 524 525 Additionally, ``in order for [49 U.S.C. 
32902(b)(3)(B) to be interpreted to apply to [49 U.S.C. 32902(k)], the 
agency would need to give less than full weight to the . . . phrase in 
[49 U.S.C. 32902(b)(1)(C)] directing the Secretary to prescribe 
standards for `work trucks and commercial MD or HD on-highway vehicles 
in accordance with Subsection (k).' Instead, this direction would need 
to be read to mean `in accordance with Subsection (k) and the remainder 
of Subsection (b).' NHTSA believes this interpretation would be 
inappropriate. Interpreting `in accordance with Subsection (k)' to mean 
something indistinct from `in accordance of this Subsection' goes 
against the canon that statutes should not be interpreted in a way that 
`render[s] language superfluous.' Dobrova v. Holder, 607 F.3d 297, 302 
(2d Cir. 2010), quoting Mendez v. Holder, 566 F.3d 316, 321-22 (2d Cir. 
2009).'' \526\ As a result, the standards previously set remain in 
effect indefinitely at the levels required in the last MY, until 
amended by a future rulemaking action.
---------------------------------------------------------------------------

    \524\ ``[W]here Congress includes particular language in one 
section of a statute but omits it in another section of the same 
Act, it is generally presumed that Congress acts intentionally and 
purposely in the disparate inclusion or exclusion.'' Russello v. 
United States, 464 U.S. 16, 23 (1983), quoting U.S. v. Wong Kim Bo, 
472 F.2d 720, 722 (5th Cir. 1972). See also Mayo v. Questech, Inc., 
727 F.Supp. 1007, 1014 (E.D. Va. 1989) (conspicuous absence of 
provision from section where inclusion would be most logical signals 
Congress did not intend for it to be implied).
    \525\ 76 FR 57106, 57131 (Sep. 15, 2011).
    \526\ Id.
---------------------------------------------------------------------------

5. Maximum Feasible Standards
    As discussed above, EPCA requires NHTSA to consider four factors in 
determining what levels of CAFE standards (for passenger cars and light 
trucks) would be maximum feasible--technological feasibility, economic 
practicability, the effect of other motor vehicle standards of the 
Government on fuel economy, and the need of the United States to 
conserve energy. For determining what levels of fuel efficiency 
standards (for HDPUVs) would be maximum feasible, EISA requires NHTSA 
to consider three factors--whether a given fuel efficiency standard 
would be appropriate, cost-effective, and technologically feasible. 
NHTSA presents in the sections below its understanding of the meanings 
of all those factors in their respective decision-making contexts.

[[Page 56314]]

a. Passenger Cars and Light Trucks
(1) Technological Feasibility
    ``Technological feasibility'' refers to whether a particular method 
of improving fuel economy is available for deployment in commercial 
application in the MY for which a standard is being established. Thus, 
NHTSA is not limited in determining the level of new standards to 
technology that is already being applied commercially at the time of 
the rulemaking. For this proposal, NHTSA has considered a wide range of 
technologies that improve fuel economy, while considering the need to 
account for which technologies have already been applied to which 
vehicle mode/configuration, as well as the need to estimate, 
realistically, the cost and fuel economy impacts of each technology as 
applied to different vehicle models/configurations. NHTSA believes that 
the range of technologies considered, as well as how the technologies 
are defined for purposes of the analysis, is reasonable, based on our 
technical expertise, our independent research, and our interactions 
with stakeholders. NHTSA has not, however, attempted to account for 
every technology that might conceivably be applied to improve fuel 
economy, nor does NHTSA believe it is necessary to do so, given that 
many technologies address fuel economy in similar ways.\527\
---------------------------------------------------------------------------

    \527\ For example, NHTSA has not considered high-speed flywheels 
as potential energy storage devices for hybrid vehicles; while such 
flywheels have been demonstrated in the laboratory and even tested 
in concept vehicles, commercially available hybrid vehicles 
currently known to NHTSA use chemical batteries as energy storage 
devices, and the agency has considered a range of hybrid vehicle 
technologies that do so.
---------------------------------------------------------------------------

    NHTSA notes that the technological feasibility factor allows NHTSA 
to set standards that force the development and application of new 
fuel-efficient technologies, but this factor does not require NHTSA to 
do so.\528\ In the 2012 final rule, NHTSA stated that ``[i]t is 
important to remember that technological feasibility must also be 
balanced with the other of the four statutory factors. Thus, while 
`technology feasibility' can drive standards higher by assuming the use 
of technologies that are not yet commercial, `maximum feasible' is also 
defined in terms of economic practicability, for example, which might 
caution the agency against basing standards (even fairly distant 
standards) entirely on such technologies.'' \529\ NHTSA further stated 
that ``as the `maximum feasible' balancing may vary depending on the 
circumstances at hand for the MY in which the standards are set, the 
extent to which technological feasibility is simply met or plays a more 
dynamic role may also shift.'' \530\
---------------------------------------------------------------------------

    \528\ See 77 FR 63015 (Oct. 12, 2012).
    \529\ Id.
    \530\ Id.
---------------------------------------------------------------------------

    For purposes of MYs 2027-2032, NHTSA tentatively concludes that 
sufficient technology exists to meet the proposed standards. NHTSA has 
grappled with whether the ``available for deployment in commercial 
application'' language of our historical interpretation of 
technological feasibility is appropriately read as ``available for 
deployment in the world'' or ``available for deployment given the 
restrictions of 32902(h).'' In the overall balancing of factors for 
determining maximum feasible, the above interpretive question may not 
matter, because it is clear that the very high cost of the most 
stringent alternatives likely puts them out of range of economic 
practicability, especially if manufacturers appear to be resorting to 
payment of civil penalties rather than complying through technology 
application. Effectively, given the statutory constraints under which 
NHTSA must operate, NHTSA does not see a technology path to reach the 
higher fuel economy levels that would be required by the more stringent 
alternatives. Moreover, even if technological feasibility were not a 
barrier, that does not mean that requiring that technology to be added 
would be economically practicable.
(2) Economic Practicability
    ``Economic practicability'' has consistently referred to whether a 
standard is one ``within the financial capability of the industry, but 
not so stringent as to'' lead to ``adverse economic consequences, such 
as a significant loss of jobs or unreasonable elimination of consumer 
choice.'' \531\ In evaluating economic practicability, NHTSA considers 
the uncertainty surrounding future market conditions and consumer 
demand for fuel economy alongside consumer demand for other vehicle 
attributes. There is not necessarily a bright-line test for whether a 
regulatory alternative is economically practicable, but there are 
several metrics that we discuss below that we find can be useful for 
making this assessment. In determining whether standards may or may not 
be economically practicable, NHTSA considers:
---------------------------------------------------------------------------

    \531\ 67 FR 77015, 77021 (Dec. 16, 2002).
---------------------------------------------------------------------------

    Application rate of technologies--whether it appears that a 
regulatory alternative would impose undue burden on manufacturers in 
either or both the near and long term in terms of how much and which 
technologies might be required. This metric connects to the next two 
metrics, as well.
    Other technology-related considerations--related to the application 
rate of technologies, whether it appears that the burden on several or 
more manufacturers might cause them to respond to the standards in ways 
that compromise, for example, vehicle safety, or other aspects of 
performance that may be important to consumer acceptance of new 
products.
    Cost of meeting the standards--even if the technology exists and it 
appears that manufacturers can apply it consistent with their product 
cadence, if meeting the standards is estimated to raise per-vehicle 
cost more than we believe consumers are likely to accept, which could 
negatively impact sales and employment in the automotive sector, the 
standards may not be economically practicable. While consumer 
acceptance of additional new vehicle cost associated with more 
stringent CAFE standards is uncertain, NHTSA still finds this metric 
useful for evaluating economic practicability.
    Sales and employment responses--as discussed above, sales and 
employment responses have historically been key to NHTSA's 
understanding of economic practicability.
    Uncertainty and consumer acceptance \532\ of technologies--
considerations not accounted for expressly in our modeling analysis, 
but important to an assessment of economic practicability given the 
timeframe of this rulemaking. Consumer acceptance can involve 
consideration of anticipated consumer response not just to increased 
vehicle cost and consumer valuation of fuel economy, but also the way 
manufacturers may change vehicle models and vehicle sales mix in 
response to CAFE standards.
---------------------------------------------------------------------------

    \532\ See, e.g., Center for Auto Safety v. NHTSA (CAS), 793 F.2d 
1322 (D.C. Cir. 1986) (Administrator's consideration of market 
demand as component of economic practicability found to be 
reasonable).
---------------------------------------------------------------------------

    Over time, NHTSA has tried different methods to account for 
economic practicability. NHTSA has long abandoned the ``least capable 
manufacturer'' approach to ensuring economic practicability, of setting 
standards at or near the level of the manufacturer whose fleet mix was, 
on average, the largest and heaviest, generally having the highest 
capacity (for passengers and/or cargo) and capability (in terms of 
ability to perform their intended function(s)) so as not to limit the 
availability of those types of

[[Page 56315]]

vehicles to consumers.\533\ NHTSA does not believe that such an 
approach would be consistent with our root interpretation of economic 
practicability. Economic practicability focuses on the capability of 
the industry and seeks to avoid adverse consequences such as (inter 
alia) a significant loss of jobs or unreasonable elimination of 
consumer choice. If the overarching purpose of EPCA is energy 
conservation, NHTSA believes that it is reasonable to expect that 
maximum feasible standards may be harder for some automakers than for 
others, and that they need not be keyed to the capabilities of the 
least capable manufacturer. Indeed, keying standards to the least 
capable manufacturer may disincentivize innovation by rewarding laggard 
performance, and it will very foreseeably result in less energy 
conservation than an approach that looks at the abilities of the 
industry as a whole.
---------------------------------------------------------------------------

    \533\ NHTSA has not used the ``least capable manufacturer'' 
approach since prior to the MY 2005-2007 rulemaking (68 FR 16868, 
Apr. 7, 2003) under the non-attribute-based (fixed) CAFE standards.
---------------------------------------------------------------------------

    NHTSA has also sought to account for economic practicability by 
applying marginal cost-benefit analysis since the first rulemakings 
establishing attribute-based standards, considering both overall 
societal impacts and overall consumer impacts. Whether the standards 
maximize net benefits has thus been a relevant, albeit not dispositive, 
factor in the past for NHTSA's consideration of economic 
practicability. E.O. 12866 states that agencies should ``select, in 
choosing among alternative regulatory approaches, those approaches that 
maximize net benefits . . .'' As the E.O. further recognizes, agencies, 
including NHTSA, must acknowledge that the modeling of net benefits 
does not capture all considerations relevant to economic 
practicability, and moreover that the uncertainty of input assumptions 
makes perfect foresight impossible. As in past rulemakings, NHTSA is 
considering our estimates of net societal impacts, net consumer 
impacts, and other related elements in the consideration of economic 
practicability. We emphasize, however, that it is well within our 
discretion to deviate from the level at which modeled net benefits 
appear to be maximized if we conclude that the level would not 
represent the maximum feasible level for future CAFE standards, given 
all relevant and statutorily-directed considerations, as well as 
unquantifiable benefits.\534\ Economic practicability is complex, and 
like the other factors must be considered in the context of the overall 
balancing and EPCA's overarching purpose of energy conservation.
---------------------------------------------------------------------------

    \534\ Even E.O. 12866 acknowledges that ``Nothing in this order 
shall be construed as displacing the agencies' authorities or 
responsibilities, as authorized by law.'' E.O. 12866, Sec. 9.
---------------------------------------------------------------------------

(3) The Effect of Other Motor Vehicle Standards of the Government on 
Fuel Economy
    ``The effect of other motor vehicle standards of the Government on 
fuel economy'' involves analysis of the effects of compliance with 
emission, safety, noise, or damageability standards on fuel economy 
capability, and thus on the industry's ability to meet a given level of 
CAFE standards. In many past CAFE rulemakings, NHTSA has said that it 
considers the adverse effects of other motor vehicle standards on fuel 
economy. It said so because, from the CAFE program's earliest years 
\535\ until recently, compliance with these other types of standards 
has had a negative effect on fuel economy. For example, safety 
standards that have the effect of increasing vehicle weight thereby 
lowers fuel economy capability (because a heavier vehicle must work 
harder to travel the same distance, and in working harder, consumes 
more energy), thus decreasing the level of average fuel economy that 
NHTSA can determine to be feasible. NHTSA has also accounted for 
Federal Tier 3 and California LEV III criteria pollutant standards 
within its estimates of technology effectiveness in this proposal.\536\
---------------------------------------------------------------------------

    \535\ 43 FR 63184, 63188 (Dec. 15, 1977). See also 42 FR 33534, 
33537 (Jun. 30, 1977).
    \536\ For most ICE vehicles on the road today, the majority of 
vehicle-based NOX, NMOG, and CO emissions occur during 
``cold-start,'' before the three-way catalyst has reached higher 
exhaust temperatures (e.g., approximately 300 [deg]C), at which 
point it is able to convert (through oxidation and reduction 
reactions) those emissions into less harmful derivatives. By 
limiting the amount of those emissions, vehicle-level smog standards 
require the catalyst to be brought to temperature rapidly, so modern 
vehicles employ cold-start strategies that intentionally release 
fuel energy into the engine exhaust to heat the catalyst to the 
right temperature as quickly as possible. The additional fuel that 
must be used to heat the catalyst is typically referred to as a 
``cold-start penalty,'' meaning that the vehicle's fuel economy 
(over a test cycle) is reduced because the fuel consumed to heat the 
catalyst did not go toward the goal of moving the vehicle forward. 
The Autonomie work employed to develop technology effectiveness 
estimates for this proposal accounts for cold-start penalties, as 
discussed in the Chapter ``Cold-start Penalty'' of the ``CAFE 
Analysis Autonomie Documentation''.
---------------------------------------------------------------------------

    In other cases, the effect of other motor vehicle standards of the 
Government on fuel economy may be neutral, or positive. Since the Obama 
Administration, NHTSA has considered the GHG standards set by EPA as 
``other motor vehicle standards of the Government.'' In the 2012 final 
rule, NHTSA stated that ``[t]o the extent the GHG standards result in 
increases in fuel economy, they would do so almost exclusively as a 
result of inducing manufacturers to install the same types of 
technologies used by manufacturers in complying with the CAFE 
standards.'' \537\ NHTSA concluded in 2012 that ``no further action was 
needed'' because ``the agency had already considered EPA's [action] and 
the harmonization benefits of the National Program in developing its 
own [action].'' \538\ In the 2020 final rule, NHTSA reinforced that 
conclusion by explaining that a textual analysis of the statutory 
language made it clear that EPA's GHG standards are literally ``other 
motor vehicle standards of the Government'' because they are standards 
set by a Federal agency that apply to motor vehicles. NHTSA and EPA are 
obligated by Congress to exercise their own independent judgment in 
fulfilling their statutory missions, even though both agencies' 
regulations affect both fuel economy and CO2 emissions. 
There are differences between the two agencies' programs that make 
NHTSA's CAFE standards and EPA's GHG standards not perfectly one-to-one 
(even besides the fact that EPA regulates other GHGs besides 
CO2, EPA's CO2 standards also differ from NHTSA's 
in a variety of ways, often because NHTSA is bound by statute to a 
certain aspect of CAFE regulation). NHTSA creates standards that meet 
our statutory obligations, including through considering EPA's 
standards as other motor vehicle standards of the Government.\539\ 
Specifically, NHTSA has considered EPA's standards for this proposal by 
including the baseline (i.e., the MYs 2024-2026) GHG standards in our 
analytical baseline for the main analysis. Because the EPA and NHTSA 
programs were developed in coordination, and stringency decisions were 
made in coordination, NHTSA has not incorporated EPA's proposed 
CO2 standards for MYs 2027-2032 as part of the analytical 
baseline for this proposal's main analysis. NHTSA recognizes that the 
proposed CAFE standards thus sit alongside EPA's light-duty vehicle 
multipollutant emission

[[Page 56316]]

standards that were proposed in April. NHTSA's intention is to finalize 
regulations that achieve energy conservation per its statutory mandate 
and consistent with its statutory constraints, that work in harmony 
with EPA's regulations addressing air pollution. NHTSA believes that 
these statutory mandates can be met while ensuring that manufacturers 
have the flexibility they need to achieve cost-effective compliance. 
Between proposed and final rules, NHTSA will continue to coordinate 
with EPA to optimize the effectiveness of NHTSA's standards while 
minimizing compliance costs, informed by public comments from all 
stakeholders and consistent with the statutory factors. NHTSA seeks 
input to help inform these objectives.
---------------------------------------------------------------------------

    \537\ 77 FR 62624, 62669 (Oct. 15, 2012).
    \538\ Id.
    \539\ Massachusetts v. EPA, 549 U.S. 497, 532 (2007) (``[T]here 
is no reason to think that the two agencies cannot both administer 
their obligations and yet avoid inconsistency.'').
---------------------------------------------------------------------------

    With regard to state standards, NHTSA has also considered and 
accounted for the impacts of anticipated manufacturer compliance with 
California's ZEV mandate (and its adoption by the Section 177 states), 
incorporating them into the baseline No-Action Alternative as other 
regulatory requirements foreseeably applicable to automakers during the 
rulemaking time frame. In so doing, we are not taking a position on 
whether or not these programs are preempted under EPCA, nor does NHTSA 
even have authority to make such determinations with the force of law. 
NHTSA is also not taking a position on whether these regulatory 
requirements are or are not other motor vehicle standards of the 
Government; in either event, it is still appropriate to include these 
requirements in the regulatory baseline because they are foreseeable 
legal obligations applying to the automakers during the rulemaking time 
frame and are therefore relevant to understanding the state of the 
world absent any further regulatory action by NHTSA. NHTSA continues 
not to model state-level GHG standards, as discussed in the 2022 final 
rule.\540\
---------------------------------------------------------------------------

    \540\ See 87 FR at 25982 (May 2, 2022).
---------------------------------------------------------------------------

(4) The Need of the U.S. To Conserve Energy
    NHTSA has consistently interpreted ``the need of the United States 
to conserve energy'' to mean ``the consumer cost, national balance of 
payments, environmental, and foreign policy implications of our need 
for large quantities of petroleum, especially imported petroleum.'' 
\541\ The following sections discuss each of these elements in more 
detail.
---------------------------------------------------------------------------

    \541\ See, e.g., 42 FR 63184, 63188 (Dec. 15, 1977); 77 FR 
62624, 62669 (Oct. 15, 2012).
---------------------------------------------------------------------------

(c) Consumer Costs and Fuel Prices
    Fuel for vehicles costs money for vehicle owners and operators, so 
all else equal, consumers benefit from vehicles that need less fuel to 
perform the same amount of work. Future fuel prices are a critical 
input into the economic analysis of potential CAFE standards because 
they determine the value of fuel savings both to new vehicle buyers and 
to society; the amount of fuel economy that the new vehicle market is 
likely to demand in the absence of regulatory action; and they inform 
NHTSA about the ``consumer cost . . . of our need for large quantities 
of petroleum.'' For this proposal, NHTSA relied on fuel price 
projections from the EIA AEO for 2022. Federal Government agencies 
generally use EIA's price projections in their assessment of future 
energy-related policies.
    Raising fuel economy standards can reduce consumer costs on fuel--
this has long been a major focus of the CAFE program and was one of the 
driving considerations for Congress in establishing the CAFE program 
originally. Over time, as average VMT has increased and more and more 
Americans have come to live farther and farther from their workplaces 
and activities, fuel costs have become even more important. Even when 
gasoline prices, for example, are relatively low, they can still add up 
quickly for consumers whose daily commute measures in hours, like many 
Americans in economically disadvantaged and historically underserved 
communities. When vehicles can go farther on a gallon of gasoline, 
consumers save money, and for lower-income consumers the savings may 
represent a larger percentage of their income and overall expenditures 
than for more-advantaged consumers. Of course, when fuel prices spike, 
lower-income consumers suffer disproportionately. Thus, clearly, the 
need of the United States to conserve energy is well-served by helping 
consumers save money at the gas pump.
    NHTSA and the DOT are committed to improving equity in 
transportation. Helping economically disadvantaged and historically 
underserved Americans save money on fuel and get where they need to go 
is an important piece of this puzzle, and it also improves energy 
conservation, thus implementing Congress' intent in EPCA. All of the 
action alternatives considered in this proposal improve fuel economy as 
compared to the baseline standards, with the most stringent 
alternatives saving consumers the most on fuel costs.
    That said, in many previous CAFE rulemakings, discussions of fuel 
prices have always been intended to reflect the price of motor 
gasoline. However, a growing set of vehicle offerings that rely in 
part, or entirely, on electricity suggests that gasoline prices are no 
longer the only fuel prices relevant to evaluations of the effects of 
different possible CAFE standards. In the analysis supporting this 
proposal, NHTSA considers the energy consumption from the entire on-
road fleet, which already contains a number of plug-in hybrid and fully 
electric vehicles that are part of the fleet independent of proposed 
CAFE standards.\542\ While the current national average electricity 
price is significantly higher than that of gasoline, on an energy 
equivalent basis ($/MMBtu),\543\ electric motors convert energy into 
propulsion much more efficiently than ICEs. This means that, even 
though the energy-equivalent prices of electricity are higher, electric 
vehicles still produce fuel savings for their owners. EIA's AEO 2022 
also projects some amount of rise in real gasoline prices over the next 
three decades,\544\ while projecting real electricity prices to 
decrease slightly.\545\ As the reliance on electricity grows in the LD 
fleet, NHTSA will continue to monitor the trends in electricity prices 
and their implications, if any, for CAFE standards.
---------------------------------------------------------------------------

    \542\ Higher CAFE standards encourage manufacturers to improve 
fuel economy; at the same time, manufacturers will foreseeably seek 
to continue to maximize profit, and to the extent that plug-in 
hybrids and fully-electric vehicles are cost-effective to build and 
desired by the market, manufacturers may well build more of these 
vehicles, even though NHTSA does not expressly consider them as a 
compliance option when we are determining maximum feasible CAFE 
stringency. Due to forces other than CAFE standards, however, we do 
expect continued growth in electrification technologies (and we 
reflect those forces in the analytical baseline).
    \543\ See AEO. 2022. Table 3: Energy Prices by Sector and 
Source. Available at: https://www.eia.gov/outlooks/aeo/data/browser/#/?id=3-AEO2022&cases=ref2022&sourcekey=0. (Accessed: May 31, 2023).
    \544\ See AEO. 2022. Table 12: Petroleum and Other Liquids 
Prices. Available at: https://www.eia.gov/outlooks/aeo/data/browser/#/?id=12-AEO2022&cases=ref2022&sourcekey=0. (Accessed: May 31, 
2023).
    \545\ See AEO. 2022. Table 8: Electricity Supply, Disposition, 
Prices, and Emissions. Available at: https://www.eia.gov/outlooks/aeo/data/browser/#/?id=8-AEO2022&cases=ref2022&sourcekey=0. 
(Accessed May 31, 2023).
---------------------------------------------------------------------------

(b) National Balance of Payments
    NHTSA has consistently included consideration of the ``national 
balance of payments'' as part of the need of the U.S. to conserve 
energy because of concerns that importing large amounts of oil created 
a significant wealth transfer to oil-exporting countries and

[[Page 56317]]

left the U.S. economically vulnerable.\546\ According to EIA, the net 
U.S. petroleum trade value deficit peaked in 2008, but it has fallen 
over the past decade as volumes of U.S. petroleum exports increased to 
record-high levels and imports decreased.\547\ The 2020 net U.S. 
petroleum trade value deficit was $3 billion, the smallest on record, 
partially because of less consumption amid COVID mitigation 
efforts.\548\ In 2020 and 2021, annual total petroleum net imports were 
actually negative, the first years since at least 1949. For petroleum 
that was imported in 2021, 51 percent came from Canada, 8 percent came 
from Mexico, 8 percent came from Russia, 5 percent came from Saudi 
Arabia, and 2 percent came from Colombia.\549\ While transportation 
demand is expected to continue to increase as the economy recovers from 
the pandemic, it is foreseeable that the trend of trade in consumer 
goods and services continuing to dominate the national balance of 
payments, as compared to petroleum, will continue during the rulemaking 
time frame.\550\ Regardless, the U.S. does continue to rely on oil 
imports. Moreover, because the oil market is global in nature, the U.S. 
is still subject to price volatility, as recent global events have 
demonstrated. NHTSA recognizes that reducing the vulnerability of the 
U.S. to possible oil price shocks remains important. This proposal aims 
to improve fleet-wide fuel efficiency and to help reduce the amount of 
petroleum consumed in the U.S., and therefore aims to improve this part 
of the U.S. balance of payments as well as to protect consumers from 
global price shocks.
---------------------------------------------------------------------------

    \546\ For the earliest discussion of this topic, see 42 FR 
63184, 63192 (Dec. 15, 1977).
    \547\ EIA. Today in Energy: U.S. energy trade lowers the overall 
2020 U.S. trade deficit for the first time on record. September 22, 
2021. Available at https://www.eia.gov/todayinenergy/detail.php?id=49656#. (Accessed: May 31, 2023).
    \548\ EIA. Oil and Petroleum Products explained, Oil imports and 
exports. Updated Nov. 2, 2022. Available at https://www.eia.gov/energyexplained/oil-and-petroleum-products/imports-and-exports.php. 
(Accessed May 31, 2023).
    \549\ Id.
    \550\ Id.
---------------------------------------------------------------------------

(c) Environmental Implications
    Higher fleet fuel economy reduces U.S. emissions of CO2 
as well as various other pollutants by reducing the amount of oil that 
is produced and refined for the U.S. vehicle fleet but can also 
potentially increase emissions by reducing the cost of driving, which 
can result in increased vehicle miles traveled (i.e., the rebound 
effect). Thus, the net effect of more stringent CAFE standards on 
emissions of each pollutant depends on the relative magnitudes of its 
reduced emissions in fuel refining and distribution and any increases 
in emissions from increased vehicle use. Fuel savings from CAFE 
standards also result in lower emissions of CO2, the main 
GHG emitted as a result of refining, distribution, and use of 
transportation fuels.
    NHTSA has considered environmental issues, both within the context 
of EPCA and the context of NEPA, in making decisions about the setting 
of standards since the earliest days of the CAFE program. As courts of 
appeal have noted in three decisions stretching over the last 20 
years,\551\ NHTSA defined ``the need of the United States to conserve 
energy'' in the late 1970s as including, among other things, 
environmental implications. In 1988, NHTSA included climate change 
considerations in its CAFE notices and prepared its first environmental 
assessment addressing that subject.\552\ It cited concerns about 
climate change as one of the reasons for limiting the extent of its 
reduction of the CAFE standard for MY 1989 passenger cars.\553\
---------------------------------------------------------------------------

    \551\ CAS, 793 F.2d 1322, 1325 n. 12 (D.C. Cir. 1986); Public 
Citizen, 848 F. 2d 256, 262-63 n. 27 (D.C. Cir. 1988) (noting that 
``NHTSA itself has interpreted the factors it must consider in 
setting CAFE standards as including environmental effects''); CBD, 
538 F.3d 1172 (9th Cir. 2007).
    \552\ 53 FR 33080, 33096 (Aug. 29, 1988).
    \553\ 63 FR 39275, 39302 (Oct. 6, 1988).
---------------------------------------------------------------------------

    NHTSA also considers EJ issues as part of the environmental 
considerations under the need of the United States to conserve energy, 
consistent with E.O.s and DOT Order 5610.2(c), ``U.S. [DOT] Actions to 
Address EJ in Minority Populations and Low-Income Populations.'' \554\ 
The affected environment for EJ is nationwide, with a focus on areas 
that could contain communities with EJ concerns who would most likely 
be exposed to the environmental and health effects of oil production, 
distribution, and consumption, or the impacts of climate change. This 
includes areas where oil production and refining occur, areas near 
roadways, coastal flood-prone areas, and urban areas that are subject 
to the heat island effect.
---------------------------------------------------------------------------

    \554\ Department Of Transportation. 2021. Updated Environmental 
Justice Order 5610.2(c).
---------------------------------------------------------------------------

    Numerous studies have found that some environmental hazards are 
more prevalent in areas where minority and low-income populations 
represent a higher proportion of the population compared with the 
general population. In terms of effects due to criteria pollutants and 
air toxics emissions, the body of scientific literature points to 
disproportionate representation of minority and low-income populations 
in proximity to a range of industrial, manufacturing, and hazardous 
waste facilities that are stationary sources of air pollution, although 
results of individual studies may vary. While the scientific literature 
specific to oil refineries is limited, disproportionate exposure of 
minority and low-income populations to air pollution from oil 
refineries is suggested by other broader studies of racial and 
socioeconomic disparities in proximity to industrial facilities 
generally. Studies have also consistently demonstrated a 
disproportionate prevalence of minority and low-income populations 
living near mobile sources of pollutants (such as roadways) and 
therefore are exposed to higher concentrations of criteria air 
pollutants in multiple locations across the United States. Lower-
positioned socioeconomic groups are also generally more exposed to air 
pollution, and thus generally more vulnerable to effects of exposure.
    In terms of exposure to climate change risks, the literature 
suggests that across all climate risks, low-income communities, some 
communities of color, and those facing discrimination are 
disproportionately affected by climate events. Communities overburdened 
by poor environmental quality experience increased climate risk due to 
a combination of sensitivity and exposure. Urban populations 
experiencing inequities and health issues have greater susceptibility 
to climate change, including substantial temperature increases. Some 
communities of color facing cumulative exposure to multiple pollutants 
also live in areas prone to climate risk. Indigenous peoples in the 
United States face increased health disparities that cause increased 
sensitivity to extreme heat and air pollution. Together, this 
information indicates that climate impacts disproportionately affect 
minority and low-income populations because of socioeconomic 
circumstances, including location of lower-income housing, histories of 
discrimination, and inequity. Furthermore, high temperatures can 
exacerbate poor air quality, further compounding the risk to 
overburdened communities. Finally, health-related sensitivities in low-
income and minority populations increase risk of damaging impacts from 
poor air quality under climate change, underscoring the potential 
benefits of improving air quality to communities overburdened by poor 
environmental quality. Chapter

[[Page 56318]]

7 of the Draft EIS discusses EJ issues in more detail.
    In the Draft EIS, Chapters 3 through 5 discuss the connections 
between oil production, distribution, and consumption, and their health 
and environmental impacts. Electricity production and distribution also 
have health and environmental impacts, discussed in those chapters as 
well.
    All of the action alternatives in this NPRM reduce carbon dioxide 
emissions and, thus, the effects of climate change, as compared to the 
baseline. Effects on criteria pollutants and air toxics emissions are 
more varied, with more stringent standards generally reducing 
downstream emissions but potentially increasing upstream emissions of 
certain pollutants due to greater electricity use (in the standard-
setting analysis, by PHEVs during the standard setting years). Chapters 
4 and 5 of the Draft EIS discuss this in more detail.
    As discussed above, while our analysis suggests that the majority 
of LDVs will continue to be powered by ICEs in the near- to mid-term 
under all regulatory alternatives, greater electrification in the mid- 
to longer-term is foreseeable. While NHTSA is prohibited from 
considering the fuel economy of EVs in determining maximum feasible 
CAFE standards, EVs (which appear both in NHTSA's baseline and which 
may be produced in MYs following the period of regulation as an 
indirect effect of more stringent standards, or in response to other 
non-NHTSA standards, or in response to tax incentives and other 
government incentives, or in response to market demand) produce few to 
zero combustion-based emissions. As a result, electrification 
contributes meaningfully to the decarbonization of the transportation 
sector, in addition to having additional environmental, health, and 
economic development benefits, although these benefits may not yet be 
equally distributed across society. They also present new environmental 
(and social) questions, like the consequences of upstream electricity 
production, minerals extraction for battery components, and ability to 
charge an EV. The upstream environmental effects of extraction and 
refining for petroleum are well-recognized; minerals extraction and 
refining can also have significant downsides. NHTSA's Draft EIS 
discusses these and other effects (such as production and end-of-life 
issues) in more detail in Chapter 6, and NHTSA will continue to monitor 
these issues going forward insofar as CAFE standards may end up causing 
increased electrification levels even if NHTSA does not consider 
electrification in setting those standards, because NHTSA does not 
control what technologies manufacturers use to meet those standards, 
and because NHTSA is required to consider the environmental effects of 
its standards under NEPA.
    NHTSA carefully considered the environmental effects of this 
rulemaking, both quantitative and qualitative, as discussed in the 
Draft EIS and in Sections V.C and V.D of this preamble.
(d) Foreign Policy Implications
    U.S. consumption and imports of petroleum products impose costs on 
the domestic economy that are not reflected in the market price for 
crude petroleum or in the prices paid by consumers for petroleum 
products such as gasoline. These costs include (1) higher prices for 
petroleum products resulting from the effect of U.S. oil demand on 
world oil prices; (2) the risk of disruptions to the U.S. economy, and 
the effects of those disruptions on consumers, caused by sudden 
increases in the global price of oil and its resulting impact of fuel 
prices faced by U.S. consumers; (3) expenses for maintaining the 
Strategic Petroleum Reserve (SPR) to provide a response option should a 
disruption in commercial oil supplies threaten the U.S. economy, to 
allow the U.S. to meet part of its International Energy Agency 
obligation to maintain emergency oil stocks, and to provide a national 
defense fuel reserve; and (4) the threat of significant economic 
disruption, and the underlying effect on U.S. foreign policy, if an 
oil-exporting country threatens the United States and uses, as part of 
its threat, its power to upend the U.S. economy. Reducing U.S. 
consumption of crude oil or refined petroleum products (by reducing 
motor fuel use) can reduce these external costs.
    In addition, a 2006 report by the Council on Foreign Relations 
identified six foreign policy costs that it said arose from U.S. 
consumption of imported oil: (1) The adverse effect that significant 
disruptions in oil supply will have for political and economic 
conditions in the U.S. and other importing countries; (2) the fears 
that the current international system is unable to secure oil supplies 
when oil is seemingly scarce and oil prices are high; (3) political 
realignment from dependence on imported oil that limits U.S. alliances 
and partnerships; (4) the flexibility that oil revenues give oil-
exporting countries to adopt policies that are contrary to U.S. 
interests and values; (5) an undermining of sound governance by the 
revenues from oil and gas exports in oil-exporting countries; and (6) 
an increased U.S. military presence in the Middle East that results 
from the strategic interest associated with oil consumption.
    CAFE standards over the last few decades have conserved significant 
quantities of oil, and the petroleum intensity of the U.S. fleet has 
decreased significantly. Continuing to improve energy conservation and 
reduce U.S. oil consumption by raising CAFE standards further has the 
potential to continue to help with all of these considerations. Even if 
the energy security picture has changed since the 1970s, due in no 
small part to the achievements of the CAFE program itself in increasing 
fleetwide fuel economy, energy security in the petroleum consumption 
context remains extremely important. Congress' original concern with 
energy security was the impact of supply shocks on American consumers 
in the event that the U.S.'s foreign policy objectives lead to 
conflicts with oil-producing nations or that global events more 
generally lead to fuel disruptions. Moreover, oil is produced, refined, 
and sold in a global marketplace, so events that impact it anywhere, 
impact it everywhere. The world is dealing with these effects 
currently. Oil prices have fluctuated dramatically in recent years and 
reached over $100/barrel in 2022. A motor vehicle fleet with greater 
fuel economy is better able to absorb increased fuel costs, 
particularly in the short-term, without those costs leading to a 
broader economic crisis, as had occurred in the 1973 and 1979 oil 
crises. Ensuring that the U.S. fleet is positioned to take advantage of 
cost-effective technology innovations will allow the U.S. to continue 
to base its international activities on foreign policy objectives that 
are not limited, at least not completely, by petroleum issues. Further, 
when U.S. oil consumption is linked to the globalized and tightly 
interconnected oil market, as it is now, the only means of reducing the 
exposure of U.S. consumers to global oil shocks is to reduce their oil 
consumption and the overall oil intensity of the U.S. economy. Thus, 
the reduction in oil consumption driven by fuel economy standards 
creates an energy security benefit.
    This benefit is the original purpose behind the CAFE standards. Oil 
prices are inherently volatile, in part because geopolitical risk 
affects prices. International conflicts, sanctions, civil conflicts 
targeting oil production infrastructure, pandemic-related economic 
upheaval, cartels, all of these have had dramatic and sudden effects on 
oil prices in recent years. For all of these reasons, energy security 
remains

[[Page 56319]]

quite relevant for NHTSA in determining maximum feasible CAFE 
standards.\555\ There are extremely important energy security benefits 
associated with raising CAFE stringency that are not discussed in the 
Draft TSD Chapter 6.2.4, and which are difficult to quantify, but have 
weighed importantly for NHTSA in developing the proposed standards in 
this NPRM.
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    \555\ Draft TSD Chapter 6.2.4 also discusses emerging energy 
security considerations associated with vehicle electrification, but 
NHTSA only considers these effects for decision-making purposes 
within the framework of the statutory restrictions applicable to 
NHTSA's determination of maximum feasible CAFE standards.
---------------------------------------------------------------------------

(5) Factors That NHTSA Is Prohibited From Considering
    EPCA also provides that in determining the level at which it should 
set CAFE standards for a particular MY, NHTSA may not consider the 
ability of manufacturers to take advantage of several EPCA provisions 
that facilitate compliance with CAFE standards and thereby reduce the 
costs of compliance.\556\ NHTSA cannot consider the trading, 
transferring, or availability of compliance credits that manufacturers 
earn by exceeding the CAFE standards and then use to achieve compliance 
in years in which their measured average fuel economy falls below the 
standards. NHTSA also must consider dual fueled automobiles to be 
operated only on gasoline or diesel fuel, and it cannot consider the 
possibility that manufacturers would create new dedicated alternative 
fueled automobiles--including battery-electric vehicles--to comply with 
the CAFE standards in any MY for which standards are being set. EPCA 
encourages the production of AFVs by specifying that their fuel economy 
is to be determined using a special calculation procedure; this 
calculation results in a more-generous fuel economy assignment for 
alternative-fueled vehicles compared to what they actually achieve 
under a strict energy efficiency conversion calculation. Of course, 
manufacturers are free to use dedicated and dual-fueled AFVs and 
credits in achieving compliance with CAFE standards.
---------------------------------------------------------------------------

    \556\ 49 U.S.C. 32902(h).
---------------------------------------------------------------------------

    The effect of the prohibitions against considering these statutory 
flexibilities (like the compliance boosts for dedicated and dual-fueled 
alternative vehicles, and the use and availability of overcompliance 
credits) in setting the CAFE standards is that NHTSA cannot set 
standards that assume the use of these flexibilities in response to 
those standards--in effect, that NHTSA cannot set standards as 
stringent as NHTSA would if NHTSA could account for the availability of 
those flexibilities. For example, NHTSA cannot set standards based on 
an analysis that modeled technology pathway that includes additional 
BEV penetration specifically in response to more stringent CAFE 
standards.
    In contrast, for the non-statutory fuel economy improvement value 
program that NHTSA developed by regulation, NHTSA has determined that 
these fuel economy adjustments are not subject to the 49 U.S.C. 
32902(h) prohibition. The statute is very clear as to which 
flexibilities are not to be considered in determining maximum feasible 
CAFE standards. When NHTSA has introduced additional compliance 
mechanisms such as AC efficiency and ``off-cycle'' technology fuel 
improvement values, NHTSA has considered those technologies as 
available in the analysis. Thus, the analysis for this proposal 
includes assumptions about manufacturers' use of those technologies, as 
detailed in Chapter 2 of the accompanying Draft TSD.
    NHTSA recognizes that some stakeholders have requested that we 
interpret 32902(h) to erase completely all knowledge of BEVs' existence 
from the analysis, not only restricting their application during the 
standard-setting years, but restricting their application entirely, for 
any reason, and deleting them from the existing fleet that NHTSA uses 
to create an analytical baseline. PHEVs would correspondingly be 
counted simply as strong hybrids, considered only in ``charge-
sustaining'' mode. NHTSA continues to restrict the application of BEVs 
(and other dedicated alternative fueled vehicles) during standard-
setting years (except as is necessary to model compliance with state 
ZEV mandates), and to count PHEVs only in charge-sustaining mode during 
that time frame, which for this proposal is MYs 2027-2032. NHTSA's 
analysis also mandates the same compliance solution (based on 
compliance with the baseline standards) for all regulatory alternatives 
for the MYs 2022-2026 period. This ensures that the model does not 
simulate manufacturers creating new BEVs prior to the standard-setting 
years in anticipation of the need to comply with the CAFE standards 
during those standard-setting years. Additionally, because the model is 
restricted (for purposes of the standard-setting analysis) from 
applying BEVs during MYs 2027-2032 (again, except as is necessary to 
model compliance with state ZEV mandates), it literally cannot apply 
BEVs in those MYs in an effort to reach compliance in subsequent MYs. 
NHTSA has not taken the additional step of removing BEVs from the 
baseline fleet, and we continue to assume that manufacturers will meet 
their California ZEV obligations whether or not NHTSA sets new CAFE 
standards. We reflect those manufacturer efforts in the baseline fleet. 
We interpret the 32902(h) prohibition as preventing NHTSA from setting 
CAFE standards that effectively require additional application of 
dedicated alternative fueled vehicles in response to those standards, 
not as preventing NHTSA from being aware of the existence of dedicated 
alternative fueled vehicles that are already being produced for other 
reasons besides CAFE standards. Modeling the application of BEV 
technology in MYs outside the standard-setting years allows NHTSA to 
account for BEVs that manufacturers may produce for reasons other than 
the CAFE standards, without accounting for those BEVs that would be 
produced because of the CAFE standards. This is consistent with 
Congress' intent, made evident in the statute, that NHTSA does not 
consider the potential for manufacturers to comply with CAFE standards 
by producing additional dedicated alternative fuel automobiles. 
Moreover, OMB Circular A-4 directs agencies to conduct cost-benefit 
analyses against a baseline that represents the world in the absence of 
further regulatory action. An artificial baseline that pretends that 
dedicated alternative fueled vehicles do not exist would not be 
consistent with that directive, and we could not fulfill our statutory 
mandate to set maximum feasible CAFE standards without understanding 
these real-world baseline effects. NHTSA is aware of challenges to this 
approach in Natural Resources Defense Council v. NHTSA, No. 22-1080 
(D.C. Cir.), and our analysis will account for any judgment in that 
case that may be final before the issuance of the final rule.
    In order to test the possible effects of this interpretation on 
NHTSA's analysis, NHTSA conducted several sensitivity cases: one which 
applied the EPCA restrictions from MYs 2027-2035, one which applied the 
EPCA restrictions from MYs 2027-2050, and one which applied the EPCA 
restrictions for all MYs covered by the analysis. Even under the most 
extreme scenario, applying the restrictions to all MYs in the analysis, 
fuel consumption (both gasoline and electricity) fell relative to the 
RC: gasoline consumption did not fall by as much as the RC, and 
electricity consumption increased by

[[Page 56320]]

less than the RC, but this should be foreseeable in a scenario where 
fewer BEVs are available to be applied over time. The amount of carbon 
dioxide reduced also fell compared to the RC, and per-vehicle 
regulatory costs and fuel savings also dropped--but even so, the net 
impact on consumers was really not that much different (still slightly 
positive), and the order of alternatives, in terms of results for all 
of these metrics, did not change from the RC. Chapter 9 of the PRIA 
describes the results in much more detail. NHTSA does not believe that 
the results of this sensitivity analysis are significant enough to 
change our position on what regulatory alternative is maximum feasible 
for purposes of this proposal, as will be discussed further in Section 
V.D.
(6) Other Considerations in Determining Maximum Feasible CAFE Standards
    NHTSA has historically considered the potential for adverse safety 
effects in setting CAFE standards. This practice has been upheld in 
case law.\557\ NHTSA's findings are discussed in Section IV.B of this 
preamble and in Chapter 8.2.4.5 of the accompanying PRIA, and NHTSA 
discusses its consideration of these effects in Section V.D below.
---------------------------------------------------------------------------

    \557\ As courts have recognized, ``NHTSA has always examined the 
safety consequences of the CAFE standards in its overall 
consideration of relevant factors since its earliest rulemaking 
under the CAFE program.'' Competitive Enterprise Institute v. NHTSA, 
901 F.2d 107, 120 n. 11 (D.C. Cir. 1990) (``CEI-I'') (citing 42 FR 
33534, 33551 (Jun. 30, 1977)). Courts have consistently upheld 
NHTSA's implementation of EPCA in this manner. See, e.g., 
Competitive Enterprise Institute v. NHTSA, 956 F.2d 321, 322 (D.C. 
Cir. 1992) (``CEI-II'') (in determining the maximum feasible 
standard, ``NHTSA has always taken passenger safety into account'') 
(citing CEI-I, 901 F.2d at 120 n. 11); Competitive Enterprise 
Institute v. NHTSA, 45 F.3d 481, 482-83 (D.C. Cir. 1995) (``CEI-
III'') (same); Center for Biological Diversity v. NHTSA, 538 F.3d 
1172, 1203-04 (9th Cir. 2008) (upholding NHTSA's analysis of vehicle 
safety issues associated with weight in connection with the MYs 
2008-2011 CAFE rulemaking).
---------------------------------------------------------------------------

b. Heavy-Duty Pickups and Vans
    Statutory authority for the fuel consumption standards proposed in 
this document for HDPUVs is found in Section 103 of EISA, codified at 
49 U.S.C. 32902(k). That section authorizes a fuel efficiency 
improvement program, designed to achieve the maximum feasible 
improvement, to be created for (among other things) HDPUVs. Congress 
directed that the standards, test methods, measurement metrics, and 
compliance and enforcement protocols for HDPUVs be ``appropriate, cost-
effective, and technologically feasible,'' while achieving the 
``maximum feasible improvement'' in fuel efficiency. These three 
factors are similar to and yet somewhat different from the four factors 
that NHTSA considers for passenger car and light truck standards, but 
they still modify ``feasible'' in ``maximum feasible'' in the context 
of the HDPUV proposal beyond a plain meaning of ``capable of being 
done.'' \558\ Importantly, NHTSA interprets them as giving NHTSA 
similarly broad authority to weigh potentially conflicting priorities 
to determine maximum feasible standards.\559\ Thus, as with passenger 
car and light truck standards, NHTSA believes that it is firmly within 
our discretion to weigh and balance the HDPUV factors in a way that is 
technology-forcing, as evidenced by this proposal, but not in a way 
that requires the application of technology that will not be available 
in the lead time provided by this proposal, or that is not cost-
effective.
---------------------------------------------------------------------------

    \558\ See Center for Biological Diversity v. NHTSA, 538 F. 3d 
1172, 1194 (9th Cir. 2008).
    \559\ Where Congress has not directly spoken to a potential 
issue related to such a balancing, NHTSA's interpretation must be a 
``reasonable accommodation of conflicting policies . . . committed 
to the agency's care by the statute.'' Id. at 1195.
---------------------------------------------------------------------------

    While NHTSA has sought in the past to set HDPUV standards that are 
maximum feasible by balancing the considerations of whether standards 
are appropriate, cost-effective, and technologically feasible, NHTSA 
has not sought to interpret those factors more specifically. In the 
interest of helping NHTSA ground the elements of its analysis in the 
words of the statute, without intending to restrict NHTSA's 
consideration of any important factors, NHTSA proposes to interpret the 
32902(k)(2) factors as follows.
(1) Appropriate
    Given that the overarching purpose of EPCA is energy conservation, 
the amount of energy conserved by standards should inform whether 
standards are appropriate. When considering energy conservation, NHTSA 
may consider things like average estimated fuel savings to consumers, 
average estimated total fuel savings, and benefits to our nation's 
energy security, among other things. Environmental benefits are another 
facet of energy conservation, and NHTSA may consider carbon dioxide 
emissions avoided, criteria pollutant and air toxics emissions avoided, 
and so forth. Given NHTSA's additional mission as a safety agency, 
NHTSA may also consider the possible safety effects of different 
potential standards in determining whether those standards are 
appropriate. Effects on the industry that do not relate directly to 
``cost-effectiveness'' may be encompassed here, such as estimated 
effects on sales and employment, and effects in the industry that 
appear to be happening for reasons other than NHTSA's regulations may 
also be encompassed. NHTSA interprets ``appropriate'' broadly, as not 
prohibiting consideration of any relevant elements that are not already 
considered under one of the other factors.
(2) Cost-Effective
    Congress' use of the term ``cost-effective'' in 32902(k) appears to 
have a more specific aim than the broader term ``economic 
practicability'' in 32902(f). In past rulemakings covering HDPUVs, 
NHTSA has considered the ratio of estimated technology (or regulatory) 
costs to the estimated value of GHG emissions avoided, and also to 
estimated fuel savings. In setting passenger car and light truck 
standards, NHTSA often looks at consumer costs and benefits, like the 
estimated additional upfront cost of the vehicle (as above, assuming 
that the cost of additional technology required to meet standards gets 
passed forward to consumers) and the estimated fuel savings. Another 
way to consider cost-effectiveness could be total industry-wide 
estimated compliance costs compared to estimated societal benefits. 
Other similar comparisons of costs and benefits may also be relevant. 
NHTSA interprets ``cost-effective'' as encompassing these kinds of 
comparisons.
(3) Technologically Feasible
    Technological feasibility in the HDPUV context is similar to how 
NHTSA interprets it in the passenger car and light truck context. NHTSA 
has previously interpreted ``technological feasibility'' to mean 
``whether a particular method of improving fuel economy can be 
available for commercial application in the MY for which a standard is 
being established,'' as discussed above. NHTSA has further clarified 
that the consideration of technological feasibility ``does not mean 
that the technology must be available or in use when a standard is 
proposed or issued.'' \560\ Consistent with these previous 
interpretations, NHTSA believes that a technology does not necessarily 
need to be currently available or already in use for all regulated 
parties to be ``technologically feasible'' for these proposed 
standards,

[[Page 56321]]

as long as it is reasonable to expect, based on the evidence before us, 
that the technology will be available in the MY in which the relevant 
standard takes effect.
---------------------------------------------------------------------------

    \560\ Center for Auto Safety v. NHTSA, 793 F.2d 1322, 1325 n. 12 
(D.C. Cir. 1986), quoting 42 FR 63, 184 (1977).
---------------------------------------------------------------------------

B. Administrative Procedure Act

    The APA governs agency rulemaking generally and provides the 
standard of judicial review for agency actions. To be upheld under the 
``arbitrary and capricious'' standard of judicial review under the APA, 
an agency rule must be rational, based on consideration of the relevant 
factors, and within the scope of authority delegated to the agency by 
statute. The agency must examine the relevant data and articulate a 
satisfactory explanation for its action, including a ``rational 
connection between the facts found and the choice made.'' \561\ The APA 
also requires that agencies provide notice and comment to the public 
when proposing regulations,\562\ as NHTSA is doing with this NPRM and 
its accompanying materials.
---------------------------------------------------------------------------

    \561\ Burlington Truck Lines, Inc. v. United States, 371 U.S. 
156, 168 (1962).
    \562\ 5 U.S.C. 553.
---------------------------------------------------------------------------

C. National Environmental Policy Act

    The National Environmental Policy Act (NEPA) directs that 
environmental considerations be integrated into Federal decision making 
process, considering the purpose and need for agencies' actions.\563\ 
As discussed above, EPCA requires NHTSA to determine the level at which 
to set CAFE standards for passenger cars and light trucks by 
considering the four factors of technological feasibility, economic 
practicability, the effect of other motor vehicle standards of the 
Government on fuel economy, and the need of the U.S. to conserve 
energy, and to set fuel efficiency standards for HDPUVs by adopting and 
implementing appropriate test methods, measurement metrics, fuel 
economy standards,\564\ and compliance and enforcement protocols that 
are appropriate, cost-effective, and technologically feasible.\565\ To 
explore the potential environmental consequences of this proposal, 
NHTSA prepared a Draft EIS for this NPRM. The purpose of an EIS is to 
``. . . provide full and fair discussion of significant environmental 
impacts and [to] inform decision makers and the public of reasonable 
alternatives that would avoid or minimize adverse impacts or enhance 
the quality of the human environment.'' \566\ This section of the 
preamble describes results from NHTSA's Draft EIS, which is being 
publicly issued simultaneously with this NPRM.
---------------------------------------------------------------------------

    \563\ NEPA is codified at 42 U.S.C. 4321-47. The Council on 
Environmental Quality (CEQ) NEPA implementing regulations are 
codified at 40 CFR parts 1500 through 1508.
    \564\ In the Phase 1 HD Fuel Efficiency Improvement Program 
rulemaking, NHTSA, aided by the National Academies of Sciences 
report, assessed potential metrics for evaluating fuel efficiency. 
NHTSA found that fuel economy would not be an appropriate metric for 
HD vehicles. Instead, NHTSA chose a metric that considers the amount 
of fuel consumed when moving a ton of freight (i.e., performing 
work). As explained in the Phase 2 HD Fuel Efficiency Improvement 
Program Final Rule, this metric, delegated by Congress to NHTSA to 
formulate, is not precluded by the text of the statute. The agency 
concluded that it is a reasonable way by which to measure fuel 
efficiency for a program designed to reduce fuel consumption. 
Greenhouse Gas Emissions and Fuel Efficiency Standards for Medium- 
and Heavy-Duty Engines and Vehicles--Phase 2; Final Rule, 81 FR 
73478, 73520 (Oct. 25, 2016).
    \565\ 49 U.S.C. 32902(k)(2).
    \566\ 40 CFR 1502.1.
---------------------------------------------------------------------------

    EPCA and EISA require that the Secretary of Transportation 
determine the maximum feasible levels of CAFE standards in a manner 
that sets aside the potential use of CAFE credits or application of 
alternative fuel technologies toward compliance in MYs for which NHTSA 
is issuing new standards. NEPA, however, does not impose such 
constraints on analysis; instead, its purpose is to ensure that 
``Federal agencies consider the environmental impacts of their actions 
in the decision-making process.'' \567\ As the environmental impacts of 
this action depend on manufacturer's actual responses to proposed 
standards, and those responses are not constrained by the adoption of 
alternative fueled technologies or the use of compliance credits, the 
Draft EIS is based on ``unconstrained'' modeling rather than ``standard 
setting'' modeling. The ``unconstrained'' analysis considers 
manufacturers' potential use of CAFE credits and application of 
alternative fuel technologies in order to disclose and allow 
consideration of the real-world environmental consequences of the 
Proposed Action and alternatives.
---------------------------------------------------------------------------

    \567\ 40 CFR 1500.1(a).
---------------------------------------------------------------------------

    NHTSA conducts modeling both ways in order to reflect the various 
statutory requirements of EPCA/EISA and NEPA. The rest of the preamble, 
and importantly, NHTSA's balancing of relevant EPCA/EISA factors 
explained in Section V.D, employs the ``standard setting'' modeling in 
order to aid the decision-maker in avoiding consideration of the 
prohibited items in 49 U.S.C. 32902(h) in determining maximum feasible 
standards, but as a result, the impacts reported here may differ from 
those reported elsewhere in the preamble.\568\ However, NHTSA is 
informed by the impacts reported in the Draft EIS, in addition to the 
other information presented in this preamble, the Draft TSD, and the 
PRIA, as part of its decision-making process.
---------------------------------------------------------------------------

    \568\ ``Unconstrained'' modeling results are presented for 
comparison purposes only in some sections of the PRIA and 
accompanying databooks.
---------------------------------------------------------------------------

    NHTSA's overall EIS-related obligation is to ``take a `hard look' 
at the environmental consequences'' as appropriate.\569\ Significantly, 
``[i]f the adverse environmental effects of the proposed action are 
adequately identified and evaluated, the agency is not constrained by 
NEPA from deciding that other values outweigh the environmental 
costs.'' \570\ The agency must identify the ``environmentally 
preferable'' alternative but need not adopt it.\571\ ``Congress in 
enacting NEPA . . . did not require agencies to elevate environmental 
concerns over other appropriate considerations.'' \572\ Instead, NEPA 
requires an agency to develop and consider alternatives to the proposed 
action in preparing an EIS.\573\ The statute and implementing 
regulations do not command an agency to favor an environmentally 
preferable course of action, only that it make its decision to proceed 
with the action after taking a hard look at the potential environmental 
consequences and consider the relevant factors in making a decision 
among alternatives.\574\
---------------------------------------------------------------------------

    \569\ Baltimore Gas & Elec. Co. v. Natural Resources Defense 
Council, Inc., 462 U.S. 87, 97 (1983).
    \570\ Robertson v. Methow Valley Citizens Council, 490 U.S. 332, 
350 (1989).
    \571\ See 40 CFR 1505.2(a)(2). Vermont Yankee Nuclear Power 
Corp. v. Nat. Res. Def. Council, Inc., 435 U.S. 519, 558 (1978).
    \572\ Baltimore Gas, 462 U.S. at 97.
    \573\ 42 U.S.C. 4332(2)(c)(iii).
    \574\ See 40 CFR 1505.2(a)(2).
---------------------------------------------------------------------------

    When preparing an EIS, NEPA requires an agency to compare the 
potential environmental impacts of its proposed action and a reasonable 
range of alternatives. Because NHTSA intends to set standards for 
passenger cars, light trucks, and HDPUVs,\575\ and because evaluating 
the environmental impacts of this rulemaking requires consideration of 
the impacts of the standards for all three vehicle classes, the main 
analyses of direct and indirect effects of the action alternatives 
presented in the Draft EIS reflect: (1) the environmental

[[Page 56322]]

impacts associated with the proposed CAFE standards for LDVs, and (2) 
the environmental impacts associated with the proposed HDPUV FE 
standards. The analyses of cumulative impacts of the action 
alternatives presented in this Draft EIS reflect the cumulative or 
combined impact of the two sets of standards that are being proposed by 
NHTSA in this NPRM.
---------------------------------------------------------------------------

    \575\ Under EPCA, as amended by EISA, NHTSA is required to set 
the fuel economy standards for passenger cars in each MY at the 
maximum feasible level and to do so separately for light trucks. 
Separately, and in accordance with EPCA, as amended by EISA, NHTSA 
is required to set FE standards for HDPUVs in each MY that are 
``designed to achieve the maximum feasible improvement'' (49 U.S.C. 
32902(k)(2)).
---------------------------------------------------------------------------

    In the Draft EIS, NHTSA has analyzed a CAFE No-Action Alternative 
and four action alternatives for passenger car and light truck 
standards, along with a HDPUV FE No-Action Alternative and three action 
alternatives for HDPUV FE standards. The alternatives represent a range 
of potential actions NHTSA could take, and they are described more 
fully in Section III of this preamble, Chapter 1 of the Draft TSD, and 
Chapter 3 of the PRIA. The estimated environmental impacts of these 
alternatives, in turn, represent a range of potential environmental 
impacts that could result from NHTSA's setting maximum feasible fuel 
economy standards for passenger cars and light trucks and fuel 
efficiency standards for HDPUVs.
    To derive the direct, indirect, and cumulative impacts of the CAFE 
standard action alternatives and the HDPUV FE standard action 
alternatives, NHTSA compared each action alternative to the relevant 
No-Action Alternative, which reflects baseline trends that would be 
expected in the absence of any further regulatory action. More 
specifically, the CAFE No-Action Alternative in the Draft EIS assumes 
that the CAFE standards set in the 2022 final rule for MYs 2024-2026 
passenger cars and light trucks would remain in effect. The HDPUV FE 
No-Action Alternative in the Draft EIS assumes that the fuel efficiency 
standards set in the 2016 ``Phase 2'' final rule for MYs 2027 and later 
HDPUVs would remain in effect. Like all of the action alternatives, the 
No-Action Alternatives also include other considerations that will 
foreseeably occur during the rulemaking time frame, as discussed in 
more detail in Section III above. The No-Action Alternatives assume 
that manufacturers will comply with ZEV mandates set by California and 
other Section 177 states.\576\ The No-Action Alternatives also assume 
that manufacturers would make production decisions in response to 
estimated market demand for fuel economy or fuel efficiency, 
considering estimated fuel prices; estimated product development 
cadence; estimated availability, applicability, cost, and effectiveness 
of fuel-saving technologies; and available tax credits. The No-Action 
Alternatives further assume the applicability of recently passed tax 
credits for battery-based vehicle technologies, which improve the 
attractiveness of those technologies to consumers. The No-Action 
Alternatives provide a baseline (i.e., an illustration of what would be 
occurring in the world in the absence of new Federal regulations) 
against which to compare the environmental impacts of other 
alternatives presented in the Draft EIS.\577\
---------------------------------------------------------------------------

    \576\ Section 177 of the CAA allows states to adopt motor 
vehicle emissions standards California has put in place to make 
progress toward attainment of national ambient air quality 
standards. At the time of writing, Colorado, Connecticut, Maine, 
Maryland, Massachusetts, New Jersey, New York, Oregon, Rhode Island, 
Vermont, and Washington have adopted California's ZEV mandate. See 
CARB. States that have Adopted California's Vehicle Standards under 
section 177 of the Federal CAA. Available at: https://ww2.arb.ca.gov/resources/documents/states-have-adopted-californias-vehicle-standards-under-section-177-federal. (Accessed: May 31, 
2023).
    \577\ See 40 CFR 1502.2(e), 1502.14(d). CEQ has explained that 
``[T]he regulations require the analysis of the No-Action 
Alternative even if the agency is under a court order or legislative 
command to act. This analysis provides a benchmark, enabling 
decision makers to compare the magnitude of environmental effects of 
the action alternatives [See 40 CFR 1502.14(c).] . . . Inclusion of 
such an analsyis in the EIS is necessary to inform Congress, the 
public, and the President as intended by NEPA. [See 40 CFR 
1500.1(a).]'' Forty Most Asked Questions Concerning CEQ's NEPA 
Regulations, 46 FR 18026 (Mar. 23, 1981).
---------------------------------------------------------------------------

    The range of CAFE and HDPUV FE standard action alternatives, as 
well as the relevant No-Action Alternative in the Draft EIS, 
encompasses a spectrum of possible fuel economy and fuel efficiency 
standards that NHTSA could determine were maximum feasible based on the 
different ways NHTSA could weigh the applicable statutory factors. 
NHTSA analyzed four CAFE standard action alternatives, Alt. PC1LT3, 
Alt. PC2LT4, Alt. PC3LT5, and Alt. PC6LT8 for passenger cars and light 
trucks, and three HDPUV FE standard action alternatives, Alt. HDPUV4, 
Alt. HDPUV10, and Alt. HDPUV14 for HDPUVs. Under PC1LT3, fuel economy 
stringency would increase, on average, 1 percent per year, year over 
year for MY 2027-2032 passenger cars, and 3 percent per year, year over 
year for MY 2027-2032 light trucks. Under PC2LT4, fuel economy 
stringency would increase, on average, 2 percent per year, year over 
year for MY 2027-2032 passenger cars, and 4 percent per year, year over 
year for MY 2027-2032 light trucks (PC2LT4 is NHTSA's Preferred 
Alternative for CAFE standards). Under PC3LT5, fuel economy stringency 
would increase, on average, 3 percent per year, year over year for MY 
2027-2032 passenger cars, and 5 percent per year, year over year for MY 
2027-2032 light trucks. Under PC6LT8, fuel economy stringency would 
increase, on average, 6 percent per year, year over year for MY 2027-
2032 passenger cars, and 8 percent per year, year over year for MY 
2027-2032light trucks. Under HDPUV4, FE stringency would increase, on 
average, 4 percent per year, year over year, for MY 2030-2035 HDPUVs. 
Under HDPUV10, FE stringency would increase, on average, 10 percent per 
year, year over year, for MY 2030-2035 HDPUVs (HDPUV10 is NHTSA's 
Preferred Alternative for HDPUV FE standards). Under HDPUV14, FE 
stringency would increase on average, 14 percent per year, year over 
year, for MY 2030-2035 HDPUVs. NHTSA also analyzed three CAFE and HDPUV 
FE alternative combinations for the cumulative impacts analysis, 
Alternatives PC1LT3 and HDPUV4 (the lowest stringency CAFE and HDPUV FE 
alternatives), Alternatives PC2LT4 and HDPUV10 (the Preferred CAFE and 
HDPUV FE alternatives), and Alternatives PC6LT8 and HDPUV14 (the 
highest stringency CAFE and HDPUV FE alternatives). Throughout the 
Draft EIS, estimated impacts were shown for all of these action 
alternatives, as well as for the relevant No-Action Alternative. For a 
more detailed discussion of the environmental impacts associated with 
the alternatives, see Chapters 3-8 of the Draft EIS, as well as Section 
IV.C of this preamble.
    The Draft EIS describes potential environmental impacts to a 
variety of resources, including fuel and energy use, air quality, 
climate, land use and development, hazardous materials and regulated 
waste, EJ, and historic and cultural resources. The Draft EIS also 
describes how climate change resulting from global GHG emissions 
(including CO2 emissions attributable to the U.S. LD 
transportation sector under the alternatives considered) could affect 
certain key natural and human resources. Resource areas are assessed 
qualitatively and quantitatively, as appropriate, in the Draft EIS, and 
the findings of that analysis are summarized here. As explained above, 
the qualitative impacts presented below come from the Draft EIS' 
``unconstrained'' modeling so that NHTSA is appropriately informed 
about the potential environmental impacts of this action. Qualitative 
discussions of impacts related to life-cycle assessment of vehicle 
materials, EJ, and historic and cultural resources are located in the 
Draft EIS, while the impacts summarized here focus on energy, air 
quality, and climate change.

[[Page 56323]]

1. Environmental Consequences
a. Energy
(1) Direct and Indirect Impacts
    As the stringency of the CAFE standard alternatives increases, 
total U.S. passenger car and light truck fuel consumption for the 
period of 2022 to 2050 decreases. Total LDV fuel consumption from 2022 
to 2050 under the No-Action Alternative is projected to be 2,761 
billion gasoline gallon equivalents (GGE). LDV fuel consumption from 
2022 to 2050 under the action alternatives is projected to range from 
2,744 billion GGE under PC1LT3 to 2,548 billion GGE under PC6LT8. Under 
PC2LT4, LDV fuel consumption from 2022 to 2050 is projected to be 2,727 
billion GGE. Under PC3LT5, LDV fuel consumption from 2022 to 2050 is 
projected to be 2,688 billion GGE. All of the CAFE standard action 
alternatives would decrease fuel consumption compared to the relevant 
No-Action Alternative, with fuel consumption decreases that range from 
17 billion GGE under PC1LT3 to 212 billion GGE under PC6LT8. For the 
preferred alternative, fuel consumption decreases by 34 billion GGE.
    As the stringency of the HDPUV FE standard alternatives increases, 
total U.S. HDPUV fuel consumption for the period of 2022 to 2050 
decreases. Total HDPUV vehicle fuel consumption from 2022 to 2050 under 
the No-Action Alternative is projected to be 412.2 billion GGE. HDPUV 
fuel consumption from 2022 to 2050 under the action alternatives is 
projected to range from 412.1 billion GGE under HDPUV4 to 403.3 billion 
GGE under HDPUV14. Under HDPUV10, HDPUV vehicle fuel consumption from 
2022 to 2050 is projected to be 410.3 billion GGE. All of the HDPUV 
standard action alternatives would decrease fuel consumption compared 
to the relevant No-Action Alternative, with fuel consumption decreases 
that range from 0.1 billion GGE under HDPUV4 to 8.9 billion GGE under 
HDPUV14. For the preferred alternative, fuel consumption decreases by 
1.9 billion GGE.
(2) Cumulative Impacts
    Energy cumulative impacts are composed of both LD and HDPUV energy 
use in addition to other past, present, and reasonably foreseeable 
future actions. As the CAFE Model includes many foreseeable trends, 
like gas price projections from AEO 2022's RC, NHTSA examined two AEO 
2022 side cases that could proxy a range of future outcomes where oil 
consumption is lower based on a range of macroeconomic factors. Since 
the results of the CAFE and HDPUV FE standards are a decline in oil 
consumption, examining side cases that also result in lower oil 
consumption while varying macroeconomic factors provides some insights 
into the cumulative effects of CAFE standards paired other potential 
future events. Energy production and consumption from those side cases 
is presented in comparison to the RC qualitatively in the Draft EIS. 
Below, we present the combined fuel consumption savings from the LD 
CAFE and HDPUV FE standards.
    Total LDV and HDPUV fuel consumption from 2022 to 2050 under the 
No-Action Alternatives is projected to be 3,173 billion GGE. LDV and 
HDPUV fuel consumption from 2022 to 2050 under the action alternatives 
is projected to range from 3,156 billion GGE under Alternatives PC1LT3 
and HDPUV4 to 2,952 billion GGE under Alternatives PC6LT8 and HDPUV14. 
Under Alternatives PC2LT4 and HDPUV10, the total LDV and HDPUV fuel 
consumption from 2022 to 2050 is projected to be 3,138 billion GGE. All 
of the action alternatives would decrease fuel consumption compared to 
the No-Action Alternatives, with decreases ranging from 17 billion GGE 
under Alternatives PC1LT3 and HDPUV4 to 221 billion GGE under 
Alternatives PC6LT8 and HDPUV14. For the proposed alternatives, fuel 
consumption decreases by 36 billion GGE.
    Changing CAFE and HDPUV FE standards are expected to reduce 
gasoline and diesel fuel use in the transportation sector but are not 
expected to have any discernable effect on energy consumption by other 
sectors of the U.S. economy because petroleum products account for a 
very small share of energy use in other sectors. Gasoline and diesel 
(distillate fuel oil) account for less than 5 percent of energy use in 
the industrial sector, less than 4 percent of energy use in the 
commercial building sector, 2 percent of energy use in the residential 
sector, and only about 0.2 percent of energy use in the electric power 
sector.
b. Air Quality
(1) Direct and Indirect Impacts
    The relationship between stringency and criteria and air toxics 
pollutant emissions is less straightforward, reflecting the complex 
interactions among the vehicle-based emissions rates of the various 
vehicle types (passenger cars and light trucks, HDPUVs, ICE vehicles 
and EVs, older and newer vehicles, etc.), the technologies assumed to 
be incorporated by manufacturers in response to CAFE and HDPUV FE 
standards, upstream emissions rates, the relative proportions of 
gasoline, diesel, and electricity in total fuel consumption, and 
changes in VMT from the rebound effect. In general, emissions of 
criteria and toxic air pollutants increase very slightly in the short 
term, and then decrease dramatically in the longer term, across all 
action alternatives, with some exceptions. In addition, the action 
alternatives would result in decreased incidence of PM2.5-
related health impacts in most years and alternatives due to the 
emissions decreases. Decreases in adverse health outcomes include 
decreased incidences of premature mortality, acute bronchitis, 
respiratory emergency room visits, and work-loss days.
(e) Criteria Pollutants
    In 2035, emissions of NO, PM2.5, and 
SO2 increase, and emissions of CO and VOCs decrease, under 
all CAFE standard action alternatives compared to the CAFE No-Action 
Alternative. Relative to the CAFE No-Action Alternative, the modeling 
results suggest NOX, PM2.5, and SO2 
emissions increases in 2035 get larger from Alternative PC1LT3 through 
Alternative PC6LT8 (the most stringent alternative in terms of 
estimated required mpg). The increases in NOX, 
PM2.5, and SO2 emissions reflect the projected 
increase in EV use in the later years, which would result in greater 
emissions from fossil-fueled power plants to generate the electricity 
for charging the EVs even as the electric grid that charges EVs gets 
progressively cleaner in later years. For CO and VOCs, the emissions 
decrease in 2035 get larger from Alternative PC1LT3 through Alternative 
PC6LT8 relative to the CAFE No-Action Alternative.
    In 2050, emissions of NOX and SO2 increase 
under some CAFE standard action alternatives and decrease under others, 
compared to the CAFE No-Action Alternative. NOX emissions 
decrease under Alternatives PC1LT3 and PC2LT4 but increase under 
Alternatives PC3LT5 and PC6LT8, compared to the CAFE No-Action 
Alternative. SO2 emissions decrease under Alternative PC1LT3 
but increase under Alternatives PC2LT4 through PC6LT8, and the 
increases get larger from Alternative PC2LT4 through Alternative 
PC6LT8. PM2.5 emissions in 2050 decrease under all action 
alternatives, but the decrease under Alternative PC3LT5 is less than 
the decrease under Alternative PC2LT4. As in 2035, emissions in 2050 of 
CO and VOCs decrease under the action alternatives compared to the CAFE 
No-Action Alternative. The CO and VOC

[[Page 56324]]

emissions decreases get larger from Alternative PC1LT3 through 
Alternative PC6LT8. SO2 increases are largely due to higher 
upstream emissions associated with electricity use by greater numbers 
of electrified vehicles being produced in response to the standards.
    Under each CAFE standard action alternative compared to the CAFE 
No-Action Alternative, the largest relative increases in emissions 
among the criteria pollutants would occur for SO2, for which 
emissions would increase by as much as 16.8 percent under Alternative 
PC6LT8 in 2035 compared to the CAFE No-Action Alternative. The largest 
relative decreases in emissions would occur for CO, for which emissions 
would decrease by as much as 27.8 percent under Alternative PC6LT8 in 
2050 compared to the CAFE No-Action Alternative. Percentage increases 
and decreases in emissions of NOX, PM2.5, and 
VOCs would be less, as small as less than 1 percent. The smaller 
differences are not expected to lead to measurable changes in 
concentrations of criteria pollutants in the ambient air. The larger 
differences in emissions could lead to changes in ambient pollutant 
concentrations.
    In 2035, emissions of NOX, PM2.5, and 
SO2 increase under the HDPUV FE standard action alternatives 
compared to the HDPUV FE No-Action Alternative, while emissions of CO 
and VOCs decrease. Relative to the HDPUV FE No-Action Alternative, the 
modeling results suggest NOX, PM2.5, and 
SO2 emissions increases in 2035 get larger from Alternative 
HDPUV4 through Alternative HDPUV14 (the most stringent alternative in 
terms of the estimated required fuel consumption [gallons of fuel per 
100 ton-mile]). For CO and VOCs, the emissions decrease in 2035 get 
larger from Alternative HDPUV4 through Alternative HDPUV14 relative to 
the HDPUV FE No-Action Alternative.
    In 2050, emissions of NOX and SO2 increase 
under all HDPUV FE standard action alternatives compared to the HDPUV 
FE No-Action Alternative, and the increases get larger from Alternative 
HDPUV4 through Alternative HDPUV14. Emissions of CO, PM2.5, 
and VOCs decrease under all action alternatives compared to the HDPUV 
FE No-Action Alternative, and the decreases get larger from Alternative 
HDPUV4 through Alternative HDPUV14. Under each HDPUV FE standard action 
alternative compared to the HDPUV FE No-Action Alternative, the largest 
relative increases in emissions among the criteria pollutants would 
occur for SO2, for which emissions would increase by as much 
as 4.2 percent under Alternative HDPUV14 in 2050 compared to the HDPUV 
FE No-Action Alternative. The largest relative decreases in emissions 
would occur for CO and VOCs, for which emissions would decrease by as 
much as 5.7 percent under Alternative HDPUV14 in 2050 compared to the 
HDPUV FE No-Action Alternative. Percentage increases and reductions in 
emissions of NOX and PM2.5 would be less, as 
small as less than 1 percent. The smaller differences are not expected 
to lead to measurable changes in concentrations of criteria pollutants 
in the ambient air. The larger differences in emissions could lead to 
changes in ambient pollutant concentrations.
(f) Toxic Air Pollutants
    Under each CAFE standard action alternative in 2035 and 2050 
relative to the CAFE No-Action Alternative, decreases in emissions 
would occur for all toxic air pollutants. The decreases get larger from 
Alternative PC1LT3 through Alternative PC6LT8. The largest relative 
decreases in emissions would occur for acetaldehyde, acrolein, 1,3-
butadiene, and formaldehyde, for which emissions would decrease by as 
much as 36 percent under Alternative PC6LT8 in 2050. Percentage 
decreases in emissions of benzene and diesel particulate matter (DPM) 
would be less, in some cases less than 1 percent.
    Under each HDPUV FE standard action alternative in 2035 and 2050 
relative to the HDPUV FE No-Action Alternative, emissions either remain 
the same or decrease for all toxic air pollutants. The decreases get 
larger from Alternative HDPUV4 through Alternative HDPUV14. The largest 
relative decreases in national emissions of toxic air pollutants among 
the HDPUV FE standard action alternatives, compared to the HDPUV FE No-
Action Alternative, generally would occur for acetaldehyde, acrolein, 
benzene, 1,3-butadiene, and formaldehyde, for which emissions would 
decrease by as much as 7 percent under Alternative HDPUV14 in 2050. 
Percentage decreases in emissions of DPM would be less, in some cases 
less than 1 percent.
(g) Health Impacts
    In 2035 and 2050, all CAFE standard action alternatives would 
result in decreases in adverse health impacts (mortality, acute 
bronchitis, respiratory emergency room visits, and other health 
effects) nationwide compared to the CAFE No-Action Alternative. The 
improvements to health impacts (or decreases in health incidences) 
would get larger from Alternative PC1LT3 to Alternative PC6LT8 in 2035 
and 2050. These decreases reflect the generally increasing stringency 
of the action alternatives as they become implemented.
    In 2035 and 2050, all HDPUV FE standard action alternatives would 
remain the same or decrease nationwide compared to the HDPUV FE No-
Action Alternative.
(2) Cumulative Impacts
(h) Criteria Pollutants
    In 2035, emissions of NOX, PM2.5, and 
SO2 increase under the CAFE and HDPUV FE alternative 
combinations compared to the No-Action Alternatives, while emissions of 
CO and VOCs decrease. Relative to the No-Action Alternatives, the 
modeling results suggest NOX, PM2.5, and 
SO2 emissions increases in 2035 get smaller from 
Alternatives PC1LT3 and HDPUV4 to Alternatives PC2LT4 and HDPUV10, then 
larger from Alternatives PC2LT4 and HDPUV10 to Alternatives PC6LT8 and 
HDPUV14 (the combination of the most stringent CAFE and HDPUV FE 
standard alternatives). For CO and VOCs, the emissions decrease in 2035 
get smaller from Alternatives PC1LT3 and HDPUV4 to Alternatives PC2LT4 
and HDPUV10, then larger from Alternatives PC2LT4 and HDPUV10 to 
Alternatives PC6LT8 and HDPUV14, relative to the No-Action 
Alternatives.
    In 2050, emissions of NOX decrease under Alternatives 
PC1LT3 and HDPUV4 and Alternatives PC2LT4 and HDPUV10 but increase 
under Alternatives PC6LT8 and HDPUV14, compared to the No-Action 
Alternatives. Emissions of SO2 decrease under Alternatives 
PC1LT3 and HDPUV4 but increase under Alternatives PC2LT4 and HDPUV10 
and Alternatives PC6LT8 and HDPUV14, compared to the No-Action 
Alternatives. Emissions of CO, PM2.5, and VOCs decrease 
under all CAFE and HDPUV alternative combinations compared to the No-
Action Alternatives, and the decreases get larger from Alternatives 
PC1LT3 and HDPUV4 through Alternatives PC6LT8 and HDPUV14 for CO and 
VOCs, while the decreases for PM2.5 get smaller from 
Alternatives PC1LT3 and HDPUV4 to Alternatives PC2LT4 and HDPUV10, and 
then larger from Alternatives PC2LT4 and HDPUV10 to Alternatives PC6LT8 
and HDPUV14, compared to the No-Action Alternatives.
    Under each CAFE and HDPUV FE alternative combination compared to 
the No-Action Alternatives, the largest relative increases in emissions 
among the criteria pollutants would occur for SO2, for which 
emissions would increase by as much as 15.2 percent

[[Page 56325]]

under Alternatives PC6LT8 and HDPUV14 in 2035, compared to the No-
Action Alternatives. The largest relative decreases in emissions would 
occur for CO, for which emissions would decrease by as much as 25.2 
percent under Alternatives PC6LT8 and HDPUV14 in 2050, compared to the 
No-Action Alternatives. Percentage increases and decreases in emissions 
of NOX and PM2.5 would be less, as small as less 
than 1 percent. The smaller differences are not expected to lead to 
measurable changes in concentrations of criteria pollutants in the 
ambient air. The larger differences in emissions could lead to changes 
in ambient pollutant concentrations.
(b) Toxic Air Pollutants
    Toxic air pollutant emissions across the CAFE and HDPUV FE 
alternative combinations remain the same or decrease in 2035 and 2050, 
relative to the No-Action Alternatives. The decreases in 2035 get 
smaller from Alternatives PC1LT3 and HDPUV4 to Alternatives PC2LT4 and 
HDPUV10 and then larger from Alternatives PC2LT4 and HDPUV10 to 
Alternatives PC6LT8 and HDPUV14; the decreases in 2050 get larger from 
Alternatives PC1LT3 and HDPUV4 through Alternatives PC6LT8 and HDPUV14.
    The largest relative decreases in emissions generally would occur 
for acetaldehyde, acrolein, benzene, 1,3-butadiene, and formaldehyde, 
for which emissions would decrease by as much as 29 percent under 
Alternatives PC6LT8 and HDPUV14 in 2050, compared to the No-Action 
Alternatives. Percentage decreases in emissions of DPM would be less, 
as small as less than 1 percent.
(c) Health Impacts
    Adverse health impacts (mortality, acute bronchitis, respiratory 
emergency room visits, and other health effects) from criteria 
pollutant emissions would remain the same or decrease nationwide in 
2035 and 2050 under all CAFE and HDPUV FE alternative combinations, 
relative to the No-Action Alternatives. The improvements to health 
impacts (or decreases in health incidences) in 2035 would get smaller 
or stay the same from Alternatives PC1LT3 and HDPUV4 to Alternatives 
PC2LT4 and HDPUV10 and then get larger from Alternatives PC2LT4 and 
HDPUV10 to Alternatives PC6LT8 and HDPUV14. In 2050, the improvements 
would get larger from Alternatives PC1LT3 and HDPUV4 to Alternatives 
PC6LT8 and HDPUV14. These decreases reflect the generally increasing 
stringency of the CAFE and HDPUV FE standard action alternatives as 
they become implemented.
    As mentioned above, changes in assumptions about modeled technology 
adoption; the relative proportions of gasoline, diesel, and other fuels 
in total fuel consumption changes; and changes in VMT from the rebound 
effect would alter these health impact results; however, NHTSA believes 
that these assumptions are reasonable.
c. Greenhouse Gas Emissions and Climate Change
(1) Direct and Indirect Impacts
    In terms of climate effects, the action alternatives would decrease 
both U.S. passenger car and light truck, and HDPUV fuel consumption and 
CO2 emissions compared with the relevant No-Action 
Alternative, resulting in reductions in the anticipated increases in 
global CO2 concentrations, temperature, precipitation, sea 
level, and ocean acidification that would otherwise occur. They would 
also, to a small degree, reduce the impacts and risks associated with 
climate change. The impacts of the action alternatives on atmospheric 
CO2 concentration, global mean surface temperature, 
precipitation, sea level, and ocean pH would be small in relation to 
global emissions trajectories. Although these effects are small, they 
occur on a global scale and are long lasting; therefore, in aggregate, 
they can have large consequences for health and welfare and can make an 
important contribution to reducing the risks associated with climate 
change.
(a) Greenhouse Gas Emissions
    The CAFE standard action alternatives would have the following 
impacts related to GHG emissions: Passenger cars and light trucks are 
projected to emit 52,800 million metric tons of carbon dioxide 
(MMTCO2) from 2027 through 2100 under the CAFE No-Action 
Alternative. Compared to the No-Action Alternative, projected emissions 
reductions from 2027 to 2100 under the CAFE action alternatives would 
range from 300 to 8,600 MMTCO2. Under Alternative PC2LT4, 
emissions reductions from 2027 to 2100 are projected to be 1,100 
MMTCO2. The CAFE action alternatives would reduce total 
CO2 emissions from U.S. passenger cars and light trucks by a 
range of 0.6 to 16.3 percent from 2027 to 2100 compared to the CAFE No-
Action Alternative. Alternative PC2LT4 would decrease these emissions 
by 2.1 percent through 2100. All CO2 emissions estimates 
associated with the CAFE standard action alternatives include upstream 
emissions.
    The HDPUV FE standard action alternatives would have the following 
impacts related to GHG emissions: HDPUVs are projected to emit 9,800 
million metric tons of carbon dioxide (MMTCO2) from 2027 
through 2100 under the HDPUV FE No-Action Alternative. Compared to the 
No-Action Alternative, projected emissions reductions from 2027 to 2100 
under the HDPUV action alternatives would range from 0 to 400 
MMTCO2. Under Alternative HDPUV10, emissions reductions from 
2027 to 2100 are projected to be 100 MMTCO2. The action 
alternatives would decrease these emissions by a range of less than 0.1 
percent under HDPUV4 to 4.1 percent under HDPUV14 through 2100. 
Alternative HDPUV10 would decrease these emissions by 1 percent over 
the same period. All CO2 emissions estimates associated with 
the HDPUV FE standard action alternatives include upstream emissions.
    Compared with total projected CO2 emissions of 559 
MMTCO2 from all passenger cars and light trucks under the 
CAFE No-Action Alternative in the year 2100, the CAFE standard action 
alternatives are expected to decrease CO2 emissions from 
passenger cars and light trucks in the year 2100 less than 1 percent 
under Alternative PC1LT3, 7 percent under Alternative PC3LT5, and 21 
percent under Alternative PC6LT8. Under Alternative PC2LT4, the 2100 
total projected CO2 emissions for all passenger cars and 
light trucks are 546 MMTCO2, reflecting a 2 percent 
decrease.
    Compared with total projected CO2 emissions of 115 
MMTCO2 from all HDPUVs under the HDPUV FE No-Action 
Alternative in the year 2100, the HDPUV FE standard action alternatives 
are expected to decrease CO2 emissions from HDPUVs in the 
year 2100 by a range of less than 1 percent under Alternative HDPUV4 to 
5 percent under Alternative HDPUV14. Under Alternative HDPUV10, the 
2100 total projected CO2 emissions for all HDPUVs are 113 
MMTCO2, reflecting a 2 percent decrease.
    To estimate changes in CO2 concentrations and global 
mean surface temperature, NHTSA used a reduced-complexity climate model 
(MAGICC). The reference scenario used in the direct and indirect 
analysis is the SSP3-7.0 scenario, which the Intergovernmental Panel on 
Climate Change (IPCC) describes as a high emissions scenario that 
assumes no successful, comprehensive global actions to mitigate GHG 
emissions and

[[Page 56326]]

yields atmospheric CO2 levels of 800 ppm and an effective 
radiative forcing (ERF) of 7.0 watts per square meter (W/m\2\) in 2100. 
Compared to SSP3-7.0 total global CO2 emissions projection 
of 4,991,547 MMTCO2 under the CAFE No-Action Alternative 
from 2027 through 2100, the CAFE standard action alternatives are 
expected to reduce global CO2 by 0.01 percent under 
Alternative PC1LT3, 0.02 percent under Alternative PC2LT4, 0.06 percent 
under Alternative PC3LT5, and 0.17 percent under Alternative PC6LT8 by 
2100.
    Compared to SSP3-7.0 total global CO2 emissions 
projection of 4,991,547 MMTCO2 under the HDPUV No-Action 
Alternative from 2027 through 2100, the HDPUV action alternatives are 
expected to reduce global CO2 by less than 0.01 percent 
under Alternatives HDPUV4 and HDPUV10, and 0.01 percent under 
Alternative HDPUV14 by 2100.
    The emissions reductions from all passenger cars and light trucks 
in 2035 compared with emissions under the CAFE No-Action Alternative 
are approximately equivalent to the annual emissions from 2,481,083 
vehicles under Alternative PC1LT3, 4,006,611 vehicles under Alternative 
PC2LT4, 8,125,856 vehicles under Alternative PC3LT5, and 21,921,146 
vehicles under Alternative PC6LT8. (A total of 260,514,221 passenger 
cars and light trucks are projected to be on the road in 2035 under the 
No-Action Alternative).
    The emissions reductions from HDPUVs in 2032 compared with 
emissions under the HDPUV FE No-Action Alternative are approximately 
equivalent to the annual emissions from 2,325 vehicles under 
Alternative HDPUV4, 59,962 vehicles under Alternative HDPUV10, and 
297,812 vehicles under Alternative HDPUV14. (A total of 18,607,101 
HDPUVs are projected to be on the road in 2032 under the No-Action 
Alternative.)
(b) Climate Change Indicators (Carbon Dioxide Concentration, Global 
Mean Surface Temperature, Sea Level, Precipitation, and Ocean pH)
    CO2 emissions affect the concentration of CO2 
in the atmosphere, which in turn affects global temperature, sea level, 
precipitation, and ocean pH. For the analysis of direct and indirect 
impacts, NHTSA used the SSP3-7.0 scenario to represent the RC emissions 
scenario (i.e., future global emissions assuming no comprehensive 
global actions to mitigate GHG emissions). NHTSA selected the SSP3-7.0 
scenario for its incorporation of a comprehensive suite of GHG and 
pollutant gas emissions, including carbonaceous aerosols and a global 
context of emissions with a full suite of GHGs and ozone precursors.
    The CO2 concentrations under the SSP3-7.0 emissions 
scenario in 2100 are estimated to be 838.31 ppm under the CAFE No-
Action Alternative. CO2 concentrations under the CAFE 
standard action alternatives could reach 837.48 ppm under Alternative 
PC6LT8, indicating a maximum atmospheric CO2 decrease of 
approximately 0.83 ppm compared to the CAFE No-Action Alternative. 
Atmospheric CO2 concentrations under Alternative PC1LT3 
would decrease by 0.03 ppm compared with the CAFE No-Action 
Alternative.
    Under the HDPUV FE standard action alternatives, CO2 
concentrations under the SSP3-7.0 emissions scenario in 2100 are 
estimated to decrease to 838.27 ppm under Alternative HDPUV14, 
indicating a maximum atmospheric CO2 decrease of 
approximately 0.04 ppm compared to the HDPUV FE No-Action Alternative. 
Atmospheric CO2 concentrations under Alternative HDPUV4 
would decrease by 0.01 ppm compared with the HDPUV FE No-Action 
Alternative.
    Under the SSP3-7.0 emissions scenario, global mean surface 
temperature is projected to increase by approximately 4.34 [deg]C (7.81 
[deg]F) under the CAFE No-Action Alternative by 2100. Implementing the 
most stringent alternative (Alternative PC6LT8) would decrease this 
projected temperature rise by 0.004 [deg]C (0.007 [deg]F), while 
Alternative PC1LT3 would decrease projected temperature rise by 0.001 
[deg]C (0.002 [deg]F).
    Under the SSP3-7.0 emissions scenario, global mean surface 
temperature is projected to increase by approximately 4.34 [deg]C (7.81 
[deg]F) under the HDPUV FE No-Action Alternative by 2100. The range of 
temperature increases under the HDPUV FE standard action alternatives 
would decrease this projected temperature rise by a range of less than 
0.0001 [deg]C (0.0002 [deg]F) under Alternative HDPUV4 to 0.0002 [deg]C 
(0.003 [deg]F) under Alternative HDPUV14.
    Under the CAFE standard action alternatives, projected sea-level 
rise in 2100 under the SSP3-7.0 scenario ranges from a high of 83.24 
centimeters (32.77 inches) under the CAFE No-Action Alternative to a 
low of 83.16 centimeters (32.74 inches) under Alternative PC6LT8. 
Alternative PC6LT8 would result in a decrease in sea-level rise equal 
to 0.08 centimeter (0.03 inch) by 2100 compared with the level 
projected under the CAFE No-Action Alternative. Alternative PC1LT3 
would result in a decrease of less than 0.01 centimeter (0.004 inch) 
compared with the CAFE No-Action Alternative.
    Under the HDPUV FE standard action alternatives, projected sea-
level rise in 2100 under the SSP3-7.0 scenario varies less than .01 
centimeter (.004 inch) from a high of 83.24 centimeters (32.77 inches) 
under HDPUV FE No-Action Alternative.
    Under the SSP3-7.0 scenario, global mean precipitation is 
anticipated to increase by 7.42 percent by 2100 under the CAFE No-
Action Alternative. Under the CAFE standard action alternatives, this 
increase in precipitation would be reduced by 0.00 to 0.01 percent.
    Under the SSP3-7.0 scenario, global mean precipitation is 
anticipated to increase by 7.42 percent by 2100 under the HDPUV FE No-
Action Alternative. HDPUV FE standard action alternatives would see a 
reduction in precipitation in the range of 0.00 to 0.01 percent.
    Under the SSP3-7.0 scenario, ocean pH in 2100 is anticipated to be 
8.1937 under Alternative PC6LT8, about 0.0004 more than the CAFE No-
Action Alternative. Under Alternative PC1LT3, ocean pH in 2100 would be 
8.1933, or less than 0.0001 more than the CAFE No-Action Alternative.
    Under the SSP3-7.0 scenario, ocean pH in 2100 is anticipated to be 
8.1933 under Alternative HDPUV14, or less than 0.0001 more than the 
HDPUV FE No-Action Alternative.
    The action alternatives for both CAFE and HDPUV FE standards would 
reduce the impacts of climate change that would otherwise occur under 
the No-Action Alternative. Although the projected reductions in 
CO2 and climate effects are small compared with total 
projected future climate change, they are quantifiable and 
directionally consistent and would represent an important contribution 
to reducing the risks associated with climate change.
(2) Cumulative Impacts
(a) Greenhouse Gas Emissions
    The CAFE and HDPUV alternative combinations would have the 
following impacts related to GHG emissions: Projections of total 
emissions reductions from 2027 to 2100 under the CAFE and HDPUV 
alternative combinations and other reasonably foreseeable future 
actions compared with the No-Action Alternatives range from 300 
MMTCO2 under Alternatives PC1LT3 and HDPUV4 to 9,000 
MMTCO2 under Alternatives PC6LT8 and HDPUV14. Under 
Alternatives PC2LT4 and HDPUV10, emissions reductions from 2027 to 2100 
are projected to be 1,200 MMTCO2. The action alternatives 
would decrease total vehicle emissions by between 0.5 percent under 
Alternatives PC1LT3 and HDPUV4 and 14.4 percent

[[Page 56327]]

under Alternatives PC6LT8 and HDPUV14 by 2100. Alternatives PC2LT4 and 
HDPUV10 would decrease these emissions by 1.9 percent over the same 
period. Compared with projected total global CO2 emissions 
of 2,484,191 MMTCO2 from all sources from 2027 to 2100 using 
the moderate climate scenario, the incremental impact of this 
rulemaking is expected to decrease global CO2 emissions 
between 0.01 percent under Alternatives PC1LT3 and HDPUV4 and 0.36 
percent under Alternatives PC6LT8 and HDPUV14 by 2100. Alternatives 
PC2LT4 and HDPUV10 would decrease these emissions by .05 percent over 
the same period.
(b) Climate Change Indicators (Carbon Dioxide Concentration, Global 
Mean Surface Temperature, Sea Level, Precipitation, and Ocean pH)
    Estimated atmospheric CO2 concentrations in 2100 range 
from 587.78 ppm under the No-Action Alternatives to 587.00 ppm under 
Alternatives PC6LT8 and HDPUV14 (the combination of the most stringent 
CAFE and HDPUV FE standard alternatives). This is a decrease of 0.78 
ppm compared with the No-Action Alternatives.
    Global mean surface temperature decreases for the CAFE and HDPUV 
alternative combinations compared with the No-Action Alternatives in 
2100 range from a low of less than 0.001 [deg]C (0.002 [deg]F) under 
Alternatives PC1LT3 and HDPUV4 to a high of 0.004 [deg]C (0.007 [deg]F) 
under Alternatives PC6LT8 and HDPUV14.
    Global mean precipitation is anticipated to increase 6.11 percent 
under the No-Action Alternatives, with the CAFE and HDPUV alternative 
combinations reducing this effect up to 0.01 percent.
    Projected sea-level rise in 2100 ranges from a high of 67.12 
centimeters (26.42 inches) under the No-Action Alternatives to a low of 
67.03 centimeters (26.39 inches) under Alternatives PC6LT8 and HDPUV14, 
indicating a maximum decrease in projected sea-level rise of 0.08 
centimeter (0.03 inch) by 2100.
    Ocean pH in 2100 is anticipated to be 8.3333 under Alternatives 
PC6LT8 and HDPUV14, about 0.005 less than the No-Action Alternatives.
(c) Health, Societal, and Environmental Impacts of Climate Change
    The action alternatives would reduce the impacts of climate change 
that would otherwise occur under the No-Action Alternatives. The 
magnitude of the changes in climate effects that would be produced by 
the most stringent action alternatives combination, which are 
Alternatives PC6LT8 and HDPUV14. Using the three-degree sensitivity 
analysis by the year 2100 CO2 would have a .78 ppm lower 
concentration, a four-thousandths-of-a-degree increase in the rate of 
temperature rise, a small percentage change in the rate of 
precipitation increase, between 0.10 and 0.11 centimeter (0.04 inch) 
decrease in projected sea-level rise, and an increase of 0.0005 in 
ocean pH. Although the projected reductions in CO2 and 
climate effects are small compared with total projected future climate 
change, they are quantifiable, directionally consistent, and would 
represent an important contribution to reducing the risks associated 
with climate change.
    Although NHTSA does quantify the changes in monetized damages that 
can be attributable to each action alternative, many specific impacts 
of climate change on health, society, and the environment cannot be 
estimated quantitatively. Therefore, NHTSA provides a qualitative 
discussion of these impacts by presenting the findings of peer-reviewed 
panel reports including those from IPCC, the Global Change Research 
Program, the Climate Change Science Program, the NRC, and the Arctic 
Council, among others. While the action alternatives would decrease 
growth in GHG emissions and reduce the impact of climate change across 
resources relative to the No-Action Alternative, they would not 
themselves prevent climate change and associated impacts. Long-term 
climate change impacts identified in the scientific literature are 
briefly summarized below, and vary regionally, including in scope, 
intensity, and directionality (particularly for precipitation). While 
it is difficult to attribute any particular impact to emissions that 
could result from this rulemaking, the following impacts are likely to 
be beneficially affected to some degree by reduced emissions from the 
action alternatives:
     Freshwater Resources: Projected risks to freshwater 
resources are expected to increase due to changing temperature and 
precipitation patterns as well as the intensification of extreme events 
like floods and droughts, affecting water security in many regions of 
the world and exacerbating existing water-related vulnerabilities.
     Terrestrial and Freshwater Ecosystems: Climate change is 
affecting terrestrial and freshwater ecosystems, including their 
component species and the services they provide. This impact can range 
in scale (from individual to population to species) and can affect all 
aspects of an organism's life, including its range, phenology, 
physiology, and morphology.
     Ocean Systems, Coasts, and Low[hyphen]Lying Areas: Climate 
change-induced impacts on the physical and chemical characteristics of 
oceans (primarily through ocean warming and acidification) are exposing 
marine ecosystems to unprecedented conditions and adversely affecting 
life in the ocean and along its coasts. Anthropogenic climate change is 
also worsening the impacts on non-climatic stressors, such as habitat 
degradation, marine pollution, and overfishing.
     Food, Fiber, and Forest Products: Through its impacts on 
agriculture, forestry and fisheries, climate change adversely affects 
food availability, access, and quality, and increases the number of 
people at risk of hunger, malnutrition, and food insecurity.
     Urban Areas: Extreme temperatures, extreme precipitation 
events, and rising sea levels are increasing risks to urban 
communities, their health, wellbeing, and livelihood, with the 
economically and socially marginalized being most vulnerable to these 
impacts.
     Rural Areas: A high dependence on natural resources, 
weather-dependent livelihood activities, lower opportunities for 
economic diversity, and limited infrastructural resources subject rural 
communities to unique vulnerabilities to climate change impacts.
     Human Health: Climate change can affect human health, 
directly through mortality and morbidity caused by heatwaves, floods 
and other extreme weather events, changes in vector-borne diseases, 
changes in water and food-borne diseases, and impacts on air quality as 
well as through indirect pathways such as increased malnutrition and 
mental health impacts on communities facing climate-induced migration 
and displacement.
     Human Security: Climate change threatens various 
dimensions of human security, including livelihood security, food 
security, water security, cultural identity, and physical safety from 
conflict, displacement, and violence. These impacts are interconnected 
and unevenly distributed across regions and within societies based on 
differential exposure and vulnerability.
     Stratospheric Ozone: There is strong evidence that 
anthropogenic influences, particularly the addition of GHGs and ozone-
depleting substances to the atmosphere, have led to a detectable 
reduction in stratospheric ozone concentrations and contributed to 
tropospheric warming and related

[[Page 56328]]

cooling in the lower stratosphere. These changes in stratospheric ozone 
have further influenced the climate by affecting the atmosphere's 
temperature structure and circulation patterns.
     Compound events: Compound events consist of combinations 
of multiple hazards that contribute to amplified societal and 
environmental impacts. Observations and projections show that climate 
change may increase the underlying probability of compound events 
occurring. To the extent the Proposed Action and alternatives would 
decrease the rate of CO2 emissions relative to the relevant 
No-Action Alternative, they would contribute to the general decreased 
risk of extreme compound events. While this rulemaking alone would not 
necessarily decrease compound event frequency and severity from climate 
change, it would be one of many global actions that, together, could 
reduce these effects.
     Tipping Points and Abrupt Climate Change: Tipping points 
represent thresholds within Earth systems that could be triggered by 
continued increases in the atmospheric concentration of GHGs, 
incremental increases in temperature, or other relatively small or 
gradual changes related to climate change. For example, the melting of 
the Greenland ice sheet, Arctic sea-ice loss, destabilization of the 
West Antarctic ice sheet, and deforestation in the Amazon and dieback 
of boreal forests are seen as potential tipping points that can cause 
large-scale, abrupt changes in the climate system and lead to 
significant impacts on human and natural systems. We note that all of 
these adverse effects would be mitigated to some degree by our proposed 
standards.
2. Conclusion
    In most cases, NHTSA presents the findings of a literature review 
of scientific studies in the Draft EIS, such as in Chapter 6, where 
NHTSA provides a literature synthesis focusing on existing credible 
scientific information to evaluate the most significant lifecycle 
environmental impacts from some of the technologies that may be used to 
comply with the alternatives. In Chapter 6, NHTSA describes the life-
cycle environmental implications related to the vehicle cycle phase 
considering the materials and technologies (e.g., batteries) that NHTSA 
forecasts vehicle manufacturers might use to comply with the CAFE and 
HDPUV FE standards. In Chapter 7, NHTSA discusses EJ and qualitatively 
describes potential disproportionate impacts on low-income and minority 
populations. In Chapter 8, NHTSA qualitatively describes potential 
impacts on historic and cultural resources. In these chapters, NHTSA 
concludes that impacts would vary between the action alternatives. 
Based on the foregoing, NHTSA concludes from the Draft EIS that 
Alternative PC6LT8 is the overall environmentally preferable 
alternative for MYs 2027-2032 CAFE standards and Alternative HDPUV14 is 
the overall environmentally preferable alternative for MYs 2030-2035 
HDPUV FE standards because, assuming full compliance were achieved 
regardless of NHTSA's assessment of the costs to industry and society, 
it would result in the largest reductions in fuel use and 
CO2 emissions among the alternatives considered. In 
addition, Alternative PC6LT8 and Alternative HDPUV14 would result in 
lower overall emissions levels over the long term of criteria air 
pollutants and of the toxic air pollutants studied by NHTSA. Impacts on 
other resources would be proportional to the impacts on fuel use and 
emissions, as further described in the Draft EIS, with Alternative 
PC6LT8 and Alternative HDPUV10 being expected to have the fewest 
negative environmental impacts. Although the CEQ regulations require 
NHTSA to identify the environmentally preferable alternative, NHTSA 
need not adopt it, as described above. The following section explains 
how NHTSA balanced the relevant factors to determine which alternative 
represented the maximum feasible standards, including why NHTSA does 
not believe that the environmentally preferable alternative is maximum 
feasible.
    NHTSA is informed by the discussion above and the Draft EIS in 
arriving at its tentative conclusion that Alternative PC2LT4 and 
HDPUV10 is maximum feasible, as discussed below. The following section 
(Section VI.D) explains how NHTSA balanced the relevant factors to 
determine which alternatives represented the maximum feasible standards 
for passenger cars, light trucks, and HDPUVs.

D. Evaluating the EPCA/EISA Factors and Other Considerations To Arrive 
at the Proposed Standards

    Accounting for all of the information presented in this preamble, 
in the Draft TSD, in the PRIA, and in the Draft EIS, consistent with 
our statutory authorities, NHTSA continues to approach the decision of 
what standards would be ``maximum feasible'' as a balancing of relevant 
factors and information, both for passenger cars and light trucks, and 
for HDPUVs. The different regulatory alternatives considered in this 
proposal represent different balancings of the factors--for example, 
PC1LT3, an alternative less stringent than the preferred alternative, 
would represent a balancing in which NHTSA determined that economic 
practicability significantly outweighed the need of the U.S. to 
conserve energy for purposes of the rulemaking time frame. By contrast, 
PC6LT8, a more stringent alternative, would represent a balancing in 
which NHTSA determined that the need of the U.S. to conserve energy 
significantly outweighed economic practicability during the same 
period. Because the statutory factors that NHTSA must consider are 
slightly different between passenger cars and light trucks on the one 
hand, and HDPUVs on the other, the following sections separate the 
segments and describe NHTSA's balancing approach for each proposal.
1. Passenger Cars and Light Trucks
    NHTSA's purpose in setting CAFE standards is to conserve energy, as 
directed by EPCA/EISA. Energy conservation provides many benefits to 
the American public, including better protection for consumers against 
changes in fuel prices, significant fuel savings and reduced impacts 
from harmful pollution. NHTSA continues to believe that strong fuel 
economy standards function as an important insurance policy against oil 
price volatility, particularly to protect consumers even as the U.S. 
has improved its energy independence over time. The U.S. participates 
in the global market for oil and petroleum fuels. As a market 
participant--on both the demand and supply sides--the nation is exposed 
to fluctuations in that market. The fact that the U.S. may produce more 
petroleum in a given period does not in and of itself protect the 
nation from the consequences of these fluctuations. Accordingly, the 
nation must conserve petroleum and reduce the oil intensity of the 
economy to insulate itself from the effects of market volatility. The 
primary mechanism for doing so in the transportation sector is to 
continue to improve fleet fuel economy. In addition, better fuel 
economy saves consumers money at the gas pump. For example, our 
preferred alternative would reduce fuel consumption by 88 billion 
gallons through CY 2050 and save buyers of new MY 2032 vehicles an 
average of $1,043 in gasoline over the lifetime of the vehicle. 
Moreover, as climate change progresses, the U.S. may face new energy-
related security risks if climate effects exacerbate geopolitical 
tensions and destabilization. Thus, mitigating climate effects by 
increasing fuel economy standards, as all of the action

[[Page 56329]]

alternatives in this proposal would do, can also potentially improve 
energy security.
    Maximum feasible CAFE standards look to balance the need of the 
U.S. to conserve energy with the technological feasibility and economic 
impacts of more stringent standards, while also considering other motor 
vehicle standards of the Government that may affect automakers' ability 
to meet CAFE standards. In order to comply with our statutory 
constraints, NHTSA disallows the application of BEVs (and other 
dedicated AFVs) in our analysis in response to potential new CAFE 
standards, and PHEVs are applied only with their charge-sustaining mode 
fuel economy.
    In considering this proposal, NHTSA is mindful of the fact that the 
standards for MYs 2024-2026 included year-by-year improvements compared 
to the standards established in 2020 that were faster than had been 
typical since the inception of the CAFE program in the late 1970s and 
early 1980s. Those standards were intended to correct for the lack of 
adequate consideration of the need for energy conservation in the 2020 
rule and were intended to reestablish the appropriate level of 
consideration of these effects that had been included in the initial 
2012 rule. Thus, though the standards increased significantly when 
compared to the 2020 rule, they were comparable to the standards that 
were initially projected as augural standards for the MYs included in 
the 2012 final rule. The world has changed considerably in some ways, 
but less so in others. Since May 2022, the U.S. economy continues to 
have strengths and weaknesses; the auto industry remains in the middle 
of a major transition for a variety of reasons besides the CAFE 
program. Similarly, our technical analysis has changed considerably in 
some ways, but less so in others. Since May 2022, NHTSA has updated 
technologies considered in our analysis (removing some, adding others); 
updated macroeconomic input assumptions as with each round of analysis; 
improved user control of various input parameters; updated its approach 
to modeling the ZEV program; expanded accounting for Federal 
incentives; expanded procedures for estimating new vehicle sales and 
fleet shares; updated inputs for projecting aggregate LD VMT; and added 
various output values and options. Further stringency increases at a 
comparable rate, immediately on the heels of the increases for MYs 
2024-2026, may therefore be beyond maximum feasible for MYs 2027-2032.
    NHTSA tentatively concludes Alternative PC2LT4 is the maximum 
feasible alternative that best balances all relevant factors for 
passenger cars and light trucks built in MYs 2027-2032. Energy 
conservation is still our paramount objective, for the consumer 
benefits, energy security benefits, and environmental benefits that it 
provides. NHTSA believes that a large percentage of the fleet will 
remain propelled by ICEs through 2032, despite the potential 
significant transformation being driven by reasons other than the CAFE 
standards. NHTSA believes that the alternative we are proposing will 
encourage those ICE vehicles produced during the standard-setting time 
frame to achieve and maintain significant fuel economies, improve 
energy security, and reduce GHG emissions and other air pollutants. At 
the same time, NHTSA is proposing standards that our estimates suggest 
will continue to reduce petroleum dependence, saving consumers money 
and fuel over the lifetime of their vehicles, particularly light truck 
buyers, among other benefits, while being economically practicable for 
manufacturers to achieve.
    Although Alternatives PC3LT5 and PC6LT8 would conserve more energy 
and provide greater fuel savings benefits and carbon dioxide emissions 
reductions, NHTSA currently estimates that those alternatives may 
simply not be achievable for many manufacturers in the rulemaking time 
frame, particularly given NHTSA's statutory restrictions on the 
technologies we may consider when determining maximum feasible 
standards. Additionally, compliance with those more stringent 
alternatives would impose significant costs on individual consumers 
without corresponding fuel savings benefits large enough to, on 
average, offset those costs. Within that framework, NHTSA's analysis 
suggests that the more stringent alternatives could push more 
technology application than would be economically practicable, given 
the rate of increase for the MYs 2024-2026 standards, given anticipated 
baseline activity on which our standards will be building, and given a 
realistic consideration of the rate of response industry is capable of 
achieving. In contrast to Alternatives PC3LT5 and PC6LT8, Alternative 
PC2LT4 comes at a cost we believe the market can bear, appears to be 
much more achievable, and will still result in consumer net benefits on 
average. The proposed alternative also achieves large fuel savings 
benefits and significant reductions in carbon dioxide emissions. NHTSA 
tentatively concludes Alternative PC2LT4 is a better choice than PC3LT5 
and PC6LT8 given these factors.
    The following text will walk through the four statutory factors in 
more detail and discuss NHTSA's decision-making process more 
thoroughly. The tentative balancing of factors presented here 
represents NHTSA's thinking at the present time, based on all of the 
information presented in the record for this proposal. NHTSA 
acknowledges that a different balancing may turn out to be appropriate 
for the final rule depending on information that arrives between now 
and then, both through the public comment process and otherwise. NHTSA 
seeks comment on this discussion and NHTSA's tentative conclusions.
    For context and the reader's reference, here again are the 
regulatory alternatives among which NHTSA has tentatively chosen 
maximum feasible CAFE standards for MYs 2027-2032, representing 
different annual rates of stringency increase over the required levels 
in MY 2026:

Table V-1--Regulatory Alternatives Under Consideration for MYs 2027-2032
                     Passenger Cars and Light Trucks
------------------------------------------------------------------------
                                           Passenger car    Light truck
                                            stringency      stringency
          Name of  alternative              increases,      increases,
                                            year- over-   year-over-year
                                             year (%)           (%)
------------------------------------------------------------------------
No-Action Alternative...................             n/a             n/a
Alternative PC1LT3......................               1               3
Alternative PC2LT4 (Preferred                          2               4
 Alternative)...........................
Alternative PC3LT5......................               3               5

[[Page 56330]]

 
Alternative PC6LT8......................               6               8
------------------------------------------------------------------------

    In evaluating the statutory factors to determine maximum feasible 
standards, EPCA's overarching purpose of energy conservation suggests 
that NHTSA should begin with the need of the U.S. to conserve energy. 
According to the analysis presented in Section IV and in the 
accompanying PRIA, Alternative PC6LT8 is estimated to save consumers 
the most in fuel costs. Even in the rulemaking time frame of MYs 2027-
2032, when many forces other than CAFE standards will foreseeably be 
driving higher rates of passenger car and light truck electrification, 
NHTSA believes that gasoline will still likely be the dominant fuel 
used in LD transportation. This means that consumers, and the economy 
more broadly, remain subject to fluctuations in gasoline price that 
impact the cost of travel and, consequently, the demand for mobility. 
The American economy is largely built around the availability of 
affordable personal transportation. Vehicles are long-lived assets, and 
the long-term price uncertainty and volatility of petroleum prices 
still represents a risk to consumers. By increasing the fuel economy of 
vehicles in the marketplace, more stringent CAFE standards help to 
better insulate consumers, and the economy more generally, against 
these risks over longer periods of time. Fuel economy improvements that 
reduce demand are an effective hedging strategy against price 
volatility, because gasoline prices are linked to global oil prices. 
Continuing to reduce the amount of money that consumers spend on 
vehicle fuel thus remains an important consideration for the need of 
the U.S. to conserve energy. Additionally, by reducing U.S. 
participation in global oil markets, fuel economy standards also 
improve U.S. energy security and our national balance of payments. 
Again, by reducing the most fuel consumed, Alternative PC6LT8 would 
likely best serve the need of the U.S. to conserve energy in these 
respects.
    With regard to pollution effects, Alternative PC6LT8 would also 
result in the greatest reduction in CO2 emissions over time, 
and thus have the largest (relative) impact on climate change. The 
effects of other pollutants are more mixed--while the emissions of 
NOX and PM2.5 eventually decrease over time, with 
effects being greater as stringency increases, SOX emissions 
increase in all action alternations as compared to the No-Action 
Alternative, again with effects being greater as stringency 
increases.\578\ Chapter 8.5 and 8.6 of the PRIA discuss estimated 
environmental effects of the regulatory alternatives in more detail.
---------------------------------------------------------------------------

    \578\ We note also that some of the increase in certain 
pollutants, notably SOX, results from estimated increases 
in electricity usage over time, as a result of greater 
electrification in the fleet, both in the baseline/No-Action 
Alternative and in the later years of the rulemaking analysis, 2040-
2050. While 49 U.S.C. 32902(h) prohibits NHTSA from considering the 
fuel economy of BEVs and the electric-only-operation fuel economy of 
PHEVs during the rulemaking time frame, NHTSA believes it would be 
remiss to fail to account for the emissions consequences of the 
energy consumed to power those vehicles. Fuel economy and emissions 
consequences are actually different things for purposes of this 
proposal and analysis--fuel economy is simply an input to 
calculating manufacturer compliance positions, while emissions are 
estimated based on estimated on-road vehicle use. Emissions are 
affected by fuel economy, but they are not literally fuel economy. 
Moreover, as explained, these specific emissions effects from 
greater electrification are extremely small, and even if the agency 
retained ``standard setting'' constraints through MY 2050, the 
effects would not be significant enough to change the agency's 
tentative determination of which regulatory alternative is maximum 
feasible for the rulemaking time frame. NHTSA notes that recent 
projections available since NHTSA finished modeling for this 
proposal show notable decreases in power sector emissions that would 
likely affect the CAFE Model emissions result. NHTSA intends to 
analyze those projections and update them for the final rule. 
Finally, NHTSA notes that power sector emissions projections using 
more up-to-date data do not project this increase in SOX 
emissions.
---------------------------------------------------------------------------

    These results are a direct consequence of the input assumptions 
used for this analysis, as well as the uncertainty surrounding these 
assumptions. However, both relative and absolute effects for 
NOX, PM2.5, and SOX under each 
regulatory alternative are quite small in the context of overall U.S. 
emissions of these pollutants, and even in the context of U.S. 
transportation sector emissions of these pollutants. CAFE standards are 
not a primary driver for these pollutants; the estimated effects 
instead come largely from potential changes in travel demand that may 
result from improved fuel economy, rather than from the standards 
themselves. NHTSA would thus say, generally speaking, that Alternative 
PC6LT8 likely best meets the need of the U.S. to conserve energy in 
terms of environmental effects, because it saves the most fuel, which 
consequently means that it (1) maximizes consumer savings on fuel 
costs, (2) reduces a variety of pollutant emissions by the greatest 
amount, and (3) most reduces U.S. participation in global oil markets, 
with attendant benefits to energy security and the national balance of 
payments.
    However, even though Alternative PC6LT8 may best meet the need of 
the U.S. to conserve energy, NHTSA is concerned that it may be beyond 
maximum feasible in the rulemaking time frame. NHTSA is arriving at the 
current tentative conclusion based on the other factors that we 
consider, because all of the statutory factors must be considered in 
determining maximum feasible CAFE standards. The need of the U.S. to 
conserve energy nearly always works in NHTSA's balancing to push 
standards more stringent, while other factors may work in the opposite 
direction.
    Specifically, based on the information currently available, NHTSA 
is concerned that the more stringent regulatory alternatives considered 
in this analysis may land past the point of economic practicability in 
this time frame. In considering economic practicability, NHTSA tries to 
evaluate where the tipping point in the balancing of factors might be 
through a variety of metrics and considerations, examined in more 
detail below. For example, if the amounts of technology or the per-
vehicle cost increases required to meet the standards appear to be 
beyond what we believe the market could bear in the relevant time 
frame; or sales and employment appear to be unduly impacted, NHTSA 
could decide that the future standards represented by a regulatory 
alternative under consideration may not be economically practicable.
    We underscore again that the modeling analysis does not dictate the

[[Page 56331]]

``answer,'' it is merely one source of information among others that 
aids NHTSA's balancing of the standards. We similarly underscore that 
there is no single bright line beyond which standards might be 
economically impracticable, and that these metrics are not intended to 
suggest one; they are simply ways to think about the information before 
us. The discussion of trying to identify a ``tipping point'' is simply 
an attempt to grapple with the information, and the ultimate decision 
rests with the decision-maker's discretion.
    While the need of the U.S. to conserve energy may encourage NHTSA 
to be more technology-forcing in its balancing, regulatory alternatives 
that can only be achieved by the extensive application of advanced 
technologies besides BEVs (that may have known or unknown consumer 
acceptance issues) may not be economically practicable in the MY 2027-
2032 time frame and may thus be beyond maximum feasible. Technology 
application can be considered as ``which technologies, and when''--both 
the technologies that NHTSA's analysis suggests would be used, and how 
that application occurs given manufacturers' product lifecycles. NHTSA 
does not mean to preclude the possibility that future fuel economy 
standards may be even more technology-forcing than the ones proposed 
here, because we anticipate that, among other things, consumer 
acceptance toward advanced fuel economy-improving technologies will 
continue to grow, as it is clearly doing at the present time. One 
important question would be how fast that consumer acceptance of 
advanced technologies grows, which is difficult to know in advance with 
much certainty. If consumer acceptance is outpaced by technological 
developments, it is possible that there could be sales impacts 
unforeseen by our analysis, and thus not accounted for in our decision-
making. It is crucially important to remember that NHTSA's decision-
making with regard to economic practicability and what standards are 
maximum feasible overall must be made in the context of the 32902(h) 
restrictions against considering the fuel economy of BEVs and the full 
fuel economy of PHEVs. Our results comply with those restrictions, and 
it is those results that inform NHTSA's decision-making.
    Additionally, as discussed in Section V.A, NHTSA is less certain in 
this proposal that some of the more stringent alternatives are 
technologically feasible, a point that was not a concern in prior 
rulemakings due to the state of technology development at that time. 
NHTSA has historically understood technological feasibility as 
referring to whether a particular method of improving fuel economy is 
available for deployment in commercial application in the MY for which 
a standard is being established. While all of the technology in NHTSA's 
analysis is already available for deployment, the statutory requirement 
to exclude fuel economy improvements due to electrification from 
consideration of maximum feasible standards means that NHTSA must focus 
on technology available to improve the fuel economy of ICEs, and on the 
remaining vehicles that are not yet anticipated to be fully electric 
during the rulemaking time frame. When excluding various forms of 
electrification, we believe that more stringent standards may not be 
technologically feasible. NHTSA seeks comment on this question. NHTSA 
also notes that whether or not such standards would be technologically 
feasible, they would likely not be economically practicable (and thus 
beyond maximum feasible).
    In terms of the levels of technology required and which 
technologies those may be, NHTSA's analysis estimates manufacturers' 
product ``cadence,'' representing them in terms of estimated schedules 
for redesigning and ``freshening'' vehicles, and assuming that 
significant technology changes will be implemented during vehicle 
redesigns--as they historically have been. Once applied, a technology 
will be carried forward to future MYs until superseded by a more 
advanced technology. If manufacturers are already applying technology 
widely and intensively to meet standards in earlier years, requiring 
them to add yet more technology (which may be less available and/or 
more expensive) in the MYs subject to the rulemaking may be less 
economically practicable. Conversely, if the preceding MYs require less 
technology, more technology during the rulemaking time frame may be 
more economically practicable.
    The tables below illustrate how NHTSA has modeled that process of 
manufacturers applying technologies to comply with different 
alternative standards. The Draft TSD accompanying this proposal 
described the technologies and corresponding input estimates (of, e.g., 
efficacy and cost) in detail in Chapter 3. The accompanying PRIA and 
appendices provide extensive detail regarding the estimated application 
of specific technologies to each manufacturer's fleets of passenger 
cars and light trucks in each MY. Finally, the underlying model outputs 
available on NHTSA's website provide estimates of the potential to 
apply specific technologies to specific vehicle model/configurations in 
each MY. We remind readers that the analysis represents estimates for 
purposes of determining feasibility, and that it does not provide ``the 
answer'' or mandate a specific technology path that industry must 
follow.
    The following two tables show average incremental application 
rates--that is, levels beyond those projected under the No-Action 
Alternative--by regulatory alternative for selected technologies, given 
the statutory constraints under which NHTSA must determine maximum 
feasible CAFE standards. For example, Alternative PC1LT3 would require 
hardly any technology application change for passenger cars, while 
Alternative PC6LT8 would require an additional 37 percent of the fleet 
to have strong hybrid technology and 49 percent to have advanced levels 
of MR by MY 2032 and would reduce the percentage of vehicles with 
advanced engines by 38 percentage points. Alternative PC2LT4 would 
require strong hybrids to increase by 8 percentage points by MY 2032, 
would decrease advanced engines by a similar amount, and would increase 
advanced MR by 19 percentage points.

         Table V-2--Estimated Application of Selected Technologies Relative to No-Action Alternative, Passenger Cars, Standard Setting Analysis
--------------------------------------------------------------------------------------------------------------------------------------------------------
                Technology                            Alternative             2022 (%)   2027 (%)   2028 (%)   2029 (%)   2030 (%)   2031 (%)   2032 (%)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Strong Hybrid (all types).................  PC1LT3                           .........         1%         2%         3%         2%         3%         3%
PHEV (all types)..........................  PC1LT3                           .........          0          0          0          0          0          0
Advanced Engines..........................  PC1LT3                           .........         -1         -2         -3         -2         -3         -3
Advanced AERO.............................  PC1LT3                           .........          0          1          1          1          1          1
Advanced MR...............................  PC1LT3                           .........          1         -1          2          4          6          7

[[Page 56332]]

 
Strong Hybrid (all types).................  PC2LT4                           .........          2          4          7          8          8          8
PHEV (all types)..........................  PC2LT4                           .........          0          0          0          0          0          0
Advanced Engines..........................  PC2LT4                           .........         -2         -4         -7         -8         -8         -8
Advanced AERO.............................  PC2LT4                           .........          0          1          1          1          1          1
Advanced MR...............................  PC2LT4                           .........          2          3          6         12         15         19
Strong Hybrid (all types).................  PC3LT5                           .........          2          5          9         10         12         12
PHEV (all types)..........................  PC3LT5                           .........          0          0          0          0          0          0
Advanced Engines..........................  PC3LT5                           .........         -2         -5         -9        -10        -12        -12
Advanced AERO.............................  PC3LT5                           .........          0          2          2          2          2          2
Advanced MR...............................  PC3LT5                           .........          4         11         15         21         26         32
Strong Hybrid (all types).................  PC6LT8                           .........          2         13         20         25         31         37
PHEV (all types)..........................  PC6LT8                           .........          0          0          0          1          1          1
Advanced Engines..........................  PC6LT8                           .........         -2        -14        -20        -26        -33        -38
Advanced AERO.............................  PC6LT8                           .........          0         10         10         10         10         14
Advanced MR...............................  PC6LT8                           .........          4         12         16         23         33         49
--------------------------------------------------------------------------------------------------------------------------------------------------------
Advanced Engines: Combined penetration of advanced cylinder deactivation, advanced turbo, variable compression ratio, high compression ratio, and diesel
  engines.\579\
Advanced AERO: Combined penetration of 15 and 20 percent aerodynamic improvement.
Advanced MR (mass reduction): Combined penetration of MR4 and MR5.

    For light trucks, Alternative PC1LT3 would require hardly any 
change in technology application, while Alternative PC6LT8 would 
require an additional 25 percent of the fleet to have strong hybrid 
technology and 57 percent to have advanced levels of MR by MY 2032. 
Alternative PC6LT8 would also reduce the percentage of vehicles with 
advanced engines by 38 percentage points. Alternative PC2LT4 would 
require strong hybrids to increase by 18 percentage points by MY 2032, 
would increase PHEVs \580\ by 13 percentage points, would decrease 
advanced engines by 25 percentage points, and would increase advanced 
MR by 38 percentage points.
---------------------------------------------------------------------------

    \579\ Specifically, this includes technologies with the 
following codes in the CAFE Model: TURBO0, TURBOE, TURBOD, TURBO1, 
TURBO2, ADEACD, ADEACS, HCR, HRCE, HCRD, VCR, VTG, VTGE, TURBOAD, 
ADSL, DSLI.
    \580\ We note again that PHEVs, for purposes of standard-setting 
analysis and this discussion of potential maximum feasible CAFE 
standards, are counted only in charge-sustaining mode, so that their 
electric-only operation is not counted, as required by 49 U.S.C. 
32902(h).
    \581\ Specifically, this includes technologies with the 
following codes in the CAFE Model: TURBO0, TURBOE, TURBOD, TURBO1, 
TURBO2, ADEACD, ADEACS, HCR, HRCE, HCRD, VCR, VTG, VTGE, TURBOAD, 
ADSL, DSLI.

          Table V-3--Estimated Application of Selected Technologies Relative to No-Action Alternative, Light Trucks, Standard Setting Analysis
--------------------------------------------------------------------------------------------------------------------------------------------------------
                Technology                            Alternative             2022 (%)   2027 (%)   2028 (%)   2029 (%)   2030 (%)   2031 (%)   2032 (%)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Strong Hybrid (all types).................  PC1LT3                           .........         3%         9%        10%        11%        13%        15%
PHEV (all types)..........................  PC1LT3                           .........          2          2          3          3          3          5
Advanced Engines..........................  PC1LT3                           .........         -5        -11        -13        -14        -16        -19
Advanced AERO.............................  PC1LT3                           .........          0          1          1          1          1          1
Advanced MR...............................  PC1LT3                           .........          6          6          9          9         17         21
Strong Hybrid (all types).................  PC2LT4                           .........          3          9         11         13         16         18
PHEV (all types)..........................  PC2LT4                           .........          2          3          5          5          5          7
Advanced Engines..........................  PC2LT4                           .........         -5        -12        -15        -17        -21        -25
Advanced AERO.............................  PC2LT4                           .........          1          1          2          2          2          2
Advanced MR...............................  PC2LT4                           .........          7         10         14         16         23         28
Strong Hybrid (all types).................  PC3LT5                           .........          3         10         13         16         19         22
PHEV (all types)..........................  PC3LT5                           .........          2          2          4          5          5          7
Advanced Engines..........................  PC3LT5                           .........         -5        -13        -17        -20        -24        -29
Advanced AERO.............................  PC3LT5                           .........          1          2          2          2          2          2
Advanced MR...............................  PC3LT5                           .........         10         15         20         22         31         38
Strong Hybrid (all types).................  PC6LT8                           .........          3         11         14         16         20         25
PHEV (all types)..........................  PC6LT8                           .........          2          2          5          8          9         13
Advanced Engines..........................  PC6LT8                           .........         -6        -13        -20        -25        -29        -38
Advanced AERO.............................  PC6LT8                           .........          1          3          5          5          5          5
Advanced MR...............................  PC6LT8                           .........         10         15         21         25         39         57
--------------------------------------------------------------------------------------------------------------------------------------------------------
Advanced Engines: Combined penetration of advanced cylinder deactivation, advanced turbo, variable compression ratio, high compression ratio, and diesel
  engines.\581\
Advanced AERO: Combined penetration of 15 and 20 percent aerodynamic improvement.
Advanced MR: Combined penetration of MR4 and MR5.


[[Page 56333]]

    The estimated increases in technology application shown in the 
preceding two tables are all computed relative to the No-Action 
Alternative. As discussed above and in the TSD and PRIA accompanying 
this proposal, the No-Action Alternative includes a considerable amount 
of fuel-saving technology applied in response to (1) the baseline (set 
in 2022) CAFE and CO2 standards, (2) fuel prices and 
technology cost-effectiveness (which accounts for recently-developed 
tax incentives), (3) the California Framework Agreements (albeit only 
for some intervening MYs), and (4) ZEV mandates in place in California 
and other States. The effects of this baseline application of 
technology are not attributable to this action, and NHTSA has therefore 
excluded these from our estimates of the incremental technology 
application, benefits, and costs that could result from each action 
alternative considered here. NHTSA's obligation is to understand and 
evaluate the effects of potential future CAFE standards, as compared to 
what is happening in the baseline. We realize that manufacturers face a 
combination of regulatory requirements simultaneously, which is why 
NHTSA seeks to account for those in its analytical baseline, and to 
determine what the additional incremental effects of different 
potential future CAFE standards would be, within the context of our 
statutory restrictions.
    Additionally, for both passenger cars and light trucks, NHTSA notes 
that in considering the various technology penetration rates for 
fleets, readers (and NHTSA) must keep in mind that due to the statutory 
restrictions, NHTSA's analysis considers these technologies as 
applicable to the remaining ICE vehicles that have not yet electrified 
for reasons reflected in the baseline. This means that the rates apply 
to only a fraction of each overall fleet, and thus represent a higher 
rate for that fraction.
    Another consideration for economic practicability is the extent to 
which new standards could increase the average cost to acquire new 
vehicles. Even though the underlying application of technology leads to 
reduced fuel costs over the useful lives of the affected vehicles, 
these per-vehicle cost changes provide both a measure of the degree of 
effort faced by manufacturers to comply with CAFE standards, and also 
the degree of adjustment, in the form of potential vehicle price 
increases, that will ultimately be required of vehicle purchasers. 
Because our analysis includes estimates of manufacturers' indirect 
costs and profits, as well as civil penalties that some manufacturers 
(as allowed under EPCA/EISA) might choose to pay in lieu of achieving 
compliance with CAFE standards,\582\ we report cost increases as 
estimated average increase in vehicle price (as MSRP).\583\ The 
technology costs described here are what NHTSA elsewhere calls 
``regulatory costs,'' which means the combination of additional costs 
of technology added to meet the standards, plus any civil penalties 
paid in lieu of meeting standards. NHTSA assumes for purposes of this 
analysis that all regulatory costs are passed forward to consumers as 
price increases. If the per-vehicle cost/price increases seem 
consistent with those previously found to be economically practicable, 
given what we estimate about conditions during the rulemaking time 
frame, NHTSA can more readily conclude that the standards causing those 
increases are economically practicable.
---------------------------------------------------------------------------

    \582\ To be clear, this is not an assessment that manufacturers 
will pay civil penalties, or will need to pay civil penalties, it is 
simply an assumption for purposes of this analysis that some 
manufacturers could choose to pay civil penalties rather than apply 
additional technology if they deem the former approach more cost-
effective. Manufacturers are always free to choose their own 
compliance path.
    \583\ These are average values, and the agency does not expect 
that the prices of every vehicle would increase by the same amount; 
rather, the agency's underlying analysis shows unit costs varying 
widely between different vehicle models, as evident in the model 
output available on NHTSA's website. While we recognize that 
manufacturers will distribute regulatory costs throughout their 
fleet to maximize profit, we have not attempted to estimate 
strategic pricing, having insufficient data (which would likely be 
CBI) on which to base such an attempt. Additionally, even 
recognizing that manufacturers will distribute regulatory costs 
throughout their fleets, NHTSA still believes that average per-
vehicle cost is useful for illustrating the possible broad 
affordability implications of new standards.
---------------------------------------------------------------------------

    The tables below show additional technology costs estimated to be 
incurred under each action alternative as compared to the No-Action 
Alternative, given the statutory restrictions under which NHTSA 
conducts its ``standard setting'' analysis:
BILLING CODE 4910-59-P

[[Page 56334]]

[GRAPHIC] [TIFF OMITTED] TP17AU23.099


[[Page 56335]]


[GRAPHIC] [TIFF OMITTED] TP17AU23.100

    It should be clear from the tables above that results vary by 
manufacturer, by year, and by fleet. NHTSA typically considers average 
results for a metric like per-vehicle cost, in part because NHTSA has 
typically approached

[[Page 56336]]

economic practicability as a question for the industry as a whole, such 
that standards can still be maximum feasible even if they are harder 
for some manufacturers than others.\584\ The average passenger car cost 
increase under PC6LT8 is $704 in MY 2027 but rises rapidly thereafter, 
exceeding $2,000 by MY 2030 and exceeding $3,000 by MY 2032. In 
contrast, the average passenger car cost increase under PC1LT3 reaches 
only $419 by MY 2032. This is a fairly stark difference between the 
least and most stringent action alternatives. The difference between 
average passenger car costs under PC2LT4 and PC3LT5 is only about $200 
in the earlier MYs, but it begins to diverge more in MY 2029, and by MY 
2032 the average passenger car cost under PC3LT5 is nearly twice the 
average passenger car cost under PC2LT4.
---------------------------------------------------------------------------

    \584\ See, e.g., 87 FR at 25969 (``If the overarching purpose of 
EPCA is energy conservation, NHTSA believes that it is reasonable to 
expect that maximum feasible standards may be harder for some 
automakers than for others, and that they need not be keyed to the 
capabilities of the least capable manufacturer. Indeed, keying 
standards to the least capable manufacturer may disincentivize 
innovation by rewarding laggard performance.'').
---------------------------------------------------------------------------

    For light trucks, the average light truck cost increase under 
PC6LT8 is $647, and (similarly to cars) rises rapidly thereafter, also 
exceeding $2,000 by MY 2030 and exceeding $3,000 by MY 2032. In 
contrast, the average light truck cost increase under PC1LT3 reaches 
only $687 by MY 2032. As for cars, this is a fairly stark difference 
between these alternatives. Comparing average light truck cost 
increases between PC2LT4 and PC3LT5, the divergence over time is 
actually about the same as for passenger cars, although overall costs 
are higher (over $1,000 for both alternatives) by MY 2032. As discussed 
in Section V.A, while NHTSA has no bright-line rule regarding the point 
at which per-vehicle cost becomes economically impracticable, when 
considering the stringency increases (and attendant costs) which 
manufacturers will be facing over the period immediately prior to these 
proposed standards, in the form of the MYs 2024-2026 standards, the 
over-$3,000 per vehicle estimated for PC6LT8 by MY 2032 may be too 
much. Looking at average costs, with $1,205 for passenger cars and 
$1,795 for light trucks by MY 2032, PC3LT5 may be more likely to be 
economically feasible.
    However, average results may be increasingly somewhat misleading as 
manufacturers transition their fleets to the BEVs whose fuel economy 
NHTSA is prohibited from considering when setting the standards. This 
is because fuel economy in the fleet has historically been more of a 
normal distribution (i.e., a bell curve), and with more and more BEVs, 
it becomes more of a bimodal distribution (i.e., a two-peak curve). 
Attempting to average a bimodal distribution does not necessarily give 
a clear picture of what non-BEV-specialized manufacturers are capable 
of doing, and regardless, NHTSA is directed not to consider BEV fuel 
economy. Thus, in this proposal, NHTSA believes it is appropriate to 
examine individual manufacturer results more closely. This is not to 
say that NHTSA wishes to return to a ``least capable manufacturer'' 
approach to economic practicability--rather to say that because statute 
prohibits NHTSA from determining maximum feasible standards based on 
the ``most capable'' manufacturer, we have to find a way to acknowledge 
their existence without allowing them to drive the answer to what is 
maximum feasible. If we were to do so, we would impose costs on non-
BEV-only manufacturers that we believe would likely be far too high.
    Looking at per-manufacturer results for passenger cars, under 
PC6LT8, nearly every non-BEV-only manufacturer would exceed more than 
$2,000 per passenger car in regulatory costs by MY 2032, with extremely 
high costs (well over $4,500) for Ford, GM, Hyundai-Kia, and Mazda. In 
the standard-setting analysis which NHTSA must consider here, 
significant levels of advanced MR and advanced engine technologies tend 
to be driving many of these cost increases. In many MYs, for many 
manufacturers, the inflection point in cost increases for passenger 
cars appears to be between PC2LT4 and PC3LT5, with many companies' 
passenger car costs jumping anywhere from roughly $200 to roughly $500 
from PC2LT4 to PC3LT5. Again, these changes are best understood in 
context--passenger car sales have been falling over recent years while 
prices have been rising, and most of the new vehicles sold in the last 
couple of years have been more expensive models.\585\ NHTSA does not 
want to inadvertently burden passenger car sales by requiring too much 
additional cost for new vehicles, particularly given the performance of 
the passenger car fleet in comparison to the light truck fleet in terms 
of mileage gains; every mile driven in passenger cars is, on average, 
more fuel-efficient than miles driven in light trucks. While the costs 
of PC2LT4 may challenge some manufacturers of passenger cars, they will 
do so by much less than PC3LT5.
---------------------------------------------------------------------------

    \585\ Tucker, S. KBB. 2021. Automakers Carry Tight Inventories: 
What Does It Mean to Car Buyers? Available at: https://www.kbb.com/car-advice/automakers-carry-tight-inventories-what-does-it-mean-to-car-buyers/. (Accessed May 31, 2023).
---------------------------------------------------------------------------

    Looking at per-manufacturer results for light trucks, under PC6LT8, 
every non-BEV-only manufacturer but Subaru would exceed $2,000 in per-
vehicle costs by MY 2032, with nearly all of those exceeding $3,000. 
This is likely due to a combination of MR4, AERO20, SHEV, and (for 
PC6LT8, particularly) PHEV technologies being applied to trucks in 
order to meet PC6LT8. Again, there appears to be a possible inflection 
point in costs between PC2LT4 and PC3LT5--in MY 2032 light trucks, for 
example, only one manufacturer exceeds $2,000 per vehicle under PC2LT4, 
while 5 exceed $2,000 under PC3LT5. Additionally, closer examination of 
the cost incurred under PC3LT5 versus PC2LT4 shows that under PC3LT5 
about one-third of per-vehicle costs originates from civil penalties 
paid for `shortfalls,' as discussed below, rather than actual increase 
in technology (and thus, increased fuel savings). Under PC2LT4, civil 
penalties represent only a slightly smaller share of costs, however, 
their magnitude is much smaller, about half the value we find in 
PC3LT5. Civil penalties only represent a small share of costs in all 
scenarios except for PC6LT8, the most stringent alternative.
    With regard to lead time and timing of technology application, 
NHTSA acknowledges that there is more lead time for these proposed 
standards than manufacturers had for the MYs 2024-2026 standards. That 
said, NHTSA also recognizes that we have previously stated that if the 
standards in the years immediately preceding the rulemaking time frame 
do not require significant additional technology application, then more 
technology should theoretically be available for meeting the standards 
during the rulemaking time frame--but this is not necessarily the case 
here. The technology penetration rates shown in Table V-2 and Table V-3 
suggest that, at least for purposes of what NHTSA may consider by 
statute, industry would be running up against the limits of available 
technology for the more stringent regulatory alternatives, in a way 
that has not occurred in prior rulemakings. The analysis suggests that 
in many cases, manufacturers will need to abandon smaller steps in 
advanced engine technology development and instead begin converting the 
remaining fleet of ICE vehicles to SHEV with advanced MR, at a high 
cost for several major manufacturers. Lead time may not be able to 
overcome the costs of

[[Page 56337]]

applying additional technology at a high rate, beyond what is already 
being applied to the fleet for other reasons during the rule making 
time frame and, in the years immediately preceding it, when considered 
in the context of NHTSA's statutory restrictions.
    When manufacturers do not achieve required fuel economy levels, 
NHTSA describes them as ``in shortfall.'' NHTSA's analysis reflects 
several possible ways that manufacturers could fail to meet required 
fuel economy levels. For some companies that NHTSA judges willing to 
pay civil penalties in lieu of compliance, usually based on past 
history of penalty payment, NHTSA assumes that they will do so as soon 
as it becomes more cost-effective to pay penalties rather than add 
technology. For other companies whom NHTSA judges unwilling to pay 
civil penalties, if they have converted all vehicles available to be 
redesigned in a given MY to SHEV or PHEV and still cannot meet the 
required standard, then NHTSA does not assume that these companies will 
break redesign or refresh cycles to convert even more (of the remaining 
ICE) vehicles to SHEV or PHEV.\586\ In these instances, a manufacturer 
would be ``in shortfall'' in NHTSA's analysis. Shortfall rates can also 
be informative for determining economic practicability, because if 
manufacturers simply are not achieving the required levels, then that 
suggests that manufacturers have generally judged it more cost-
effective not to comply by adding technology. Moreover, the standards 
would not be accomplishing what they set out to accomplish, which would 
mean that the standards are not meeting the need of the U.S. to 
conserve energy as originally expected.
---------------------------------------------------------------------------

    \586\ Ensuring that technology application occurs consistent 
with refresh/redesign schedules is part of how NHTSA accounts for 
economic practicability. Forcing technology application outside of 
those schedules would be neither realistic from a manufacturing 
perspective nor cost-effective. See Chapter 2.2.1.7 of the Draft TSD 
for more information about product timing cycles.
---------------------------------------------------------------------------

    The following figures illustrate shortfalls by fleet, MY, 
manufacturer, and regulatory alternative:

[[Page 56338]]

[GRAPHIC] [TIFF OMITTED] TP17AU23.101


[[Page 56339]]


[GRAPHIC] [TIFF OMITTED] TP17AU23.102

BILLING CODE 4910-59-C
    For passenger cars, the industry average again obscures more 
serious shortfall trends among individual manufacturers. Many 
manufacturers' passenger car fleets are estimated to fall significantly 
short of required levels under PC6LT8. Even for PC3LT5, several non-
BEV-only manufacturers still appear to be falling short in most MYs. 
Passenger car shortfalls are much less widespread under PC2LT4. For 
light trucks, the shortfalls are extensive under PC6LT8, and about half 
of non-BEV-only manufacturers fall short in

[[Page 56340]]

most if not all MYs under PC3LT5. Even PC2LT4 appears challenging under 
the standard-setting runs for several light truck non-BEV-only 
manufacturers. Given all of the data examined, NHTSA believes that 
PC2LT4 may represent the upper limit of economic practicability during 
the rulemaking time frame.
    Of course, CAFE standards are performance-based, and NHTSA does not 
dictate specific technology paths for meeting them, so it is entirely 
possible that individual manufacturers and industry as a whole will 
take a different path from the one that NHTSA presents here.\587\ 
Nonetheless, this is a path toward compliance, relying on known, 
existing technology, and NHTSA believes that our analysis suggests that 
the levels of technology and cost required by PC2LT4 are reasonable and 
economically practicable in the rulemaking time frame.
---------------------------------------------------------------------------

    \587\ NHTSA acknowledges that compliance looks easier and more 
cost-effective for many manufacturers under the ``unconstrained'' 
analysis as compared to the ``standard-setting'' analysis discussed 
here, but emphasizes that NHTSA's decision on maximum feasible 
standards must be based on the standard-setting analysis reflecting 
the 32902(h) restrictions.
---------------------------------------------------------------------------

    As in past analyses, NHTSA assumes that the cost increases 
associated with applying technology (or paying civil penalties) in 
response to more stringent standards would be passed on to consumers as 
higher retail prices. Higher retail prices are assumed to result in 
slight decreases in new vehicle sales, with larger price increases (as 
for more stringent alternatives) resulting in larger (but still 
relatively minor) sales decreases. While we estimate that the per-
vehicle costs and technology penetration rates of Alternative PC2LT4 
are reasonable, and while our analysis suggests that it maximizes net 
benefits in the rulemaking time frame given our statutory restrictions, 
we note that it produces a slight decline in new vehicle sales (less 
than 1 percent through MY 2032) as compared to the No-Action 
Alternative, as a consequence of the higher retail prices that result 
from additional technology application. NHTSA does not believe that 
this very minor estimated change in new vehicle sales over the period 
covered by the rule is a persuasive reason to choose another regulatory 
alternative, particularly as macroeconomic factors have historically 
had a far greater impact on sales than CAFE standards. Similarly, the 
estimated labor impacts within the automotive industry provide no 
evidence that another alternative should be preferred. On the one hand, 
when fewer vehicles are sold, manufacturers require fewer labor hours 
to satisfy demand, but on the other hand, development and deployment of 
new fuel-economy-improving technologies increase demand for labor. The 
analysis suggests that technology effects outweigh sales effects, at 
least for PC1LT3, PC2LT4, and PC3LT5, resulting in slightly higher 
labor utilization than under the No-Action Alternative. That said, the 
actual values are quite small in comparison to total auto industry 
employment, and as with sales, NHTSA does not believe that employment 
effects provide clear evidence that another alternative should be 
preferred. Chapter 8.2.2.3 of the PRIA contains more information.
    The tables and discussion also illustrate that, in some respects, 
economic practicability points in the opposite direction of the need of 
the U.S. to conserve energy. It is within NHTSA's discretion to forgo 
the potential prospect of additional energy conservation benefits if 
NHTSA believes that more stringent standards would be economically 
impracticable, and thus, beyond maximum feasible.
    Changes in costs for new vehicles are not the only costs that NHTSA 
considers in balancing the statutory factors. Fuel costs for consumers 
are relevant to the need of the U.S. to conserve energy, and NHTSA 
believes that consumers themselves weigh expected fuel savings against 
increases in purchase price for vehicles with higher fuel economy, 
although the extent to which consumers value fuel economy improvements 
is hotly debated, as discussed in Chapter 4.2 of the Draft TSD. Fuel 
costs (or savings) continue, for now, to be the largest source of 
benefits for CAFE standards. Comparing private costs to private 
benefits, the estimated results for American consumers are as follows:

   Table V-6--Incremental Private Benefits and Private Costs Over the
 Lifetimes of Total Passenger Car Fleet Produced Through MY 2032 (2021$
                 Billions), 3 Percent DR, by Alternative
------------------------------------------------------------------------
         Alternative            PC1LT3     PC2LT4     PC3LT5     PC6LT8
------------------------------------------------------------------------
Private Costs:
    Technology Costs to             8.3       10.9       15.7       23.9
     Increase Fuel Economy..
    Increased Maintenance           0.0        0.0        0.0        0.0
     and Repair Costs.......
    Opportunity Cost in             0.0        0.0        0.0        0.0
     Other Vehicle
     Attributes.............
    Consumer Surplus Loss           0.0        0.0        0.1        0.4
     from Reduced New
     Vehicle Sales..........
    Safety Costs                    0.3        0.6        1.0        2.3
     Internalized by Drivers
                             -------------------------------------------
        Subtotal--Incrementa        8.6       11.5       16.7       26.6
         l Private Costs....
Private Benefits:
    Reduced Fuel Costs......        2.3        4.4        6.0       14.4
    Benefits from Additional        0.4        0.9        1.5        3.5
     Driving................
    Less Frequent Refueling.        0.2        0.4        0.5        1.2
                             -------------------------------------------
        Subtotal--Incrementa        2.9        5.7        8.0       19.0
         l Private Benefits.
    Net Incremental Private        -5.7       -5.8       -8.7       -7.6
     Benefits...............
------------------------------------------------------------------------


   Table V-7--Incremental Private Benefits and Private Costs Over the
  Lifetimes of Total Light Truck Fleet Produced Through MY 2032 (2021$
                 Billions), 3 Percent DR, by Alternative
------------------------------------------------------------------------
         Alternative            PC1LT3     PC2LT4     PC3LT5     PC6LT8
------------------------------------------------------------------------
Private Costs:
    Technology Costs to            21.6       26.9       35.0       44.9
     Increase Fuel Economy..
    Increased Maintenance           0.0        0.0        0.0        0.0
     and Repair Costs.......
    Opportunity Cost in             0.0        0.0        0.0        0.0
     Other Vehicle
     Attributes.............

[[Page 56341]]

 
    Consumer Surplus Loss           0.0        0.1        0.2        0.8
     from Reduced New
     Vehicle Sales..........
    Safety Costs                    4.0        4.8        5.6        6.3
     Internalized by Drivers
                             -------------------------------------------
        Subtotal--Incrementa       25.6       31.8       40.7       52.0
         l Private Costs....
Private Benefits:
    Reduced Fuel Costs......       35.3       43.3       49.1       61.5
    Benefits from Additional        6.9        8.1        9.4       10.6
     Driving................
    Less Frequent Refueling.        1.8        2.3        2.6        3.5
                             -------------------------------------------
        Subtotal--Incrementa       43.9       53.7       61.1       75.6
         l Private Benefits.
    Net Incremental Private        18.3       21.9       20.4       23.6
     Benefits...............
------------------------------------------------------------------------

    Looking simply at the effects for consumers, our analysis suggests 
that there is no action alternative (again, in the context of the 
standard-setting analysis) in which private benefits will outweigh 
private costs for passenger cars, although PC1LT3 and PC2LT4 are the 
most beneficial, relatively speaking. For light trucks, all of the 
action alternatives appear net beneficial for consumers, with PC2LT4 
and PC6LT8 being the most beneficial. Broadening the scope to consider 
external/governmental benefits as well, we see the following:

  Table V-8--Incremental Benefits and Costs Over the Lifetimes of Total Passenger Car Fleet Produced Through MY
                    2032 (2021$ Billions), 3 Percent Social DR, by Alternative, 3% SC-GHG DR
----------------------------------------------------------------------------------------------------------------
                         Alternative                              PC1          PC2          PC3          PC6
----------------------------------------------------------------------------------------------------------------
Private Costs (see Table V-6 above):
                                                             ---------------------------------------------------
        Subtotal--Incremental Private Costs.................          8.6         11.5         16.7         26.6
External Costs:
    Congestion and Noise Costs from Rebound-Effect Driving..         -0.3          0.0          1.4          2.2
    Safety Costs Not Internalized by Drivers................         -0.3         -0.1          2.4          3.1
    Loss in Fuel Tax Revenue................................          0.4          0.8          1.0          2.5
                                                             ---------------------------------------------------
        Subtotal--Incremental External Costs................         -0.2          0.6          4.9          7.9
            Total Incremental Social Costs..................          8.4         12.1         21.6         34.5
Private Benefits (see Table V-6 above):
                                                             ---------------------------------------------------
        Subtotal--Incremental Private Benefits..............          2.9          5.7          8.0         19.0
External Benefits:
    Reduction in Petroleum Market Externality...............          0.1          0.1          0.2          0.5
    Reduced Climate Damages, 3% SC-GHG DR...................          0.6          1.3          1.7          4.1
    Reduced Health Damages..................................          0.0          0.0         -0.1         -0.1
                                                             ---------------------------------------------------
        Subtotal--Incremental External Benefits.............          0.7          1.4          1.8          4.5
            Total Incremental Social Benefits, 3% SC-GHG DR.          3.6          7.1          9.8         23.5
    Net Incremental Social Benefits, 3% SC-GHG DR...........         -4.7         -5.1        -11.7        -10.9
----------------------------------------------------------------------------------------------------------------


Table V-9--Incremental Benefits and Costs Over the Lifetimes of Total Light Truck Fleet Produced Through MY 2032
                       (2021$ Billions), 3 Percent Social DR, by Alternative, 3% SC-GHG DR
----------------------------------------------------------------------------------------------------------------
                         Alternative                              LT3          LT4          LT5          LT8
----------------------------------------------------------------------------------------------------------------
Private Costs (see Table V-7 above):
                                                             ---------------------------------------------------
        Subtotal--Incremental Private Costs.................         25.6         31.8         40.7         52.0
External Costs:
    Congestion and Noise Costs from Rebound-Effect Driving..          3.3          3.6          3.9          3.2
    Safety Costs Not Internalized by Drivers................          2.0          1.8          2.2          1.8
    Loss in Fuel Tax Revenue................................          7.5          9.3         10.3         13.1
                                                             ---------------------------------------------------
        Subtotal--Incremental External Costs................         12.8         14.7         16.4         18.1
            Total Incremental Social Costs..................         38.5         46.5         57.1         70.1
Private Benefits (see Table V-7 above):
        Subtotal--Incremental Private Benefits..............         43.9         53.7         61.1         75.6
External Benefits:
    Reduction in Petroleum Market Externality...............          1.4          1.7          1.9          2.4
    Reduced Climate Damages, 3% SC-GHG DR...................         10.3         12.7         14.3         18.1
    Reduced Health Damages..................................          0.2          0.3          0.3          0.5
                                                             ---------------------------------------------------
        Subtotal--Incremental External Benefits.............         11.9         14.7         16.6         21.0

[[Page 56342]]

 
            Total Incremental Social Benefits, 3% SC-GHG DR.         55.8         68.4         77.7         96.6
    Net Incremental Social Benefits, 3% SC-GHG DR...........         17.4         21.9         20.6         26.5
----------------------------------------------------------------------------------------------------------------

    Adding external/SCs and benefits does not change the direction of 
NHTSA's analytical findings. Net benefits for passenger cars remain 
negative across alternatives, with a trough at PC3LT5. Net benefits for 
light trucks remain positive across alternatives, with a peak at PC6LT8 
but with PC2LT4 not so far behind.
    Because NHTSA considers multiple DRs in its analysis, and because 
analysis also includes multiple values for the SC-GHG, we also estimate 
the following cumulative values for each regulatory alternative:

    Table V-10--Summary of Cumulative Benefits and Costs for Model Years through MY 2032 (2021$ Billions), by
                                        Alternative, SC-GHG Value, and DR
----------------------------------------------------------------------------------------------------------------
                                               3% Discount rate                       7% Discount rate
                                   -----------------------------------------------------------------------------
            Alternative                                           Net                                    Net
                                       Costs       Benefits     benefits      Costs       Benefits     benefits
----------------------------------------------------------------------------------------------------------------
SC-GHG discounted at 5 percent:
    PC1LT3........................         46.8         51.2          4.4         31.2         29.2         -2.0
    PC2LT4........................         58.6         65.0          6.3         39.1         37.0         -2.1
    PC3LT5........................         78.7         75.5         -3.2         52.2         42.8         -9.4
    PC6LT8........................        104.5        103.4         -1.2         70.3         58.1        -12.2
SC-GHG discounted at 3 percent:
    PC1LT3........................         46.8         59.5         12.7         31.2         37.5          6.3
    PC2LT4........................         58.6         75.5         16.8         39.1         47.5          8.4
    PC3LT5........................         78.7         87.5          8.8         52.2         54.9          2.7
    PC6LT8........................        104.5        120.1         15.6         70.3         74.8          4.5
SC-GHG discounted at 2.5 percent:
    PC1LT3........................         46.8         65.3         18.5         31.2         43.3         12.1
    PC2LT4........................         58.6         82.9         24.3         39.1         54.9         15.8
    PC3LT5........................         78.7         96.1         17.4         52.2         63.5         11.3
    PC6LT8........................        104.5        132.0         27.5         70.3         86.7         16.4
SC-GHG discounted at 3 percent,
 95th percentile:
    PC1LT3........................         46.8         81.8         35.0         31.2         59.8         28.7
    PC2LT4........................         58.6        103.9         45.2         39.1         75.9         36.8
    PC3LT5........................         78.7        120.2         41.5         52.2         87.6         35.4
    PC6LT8........................        104.5        165.4         60.9         70.3        120.1         49.8
----------------------------------------------------------------------------------------------------------------


 Table V-11--Summary of Cumulative Benefits and Costs for CY 2022-2050 (2021$ Billions), by Alternative, SC-GHG
                                                  Value, and DR
----------------------------------------------------------------------------------------------------------------
                                               3% Discount rate                       7% Discount rate
                                   -----------------------------------------------------------------------------
            Alternative                                           Net                                    Net
                                       Costs       Benefits     benefits      Costs       Benefits     benefits
----------------------------------------------------------------------------------------------------------------
SC-GHG discounted at 5 percent:
    PC1LT3........................        116.3        128.2         11.9         64.9         66.0          1.2
    PC2LT4........................        156.8        173.2         16.3         86.7         88.6          1.9
    PC3LT5........................        239.9        221.6        -18.2        130.2        112.5        -17.8
    PC6LT8........................        385.9        369.0        -16.9        206.0        184.4        -21.6
SC-GHG discounted at 3 percent:
    PC1LT3........................        116.3        150.5         34.2         64.9         88.3         23.4
    PC2LT4........................        156.8        203.3         46.5         86.7        118.8         32.1
    PC3LT5........................        239.9        260.8         21.0        130.2        151.6         21.4
    PC6LT8........................        385.9        436.9         51.0        206.0        252.3         46.4
SC-GHG discounted at 2.5 percent:
    PC1LT3........................        116.3        166.4         50.1         64.9        104.2         39.3
    PC2LT4........................        156.8        224.8         68.0         86.7        140.3         53.6
    PC3LT5........................        239.9        288.8         49.0        130.2        179.6         49.4
    PC6LT8........................        385.9        485.5         99.7        206.0        301.0         95.0
SC-GHG discounted at 3 percent,
 95th percentile:
    PC1LT3........................        116.3        210.4         94.1         64.9        148.2         83.3
    PC2LT4........................        156.8        284.3        127.5         86.7        199.8        113.1
    PC3LT5........................        239.9        366.1        126.3        130.2        257.0        126.7
    PC6LT8........................        385.9        619.3        233.5        206.0        434.8        228.8
----------------------------------------------------------------------------------------------------------------


[[Page 56343]]

    While the results shown in the tables above range widely--
underscoring that DR assumptions significantly affect benefits 
estimates--the ordering of alternatives generally remains the same 
under most discounting scenarios. In some cases, PC6LT8 appears to have 
greater net benefits, but in nearly all of those cases, PC2LT4 is the 
next most net beneficial.
    E.O. 12866 and Circular A-4 direct agencies to consider maximizing 
net benefits in rulemakings whenever possible and consistent with 
applicable law. Because it can be relevant to balancing the statutory 
factors and because it is directed by E.O. 12866 and OMB guidance, 
NHTSA does evaluate and consider net benefits associated with different 
potential future CAFE standards. As the tables above show, our analysis 
suggests that for passenger cars, net benefits are higher when 
standards are less stringent, and for light trucks, net benefits are 
higher when standards are more stringent, although not consistently. 
Looking solely at net benefits, PC6LT8 looks best overall and across 
all DRs, as well as for light truck specifically, although PC1LT3 looks 
least bad for passenger cars.
    That said, while maximizing net benefits is a valid decision 
criterion for choosing among alternatives, provided that appropriate 
consideration is given to impacts that cannot be monetized, it is not 
the only reasonable decision perspective, and we recognize that what we 
include in our cost-benefit analysis affects our estimates of net 
benefits. We also note that important benefits cannot be monetized--
including the full health and welfare benefits of reducing climate 
emissions and other pollution, which means that the benefits estimates 
are underestimates. Thus, given the uncertainties associated with many 
aspects of this analysis, NHTSA does not rely solely on net benefit 
maximization, and instead considers it as one piece of information that 
contributes to how we balance the statutory factors, in our 
discretionary judgment. NHTSA recognizes that the need of the U.S. to 
conserve energy weighs importantly in the overall balancing of factors, 
and thus believes that it is reasonable to at least consider choosing 
the regulatory alternative that produces the largest reduction in fuel 
consumption, while still remaining net beneficial. Of course, the 
benefit-cost analysis is not the sole factor that NHTSA considers in 
determining the maximum feasible stringency, though it informs NHTSA's 
tentative conclusion that Alternative PC2LT4 is the maximum feasible 
stringency. Importantly, the shortfalls discussion above suggests that 
even if PC6LT8 appears net beneficial, under the constraints of our 
standard-setting analysis which is the analysis that NHTSA is 
statutorily required to consider, the majority of manufacturers may 
simply be unable to achieve the fuel economy levels required by that 
alternative, which would mean that it would not be accomplishing its 
goal and thus almost certainly beyond maximum feasible.
    As with any analysis of sufficient complexity, there are a number 
of critical assumptions here that introduce uncertainty about 
manufacturer compliance pathways, consumer responses to fuel economy 
improvements and higher vehicle prices, and future valuations of the 
consequences from higher CAFE standards. Recognizing that uncertainty, 
NHTSA also conducted more than 70 sensitivity analysis runs for the 
passenger car and light truck fleet analysis. The entire sensitivity 
analysis is presented in the PRIA, demonstrating the effect that 
different assumptions would have on the costs and benefits associated 
with the different regulatory alternatives. While NHTSA considers 
dozens of sensitivity cases to measure the influence of specific 
parametric assumptions and model relationships, only a small number of 
them demonstrate meaningful impacts to net benefits under the different 
alternatives.
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    The results of the sensitivity analysis runs suggest that 
relatively few metrics make a major difference to cost and benefit 
outcomes, and the ones that do, act in relatively predictable ways. 
Some changes in values (fuel prices, removing ZEV, IRA tax credits) act 
on the baseline, increasing or reducing the amount of fuel economy 
improvements available for CAFE standards. Other changes in values (for 
example, fuel prices) affect benefits, and thus net benefits. 
Generally, even when costs and benefits change significantly in a 
sensitivity case, the basic ranking of alternatives in terms of net 
benefits does not change, and if it does change, it does not change by 
enough to change NHTSA's tentative conclusion that PC2LT4 is the 
maximum feasible alternative. The three cases extending the standard-
setting conditions to additional MYs do reduce net benefits, but again, 
to the extent that rankings appear to change between alternatives, the 
magnitude of the relative difference is not significant enough to 
change our tentative conclusion. NHTSA is statutorily prohibited from 
considering the fuel economy of BEVs in determining maximum feasible 
stringency but notes in passing that the case changing the value of 
DOE's PEF reduces net benefits somewhat, although not significantly, 
and that changing assumptions about the value of electrification tax 
credits that reach consumers reduces net benefits significantly. 
However, because NHTSA cannot consider the fuel economy of BEVs in 
determining maximum feasible fuel economy standards, these are effects 
that happen only in the baseline of our analysis and are not considered 
in our determination. Moreover, regardless of net benefits, NHTSA 
believes that its tentative conclusion would be the same that 
Alternative PC2LT4 is economically practicable, based on per-vehicle 
costs, technology levels estimated to be required to meet the 
standards, and manufacturers' apparent ability to even reach compliance 
in most MYs, as compared to Alternative PC3LT5.
    Finally, as discussed in Section IV.A, NHTSA accounts for the 
effects of other motor vehicle standards of the Government in its 
balancing, often through their incorporation into our regulatory 
baseline.\588\ NHTSA believes that this approach accounts for these 
effects reasonably and appropriately. NHTSA recognizes prior arguments 
from industry stakeholders that any additional investment required to 
meet CAFE standards beyond what they intended to make to meet EPA's GHG 
standards would make such CAFE standards ``too stringent.'' \589\ As 
discussed above, even when the standards of the two programs are 
coordinated closely, it is still foreseeable that there could be 
situations in which different agencies' programs could be binding for 
different manufacturers in different MYs. This has been true across 
multiple CAFE rulemakings over the past decade. Regardless of which 
agency's standards are binding given a manufacturer's chosen compliance 
path, manufacturers will choose a path that complies with both 
standards, and in doing so, will still be able to build a single fleet 
of vehicles--even if it is not exactly the fleet that the manufacturer 
might have preferred to build. This remains the case with this 
proposal.
---------------------------------------------------------------------------

    \588\ NHTSA has carefully considered EPA's standards by 
including the baseline (i.e., MYs 2024-2026) CO2 
standards in our analytical baseline. Because the EPA and NHTSA 
proposals were developed in coordination jointly, and stringency 
decisions were made in coordination, NHTSA did not include EPA's 
proposal for MYs 2027 and beyond CO2 standards in our 
analytical baseline for this proposal. The fact that EPA issued its 
proposal before NHTSA is an artifact of circumstance only.
    \589\ See, e.g., 87 FR at 26024 (May 2. 2022).
---------------------------------------------------------------------------

    NHTSA does not believe that it is a reasonable interpretation of 
Congress' direction to set ``maximum feasible'' standards, as some 
commenters might prefer, at the fuel economy level at which no 
manufacturer need ever apply any additional technology or spend any 
additional dollar beyond what EPA's standards, with their many 
flexibilities,

[[Page 56349]]

would require. NHTSA believes that CAFE standards can still be 
consistent with EPA's GHG standards even if they impose additional 
costs for certain manufacturers, although NHTSA is, of course, mindful 
of the magnitude of those costs and believes that the preferred 
alternative would impose minimal additional costs, if any, above 
compliance with EPA's standards.
    NHTSA has also carefully considered CARB's ACC2 program (which 
includes the ZEV mandate) by including it in the No-Action Alternative. 
NHTSA continues to believe that this approach is reasonable. Modeling 
anticipated manufacturer compliance with these programs enables NHTSA 
to make more realistic projections of how the U.S. vehicle fleet will 
change in the coming years, which is foundational to our ability to set 
CAFE standards that reflect the maximum feasible fuel economy level 
achievable through improvements to internal combustion vehicles. 
Likewise, by creating a more accurate projection of how manufacturers 
might modify their fleets even in the absence of new CAFE standards, we 
are better able to identify the effects of new CAFE standards, which is 
the task properly before us. If NHTSA could not account for the ACC2 
program, and could not be informed about the baseline effects, then 
NHTSA could overestimate the availability of vehicles that can be 
improved to meet potential new CAFE standards, and thus end up setting 
a fuel economy standard that requires an infeasible level of 
improvement. Moreover, as the ``No ZEV'' sensitivity case shows, the 
effect of including the ACC2 program in the baseline is simply to 
decrease costs and benefits attributable to potential future CAFE 
standards. Removing anticipated manufacturer compliance with ZEV from 
the baseline increases costs and benefits for every alternative, but 
even so, we note that net benefits change relatively little for that 
sensitivity case, as shown in more detail in Chapter 9 of the PRIA. 
While PC1LT3 looks slightly more net beneficial than PC2LT4 under that 
case, it is only very slightly, and it is not so great an effect as to 
change NHTSA's balancing of the statutory factors in this proposal. 
NHTSA continues to believe, even under this scenario, that PC2LT4 is 
maximum feasible for the rulemaking time frame.
    Even though NHTSA is statutorily prohibited from considering the 
possibility that manufacturers would produce additional BEVs to comply 
with CAFE standards, and even though manufacturers have stated their 
intention to rely more and more heavily on those BEVs for compliance, 
CAFE standards still have an important role to play in meeting the 
country's ongoing need to conserve energy. CAFE standards can also 
ensure continued improvements in energy conservation by requiring 
ongoing fuel economy improvements even if demand for more fuel economy 
flags unexpectedly, or if other regulatory pushes change in unexpected 
ways. Saving money on fuel and reducing CO2 and other 
pollutant emissions by reducing fuel consumption are also important 
equity goals. Fuel expenditures are a significant budget item for 
consumers who are part of lower-income and historically disadvantaged 
communities. Part of our goal in determining maximum feasible CAFE 
standards is trying to improve fuel savings across the fleet as a 
whole, rather than for a handful of new vehicle buyers. By maximizing 
fuel savings to consumers (given estimated effects on new vehicle 
costs), CAFE standards can help to improve equity.
    That said, NHTSA acknowledges the statute-driven cognitive 
dissonance, and NHTSA's task in approaching the determination of 
maximum feasible standards is the same as ever, to evaluate potential 
future CAFE stringencies in light of statutory constraints. NHTSA 
believes that we have identified a path to meeting the proposed 
standards that is technologically feasible and economically practicable 
and consistent with the statutory constraints. Manufacturers may object 
that it is not the path they believe themselves to be on, but NHTSA's 
analysis suggests that it is reasonable, and that it properly reflects 
our constraints. The rate of increase in the standards may be slower 
than in the last round of rulemaking, but NHTSA believes that is 
reasonable and appropriate given the likely state of the fleet by MY 
2027. Consider, for example, the non-linear relationship between fuel 
economy and fuel consumption as illustrated below:
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BILLING CODE 4910-59-C
    As fleet fuel economy improves, there are simply fewer further 
improvements to ICEs available to be made (in the absence of further 
technological innovation), and the amount of fuel consumers actually 
save is smaller, and the remaining available improvements are 
increasingly expensive. This is even more true given the statutory 
restrictions that NHTSA must observe. This is not a bad outcome--in 
some ways, it is a testament to manufacturer efforts and the success of 
this program, that we are beginning to reach the limits of fuel economy 
improvements that can be considered. CAFE standards can still help 
industry complete that journey, and as such, based on all of the 
information contained in this record, NHTSA tentatively concludes that 
PC2LT4 represents the maximum feasible standards for passenger cars and 
light trucks in the MYs 2027 to 2032 time frame. We seek comment on 
this tentative conclusion and all aspects of this discussion.
2. Heavy-Duty Pickups and Vans
    NHTSA has not set new HDPUV standards since 2016, and the 
technology offerings on available models in that segment have changed 
relatively little since then. The redesign cycles in this segment are 
slightly longer than for passenger cars and light trucks, roughly 6-7 
years for pickups and roughly 9 years for vans.\590\ To our knowledge, 
technology for pickups in this segment has been relatively slow to 
advance compared to in the light truck segment, and there are still no 
hybrid HD pickups. That said, electrification is beginning to appear 
among the vans in this segment, perhaps especially among vans typically 
used for deliveries,\591\ and under NHTSA's distinct statutory 
authority for setting HDPUV standards, expanding BEV technologies are 
part of NHTSA's standard setting consideration. The Ford E-Transit, for 
example, is based on the Mach-E platform and uses similar battery 
architecture; \592\ other manufacturers have also shown a willingness 
to transition to electric vans and away from conventional 
powertrains.\593\

[[Page 56351]]

NHTSA is aware that some historic Light truck applications now being 
offered as BEVs may be heavy enough to fall outside the Light Truck 
segment and into the HDPUV segment,\594\ but NHTSA expects 
manufacturers to find strategies to return them to the CAFE Light Truck 
fleet in the coming years. This could include development in battery 
design or electrified powertrain architecture that could reduce vehicle 
weight. The vehicles in these segments are purpose-built for key 
applications and we expect manufactures will cater electrified 
offerings for businesses that maximize benefits in small volumes. 
However, until these technologies materialize, NHTSA assumes in its 
analysis there will continue to be `spill-over' of vehicles that exist 
as edge cases.
---------------------------------------------------------------------------

    \590\ See Draft TSD Chapter 2.2.1.7. HDPUVs have limited makes 
and models. Assumptions about their refresh and redesign schedules 
have an outsized impact on our modeling of HDPUVs, where a single 
redesign can have a noticeable effect on technology penetration, 
costs, and benefits. We seek comment on our approach, specifically 
if there are additional opportunities for manufacturers to apply 
technology in the HDPUV space to mitigate costs.
    \591\ NACFE. 2022. Electric Trucks Have Arrived: The Use Case 
For Vans and Step Vans. Available at: https://nacfe.org/research/run-on-less-electric/#vans-step-vans. (Accessed May 31, 2023).
    \592\ Martinez, M. 2023. Ford to Sell EVs With 2 Types of 
Batteries, Depending On Customer Needs. Last revised: Mar. 5, 2023. 
Available at: https://www.autonews.com/technology/ford-will-offer-second-ev-battery-type-lower-cost-and-range. (Accessed: May 31, 
2023).
    \593\ Hawkins, T. 2023. Mercedes-Benz eSprinter Unveiled As 
BrightDrop Zevo Rival. GM Authority. Available at: https://gmauthority.com/blog/2023/02/mercedes-benz-esprinter-unveiled-as-brightdrop-zevo-rival/. (Accessed: May 31, 2023).
    \594\ Gilboy, J. 2023. The Drive. Massive Weight Could Push Past 
EPA's Light-Duty Rules. Available at: https://www.thedrive.com/news/the-2025-ram-1500-revs-massive-weight-could-push-past-epas-light-duty-rules. (Accessed May 31, 2023). See also Arbelaez, R. 2023. 
IIHS Insight. As heavy EVs proliferate, their weight may be a drag 
on safety. Available at: https://www.iihs.org/news/detail/as-heavy-evs-proliferate-their-weight-may-be-a-drag-on-safety. (Accessed May 
31, 2023).
---------------------------------------------------------------------------

    The following text will walk through the three statutory factors in 
more detail and discuss NHTSA's decision-making process more 
thoroughly. The tentative balancing of factors presented here 
represents NHTSA's thinking at the present time, based on all of the 
information presented in the record for this proposal. NHTSA 
acknowledges that a different balancing may turn out to be appropriate 
for the final rule depending on information that arrives between now 
and then, both through the public comment process and otherwise.
    For the reader's reference, the regulatory alternatives under 
consideration for HDPUVs are presented again below:

  Table V-13--Regulatory Alternatives Under Consideration for MYs 2030-
                               2035 HDPUVs
------------------------------------------------------------------------
                                                                HDPUV
                                                              Stringency
                    Name of alternative                       increases,
                                                              year-over-
                                                               year (%)
------------------------------------------------------------------------
No-Action Alternative......................................          n/a
Alternative HDPUV4.........................................            4
Alternative HDPUV10 (Preferred Alternative)................           10
Alternative HDPUV14........................................           14
------------------------------------------------------------------------

    As discussed in Section V.A, the three statutory factors for HDPUV 
standards are similar to and yet somewhat different from the four 
factors that NHTSA considers for passenger car and light truck 
standards, but they still modify ``feasible'' in ``maximum feasible.'' 
NHTSA also interprets the HDPUV factors as giving us broad authority to 
weigh potentially conflicting priorities to determine maximum feasible 
standards. It is firmly within NHTSA's discretion to weigh and balance 
the HDPUV factors in a way that is technology-forcing, although NHTSA 
would find a balancing of the factors in a way that would require the 
application of technology that will not be available in the lead time 
provided by this proposal, or that is not cost-effective, to be beyond 
maximum feasible.
    That said, because HDPUV standards are set in accordance with 49 
U.S.C. 32902(k), NHTSA is not bound by the 32902(h) factors when it 
determines maximum feasible HDPUV standards.\595\ That means that NHTSA 
may, and does, consider the full fuel efficiency of BEVs and PHEVs, and 
that NHTSA may consider the availability and use of overcompliance 
credits, in this proposal. These considerations thus play a role in 
NHTSA's balancing of the HDPUV factors, as described below.
---------------------------------------------------------------------------

    \595\ 49 U.S.C. 32902(h) clearly states that it applies only to 
actions taken under subsections (c), (f), and (g) of 49 U.S.C. 
32902.
---------------------------------------------------------------------------

    In evaluating whether HDPUV standards are appropriate, NHTSA could 
begin by seeking to isolate the effects of new HDPUV standards from 
NHTSA, by understanding effects in the industry that appear to be 
happening for reasons other than potential new NHTSA regulations. NHTSA 
explained in Chapter 1.4.1 of the Draft TSD that the No-Action 
Alternative for HDPUV accounts for existing technology on HDPUVs, 
technology sharing across platforms, manufacturer compliance with 
existing HDPUV standards from NHTSA and EPA (i.e., those standards set 
in the Phase 2 final rule in 2016 for MY 2021 to MY 2029), manufacturer 
compliance with California's ACT and ZEV programs, and foreseeable 
voluntary manufacturer application of fuel-efficiency-improving 
technologies (whether because of tax credits or simply because the 
technologies are estimated to pay for themselves within 30 months). One 
consequence of accounting for these effects in the No-Action 
Alternative is that the effects of the different regulatory 
alternatives under consideration appear less cost-beneficial than they 
would otherwise. Nonetheless, NHTSA believes that this is reasonable 
and appropriate to better ensure that NHTSA has the clearest possible 
understanding of the effects of the decision being made, as opposed to 
the effects of many things that will be occurring simultaneously. All 
estimates of effects of the different regulatory alternatives presented 
in this section are thus relative to the No-Action Alternative.
    Other information that are relevant to whether HDPUV standards are 
appropriate could include how much energy we estimate they would 
conserve; the magnitude of emissions reductions; possible safety 
effects, if any; and estimated effects on sales and employment. In 
terms of energy conservation, Alternative HDPUV14 would conserve the 
most energy and produce the greatest reduction in fuel expenditure, as 
shown below:

  Table V-14--Fuel Consumption Under HDPUV Regulatory Alternatives, as
                    Compared to No-Action Alternative
                         [quads, CYs 2022-2050]
------------------------------------------------------------------------
               Fuel type                   HDPUV4    HDPUV10    HDPUV14
------------------------------------------------------------------------
Diesel.................................          0      0.001      0.003
E85....................................          0     -0.002     -0.009
Gasoline...............................     -0.013     -0.305     -1.357
Electricity............................      0.004      0.083      0.345

[[Page 56352]]

 
Total..................................     -0.009     -0.223     -1.019
------------------------------------------------------------------------


             Table V-15--Lifetime Fuel Expenditure Under HDPUV Regulatory Alternatives, as Compared to No-Action Alternative, MYs 2030-2038
                                                                 [$ In millions, 3% DR]
--------------------------------------------------------------------------------------------------------------------------------------------------------
                Model year                     2030       2031       2032       2033       2034       2035       2036       2037       2038      Total
--------------------------------------------------------------------------------------------------------------------------------------------------------
HDPUV4....................................       -4.4       -5.0       -4.8       -9.1       -8.8       -8.3       -8.1       -7.6       -7.6      -63.7
HDPUV10...................................      -15.5      -27.4      -26.9     -303.8     -320.9     -313.0     -306.2     -301.5     -295.5   -1,910.7
HDPUV14...................................      -38.4     -622.8     -611.1   -1,146.8   -1,139.8   -1,511.0   -1,478.6   -1,451.6   -1,422.7   -9,422.8
--------------------------------------------------------------------------------------------------------------------------------------------------------


               Table V-16--Per-Vehicle Lifetime Fuel Expenditure Under HDPUV Regulatory Alternatives, as Compared to No-Action Alternative
                                                                       [$, 3% DR]
--------------------------------------------------------------------------------------------------------------------------------------------------------
                      Model Year                          2030       2031       2032       2033       2034       2035       2036       2037       2038
--------------------------------------------------------------------------------------------------------------------------------------------------------
HDPUV4...............................................         -6         -6         -6        -12        -12        -12        -12        -12        -12
HDPUV10..............................................        -19        -34        -35       -400       -427       -430       -433       -437       -439
HDPUV14..............................................        -39       -764       -772     -1,505     -1,516     -2,077     -2,092     -2,106     -2,117
--------------------------------------------------------------------------------------------------------------------------------------------------------

    Assuming that benefits to energy security correlate directly with 
fuel consumption avoided, Alternative HDPUV14 would likely also 
contribute the most to improving U.S. energy security. The discussion 
about energy security effects of passenger car and light truck 
standards applies for HDPUVs as well.
    In terms of environmental benefits, Alternative HDPUV14 is also 
estimated to be the most beneficial for most metrics:

  Table V-17--Emissions Effects Under HDPUV Regulatory Alternatives, as
                    Compared to No-Action Alternative
------------------------------------------------------------------------
                                           HDPUV4    HDPUV10    HDPUV14
------------------------------------------------------------------------
Estimated CO2 emissions avoided (mmt)..      -0.91     -22.28    -101.28
Maximum observed change in criteria
 pollutant emissions compared to No-
 Action Alternative:
    NOX total..........................       0.0%       0.3%       0.8%
    NOX upstream.......................       0.1%       0.9%       3.6%
    NOX downstream.....................      -0.1%      -1.3%      -4.3%
    PM2.5 total........................       0.0%      -0.1%      -0.7%
    PM2.5 upstream.....................       0.1%       1.1%       4.4%
    PM2.5 downstream...................      -0.1%      -2.0%      -6.8%
    SOX total..........................       0.1%       1.4%       6.0%
    SOX upstream.......................       0.1%       1.6%       6.6%
    SOX downstream.....................      -0.1%      -2.6%      -9.5%
------------------------------------------------------------------------

    The criteria pollutant effects demonstrate that increased 
electrification (which increases faster under more stringent 
alternatives) reduces vehicle-based emissions while increasing upstream 
emissions due to increased demand for electricity.
    Some other effects are fairly muted, possibly due to the relatively 
small size of the HDPUV fleet. The safety effects associated with the 
HDPUV alternatives are extremely small, too small to affect our 
decision-making in this proposal. Readers may refer to Chapter 8.3.4.5 
of the PRIA for specific information. For sales and employment, readers 
may refer to Chapter 8.3.2.3 of the PRIA for more specific information, 
but there is very little difference in sales between HDPUV 
alternatives, less than one percent relative to the No-Action 
Alternatives. Employment effects are of similar relative magnitude; 
HDPUV10 and HDPUV14 both subtract slightly from the baseline employment 
utilization, as sales declines produce a small decrease in labor 
utilization that are not offset by technology effects (i.e., that 
development and deployment of new fuel-efficient technologies increases 
demand for labor). Estimated safety, sales, and employment effects are 
thus all too small to be dispositive.
    In evaluating whether HDPUV standards are cost-effective, NHTSA 
could consider different ratios of cost versus the primary benefits of 
the standards, such as fuel saved and GHG emissions avoided. Table V-18 
and Table V-19 include a number of informative metrics of the proposed 
HDPUV alternatives relative to the No-Action Alternative. None of the 
proposed action alternatives emerges as a clearly superior option when 
evaluated along this dimension. When considering aggregate societal 
effects, as well as when narrowing the focus to private benefits and 
costs, HDPUV10 produces the highest benefit-cost ratios.

[[Page 56353]]



      Table V-18--Cost-Effectiveness Metrics Under HDPUV Regulatory
           Alternatives, as Compared to No-Action Alternative
                             [$2021, 3% DR]
------------------------------------------------------------------------
                 Ratio                     HDPUV4    HDPUV10    HDPUV14
------------------------------------------------------------------------
Total societal benefits to total              1.29       2.08       1.85
 societal costs (CYs 2022-2050, 3% SC-
 GHG discount rate)....................
Total private benefits to total private       1.40       2.23       1.87
 costs (CYs 2022-2050).................
Fuel savings to regulatory cost (CYs          2.57       2.32       2.37
 2022-2050)............................
Sales-weighted per-vehicle fuel savings       2.81       2.83       2.65
 to regulatory cost (MYs 2030-2035)....
Sales-weighted per-vehicle fuel savings       3.11       3.01       2.90
 to regulatory cost (MYs 1983-2038)....
Total societal benefits to total              2.46       3.36       3.00
 regulatory cost (CYs 2022-2050, 3% SC-
 GHG discount rate)....................
------------------------------------------------------------------------


      Table V-19--Cost-Effectiveness Metrics Under HDPUV Regulatory
           Alternatives, as Compared to No-Action Alternative
                             [$2021, 7% DR]
------------------------------------------------------------------------
                 Ratio                     HDPUV4    HDPUV10    HDPUV14
------------------------------------------------------------------------
Total societal benefits to total              1.68       2.45       2.17
 societal costs (CYs 2022-2050, 3% SC-
 GHG discount rate)....................
Total private benefits to total private       1.00       2.00       1.61
 costs (CYs 2022-2050).................
Fuel savings to regulatory cost (CYs          2.19       2.03       2.03
 2022-2050)............................
Sales-weighted per-vehicle fuel savings       2.16       2.18       2.04
 to regulatory cost (MYs 2030-2035)....
Sales-weighted per-vehicle fuel savings       2.39       2.32       2.23
 to regulatory cost (MYs 1983-2038)....
Total societal benefits to total              3.01       3.79       3.35
 regulatory cost (CYs 2022-2050, 3% SC-
 GHG discount rate)....................
------------------------------------------------------------------------

    Because NHTSA considers multiple DRs in its analysis, and because 
analysis also includes multiple values for the SC-GHG, we also estimate 
the following cumulative values for each regulatory alternative:

 Table V-20--Summary of Cumulative Benefits and Costs for CY 2022-2050 (2021$ Billions), by Alternative, SC-GHG
                                                  Value, and DR
----------------------------------------------------------------------------------------------------------------
                                                        3% Discount rate                 7% Discount rate
                                               -----------------------------------------------------------------
                  Alternative                                            Net                              Net
                                                  Costs     Benefits   benefits    Costs     Benefits   benefits
----------------------------------------------------------------------------------------------------------------
SC-GHG discounted at 5 percent:
    HDPUV4....................................       0.09       0.08     -0.005       0.04       0.04     -0.001
    HDPUV10...................................       2.07       3.58       1.50       0.99       1.69       0.69
    HDPUV14...................................       9.43      14.03       4.61       4.67       6.73       2.05
SC-GHG discounted at 3 percent:
    HDPUV4....................................       0.09       0.11       0.03       0.04       0.07       0.03
    HDPUV10...................................       2.07       4.32       2.25       0.99       2.43       1.44
    HDPUV14...................................       9.43      17.43       8.00       4.67      10.12       5.45
SC-GHG discounted at 2.5 percent:
    HDPUV4....................................       0.09       0.14       0.05       0.04       0.09       0.05
    HDPUV10...................................       2.07       4.85       2.78       0.99       2.97       1.97
    HDPUV14...................................       9.43      19.87      10.44       4.67      12.56       7.89
SC-GHG discounted at 3 percent, 95th
 percentile:
    HDPUV4....................................       0.09       0.19       0.11       0.04       0.15       0.11
    HDPUV10...................................       2.07       6.31       4.24       0.99       4.42       3.43
    HDPUV14...................................       9.43      26.53      17.10       4.67      19.23      14.55
----------------------------------------------------------------------------------------------------------------

    E.O. 12866 and Circular A-4 direct agencies to consider maximizing 
net benefits in rulemakings whenever possible and consistent with 
applicable law. Because it can inform NHTSA's consideration of the 
statutory factors and because it is directed by E.O. 12866 and OMB 
guidance, NHTSA does evaluate and consider net benefits associated with 
different potential future HDPUV standards. As Table V-20 shows, our 
analysis suggests that HDPUV14 produces the largest net benefits, 
although we note that the step from HDPUV10 to HDPUV14 results in a 
substantial jump in total costs.
    Our analysis also suggests that all alternatives will result in 
fuel savings for consumers, and that all alternatives will be cost-
effective under nearly every listed metric of comparison and at either 
DR. Overall, avoided climate damages are lower and with each 
alternative the ratio of cost to benefits for this metric decreases due 
to increased cost and diminishing climate benefits. As discussed 
earlier, the HDPUV fleet is a smaller fleet compared to passenger cars 
and light trucks, and so for a manufacturer to meet standards that are 
more or less stringent, they must transition a relatively larger 
portion of that smaller fleet to new technologies. Thus, under many 
comparisons, HDPUV10 appears the most cost-effective; under others, 
HDPUV4 appears the most cost-effective.
    As discussed above for passenger car and light truck standards, 
while maximizing net benefits is a valid decision criterion for 
choosing among alternatives, provided that appropriate

[[Page 56354]]

consideration is given to impacts that cannot be monetized, it is not 
the only reasonable decision perspective. We recognize that what we 
include in our cost-benefit analysis affects our estimates of net 
benefits. We also note that important benefits cannot be monetized--
including the full health and welfare benefits of reducing climate and 
other pollution, which means that the benefits estimates are 
underestimates. Thus, given the uncertainties associated with many 
aspects of this analysis, NHTSA does not rely solely on net benefit 
maximization, and instead considers it as one piece of information that 
contributes to how we balance the statutory factors, in our 
discretionary judgment.
    In evaluating whether HDPUV standards are technologically feasible, 
NHTSA could consider whether the standards represented by the different 
regulatory alternatives could be met using technology expected to be 
available in the rulemaking time frame. On the one hand, the HDPUV 
analysis only employs existing technologies, and our analysis suggests 
fairly widespread compliance with all regulatory alternatives, which 
might initially suggest that technological feasibility is not at issue 
for this proposal. At the industry level, technology penetration rates 
estimated to meet the different regulatory alternatives in the 
different MYs would be as follows:
BILLING CODE 4910-59-P

[[Page 56355]]

[GRAPHIC] [TIFF OMITTED] TP17AU23.110

BILLING CODE 4910-59-C
    As Table V-21 shows, it is immediately clear that most technology 
application between now and MY 2038 would be occurring as a result of 
baseline efforts and would not be an effect of new NHTSA standards. 
Under

[[Page 56356]]

the baseline, as early as MY 2033, fully 80 percent of the fleet would 
be electrified (including SHEV, PHEV, and BEV), with slight shifts over 
time in the relative percentages of those technologies' representation 
in the fleet (BEVs taking away some market share from PHEVs by MY 
2038). NHTSA believes that these baseline technology penetration rates, 
while high, may potentially be feasible in this time frame, given 
projected trends for HD vans in particular. Due to the relatively small 
number of models in the HDPUV fleet as compared to the passenger car 
and light truck fleets, just a few models becoming electrified can have 
large effects in terms of the overall fleet. NHTSA also recognizes that 
these baseline technology penetration rates result from our assumptions 
about battery costs and available tax credits, among other things.\597\
---------------------------------------------------------------------------

    \596\ The list of these engines is discussed in Draft TSD 
Chapter 3.1.
    \597\ All EVs have zero emissions and are asisgned the fuel 
consumption test group result to a value of zero gallons per 100 
miles per 49 CFR 535.6(a)(3)(iii).
---------------------------------------------------------------------------

    Against the backdrop of this baseline, HDPUV4 would require no 
additional technology at all, on average, which explains why the per-
vehicle fuel cost savings associated with it is nearly zero. HDPUV10 
could be met with an additional 1 percent increase in PHEVs starting in 
MY 2033, and a 1 to 2 percent increase in advanced engines in the later 
years of the rulemaking time frame. HDPUV14 could be met with an 
additional 4 percent increase in PHEVs, an additional 3 percent 
increase in BEVs, and an additional 10 percent increase in advanced 
engines by MY 2038.
    As in the analysis for passenger cars and light trucks, however, 
NHTSA finds manufacturer-level results to be particularly informative 
for this analysis. Of the six manufacturers modeled for HDPUV, 
Mercedes-Benz, Nissan, Rivian, and Stellantis would be able to meet all 
regulatory alternatives with baseline technologies--only Ford and GM 
show any activity in response to any of the regulatory alternatives. 
HDPUV14 pushes both Ford and GM to increase their volumes of advanced 
gasoline engines and PHEVs, and GM to increase its volume of BEVs.

                  Table V-22--Technology Availability by Manufacturer for Selected Model Years
----------------------------------------------------------------------------------------------------------------
                                           HDPUV4          HDPUV10         HDPUV14     MY 2030 to MY 2038 Change
                                      --------------------------------------------------------------------------
                                        2030    2038    2030    2038    2030    2038
                                         (%)     (%)     (%)     (%)     (%)     (%)    HDPUV4  HDPUV10  HDPUV14
----------------------------------------------------------------------------------------------------------------
Ford:
    Strong Hybrid (all types)........      28      28      28      28      28      28        0        0        0
    PHEV (all types).................       0       0       0       0       0       4        0        0       +4
    BEV (all types)..................      40      51      40      51      40      51      +11      +11      +11
    Advanced Engines.................      11       2      11       2      12      17      -10      -10       +6
    Advanced AERO....................     100     100     100     100     100     100        0        0        0
    Advanced MR......................       0       0       0       0       0       0        0        0        0
GM:
    Strong Hybrid (all types)........      45      16      45      16      45      16      -29      -29      -28
    PHEV (all types).................       0      29       0      34       0      37      +29      +34      +37
    BEV (all types)..................       5      18       5      18       5      27      +13      +13      +21
    Advanced Engines.................       7       6       7      11       7      20        0       +5      +14
    Advanced AERO....................     100     100     100     100     100     100        0        0        0
    Advanced MR......................       0       0       0       0       0       0        0        0        0
Mercedes-Benz:
    Strong Hybrid (all types)........      60      21      60      21      60      21      -40      -40      -40
    PHEV (all types).................       0       0       0       0       0       0        0        0        0
    BEV (all types)..................      40      79      40      79      40      79      +40      +40      +40
    Advanced Engines.................       0       0       0       0       0       0        0        0        0
    Advanced AERO....................     100     100     100     100     100     100        0        0        0
    Advanced MR......................       0       0       0       0       0       0        0        0        0
Nissan:
    Strong Hybrid (all types)........       1       0       1       0       1       0       -1       -1       -1
    PHEV (all types).................       0       0       0       0       0       0        0        0        0
    BEV (all types)..................      64      70      64      70      64      70       +6       +6       +6
    Advanced Engines.................       5      30       5      30       5      30      +25      +25      +25
    Advanced AERO....................     100     100     100     100     100     100        0        0        0
    Advanced MR......................       0       0       0       0       0       0        0        0        0
Rivian:
    Strong Hybrid (all types)........       0       0       0       0       0       0        0        0        0
    PHEV (all types).................       0       0       0       0       0       0        0        0        0
    BEV (all types)..................     100     100     100     100     100     100        0        0        0
    Advanced Engines.................       0       0       0       0       0       0        0        0        0
    Advanced AERO....................       0       0       0       0       0       0        0        0        0
    Advanced MR......................       0       0       0       0       0       0        0        0        0
Stellantis:
    Strong Hybrid (all types)........       0      47       0      47       0      47      +47      +47      +47
    PHEV (all types).................       0       1       0       1       0       1       +1       +1       +1
    BEV (all types)..................      31      50      31      50      31      50      +19      +19      +19
    Advanced Engines.................      69       1      69       1      69       1      -67      -67      -67
    Advanced AERO....................     100     100     100     100     100     100        0        0        0
    Advanced MR......................       0       0       0       0       0       0        0        0        0
----------------------------------------------------------------------------------------------------------------

    Again, it is clear that a great deal of technology application is 
expected in response to the baseline, as evidenced by the fact that 
technology penetration rates for most manufacturers do not change 
between alternatives. For example, Stellantis is assumed to go from 0 
percent strong hybrids in its HDPUV fleet in MY 2030 to 47 percent 
strong hybrids by MY 2038 under each regulatory alternative, which 
means that the regulatory alternatives are not influencing that 
decision--because if they were, we would see technology differences 
between the alternatives. Of

[[Page 56357]]

the two manufacturers who appear to need to change technology 
application to meet HDPUV10 and HDPUV14, Ford and GM, we note that the 
changes for Ford are relatively minor: replacing 4 percent of its 
``advanced engine'' vehicles with PHEVs between MYs 2030 and 2038. GM 
shows more movement, but NHTSA suspects this may be an artifact of our 
relatively-meager data for the HDPUV fleet. It is very possible that 
the apparent increase in BEV and advanced engine rates could be due to 
the fact that technologies in the baseline fleet are based on Phase 1 
standards and manufacturers have not started adopting technologies to 
meet Phase 2 standards. Additionally, NHTSA is allowed to consider 
banked overcompliance credits for the HDPUV fleet,\598\ as well as the 
full fuel efficiency of AFVs like BEVs and PHEVs.\599\ Combined with 
the fact that BEVs and the electric operation of PHEVs are granted 0 
gal/100 miles fuel consumption for compliance purposes, our analysis 
shows that even with one redesign we see large improvements in the 
fleet even at low volumes. Based on the information before us, NHTSA 
cannot conclude that technological feasibility is necessarily a barrier 
to choosing any of regulatory alternatives considered in this proposal.
---------------------------------------------------------------------------

    \598\ See Manufacturers tab in the CAFE Model Input file 
market_data_HDPUV_ref.xlsx for HDPUV banked credits.
    \599\ 49 CFR 535.6(a)(3)(iii).
---------------------------------------------------------------------------

    The information presented thus far suggests that HDPUV14 would 
result in the best outcomes for energy conservation, including fuel 
consumption and fuel expenditure reduced, energy security, climate 
effects, and most criteria pollutant effects; that it would produce the 
largest net benefits, and that it is likely achievable with not much 
more technology than would be applied in the baseline regardless of new 
HDPUV standards from NHTSA; even if it would not necessarily be the 
most cost-effective, would result in the highest overall costs, and 
does not provide the largest consumer net benefits. There is likely a 
credible case to be made for choosing HDPUV14. For purposes of this 
proposal, however, NHTSA tentatively concludes that some conservatism 
may still be appropriate.
    There are several reasons for this conservatism. First, NHTSA 
recognizes that standards have remained stable for this segment for 
many years, since 2016. While on the one hand, that may mean that the 
segment has room for improvement, or at least for standards to catch up 
to where the fleet is, NHTSA is also mindful that the sudden imposition 
of stringency where there was previously little may require some 
adjustment time especially with technologies like BEVs and PHEVs that 
have not been in mass production in the HDPUV space. Second, NHTSA 
acknowledges that our available data in this segment may be less 
complete than our data for passenger cars and light trucks. Compared to 
the CAFE program's robust data submission requirements, manufacturers 
submit many fewer data elements in the HD program, and the program is 
newer, so we have many fewer years of historical data. If NHTSA's 
technology or vehicle make/model assumptions in the baseline lags on 
road production, then our estimated manufacturer responses to potential 
new HDPUV standards could lack realism in important ways, particularly 
given the relatively smaller fleet and fewer numbers of make/models 
across which manufacturers can spread technology improvements in 
response to standards. Although NHTSA also relies on manufacturer media 
publications for announcements of new vehicles and technologies, we are 
considerate of how those will be produced in large quantities and if 
they can be considered by other competitors due to intellectual 
property issues and availability.
    Third, again perhaps because of the relatively smaller fleet and 
fewer numbers of make/models, the sensitivity analysis for HDPUVs 
strongly suggests that uncertainty in the input assumptions can have 
significant effects on outcomes. As with any analysis of sufficient 
complexity, there are a number of critical assumptions here that 
introduce uncertainty about manufacturer compliance pathways, consumer 
responses to fuel efficiency improvements and higher vehicle prices, 
and future valuations of the consequences from higher HDPUV standards. 
Recognizing that uncertainty, NHTSA also conducted nearly 40 
sensitivity analysis runs for the HDPUV fleet analysis. The entire 
sensitivity analysis is presented in Chapter 9 of the PRIA, 
demonstrating the effect that different assumptions would have on the 
costs and benefits associated with the different regulatory 
alternatives. While NHTSA considers dozens of sensitivity cases to 
measure the influence of specific parametric assumptions and model 
relationships, only a small number of them demonstrate meaningful 
impacts to net benefits under the different alternatives.
    The results of the sensitivity analyses for HDPUVs are different 
from the sensitivity analysis results for passenger cars and light 
trucks. Generally speaking, for HDPUVs, varying the inputs seems either 
to make no difference at all, or to make a fairly major difference. As 
suggested above, NHTSA interprets this as likely resulting from the 
relatively smaller size and ``blockiness'' of the HDPUV fleet: there 
are simply fewer vehicles, and fewer models, so variation in input 
parameters may cause notable moves in tranches of the fleet that are 
large enough (as a portion of the total HDPUV fleet) to produce 
meaningful effects on the modeling results. For example, Table V-23 
shows estimated per-vehicle costs by HDPUV manufacturer, by regulatory 
alternative, for the RC (the central analysis) and several selected 
sensitivity runs with the following effects:

      Table V-23--Effects of Selected Sensitivity Runs on Per-Vehicle Costs in MY 2038 (2021$), HDPUV Fleet
----------------------------------------------------------------------------------------------------------------
                                                                                      Sensitivity runs
                                                                          --------------------------------------
            Manufacturer                    Regulatory         Reference                 Tax credit    AEO 2022
                                            alternative           case       Battery    passthrough    low oil
                                                                            costs +20%      75%         price
----------------------------------------------------------------------------------------------------------------
Ford................................  No-Action.............        2,519          257         -102         -285
                                      HDPUV4................            8          327          261          388
                                      HDPUV10...............           17        2,821        2,126        2,322
                                      HDPUV14...............          451        4,144        3,084        3,263
GM..................................  No-Action.............          645         -990       -1,358       -1,395
                                      HDPUV4................            0            0            0           13

[[Page 56358]]

 
                                      HDPUV10...............          405        2,810        2,382        2,425
                                      HDPUV14...............        1,517        4,343        3,570        3,606
Mercedes-Benz.......................  No-Action.............        2,080          437          854         -381
                                      HDPUV4................            3           -3           -1           -1
                                      HDPUV10...............            3        1,303           68          851
                                      HDPUV14...............            2        2,474          418        1,652
Nissan..............................  No-Action.............        5,562        2,229        1,863        1,492
                                      HDPUV4................           -3        1,037          751        1,147
                                      HDPUV10...............           -4        3,575        2,725        2,927
                                      HDPUV14...............           -3        4,534        3,835        4,207
Rivian..............................  No-Action.............            0            0            0            0
                                      HDPUV4................            0            0            0            0
                                      HDPUV10...............            0            0            0            0
                                      HDPUV14...............            0            0            0            0
Stellantis..........................  No-Action.............        1.095       -1,446       -1,742       -2,055
                                      HDPUV4................            0            0            0            0
                                      HDPUV10...............            2        2,200        1,658        1,902
                                      HDPUV14...............            2        3,699        2,688        2,891
Industry Average....................  No-Action.............        1,520         -477         -781         -970
                                      HDPUV4................            3          138          111          166
                                      HDPUV10...............          131        2,483        2,033        2,092
                                      HDPUV14...............          633        3,820        3,065        3,062
----------------------------------------------------------------------------------------------------------------

    In this table, ``Battery Costs +20%'' means that direct 
manufacturing costs for batteries would be 20 percent higher than 
estimated for the central analysis; ``Tax Credit Passthrough 75%'' 
means that 75 percent of the value of modeled tax credits would be 
captured by consumers (meaning that less of the value of modeled tax 
credits would be available to manufacturers to offset vehicle costs, as 
compared to the central analysis); and ``AEO 2022 Low Oil Price'' means 
that the forecasted future price of gasoline would be lower than 
estimated for the central analysis. Dollar values are incremental to 
the No-Action alternative and to the RC, and if they are negative, that 
means that the change in the input assumption causes the model to 
estimate that costs would decrease with the alternate input. These 
cases were not chosen for illustration because NHTSA lacks confidence 
in our assumptions for the central analysis, but simply to show the 
magnitude of the effect of relatively routine alternate assumptions for 
important inputs. The proposed standards for HDPUVs will result in a 
total of 60 percent FE improvement in the rulemaking time frame of only 
6 years. With the vehicles in this segment having the same if not 
longer redesign cycle time, our analysis shows that any change to these 
inputs could have a dramatic impact on the manufacturers. As shown in 
Table V-23 above, the industry average incremental cost for HDPUV10 is 
$131, but that increases to over $2,033 to $2,483 with the change to an 
input that could be due to any number of global circumstances. These 
considerations help give NHTSA confidence that HDPUV10 is maximum 
feasible for the rulemaking time frame.
    Specifically, each of these sensitivity runs illustrate that per-
vehicle costs for nearly every manufacturer to comply with HDPUV10 and 
HDPUV14 could be significantly higher under any of these cases. Looking 
at the industry average results, each of the three sensitivity runs 
presented here could bring per-vehicle costs over $3,000 per vehicle in 
MY 2038. Battery costs only 20 percent higher could bring half the 
manufacturers over $4,000 higher per vehicle. When costs appear to be 
negative in response to the No-Action alternative, that means that it 
is more cost-effective to apply technology in the baseline, which means 
that less technology is available to meet new NHTSA standards (because 
it has already been applied in the baseline), which means that 
relatively more expensive technology is what is left to meet more 
stringent alternatives like HDPUV10 and HDPUV14. For each manufacturer 
(besides Rivian, a small BEV manufacturer), the jump in cost from 
HDPUV4 to HDPUV10 is quite large under each sensitivity run shown; the 
costs for HDPUV14 under each of the sensitivity runs shown would be 
greater than NHTSA would likely conclude was appropriate for this 
segment.
    Again, that is not to say that NHTSA lacks confidence in its 
assumptions, but simply that to the extent uncertainty exists, it 
matters for this segment and the effects that new HDPUV standards would 
have on the affordability of these vehicles. The nature of this fleet--
smaller, with fewer models--and the nature of the technologies that 
this fleet will be applying leading up to and during the rulemaking 
time frame, means that the analysis is very sensitive to changes in 
inputs, and the inputs are admittedly uncertain. If the uncertainty 
causes NHTSA to set standards higher than they would otherwise have 
been, and industry is unable to meet the standards, the resources they 
would have to expend on civil penalties (which can potentially be much 
higher for HDPUVs than for passenger cars and light truck) would be 
diverted from their investments in the technological transition, and 
the estimated benefits would not come to pass anyway. To provide some 
margin for that uncertainty given the technological transition that 
this segment is trying to make, NHTSA believes that some conservatism 
is reasonable and appropriate for this round of standards.
    We also note, that because NHTSA does consider BEV technologies in 
the HDPUV analysis, and because our current regulations assign BEVs a 
fuel consumption value for compliance

[[Page 56359]]

purposes of 0 gal/100 miles, this significantly influences our modeling 
results. This is an artifact of the mathematics of averaging, where 
including a ``0'' value in the calculation effectively reduces other 
values by as much as 50 percent (depending on sample size) and is 
exaggerated when BEV-only manufacturers are considered in industry-
average calculations. This effect creates the appearance of 
overcompliance at the industry level. As for the analysis for passenger 
cars and light trucks, examining individual manufacturer results can be 
more informative, and Chapter 8.3 of the PRIA shows that non-BEV-only 
manufacturers are more challenged by, for example, HDPUV14, although 
overcompliance is still evident in many MYs. This underscores the 
effect of BEVs on compliance, particularly when their fuel consumption 
is counted as 0 even though their energy consumption is non-zero. It 
also indirectly underscores the effect of the 32902(h) restrictions on 
NHTSA's decision-making for passenger car and light truck standard 
stringency, which does not apply in the HDPUV context. We are seeking 
comment on the assignment of 0 gal/100 miles value for HDPUV BEV 
compliance. Any change to this value would change the appearance of 
overcompliance in NHTSA's analysis, and this is another potential 
reason to be conservative in our proposal.
    Based on the information in the record, NHTSA tentatively concludes 
that HDPUV10 represents the maximum feasible standards for HDPUVs in 
the MYs 2030 to 2035 time frame. While HDPUV14 could potentially save 
more fuel and reduce emissions further, it is less cost-effective than 
HDPUV10 by every metric that NHTSA considered, and the longer redesign 
cycles in this segment make NHTSA cautious of proposing HDPUV14, even 
though this segment has plenty of opportunity to improve. Moreover, the 
effects of uncertainty for our analytical inputs are significant in 
this analysis, as discussed, and NHTSA believes some conservatism is 
appropriate for this rulemaking time frame. HDPUV10 will still 
encourage technology application for some manufacturers while 
functioning as a backstop for the others, and it remains net beneficial 
for consumers. For these reasons, NHTSA is proposing HDPUV10 for MYs 
2030-2035 HDPUVs. We seek comment on this tentative conclusion, on the 
feasibility of HDPUV10 in light of the regulatory analysis, and on all 
aspects of this discussion, including whether and how standards more 
closely aligned with EPA's standards for these vehicles would be 
appropriate and maximum feasible for NHTSA to adopt for the model years 
subject to this rulemaking.
3. Severability
    For the reasons described above, NHTSA believes that its authority 
to propose and implement CAFE and HDPUV standards for the various 
fleets described is well-supported in law and practice and should be 
upheld in any legal challenge. NHTSA also believes that its exercise of 
its authority reflects sound policy.
    However, in the event that any portion of the proposed rule is 
declared invalid, NHTSA intends that the various aspects of the 
proposal be severable, and specifically, that each proposed standard 
and each year of each proposed standard is severable, as well as the 
various compliance proposals discussed in the following section of this 
preamble. Any of the proposed standards could be implemented 
independently if any of the other proposed standards were struck down, 
and NHTSA firmly believes that it would be in the best interests of the 
nation as a whole for the standards to be applicable in order to 
support EPCA's overarching purpose of energy conservation. Each 
proposed standard is justified independently on both legal and policy 
grounds and could be implemented effectively by NHTSA.

VI. Compliance and Enforcement

    NHTSA is proposing changes to its enforcement programs for LDVs in 
the CAFE program as well for HDPUVs in the Heavy-Duty National Program. 
These changes include: (1) eliminating AC and off-cycle (OC) fuel 
consumption improvement values (FCIVs) for BEVs in the LD program, (2) 
eliminating the 5-cycle and alternative approval pathways for OC FCIVs 
in the LD program, (3) adding additional deadlines for the alternative 
approval process for MYs 2025-2026 for the LD program, (4) eliminating 
OC FCIVs for HDPUVs, (5) making technical amendments to the regulations 
pertaining to advanced technology credits, and (6) making an assortment 
of minor technical amendments. To provide context for these proposed 
changes, this section first provides an overview of NHTSA's enforcement 
programs. The section then discusses and requests comment on each of 
the proposed changes. NHTSA is also requesting comment on phasing out 
FCIVs for CAFE program. Finally, this section concludes with a 
discussion of one requested change, to create a new program for EJ 
credits, that NHTSA has decided is not practical to implement at this 
time.

A. Background

    NHTSA has separate enforcement programs for LDVs in the CAFE 
program and HD vehicles in the Heavy-Duty National program. NHTSA's 
CAFE enforcement program is largely established by EPCA, as amended by 
EISA, and is very prescriptive regarding enforcement. EPCA and EISA 
also clearly specify a number of flexibilities and incentives that are 
available to manufacturers to help them comply with the CAFE standards. 
EISA also provides DOT and NHTSA with the authority to regulate HD 
vehicles, and NHTSA structured the enforcement program for HDPUVs to be 
similar to its LD enforcement program.
    The LD CAFE program includes all vehicles with a Gross Vehicle 
Weight Rating (GVWR) of 8,500 pounds or less as well as vehicles 
between 8,501 and 10,000 pounds that are classified as medium-duty 
passenger vehicles (MDPVs). As prescribed by 49 U.S.C. 32901(a)(19)(B) 
\600\ and defined in 40 CFR 86.1803-01, an MDPV means any HD vehicle 
with a GVWR of less than 10,000 pounds that is designed primarily for 
the transportation of persons \601\ and subject to requirements that 
apply for LD trucks.\602\ The MDHD Program includes all vehicles 8,501 
pounds and up, and the engines that power them, except for MDPVs, that 
are covered under the LD fuel economy program.
---------------------------------------------------------------------------

    \600\ As prescribed in 49 U.S.C. 32901(a)(19)(B), an MDPV is 
``defined in section 86.1803-01 of title 40, Code of Federal 
Regulations, as in effect on the date of the enactment of the Ten-
in-Ten Fuel Economy Act.''
    \601\ 40 CFR 86.1803 defines an MDPV as ``any vehicle which: (1) 
Is an ``incomplete truck'' as defined in this subpart; or (2) Has a 
seating capacity of more than 12 persons; or (3) Is designed for 
more than 9 persons in seating rearward of the driver's seat; or (4) 
Is equipped with an open cargo area (for example, a pick-up truck 
box or bed) of 72.0 inches in interior length or more. A covered box 
not readily accessible from the passenger compartment will be 
considered an open cargo area for purposes of this definition.''
    \602\ See Heavy-duty vehicle definition in 40 CFR 86.1803.
---------------------------------------------------------------------------

    NHTSA's authority to regulate HD vehicles under EISA directs NHTSA 
to establish fuel efficiency standards for commercial medium- and 
heavy-duty on-highway vehicles \603\ and work trucks.\604\ Under this 
authority, NHTSA

[[Page 56360]]

has developed standards for three regulatory categories of HD vehicles: 
combination tractors; HDPUVs; and vocational vehicles. HDPUVs include 
HD vehicles with a GVWR between 8,501 pounds and 14,000 pounds (known 
as Class 2b through 3 vehicles) manufactured as complete vehicles by a 
single or final stage manufacturer or manufactured as incomplete 
vehicles as designated by a manufacturer.\605\ The majority of these 
HDPUVs are 3/4-ton and 1-ton pickup trucks, 12-and 15-passenger vans, 
and large work vans that are sold by vehicle manufacturers as complete 
vehicles, with no secondary manufacturer making substantial 
modifications prior to registration and use. These vehicles can also be 
sold as cab-complete vehicles (i.e., incomplete vehicles that include 
complete or nearly complete cabs that are sold to secondary 
manufacturers).
---------------------------------------------------------------------------

    \603\ EISA added the following definition to the automobile fuel 
economy chapter of the U.S. Code: ``commercial medium- and heavy-
duty on-highway vehicle'' means an on-highway vehicle with a gross 
vehicle weight rating of 10,000 pounds or more. 49 U.S.C. 
32901(a)(7).
    \604\ EISA added the following definition to the automobile fuel 
economy chapter of the U.S. Code: ``work truck'' means a vehicle 
that--(A) is rated at between 8,500 and 10,000 pounds gross vehicle 
weight; and (B) is not a medium-duty passenger vehicle (as defined 
in section 86.1803-01 of title 40, Code of Federal Regulations, as 
in effect on the date of the enactment of [EISA]). 49 U.S.C. 
32901(a)(19).
    \605\ See 49 CFR 523.7, 40 CFR 86.1801-12, 40 CFR 86.1819-17, 40 
CFR 1037.150.
---------------------------------------------------------------------------

B. Overview of Enforcement

    This subsection is intended to provide a general overview of 
NHTSA's enforcement of its fuel economy and fuel efficiency standards 
in order to provide context for the discussion of the proposed changes 
to these enforcement programs. At a high-level, NHTSA's fuel efficiency 
and fuel economy enforcement programs encompass how NHTSA determines 
whether manufacturers comply with standards for each MY, and how 
manufacturers may use compliance flexibilities and incentives, or 
alternatively address noncompliance through paying civil penalties. 
NHTSA's goal in administering these programs is to balance the energy-
saving purposes of the authorizing statutes against the benefits of 
certain flexibilities and incentives. More detailed explanations of 
NHTSA's enforcement programs have also been included in recent 
rulemaking documents.606 607
---------------------------------------------------------------------------

    \606\ For more detailed explanations of CAFE enforcement, see 77 
FR 62649 (October 15, 2012) and 87 FR 26025 (May 2, 2022).
    \607\ For more detailed explantions of heavy-duty pickup trucks 
and vans fuel efficiency standards and enforcement, see 76 FR 57256 
(September 15, 2011) and 81 FR 73478 (October 25, 2016).
---------------------------------------------------------------------------

1. Light Duty CAFE Program
    As mentioned above, there are three primary components to NHTSA's 
compliance program: (1) determining compliance; (2) using flexibilities 
and incentives; and (3) paying civil penalties for shortfalls. The 
following table provides an overview of the CAFE program for LDVs and 
MDPVs.

                  Table V-24--Overview of Compliance for Corporate Average Fuel Economy Program
        [Vehicles with a GVWR of 8,500 lbs. or less and MDPVs with a GVWR between 8,501 and 10,000 lbs.]
----------------------------------------------------------------------------------------------------------------
                                         Fleet performance requirements
-----------------------------------------------------------------------------------------------------------------
                                      Applicable  regulation                                Proposed changes in
             Component                (statutory  authority)       General description             NPRM?
----------------------------------------------------------------------------------------------------------------
Fuel Economy Standards.............  49 CFR 531.5 and 49 CFR   Standards are footprint-    Yes: Proposed
                                      533.5 (49 U.S.C. 32902).  based fleet average         amendments to 49 CFR
                                                                standards for each of a     531.5(c)(2) and 49
                                                                manufacturer's fleets       CFR 533.5(a) to set
                                                                (i.e., domestic passenger   standards for MY
                                                                vehicle, import passenger   2027-2032.
                                                                vehicle, and light truck)
                                                                and expressed in miles
                                                                per gallon (mpg). NHTSA
                                                                sets average fuel economy
                                                                standards that are the
                                                                maximum feasible for each
                                                                fleet for each model
                                                                year. In setting these
                                                                standards, NHTSA
                                                                considers technological
                                                                feasibility, economic
                                                                practicability, the
                                                                effect of other motor
                                                                vehicle standards of the
                                                                Government on fuel
                                                                economy, and the need of
                                                                the U.S. to conserve
                                                                energy. NHTSA is
                                                                precluded from
                                                                considering the fuel
                                                                economy of vehicles that
                                                                operate only on
                                                                alternative fuels, the
                                                                portion of operation of a
                                                                dual fueled vehicle
                                                                powered by alternative
                                                                fuel, and the trading,
                                                                transferring, or
                                                                availability of credits.
Minimum Domestic Passenger Car       49 CFR 531.5 (49 U.S.C.   Minimum fleet standards     Yes: Proposed
 Standards.                           32902(b)(4)).             for domestically            amendments to 49 CFR
                                                                manufactured passenger      531.5(d) to set
                                                                vehicles.                   standards for MY
                                                                                            2027-2032.
----------------------------------------------------------------------------------------------------------------
                                      Determining Average Fleet Performance
----------------------------------------------------------------------------------------------------------------
2-Cycle Testing....................  49 CFR 531.6(a) citing    Vehicle testing is          No proposed changes.
                                      40 CFR part 600 and 49    conducted by EPA using
                                      CFR 533.6 citing 40 CFR   the Federal Test
                                      part 600 (49 U.S.C.       Procedure (Light-duty FTP
                                      32904).                   or ``city'' test) and
                                                                Highway Fuel Economy Test
                                                                (HFET or ``highway''
                                                                test).

[[Page 56361]]

 
AC efficiency FCIV.................  49 CFR 531.6(b)(1) and    This adjustment to the      Yes: Proposed changes
                                      49 CFR 533.6(c)(1) (49    results from the 2-cycle    to 49 CFR 531.6 and
                                      U.S.C. 32904) citing 40   testing accounts for fuel   533.6 to eliminate
                                      CFR 86.1868-12.           consumption improvement     AC efficiency FCIVs
                                                                from technologies that      for BEVs starting in
                                                                improve AC efficiency       MY 2027.
                                                                that are not accounted
                                                                for in the 2-cycle
                                                                testing. The AC
                                                                efficiency FCIV program
                                                                began in MY 2017.
Off-cycle FCIV.....................  49 CFR 531.6(b)(2) and    This adjustment to the      Yes: Proposing
                                      (3) and 49 CFR            results from the 2-cycle    changes to 49 CFR
                                      533.6(c)(3) and (4) (49   testing accounts for fuel   531.6 and 533.6 to
                                      U.S.C. 32904) citing 40   consumption improvement     eliminate off-cycle
                                      CFR 86.1869-12.           from technologies that      menu FCIVs for BEVs
                                                                are not accounted for or    and to eliminate the
                                                                not fully accounted for     5-cycle and
                                                                in the 2-cycle testing.     alternative
                                                                The off-cycle FCIV          approvals starting
                                                                program began in MY 2017.   in MY 2027. PHEVs
                                                                                            retain benefits.
                                                                                            Proposing a 60-day
                                                                                            response deadline
                                                                                            for requests for
                                                                                            information
                                                                                            regarding off-cycle
                                                                                            requests for MY 2025-
                                                                                            2026.
Advanced full-size pickup trucks     49 CFR 533.6(c)(2)        This adjustment increases   No proposed changes.
 FCIV.                                citing 40 CFR 86.1870-    a manufacturer's average    The program is set
                                      12 (49 U.S.C. 32904).     fuel economy for            to sunset in MY 2024
                                                                hybridized and other        and NHTSA is not
                                                                performance-based           proposing to extend
                                                                technologies for MY 2017    it.
                                                                and 2024.
Dedicated alternative fueled         49 CFR 536.10 citing 40   EPA calculates the fuel     No proposed changes.
 vehicles.                            CFR 600.510-12(c) (49     economy of dedicated
                                      U.S.C. 32905(a) and       alternative fueled
                                      (c)).                     vehicles assuming that a
                                                                gallon of liquid/gaseous
                                                                alternative fuel is
                                                                equivalent to 0.15
                                                                gallons of gasoline per
                                                                49 U.S.C. 32905(a). For
                                                                BEVs, EPA uses the
                                                                petroleum equivalency
                                                                factor as defined by the
                                                                Department of Energy (see
                                                                10 CFR 474.3) (per 49
                                                                U.S.C. 32904(a)(2).
Dual-fueled vehicles...............  49 CFR 536.10 citing 40   EPA calculates the fuel     No proposed changes.
                                      CFR 600.510-12(c) (49     economy of dual-fueled
                                      U.S.C. 32905(b), (d),     vehicles using a utility
                                      and (e) and 49 U.S.C.     factor to account the
                                      32906(a)).                portion of power energy
                                                                consumption from the
                                                                different energy sources.
                                                                Starting in MY 2019,
                                                                there is no adjustment to
                                                                the fuel economy of dual-
                                                                fueled vehicles other
                                                                than electric hybrids.
                                                                For electric hybrids, EPA
                                                                uses the petroleum
                                                                equivalency factor for
                                                                the electric portion of
                                                                the vehicle's expected
                                                                energy use (per 49 U.S.C.
                                                                32904(a)(2).
----------------------------------------------------------------------------------------------------------------
                     Earning and Using Credits for Overcompliance and Addressing Shortfalls
----------------------------------------------------------------------------------------------------------------
Earning Credits....................  49 CFR 536.4 (49 U.S.C.   Manufacturers earn credits  No proposed changes.
                                      32903(a)).                for each one tenth of
                                                                mile by which the average
                                                                fuel economy vehicles in
                                                                a particular compliance
                                                                category in a model year
                                                                exceeds the applicable
                                                                fuel economy standard,
                                                                multiplied by the number
                                                                of vehicles sold in that
                                                                compliance category
                                                                (i.e., fleet).
Carry-forward Credits..............  49 U.S.C. 32903(a)(2)...  Manufacturers may carry-    No proposed changes.
                                                                forward credits up to 5
                                                                model years into the
                                                                future.
Carry-back Credits.................  49 CFR part 536 (49       Manufacturers may carry-    No proposed changes.
                                      U.S.C. 32903(a)(1)).      back credits up to 3
                                                                model years into the past.
Credit Transfers...................  49 CFR part 536 (49       Manufacturers may transfer  No proposed changes.
                                      U.S.C. 32903(g)).         credits between their
                                                                fleets to increase a
                                                                fleet's average fuel
                                                                economy by up to 2 mpg.
                                                                Manufacturers may not use
                                                                transferred credits to
                                                                meet the minimum domestic
                                                                passenger car standards
                                                                (see 49 U.S.C.
                                                                32903(g)(4) and 49 CFR
                                                                536.9).

[[Page 56362]]

 
Credit Trading.....................  49 CFR 536.8 (49 U.S.C.   Manufacturers may trade an  No proposed changes.
                                      32903(f)).                unlimited quantity of
                                                                credits into fleets of
                                                                the same compliance
                                                                category. A manufacturer
                                                                may then transfer those
                                                                credits to a different
                                                                compliance category, but
                                                                only up to the 2 mpg
                                                                limit for transfers.
                                                                Manufacturers may not use
                                                                traded credits to meet
                                                                the minimum domestic
                                                                passenger car standards
                                                                (see 49 U.S.C.
                                                                32903(f)(2) and 49 CFR
                                                                536.9).
Civil Penalties....................  49 CFR 578.6(h) (49       Starting in 2023, the       No proposed changes.
                                      U.S.C. 3912.).            civil penalty for CAFE
                                                                shortfalls is $16 for
                                                                each tenth of a mpg that
                                                                a manufacturer's average
                                                                fuel economy falls short
                                                                of the standard
                                                                multiplied by the total
                                                                number of vehicles in the
                                                                affected fleet. The civil
                                                                penalty is adjusted
                                                                periodically for
                                                                inflation.
----------------------------------------------------------------------------------------------------------------

a. Determining Compliance
    This first component of NHTSA's enforcement program pertains to how 
NHTSA determines compliance with its fuel economy standards. In 
general, as prescribed by Congress, NHTSA finalizes footprint-based 
fleet average standards for LDVs for fuel economy on a mpg basis. In 
that way, the standard applies to the fleet as a whole and not to a 
specific vehicle, and manufacturers can balance the performance of 
their vehicles and technologies in complying with standards. Also, as 
specified by Congress, LDVs must be is broken down into 3 fleets for 
compliance purposes: domestic passenger vehicles, import passenger 
vehicles, and light trucks. Each manufacturer must comply with the 
fleet average standard derived from the model type target standards. 
These target standards are taken from a set of curves (mathematical 
functions) for each fleet. Vehicle testing for the LDV programs is 
conducted by EPA using the FTP (or ``city'' test) and HFET (or 
``highway'' test).\608\
---------------------------------------------------------------------------

    \608\ 40 CFR part 600.
---------------------------------------------------------------------------

    At the end of each MY NHTSA confirms whether a manufacturer's fleet 
average performance for each of its fleets of LDVs exceeds the 
applicable target-based fleet standard. NHTSA makes its ultimate 
determination of a manufacturer's CAFE compliance obligation based on 
official reported and verified CAFE data received from EPA. Pursuant to 
49 U.S.C. 32904(e), EPA is responsible for calculating manufacturers' 
CAFE values so that NHTSA can determine compliance with its CAFE 
standards. The EPA-verified data is based on information from NHTSA's 
testing,\609\ its own vehicle testing, and FMY data submitted by 
manufacturers to EPA pursuant to 40 CFR 600.512-12. A manufacturer's 
FMY report must be submitted to EPA no later than 90 days after 
December 31st of the MY including any adjustment for off-cycle credits 
for the addition of technologies that result in real-world fuel 
improvements that are not accounted for in the 2-cycle testing as 
specified in 40 CFR part 600 and 40 CFR part 86. EPA verifies the data 
submitted by manufacturers and issues final CAFE reports that are sent 
to manufacturers and to NHTSA electronically between April and October 
of each year. NHTSA's database system identifies which fleets do not 
meet the applicable CAFE fleet standards and calculates each 
manufacturer's credit amounts (credits for vehicles exceeding the 
standards), credit excesses (credits accrued for a fleet exceeding the 
standards), and shortfalls (amount by which a fleet fails to meet the 
standards). A manufacturer meets NHTSA's fuel economy standard if its 
fleet average performance is greater than or equal to its required 
standard or its MDPCS (whichever is greater). Congress enacted MDPCSs 
per 49 U.S.C. 32902. These standards require that domestic passenger 
car fleets meet a minimum level directed by statute and then projected 
by the Secretary at the time a standard is promulgated in a rulemaking. 
In addition, manufacturers are not allowed to use traded or transferred 
credits to resolve credit shortfalls resulting from failing to exceed 
the MDPCS.
---------------------------------------------------------------------------

    \609\ NHTSA conducts vehicle testing under its ``Footprint'' 
attribute conformity testing to verify track width and wheelbase 
measurements used by manufactures to derive model type target 
standards. If NHTSA finds a discrepancy in its testing, 
manufacturers will need to make changes in their final reports to 
EPA.
---------------------------------------------------------------------------

    If a manufacturer's fleet fails to meet a fuel economy standard, 
NHTSA will provide written notification to the manufacturer that it has 
not met the standard. The manufacturer will be required to confirm the 
shortfall and must either submit a plan indicating how to allocate 
existing credits, or if it does not have sufficient credits available 
in that fleet, how it will address the shortfall either by earning, 
transferring and/or acquiring credits or by paying the appropriate 
civil penalty. The manufacturer must submit a plan or payment within 60 
days of receiving agency notification. Credit allocation plans received 
from the manufacturer will be reviewed and approved by NHTSA. NHTSA 
will approve a credit allocation plan unless it finds the proposed 
credits are unavailable or that it is unlikely that the plan will 
result in the manufacturer earning sufficient credits to offset the 
shortfall. If a plan is approved, NHTSA will revise the manufacturer's 
credit account accordingly. If a plan is rejected, NHTSA will notify 
the manufacturer and request a revised plan or payment of the 
appropriate fine.
b. Flexibilities
    As mentioned above, there are flexibilities manufacturers can use 
in the CAFE program for compliance purposes. Two general types of 
flexibilities that exist for the CAFE program include (1) FCIVs that 
can be used to increase CAFE values; and (2) credit flexibilities. To 
provide context for the changes NHTSA is proposing, a discussion of two 
types of FCIVs is provided below. These credits are for

[[Page 56363]]

the addition of technologies that improve air/conditioning efficiency 
(AC FCIVs) and other ``off-cycle'' technologies that reduce fuel 
consumption that are not accounted for in the 2-cycle testing (OC 
FCIVs).\610\ NHTSA is not proposing any changes to credit 
flexibilities. A discussion of these flexibilities can be found in 
previous rulemakings.\611\
---------------------------------------------------------------------------

    \610\ Manufacturers may also earn FCIVs for full size pickup 
trucks which have hybrid or electric drivetrains or have advanced 
technologies as specified in 40 CFR 86.1870-12. NHTSA is not 
providing an overview of these credits because NHTSA is not 
proposing any changes for these credits. For an an explanation of 
these credits see the May 2, 2022 final rule (87 FR 25710, page 
26025).
    \611\ October 15, 2012 (77 FR 63125, starting at page 62649) and 
May 2, 2022 (87 FR 25710, starting at page 26025).
---------------------------------------------------------------------------

    As mentioned above, the LD program provides fuel consumption 
improvement values (FCIVs) for improving the efficiency of AC 
systems.\612\ Improving the efficiency of these systems is important 
because AC usage places a load on the Internal Combustion (IC) that 
results in additional fuel consumption, and AC systems are virtually 
standard automotive accessories, with more than 95 percent of new cars 
andlight trucks sold in the U.S. equipped with mobile AC systems. 
Together, this means that AC efficiency can have a signifant impact on 
total fuel consumption. The AC FCIV program is designed to incentivize 
the adoption of more efficient systems, thereby reducing energy 
consumption across the fleet.
---------------------------------------------------------------------------

    \612\ 40 CFR 1868-12.
---------------------------------------------------------------------------

    Manufacturers can improve the efficiency of AC systems through 
redesigned and refined AC system components and controls. These 
improvements, however, are not measurable or recognized using 2-cycle 
test procedures because the AC is turned off during the CAFE compliance 
2-cycle testing. Any AC system efficiency improvements that reduce load 
on the engine and improve fuel economy, therefore, cannot be accounted 
for in those tests.
    NHTSA adopted EPA's AC efficiency program in the 2017-2025 CAFE 
final rule.\613\ The program provides a technology menu that specifies 
improvement values for the addition of specific technologies and 
specifies testing requirements to confirm that the technologies provide 
emissions reductions when installed as a system on vehicles.\614\ A 
vehicle's total AC efficiency FCIV is calculated by summing the 
individual values for each efficiency improving technology used on the 
vehicle, as specified in the AC menu or by the AC17 test result.\615\ 
The total AC efficiency FCIV sum for each vehicle is capped at 5.0 
grams/mile for cars and 7.2 grams/mile for trucks.\616\ Related to AC 
efficiency improvements, the off-cycle program, discussed in the next 
section, contains fuel consumption improvement opportunities for 
technologies that reduce the thermal loads on a vehicle from 
environmental conditions (solar loads or parked interior air 
temperature), that ultimately reduces the total energy required for AC 
operation. These technologies are listed on a thermal control menu that 
provides a predefined improvement value for each technology.\617\ If a 
vehicle has more than one thermal load improvement technology, the 
improvement values are added together, but subject to a cap of 3.0 
grams/mile for cars and 4.3 grams/mile for trucks.\618\ Manufacturers 
seeking FCIVs beyond the regulated caps may request the added benefit 
for AC technology under the off-cycle program.
---------------------------------------------------------------------------

    \613\ October 15, 2012 final rule (77 FR 62624).
    \614\ See 40 CFR 86.1868-12(e) through (g).
    \615\ See 40 CFR 1868-12(g)(2)(iii).
    \616\ See 40 CFR 1868-12(b)(2).
    \617\ See 40 CFR 86.1869-12(b)(1)(viii)(A) through (E).
    \618\ See 40 CFR 86.1869-12(b)(1)(viii).
---------------------------------------------------------------------------

    In additon to allowing improvements for AC efficiency technologies, 
the CAFE program also provides FCIVs for off-cycle technologies. ``Off-
cycle'' technologies are those that reduce vehicle fuel consumption in 
the real world, but for which the fuel consumption reduction benefits 
cannot be fully measured under the 2-cycle test procedures used to 
determine compliance with the fleet average standards. The FTP and HFET 
cycles are effective in measuring improvements in most fuel efficiency 
improving technologies; however, they are unable to measure or do not 
adequately represent certain fuel economy improving technologies 
because of limitations in the test cycles. For example, off-cycle 
technologies that improve emissions and fuel efficiency at idle (such 
as ``stop start'' systems) and those technologies that improve fuel 
economy to the greatest extent at highway speeds (such as active grille 
shutters that improve aerodynamics) are not fully accounted for in the 
2-cycle tests.
    In the 2017-2025 CAFE rulemaking, EPA, in coordination with NHTSA, 
established regulations extending benefits for off-cycle technologies 
and created FCIVs for the CAFE program starting with MY 2017.\619\ 
Under its EPCA authority for CAFE, EPA determined that the summation of 
the all the FCIVs values (for AC, OC, and advanced technology full size 
pickup trucks) in grams per mile could be converted to equivalent 
gallons per mile totals for improving CAFE values. More specifically, 
EPA normalizes the FCIVs values based on the manufacturer's total fleet 
production and then applies the values in an equation that can increase 
the manufacturer's CAFE values for each fleet instead of treating them 
as separate credits as they are in the GHG program.\620\
---------------------------------------------------------------------------

    \619\ Off-cycle credits were extened to LDVs under the CAFE 
program in the October 15, 2012 final rule (77 FR 62624).
    \620\ FCIVAC and FCIVOC are each deducted 
as separately calculated credit values from the fleet fuel economy 
per 40 CFR 600.510 12(c)(1)(ii) and 40 CFR 600.510 12(c)(3)(i) 
through (ii). AC efficiency credit falls under FCIVAC, 
while thermal load improvement technology credit falls under 
FCIVOC.
---------------------------------------------------------------------------

    For determining FCIV benefits, EPA and NHTSA created three 
compliance pathways for the off-cycle program: (1) menu technologies, 
(2) 2 to 5-Cycle Testing, and (3) an alternative approval methodology. 
Manufacturers may generate off-cycle credits or improvements through 
the EPA and NHTSA approved menu pathway without agency approval. 
Manufacturers report the inclusion of pre-defined technologies for 
vehicle configurations that utilize the technologies, from the pre-
determined values listed in 40 CFR 1869-12(b), in their PMY and MMY 
reports to NHTSA and then in their final reports to EPA.
    For off-cycle technologies both on and off the pre-defined 
technology list, EPA allows manufacturers to use 5-cycle testing to 
demonstrate off-cycle improvements.\621\ Starting in MY 2008, EPA 
developed the ``five-cycle'' test methodology to measure fuel economy 
for the purpose of improving new car window stickers (labels) and 
giving consumers better information about the fuel economy they could 
expect under real-world driving conditions. The ``five-cycle'' 
methodology was also able to capture real-world fuel consumption 
improvements that weren't fully reflected on the ``two-cycle'' test and 
EPA established this methodology as a pathway for a manufacturer to 
obtain FCIVs. The additional testing allows emission benefits to be 
demonstrated over some elements of real-world driving not captured by 
the two-cycle testing, including high speeds, rapid accelerations, hot 
temperatures, and cold temperatures. Under this pathway, manufacturers 
submit test data to EPA,

[[Page 56364]]

and EPA determines whether there is sufficient technical basis to 
approve the value of the off-cycle credit or fuel consumption 
improvement.
---------------------------------------------------------------------------

    \621\ See 40 CFR 86.1869-12(c).
---------------------------------------------------------------------------

    The final pathway allowed for manufacturers to earn OC FCIVs is an 
alternative pathway that requires a manufacturer to seek EPA review and 
approval.\622\ This path allows a manufacturer to submit an application 
to EPA to request approval of off-cycle benefits using an alternative 
methodology. The application must describe the off-cycle technology and 
how it functions to reduce CO2 emissions under conditions 
not represented in the 2-cycle testing, as well as provide a complete 
description of the methodology used to estimate the off-cycle benefit 
of the technology and all supporting data, including vehicle testing 
and in-use activity data. A manufacturer may request that EPA, in 
coordination with NHTSA, informally review their methodology prior to 
undertaking testing and/or data gathering efforts in support of their 
application. Once a manufacturer submits an application, EPA publishes 
a notice of availability in the Federal Register notifying the public 
of a manufacturer's proposed alternative off-cycle benefit calculation 
methodology.\623\ EPA makes a decision whether to approve the 
methodology after consulting with NHTSA and considering the public 
comments.
---------------------------------------------------------------------------

    \622\ 40 CFR 86.1869-12(d).
    \623\ EPA may waive the notice and comment requirements for 
technologies for which EPA has previously approved a methodology for 
determining credits. See 40 CFR 86.1869-12(d)(2)(ii).
---------------------------------------------------------------------------

c. Civil Penalties
    If a manufacturer does not comply with a CAFE standard and cannot 
or chooses not to cover the shortfall with credits, EPCA provides for 
the assessment of civil penalties. The Act specifies a precise formula 
for determining the amount of civil penalties for such noncompliance. 
Starting in MY 2023, the penalty, as adjusted for inflation by law, is 
$16 for each tenth of a mpg that a manufacturer's average fuel economy 
falls short of the standard multiplied by the total volume of those 
vehicles in the affected fleet (i.e., import passenger vehicles, 
domestic passenger vehicles, or light trucks), manufactured for that 
MY.\624\ On November 2, 2015, the Federal Civil Penalties Inflation 
Adjustment Act Improvements Act (Inflation Adjustment Act or 2015 Act), 
Pub. L. 114-74, Section 701, was signed into law. The 2015 Act required 
Federal agencies to promulgate an interim final rule to make an initial 
``catch-up'' adjustment to the civil monetary penalties they 
administer, and then to make subsequent annual adjustments. The amount 
of the penalty may not be reduced except under the unusual or extreme 
circumstances specified in the statute,\625\ which have never been 
exercised by NHTSA in the history of the CAFE program.
---------------------------------------------------------------------------

    \624\ See 49 U.S.C. 32912(b) and 49 CFR 578.6(h)(2). For MYs 
before 2019, the penalty is $5.50; for MYs 2019 through 2021, the 
civil penalty is $14; for MY 2022, the civil penalty is $15.
    \625\ See 49 U.S.C. 32913.
---------------------------------------------------------------------------

    NHTSA may also assess general civil penalties as prescribed by 
Congress under 49 U.S.C. 32912(a). A person that violates section 
32911(a) of title 49 is liable to the United States Government for a 
civil penalty of not more than $49,534 for each violation. A separate 
violation occurs for each day the violation continues. These penalties 
apply in cases in which NHTSA finds a violation outside of not meeting 
CAFE standards, such as those that may occur due to violating 
information request or reporting requirements as specified by Congress 
or codified in NHTSA's regulations.
2. Heavy-Duty Pickup Trucks and Vans
    As with the CAFE enforcement program, there are three primary 
components to NHTSA's compliance program for HD vehicles: (1) 
determining compliance; (2) using flexibilities and incentives; and (3) 
paying civil penalties for shortfalls. The following table provides an 
overview of the Heavy-Duty Fuel Efficiency Program for HDPUVs.

[[Page 56365]]



 Table V-25--Overview of Compliance for Heavy-Duty Fuel Efficiency Program for Pickup and Vans (Vehicles With a
                                       GVWR Between 8,500 and 14,000 lbs.)
----------------------------------------------------------------------------------------------------------------
                                         Fleet performance requirements
-----------------------------------------------------------------------------------------------------------------
                                      Applicable regulation                                    Proposed changes
            Component                 (statutory authority)          General description           in NPRM?
----------------------------------------------------------------------------------------------------------------
Fuel Efficiency Standards.......  49 CFR 535.5 (49 U.S.C.       Standards are attribute-      Yes: Proposed
                                   32902(k)).                    based fleet average           amendments to 49
                                                                 standards expressed in        CFR 535.5(a) to
                                                                 gallons per 100 miles. The    set standards for
                                                                 standards are based on the    MY2030 and onward
                                                                 capability of each model to   (with increases
                                                                 perform work. A model's       in the proposed
                                                                 work-factor is a measure of   standards between
                                                                 its towing and payload        MY 2030 and
                                                                 capacities and whether        2035).
                                                                 equipped with a 4-wheel
                                                                 drive configuration. In
                                                                 setting standards for the
                                                                 Heavy-Duty National
                                                                 Program, NHTSA seeks to
                                                                 implement standards
                                                                 designed to achieve the
                                                                 maximum feasible
                                                                 improvement in fuel
                                                                 efficiency, adopting and
                                                                 implementing test
                                                                 procedures, measurement
                                                                 metrics, fuel economy
                                                                 standards, and compliance
                                                                 and enforcement protocols
                                                                 that are appropriate, cost
                                                                 effective, and
                                                                 technologically feasible.
----------------------------------------------------------------------------------------------------------------
                      Determining Average Fleet Performance and Certification Flexibilities
----------------------------------------------------------------------------------------------------------------
2-Cycle Testing.................  49 CFR 535.6(a) citing 40     Vehicle testing is conducted  No proposed
                                   CFR 86.1819-14.               by EPA using the Federal      changes.
                                                                 Test Procedure and Highway
                                                                 Fuel Economy Test (HFET or
                                                                 ``highway'' test).
Exclusion of Vehicles Not         49 CFR 535.5(a)(5)..........  The standards for heavy duty  No proposed
 Certified as Complete Vehicles.                                 pickup trucks do not apply    changes.
                                                                 to vehicles that are
                                                                 chassis-certified with
                                                                 respect to EPA's criteria
                                                                 pollutant test procedure in
                                                                 40 CFR part 86, subpart S.
                                                                 Instead, the vehicles must
                                                                 comply with the vehicle
                                                                 standards in 49 CFR
                                                                 535.5(b) and the engines
                                                                 used in these vehicles must
                                                                 comply with 49 CFR
                                                                 535.5(d).
Sister Vehicles.................  49 CFR 535.5(a)(6)..........  Manufacturers may certify     No proposed
                                                                 cab-complete vehicles based   changes.
                                                                 on a complete sister
                                                                 vehicle for purposes of the
                                                                 fuel consumption standards
                                                                 in 49 CFR 535.5.
                                                                 Manufacturers may also ask
                                                                 to apply the sister vehicle
                                                                 provision to Class 2b and
                                                                 Class 3 incomplete vehicles
                                                                 in unusual circumstances.

[[Page 56366]]

 
Loose Engines...................  49 CFR 535.5(a)(7)..........  For MY 2023 and earlier,      No proposed
                                                                 manufacturers may certify     changes. The
                                                                 spark-ignition engines with   loose engine
                                                                 identical hardware compared   program ends
                                                                 with engines used in          after MY 2023.
                                                                 complete pickup trucks as
                                                                 having a fuel consumption
                                                                 target value and test
                                                                 result equal to that of the
                                                                 complete vehicle in the
                                                                 applicable test group with
                                                                 the highest equivalent test
                                                                 weight except that a
                                                                 manufacturer may not
                                                                 generate fuel consumption
                                                                 credits.
Optional Certification for        49 CFR 535.5(a)(6)(i).......  Manufacturers may certify     No proposed
 Heavier Vehicles.                                               any complete or cab-          changes.
                                                                 complete spark-ignition
                                                                 vehicles above 14,000
                                                                 pounds GVWR and at or below
                                                                 26,000 pounds GVWR to the
                                                                 fuel consumption standards
                                                                 for heavy duty pickup
                                                                 trucks and vans in 49 CFR
                                                                 535.5(a).
Alternative Fuel Conversions....  49 CFR 535.5(a)(8) citing 40  Alternative fuel vehicle      No proposed
                                   CFR 85.525.                   conversions may demonstrate   changes.
                                                                 compliance with the
                                                                 standards of this part or
                                                                 other alternative
                                                                 compliance approaches
                                                                 allowed by EPA in 40 CFR
                                                                 85.525.
----------------------------------------------------------------------------------------------------------------
                     Earning and Using Credits for Overcompliance and Addressing Shortfalls
----------------------------------------------------------------------------------------------------------------
Earning Credits.................  49 CFR 535.7(a).............  Manufacturers earn fuel       No proposed
                                                                 consumption credits (FCCs)    changes.
                                                                 for the weighted value
                                                                 representing the extent to
                                                                 which a vehicle or engine
                                                                 family or fleet within a
                                                                 particular averaging set
                                                                 performs better than the
                                                                 standard.
Advanced technology credits.....  49 CFR 535.7(a)(1)(iii); 49   Manufacturer may generate     No proposed
                                   CFR 535.7(f)(1) citing 40     credits for vehicle or        changes.
                                   CFR 86.1819-14 and 86.1865.   engine families or
                                                                 subconfigurations
                                                                 containing vehicles with
                                                                 advanced technologies
                                                                 (i.e., hybrids with
                                                                 regenerative braking,
                                                                 vehicles equipped with
                                                                 Rankine-cycle engines,
                                                                 electric and fuel cell
                                                                 vehicles).

[[Page 56367]]

 
Advanced technology credit        49 CFR 535.5(a)(9) and        In the 2016 Phase 2 Final     Yes: Proposed
 multiplier.                       535.7(f)(1).                  Rule, EPA and NHTSA           technical
                                                                 explained that                amendments to
                                                                 manufacturers may increase    accurately
                                                                 advanced technology credits   reflect changes
                                                                 by a 3.5 multiplier for       contemplated by
                                                                 plug-in hybrid electric       2016 final rule
                                                                 vehicles, 4.5 for all-        establishing
                                                                 electric vehicles, and 5.5    requirements for
                                                                 for fuel cell vehicles        Phase 2. The
                                                                 through My 2027.              multiplier for
                                                                                               advanced
                                                                                               technology
                                                                                               credits ends
                                                                                               after MY 2027.
Innovative and off-cycle          49 CFR 535.7(a)(1)(iv); 49    Manufacturer may generate     Yes: Proposed
 technology credits.               CFR 535.7(f)(2) citing 49     credits for vehicle or        changes to
                                   CFR 86.1819-14(d)(13),        engine families or            eliminate
                                   1036.610 and 1037.610.        subconfigurations having      innovative and
                                                                 fuel consumption reductions   off-cycle
                                                                 resulting from technologies   technology
                                                                 not reflected in the GEM      credits for heavy-
                                                                 simulation tool or in the     duty pickup
                                                                 FTP chassis dynamometer.      trucks and vans.
Banked Surplus Credits..........  49 CFR 535.7 (a)(3)(i)......  Manufacturers may carry-      No proposed
                                                                 forward credits up to 5       changes.
                                                                 model years into the
                                                                 future.
Credit Deficit..................  49 CFR 535.7(a)(5)..........  Manufacturers may carry-back  No proposed
                                                                 credits up to 3 model years   changes.
                                                                 into the past.
Credit Transfers................  49 CFR 535.7................  Manufacturers may transfer    Yes: Proposed
                                                                 advanced technology credits   technical
                                                                 across averaging sets.        amendment to
                                                                                               reflect, as
                                                                                               intended in the
                                                                                               2016 Phase 2 rule
                                                                                               that advanced
                                                                                               technology
                                                                                               credits may not
                                                                                               be transferred
                                                                                               across averaging
                                                                                               sets for Phase 2
                                                                                               and beyond.\626\
Credit Trading..................  49 CFR 535.7 (a)(4).........  Manufacturers may trade an    No proposed
                                                                 unlimited quantity of         changes.
                                                                 credits to other
                                                                 manufacturers in the same
                                                                 averaging set. Traded
                                                                 credits, other than
                                                                 advanced technology
                                                                 credits, may be used only
                                                                 within the averaging set in
                                                                 which they were generated.
Civil Penalties.................  49 CFR 535.9(b) and 49 CFR    In cases of noncompliance,    No proposed
                                   578.6(i) (49 U.S.C. 32912.).  NHTSA assesses civil          changes.
                                                                 penalties based upon
                                                                 consideration of a variety
                                                                 of factors. The maximum
                                                                 civil penalty for a
                                                                 violation of is not more
                                                                 than $48,779 per vehicle or
                                                                 engine. The maximum civil
                                                                 penalty for a related
                                                                 series of violations shall
                                                                 be determined by
                                                                 multiplying $48,779 times
                                                                 the vehicle or engine
                                                                 production volume for the
                                                                 model year in question
                                                                 within the regulatory
                                                                 averaging set.
----------------------------------------------------------------------------------------------------------------
\626\ Docket ID NHTSA-2020-0079-0001.


[[Page 56368]]

a. Determining Compliance
    In general, NHTSA finalizes attribute-based fleet average standards 
for fuel consumption of HDPUVs on a gal/100-mile basis using a similar 
compliance strategy as required for light-vehicles in the CAFE program. 
For these vehicles, the agencies set standards based on attribute 
factors relative to the capability of each model to perform work, which 
the agencies defined as ``work factor.'' More specifically, the work-
factor of each model is a measure of its towing and payload capacities 
and whether equipped with a 4-wheel drive configuration. Each 
manufacturer must comply with the fleet average standard derived from 
the unique subconfiguration target standards (or groups of 
subconfigurations approved by EPA in accordance with 40 CFR 86.1819-
14(a)(4)) of the model types that make up the manufacturer's fleet in a 
given MY. Each subconfiguration has a unique attribute-based target 
standard, defined by each group of vehicles having the same work 
factor. These target standards are taken from a set of curves 
(mathematical functions), with separate performance curves for gasoline 
and diesel vehicles.\627\ In general, in calculating HDPUVs, fleets 
with a mixture of vehicles with increased payloads or greater towing 
capacity (or utilizing four-wheel drive configurations) will face 
numerically less stringent standards than fleets consisting of less 
powerful vehicles. Vehicle testing for both the HD and LDV programs is 
conducted on chassis dynamometers using the drive cycles from FTP and 
HFET.\628\ While the FTP and the HFET driving patterns are identical to 
that of the LD test cycles, other test parameters for running them, 
such as test vehicle loaded weight, are specific to complete HD 
vehicles.
---------------------------------------------------------------------------

    \627\ However, both gasoline and diesel vehicles in this 
category are included in a single averaging set for generating and 
using credit flexibilities.
    \628\ The LD FTP is a vehicle driving cycle that was originally 
developed for certifying LDVs and subsequently applied to HD chassis 
testing for criteria pollutants. This contrasts with the Heavy-duty 
FTP, which refers to the transient engine test cycles used for 
certifying heavy-duty engines (with separate cycles specified for 
diesel and spark-ignition engines).
---------------------------------------------------------------------------

    Due to the variations in designs and construction processes, 
optional requirements were added to simplify testing and compliance 
burdens for cab-chassis Class 2b and 3 vehicles. Requirements were 
added to treat cab-chassis Class 2b and 3 vehicles (vehicles sold as 
incomplete vehicles with the cab substantially in place but without the 
primary load-carrying enclosure) equivalent to the complete van or 
truck product from which they are derived. Manufacturers determine 
which complete vehicle configurations most closely matches the cab-
chassis product leaving its facility and include each of these cab-
chassis vehicles in the fleet averaging calculations, as though it were 
identical to the corresponding complete ``sister'' vehicle. The Phase 1 
MDHD program also added a flexibility known as the ``loose engine'' 
provision. Under the provision, spark-ignition (SI) engines produced by 
manufacturers of HDPUVs and sold to chassis manufacturers and intended 
for use in vocational vehicles need not meet the separate SI engine 
standard, and instead may be averaged with the manufacturer's HDPUVs 
fleet.\629\ This provision was adopted primarily to address small 
volume sales of engines used in complete vehicles that are also sold to 
other manufacturers.
---------------------------------------------------------------------------

    \629\ See 40 CFR 86.1819-14(k)(8).
---------------------------------------------------------------------------

    And finally, at the end of each MY NHTSA confirms whether a 
manufacturer's fleet average performance for its fleet of HDPUVs 
exceeds the applicable target-based fleet standard using the model type 
work factors. Compliance with the fleet average standards is determined 
using 2-cycle test procedures. However, manufacturers may also earn 
credits for the addition of technologies that result in real-world fuel 
improvements that are not accounted for in the 2-cycle testing. If the 
fleet average performance exceeds the standard, the manufacturer 
complies for the MY. If the manufacturer's fleet does not meet the 
standard, the manufacturer may address the shortfall by using a credit 
flexibility equal to the credit shortage in the averaging set. The 
averaging set balance is equal to the balance of earned credits in the 
account plus any credits that are traded into or out of the averaging 
set during the MY. If a manufacturer cannot meet the standard using 
credit flexibilities, NHTSA may assess a civil penalty for any 
violation of this part under 49 CFR 535.9(b).
b. Flexibilities
    Broadly speaking, there are two types of flexibilities available to 
manufacturers for HDPUVs. Manufacturers may improve fleet averages by 
(1) earning fuel consumption incentive benefits and by (2) transferring 
or trading in credits that were earned through overcompliance with the 
standards. First, as mentioned above, manufacturers may earn credits 
associated with fuel efficiencies that are not accounted for in the 2-
cycle testing.\630\ Second, manufacturers may transfer credits into 
like fleets (i.e., averaging sets) from other manufacturers through 
trades.\631\
---------------------------------------------------------------------------

    \630\ Off-cycle benefits were extened to heavy-duty pickup 
trucks and vans through the-MDHD--Phase 1 program in the September 
15, 2011 final rule (76 FR 57106).
    \631\ See 49 CFR 535.7(a)(2)(iii) and 49 CFR 535.7(a)(4).
---------------------------------------------------------------------------

    Unlike the LDV program, there is no AC credit program for HDPUVs. 
Currently, these vehicles may only earn fuel consumption improvement 
credits through an off-cycle program, which may include earning credits 
for AC efficiency improvements. In order to receive these credits, 
manufacturers must submit a request to EPA and NHTSA with data 
supporting that the technology will result in measurable, demonstrable, 
and verifiable real-world CO2 emission reductions and fuel 
savings. After providing an opportunity for the public to comment on 
the manufacturer's methodology, the agencies make a decision whether to 
approve the methodolgy and credits.\632\
---------------------------------------------------------------------------

    \632\ See 49 CFR 535.7(f)(2), 40 CFR 86.1819-14(d)(13), and 40 
CFR 86.1869-12(c) through (e).
---------------------------------------------------------------------------

    In addition to earning additional OC FCIVs, manufacturers have the 
flexibility to transfer credits into their fleet to meet the standards. 
Manufacturers may transfer in credits from past (carry-forward credits) 
MYs of the same averaging set. \633\ Manufacturers may also trade in 
credits earned by another manufacturer, as long as the credits are 
traded into the same averaging set/fleet type. Manufacturers may not 
transfer credits between LD CAFE fleets and HD fleets. Likewise, a 
manufacturer cannot trade in credits from another manufacturer's LD 
fleet to cover shortfalls in their HD fleets. NHTSA oversees these 
credit transfer and trades through regulations issued in 49 CFR 535.7, 
which includes reporting requirements for credit trades and transfers 
for medium- and HD vehicles.
---------------------------------------------------------------------------

    \633\ See 49 CFR 535.7(a)(3)(i), 49 CFR 535.7(a)(3)(iv), 49 CFR 
535.7(a)(2)(v), and 49 CFR 535.7(a)(5).
---------------------------------------------------------------------------

c. Civil Penalties
    The framework established by Congress and codified by NHTSA for 
civil penalties for the HD program is quite different from the LD 
program. Congress did not prescribe a specific rate for the fine amount 
for civil penalties but instead gave NHTSA general authority under 
EISA, as codified at 49 U.S.C. 32902(k), to establish requirements 
based upon appropriate measurement metrics, test procedures, standards, 
and compliance and enforcement protocols for HD vehicles. NHTSA 
interpreted its

[[Page 56369]]

authority and developed an enforcement program to include the authority 
to determine and assess civil penalties for noncompliance that would 
impose penalties based on the following criteria, as codified in 49 CFR 
535.9(b).
    In cases of noncompliance, NHTSA assesses civil penalties based 
upon consideration of the following factors:
     Gravity of the violation.
     Size of the violator's business.
     Violator's history of compliance with applicable fuel 
consumption standards.
     Actual fuel consumption performance related to the 
applicable standard.
     Estimated cost to comply with the regulation and 
applicable standard.
     Quantity of vehicles or engines not complying.
     Civil penalties paid under CAA section 205 (42 U.S.C. 
7524) for noncompliance for the same vehicles or engines.
    NHTSA considers these factors in determining civil penalties to 
help ensure, given NHTSA's wide discretion, that penalties would be 
fair and appropriate, and not duplicative of penalties that could be 
imposed by EPA. NHTSA goal is to avoid imposing duplicative civil 
penalties, and both agencies consider civil penalties imposed by the 
other in the case of non-compliance with GHG and fuel consumption 
regulations. NHTSA also uses the ``estimated cost to comply with the 
regulation and applicable standard,'' \634\ to ensure that any 
penalties for non-compliance will not be less than the cost of 
compliance. It would be contrary to the purpose of the regulation for 
the penalty scheme to incentivize noncompliance. Further, NHTSA set its 
maximum civil penalty amount not to exceed the limit that EPA is 
authorized to impose under the CAA. The agencies agreed that violations 
under either program should not create greater punitive damage for one 
program over the other. Therefore, NHTSA's maximum civil penalty for a 
manufacturer would be calculated as the: Aggregate Maximum Civil 
Penalty for a Non-Compliant Regulatory Category = (CAA Limit) x 
(production volume within the regulatory category). This approach 
applies for all HD vehicles including pickup trucks and vans as well as 
engines regulated under NHTSA's fuel consumption programs.
---------------------------------------------------------------------------

    \634\ See 49 CFR 535.9(b)(4).
---------------------------------------------------------------------------

C. Proposed Changes

    The following sections describe four changes NHTSA is proposing in 
order to update its enforcement programs for LDVs and for HDPUVs. These 
changes reflect experience gained in the past few years and are 
intended to improve to the programs overall.
3. Elimination of OC and AC Efficiency FCIVs for BEVs in the CAFE 
Program
    NHTSA is proposing to remove AC and OC FCIVs for BEVs, which 
manufacturers can use to comply with CAFE standards, because the FCIVs 
represent energy savings for vehicles with ICEs. The CAFE program 
currently provides for credits for vehicles equipped with technologies 
that improve the efficiency of the vehicles' AC systems and otherwise 
reduce fuel consumption but are not accounted for in the 2-cycle 
testing.
    Beginning in MY 2027, NHTSA proposes to eliminate eligibility to 
gain FCIVs for any vehicles that do not have IC engines. Thus, BEVs 
would no longer be eligible for these credits after MY 2026. NHTSA 
believes that eliminating AC and OC FCIVs is appropriate because BEVs 
are currently generating credits in a program designed to provide 
credits based on reductions in emissions and fuel consumption of IC 
engine vehicles. In the OC program specifically, we note that the 
values associated with menu technologies were based on IC engine 
vehicles with exhaust emissions and fuel consumption. While there may 
be AC and other technologies that improve BEV energy consumption, the 
values associated with AC FCIVs and the OC menu FCIVs are based on IC 
engine vehicles and, therefore, are not appropriate to consider for 
BEVs. When EPA and NHTSA adopted these flexibilities in the MY 2012 
rule, there was little concern about this issue because BEV sales were 
only a small fraction of total sales, and no upstream net emissions 
were considered as part of the GHG and fuel economy final 
standards.635 636 Now, however, BEVs are earning FCIVs as 
part of the fleet compliance that aren't representative of real-world 
fuel consumption reduction. Therefore, NHTSA is proposing to end off-
cycle and AC efficiency FCIVs for LDVs with no IC engine beginning in 
MY 2027. NHTSA is seeking comments on this proposal.
---------------------------------------------------------------------------

    \635\ See 77 FR 62811 (October 15, 2012).
    \636\ 2022 EPA Automotive Trends Report at Table 4.1 on page 74.
---------------------------------------------------------------------------

    Relatedly, NHTSA is also seeking comment on three other possible 
changes for FCIVs. First, NHTSA is seeking comment on whether it 
should, instead of eliminating FCIVs for BEVs completely, propose new 
off-cycle and AC values for BEVs that are based on BEV powertrains 
rather than IC engines, and, if so, how those proposed values should be 
calculated. Additionally, in light of its proposal to eliminate FCIVs 
for BEVs, NHTSA is seeking comment on whether it should propose 
adjusting FCIVs for PHEVs based on utility factor for the portion only 
operated by IC engine. For CAFE compliance purposes, the fuel economy 
of dual-fueled vehicles, such as PHEVs, is calculated by EPA using a 
utility factor to account the portion of power energy consumption from 
the different energy sources. A utility factor of 0.3, for example, 
means that the vehicle is estimated to operate as an IC Engine vehicle 
70 percent of the vehicle's VMT. NHTSA is requesting comment on whether 
it should propose reducing FCIVs for PHEVs proportional to the 
estimated percentage of VMT that the vehicles would be operated as EVs.
    NHTSA is also requesting comment on whether it should propose 
phasing out OC FCIVs for all vehicles before MY 2031. For example, one 
such approach could be to phase-down the off-cycle menu cap by reducing 
it to10 g/mi in MY 2027, 8 g/mi in MY 2028, 6 g/mi in MY 2029, and 3 g/
mi in MY 2030 before eliminating OC FCIVs in MY 2031. As noted above, 
FCIVs were added to the CAFE program by the October 15, 2012 final rule 
and manufacturers were able to start earning OC FCIVs starting in MY 
2017.\637\ The value of FCIVs for OC technologies listed on the 
predefined list are derived from estimated emissions reductions 
associated with the technologies which is then converted into an 
equivalent improvement in MPG. These values, however, were established 
based on MY 2008 vehicles and technologies assessed during the 2012 
rulemaking and, therefore, the credit levels are potentially becoming 
less representative of the fuel savings provided by the off-cycle 
technologies as fuel economy is improved. There is not currently a 
mechanism to confirm that the off-cycle technologies provide fuel 
savings commensurate with the level of the credits the menu provides. 
Further, issues such as the synergistic effects and overlap among off-
cycle technologies take on more importance as the FCIVs represent a 
larger portion of the vehicle fuel economy. Over time NHTSA's standards 
for CAFE have increased while FCIVs for some menu technologies have 
remained the same, which may result in the FCIVs being less 
representative of MPG improvements provided by the off-cycle 
technologies. Therefore, NHTSA is requesting comment on whether it

[[Page 56370]]

should phase out FCIVs for off-cycle technologies for ICE vehicles. 
Alternatively, NHTSA is requesting comment on whether it should propose 
new values for off-cycle technologies that are more representative of 
the real-world fuel savings provided by these technologies, and if so, 
how NHTSA should calculate the appropriate values for these 
technologies.
---------------------------------------------------------------------------

    \637\ 77 FR 62624.
---------------------------------------------------------------------------

    To help NHTSA understand the potential impacts of some of these 
additional changes for FCIVs, we conducted sensitivity analyses on 
removing FCIVs for BEVs, and also for phasing out all FCIVs. These 
sensitivities are discussed in Chapter 9 of the accompanying PRIA. 
NHTSA is requesting comment on these analyses as well as whether there 
may be a more appropriate approach to modeling the impacts of these 
potential changes.
4. Elimination of the 5-Cycle and Alternative Approval Pathways for 
CAFE
    NHTSA is proposing to eliminate both the 5-cycle pathway and the 
alternative pathway for off-cycle FCIVs for LDVs starting in MY 2027. 
NHTSA is proposing this change because we do not believe that the 
benefit to manufacturers is significant enough to justify that the 
programs require a significant amount of time and resources to be 
committed to reviewing and approving requests. Further, based on the 
general degree of robustness of data provided by manufacturers to EPA 
and NHTSA for approval consideration, the analysis is often delayed 
and/or ultimately unproductive, causing undesirable and often 
unnecessary delays to final compliance processing.
    NHTSA does not believe that the 5-cycle pathway is beneficial to 
manufacturers or to NHTSA, as the pathway is used infrequently, 
provides minimal benefits, and requires a significant amount of time 
for review. Historically, only a few technologies have been approved 
for FCIVs through 5-cycle testing. The 5-cycle demonstrations are less 
frequent than the alternate pathway due to the complexity and cost of 
demonstrating real-world emissions reductions for technologies not 
listed on the menu. Therefore, NHTSA proposes to eliminate the 5-cycle 
pathway, starting in MY 2027 for earning off-cycle fuel economy 
improvements. NHTSA is seeking comments on this proposal.
    NHTSA is also proposing to eliminate the alternative approval 
process for off-cycle FCIVs starting in MY 2027. Manufacturers 
currently seek EPA review, in consultation with NHTSA, through a notice 
and comment process, to use an alternative methodology other than the 
menu or 5-cycle methodology. Manufacturers must provide supporting data 
on a case-by-case basis demonstrating the benefits of the off-cycle 
technology on their vehicle models. Manufacturers may also use the 
alternative approval pathway to apply for FCIVs for menu technologies 
where the manufacturer is able to demonstrate FCIVs greater than those 
provided by the menu.
    NHTSA is proposing to eliminate the alternative approval process 
for off-cycle credits starting in MY 2027. The alternative approval 
process was used successfully by several manufacturers for high 
efficiency alternators, resulting in EPA adding them to the off-cycle 
menu beginning in MY 2021.\638\ The program has resulted in a number of 
concepts for potential off-cycle technologies over the years, but few 
have been implemented, at least partly due to the difficulty in 
demonstrating the quantifiable real-world fuel consumption reductions 
associated with using the technology. Many FCIVs sought by 
manufacturers have been relatively small (less than 1 g/mile). 
Manufacturers have commented several times that the process takes too 
long, but the length of time is often associated with the need for 
additional data and information or issues regarding whether a 
technology is eligible for FCIVs. NHTSA has been significantly impacted 
in conducting its final compliance processes due to the untimeliness of 
OC approvals. Therefore, NHTSA proposes to eliminate the alternative 
approval process for earning off-cycle fuel economy improvements 
starting in MY 2027. NHTSA is seeking comments on this proposal.
---------------------------------------------------------------------------

    \638\ See 85 FR 25236 (April 30, 2020).
---------------------------------------------------------------------------

5. Elimination of OC FCIVs for Heavy-Duty Pickup Trucks and Vans 
Starting in MY 2030
    NHTSA is proposing to eliminate OC FCIVs for HDPUVs for the same 
reasons discussed above for proposing to eliminate the 5-cycle and 
alternative pathways for OC FCIVs starting in MY 2030. Currently, 
manufacturers of HDPUVs may only earn FCIVs through an off-cycle 
program that involves requesting public comment and case-by-case review 
and approval. Since its inception, the program has involved lengthy and 
resource-intensive processes that have not resulted in significant 
benefits to the HDPUV fleet. At this time, NHTSA does not believe the 
benefit provided by these credits justifies NHTSA's time and resources. 
Accordingly, NHTSA is proposing to end the off-cycle program for HDPUVs 
starting in MY 2030. NHTSA is requesting comment on this proposal.
    NHTSA is also requesting comment on eliminating OC FCIVs for BEVs 
if NHTSA does not eliminate OC FCIVs for all HDPUVs. In the current 
regulation, we are considering all BEVs and PHEVs to have no fuel usage 
in that they consume zero g/mile for compliance. Accordingly, these 
vehicles would go to negative compliance values if we allowed OC FCIVs 
to be applied.
6. Requirement To Respond to Requests for Information Regarding Off-
Cycle Requests Within 60 Days for LDVs for MYs 2025 and 2026
    For MY 2025 and MY 2026, NHTSA is proposing to create a time limit 
to respond to requests for information regarding request for OC 
petitions for LDVs. This proposal is intended to allow for the timelier 
processing of OC petitions. In the last rule, NHTSA added provisions 
clarifying and outlining the deadlines for manufacturers to submit off-
cycle requests.\639\ Since laying out those new requirements, NHTSA has 
identified another point in the OC request process that is delaying the 
timely processing of the requests. When considering OC petitions, NHTSA 
and EPA frequently need to request additional information from the 
manufacturer, and NHTSA observes that it has sometimes taken OEMs an 
extended amount of time to respond to these requests.
---------------------------------------------------------------------------

    \639\ See 49 CFR 531.6(b)(3)(i) and 49 CFR 533.6(c)(4)(i).
---------------------------------------------------------------------------

    NHTSA proposes to create a deadline of 60 days for responding to 
requests for additional information regarding OC petitions. If the 
manufacturer does not respond within the 60-day limit with the 
requested information, NHTSA may deny the petition for the petitioned 
MY. NHTSA may grant an extension for responding if the manufacturer 
responds within 60 days with a reasonable timeframe for when the 
requested information can be provided to the agencies. If an OEM does 
not respond to NHTSA/EPA's call for additional data regarding the 
request within a timely manner, the request will be denied. The request 
will no longer be considered for the MY in question, but the OEM may 
still request consideration of the credits for the following year. A 
manufacturer may request consideration for later MYs by responding to 
NHTSA/EPA's data request and expressing such interest.

[[Page 56371]]

7. Technical Amendments for Advanced Technology Credits
    NHTSA is proposing to make technical amendments to the current 
regulations pertaining to advanced technology credits. In the Phase 2 
rule for the Heavy-Duty National Program, NHTSA and EPA jointly 
explained that we were adopting advanced technology credit multipliers 
for three types of advanced technologies. As described in the final 
rule, there would be a 3.5 multiplier for advanced technology credits 
for plug-in hybrid vehicles, a 4.5 multiplier for advanced technology 
credits for all-electric vehicles, and a 5.5 multiplier for advanced 
technology credits for fuel cell vehicles. The agencies stated that 
their intention in adopting these multipliers was to create a 
meaningful incentive to manufacturers considering adopting these 
technologies in their vehicles. The agencies further noted that the 
adoption rates for these advanced technologies in heavy vehicles was 
essentially non-existent at the time the final rule was issued and 
seemed unlikely to grow significantly within the next decade without 
additional incentives. Because of their large size, the agencies 
decided to adopt them as an interim program that would continue through 
MY 2027. These changes, however, were not accurately reflected in the 
regulatory changes made by the final rule. NHTSA is now correcting the 
regulations to clarify that for Phase 2, advanced technology credits 
may be increased by the corresponding multiplier through MY 2027.
    Additionally, the final rule also explained that because of the 
adoption of the large multipliers, the agencies were discontinuing the 
allowance to use advanced technology credits across averaging sets. 
This change was also not accurately reflected in the regulatory 
changes. NHTSA is also proposing to make the technical correction to 
reflect the intended change.
    In the interim and until the proposed technical amendment is 
implemented, there is no multiplier for advanced technology credits for 
Phase 2. However, NHTSA will permit manufacturers to use the larger 
multipliers with the condition that if they choose to do so, they will 
not be permitted to transfer the increased advanced technology credits 
across averaging sets.
8. Additional Technical Amendments
    In addition to the proposed changes discussed above, NHTSA is also 
proposing to make minor technical amendments to 49 CFR parts 531, 533, 
535, and 537. These amendments are largely to update statutory 
citations and to update cross-references. Specifically, NHTSA is 
proposing to make the following technical amendments:

    a. Change references to section 502 of the Motor Vehicle 
Informaiton and Cost Savings Act to the appropriate codified 
provision (i.e., 49 U.S.C. 32901 or 32902) in 49 CFR 531.1, 531.4, 
533.1, 533.4, 535.4, 537.3, and 537.4.
    b. Amend Sec.  531.4 to include a definition for ``domestically 
manufactured passenger autobile'' which references 49 U.S.C. 
32904(b)(3) and 40 CFR 600.511-08.
    c. Amend Sec.  531.5 to correct a cross reference to the 
provision containing NHTSA's standards for low-volume motor vehicles 
(found in 49 CFR 531.5(e)) and to include references to the 
provision as appropriate.
    d. Amend Sec.  535.4 to correct a typographical error to change 
``Alterers'' to ``Alterer.''
    e. Amend Sec.  535.7(b)(2) to correct a cross-reference to the 
EPA provision's provision regarding fuel consumption values for 
advanced technologies.
    f. Amend Sec.  537.2 to correct a typographical error.
    g. Amend Sec.  537.3 to end the reporting requirements in 
(c)(7)(iii) end after MY 2027 to coincide with the sunset date for 
FCIVs for advanced full-size pickup trucks.

D. Decision Not To Propose Non-Fuel Saving Credits or Flexibilities

    In a comment to the August 16, 2022 EIS scoping notice for MY 2027 
and beyond CAFE standards,\640\ Hyundai requested that NHTSA consider 
``developing an optional program that provides additional credits or 
flexibilities to manufacturers who target higher fuel economy vehicle 
distribution in communities of color, tribal communities, and other 
historically underserved communities.'' \641\ Hyundai stated that 
``[t]he NEPA process, and specifically the EIS, is an appropriate and, 
indeed, critical opportunity for NHTSA to consider EJ and effects of 
its proposed action on EJ communities--i.e., communities of color, 
tribal communities, and other disadvantaged, underserved, or 
historically marginalized communities that often absorb negative 
environmental effects.''
---------------------------------------------------------------------------

    \640\ Notice of Intent To Prepare an Environmental Impact 
Statement for MYs 2027 and Beyond Corporate Average Fuel Economy 
Standards and MYs 2029 and Beyond Heavy-Duty Pickup Trucks and Vans 
Vehicle Fuel Efficiency Improvement Program Standards (87 FR 50386).
    \641\ Docket ID NHTSA-2022-0075-0011.
---------------------------------------------------------------------------

    Hyundai stated that ``in evaluating the range of alternatives for 
establishing new CAFE standards, Hyundai encourages NHTSA to consider 
alternatives that have lower impact on, and in fact benefit, EJ 
communities.'' Hyundai stated that more specifically, NHTSA should 
consider ``developing and evaluating an optional program that would 
allow a manufacturer to earn some type of value or flexibility--whether 
that includes an additional type of credit or a higher flexibility 
cap--for vehicles that benefit EJ communities.'' Hyundai said that 
NHTSA is well-suited to explore this concept, given NHTSA's precedent 
for such additional types of optional credits or flexibilities, ``such 
as AC credits and off-cycle credits as part of the CAFE program.'' 
Hyundai proposed that ``[t]he optional credits could be based on the 
placement of certain vehicle types in programs intended to provide 
verifiable benefits to EJ communities and could be equivalent to a 
corresponding EPA program that generates GHG credits. Similar to the 
off-cycle program, these credits could be converted/adjusted to apply 
to a manufacturer's fuel economy fleet performance.''
    Hyundai encouraged NHTSA to ``consider such alternatives that will 
allow manufacturers the option to earn additional credits for focusing 
on vehicle development and deployment programs that benefit EJ 
communities . . . Proposed additional ``EJ credits'' could apply to 
EVs, PHEV, HEVs, and better-performing combustion engines, such as 
super-ultra low emission vehicles (``SULEVs'') providing verifiable 
benefits to EJ communities.'' Hyundai stated that in addition to NHTSA 
evaluating alternatives that ``create an incentive for high-performing 
fuel economy and advanced technology vehicles that benefit EJ 
communities, such as the optional programs described above,'' NHTSA 
should ``analyze the impacts on these communities of programs that do 
not create such an incentive.'' Hyundai stated that they would provide 
more specific suggestions for implementation of such alternatives as 
part of the comment process for this proposal.
    Because creation of any such program would be a part of NHTSA's 
CAFE Compliance and Enforcement program, we respond to this comment 
here rather than in the Draft EIS.
    NHTSA has been examining EJ considerations of CAFE standards since 
the earliest CAFE EISs in the 2000s.\642\ Since that time, we have 
received feedback from States, non-government organizations, Native 
American Tribes, faith groups, and individuals on how

[[Page 56372]]

NHTSA can better consider EJ when setting CAFE standards. It is an 
important milestone that automakers now want to begin engaging in this 
conversation, as including communities with EJ concerns in their 
product planning can provide verifiable benefits to those communities, 
as Hyundai recognized.
---------------------------------------------------------------------------

    \642\ See Draft Environmental Impact Statement Corporate Average 
Fuel Economy Standards, Passenger Cars and Light Trucks, MYs 2012-
2016 (September 2009).
---------------------------------------------------------------------------

    While NHTSA shares Hyundai's desire for underserved and EJ 
communities to have greater access to higher fuel economy vehicles--and 
welcomes any further suggestions from Hyundai or other stakeholders 
about how NHTSA could, consistent with its statutory authority, work 
with the automotive industry to structure the CAFE program to better 
benefit communities with EJ concerns--NHTSA did not propose an EJ 
credit program as part of this document. The following section 
discusses the factors that NHTSA considered in response to Hyundai's 
comment. We believe framing these considerations will be instructive 
for any more specific suggestions for implementations of EJ credits 
from Hyundai or other stakeholders as part of the comment process for 
this proposal.
    In addition to NEPA and its implementing regulations,\643\ relevant 
E.O.s,\644\ and DOT Order 5610.2C, U.S. Department of Transportation 
Actions to Address Environmental Justice in Minority Populations and 
Low-Income Populations,\645\ NHTSA considers EJ as it sets vehicle fuel 
economy standards pursuant to EPCA/EISA. Without repeating extensively 
the purpose of EPCA, which is described above, ``Congress created 
mandatory vehicle fuel economy standards, intended to be technology 
forcing, with the recognition that ``market forces . . . may not be 
strong enough to bring about the necessary fuel conservation which a 
national energy policy demands.'' '' \646\ Congress provided one 
explicit statutory flexibility for vehicle manufacturers in EPCA: when 
a vehicle manufacturer's fleet achieves a higher CAFE value than its 
CAFE standard, the fleet earns overcompliance credits that can be 
carried backwards and forwards and traded between fleets, or to other 
manufacturers.\647\ However, Congress recognized that one credit is not 
necessarily equal to another,\648\ and ensured this flexibility would 
conserve energy by commanding NHTSA to administer the credit program in 
such a way that that total oil savings associated with the original 
overcompliance would be preserved.\649\
---------------------------------------------------------------------------

    \643\ 42 U.S.C. 4321 et seq; 40 CFR parts 1500 through 1508.
    \644\ E.O. 12898 on Federal Actions To Address Environmental 
Justice in Minority Populations and Low-Income Populations; E.O. 
14008 on Tackling the Climate Crisis at Home and Abroad; E.O. 13990 
on Protecting Public Health and the Environment and Restoring 
Science to Tackle the Climate Crises; E.O. 13985 on Advancing Racial 
Equity and Support for Underserved Communities Through the Federal 
Government.
    \645\ DOT Order 5610.2C, U.S. Department of Transportation 
Actions to Address Environmental Justice in Minority Populations and 
Low-Income Populations (May 16, 2021). DOT's Order defines 
``environmental justice'' as the fair treatment and meaningful 
involvement of all people, regardless of race, ethnicity, income, 
national origin, or educational level, with respect to the 
development, implementation and enforcement of environmental laws, 
regulations and policies. For the purpose of DOT's Environmental 
Justice Strategy, fair treatment means that no population, due to 
policy or economic disempowerment, is forced to bear a 
disproportionate burden of the negative human health and 
environmental impacts, including social and economic effects, 
resulting from transportation decisions, programs and policies made, 
implemented and enforced at the Federal, State, local or tribal 
level.
    \646\ Ctr. for Auto Safe'y v. Nat'l Highway Traffic Safety 
Admin., 793 F.2d 1322, 1339 (D.C. Cir. 1986) (citing S.REP. NO. 179, 
94th Cong., 1st Sess. 2 (1975), U.S. Code Cong. & Admin.News 1975, 
p. 1762).
    \647\ 49 U.S.C. 32903.
    \648\ For example, the fuel savings lost if the average fuel 
economy of a manufacturer falls one-tenth of a mpg below the level 
of a relatively low standard are greater than the fuel savings 
gained by raising the average fuel economy of a manufacturer one-
tenth of a mpg above the level of a relatively high CAFE standard. 
See also 73 FR 24462 (May 2, 2008), Table IX-I.--Comparison of Fuel 
Savings at Different Fuel Economy Baselines.
    \649\ 49 U.S.C. 32903(f).
---------------------------------------------------------------------------

    NHTSA has created some additional flexibilities by regulation 
consistent with its EPCA authority (not expressly included or 
prohibited by EPCA) to harmonize better with some of EPA's programmatic 
decisions under the CAA's more flexible regulatory structure. However, 
neither flexibilities for AC efficiency and off-cycle technology fuel 
consumption improvement values,\650\ nor the incentive for pickup truck 
performance and hybridization,\651\ seem to provide the precedent that 
Hyundai suggests. These flexibilities are intended to promote greater 
fuel economy by recognizing technologies that reduce gasoline 
consumption, and in particular in vehicle classes that previously 
struggled to adopt fuel saving technology while maintaining utility 
requirements. NHTSA has declined to provide credits for vehicle 
technologies that do not provide fuel savings connected to a specific 
technology's adoption.\652\ Hyundai's proposal for EJ credits would not 
promote greater fuel economy. Instead, the proposal would grant credit 
for technologies that are already present on vehicles.
---------------------------------------------------------------------------

    \650\ Vehicle manufacturers have the option to generate 
``credits'' for off-cycle technologies and improved AC systems under 
the EPA's CO2 program; however, under NHTSA's CAFE 
program, manufacturers receive a fuel consumption improvement value 
(FCIV) equal to the value of the technology benefit not captured on 
the 2-cycle test. The FCIV is not a ``credit'' in the NHTSA CAFE 
program--unlike, for example, the statutory overcompliance credits 
described above--but FCIVs directly increase the reported fuel 
economy of a manufacturer's fleet, which is used to determine 
compliance. FCIVs are only a ``credit'' to the extent that a 
manufacturer using these specific technologies on a vehicle 
increases their fleet fuel economy level above and beyond their CAFE 
standard. NHTSA provides for these FCIVs because there is a direct 
link between these technologies improving the fuel economy of a 
vehicle in real-world operation above and beyond the vehicle's rated 
fuel economy value on the two-cycle test.
    \651\ See 49 (copyright) 553.6(c). Like AC and off-cycle FCIVs, 
the performance and hybrid pickup truck incentive in NHTSA's program 
is an adjustment to the fuel economy value of a vehicle, per EPA's 
EPCA measurement and testing authority, and not a ``credit.'' EPA 
and NHTSA ensured that these credits would not dilute potential 
increases in fleet fuel economy or decreases in GHG emissions by 
only providing the credit if a manufacturer includes the technology 
on significant increasing quantities of its full-sized pickup 
trucks. For example, in MY 2021 a manufacturer could only receive 
the credit if at least 80% of its full-size pickup trucks met the 
incentive's requirements. Note also that to date, no manufacturer 
has claimed the hybrid and performance pickup truck credit.
    \652\ 77 FR 62732-3 (Oct. 15, 2012) (``The agencies believe that 
there is a very significant distinction between technologies 
providing direct and reliably quantifiable improvements to fuel 
economy and GHG emission reductions, and technologies which provide 
those improvements by indirect means, where the improvement is not 
reliably quantifiable, and may be speculative (or in many instances, 
non-existent), or may provide benefit to other vehicles on the road 
more than for themselves. As the agencies have reiterated, and many 
commenters have likewise maintained, credits should be available 
only for technologies providing real-world improvements, the 
improvements must be verifiable, and the process by which credits 
are granted and implemented must be transparent.'').
---------------------------------------------------------------------------

    This is not the first time that manufacturers have requested 
credits for technologies that are already present on a vehicle that 
contribute to the vehicle's increased fuel economy or decreased 
CO2 emissions values.\653\ In the 2012 rule for MYs 2017 and 
beyond, EPA and NHTSA declined to grant off-cycle credits and FCIVs for 
technologies that are integral or inherent to the basic vehicle design 
like the vehicle's engine or transmission. The agencies appropriately 
stated then that ``there are fundamental issues as to whether these 
technologies would ever warrant off-cycle credits. Being integral, 
there is no need to provide an incentive for their use, and (more 
important), these technologies would be incorporated regardless. 
Granting credits would be a windfall.'' \654\ The powertrain 
technologies that Hyundai proposes to be eligible for EJ credits 
include all of the same technologies that are integral to basic vehicle 
designs required by

[[Page 56373]]

more stringent standards under EPCA and the CAA.
---------------------------------------------------------------------------

    \653\ 77 FR 62732 (Oct. 15, 2012).
    \654\ Id.
---------------------------------------------------------------------------

    It is not at all clear that EPCA would allow such a program, but 
NHTSA also believes that any new incentive program for vehicle 
manufacturers would need to (1) provide verifiable benefits for EJ 
communities, and (2) support EPCA's overarching purpose of energy 
conservation. Accordingly, we have identified some initial substantive 
issues and questions that we believe would be helpful for Hyundai or 
any other stakeholder to address before moving forward submitting a 
proposal to NHTSA for EJ or other similar credits.
    CAFE standards have the potential to benefit communities with 
environmental justice concerns. Hyundai appears to imply in their 
comment letter that CAFE regulatory alternatives that do not include an 
EJ credit would not benefit EJ communities.\655\ There are a few 
reasons why we do not believe this is the case.
---------------------------------------------------------------------------

    \655\ Hyundai, at 4. (``At this early scoping stage, we 
encourage NHTSA to consider and evaluate such alternatives that 
create an incentive for high-performing fuel economy and advanced 
technology vehicles that benefit EJ communities, such as the 
optional programs described above. For comprehensive analysis, we 
also recommend that NHTSA analyze the impacts on these communities 
of programs that do not create such an incentive.'').
---------------------------------------------------------------------------

    Evidence suggests that the CAFE program produces fuel savings 
benefits for purchasers of vehicles, and that these benefits may be 
particularly important to households that spend a disproportionate 
share of their income on fuel, like lower income households. While it 
is true that lower income households are more likely to purchase used 
vehicles, and NHTSA's authority to regulate vehicle fuel economy 
applies to new vehicles that a manufacturer produces for sale in each 
MY,\656\ research suggests that all income groups will benefit from 
improvements in fuel efficiency. The 2015 NAS report found that CAFE 
standards made both new and used cars more affordable due to the value 
of added fuel savings realized over the lifetime of the vehicle.\657\ 
Additionally, the net benefits extended to consumers from the standards 
were estimated to be greater for low-income households.\658\
---------------------------------------------------------------------------

    \656\ NHTSA does consider the impact of CAFE regulatory costs on 
new vehicles when setting standards, and in particular for this 
proposal, concluded that the increases in regulatory costs are more 
than offset by the fuel savings that consumers will experience. 
However, some factors related to vehicle affordability--specifically 
manufacturer and dealer pricing strategies--are beyond NHTSA's 
control.
    \657\ 2015 NAS report, at 331.
    \658\ Id. The NAS report estimated that some low-income 
households spent almost 50 percent more on fuel than on vehicles in 
2011. The study estimated that the standards assessed in 2015 would 
increase vehicle prices by about 6 percent but reduce fuel 
consumption by one-third relative to the 2016 standards.
---------------------------------------------------------------------------

    More recent data affirms that fuel spending constitutes a higher 
percentage of earnings in low-income households: U.S. households 
earning less than $25,000 spend 50 percent of their income on vehicle 
ownership and operation annually, or about $7,400.\659\ Research has 
shown that CAFE standards provide distributed benefits across household 
income ranges, with low-income households in the lower 80 percent of 
the U.S. income distribution receiving annual net savings on vehicles 
and fuel estimated between 0.5 and 2.0 percent of their average annual 
income from 1980 to 2014.\660\
---------------------------------------------------------------------------

    \659\ Bauer, Gordon & Hsu, Chih-Wei & Lutsey, Nicholas. (2021). 
When might lower-income drivers benefit from electric vehicles? 
Quantifying the economic equity implications of electric vehicle 
adoption. (citing U.S. Bureau of Labor Statistics, 2020).
    \660\ Greene & Welch, 2018, Energy Policy, 122: 528-541.
---------------------------------------------------------------------------

    Separately, this proposal incorporates the use of a proposed PEF 
value that better reflects EV fuel efficiency and also a less stringent 
rate of CAFE increase for passenger cars than light trucks. This should 
allow manufacturers to increase their fleet fuel economy so that fuel 
economy improvements are not concentrated in either the vehicles that 
were traditionally the smallest and least expensive (and would then 
become more expensive from the addition of fuel-economy-improving 
technology), or in the most expensive vehicles (which would have more 
fuel economy improvements but would not be targeted towards EJ 
communities). This will also benefit buyers in the used car market 
(who, again, are more likely to be low-income buyers), as they will 
have more options for fuel efficient vehicles. The new standards 
should, in theory, incentivize manufacturers to increase the fuel 
economy of their entire fleet, and the entire range of income groups 
would receive distributed benefits accordingly.
    CAFE standards also have the potential to benefit EJ communities 
because increasing fleet fuel economy produces important environmental 
and health-related benefits, including reductions in GHGs as well as 
reductions in harmful air pollutants that are emitted from upstream 
sources of gasoline production and from vehicle exhaust systems.
    As noted in the Draft EIS, a body of scientific literature signals 
disproportionate exposure of low-income and minority populations to 
poor air quality and proximity of minority and low-income populations 
to industrial, manufacturing, and hazardous waste facilities like oil 
production and refining facilities. Similarly, research shows that 
minority and low-income populations are disproportionately located in 
proximity to electric power plants and are thus exposed to pollutants 
associated with power generation. Research also shows that communities 
that live near heavily trafficked roadways--disproportionately low 
income and communities of color--are disproportionately exposed to 
vehicle exhaust pollutants. Finally, research demonstrates that EJ 
communities are more likely to suffer the consequences of climate 
change including more ozone pollution and more exposure to potentially 
deadly heatwaves, among other impacts. Health-related sensitivities in 
low-income and minority populations additionally increase the risk of 
damaging impacts from poor air quality under climate change, 
underscoring the potential benefits of improving air quality for 
communities overburdened by poor environmental quality.
    The combined CAFE and HDPUV standards contribute to a reduction in 
fuel use, meaning that to the extent that minority and low-income 
populations live closer to upstream sources of vehicle-related 
emissions, like oil extraction, distribution, and refining facilities 
or are more susceptible to their impacts (e.g., health and other 
impacts relating to emissions, vibration, or noise from the oil 
extraction, distribution, and refining process), they are more likely 
to experience reduced impacts resulting from a reduction in these 
activities. In addition, negative impacts from electric power plant 
emissions may be mitigated to the extent that the electrical grid 
becomes cleaner and draws more from renewable energy generation, which 
is projected to occur. The EIA's AEO 2023 projects that renewable 
sources of energy will displace fossil fuels in the electric power 
sector due to declining renewable technology costs and rising subsidies 
for renewable power. Finally, emissions of most vehicle-based criteria 
pollutant and air toxic emissions are also anticipated to decrease 
across all alternatives analyzed in the Draft EIS compared to the No-
Action Alternative, even considering an increase in vehicle miles 
traveled due to vehicles becoming more efficient (i.e., the rebound 
effect). When the power sector emission projections are updated in the 
analysis that will accompany the final standards, these emission 
reductions are likely to be greater and universal across different 
pollutant types.
    Relatedly, adverse health impacts from criteria pollutant emissions 
are

[[Page 56374]]

projected to decrease nationwide under each of the action alternatives 
compared to the No-Action Alternative. To the extent that EJ 
communities are disproportionately located closer to sources of 
upstream and downstream pollution that decrease as a result of 
increased CAFE standards, those communities could see health benefits 
due to decreasing emissions.
    Finally, all action alternatives are projected to result in small 
but incrementally important decreases in global mean surface 
temperature, atmospheric CO2 concentrations, sea level rise, 
and increases in ocean pH. The reduction of air pollutants and GHGs 
could result in improvements in air quality, decreases in total health 
effects, and a reduction in the number and severity of outbreaks of 
vector-borne illnesses related to climate change for minority and low-
income communities. Fleetwide improvements in fuel economy, in other 
words, have the potential to benefit EJ communities by reducing 
disproportionate environmental impacts on those overburdened 
communities.
    Ensuring the incentive benefits environmental justice communities 
by not ``double counting'' across regulatory programs. Hyundai stated 
that ``[p]roposed additional ``EJ credits'' could apply to EVs, PHEV, 
HEVs, and better-performing combustion engines, such as [SULEVs] 
providing verifiable benefits to EJ communities.'' However, Congress 
has already provided an explicit incentive in EPCA for manufacturers to 
produce better-performing combustion engines; manufacturers earn 
overcompliance credits when their fleet of vehicles performs at a level 
more than the ``maximum feasible'' level that NHTSA determines can be 
achieve in a MY.\661\ Relatedly, Congress also provided an incentive in 
EPCA to encourage the production of alternative fueled vehicles.\662\ 
Similarly, Congress requires manufacturers to sell better-forming 
combustion engines such as SULEVs under the CAA. In fact, under EPA's 
Tier 3 emissions standards and California's Low Emission Vehicle (LEV 
III) standards, vehicle exhaust emissions are required to decrease 
significantly by MY 2025.\663\
---------------------------------------------------------------------------

    \661\ 49 U.S.C. 32903.
    \662\ See 87 FR 25995-6 (May 2, 2022) (``NHTSA agrees that the 
intent of 32902(h), when combined with the other statutory 
incentives in EPCA such as those at 49 U.S.C. 32905 and 32906, was 
to encourage production of alternative fueled vehicles. NHTSA 
disagrees that the approach taken [in regulations setting CAFE 
standards] to modeling the current existence of alternative fueled 
vehicles (AFVs) and their possible application in MYs beyond those 
for which we are setting standards in any way disincentivizes their 
application or conflicts with EPA or Administration electrification 
goals.'').
    \663\ 79 FR 23414 (April 28, 2014); U.S. EPA Green Vehicle 
Guide, Smog Rating (last updated April 4, 2023), https://www.epa.gov/greenvehicles/smog-rating; 13 CCR 1961.2.
---------------------------------------------------------------------------

    It is not clear how giving manufacturers a credit for doing 
something they are already required to do would benefit communities 
with EJ concerns without simply providing a credit windfall for 
manufacturers, which would itself reduce the air pollution reduction 
co-benefits which directly benefit these communities.
    Ensuring continued increases in overall fleet fuel economy in 
accordance with EPCA. While the CAFE standards proposed will ensure 
that manufacturers improve the fuel economy level of vehicles across 
their entire fleets, NHTSA is concerned that EJ credits may actually 
create a perverse incentive by allowing fuel economy increases in a 
manufacturer's fleet to stagnate. EJ credits may allow manufacturers to 
produce a few highly fuel-efficient vehicles that allow several other 
low-efficiency vehicles to be sold. Credits (overcompliance, proposed 
EJ, or otherwise) allow manufacturers to meet their CAFE standard 
without applying additional technology to vehicles. And, as Congress 
recognized in EPCA through its mandate to NHTSA to preserve total oil 
savings in credit exchanges, a gallon of fuel saved by technology 
application is worth more than a credit applied so that a manufacturer 
does not have to improve its fleet fuel economy through technology 
application. NHTSA is interested in comments from Hyundai or other 
stakeholders about how EJ credits would ensure continued increases in a 
manufacturer's fleet fuel economy level. Would a minimum production 
threshold, like with the full-size pickup truck incentives, be 
appropriate in a proposed EJ credit program?
    Separate from Hyundai's request, NHTSA remains mindful of its 
obligations to consider the effects of its rules on EJ communities, in 
accordance with NEPA, all relevant EOs, including President Biden's 
E.O. 14008, and the DOT's EJ strategies. The Draft EIS and this 
preamble both discuss NHTSA's considerations about the effects of this 
proposal on EJ communities. In addition, Section V of this preamble 
discusses NHTSA's considerations on the additional cost of technology 
required to meet the proposal's preferred level of CAFE standards.

VII. Public Participation

    NHTSA requests comments on all aspects of this NPRM. This section 
describes how you can participation in this process.

How do I prepare and submit comments?

    Your comments must be written and in English.\664\ To ensure that 
your comments are correctly filed in the docket, please include the 
docket number NHTSA-2023-0022 in your comments. Your comments must not 
be more than 15 pages long.\665\ NHTSA established this limit to 
encourage you to write your primary comments in a concise fashion. 
However, you may attach necessary additional documents to your 
comments, and there is no limit on the length of the attachments If you 
are submitting comments electronically as a PDF (Adobe) file, we ask 
that the documents please be scanned using the Optical Character 
Recognition (OCR) process, thus allowing NHTSA to search and copy 
certain portions of your submissions.\666\ Please note that pursuant to 
the Data Quality Act, in order for substantive data to be relied upon 
and used by NHTSA, it must meet the information quality standards set 
forth in the OMB and DOT Data Quality Act guidelines. Accordingly, we 
encourage you to consult the guidelines in preparing your comments. 
OMB's guidelines may be accessed at https://www.gpo.gov/fdsys/pkg/FR-2002-02-22/pdf/R2-59.pdf. DOT's guidelines may be accessed at https://www.transportation.gov/dot-information-dissemination-quality-guidelines.
---------------------------------------------------------------------------

    \664\ 49 CFR 553.21.
    \665\ Id.
    \666\ OCR is the process of converting an image of text, such as 
a scanned paper document or electronic fax file, into computer-
editable text.
---------------------------------------------------------------------------

Tips for Preparing Your Comments

    When submitting comments, please remember to:
     Identify the rulemaking by docket number and other 
identifying information (subject heading, Federal Register date, and 
page number).
     Explain why you agree or disagree, suggest alternatives, 
and substitute language for your requested changes.
     Describe any assumptions and provide any technical 
information and/or data that you used.
     If you estimate potential costs or burdens, explain how 
you arrived at your estimate in sufficient detail to allow for it to be 
reproduced.
     Provide specific examples to illustrate your concerns and 
suggest alternatives.

[[Page 56375]]

     Explain your views as clearly as possible, avoiding the 
use of profanity or personal threats.
     Make sure to submit your comments by the comment period 
deadline identified in the DATES section above.

How can I be sure that my comments were received?

    If you submit your comments to NHTSA's docket by mail and wish DOT 
Docket Management to notify you upon receipt of your comments, please 
enclose a self-addressed, stamped postcard in the envelope containing 
your comments. Upon receiving your comments, Docket Management will 
return the postcard by mail.

How do I submit confidential business information?

    If you wish to submit any information under a claim of 
confidentiality, you should submit your complete submission, including 
the information you claim to be CBI, to NHTSA's Office of the Chief 
Counsel. When you send a comment containing CBI, you should include a 
cover letter setting forth the information specified in our CBI 
regulation.\667\ In addition, you should submit a copy from which you 
have deleted the claimed CBI to the docket by one of the methods set 
forth above.
---------------------------------------------------------------------------

    \667\ See 49 CFR part 512.
---------------------------------------------------------------------------

    NHTSA is currently treating electronic submission as an acceptable 
method for submitting CBI to NHTSA under 49 CFR part 512. Any CBI 
submissions sent via email should be sent to an attorney in the Office 
of the Chief Counsel at the address given above under FOR FURTHER 
INFORMATION CONTACT. Likewise, for CBI submissions via a secure file 
transfer application, an attorney in the Office of the Chief Counsel 
must be set to receive a notification when files are submitted and have 
access to retrieve the submitted files. At this time, regulated 
entities should not send a duplicate hardcopy of their electronic CBI 
submissions to DOT headquarters. If you have any questions about CBI or 
the procedures for claiming CBI, please consult the person identified 
in the FOR FURTHER INFORMATION CONTACT section.

Will NHTSA consider late comments?

    NHTSA will consider all comments received before the close of 
business on the comment closing date indicated above under DATES. To 
the extent practicable, we will also consider comments received after 
that date. If interested persons believe that any information that 
NHTSA places in the docket after the issuance of the NPRM affects their 
comments, they may submit comments after the closing date concerning 
how NHTSA should consider that information for the final rule. However, 
NHTSA's ability to consider any such late comments in this rulemaking 
will be limited due to the time frame for issuing a final rule.
    If a comment is received too late for us to practicably consider in 
developing a final rule, we will consider that comment as an informal 
suggestion for future rulemaking action.

How can I read the comments submitted by other people?

    You may read the materials placed in the dockets for this document 
(e.g., the comments submitted in response to this document by other 
interested persons) at any time by going to https://www.regulations.gov. Follow the online instructions for accessing the 
dockets. You may also read the materials at the DOT Docket Management 
Facility by going to the street address given above under ADDRESSES.

How do I participate in the public hearings?

    NHTSA will hold one virtual public hearing during the public 
comment period. NHTSA will announce the specific date and web address 
for the hearing in a supplemental Federal Register notification. NHTSA 
will accept oral and written comments to the rulemaking documents and 
will also accept comments to the Draft EIS at this hearing. The hearing 
will start at 9 a.m. Eastern time and will continue until everyone has 
had a chance to speak.
    NHTSA will conduct the hearing informally, and technical rules of 
evidence will not apply. We will arrange for a written transcript of 
each hearing to be posted in the dockets as soon as it is available and 
keep the official record of the hearing open for 30 days following the 
hearing to allow you to submit supplementary information.

How do I comment on the Draft Environmental Impact Statement?

    The Draft EIS associated with this proposal has a unique public 
docket number and is available Docket No. NHTSA-2022-0075. Comments on 
the Draft EIS can be submitted electronically at https://www.regulations.gov, at this docket number. You may also mail or hand 
deliver comments to Docket Management, U.S. Department of 
Transportation, 1200 New Jersey Avenue SE, Room W12-140, Washington, DC 
20590 (referencing Docket No. NHTSA-2022-0075), between 9 a.m. and 5 
p.m., Monday through Friday, except on Federal holidays. To be sure 
that someone is there to help you, please call (202) 366-9322 before 
coming. All comments and materials received, including the names and 
addresses of the commenters who submit them, will become part of the 
administrative record and will be posted on the internet without change 
at https://www.regulations.gov.

VIII. Regulatory Notices and Analyses

A. Executive Order 12866, Executive Order 13563

    E.O. 12866, ``Regulatory Planning and Review'' (58 FR 51735, Oct. 
4, 1993), as amended by E.O. 13563, ``Improving Regulation and 
Regulatory Review'' (76 FR 3821, Jan. 21, 2011) and E.O. 14094, 
``Modernizing Regulatory Review'' (88 FR 21879), provide for making 
determinations whether a regulatory action is ``significant'' and 
therefore subject to the Office of Management and Budget (OMB) review 
process and to the requirements of the E.O. Under these E.O.s, this 
action is an ``significant regulatory action'' under section 3(f)(1) of 
Executive Order 12866 because it is likely to have an annual effect on 
the economy of $200 million or more. Accordingly, NHTSA submitted this 
action to OMB for review and any changes made in response to 
interagency feedback submitted via the OMB review process have been 
documented in the docket for this action. The estimated benefits and 
costs of this proposal are described above and in the PRIA, which is 
located in the docket and on NHTSA's website.

B. DOT Regulatory Policies and Procedures

    This proposal is also significant within the meaning of the DOT's 
Regulatory Policies and Procedures. The estimated benefits and costs of 
the proposal are described above and in the PRIA, which is located in 
the docket and on NHTSA's website.

C. Executive Order 13990

    E.O. 14037, ``Strengthening American Leadership in Clean Cars and 
Trucks'' (86 FR 43583, Aug. 10, 2021), directs the Secretary of 
Transportation (by delegation, NHTSA) to consider beginning work on a 
rulemaking under EISA to establish new fuel economy standards for 
passenger cars and LD trucks beginning with MY 2027 and extending 
through and including at least MY 2030, and to consider beginning work 
on a rulemaking under EISA to establish new fuel efficiency standards 
for HDPUVs beginning with MY 2028

[[Page 56376]]

and extending through and including at least MY 2030.\668\ The E.O. 
directs the Secretary to consider issuing any final rule no later than 
July 2024; \669\ to coordinate with the EPA and the Secretaries of 
Commerce, Labor, and Energy; \670\ and to coordinate this work, ``as 
appropriate and consistent with applicable law, with the State of 
California as well as other States that are leading the way in reducing 
vehicle emissions, including by adopting California's standards.'' 
\671\ The Secretary is also directed to ``seek input from a diverse 
range of stakeholders, including representatives from labor unions, 
States, industry, EJ organizations, and public health experts.'' \672\
---------------------------------------------------------------------------

    \668\ 86 FR 43583 (Aug. 10, 2021), Sec. 2(b) and (c).
    \669\ Id., Sec. 5(b).
    \670\ Id., Sec. 6(a) and (b).
    \671\ (copyright)., Sec. 6(c).
    \672\ Id., Sec. 6(d).
---------------------------------------------------------------------------

    This proposal seeks to follow the directions of this E.O. It is 
proposed under NHTSA's statutory authorities as set forth in EISA. It 
proposes new CAFE standards for passenger cars and light trucks 
beginning in MY 2027, and new fuel efficiency standards for HDPUVs 
beginning in MY 2030 due to statutory lead time and stability 
requirements. NHTSA coordinated with both EPA and with the State of 
California in developing this proposal, and the proposal also accounts 
for the views provided by labor unions, States, industry, and EJ 
organizations.

D. Environmental Considerations

1. National Environmental Policy Act (NEPA)
    Concurrently with this NPRM, NHTSA is releasing a Draft EIS, 
pursuant to the National Environmental Policy Act, 42 U.S.C. 4321 
through 4347, and implementing regulations issued by the Council on 
Environmental Quality (CEQ), 40 CFR part 1500, and NHTSA, 49 CFR part 
520. NHTSA prepared the Draft EIS to analyze and disclose the potential 
environmental impacts of the proposed CAFE and HDPUV FE standards and a 
range of alternatives. The Draft EIS analyzes direct, indirect, and 
cumulative impacts and analyzes impacts in proportion to their 
significance. It describes potential environmental impacts to a variety 
of resources, including fuel and energy use, air quality, climate, land 
use and development, hazardous materials and regulated wastes, 
historical and cultural resources, and EJ. The Draft EIS also describes 
how climate change resulting from global carbon dioxide emissions 
(including CO2 emissions attributable to the U.S. LD and 
HDPUV transportation sectors under the alternatives considered) could 
affect certain key natural and human resources. Resource areas are 
assessed qualitatively and quantitatively, as appropriate, in the Draft 
EIS.
    NHTSA has considered the information contained in the Draft EIS as 
part of developing this proposal. The Draft EIS is available for public 
comment; instructions for the submission of comments are included 
inside the document. NHTSA will simultaneously issue the Final 
Environmental Impact Statement and Record of Decision, pursuant to 49 
U.S.C. 304a(b), unless it is determined that statutory criteria or 
practicability considerations preclude simultaneous issuance. For 
additional information on NHTSA's NEPA analysis, please see the Draft 
EIS.
2. Clean Air Act (CAA) as Applied to NHTSA's Proposal
    The CAA (42 U.S.C. 7401 et seq.) is the primary Federal legislation 
that addresses air quality. Under the authority of the CAA and 
subsequent amendments, EPA has established National Ambient Air Quality 
Standards (NAAQS) for six criteria pollutants, which are relatively 
commonplace pollutants that can accumulate in the atmosphere as a 
result of human activity. EPA is required to review NAAQS every five 
years and to revise those standards as may be appropriate considering 
new scientific information.
    The air quality of a geographic region is usually assessed by 
comparing the levels of criteria air pollutants found in the ambient 
air to the levels established by the NAAQS (taking into account, as 
well, the other elements of a NAAQS: averaging time, form, and 
indicator). Concentrations of criteria pollutants within the air mass 
of a region are measured in parts of a pollutant per million parts 
(ppm) of air or in micrograms of a pollutant per cubic meter ([mu]g/m3) 
of air present in repeated air samples taken at designated monitoring 
locations using specified types of monitors. These ambient 
concentrations of each criteria pollutant are compared to the levels, 
averaging time, and form specified by the NAAQS in order to assess 
whether the region's air quality is in attainment with the NAAQS.
    When the measured concentrations of a criteria pollutant within a 
geographic region are below those permitted by the NAAQS, EPA 
designates the region as an attainment area for that pollutant, while 
regions where concentrations of criteria pollutants exceed Federal 
standards are called nonattainment areas. Former nonattainment areas 
that are now in compliance with the NAAQS are designated as maintenance 
areas. Each State with a nonattainment area is required to develop and 
implement a State Implementation Plan (SIP) documenting how the region 
will reach attainment levels within time periods specified in the CAA. 
For maintenance areas, the SIP must document how the State intends to 
maintain compliance with the NAAQS. EPA develops a Federal 
Implementation Plan (FIP) if a State fails to submit an approvable plan 
for attaining and maintaining the NAAQS. When EPA revises a NAAQS, each 
State must revise its SIP to address how it plans to attain the new 
standard.
    No Federal agency may ``engage in, support in any way or provide 
financial assistance for, license or permit, or approve'' any activity 
that does not ``conform'' to a SIP or FIP after EPA has approved or 
promulgated it.\673\ Further, no Federal agency may ``approve, accept 
or fund'' any transportation plan, program, or project developed 
pursuant to Title 23 or Chapter 53 of Title 49, U.S.C., unless the 
plan, program, or project has been found to ``conform'' to any 
applicable implementation plan in effect.\674\ The purpose of these 
conformity requirements is to ensure that Federally sponsored or 
conducted activities do not interfere with meeting the emissions 
targets in SIPs or FIPs, do not cause or contribute to new violations 
of the NAAQS, and do not impede the ability of a State to attain or 
maintain the NAAQS or delay any interim milestones. EPA has issued two 
sets of regulations to implement the conformity requirements:
---------------------------------------------------------------------------

    \673\ 42 U.S.C. 7506(c)(1).
    \674\ 42 U.S.C. 7506(c)(2).
---------------------------------------------------------------------------

    (1) The Transportation Conformity Rule \675\ applies to 
transportation plans, programs, and projects that are developed, 
funded, or approved under 23 U.S.C. (Highways) or 49 U.S.C. Chapter 53 
(Public Transportation)
---------------------------------------------------------------------------

    \675\ 40 CFR part 51, subpart T, and part 93, subpart A.
---------------------------------------------------------------------------

    (2) The General Conformity Rule \676\ applies to all other Federal 
actions not covered under transportation conformity. The General 
Conformity Rule establishes emissions thresholds, or de minimis levels, 
for use in evaluating the conformity of an action that results in 
emissions increases.\677\ If the net increases of direct and indirect 
emissions exceed any of these thresholds, and the action is not 
otherwise exempt, then a conformity

[[Page 56377]]

determination is required. The conformity determination can entail air 
quality modeling studies, consultation with EPA and state air quality 
agencies, and commitments to revise the SIP or to implement measures to 
mitigate air quality impacts.
---------------------------------------------------------------------------

    \676\ 40 CFR part 51, subpart W, and part 93, subpart B.
    \677\ 40 CFR 93.153(b).
---------------------------------------------------------------------------

    The proposed CAFE and HDPUV FE standards and associated program 
activities are not developed, funded, or approved under 23 U.S.C. or 49 
U.S.C. Chapter 53. Accordingly, this proposed action and associated 
program activities would not be subject to transportation conformity. 
Under the General Conformity Rule, a conformity determination is 
required where a Federal action would result in total direct and 
indirect emissions of a criteria pollutant or precursor originating in 
nonattainment or maintenance areas equaling or exceeding the rates 
specified in 40 CFR 93.153(b)(1) and (2). As explained below, NHTSA's 
action would result in neither direct nor indirect emissions as defined 
in 40 CFR 93.152.
    The General Conformity Rule defines direct emissions as ``those 
emissions of a criteria pollutant or its precursors that are caused or 
initiated by the Federal action and originate in a nonattainment or 
maintenance area and occur at the same time and place as the action and 
are reasonably foreseeable.'' \678\ NHTSA's action would set fuel 
economy standards for passenger cars and light trucks and fuel 
efficiency standards for HDPUVs. It therefore would not cause or 
initiate direct emissions consistent with the meaning of the General 
Conformity Rule.\679\ Indeed, the proposal in aggregate reduces 
emissions, and to the degree the model predicts small (and time-
limited) increases, these increases are based on a theoretical response 
by individuals to fuel prices and savings, which are at best indirect.
---------------------------------------------------------------------------

    \678\ 40 CFR 93.152.
    \679\ Dep't of Transp. v. Pub. Citizen, 541 U.S.752 at 772 
(``[T]he emissions from the Mexican trucks are not `direct' because 
they will not occur at the same time or at the same place as the 
promulgation of the regulations.''). NHTSA's action is to establish 
fuel economy standards for MY 2021-2026 passenger car and light 
trucks; any emissions increases would occur in a different place and 
well after promulgation of the final rule.
---------------------------------------------------------------------------

    Indirect emissions under the General Conformity Rule are ``those 
emissions of a criteria pollutant or its precursors (1) that are caused 
or initiated by the federal action and originate in the same 
nonattainment or maintenance area but occur at a different time or 
place as the action; (2) that are reasonably foreseeable; (3) that the 
agency can practically control; and (4) for which the agency has 
continuing program responsibility.'' \680\ Each element of the 
definition must be met to qualify as indirect emissions. NHTSA has 
determined that, for purposes of general conformity, emissions (if any) 
that may result from the proposed fuel economy and fuel efficiency 
standards would not be caused by the agency's action, but rather would 
occur because of subsequent activities the agency cannot practically 
control. ``[E]ven if a Federal licensing, rulemaking or other approving 
action is a required initial step for a subsequent activity that causes 
emissions, such initial steps do not mean that a Federal agency can 
practically control any resulting emissions.'' \681\
---------------------------------------------------------------------------

    \680\ 40 CFR 93.152.
    \681\ 40 CFR 93.152.
---------------------------------------------------------------------------

    As the CAFE and HDPUV FE programs use performance-based standards, 
NHTSA cannot control the technologies vehicle manufacturers use to 
improve the fuel economy of passenger cars and light trucks and fuel 
efficiency of HDPUVs. Furthermore, NHTSA cannot control consumer 
purchasing (which affects average achieved fleetwide fuel economy and 
fuel efficiency) and driving behavior (i.e., operation of motor 
vehicles, as measured by VMT). It is the combination of fuel economy 
and fuel efficiency technologies, consumer purchasing, and driving 
behavior that results in criteria pollutant or precursor emissions. For 
purposes of analyzing the environmental impacts of the alternatives 
considered under NEPA, NHTSA has made assumptions regarding all of 
these factors. NHTSA's Draft EIS projects that increases in air toxics 
and criteria pollutants would occur in some nonattainment areas under 
certain alternatives in the near term, although over the longer term, 
all action alternatives see improvements. However, the proposed 
standards and alternatives do not mandate specific manufacturer 
decisions, consumer purchasing, or driver behavior, and NHTSA cannot 
practically control any of them.\682\
---------------------------------------------------------------------------

    \682\ See, e.g., Dep't of Transp. v. Pub. Citizen, 541 U.S. 752, 
772-73 (2004); S. Coast Air Quality Mgmt. Dist. v. Fed. Energy 
Regulatory Comm'n, 621 F.3\d\ 1085, 1101 (9th Cir. 2010).
---------------------------------------------------------------------------

    In addition, NHTSA does not have the statutory authority or 
practical ability to control the actual VMT by drivers. As the extent 
of emissions is directly dependent on the operation of motor vehicles, 
changes in any emissions that would result from NHTSA's proposed CAFE 
and HDPUV FE standards are not changes NHTSA can practically control or 
for which NHTSA has continuing program responsibility. Therefore, the 
proposed CAFE and HDPUV FE standards and alternative standards 
considered by NHTSA would not cause indirect emissions under the 
General Conformity Rule, and a general conformity determination is not 
required.
3. National Historic Preservation Act (NHPA)
    The NHPA (54 U.S.C. 300101 et seq.) sets forth government policy 
and procedures regarding ``historic properties''--that is, districts, 
sites, buildings, structures, and objects included on or eligible for 
the National Register of Historic Places. Section 106 of the NHPA 
requires Federal agencies to ``take into account'' the effects of their 
actions on historic properties.\683\ NHTSA concludes that the NHPA is 
not applicable to this proposal because the promulgation of CAFE 
standards for passenger cars and light trucks and HDPUV FE standards 
for HDPUVs is not the type of activity that has the potential to cause 
effects on historic properties. However, NHTSA includes a brief, 
qualitative discussion of the impacts of the action alternatives on 
historical and cultural resources in the Draft EIS.
---------------------------------------------------------------------------

    \683\ Section 106 is now codified at 54 U.S.C. 306108. 
Implementing regulations for the section 106 process are located at 
36 CFR part 800.
---------------------------------------------------------------------------

4. Fish and Wildlife Conservation Act (FWCA)
    The FWCA (16 U.S.C. 2901 et seq.) provides financial and technical 
assistance to States for the development, revision, and implementation 
of conservation plans and programs for nongame fish and wildlife. In 
addition, FWCA encourages all Federal departments and agencies to 
utilize their statutory and administrative authorities to conserve and 
to promote conservation of nongame fish and wildlife and their 
habitats. NHTSA concludes that the FWCA does not apply to this proposal 
because it does not involve the conservation of nongame fish and 
wildlife and their habitats. However, NHTSA conducted a qualitative 
review in its Draft EIS of the related direct, indirect, and cumulative 
impacts, positive or negative, of the Proposed Action and alternatives 
on potentially affected resources, including nongame fish and wildlife 
and their habitats.
5. Coastal Zone Management Act (CZMA)
    The CZMA (16 U.S.C. 1451 et seq.) provides for the preservation, 
protection, development, and (where

[[Page 56378]]

possible) restoration and enhancement of the Nation's coastal zone 
resources. Under the statute, States are provided with funds and 
technical assistance in developing coastal zone management programs. 
Each participating State must submit its program to the Secretary of 
Commerce for approval. Once the program has been approved, any activity 
of a Federal agency, either within or outside of the coastal zone, that 
affects any land or water use or natural resource of the coastal zone 
must be carried out in a manner that is consistent, to the maximum 
extent practicable, with the enforceable policies of the State's 
program.\684\
---------------------------------------------------------------------------

    \684\ 16 U.S.C. 1456(c)(1)(A).
---------------------------------------------------------------------------

    NHTSA concludes that the CZMA does not apply to this proposal 
because it does not involve an activity within, or outside of, the 
nation's coastal zones that affects any land or water use or natural 
resource of the coastal zone. NHTSA has, however, conducted a 
qualitative review in the Draft EIS of the related direct, indirect, 
and cumulative impacts, positive or negative, of the action 
alternatives on potentially affected resources, including coastal 
zones.
6. Endangered Species Act (ESA)
    Under section 7(a)(2) of the ESA, Federal agencies must ensure that 
actions they authorize, fund, or carry out are ``not likely to 
jeopardize the continued existence'' of any Federally listed threatened 
or endangered species (collectively, ``listed species'') or result in 
the destruction or adverse modification of the designated critical 
habitat of these species.\685\ If a Federal agency determines that an 
agency action may affect a listed species or designated critical 
habitat, it must initiate consultation with the appropriate Service--
the U.S. Fish and Wildlife Service (FWS) of the Department of the 
Interior (DOI) or the National Oceanic and Atmospheric Administration's 
National Marine Fisheries Service of the Department of Commerce 
(together, ``the Services'') or both, depending on the species 
involved--in order to ensure that the action is not likely to 
jeopardize the species or destroy or adversely modify designated 
critical habitat.\686\ Under this standard, the Federal agency taking 
action evaluates the possible effects of its action and determines 
whether to initiate consultation.\687\
---------------------------------------------------------------------------

    \685\ 16 U.S.C. 1536(a)(2).
    \686\ See 50 CFR 402.14.
    \687\ See 50 CFR 402.14(a) (``Each Federal agency shall review 
its actions at the earliest possible time to determine whether any 
action may affect listed species or critical habitat.'').
---------------------------------------------------------------------------

    The section 7(a)(2) implementing regulations require consultation 
if a Federal agency determines its action ``may affect'' listed species 
or critical habitat.\688\ The regulations define ``effects of the 
action'' as ``all consequences to listed species or critical habitat 
that are caused by the proposed action, including the consequences of 
other activities that are caused by the proposed action. A consequence 
is caused by the proposed action if it would not occur but for the 
proposed action and it is reasonably certain to occur.'' \689\ The 
definition makes explicit a ``but for'' test and the concept of 
``reasonably certain to occur'' for all effects.\690\ The Services have 
defined ``but for'' causation to mean ``that the consequence in 
question would not occur if the proposed action did not go forward. In 
other words, if the agency fails to take the proposed action and the 
activity would still occur, there is no `but for' causation. In that 
event, the activity would not be considered an effect of the action 
under consultation.'' \691\
---------------------------------------------------------------------------

    \688\ 50 CFR 402.14(a). The recently issued final rule revising 
the regulations governing the ESA section 7 consultation process was 
published at 84 FR 44976 (Aug. 27, 2019). The effective date of the 
new regulations was subsequently delayed to October 28, 2019. 84 FR 
50333 (Sept. 25, 2019). As discussed in the text that follows, NHTSA 
believes that the conclusion would be the same under both the 
current and prior regulations.
    \689\ 50 CFR 402.02 (emphasis added), as amended by 84 FR 44976, 
45016 (Aug. 27, 2019).
    \690\ The Services' prior regulations defined ``effects of the 
action'' in relevant part as ``the direct and indirect effects of an 
action on the species or critical habitat, together with the effects 
of other activities that are interrelated or interdependent with 
that action, that will be added to the environmental baseline.'' 50 
CFR 402.02 (as in effect prior to Oct. 28, 2019). Indirect effects 
were defined as ``those that are caused by the proposed action and 
are later in time, but still are reasonably certain to occur.'' Id.
    \691\ 84 FR 44977 (Aug. 27, 2019) (``As discussed in the 
proposed rule, the Services have applied the `but for' test to 
determine causation for decades. That is, we have looked at the 
consequences of an action and used the causation standard of `but 
for' plus an element of foreseeability (i.e., reasonably certain to 
occur) to determine whether the consequence was caused by the action 
under consultation.''). We note that as the Services do not consider 
this to be a change in their longstanding application of the ESA, 
this interpretation applies equally under the prior regulations 
(which were effective through October 28, 2019), and the current 
regulations.
---------------------------------------------------------------------------

    The ESA regulations also provide a framework for determining 
whether consequences are caused by a proposed action and are therefore 
``effects'' that may trigger consultation. The regulations provide in 
part:
    To be considered an effect of a proposed action, a consequence must 
be caused by the proposed action (i.e., the consequence would not occur 
but for the proposed action and is reasonably certain to occur). A 
conclusion of reasonably certain to occur must be based on clear and 
substantial information, using the best scientific and commercial data 
available. Considerations for determining that a consequence to the 
species or critical habitat is not caused by the proposed action 
include, but are not limited to:
    (1) The consequence is so remote in time from the action under 
consultation that it is not reasonably certain to occur; or
    (2) The consequence is so geographically remote from the immediate 
area involved in the action that it is not reasonably certain to occur; 
or
    (3) The consequence is only reached through a lengthy causal chain 
that involves so many steps as to make the consequence not reasonably 
certain to occur.\692\
---------------------------------------------------------------------------

    \692\ 50 CFR 402.17(b).
---------------------------------------------------------------------------

    The regulations go on to make clear that the action agency must 
factor these considerations into its assessments of potential 
effects.\693\
---------------------------------------------------------------------------

    \693\ 50 CFR 402.17(c) (``Required consideration. The provisions 
in paragraphs (a) and (b) of this section must be considered by the 
action agency and the Services.'').
---------------------------------------------------------------------------

    The Services have previously provided legal and technical guidance 
about whether CO2 emissions associated with a specific 
proposed Federal action trigger ESA section 7(a)(2) consultation. NHTSA 
analyzed the Services' history of actions, analysis, and guidance in 
Appendix G of the MY 2012-2016 CAFE standards EIS and now incorporate 
by reference that appendix here.\694\ In that appendix, NHTSA looked at 
the history of the Polar Bear Special Rule and several guidance 
memoranda provided by FWS and the U.S. Geological Survey. Ultimately, 
DOI concluded that a causal link could not be made between 
CO2 emissions associated with a proposed Federal action and 
specific effects on listed species; therefore, no section 7(a)(2) 
consultation would be required.
---------------------------------------------------------------------------

    \694\ Available on NHTSA's Corporate Average Fuel Economy 
website at https://static.nhtsa.gov/nhtsa/downloads/CAFE/2012-2016%20Docs-PCLT/2012-2016%20Final%20Environmental%20Impact%20Statement/Appendix_G_Endangered_Species_Act_Consideration.pdf.
---------------------------------------------------------------------------

    Subsequent to the publication of that appendix, a court vacated the 
Polar Bear Special Rule on NEPA grounds, though it upheld the ESA 
analysis as having a rational basis.\695\ FWS then issued a revised 
Final Special Rule for the Polar Bear.\696\ In that final rule, FWS 
provided

[[Page 56379]]

that for ESA section 7, the determination of whether consultation is 
triggered is narrow and focused on the discrete effect of the proposed 
agency action. FWS wrote, ``[T]he consultation requirement is triggered 
only if there is a causal connection between the proposed action and a 
discernible effect to the species or critical habitat that is 
reasonably certain to occur. One must be able to `connect the dots' 
between an effect of a proposed action and an impact to the species and 
there must be a reasonable certainty that the effect will occur.'' 
\697\ The statement in the revised Final Special Rule is consistent 
with the prior guidance published by FWS and remains valid today.\698\ 
Likewise, the current regulations identify remoteness in time, 
geography, and the causal chain as factors to be considered in 
assessing whether a consequence is ``reasonably certain to occur.'' If 
the consequence is not reasonably certain to occur, it is not an 
``effect of a proposed action'' and does not trigger the consultation 
requirement.
---------------------------------------------------------------------------

    \695\ In re: Polar Bear Endangered Species Act Listing and 
Section 4(D) Rule Litigation, 818 F.Supp.2d 214 (DDC Oct. 17, 2011).
    \696\ 78 FR 11766 (Feb. 20, 2013).
    \697\ 78 FR 11784-11785 (Feb. 20, 2013).
    \698\ See DOI Solicitor's Opinion No. M-37017, ``Guidance on the 
Applicability of the Endangered Species Act Consultation 
Requirements to Proposed Actions Involving the Emissions of 
Greenhouse Gases'' (Oct. 3, 2008).
---------------------------------------------------------------------------

    In this NPRM, NHTSA states that pursuant to section 7(a)(2) of the 
ESA, NHTSA considered the effects of the proposed standards and 
reviewed applicable ESA regulations, case law, and guidance to 
determine what, if any, impact there might be to listed species or 
designated critical habitat. NHTSA has considered issues related to 
emissions of CO2 and other GHGs, and issues related to non-
GHG emissions. Based on this assessment, NHTSA determines that the 
action of setting CAFE and HDPUV FE standards does not require 
consultation under section 7(a)(2) of the ESA. Accordingly, NHTSA has 
concluded its review of this action under section 7 of the ESA.
7. Floodplain Management (Executive Order 11988 and DOT Order 5650.2)
    These Orders require Federal agencies to avoid the long- and short-
term adverse impacts associated with the occupancy and modification of 
floodplains, and to restore and preserve the natural and beneficial 
values served by floodplains. E.O. 11988, ``Floodplain management'' 
(May 24, 1977), also directs agencies to minimize the impacts of floods 
on human safety, health and welfare, and to restore and preserve the 
natural and beneficial values served by floodplains through evaluating 
the potential effects of any actions the agency may take in a 
floodplain and ensuring that its program planning and budget requests 
reflect consideration of flood hazards and floodplain management. DOT 
Order 5650.2, ``Floodplain Management and Protection'' (April 23, 
1979), sets forth DOT policies and procedures for implementing E.O. 
11988. The DOT Order requires that the agency determine if a proposed 
action is within the limits of a base floodplain, meaning it is 
encroaching on the floodplain, and whether this encroachment is 
significant. If significant, the agency is required to conduct further 
analysis of the proposed action and any practicable alternatives. If a 
practicable alternative avoids floodplain encroachment, then the agency 
is required to implement it.
    In this proposal, NHTSA is not occupying, modifying, and/or 
encroaching on floodplains. NHTSA therefore concludes that the Orders 
do not apply to this proposal. NHTSA has, however, conducted a review 
of the alternatives on potentially affected resources, including 
floodplains, in its Draft EIS.
8. Preservation of the Nation's Wetlands (Executive Order 11990 and DOT 
Order 5660.1a)
    These Orders require Federal agencies to avoid, to the extent 
possible, undertaking or providing assistance for new construction 
located in wetlands unless the agency head finds that there is no 
practicable alternative to such construction and that the proposed 
action includes all practicable measures to minimize harms to wetlands 
that may result from such use. E.O. 11990, ``Protection of Wetlands'' 
(May 24, 1977), also directs agencies to take action to minimize the 
destruction, loss, or degradation of wetlands in ``conducting Federal 
activities and programs affecting land use, including but not limited 
to water and related land resources planning, regulating, and licensing 
activities.'' DOT Order 5660.1a, ``Preservation of the Nation's 
Wetlands'' (August 24, 1978), sets forth DOT policy for interpreting 
E.O. 11990 and requires that transportation projects ``located in or 
having an impact on wetlands'' should be conducted to assure protection 
of the Nation's wetlands. If a project does have a significant impact 
on wetlands, an EIS must be prepared.
    NHTSA is not undertaking or providing assistance for new 
construction located in wetlands. NHTSA therefore concludes that these 
Orders do not apply to this NPRM. NHTSA has, however, conducted a 
review of the alternatives on potentially affected resources, including 
wetlands, in its Draft EIS.
9. Migratory Bird Treaty Act (MBTA), Bald and Golden Eagle Protection 
Act (BGEPA), Executive Order 13186
    The MBTA (16 U.S.C. 703-712) provides for the protection of certain 
migratory birds by making it illegal for anyone to ``pursue, hunt, 
take, capture, kill, attempt to take, capture, or kill, possess, offer 
for sale, sell, offer to barter, barter, offer to purchase, purchase, 
deliver for shipment, ship, export, import, cause to be shipped, 
exported, or imported, deliver for transportation, transport or cause 
to be transported, carry or cause to be carried, or receive for 
shipment, transportation, carriage, or export'' any migratory bird 
covered under the statute.\699\
---------------------------------------------------------------------------

    \699\ 16 U.S.C. 703(a).
---------------------------------------------------------------------------

    The BGEPA (16 U.S.C. 668-668d) makes it illegal to ``take, possess, 
sell, purchase, barter, offer to sell, purchase or barter, transport, 
export or import'' any bald or golden eagles.\700\ E.O. 13186, 
``Responsibilities of Federal Agencies to Protect Migratory Birds,'' 
helps to further the purposes of the MBTA by requiring a Federal agency 
to develop an MOU with FWS when it is taking an action that has (or is 
likely to have) a measurable negative impact on migratory bird 
populations.
---------------------------------------------------------------------------

    \700\ 16 U.S.C. 668(a).
---------------------------------------------------------------------------

    NHTSA concludes that the MBTA, BGEPA, and E.O. 13186 do not apply 
to this NPRM because there is no disturbance, take, measurable negative 
impact, or other covered activity involving migratory birds or bald or 
golden eagles involved in this rulemaking.
10. Department of Transportation Act (Section 4(f))
    Section 4(f) of the Department of Transportation Act of 1966 (49 
U.S.C. 303), as amended, is designed to preserve publicly owned park 
and recreation lands, waterfowl and wildlife refuges, and historic 
sites. Specifically, section 4(f) provides that DOT agencies cannot 
approve a transportation program or project that requires the use of 
any publicly owned land from a public park, recreation area, or 
wildlife or waterfowl refuge of national, State, or local significance, 
unless a determination is made that:
    (1) There is no feasible and prudent alternative to the use of 
land, and
    (2) The program or project includes all possible planning to 
minimize harm to the property resulting from the use.
    These requirements may be satisfied if the transportation use of a 
section 4(f)

[[Page 56380]]

property results in a de minimis impact on the area.
    NHTSA concludes that section 4(f) does not apply to this NPRM 
because this rulemaking is not an approval of a transportation program 
nor project that requires the use of any publicly owned land.
11. Department of Transportation Act (Section 4(f))
    E.O. 12898, ``Federal Actions to Address EJ in Minority Populations 
and Low-Income Populations'' (Feb. 16, 1994), directs Federal agencies 
to promote nondiscrimination in federal programs substantially 
affecting human health and the environment, and provide minority and 
low-income communities access to public information on, and an 
opportunity for public participation in, matters relating to human 
health or the environment. E.O. 12898 also directs agencies to identify 
and consider any disproportionately high and adverse human health or 
environmental effects that their actions might have on minority and 
low-income communities and provide opportunities for community input in 
the NEPA process. CEQ has provided agencies with general guidance on 
how to meet the requirements of the E.O. as it relates to NEPA. E.O. 
14096, ``Revitalizing Our Nation's Commitment to Environmental Justice 
for All,'' (April 21, 2023), builds on and supplements E.O. 12898, and 
further directs Federal agencies to prioritize EJ initiatives in their 
core missions.
    Additionally, the 2021 DOT Order 5610.2C, ``U.S. Department of 
Transportation Actions to Address Environmental Justice in Minority 
Populations and Low-Income Populations'' (May 16, 2021), describes the 
process for DOT agencies to incorporate EJ principles in programs, 
policies, and activities. The DOT's EJ Strategy specifies that EJ and 
fair treatment of all people means that no population be forced to bear 
a disproportionate burden due to transportation decisions, programs, 
and policies. It also defines the terms minority and low-income in the 
context of DOT's EJ analyses. Minority is defined as a person who is 
Black, Hispanic or Latino, Asian American, American Indian or Alaskan 
Native, or Native Hawaiian or other Pacific Islander. Low-income is 
defined as a person whose household income is at or below the 
Department of Health and Human Services poverty guidelines. Low-income 
and minority populations may live in geographic proximity or be 
geographically dispersed/transient. In 2021, DOT reviewed and updated 
its EJ strategy to ensure that it continues to reflect its commitment 
to EJ principles and integrate those principles into DOT programs, 
policies, and activities.
    Section VI and the Draft EIS discuss NHTSA's consideration of EJ 
issues associated with this proposal.
12. Executive Order 13045
    This action is subject to E.O. 13045 (62 FR 19885, Apr. 23, 1997) 
because it is an economically significant regulatory action as defined 
by E.O. 12866, and NHTSA has reason to believe that the environmental 
health and safety risks related to this action, although small, may 
have a disproportionate effect on children. Specifically, children are 
more vulnerable to adverse health effects related to mobile source 
emissions, as well as to the potential long-term impacts of climate 
change. Pursuant to E.O. 13045, NHTSA must prepare an evaluation of the 
environmental health or safety effects of the planned action on 
children and an explanation of why the planned action is preferable to 
other potentially effective and reasonably feasible alternatives 
considered by NHTSA. Further, this analysis may be included as part of 
any other required analysis.
    All of the action alternatives would reduce CO2 
emissions relative to the baseline and thus have positive effects on 
mitigating global climate change, and thus environmental and health 
effects associated with climate change. While environmental and health 
effects associated with criteria pollutant and toxic air pollutant 
emissions vary over time and across alternatives, negative effects, 
when estimated, are extremely small. This preamble and the Draft EIS 
discuss air quality, climate change, and their related environmental 
and health effects. In addition, Section V of this preamble explains 
why NHTSA believes that the proposed standards are preferable to other 
alternatives considered. Together, this preamble and Draft EIS satisfy 
NHTSA's responsibilities under E.O. 13045.
E. Regulatory Flexibility Act
    Pursuant to the Regulatory Flexibility Act (5 U.S.C. 601 et seq., 
as amended by the Small Business Regulatory Enforcement Fairness Act 
(SBREFA) of 1996), whenever an agency is required to publish an NPRM or 
final rule, it must prepare and make available for public comment a 
regulatory flexibility analysis that describes the effect of the rule 
on small entities (i.e., small businesses, small organizations, and 
small governmental jurisdictions). No regulatory flexibility analysis 
is required if the head of an agency certifies the rule will not have a 
significant economic impact on a substantial number of small entities. 
SBREFA amended the Regulatory Flexibility Act to require Federal 
agencies to provide a statement of the factual basis for certifying 
that a rule will not have a significant economic impact on a 
substantial number of small entities.
    NHTSA has considered the impacts of this proposed rule under the 
Regulatory Flexibility Act and the head of NHTSA certifies that this 
proposed rule will not have a significant economic impact on a 
substantial number of small entities. The following is NHTSA's 
statement providing the factual basis for this certification pursuant 
to 5 U.S.C. 605(b).
    Small businesses are defined based on the North American Industry 
Classification System (NAICS) code.\701\ One of the criteria for 
determining size is the number of employees in the firm. For 
establishments primarily engaged in manufacturing or assembling 
automobiles, including HDPUVs, the firm must have less than 1,500 
employees to be classified as a small business. This rulemaking would 
affect motor vehicle manufacturers. As shown in Table VII-1, NHTSA has 
identified fourteen small manufacturers that produce passenger cars, 
light trucks, SUVs, HD pickup trucks, and vans of electric, hybrid, and 
ICEs. NHTSA acknowledges that some very new manufacturers may 
potentially not be listed. However, those new manufacturers tend to 
have transportation products that are not part of the LD and HDPUV 
vehicle fleet and have yet to start production of relevant vehicles. 
Moreover, NHTSA does not believe that there are a ``substantial 
number'' of these companies.\702\
---------------------------------------------------------------------------

    \701\ Classified in NAICS under Subsector 336--Transportation 
Equipment Manufacturing for Automobile and Light Duty Motor Vehicle 
Manufacturing (336110) and Heavy Duty Truck Manufacturing (336120). 
Available at: https://www.sba.gov/document/support-table-size-standards. (Accessed: May 31, 2023).
    \702\ 5 U.S.C. 605(b).

[[Page 56381]]



                                    Table VII-1--Small Domestic Manufacturers
----------------------------------------------------------------------------------------------------------------
                                                                                                Estimated annual
                        Manufacturers                            Founded     Employees \703\    Production \704\
----------------------------------------------------------------------------------------------------------------
BXR Motors...................................................         2007               < 20              < 100
Canoo (HDPUV)................................................         2018                812                  0
Falcon Motorsports...........................................         2009               < 10              < 100
Faraday Future (HDPUV).......................................         2014                600                  0
Fisker (HDPUV)...............................................         2016                455              < 500
Lordstown (HDPUV)............................................         2018                260              < 100
Lucra Cars...................................................         2005               < 10              < 100
Lyons Motor Car..............................................         2012                 12              < 100
Panoz........................................................         1988               < 50              < 100
Rezvani Motors...............................................         2014                 10              < 100
Rossion Automotive...........................................         2007               < 20              < 100
Saleen.......................................................         1984                 81              < 100
Shelby American..............................................         1962              < 200              < 100
Workhorse Group (HDPUV)......................................         2007                331              < 100
----------------------------------------------------------------------------------------------------------------

    NHTSA believes that the proposed rulemaking would not have a 
significant economic impact on small vehicle manufacturers, because 
under 49 CFR part 525 passenger car manufacturers building less than 
10,000 vehicles per year can petition NHTSA to have alternative 
standards determined for them. Listed manufacturers producing ICE 
vehicles do not currently meet the standard and must already petition 
NHTSA for relief. If the standard is raised, it has no meaningful 
impact on these manufacturers--they still must go through the same 
process and petition for relief. Given there already is a mechanism for 
relieving burden on small businesses, a regulatory flexibility analysis 
was not prepared.
---------------------------------------------------------------------------

    \703\ Estimated number of employees as of December 2022, source: 
linkedin.com, zoominfo.com, rocketreach.co, and datanyze.com.
    \704\ Rough estimate of LDV production for MY 2022.
---------------------------------------------------------------------------

    All HDPUV manufacturers listed in Table VII-1 build BEVs which far 
exceed the fuel economy standards. NHTSA has researched the HDPUV 
manufacturing industry and found no small manufacturers of ICE vehicles 
that would be impacted by the proposed rulemaking. NHTSA welcomes 
comment on any information regarding small business HDPUV manufacturers 
that have may been omitted.
    Further, small manufacturers of EVs would not face a significant 
economic impact. The method for earning credits applies equally across 
manufacturers and does not place small entities at a significant 
competitive disadvantage. In any event, even if the rulemaking had a 
``significant economic impact'' on these small EV manufacturers, the 
number of these companies is not ``a substantial number.'' \705\ For 
these reasons, their existence does not alter NHTSA's analysis of the 
applicability of the Regulatory Flexibility Act.
---------------------------------------------------------------------------

    \705\ 5 U.S.C. 605.
---------------------------------------------------------------------------

F. Executive Order 13132 (Federalism)

    E.O. 13132 requires Federal agencies to develop an accountable 
process to ensure ``meaningful and timely input by State and local 
officials in the development of regulatory policies that have 
federalism implications.'' The order defines the term ``[p]olicies that 
have federalism implications'' to include regulations that have 
``substantial direct effects on the States, on the relationship between 
the national government and the States, or on the distribution of power 
and responsibilities among the various levels of government.'' Under 
the order, agencies may not issue a regulation that has federalism 
implications, that imposes substantial direct compliance costs, unless 
the Federal Government provides the funds necessary to pay the direct 
compliance costs incurred by the State and local governments, or the 
agencies consult with State and local officials early in the process of 
developing the proposed regulation.
    Similar to the CAFE preemption final rule,\706\ NHTSA does not 
believe that this proposal implicates E.O. 13132, because it neither 
imposes substantial direct compliance costs on State, local, or Tribal 
governments, nor does it preempt State law. Thus, this proposal does 
not implicate the consultation procedures that E.O. 13132 imposes on 
agency regulations that would either preempt State law or impose 
substantial direct compliance costs on State, local, or Tribal 
governments, because the only entities subject to this proposal are 
vehicle manufacturers. Nevertheless, NHTSA has complied with the 
Order's requirements and consulted directly with the CARB in developing 
a number of elements of this proposal.
---------------------------------------------------------------------------

    \706\ See 86 FR 74236, 74365 (Dec. 29, 2021).
---------------------------------------------------------------------------

G. Executive Order 12988 (Civil Justice Reform)

    Pursuant to E.O. 12988, ``Civil Justice Reform'' (61 FR 4729, Feb. 
7, 1996), NHTSA has considered whether this proposal would have any 
retroactive effect. This proposal does not have any retroactive effect.

H. Executive Order 13175 (Consultation and Coordination With Indian 
Tribal Governments)

    This proposal does not have tribal implications, as specified in 
E.O. 13175 (65 FR 67249, Nov. 9, 2000). This proposal would be 
implemented at the Federal level and would impose compliance costs only 
on vehicle manufacturers. Thus, E.O. 13175, which requires consultation 
with Tribal officials when agencies are developing policies that have 
``substantial direct effects'' on Tribes and Tribal interests, does not 
apply to this proposal.

I. Unfunded Mandates Reform Act

    Section 202 of the Unfunded Mandates Reform Act of 1995 (UMRA) 
requires Federal agencies to prepare a written assessment of the costs, 
benefits, and other effects of a proposed or final rule that includes a 
Federal mandate likely to result in the expenditure by State, local, or 
Tribal governments, in the aggregate, or by the private sector, of more 
than $100 million in any one year (adjusted for inflation with base 
year of 1995). Adjusting this amount by the implicit gross domestic 
product price deflator for 2021 results in $166 million (118.895/71.823 
= 1.66).\707\ Before

[[Page 56382]]

promulgating a rule for which a written statement is needed, section 
205 of UMRA generally requires NHTSA to identify and consider a 
reasonable number of regulatory alternatives and adopt the least 
costly, most cost-effective, or least burdensome alternative that 
achieves the objective of the rule. The provisions of section 205 do 
not apply when they are inconsistent with applicable law. Moreover, 
section 205 allows NHTSA to adopt an alternative other than the least 
costly, most cost-effective, or least burdensome alternative if NHTSA 
publishes with the rule an explanation of why that alternative was not 
adopted.
---------------------------------------------------------------------------

    \707\ BEA. 2023. National Income and Product Accounts, Table 
1.1.9: Implicit Price Deflators for Gross Domestic Product. 
Available at: https://apps.bea.gov/iTable/?reqid=19&step=2&isuri=1&categories=survey. (Accessed: May 31, 
2023).
---------------------------------------------------------------------------

    This rulemaking will not result in the expenditure by State, local, 
or Tribal governments, in the aggregate, of more than $166 million 
annually, but it will result in the expenditure of that magnitude by 
vehicle manufacturers and/or their suppliers. In developing this 
proposed rule, we considered a range of alternative fuel economy and 
fuel efficiency standards. As explained in detail in Section V of the 
preamble above, NHTSA tentatively concludes that our selected 
alternatives are the maximum feasible alternatives that achieve the 
objectives of this rulemaking, as required by EPCA/EISA.

J. Regulation Identifier Number

    The DOT assigns a regulation identifier number (RIN) to each 
regulatory action listed in the Unified Agenda of Federal Regulations. 
The Regulatory Information Service Center publishes the Unified Agenda 
in April and October of each year. The RIN contained in the heading at 
the beginning of this document may be used to find this action in the 
Unified Agenda.

K. National Technology Transfer and Advancement Act

    Section 12(d) of the National Technology Transfer and Advancement 
Act (NTTAA) requires NHTSA evaluate and use existing voluntary 
consensus standards in its regulatory activities unless doing so would 
be inconsistent with applicable law (e.g., the statutory provisions 
regarding NHTSA's vehicle safety authority) or otherwise 
impractical.\708\
---------------------------------------------------------------------------

    \708\ 15 U.S.C. 272.
---------------------------------------------------------------------------

    Voluntary consensus standards are technical standards developed or 
adopted by voluntary consensus standards bodies. Technical standards 
are defined by the NTTAA as ``performance-based or design-specific 
technical specification and related management systems practices.'' 
They pertain to ``products and processes, such as size, strength, or 
technical performance of a product, process or material.''
    Examples of organizations generally regarded as voluntary consensus 
standards bodies include the American Society for Testing and 
Materials, International, the SAE, and the American National Standards 
Institute (ANSI). If NHTSA does not use available and potentially 
applicable voluntary consensus standards, it is required by the Act to 
provide Congress, through OMB an explanation of reasons for not using 
such standards. There are currently no consensus standards that NHTSA 
administers relevant to these proposed CAFE standards.

L. Department of Energy Review

    In accordance with 49 U.S.C. 32902(j)(2), NHTSA submitted this 
proposal to the DOE for review. That agency did not make any comments 
that NHTSA did not address.

M. Paperwork Reduction Act

    Under the procedures established by the Paperwork Reduction Act of 
1995 (PRA) (44 U.S.C. 3501, et. seq.), Federal agencies must obtain 
approval from the OMB for each collection of information they conduct, 
sponsor, or require through regulations. A person is not required to 
respond to a collection of information by a Federal Agency unless the 
collection displays a valid OMB control number. This NPRM proposes 
changes that relate to an information collection that is subject to the 
PRA, but the changes are not expected to increase the burden associated 
with the information collection. Additional details about NHTSA's 
information collection for its Corporate Average Fuel Economy (CAFE) 
program (OMB control number 2127-0019) and how NHTSA estimated burden 
for this collection are available in the supporting statements for the 
currently approved collection.\709\
---------------------------------------------------------------------------

    \709\ Office of Information and Regulatory Affairs. 2022. 
Supporting Statements: Part A, Corporate Average Fuel Economy 
Reporting. OMB 2127-0019. Available at: https://www.reginfo.gov/public/do/PRAViewDocument?ref_nbr=202210-2127-003. (Accessed: May 
31, 2023).
---------------------------------------------------------------------------

N. Privacy Act

    In accordance with 5 U.S.C. 553(c), NHTSA is soliciting comments 
from the public to inform the rulemaking process better. These comments 
will post, without edit, to https://www.regulations.gov, as described 
in DOT's systems of records notice, DOT/ALL-14 FDMS, accessible through 
https://www.transportation.gov/individuals/privacy/privacy-act-system-records-notices. In order to facilitate comment tracking and response, 
NHTSA encourages commenters to provide their names or the names of 
their organizations; however, submission of names is completely 
optional.

IX. Regulatory Text

List of Subjects in 49 CFR Parts 531, 533, 535, and 537

    Fuel economy, Reporting and recordkeeping requirements.

    For the reasons discussed in the preamble, NHTSA proposes to amend 
49 CFR parts 531, 533, 535, and 537 as follows:

PART 531--PASSENGER AUTOMOBILE AVERAGE FUEL ECONOMY STANDARDS

0
1. The authority citation for Part 531 continues to read as follows:

    Authority:  49 U.S.C. 32902; delegation of authority at 49 CFR 
1.95.

0
2. Revise Sec.  531.1 to read as follows:


Sec.  531.1  Scope.

    This part establishes average fuel economy standards pursuant to 49 
U.S.C. 32902 for passenger automobiles.
0
3. Revise Sec.  531.4 to read as follows:


Sec.  531.4  Definitions.

    (a) Statutory terms. (1) The terms average fuel economy, 
manufacture, manufacturer, and model year are used as defined in 49 
U.S.C. 32901.
    (2) The terms automobile and passenger automobile are used as 
defined in 49 U.S.C. 32901 and in accordance with the determination in 
part 523 of this chapter.
    (b) Other terms. As used in this part, unless otherwise required by 
the context--
    (1) The term domestically manufactured passenger automobile means 
the vehicle is deemed to be manufactured domestically under 49 U.S.C. 
32904(b)(3) and 40 CFR 600.511-08.
    (2) [Reserved]
0
4. Amend Sec.  531.5 by revising paragraphs (a) through (d) to read as 
follows:

[[Page 56383]]

Sec.  531.5  Fuel economy standards.

    (a) Except as provided in paragraph (e) of this section, each 
manufacturer of passenger automobiles shall comply with the fleet 
average fuel economy standards in table 1 to this paragraph (a), 
expressed in miles per gallon, in the model year specified as 
applicable:

                        Table 1 to Paragraph (a)
------------------------------------------------------------------------
                                                           Average fuel
                                                              economy
                       Model year                            standard
                                                            (miles per
                                                              gallon)
------------------------------------------------------------------------
1978....................................................            18.0
1979....................................................            19.0
1980....................................................            20.0
1981....................................................            22.0
1982....................................................            24.0
1983....................................................            26.0
1984....................................................            27.0
1985....................................................            27.5
1986....................................................            26.0
1987....................................................            26.0
1988....................................................            26.0
1989....................................................            26.5
1990-2010...............................................            27.5
------------------------------------------------------------------------

    (b) Except as provided in paragraph (e) of this section, for model 
year 2011, a manufacturer's passenger automobile fleet shall comply 
with the fleet average fuel economy level calculated for that model 
year according to figure 1 and the appropriate values in table 2 to 
this paragraph (b).
[GRAPHIC] [TIFF OMITTED] TP17AU23.111


Where:

N is the total number (sum) of passenger automobiles produced by a 
manufacturer;
Ni is the number (sum) of the ith passenger automobile 
model produced by the manufacturer; and
Ti is the fuel economy target of the ith model passenger 
automobile, which is determined according to the following formula, 
rounded to the nearest hundredth:
[GRAPHIC] [TIFF OMITTED] TP17AU23.114

Where:

Parameters a, b, c, and d are defined in table 2 to this paragraph 
(b);
e = 2.718; and
x = footprint (in square feet, rounded to the nearest tenth) of the 
vehicle model.

             Table 2 to Paragraph (b)--Parameters for the Passenger Automobile Fuel Economy Targets
----------------------------------------------------------------------------------------------------------------
                                                                      Parameters
             Model year              ---------------------------------------------------------------------------
                                           a (mpg)            b (mpg)        c (gal/mi/ft\2\)      d (gal/mi)
----------------------------------------------------------------------------------------------------------------
2011................................              31.20              24.00              51.41               1.91
----------------------------------------------------------------------------------------------------------------

    (c) Except as provided in paragraph (e) of this section, for model 
years 2012-2032, a manufacturer's passenger automobile fleet shall 
comply with the fleet average fuel economy level calculated for that 
model year according to this figure 2 and the appropriate values in 
this table 3 to this paragraph (c).

Figure 2 to paragraph (c)
[GRAPHIC] [TIFF OMITTED] TP17AU23.112

Where:

CAFErequired is the fleet average fuel economy standard for a given 
fleet (domestic passenger automobiles or import passenger 
automobiles);
Subscript i is a designation of multiple groups of automobiles, 
where each group's designation, i.e., i = 1, 2, 3, etc., represents 
automobiles that share a unique model type and footprint within the 
applicable fleet, either domestic passenger automobiles or import 
passenger automobiles;
Productioni is the number of passenger automobiles produced for sale 
in the United States within each ith designation, i.e., which share 
the same model type and footprint;

[[Page 56384]]

TARGETi is the fuel economy target in miles per gallon (mpg) 
applicable to the footprint of passenger automobiles within each ith 
designation, i.e., which share the same model type and footprint, 
calculated according to Figure 3 and rounded to the nearest 
hundredth of a mpg, i.e., 35.455 = 35.46 mpg, and the summations in 
the numerator and denominator are both performed over all models in 
the fleet in question.

Figure 3 to Paragraph (c)
[GRAPHIC] [TIFF OMITTED] TP17AU23.113

Where:

TARGET is the fuel economy target (in mpg) applicable to vehicles of 
a given footprint (FOOTPRINT, in square feet);
Parameters a, b, c, and d are defined in table 3 to this paragraph 
(c); and
The MIN and MAX functions take the minimum and maximum, 
respectively, of the included values.

             Table 3 to Paragraph (c)--Parameters for the Passenger Automobile Fuel Economy Targets
                                                 [MYs 2012-2032]
----------------------------------------------------------------------------------------------------------------
                                                                            Parameters
                                                 ---------------------------------------------------------------
                   Model year                                                       c (gal/mi/
                                                      a (mpg)         b (mpg)         ft\2\)        d (gal/mi)
----------------------------------------------------------------------------------------------------------------
2012............................................           35.95           27.95       0.0005308        0.006057
2013............................................           36.80           28.46       0.0005308        0.005410
2014............................................           37.75           29.03       0.0005308        0.004725
2015............................................           39.24           29.90       0.0005308        0.003719
2016............................................           41.09           30.96       0.0005308        0.002573
2017............................................           43.61           32.65       0.0005131        0.001896
2018............................................           45.21           33.84       0.0004954        0.001811
2019............................................           46.87           35.07       0.0004783        0.001729
2020............................................           48.74           36.47       0.0004603        0.001643
2021............................................           49.48           37.02        0.000453         0.00162
2022............................................           50.24           37.59        0.000447         0.00159
2023............................................           51.00           38.16        0.000440         0.00157
2024............................................           55.44           41.48        0.000405         0.00144
2025............................................           60.26           45.08        0.000372         0.00133
2026............................................           66.95           50.09        0.000335         0.00120
2027............................................           68.32           51.12         0.00033         0.00117
2028............................................           69.71           52.16         0.00032         0.00115
2029............................................           71.14           53.22         0.00032         0.00113
2030............................................           72.59           54.31         0.00031         0.00110
2031............................................           74.07           55.42         0.00030         0.00108
2032............................................           75.58           56.55         0.00030         0.00106
----------------------------------------------------------------------------------------------------------------

    (d) In addition to the requirements of paragraphs (b) and (c) of 
this section, each manufacturer, other than manufacturers subject to 
standards in paragraph (e) of this section, shall also meet the minimum 
fleet standard for domestically manufactured passenger automobiles 
expressed in table 4 to this paragraph (d):

      Table 4 to Paragraph (d)--Minimum Fuel Economy Standards for
             Domestically Manufactured Passenger Automobiles
                             [MYs 2011-2032]
------------------------------------------------------------------------
                                                               Minimum
                         Model year                            standard
------------------------------------------------------------------------
2011.......................................................         27.8
2012.......................................................         30.7
2013.......................................................         31.4
2014.......................................................         32.1
2015.......................................................         33.3
2016.......................................................         34.7
2017.......................................................         36.7
2018.......................................................         38.0
2019.......................................................         39.4
2020.......................................................         40.9
2021.......................................................         39.9
2022.......................................................         40.6
2023.......................................................         41.1
2024.......................................................         44.3
2025.......................................................         48.1
2026.......................................................         53.5
2027.......................................................         54.1
2028.......................................................         55.3
2029.......................................................         56.4
2030.......................................................         57.5
2031.......................................................         58.7
2032.......................................................         59.9
------------------------------------------------------------------------

* * * * *
0
4. Amend Sec.  531.6 by revising paragraph (b) to read as follows:


Sec.  531.6  Measurement and calculation procedures.

* * * * *
    (b) For model years 2017 and later, a manufacturer is eligible to 
increase the fuel economy performance of passenger cars in accordance 
with procedures established by the Environmental

[[Page 56385]]

Protection Agency (EPA) set forth in 40 CFR part 600, subpart F, 
including adjustments to fuel economy for fuel consumption improvements 
related to air conditioning (AC) efficiency and off-cycle technologies. 
Manufacturers must provide reporting on these technologies as specified 
in Sec.  537.7 of this chapter by the required deadlines.
    (1) Efficient AC technologies. A manufacturer may increase its 
fleet average fuel economy performance through the use of technologies 
that improve the efficiency of AC systems pursuant to the requirements 
in 40 CFR 86.1868-12. Fuel consumption improvement values resulting 
from the use of those AC systems must be determined in accordance with 
40 CFR 600.510-12(c)(3)(i). Starting in MY 2027, fuel consumption 
improvement values may only increase the fuel economy of vehicles 
propelled by internal combustion engines (ICEs) and, therefore, will be 
calculated based only on the number of vehicles with internal 
combustion vehicles that are equipped with the technologies.
    (2) Off-cycle technologies on EPA's predefined list. A manufacturer 
may increase its fleet average fuel economy performance through the use 
of off-cycle technologies pursuant to the requirements in 40 CFR 
86.1869-12for predefined off-cycle technologies in accordance with 40 
CFR 86.1869-12(b). The fuel consumption improvement is determined in 
accordance with 40 CFR 600.510-12(c)(3)(ii). Starting in MY 2027, fuel 
consumption improvement values may only increase the fuel economy of 
vehicles propelled by ICEs and, therefore, will be calculated based 
only on the number of vehicles with internal combustion vehicles that 
are equipped with the technologies.
    (3) Off-cycle technologies using 5-cycle testing. Through MY 2027, 
a manufacturer may increase its fleet average fuel economy performance 
through the use of off-cycle technologies tested using the EPA's 5-
cycle methodology in accordance with 40 CFR 86.1869-12(c). The fuel 
consumption improvement is determined in accordance with 40 CFR 
600.510-12(c)(3)(ii).
    (4) Off-cycle technologies using the alternative EPA-approved 
methodology. Through MY 2027, a manufacturer may seek to increase its 
fuel economy performance through use of an off-cycle technology 
requiring an application request made to the EPA in accordance with 40 
CFR 86.1869-12(d).
    (i) Eligibility under the Corporate Average Fuel Economy (CAFE) 
program requires compliance with paragraphs (b)(4)(i)(A) through (C) of 
this section. Paragraphs (b)(4)(i)(A), (B) and (D) of this section 
apply starting in model year 2024. Paragraph (b)(4)(i)(E) of this 
section applies starting in MY 2025.
    (A) A manufacturer seeking to increase its fuel economy performance 
using the alternative methodology for an off-cycle technology, should 
submit a detailed analytical plan to EPA prior to the applicable model 
year. The detailed analytical plan may include information, such as 
planned test procedure and model types for demonstration. The plan will 
be approved or denied in accordance with 40 CFR 86.1869.12(d).
    (B) A manufacturer seeking to increase its CAFE program fuel 
economy performance using the alternative methodology for an off-cycle 
technology must submit an official credit application to EPA and obtain 
approval in accordance with 40 CFR 86.1869.12(e) prior to September of 
the given model year.
    (C) A manufacturer's plans, applications and requests approved by 
the EPA must be made in consultation with NHTSA. To expedite NHTSA's 
consultation with the EPA, a manufacturer must concurrently submit its 
application to NHTSA if the manufacturer is seeking off-cycle fuel 
economy improvement values under the CAFE program for those 
technologies. For off-cycle technologies that are covered under 40 CFR 
86.1869-12(d), NHTSA will consult with the EPA regarding NHTSA's 
evaluation of the specific off-cycle technology to ensure its impact on 
fuel economy and the suitability of using the off-cycle technology to 
adjust the fuel economy performance.
    (D) A manufacturer may request an extension from NHTSA for more 
time to obtain an EPA approval. Manufacturers should submit their 
requests 30 days before the deadlines in paragraphs (b)(4)(i)(A) 
through (C) of this section. Requests should be submitted to NHTSA's 
Director of the Office of Vehicle Safety Compliance at [email protected].
    (E) For MYs 2025 and 2026, a manufacturer must respond within 60-
days to any requests from EPA or NHTSA for additional information or 
clarifications to submissions provided pursuant to paragraphs 
(b)(4)(i)(A) and (B) of this section. Failure to respond within 60 days 
may result in denial of the manufacturer's request to increase its fuel 
economy performance through use of an off-cycle technology requests 
made to the EPA in accordance with 40 CFR 86.1869-12(d).
    (ii) Review and approval process. NHTSA will provide its views on 
the suitability of the technology for that purpose to the EPA. NHTSA's 
evaluation and review will consider:
    (A) Whether the technology has a direct impact upon improving fuel 
economy performance;
    (B) Whether the technology is related to crash-avoidance 
technologies, safety critical systems or systems affecting safety-
critical functions, or technologies designed for the purpose of 
reducing the frequency of vehicle crashes;
    (C) Information from any assessments conducted by the EPA related 
to the application, the technology and/or related technologies; and
    (D) Any other relevant factors.
    (iii) Safety. (A) Technologies found to be defective or non-
compliant, subject to recall pursuant to part 573 of this chapter, 
Defect and Noncompliance Responsibility and Reports, due to a risk to 
motor vehicle safety, will have the values of approved off-cycle 
credits removed from the manufacturer's credit balance or adjusted to 
the population of vehicles the manufacturer remedies as required by 49 
U.S.C. chapter 301. NHTSA will consult with the manufacturer to 
determine the amount of the adjustment.
    (B) Approval granted for innovative and off-cycle technology 
credits under NHTSA's fuel efficiency program does not affect or 
relieve the obligation to comply with the Vehicle Safety Act (49 U.S.C. 
chapter 301), including the ``make inoperative'' prohibition (49 U.S.C. 
30122), and all applicable Federal motor vehicle safety standards 
(FMVSSs) issued thereunder (part 571 of this chapter). In order to 
generate off-cycle or innovative technology credits manufacturers must 
state--
    (1) That each vehicle equipped with the technology for which they 
are seeking credits will comply with all applicable FMVSS(s); and
    (2) Whether or not the technology has a fail-safe provision. If no 
fail-safe provision exists, the manufacturer must explain why not and 
whether a failure of the innovative technology would affect the safety 
of the vehicle.

PART 533--LIGHT TRUCK FUEL ECONOMY STANDARDS

0
5. The authority citation for part 533 continues to read as follows:

    Authority:  49 U.S.C. 32902; delegation of authority at 49 CFR 
1.95.

0
6. Revise Sec.  533.1 to read as follows:


Sec.  533.1  Scope.

    This part establishes average fuel economy standards pursuant to 49 
U.S.C. 32902 for light trucks.
0
7. Revise Sec.  533.4 to read as follows:

[[Page 56386]]

Sec.  533.4  Definitions.

    (a) Statutory terms. (1) The terms average fuel economy, average 
fuel economy standard, fuel economy, import, manufacture, manufacturer, 
and model year are used as defined in 49 U.S.C. 32901.
    (2) The term automobile is used as defined in 49 U.S.C. 32901 and 
in accordance with the determinations in part 523 of this chapter.
    (b) Other terms. As used in this part, unless otherwise required by 
the context--
    (1) Light truck is used in accordance with the determinations in 
part 523 of this chapter.
    (2) Captive import means with respect to a light truck, one which 
is not domestically manufactured, as defined in section 502(b)(2)(E) of 
the Motor Vehicle Information and Cost Savings Act, but which is 
imported in the 1980 model year or thereafter by a manufacturer whose 
principal place of business is in the United States.
    (3) 4-wheel drive, general utility vehicle means a 4-wheel drive, 
general purpose automobile capable of off-highway operation that has a 
wheelbase of not more than 280 centimeters, and that has a body shape 
similar to 1977 Jeep CJ-5 or CJ-7, or the 1977 Toyota Land Cruiser.
    (4) Basic engine means a unique combination of manufacturer, engine 
displacement, number of cylinders, fuel system (as distinguished by 
number of carburetor barrels or use of fuel injection), and catalyst 
usage.
    (5) Limited product line light truck means a light truck 
manufactured by a manufacturer whose light truck fleet is powered 
exclusively by basic engines which are not also used in passenger 
automobiles.
0
8. Amend Sec.  533.5 by revising table 7 to paragraph (a) and paragraph 
(j) to read as follows:


Sec.  533.5  Requirements.

    (a) * * *

                                  Table 7 to Paragraph (a)--Parameters for the Light Truck Fuel Economy Targets for MYs
                                                                       [2017-2032]
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                                        Parameters
                                                                 ---------------------------------------------------------------------------------------
                           Model year                                                c (gal/mi/                                  g (gal/mi/
                                                                  a (mpg)  b (mpg)     ft\2\)     d (gal/mi)  e (mpg)  f (mpg)     ft\2\)     h (gal/mi)
--------------------------------------------------------------------------------------------------------------------------------------------------------
2017............................................................    36.26    25.09    0.0005484     0.005097    35.10    25.09    0.0004546     0.009851
2018............................................................    37.36    25.20    0.0005358     0.004797    35.31    25.20    0.0004546     0.009682
2019............................................................    38.16    25.25    0.0005265     0.004623    35.41    25.25    0.0004546     0.009603
2020............................................................    39.11    25.25    0.0005140     0.004494    35.41    25.25    0.0004546     0.009603
2021............................................................    39.71    25.63     0.000506      0.00443       NA       NA           NA           NA
2022............................................................    40.31    26.02     0.000499      0.00436       NA       NA           NA           NA
2023............................................................    40.93    26.42     0.000491      0.00429       NA       NA           NA           NA
2024............................................................    44.48    26.74     0.000452      0.00395       NA       NA           NA           NA
2025............................................................    48.35    29.07     0.000416      0.00364       NA       NA           NA           NA
2026............................................................    53.73    32.30     0.000374      0.00327       NA       NA           NA           NA
2027............................................................    55.96    33.64      0.00036      0.00314       NA       NA           NA           NA
2028............................................................    58.30    35.05      0.00034      0.00302       NA       NA           NA           NA
2029............................................................    60.73    36.51      0.00033      0.00289       NA       NA           NA           NA
2030............................................................    63.26    38.03      0.00032      0.00278       NA       NA           NA           NA
2031............................................................    65.89    39.61      0.00031      0.00267       NA       NA           NA           NA
2032............................................................    68.64    41.26      0.00029      0.00256       NA       NA           NA           NA
--------------------------------------------------------------------------------------------------------------------------------------------------------

* * * * *
    (j) For model years 2017-2032, a manufacturer's light truck fleet 
shall comply with the fleet average fuel economy standard calculated 
for that model year according to figures 2 and 4 to paragraph (a) of 
this section and the appropriate values in table 7 to paragraph (a) of 
this section.
0
9. Amend Sec.  533.6 by:
0
a. Revising paragraphs (c) introductory text, (c)(1) and (3);
0
b. Redesignating paragraph (c)(4) as (c)(5);
0
c. Adding a new paragraph (c)(4); and
0
d. Revising newly redesignated paragraph (c)(5).
    The revisions and addition read as follows:


Sec.  533.6  Measurement and calculation procedures.

* * * * *
    (c) For model years 2017 and later, a manufacturer is eligible to 
increase the fuel economy performance of light trucks in accordance 
with procedures established by the Environmental Protection Agency 
(EPA) set forth in 40 CFR part 600, subpart F, including adjustments to 
fuel economy for fuel consumption improvements related to air 
conditioning (AC) efficiency, off-cycle technologies, and hybridization 
and other performance-based technologies for full-size pickup trucks 
that meet the requirements specified in 40 CFR 86.1803. Manufacturers 
must provide reporting on these technologies as specified in Sec.  
537.7 of this chapter by the required deadlines.
    (1) Efficient AC technologies. A manufacturer may seek to increase 
its fleet average fuel economy performance through the use of 
technologies that improve the efficiency of AC systems pursuant to the 
requirements in 40 CFR 86.1868-12. Fuel consumption improvement values 
resulting from the use of those AC systems must be determined in 
accordance with 40 CFR 600.510-12(c)(3)(i). Starting in MY 2027, fuel 
consumption improvement values may only increase the fuel economy of 
vehicles propelled by internal combustion engines (ICEs) and, 
therefore, will be calculated based only on the number of vehicles with 
internal combustion vehicles that are equipped with the technologies.
* * * * *
    (3) Off-cycle technologies on EPA's predefined list. A manufacturer 
may seek to increase its fleet average fuel economy performance through 
the use of off-cycle technologies pursuant to the requirements in 40 
CFR 86.1869-12 for predefined off-cycle technologies in accordance with 
40 CFR 86.1869-12(b). The fuel consumption improvement is determined in 
accordance with 40 CFR 600.510-12(c)(3)(ii). Starting in MY 2027, fuel 
consumption improvement values may only increase the fuel economy of 
vehicles propelled by ICEs and, therefore, will be calculated based

[[Page 56387]]

only on the number of vehicles with internal combustion vehicles that 
are equipped with the technologies.
    (4) Off-cycle technologies using 5-cycle testing. Through MY 2027, 
a manufacturer may increase its fleet average fuel economy performance 
through the use of off-cycle technologies tested using the EPA's 5-
cycle methodology in accordance with 40 CFR 86.1869-12(c). The fuel 
consumption improvement is determined in accordance with 40 CFR 
600.510-12(c)(3)(ii).
    (5) Off-cycle Technologies using the alternative EPA-approved 
methodology. Through MY 2027, a manufacturer may seek to increase its 
fuel economy performance through use of an off-cycle technology 
requiring an application request made to the EPA in accordance with 40 
CFR 86.1869-12(d).
    (i) Eligibility under the Corporate Average Fuel Economy (CAFE) 
program requires compliance with paragraphs (c)(5)(i)(A) through (C) of 
this section. Paragraphs (c)(5)(i)(A), (B) and (D) of this section 
apply starting in model year 2024. Paragraph (b)(5)(i)(E) of this 
section applies starting in MY 2025.
    (A) A manufacturer seeking to increase its fuel economy performance 
using the alternative methodology for an off-cycle technology, should 
submit a detailed analytical plan to EPA prior to the applicable model 
year. The detailed analytical plan may include information such as, 
planned test procedure and model types for demonstration. The plan will 
be approved or denied in accordance with 40 CFR 86.1869.12(d).
    (B) A manufacturer seeking to increase its fuel economy performance 
using the alternative methodology for an off-cycle technology must 
submit an official credit application to EPA and obtain approval in 
accordance with 40 CFR 86.1869.12(e) prior to September of the given 
model year.
    (C) A manufacturer's plans, applications and requests approved by 
the EPA must be made in consultation with NHTSA. To expedite NHTSA's 
consultation with the EPA, a manufacturer must concurrently submit its 
application to NHTSA if the manufacturer is seeking off-cycle fuel 
economy improvement values under the CAFE program for those 
technologies. For off-cycle technologies that are covered under 40 CFR 
86.1869-12(d), NHTSA will consult with the EPA regarding NHTSA's 
evaluation of the specific off-cycle technology to ensure its impact on 
fuel economy and the suitability of using the off-cycle technology to 
adjust the fuel economy performance.
    (D) A manufacturer may request an extension from NHTSA for more 
time to obtain an EPA approval. Manufacturers should submit their 
requests 30 days before the deadlines above. Requests should be 
submitted to NHTSA's Director of the Office of Vehicle Safety 
Compliance at [email protected].
    (E) For MYs 2025 and 2026, a manufacturer must respond within 60-
days to any requests from EPA or NHTSA for additional information or 
clarifications to submissions provided pursuant to paragraphs 
(b)(4)(i)(A) and (B) of this section. Failure to respond within 60 days 
may result in denial of the manufacturer's request to increase its fuel 
economy performance through use of an off-cycle technology requests 
made to the EPA in accordance with 40 CFR 86.1869-12(d).
    (ii) Review and approval process. NHTSA will provide its views on 
the suitability of the technology for that purpose to the EPA. NHTSA's 
evaluation and review will consider:
    (A) Whether the technology has a direct impact upon improving fuel 
economy performance;
    (B) Whether the technology is related to crash-avoidance 
technologies, safety critical systems or systems affecting safety-
critical functions, or technologies designed for the purpose of 
reducing the frequency of vehicle crashes;
    (C) Information from any assessments conducted by the EPA related 
to the application, the technology and/or related technologies; and
    (D) Any other relevant factors.
    (E) NHTSA will collaborate to host annual meetings with EPA at 
least once by July 30th before the model year begins to provide general 
guidance to the industry on past off-cycle approvals.
    (iii) Safety. (A) Technologies found to be defective or non-
compliant, subject to recall pursuant to part 573 of this chapter, 
Defect and Noncompliance Responsibility and Reports, due to a risk to 
motor vehicle safety, will have the values of approved off-cycle 
credits removed from the manufacturer's credit balance or adjusted to 
the population of vehicles the manufacturer remedies as required by 49 
U.S.C. chapter 301. NHTSA will consult with the manufacturer to 
determine the amount of the adjustment.
    (B) Approval granted for innovative and off-cycle technology 
credits under NHTSA's fuel efficiency program does not affect or 
relieve the obligation to comply with the Vehicle Safety Act (49 U.S.C. 
chapter 301), including the ``make inoperative'' prohibition (49 U.S.C. 
30122), and all applicable Federal motor vehicle safety standards 
issued thereunder (FMVSSs) (part 571 of this chapter). In order to 
generate off-cycle or innovative technology credits manufacturers must 
state--
    (1) That each vehicle equipped with the technology for which they 
are seeking credits will comply with all applicable FMVSS(s); and
    (2) Whether or not the technology has a fail-safe provision. If no 
fail-safe provision exists, the manufacturer must explain why not and 
whether a failure of the innovative technology would affect the safety 
of the vehicle.

PART 535--MEDIUM- AND HEAVY-DUTY VEHICLE FUEL EFFICIENCY PROGRAM

0
10. The authority citation for part 535 continues to read as follows:

    Authority:  49 U.S.C. 32902 and 30101; delegation of authority 
at 49 CFR 1.95.

0
11. Amend Sec.  535.4 by revising the introductory text, removing the 
definition for ``Alterers'', and adding the definition for ``Alterer'', 
in alphabetical order, to read as follows:


Sec.  535.4  Definitions.

    The terms manufacture, manufacturer, commercial medium-duty on 
highway vehicle, commercial heavy-duty on highway vehicle, fuel, and 
work truck are used as defined in 49 U.S.C. 32901. See 49 CFR 523.2 for 
general definitions related to NHTSA's fuel efficiency programs.
* * * * *
    Alterer means a manufacturer that modifies an altered vehicle as 
defined in 49 CFR 567.3
* * * * *
0
12. Amend Sec.  535.5 by revising paragraphs (a) introductory text, 
(a)(1), (2) and (9) to read as follows:


Sec.  535.5  Standards.

    (a) Heavy-duty pickup trucks and vans. Each manufacturer's fleet of 
heavy-duty pickup trucks and vans (HDPUVs) shall comply with the fuel 
consumption standards in this paragraph (a) expressed in gallons per 
100 miles. Each vehicle must be manufactured to comply for its full 
useful life. For the Phase 1 program, if the manufacturer's fleet 
includes conventional vehicles (gasoline, diesel and alternative fueled 
vehicles) and advanced technology vehicles (hybrids with powertrain 
designs that include energy storage systems, vehicles with waste heat 
recovery, EVs and fuel cell vehicles), it may divide its fleet into two 
separate fleets each with its own separate fleet average fuel 
consumption standard which the manufacturer must comply with the 
requirements of this paragraph (a). For Phase 2 and later,

[[Page 56388]]

manufacturers may calculate their fleet average fuel consumption 
standard for a conventional fleet and multiple advanced technology 
vehicle fleets. Advanced technology vehicle fleets should be separated 
into plug-in hybrid electric vehicles, electric vehicles and fuel cell 
vehicles. NHTSA standards correspond to the same requirements for the 
Environmental Protection Agency (EPA) as specified in 40 CFR 86.1819-
14.
    (1) Mandatory standards. For model years 2016 and later, each 
manufacturer must comply with the fleet average standard derived from 
the unique subconfiguration target standards (or groups of 
subconfigurations approved by EPA in accordance with 40 CFR 86.1819) of 
the model types that make up the manufacturer's fleet in a given model 
year. Each subconfiguration has a unique attribute-based target 
standard, defined by each group of vehicles having the same payload, 
towing capacity and whether the vehicles are equipped with a 2-wheel or 
4-wheel drive configuration. Phase 1 target standards apply for model 
years 2016 through 2020. Phase 2 target standards apply for model year 
2021 through 2029. NHTSA's Phase 3 HDPUVs apply for model year 2030 and 
later.
    (2) Subconfiguration target standards. (i) Two alternatives exist 
for determining the subconfiguration target standards for Phase 1. For 
each alternative, separate standards exist for compression-ignition and 
spark-ignition vehicles:
    (A) The first alternative allows manufacturers to determine a fixed 
fuel consumption standard that is constant over the model years; and
    (B) The second alternative allows manufacturers to determine 
standards that are phased-in gradually each year.
    (ii) Calculate the subconfiguration target standards as specified 
in this paragraph (a)(2)(ii), using the appropriate coefficients from 
table 1 to paragraph (a)(2)(ii), choosing between the alternatives in 
paragraph (a)(2)(i) of this section. For electric or fuel cell heavy-
duty vehicles, use compression-ignition vehicle coefficients ``c'' and 
``d'' and for hybrid (including plug-in hybrid), dedicated and dual-
fueled vehicles, use coefficients ``c'' and ``d'' appropriate for the 
engine type used. Round each standard to the nearest 0.001 gallons per 
100 miles and specify all weights in pounds rounded to the nearest 
pound. Calculate the subconfiguration target standards using the 
following equation:

Subconfiguration Target Standard (gallons per 100 miles) = [c x (WF)] + 
d

Where:

WF = Work Factor = [0.75 x (Payload Capacity + Xwd)] + [0.25 x 
Towing Capacity]
Xwd = 4wd Adjustment = 500 lbs. if the vehicle group is equipped 
with 4wd and all-wheel drive, otherwise equals 0 lbs. for 2wd.
Payload Capacity = GVWR (lbs.)--Curb Weight (lbs.) (for each vehicle 
group) Towing Capacity = GCWR (lbs.)--GVWR (lbs.) (for each vehicle 
group)

       Table 1 to Paragraph (a)(2)(ii)--Coefficients for Mandatory
                    Subconfiguration Target Standards
------------------------------------------------------------------------
 
------------------------------------------------------------------------
              Phase 1 Alternative 1--Fixed Target Standards
------------------------------------------------------------------------
Compression Ignition (CI) Vehicle Coefficients
------------------------------------------------------------------------
Model Year(s)                                                 c        d
------------------------------------------------------------------------
    2016 to 2018...................................   0.0004322    3.330
    2019 to 2020...................................   0.0004086    3.143
SI Vehicle Coefficients
    2016 to 2017...................................   0.0005131    3.961
    2018 to 2020...................................   0.0004086    3.143
------------------------------------------------------------------------
            Phase 1 Alternative 2--Phased-in Target Standards
------------------------------------------------------------------------
CI Vehicle Coefficients
    2016...........................................   0.0004519    3.477
    2017...........................................   0.0004371    3.369
    2018 to 2020...................................   0.0004086    3.143
SI Vehicle Coefficients
    2016...........................................   0.0005277    4.073
    2017...........................................   0.0005176    3.983
    2018 to 2020...................................   0.0004951    3.815
------------------------------------------------------------------------
                     Phase 2--Fixed Target Standards
------------------------------------------------------------------------
CI Vehicle Coefficients
    2021...........................................   0.0003988    3.065
    2022...........................................   0.0003880    2.986
    2023...........................................   0.0003792    2.917
    2024...........................................   0.0003694    2.839
    2025...........................................   0.0003605    2.770
    2026...........................................   0.0003507    2.701
    2027 to 2029...................................   0.0003418    2.633
    2030...........................................   0.0003076    2.370
    2031...........................................   0.0002769    2.133
    2032...........................................   0.0002492    1.919
    2033...........................................   0.0002243    1.728
    2034...........................................   0.0002018    1.555
    2035...........................................   0.0001816    1.399
SI Vehicle Coefficients
    2021...........................................   0.0004827    3.725
    2022...........................................   0.0004703    3.623
    2023...........................................   0.0004591    3.533
    2024...........................................   0.0004478    3.443
    2025...........................................   0.0004366    3.364
    2026...........................................   0.0004253    3.274
    2027 to 2029...................................   0.0004152    3.196
    2030...........................................   0.0003737    2.876
    2031...........................................   0.0003363    2.589
    2032...........................................   0.0003027    2.330
    2033...........................................   0.0002724    2.097
    2034...........................................   0.0002452    1.887
    2035...........................................   0.0002207    1.698
------------------------------------------------------------------------

* * * * *
    (9) Advanced, innovative and off-cycle technologies. For vehicles 
subject to Phase 1 standards, manufacturers may generate separate 
credit allowances for advanced and innovative technologies as specified 
in Sec.  535.7(f)(1) and (2). For vehicles subject to Phase 2 
standards, manufacturers may generate separate credits allowance for 
off-cycle technologies in accordance with Sec.  535.7(f)(2). Separate 
credit allowances for advanced technology vehicles cannot be generated; 
instead, manufacturers may use the credit m specified in Sec.  
535.7(f)(1)(ii) through model year 2026.
* * * * *
0
13. Amend Sec.  535.6 by revising paragraph (a)(1) to read as follows:


Sec.  535.6  Measurement and calculation procedures.

* * * * *
    (a) * * *
    (1) For the Phase 1 program, if the manufacturer's fleet includes 
conventional vehicles (gasoline, diesel and alternative fueled 
vehicles) and advanced technology vehicles (hybrids with powertrain 
designs that include energy storage systems, vehicles with waste heat 
recovery, electric vehicles and fuel cell vehicles), it may divide its 
fleet into two separate fleets each with its own separate fleet average 
fuel consumption performance rate. For Phase 2 and later, manufacturers 
may calculate their fleet average fuel consumption rates for a 
conventional fleet and separate advanced technology vehicle fleets. 
Advanced technology vehicle fleets should be separated into plug-in 
hybrid electric vehicles, electric vehicles and fuel cell vehicles.
* * * * *
0
14. Amend Sec.  535.7 by revising paragraphs (a)(1)(iii) and (iv), 
(a)(2)(iii), (a)(4)(i) and (ii), (b)(2), (f)(1)(ii), (f)(2) 
introductory text, (f)(2)(ii), and (f)(2)(vi)(B) to read as follows:


Sec.  535.7  Averaging, banking, and trading (ABT) credit program.

    (a) * * *
    (1) * * *
    (iii) Advanced technology credits. Credits generated by vehicle or 
engine families or subconfigurations containing vehicles with advanced 
technologies (i.e., hybrids with regenerative braking, vehicles 
equipped with Rankine-cycle engines, electric and fuel cell vehicles).
    (iv) Innovative and off-cycle technology credits. Credits can be 
generated by vehicle or engine families or subconfigurations having 
fuel consumption reductions resulting from technologies not reflected 
in the GEM

[[Page 56389]]

simulation tool or in the Federal Test Procedure (FTP) chassis 
dynamometer and that were not in common use with heavy-duty vehicles or 
engines before model year 2010 that are not reflected in the specified 
test procedure. Manufacturers should prove that these technologies were 
not in common use in heavy-duty vehicles or engines before model year 
2010 by demonstrating factors such as the penetration rates of the 
technology in the market. NHTSA will not approve any request if it 
determines that these technologies do not qualify. The approach for 
determining innovative and off-cycle technology credits under this fuel 
consumption program is described in paragraph (f)(2) of this section 
and by the Environmental Protection Agency (EPA) under 40 CFR 86.1819-
14(d)(13), 1036.610, and 1037.610. Starting in model year 2030, 
manufacturers certifying vehicles under Sec.  535.5(a) may not earn 
off-cycle technology credits under 40 CFR 86.1819-14(d)(13).
    (2) * * *
    (iii) Positive credits, other than advanced technology credits in 
Phase 1, generated and calculated within an averaging set may only be 
used to offset negative credits within the same averaging set.
* * * * *
    (4) * * *
    (i) Manufacturers may only trade banked credits to other 
manufacturers to use for compliance with fuel consumption standards. 
Traded FCCs, other than advanced technology credits earned in Phase 1, 
may be used only within the averaging set in which they were generated. 
Manufacturers may only trade credits to other entities for the purpose 
of expiring credits.
    (ii) Advanced technology credits earned in Phase 1 can be traded 
across different averaging sets.
* * * * *
    (b) * * *
    (2) Adjust the fuel consumption performance of subconfigurations 
with advanced technology for determining the fleet average actual fuel 
consumption value as specified in paragraph (f)(1) of this section and 
40 CFR 86.1819-14(d)(6)(iii). Advanced technology vehicles can be 
separated in a different fleet for the purpose of applying credit 
incentives as described in paragraph (f)(1) of this section.
* * * * *
    (f) * * *
    (1) * * *
    (ii) There are no separate credit allowances for advanced 
technology vehicles in the Phase 2 program. Instead, vehicle families 
containing plug-in battery electric hybrids, all-electric, and fuel 
cell vehicles certifying to Phase 2 standards may multiply credits by a 
multiplier of:
    (A) 3.5 times for plug-in hybrid electric vehicles;
    (B) 4.5 times for all-electric vehicles; and
    (C) 5.5 times for fuel cell vehicles.
* * * * *
    (2) Innovative and off-cycle technology credits. This provision 
allows fuel saving innovative and off-cycle engine and vehicle 
technologies to generate fuel consumption credits (FCCs) comparable to 
CO2 emission credits consistent with the provisions of 40 
CFR 86.1819-14(d)(13) (for heavy-duty pickup trucks and vans), 40 CFR 
1036.610 (for engines), and 40 CFR 1037.610 (for vocational vehicles 
and tractors) through MY 2029.
* * * * *
    (ii) For model years 2021 through 2029, manufacturers may generate 
off-cycle technology credits for introducing technologies that are not 
reflected in the EPA specified test procedures. Upon identification and 
joint approval with EPA, NHTSA will allow equivalent FCCs into its 
program to those allowed by EPA for manufacturers seeking to obtain 
innovative technology credits in a given model year. Such credits must 
remain within the same regulatory subcategory in which the credits were 
generated. NHTSA will adopt FCCs depending upon whether--
    (A) The technology meets paragraphs (f)(2)(i)(A) and (B) of this 
section.
    (B) For heavy-duty pickup trucks and vans, manufacturers using the 
5-cycle test to quantify the benefit of a technology are not required 
to obtain approval from the agencies to generate results.
* * * * *
    (vi) * * *
    (B) For model years 2021 through 2029, manufacturers may not rely 
on an approval for model years before 2021. Manufacturers must 
separately request the agencies' approval before applying an 
improvement factor or credit under this section for 2021 through 2029 
engines and vehicle, even if the agencies approve the improvement 
factor or credit for similar engine and vehicle models before model 
year 2021.
* * * * *

PART 537--AUTOMOTIVE FUEL ECONOMY REPORTS

0
15. The authority citation for part 537 continues to read as follows:

    Authority:  49 U.S.C. 32907; delegation of authority at 49 CFR 
1.95.

0
16. Revise Sec.  537.2 to read as follows:


Sec.  537.2  Purpose.

    The purpose of this part is to obtain information to aid the 
National Highway Traffic Safety Administration in evaluating automobile 
manufacturers' plans for complying with average fuel economy standards 
and in preparing an annual review of the average fuel economy 
standards.
0
17. Revise Sec.  537.3 to read as follows:


Sec.  537.3  Applicability.

    This part applies to automobile manufacturers, except for 
manufacturers subject to an alternate fuel economy standard under 49 
U.S.C. 32902(d).
0
18. Revise Sec.  537.4 to read as follows:


Sec.  537.4  Definitions.

    (a) Statutory terms. (1) The terms average fuel economy standard, 
fuel, manufacture, and model year are used as defined in 49 U.S.C. 
32901.
    (2) The term manufacturer is used as defined in 49 U.S.C. 32901and 
in accordance with part 529 of this chapter.
    (3) The terms average fuel economy, fuel economy, and model type 
are used as defined in subpart A of 40 CFR part 600.
    (4) The terms automobile, automobile capable of off-highway 
operation, and passenger automobile are used as defined in 49 U.S.C. 
32901 and in accordance with the determinations in part 523 of this 
chapter.
    (b) Other terms. (1) The term loaded vehicle weight is used as 
defined in subpart A of 40 CFR part 86.
    (2) The terms axle ratio, base level, body style, car line, 
combined fuel economy, engine code, equivalent test weight, gross 
vehicle weight, inertia weight, transmission class, and vehicle 
configuration are used as defined in subpart A of 40 CFR part 600.
    (3) The term light truck is used as defined in part 523 of this 
chapter and in accordance with determinations in that part.
    (4) The terms approach angle, axle clearance, brakeover angle, 
cargo carrying volume, departure angle, passenger carrying volume, 
running clearance, and temporary living quarters are used as defined in 
part 523 of this chapter.
    (5) The term incomplete automobile manufacturer is used as defined 
in part 529 of this chapter.
    (6) As used in this part, unless otherwise required by the context:
    (i) Administrator means the Administrator of the National Highway 
Traffic Safety Administration or the Administrator's delegate.

[[Page 56390]]

    (ii) Current model year means:
    (A) In the case of a pre-model year report, the full model year 
immediately following the period during which that report is required 
by Sec.  537.5(b) to be submitted.
    (B) In the case of a mid-model year report, the model year during 
which that report is required by Sec.  537.5(b) to be submitted.
    (iii) Average means a production-weighted harmonic average.
    (iv) Total drive ratio means the ratio of an automobile's engine 
rotational speed (in revolutions per minute) to the automobile's 
forward speed (in miles per hour).
0
19. Amend Sec.  537.7 by revising paragraphs (c)(7)(i) through (iii) to 
read as follows:


Sec.  537.7  Pre-model year and mid-model year reports.

* * * * *
    (c) * * *
    (7) * * *
    (i) Provide a list of each air conditioning (AC) efficiency 
improvement technology utilized in your fleet(s) of vehicles for each 
model year for which the manufacturer qualifies for fuel consumption 
improvement values under 49 CFR 531.6 or 533.6. For each technology 
identify vehicles by make and model types that have the technology, 
which compliance category those vehicles belong to and the number of 
vehicles for each model equipped with the technology. For each 
compliance category (domestic passenger car, import passenger car, and 
light truck), report the AC fuel consumption improvement value in 
gallons/mile in accordance with the equation specified in 40 CFI00.510-
12(c)(3)(i).
    (ii) Manufacturers must provide a list of off-cycle efficiency 
improvement technologies utilized in its fleet(s) of vehicles for each 
model year that is pending or approved by the Environmental Protection 
Agency (EPA) for which the manufacturer qualifies for fuel consumption 
improvement values under 49 CFR 531.6 or 533.6. For each technology, 
manufacturers must identify vehicles by make and model types that have 
the technology, which compliance category those vehicles belong to, the 
number of vehicles for each model equipped with the technology, and the 
associated off-cycle credits (grams/mile) available for each 
technology. For each compliance category (domestic passenger car, 
import passenger car, and light truck), manufacturers must calculate 
the fleet off-cycle fuel consumption improvement value in gallons/mile 
in accordance with the equation specified in 40 CFR 600.510-
12(c)(3)(ii).
    (iii) For model years up to 2024, manufacturers must provide a list 
of full-size pickup trucks in its fleet that meet the mild and strong 
hybrid vehicle definitions. For each mild and strong hybrid type, 
manufacturers must identify vehicles by make and model types that have 
the technology, the number of vehicles produced for each model equipped 
with the technology, the total number of full-size pickup trucks 
produced with and without the technology, the calculated percentage of 
hybrid vehicles relative to the total number of vehicles produced, and 
the associated full-size pickup truck credits (grams/mile) available 
for each technology. For the light truck compliance category, 
manufacturers must calculate the fleet pickup truck fuel consumption 
improvement value in gallons/mile in accordance with the equation 
specified in 40 CFR 600.510-12(c)(3)(iii).

    Issued on July 28, 2023, in Washington, DC, under authority 
delegated in 49 CFR 1.95.
Ann Carlson,
Acting Administrator.
[FR Doc. 2023-16515 Filed 8-16-23; 8:45 am]
BILLING CODE 4910-59-P