[Federal Register Volume 86, Number 169 (Friday, September 3, 2021)]
[Proposed Rules]
[Pages 49602-49883]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2021-17496]
[[Page 49601]]
Vol. 86
Friday,
No. 169
September 3, 2021
Part II
Department of Transportation
-----------------------------------------------------------------------
National Highway Traffic Safety Administration
-----------------------------------------------------------------------
49 CFR Parts 531, 533 et al.
Corporate Average Fuel Economy Standards for Model Years 2024-2026
Passenger Cars and Light Trucks; Proposed Rule
Federal Register / Vol. 86, No. 169 / Friday, September 3, 2021 /
Proposed Rules
[[Page 49602]]
-----------------------------------------------------------------------
DEPARTMENT OF TRANSPORTATION
National Highway Traffic Safety Administration
49 CFR Parts 531, 533, 536, and 537
[NHTSA-2021-0053]
RIN 2127-AM34
Corporate Average Fuel Economy Standards for Model Years 2024-
2026 Passenger Cars and Light Trucks
AGENCY: National Highway Traffic Safety Administration (NHTSA),
Department of Transportation (DOT).
ACTION: Notice of proposed rulemaking.
-----------------------------------------------------------------------
SUMMARY: NHTSA, on behalf of the Department of Transportation, is
proposing revised fuel economy standards for passenger cars and light
trucks for model years 2024-2026. On January 20, 2021, President Biden
signed an Executive order (E.O.) entitled, ``Protecting Public Health
and the Environment and Restoring Science To Tackle the Climate
Crisis.'' In it, the President directed that ``The Safer Affordable
Fuel-Efficient (SAFE) Vehicles Rule for Model Years 2021-2026 Passenger
Cars and Light Trucks'' (hereafter, ``the 2020 final rule'') be
immediately reviewed for consistency with our Nation's abiding
commitment to empower our workers and communities; promote and protect
our public health and the environment; and conserve our national
treasures and monuments, places that secure our national memory.
President Biden further directed that the 2020 final rule be reviewed
at once and that (in this case) the Secretary of Transportation
consider ``suspending, revising, or rescinding'' it, via a new
proposal, by July 2021. Because of the President's direction in the
E.O., NHTSA reexamined the 2020 final rule under its authority to set
corporate average fuel economy (CAFE) standards. In doing so, NHTSA
tentatively concluded that the fuel economy standards set in 2020
should be revised so that they increase at a rate of 8 percent year
over year for each model year from 2024 through 2026, for both
passenger cars and light trucks. This responds to the agency's
statutory mandate to improve energy conservation. This proposal also
makes certain minor changes to fuel economy reporting requirements.
DATES: Comments: Comments are requested on or before October 26, 2021.
In compliance with the Paperwork Reduction Act, NHTSA is also seeking
comment on a revision to an existing information collection. For
additional information, see the Paperwork Reduction Act Section under
Section IX, below. All comments relating to the information collection
requirements should be submitted to NHTSA and to the Office of
Management and Budget (OMB) at the address listed in the ADDRESSES
section on or before October 26, 2021. 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
notification. The agency will accept oral and written comments on the
rulemaking documents and will also accept comments on the Supplemental
Environmental Impact Statement (SEIS) at this hearing. The hearing will
start at 9 a.m. Eastern standard 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-2021-
0053, by any of the following methods:
Federal eRulemaking Portal: http://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.
Comments on the proposed information collection requirements should
be submitted to: Office of Management and Budget at www.reginfo.gov/public/do/PRAMain. To find this particular information collection,
select ``Currently under Review--Open for Public Comment'' or use the
search function. NHTSA requests that comments sent to the OMB also be
sent to the NHTSA rulemaking docket identified in the heading of this
document.
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
http://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 http://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: 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:
Does this action apply to me?
This action affects companies that manufacture or sell new
passenger automobiles (passenger cars) and non-passenger automobiles
(light trucks) as defined under NHTSA's CAFE regulations.\1\ Regulated
categories and entities include:
---------------------------------------------------------------------------
\1\ ``Passenger car'' and ``light truck'' are defined in 49 CFR
part 523.
[[Page 49603]]
------------------------------------------------------------------------
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
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 person
listed in FOR FURTHER INFORMATION CONTACT.
I. Executive Summary
NHTSA, on behalf of the Department of Transportation, is proposing
to amend standards regulating corporate average fuel economy (CAFE) for
passenger cars and light trucks for model years (MYs) 2024-2026. This
proposal responds to NHTSA's statutory obligation to set maximum
feasible CAFE standards to improve energy conservation, and to
President Biden's directive in Executive Order 13990 of January 20,
2021 that ``The Safer Affordable Fuel-Efficient (SAFE) Vehicles Rule
for Model Years 2021-2026 Passenger Cars and Light Trucks'', 2020 final
rule or 2020 CAFE rule (85 FR 24174 (April 30, 2020)), be immediately
reviewed for consistency with our Nation's abiding commitment to
promote and protect our public health and the environment, among other
things. NHTSA undertook that review immediately, and this proposal is
the result of that process.
The proposed amended CAFE standards would increase in stringency
from MY 2023 levels by 8 percent per year, for both passenger cars and
light trucks over MYs 2024-2026. NHTSA tentatively concludes that this
level is maximum feasible for these model years, as discussed in more
detail in Section VI, and seeks comment on that conclusion. The
proposal considers a range of regulatory alternatives, consistent with
NHTSA's obligations under the National Environmental Policy Act (NEPA)
and Executive Order 12866. While E.O. 13990 directed the review of CAFE
standards for MYs 2021-2026, statutory lead time requirements mean that
the soonest model year that can currently be amended in the CAFE
program is MY 2024. The proposed standards would remain vehicle
footprint-based, like the CAFE standards in effect since MY 2011.
Recognizing that many readers think about CAFE standards in terms of
the miles per gallon (mpg) values that the standards are projected to
eventually require, NHTSA currently projects that the proposed
standards would require, on an average industry fleet-wide basis,
roughly 48 mpg in MY 2026. NHTSA notes both that real-world fuel
economy is generally 20-30 percent lower than the estimated required
CAFE level stated above, and also that the actual CAFE standards are
the footprint target curves for passenger cars and light trucks,
meaning that ultimate fleet-wide levels will vary depending on the mix
of vehicles that industry produces for sale in those model years. Table
I-1 shows the incremental differences in stringency levels for
passenger cars and light trucks, by regulatory alternative, in the
model years subject to regulation.
[GRAPHIC] [TIFF OMITTED] TP03SE21.000
[[Page 49604]]
This proposal is significantly different from the conclusion that
NHTSA reached in the 2020 final rule, but this is because important
facts have changed, and because NHTSA has reconsidered how to balance
the relevant statutory considerations in light of those facts. NHTSA
tentatively concludes that significantly more stringent standards are
maximum feasible. Contrary to the 2020 final rule, NHTSA recognizes
that the need of the United States to conserve energy must include
serious consideration of the energy security risks of continuing to
consume oil, which more stringent fuel economy standards can reduce.
Reducing our Nation's climate impacts can also benefit our national
security. Additionally, at least part of the automobile industry
appears increasingly convinced that improving fuel economy and reducing
greenhouse gas (GHG) emissions is a growth market for them, and that
the market rewards investment in advanced technology. Nearly all auto
manufacturers have announced forthcoming new higher fuel-economy and
electric vehicle models, and five major manufacturers voluntarily bound
themselves to stricter GHG requirements than set forth by NHTSA and the
Environmental Protection Agency (EPA) in 2020 through contractual
agreements with the State of California, which will result in their
achieving fuel economy levels well above the standards set forth in the
2020 final rule. These companies are sophisticated, for-profit
enterprises. If they are taking these steps, NHTSA can be more
confident than the agency was in 2020 that the market is getting ready
to make the leap to significantly higher fuel economy. The California
Framework and the clear planning by industry to migrate toward more
advanced fuel economy technologies are evidence of the practicability
of more stringent standards. Moreover, more stringent CAFE standards
will help to encourage industry to continue improving the fuel economy
of all vehicles, rather than simply producing a few electric vehicles,
such that all Americans can benefit from higher fuel economy and save
money on fuel. NHTSA cannot consider the fuel economy of dedicated
alternative fuel vehicles like battery electric vehicles when
determining maximum feasible standards, but the fact that industry
increasingly appears to believe that there is a market for these
vehicles is broader evidence of market (and consumer) interest in fuel
economy, which is relevant to NHTSA's determination of whether more
stringent standards would be economically practicable. For all of these
reasons, NHTSA tentatively concludes that standards that increase at 8
percent per year are maximum feasible.
This proposal is also different from the 2020 final rule in that it
is issued by NHTSA alone, and EPA has issued a separate proposal. The
primary reason for this is the difference in statutory authority--EPA
does not have the same lead time requirements as NHTSA and is thus able
to amend MY 2023 in addition to MYs 2024-2026. An important consequence
of this is that EPA's proposed rate of stringency increase, after
taking a big leap in MY 2023, looks slower than NHTSA's over the same
time period. NHTSA emphasizes, however, that the proposed standards are
what NHTSA believes best fulfills our statutory directive of energy
conservation, and in the context of the EPA standards, the analysis we
have done is tackling the core question of whether compliance with both
standards should be achievable with the same vehicle fleet, after
manufacturers fully understand the requirements from both proposals.
The differences in what the two agencies' standards require become
smaller each year, until alignment is achieved. While NHTSA recognizes
that the last several CAFE standard rulemakings have been issued
jointly with EPA, and that issuing separate proposals represents a
change in approach, the agencies worked together to avoid
inconsistencies and to create proposals that would continue to allow
manufacturers to build a single fleet of vehicles to meet both
agencies' proposed standards. Additionally, and importantly, NHTSA has
also considered and accounted for California's Zero Emission Vehicle
(ZEV) program (and its adoption by a number of other states) in
developing the baseline for this proposal, and has accounted for the
aforementioned ``Framework Agreements'' between California and BMW,
Ford, Honda, Volkswagen of America (VWA), and Volvo, which are
national-level GHG standards to which these companies committed for
several model years.
A number of other improvements and updates have been made to the
analysis since the 2020 final rule. Table I-2 summarizes these, and
they are discussed in much more detail below and in the documents
accompanying this preamble.
BILLING CODE 4910-59-P
[[Page 49605]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.001
BILLING CODE 4910-59-C
NHTSA estimates that this proposal could reduce average
undiscounted fuel outlays over the lifetimes of MY 2029 vehicles by
about $1,280, while increasing the average cost of those vehicles by
about $960 over the baseline described above. With the social cost of
carbon (SCC) discounted at 2.5 percent and other benefits and costs
discounted at 3 percent, for the three affected model years NHTSA finds
$65.8 billion in benefits attributable to the proposed standards and
$37.4 billion in proposed costs so that present net benefits could be
$28.4 billion.\2\ Applied to the entire fleet for MYs 1981-2029, NHTSA
estimates $120 billion in costs and $121
[[Page 49606]]
billion in benefits attributable to the proposed standards, such that
the present value of aggregate net benefits to society could be $1
billion. Like any analysis of this magnitude attempting to forecast
future effects of current policies, significant uncertainty exists
about many key inputs. Changes in the price of fuel or in the social
cost of carbon could dramatically change benefits, for example, and
readers should expect that the eventual final rule will reflect any
updates made to those (and many other) values that occur between now
and then. It is also worth stressing that NHTSA's statutory authority
requires that its standards be maximum feasible, taking into account
four statutory factors. While NHTSA's estimates of costs and benefits
are important considerations, it is the maximum feasible analysis that
controls the setting of CAFE standards.
---------------------------------------------------------------------------
\2\ As discussed in Section III.G.2.b), NHTSA has discounted the
SCC at 2.5% when other benefits and costs are discounted at 3% but
seeks comment on this approach.
---------------------------------------------------------------------------
Like many other types of regulations, CAFE standards apply only to
new vehicles. The costs attributable to new CAFE standards are thus
``front-loaded,'' because they result primarily from the application of
fuel-saving technology to new vehicles. On the other hand, the impact
of new CAFE standards on fuel consumption and greenhouse gases--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 model years and extending well into the future (2050), our
analysis accounts for these differing patterns in impacts, benefits,
and costs. Our analysis also accounts for the potential that, by
changing new vehicle prices and fuel economy levels, CAFE standards
could indirectly impact the operation of vehicles produced before or
after the model years (2024-2026) for which we are proposing new CAFE
standards. This means that some of the proposal's impacts and
corresponding benefits and costs are actually attributable to indirect
impacts on vehicles produced before and after model years 2024-2026.
The bulk of our analysis considers a ``model year'' (MY)
perspective that considers the lifetime impacts attributable to all
vehicles produced prior to model year 2030, accounting for the
operation of these vehicles over their entire useful lives (with some
model year 2029 vehicles estimated to be in service as late as 2068).
This approach emphasizes the role of model years 2024-2026, while
accounting for the potential that it may take manufacturers a few
additional years to produce fleets fully responsive to the proposed MY
2026 standards, and for the potential that the proposal could induce
some changes in the operation of vehicles produced prior to MY 2024.
Our analysis also considers a ``calendar year'' (CY) perspective
that includes the annual impacts attributable to all vehicles estimated
to be in service in each calendar year for which our analysis includes
a representation of the entire registered light-duty fleet. For this
NPRM, this calendar year perspective covers each of calendar years
2021-2050, with differential impacts accruing as early as model year
2023. Compared to the ``model year'' perspective, this calendar year
perspective emphasizes model years of vehicles produced in the longer
term, beyond those model years for which standards are currently being
proposed. Table I-3 summarizes estimates of selected physical impacts
viewed from each of these two perspectives, as well as corresponding
estimates of the present values of cumulative benefits, costs, and net
benefits.
BILLING CODE 4910-59-P
[[Page 49607]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.002
Finally, for purposes of comparing the benefits and costs of new
CAFE standards to the benefits and costs of other Federal regulations,
policies, and programs, we have computed ``annualized'' benefits and
costs. These are the annual averages of the cumulative benefits and
costs over the covered model or calendar years, after expressing these
in present value terms.
[GRAPHIC] [TIFF OMITTED] TP03SE21.003
[[Page 49608]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.004
[GRAPHIC] [TIFF OMITTED] TP03SE21.005
[GRAPHIC] [TIFF OMITTED] TP03SE21.006
[GRAPHIC] [TIFF OMITTED] TP03SE21.007
[GRAPHIC] [TIFF OMITTED] TP03SE21.008
As discussed in detail below, the monetized estimated costs and
benefits of this proposal are relevant and important to the agency's
tentative conclusion, but they are not the whole of the conclusion.
[[Page 49609]]
Additionally, 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 them to
reduce their compliance burden. Table I-10 through Table I-13 below
summarizes available compliance flexibilities. NHTSA seeks comment on
whether to retain non-statutory flexibilities for the final rule.
[GRAPHIC] [TIFF OMITTED] TP03SE21.009
[GRAPHIC] [TIFF OMITTED] TP03SE21.010
[GRAPHIC] [TIFF OMITTED] TP03SE21.011
[[Page 49610]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.012
BILLING CODE 4910-59-C
NHTSA recognizes that the lead time for this proposal is shorter
than past rulemakings have provided, and that the economy and the
country are in the process of recovering from a global pandemic and the
resulting economic distress. At the same time, NHTSA also recognizes
that at least parts of the industry are nonetheless stepping up their
product offerings and releasing more and more high fuel-economy vehicle
models, and many companies did not deviate significantly from product
plans established in response to the standards set forth in the 2012
final rule (77 FR 62624, Oct. 15, 2012) and confirmed by EPA in its
January 2017 Final Determination. With these considerations in mind,
NHTSA is proposing to amend the CAFE standards for MYs 2024-2026.
NHTSA, like any other Federal agency, is afforded an opportunity to
reconsider prior views and, when warranted, to adopt new positions.
Indeed, as a matter of good governance, agencies should revisit their
positions when appropriate, especially to ensure that their actions and
regulations reflect legally sound interpretations of the agency's
authority and remain consistent with the agency's views and practices.
As a matter of law, ``an Agency is entitled to change its
interpretation of a statute.'' \3\ Nonetheless, ``[w]hen an Agency
adopts a materially changed interpretation of a statute, it must in
addition provide a `reasoned analysis' supporting its decision to
revise its interpretation.'' \4\ The analysis presented in this
preamble and in the accompanying Technical Support Document (TSD),
Preliminary Regulatory Impact Analysis (PRIA), Supplemental
Environmental Impact Statement (SEIS), CAFE Model documentation, and
extensive rulemaking docket fully supports the proposed decision and
revised balancing of the statutory factors for MYs 2024-2026 standards.
NHTSA seeks comment on the entirety of the rulemaking record.
---------------------------------------------------------------------------
\3\ Phoenix Hydro Corp. v. FERC, 775 F.2d 1187, 1191 (D.C. Cir.
1985).
\4\ Alabama Educ. Ass'n v. Chao, 455 F.3d 386, 392 (D.C. Cir.
2006) (quoting Motor Vehicle Mfrs. Ass'n of U.S., Inc. v. State Farm
Mut. Auto. Ins. Co., 463 U.S. 29, 57 (1983)); see also Encino
Motorcars, LLC v. Navarro, 136 S.Ct. 2117, 2125 (2016) (``Agencies
are free to change their existing policies as long as they provide a
reasoned explanation for the change.'') (citations omitted).
---------------------------------------------------------------------------
II. Introduction
In this notice of proposed rulemaking (NPRM), NHTSA is proposing to
revise CAFE standards for model years (MYs) 2024-2026. On January 20,
2021, the President signed Executive Order (E.O.) 13990, ``Protecting
Public Health and the Environment and Restoring Science To Tackle the
Climate Crisis.'' \5\ In it, the President directed that ``The Safer
Affordable Fuel-Efficient (SAFE) Vehicles Rule for Model Years 2021-
2026 Passenger Cars and Light Trucks'' (hereafter, ``the 2020 final
rule''), 85 FR 24174 (April 30, 2020), must be immediately reviewed for
consistency with our Nation's abiding commitment to empower our workers
and communities; promote and protect our public health and the
environment; and conserve our national treasures and monuments, places
that secure our national memory. E.O. 13990 states expressly that the
Administration prioritizes listening to the science, improving public
health and protecting the environment, reducing greenhouse gas
emissions, and improving environmental justice while creating well-
paying union jobs. The E.O. thus directs that the 2020 final rule be
reviewed at once and that (in this case) the Secretary of
Transportation consider ``suspending, revising, or rescinding'' it, via
an NPRM, by July 2021.\6\
---------------------------------------------------------------------------
\5\ 86 FR 7037 (Jan. 25, 2021).
\6\ Id., Sec. 2(a)(ii).
---------------------------------------------------------------------------
Section 32902(g)(1) of Title 49, United States Code allows the
Secretary (by delegation to NHTSA) to prescribe regulations amending an
average fuel economy standard prescribed under 49 U.S.C. 32902(a), like
those prescribed in the 2020 final rule, if the amended standard meets
the requirements of 32902(a). The Secretary's authority to set fuel
economy standards is delegated to NHTSA at 49 CFR 1.95(a); therefore,
in this NPRM, NHTSA proposes revised fuel economy standards for MYs
2024-2026. Section 32902(g)(2) states that when the amendment makes an
average fuel economy standard more stringent, it must be prescribed at
least 18 months before the beginning of the model year to which the
amendment applies. NHTSA generally calculates the 18-month lead time
requirement as April of the calendar year prior to the start of the
model year. Thus, 18 months before MY 2023 would be April 2021, because
MY 2023 begins in September 2022. Because of this lead time
requirement, NHTSA is not proposing to amend the CAFE standards for MYs
2021-2023, even though the 2020 final rule also covered those model
years. For purposes of the CAFE program, the 2020 final rule's
standards for MYs 2021-2023 will remain in effect.
For the MYs for which there is statutory lead time to amend the
standards, however, NHTSA is proposing amendments to the currently
applicable fuel economy standards. Although only one year has passed
since the 2020 final rule, the agency believes it is reasonable and
appropriate to revisit the CAFE standards for MYs 2024-2026. In
particular, the agency has further considered the serious adverse
effects on energy conservation that the standards finalized in 2020
would cause
[[Page 49611]]
as compared to the proposed standards. The need of the U.S. to conserve
energy is greater than understood in the 2020 final rule. In addition,
standards that are more stringent than those that were finalized in
2020 appear economically practicable. Nearly all auto manufacturers
have announced forthcoming new advanced technology vehicle models with
higher fuel economy, making strong public commitments that mirror those
of the Administration. Five major manufacturers voluntarily bound
themselves to stricter national-level GHG requirements as part of the
California Framework agreement. Meanwhile, certain facts on the ground
remain similar to what was before NHTSA in the prior analysis--gas
prices still remain relatively low in the U.S., for example, and while
light-duty vehicle sales fell sharply in MY 2020, the vehicles that did
sell tended to be, on average, larger, heavier, and more powerful, all
factors that increase fuel consumption. However, the renewed focus on
addressing energy conservation and the industry's apparent ability to
meet more stringent standards show that a rebalancing of the EPCA
factors, and the proposal of more stringent standards, is appropriate
for model years 2024-2026.
The following sections introduce the proposal in more detail.
A. What is NHTSA proposing?
NHTSA is proposing to set CAFE standards for passenger cars and
light trucks manufactured for sale in the United States in MYs 2024-
2026. 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 vehicles, larger/
heavier two-wheel drive sport utility vehicles, pickups, minivans, and
passenger/cargo vans.\7\ The proposed standards would increase at 8
percent per year for both cars and trucks, and are represented by
regulatory Alternative 2 in the agency's analysis. The proposed
standards would be defined by a mathematical equation that represents a
constrained linear function relating vehicle footprint to fuel economy
targets for both cars and trucks; vehicle footprint is roughly measured
as the rectangle that is made by the four points where the vehicle's
tires touch the ground. Generally, passenger cars will have more
stringent targets than light trucks regardless of footprint, and
smaller vehicles will have more stringent targets than larger vehicles.
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.
---------------------------------------------------------------------------
\7\ ``Passenger car'' and ``light truck'' are defined at 49 CFR
part 523.
---------------------------------------------------------------------------
The proposed target curves \8\ for passenger cars and light trucks
are as follows; curves for MYs 2020-2023 are included in Figure II-1
and Figure II-2 for context.
---------------------------------------------------------------------------
\8\ NHTSA underscores that the equations and coefficients
defining the curves are what the agency is proposing, and not the
mpg numbers that the agency currently estimates could result from
manufacturers complying with the curves. Because the estimated mpg
numbers are an effect of the proposed curves, they are presented in
the following section.
---------------------------------------------------------------------------
BILLING CODE 4910-59-P
[[Page 49612]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.013
[[Page 49613]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.014
BILLING CODE 4910-59-C
NHTSA is also proposing to amend the minimum domestic passenger car
CAFE standards for MYs 2024-2026. The provision at 49 U.S.C.
32902(b)(4) requires NHTSA to project the minimum standard when it
promulgates passenger car standards for a model year, so it is
appropriate to revisit the minimum standards at this time. NHTSA is
proposing to retain the 1.9 percent offset used in the 2020 final rule,
such that the minimum domestic passenger car standard would be as shown
in Table II-1.
[GRAPHIC] [TIFF OMITTED] TP03SE21.015
The next section describes some of the effects that NHTSA estimates
would follow from this proposal, including how the curves shown above
translate to estimated average mile per gallon requirements for the
industry.
B. What does NHTSA estimate the effects of proposing this would be?
As for past CAFE rulemakings, NHTSA has used the CAFE Model to
estimate the effects of proposed CAFE standards, and of other
regulatory alternatives under consideration. Some inputs to the CAFE
Model are derived from other models, such as Argonne National
Laboratory's ``Autonomie'' vehicle simulation tool and Argonne's
Greenhouse gases, Regulated Emissions, and Energy use in Transportation
(GREET) fuel-cycle emissions analysis model, the U.S. Energy
Information Administration's (EIA's) National Energy Modeling System
(NEMS), and EPA's Motor Vehicle Emission Simulator (MOVES) vehicle
emissions model. Especially given the scope of the
[[Page 49614]]
NHTSA's analysis (through model years 2050, with driving of model year
2029 vehicles accounted for through calendar year 2068), these inputs
involve a multitude of uncertainties. For example, a set of inputs with
significant uncertainty could include future population and economic
growth, future gasoline and electricity prices, future petroleum market
characteristics (e.g., imports and exports), future battery costs,
manufacturers' future responses to standards and fuel prices, buyers'
future responses to changes in vehicle prices and fuel economy levels,
and future emission rates for ``upstream'' processes (e.g., refining,
finished fuel transportation, electricity generation). Considering that
all of this is uncertain from a 2021 vantage point, NHTSA underscores
that all results of this analysis are, in turn, uncertain, and simply
represent the agency's best estimates based on the information
currently before us.
NHTSA estimates that this proposal would increase the eventual \9\
average of manufacturers' CAFE requirements to about 48 mpg by 2026
rather than, under the No-Action Alternative (i.e., the baseline
standards issued in 2020), about 40 mpg. For passenger cars, the
average in 2026 is estimated to reach about 58 mpg, and for light
trucks, about 42. This compares with 47 mpg and 34 mpg for cars and
trucks, respectively, under the No-Action Alternative.
---------------------------------------------------------------------------
\9\ Here, ``eventual'' means by MY 2029, after most of the fleet
will have been redesigned under the MY 2026 standards. NHTSA allows
the CAFE Model to continue working out compliance solutions for the
regulated model years for three model years after the last regulated
model year, in recognition of the fact that manufacturers do not
comply perfectly with CAFE standards in each model year.
[GRAPHIC] [TIFF OMITTED] TP03SE21.016
Because manufacturers do not comply exactly with each standard in
each model year, but rather focus their compliance efforts when and
where it is most cost-effective to do so, ``estimated achieved'' fuel
economy levels differ somewhat from ``estimated required'' levels for
each fleet, for each year. NHTSA estimates that the industry-wide
average fuel economy achieved in MY 2029 could increase from about 44
mpg under the No-Action Alternative to about 49 mpg under the proposal.
[GRAPHIC] [TIFF OMITTED] TP03SE21.017
As discussed above, NHTSA's analysis--unlike its previous CAFE
analyses--estimates manufacturers' potential responses to the combined
effect of CAFE standards and separate CO2 standards
(including agreements some manufacturers have reached with California),
ZEV mandates, and fuel prices. Together, the aforementioned regulatory
programs are more binding than any single program considered in
isolation, and this analysis, like past analyses, shows some estimated
overcompliance with the proposed CAFE standards, albeit by much less
than what was shown in the NPRM that preceded the 2020 final rule, and
any overcompliance is highly manufacturer-dependent.
Expressed as equivalent required and achieved average
CO2 levels (using 8887 grams of CO2 per gallon of
gasoline vehicle certification fuel), the above CAFE levels appear as
shown in Table II-4 and Table II-5.
[GRAPHIC] [TIFF OMITTED] TP03SE21.018
[[Page 49615]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.019
Average requirements and achieved CAFE levels would ultimately
depend on manufacturers' and consumers' responses to standards,
technology developments, economic conditions, fuel prices, and other
factors.
NHTSA estimates that over the lives of vehicles produced prior to
MY 2030, the proposal would save about 50 billion gallons of gasoline
and increase electricity consumption (as the percentage of electric
vehicles increases over time) by about 275 terawatts (TWh), compared to
levels of gasoline and electricity consumption NHTSA projects would
occur under the baseline standards (i.e., the No-Action Alternative).
[GRAPHIC] [TIFF OMITTED] TP03SE21.020
NHTSA's analysis also estimates total annual consumption of fuel by
the entire on-road fleet from calendar year 2020 through calendar year
2050. On this basis, gasoline and electricity consumption by the U.S.
light-duty vehicle fleet evolves as shown in Figure II-3 and Figure II-
4, each of which shows projections for the No-Action Alternative
(Alternative 0, i.e., the baseline), Alternative 1, Alternative 2 (the
proposal), and Alternative 3.
BILLING CODE 4910-59-P
[[Page 49616]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.021
[[Page 49617]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.022
Accounting for emissions from both vehicles and upstream energy
sector processes (e.g., petroleum refining and electricity generation),
NHTSA estimates that the proposal would reduce greenhouse gas emissions
by about 465 million metric tons of carbon dioxide (CO2),
about 500 thousand metric tons of methane (CH4), and about
12 thousand tons of nitrous oxide (N2O).
[GRAPHIC] [TIFF OMITTED] TP03SE21.023
As for fuel consumption, NHTSA's analysis also estimates annual
emissions attributable to the entire on-road fleet from calendar year
2020 through calendar year 2050. Also accounting for both vehicles and
upstream processes, NHTSA estimates that CO2 emissions could
evolve over time as shown in Figure II-5, which accounts for both
emissions from both vehicles and upstream processes.
[[Page 49618]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.024
Estimated emissions of methane and nitrous oxides follow similar
trends. As discussed in the TSD, PRIA, and this NPRM, NHTSA has
performed two types of supporting analysis. This NPRM and PRIA focus on
the ``standard setting'' analysis, which sets aside the potential that
manufacturers could respond to standards by using compliance credits or
introducing new alternative fuel vehicle (including BEVs) models during
the ``decision years'' (for this NPRM, 2024, 2025, and 2026). The
accompanying SEIS focuses on an ``unconstrained'' analysis, which does
not set aside these potential manufacturer actions. The SEIS presents
much more information regarding projected GHG emissions, as well as
model-based estimates of corresponding impacts on several measures of
global climate change.
Also accounting for vehicular and upstream emissions, NHTSA has
estimated annual emissions of most criteria pollutants (i.e.,
pollutants for which EPA has issued National Ambient Air Quality
Standards). NHTSA estimates that under each regulatory alternative,
annual emissions of carbon monoxide (CO), volatile organic compounds
(VOC), nitrogen oxide (NOX), and fine particulate matter
(PM2.5) attributable to the light-duty on-road fleet will
decline dramatically between 2020 and 2050, and that emissions in any
given year could be very nearly the same under each regulatory
alternative. For example, Figure II-6 shows NHTSA's estimate of future
NOX emissions under each alternative.
[[Page 49619]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.025
BILLING CODE 4910-59-C
On the other hand, as discussed in the PRIA and SEIS, NHTSA
projects that annual SO2 emissions attributable to the
light-duty 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). The adoption of actions--such as actions prompted by
President Biden's Executive order directing agencies to develop a
Federal Clean Electricity and Vehicle Procurement Strategy--to reduce
electricity generation emission rates beyond projections underlying
NHTSA's analysis (discussed in the TSD) could dramatically reduce
SO2 emissions under all regulatory alternatives considered
here.\10\
---------------------------------------------------------------------------
\10\ https://www.whitehouse.gov/briefing-room/presidential-actions/2021/01/27/executive-order-on-tackling-the-climate-crisis-at-home-and-abroad/, accessed June 17, 2021.
---------------------------------------------------------------------------
For the ``standard setting'' analysis, the PRIA accompanying this
NPRM provides additional detail regarding projected criteria pollutant
emissions and health effects, as well as the inclusion of these impacts
in this benefit-cost analysis. For the ``unconstrained'' or ``EIS''
type of analysis, the SEIS accompanying this NPRM presents much more
information regarding projected criteria pollutant emissions, as well
as model-based estimates of corresponding impacts on several measures
of urban air quality and public health. As mentioned above, these
estimates of criteria pollutant emissions are based on a complex
analysis involving interacting simulation techniques and a myriad of
input estimates and assumptions. Especially extending well past 2040,
the analysis involves a multitude of uncertainties. Therefore, actual
criteria pollutant emissions could ultimately be different from NHTSA's
current estimates.
To illustrate the effectiveness of the technology added in response
to this proposal, Table II-8 presents NHTSA's estimates for increased
vehicle cost and lifetime fuel expenditures if we assumed the
behavioral response to the lower cost of driving were zero.\11\ These
numbers are presented in lieu of NHTSA's primary estimate of lifetime
fuel savings, which would give an incomplete picture of technological
effectiveness because the analysis accounts for consumers' behavioral
response to the lower cost-per-mile of driving a more fuel-efficient
vehicle.
---------------------------------------------------------------------------
\11\ While this comparison illustrates the effectiveness of the
technology added in response to this proposal, it does not represent
a full consumer welfare analysis, which would account for drivers'
likely response to the lower cost-per-mile of driving, as well as a
variety of other benefits and costs they will experience. The
agency's complete analysis of the proposal's likely impacts on
passenger car and light truck buyers appears in the PRIA, Appendix
I, Table A-23-1.
---------------------------------------------------------------------------
[[Page 49620]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.026
With the SCC discounted at 2.5% and other benefits and costs
discounted at 3%, NHTSA estimates that costs and benefits could be
approximately $120 billion and $121 billion, respectively, such that
the present value of aggregate net benefits to society could be
somewhat less than $1 billion. With the social cost of carbon (SCC)
discounted at 3% and other benefits and costs discounted at 7%, NHTSA
estimates approximately $90 billion in costs and $76 billion in
benefits could be attributable to vehicles produced prior to MY 2030
over the course of their lives, such that the present value of
aggregate net costs to society could be approximately $15 billion.\13\
---------------------------------------------------------------------------
\12\ Assumes no rebound effect.
\13\ NHTSA interprets the 2021 IWG draft guidance as indicating
that a 2.5% discount rate for the SCC is consistent with discounting
near-term benefits and costs of the proposal at the OMB-recommended
consumption discount rate of 3%. For the OMB-recommended discount
rate of 7%, NHTSA concluded that a 3% discount rate for the SCC was
reasonable given that the IWG draft guidance suggested that the
appropriate discount rate for the SCC was likely lower than 3%.
NHTSA refers readers specifically to pp. 16-17 of that guidance,
available at https://www.whitehouse.gov/wp-content/uploads/2021/02/TechnicalSupportDocument_SocialCostofCarbonMethaneNitrousOxide.pdf?source=email.
[GRAPHIC] [TIFF OMITTED] TP03SE21.027
Model results can be viewed many different ways, and NHTSA's
rulemaking considers both ``model year'' and ``calendar year''
perspectives. The ``model year'' perspective, above, considers vehicles
projected to be produced in some range of model years, and accounts for
impacts, benefits, and costs attributable to these vehicles from the
present (from the model year's perspective, 2020) until they are
projected to be scrapped. The bulk of NHTSA's analysis considers
vehicles produced prior to model year 2030, accounting for the
estimated indirect impacts new standards could have on the remaining
operation of vehicles already in service. This perspective emphasizes
impacts on those model years nearest to those (2024-2026) for which
NHTSA is proposing new standards. NHTSA's analysis also presents some
results focused only on model years 2024-2026, setting aside the
estimated indirect impacts on earlier model years, and the impacts
estimated to occur during model years 2027-2029, as some manufacturers
and products ``catch up'' to the standards.
Another way to present the benefits and costs of the proposal is
the ``calendar year'' perspective shown in Table II-10, which is
similar to how EPA presents benefits and costs in its proposal for GHG
standards for MYs 2023-2026. The calendar year perspective considers
all vehicles projected to be in service in each of some range of future
calendar years. NHTSA's presentation of results from this perspective
considers calendar years 2020-2050, because the model's representation
of the full on-road fleet extends through 2050. Unlike the model year
perspective, this perspective includes vehicles projected produced
during model years 2030-2050. This perspective emphasizes longer-term
impacts that could accrue if standards were to continue without change.
Table II-10 shows costs and benefits for MYs 2023-2026 while Table II-9
shows costs and benefits through MY 2029.
[[Page 49621]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.028
Though based on the exact same model results, these two
perspectives provide considerably different views of estimated costs
and benefits. Because technology costs account for a large share of
overall estimated costs, and are also projected to decline over time
(as manufacturers gain more experience with new technologies), costs
tend to be ``front loaded''--occurring early in a vehicle's life and
tending to be higher in earlier model years than in later model years.
Conversely, because social benefits of standards occur as vehicles are
driven, and because both fuel prices and the social cost of
CO2 emissions are projected to increase in the future,
benefits tend to be ``back loaded.'' As a result, estimates of future
fuel savings, CO2 reductions, and net social benefits are
higher under the calendar year perspective than under the model year
perspective. On the other hand, with longer-term impacts playing a
greater role, the calendar year perspective is more subject to
uncertainties regarding, for example, future technology costs and fuel
prices.
Even though NHTSA and EPA estimate benefits, costs, and net
benefits using similar methodologies and achieve similar results,
different approaches to accounting may give the false appearance of
significant divergences. Table II-10 above presents NHTSA's results
using comparable accounting to EPA's preamble Table 5. EPA also
presents cost and benefit information in its RIA over calendar years
2021 through 2050. The numbers most comparable to those presented in
EPA's RIA are those NHTSA developed to complete its Supplemental
Environmental Impact Statement (SEIS) using an identical accounting
approach. This is because the statutory limitations constraining
NHTSA's standard setting analysis, such as those in 49 U.S.C. 32902(h)
prohibiting consideration of full vehicle electrification during the
rulemaking timeframe, or consideration of the trading or transferring
of overcompliance credits, do not similarly apply to its EIS
analysis.\14\ NHTSA's EIS analysis estimates $312 billion in costs,
$443 billion in benefits, and $132 billion in net benefits using a 3%
discount rate over calendar years 2021 through 2050.\15\ NHTSA
describes its cost and benefit accounting approach in Section V of this
preamble.
---------------------------------------------------------------------------
\14\ As the EIS analysis contains information that NHTSA is
statutorily prevented from considering, the agency does not rely on
this analysis in regulatory decision-making.
\15\ See PRIA Chapter 6.5 for more information regarding NHTSA's
estimates of annual benefits and costs using NHTSA's standard
setting analysis. See Tables B-7-25 through B-7-30 in Appendix II of
the PRIA for a more detailed breakdown of NHTSA's EIS analysis.
---------------------------------------------------------------------------
C. Why does NHTSA tentatively believe the proposal would be maximum
feasible, and how and why is this tentative conclusion different from
the 2020 final rule?
NHTSA's tentative conclusion, after consideration of the factors
described below and information in the administrative record for this
action, is that 8 percent increases in stringency for MYs 2024-2026
(Alternative 2 of this analysis) are maximum feasible. The Department
of Transportation is deeply committed to working aggressively to
improve energy conservation and reduce security risks associated with
energy use, and higher standards appear increasingly likely to be
economically practicable given almost-daily announcements by major
automakers about forthcoming new high-fuel-economy vehicle models, as
described in more detail below. Despite only one year having passed
since the 2020 final rule, enough has changed in the U.S. and the world
that revisiting the CAFE standards for MYs 2024-2026, and raising their
stringency considerably, is both appropriate and reasonable.
The 2020 final rule set CAFE standards that increased at 1.5
percent per year for cars and trucks for MYs 2021-2026, in large part
because it prioritized industry concerns and reducing vehicle purchase
costs to consumers and manufacturers. This proposed rule acknowledges
the priority of energy conservation, consistent with NHTSA's statutory
authority. Moreover, NHTSA is also legally required to consider the
environmental implications of this action under NEPA, and while the
2020 final rule did undertake a NEPA analysis, it did not prioritize
the environmental considerations aspects of the statutory need of the
U.S. to conserve energy.
NHTSA recognizes that the amount of lead time available before MY
2024 is less than what was provided in the 2012 rule. As will be
discussed further in Section VI, NHTSA believes that the evidence
suggests that the proposed standards are still economically
practicable.
We note further that while this proposal is different from the 2020
final rule (and also from the 2012 final rule), NHTSA, like any other
Federal agency, is afforded an opportunity to reconsider prior views
and, when warranted, to adopt new positions. Indeed, as a matter of
good governance, agencies should revisit their positions when
appropriate, especially to ensure that their actions and regulations
reflect legally sound interpretations of the agency's authority and
remain consistent with the agency's views and practices. As a matter of
law, ``an Agency is entitled to change its interpretation of a
statute.'' \16\ Nonetheless, ``[w]hen an Agency adopts a materially
changed interpretation of a statute, it must in addition provide a
`reasoned analysis' supporting its decision to revise its
interpretation.'' \17\
[[Page 49622]]
This preamble and the accompanying TSD and PRIA all provide extensive
detail on the agency's updated analysis, and Section VI contains the
agency's explanation of how the agency has considered that analysis and
other relevant information in tentatively determining that the proposed
CAFE standards are maximum feasible for MYs 2024-2026 passenger cars
and light trucks.
---------------------------------------------------------------------------
\16\ Phoenix Hydro Corp. v. FERC, 775 F.2d 1187, 1191 (D.C. Cir.
1985).
\17\ Alabama Educ. Ass'n v. Chao, 455 F.3d 386, 392 (D.C. Cir.
2006) (quoting Motor Vehicle Mfrs. Ass'n of U.S., Inc. v. State Farm
Mut. Auto. Ins. Co., 463 U.S. 29, 57 (1983)); see also Encino
Motorcars, LLC v. Navarro, 136 S.Ct. 2117, 2125 (2016) (``Agencies
are free to change their existing policies as long as they provide a
reasoned explanation for the change.'') (citations omitted).
---------------------------------------------------------------------------
D. How is this proposal consistent with EPA's proposal and with
California's programs?
The NHTSA and EPA proposals remain coordinated despite being issued
as separate regulatory actions. Because NHTSA and EPA are regulating
the exact same vehicles and manufacturer will use the same technologies
to meet both sets of standards, NHTSA and EPA coordinated during the
development of each agency's independent proposal to revise the
standards set forth in the 2020 final rule. The NHTSA-proposed CAFE and
EPA-proposed CO2 standards for MY 2026 represent roughly
equivalent levels of stringency and may serve as a coordinated starting
point for subsequent standards. While the proposed CAFE and
CO2 standards for MYs 2024-2025 are different, this is
largely due to the difference in the ``start year'' for the revised
regulations--EPA is proposing to revise standards for MY 2023, while
EPCA's lead time requirements, which do not apply to EPA, prevent NHTSA
from proposing revised standards until MY 2024. In order to set
standards for MY 2023, EPA intends to issue its final rule by December
31, 2021, whereas NHTSA has until April 2022 to finalize standards for
MY 2024. The difference in timing makes separate rulemaking actions
reasonable and prudent. The specific differences in what the two
agencies' standards require become smaller each year, until alignment
is achieved. The agencies still have coordinated closely to minimize
inconsistency between the programs and will continue to do so through
the final rule stage.
While NHTSA's and EPA's programs differ in certain other respects,
like programmatic flexibilities, those differences are not new in this
proposal. Some parts of the programs are harmonized, and others differ,
often as a result of statute. Since NHTSA and EPA began regulating
together under President Obama, differences in programmatic
flexibilities have meant that manufacturers have had (and will have) to
plan their compliance strategies considering both the CAFE standards
and the GHG standards and assure that they are in compliance with both,
while still building a single fleet of vehicles to accomplish that
goal. NHTSA is proposing CAFE standards that increase at 8 percent per
year over MYs 2024-2026 because that is what NHTSA has tentatively
concluded is maximum feasible in those model years, under the EPCA
factors, and is confident that industry would still be able to build a
single fleet of vehicles to meet both the NHTSA and EPA standards. Auto
manufacturers are extremely sophisticated companies, well-able to
manage complex compliance strategies that account for multiple
regulatory programs concurrently. If different agencies' standards are
more binding for some companies in certain years, this does not mean
that manufacturers must build multiple fleets of vehicles, simply that
they will have to be more strategic about how they build their fleet.
NHTSA has also considered and accounted for California's ZEV
mandate (and its adoption by a number of other states) in developing
the baseline for this proposal, and has also accounted for the
Framework Agreements between California, BMW, Ford, Honda, VWA, and
Volvo. NHTSA believes that it is reasonable to include ZEV in the
baseline for this proposal regardless of whether California receives a
waiver of preemption under the Clean Air Act (CAA) because, according
to California, industry overcompliance with the ZEV mandate has been
extensive, which indicates that whether or not a waiver exists, many
companies intend to produce ZEVs in volumes comparable to what a ZEV
mandate would require. Because no decision has yet been made on a CAA
waiver for California, and because modeling a sub-national fleet is not
currently an analytical option for NHTSA, NHTSA has not expressly
accounted for California GHG standards in the analysis for this
proposal, although we seek comment on whether and how to account for
them in the final rule. Chapter 6 of the accompanying PRIA shows the
estimated effects of all of these programs simultaneously.
III. Technical Foundation for NPRM Analysis
A. Why does NHTSA conduct this analysis?
NHTSA is proposing to establish revised CAFE standards for
passenger cars and light trucks produced for model years (MYs) 2024-
2026. NHTSA's review of the existing standards is consistent with
Executive Order 13990, Protecting Public Health and the Environment and
Restoring Science to Tackle the Climate Crisis, signed on January 20,
2021, directing the review of the 2020 final rule that established CAFE
standards for MYs 2021-2026 and the consideration of whether to
suspend, revise, or rescind that action by July 2021.\18\ NHTSA
establishes CAFE standards under the Energy Policy and Conservation
Act, as amended, and this proposal is undertaken pursuant to that
authority. This proposal would require CAFE stringency for both
passenger cars and light trucks to increase at a rate of 8 percent per
year annually from MY 2024 through MY 2026. NHTSA estimates that over
the useful lives of vehicles produced prior to MY 2030, the proposal
would save about 50 billion gallons of gasoline and increase
electricity consumption by about 275 TWh. Accounting for emissions from
both vehicles and upstream energy sector processes (e.g., petroleum
refining and electricity generation), NHTSA estimates that the proposal
would reduce greenhouse gas emissions by about 465 million metric tons
of carbon dioxide (CO2), about 500 thousand tons metric tons
of methane (CH4), and about 12 thousand tons of nitrous
oxide (N2O).
---------------------------------------------------------------------------
\18\ 86 FR 7037 (Jan. 25, 2021).
---------------------------------------------------------------------------
When NHTSA promulgates new regulations, it generally presents an
analysis that estimates the impacts of such regulations, and the
impacts of other regulatory alternatives. These analyses derive from
statutes such as the Administrative Procedure Act (APA) and National
Environmental Policy Act (NEPA), from Executive orders (such as
Executive Order 12866 and 13653), and from other administrative
guidance (e.g., Office of Management Budget Circular A-4). For CAFE,
the Energy Policy and Conservation Act (EPCA), as amended by the Energy
Independence and Security Act (EISA), contains a variety of provisions
that require NHTSA to consider certain compliance elements in certain
ways and avoid considering other things, in determining maximum
feasible CAFE standards. Collectively, capturing all of these
requirements and guidance elements analytically means that, at least
for CAFE, 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's express requirements for the CAFE program
[[Page 49623]]
(e.g., passenger cars and light trucks are regulated separately, and
the standard for each fleet must be set at the maximum feasible level
in each model year).
NHTSA's decision regarding the proposed standards is thus supported
by extensive analysis of potential impacts of the regulatory
alternatives under consideration. Along with this preamble, a Technical
Support Document (TSD), a Preliminary Regulatory Impact Analysis
(PRIA), and a Supplemental Environmental Impact Statement (SEIS),
together provide an extensive and detailed enumeration of related
methods, estimates, assumptions, and results. NHTSA's analysis has been
constructed specifically to reflect various aspects of governing law
applicable to CAFE standards and has been expanded and improved in
response to comments received to the prior rulemaking and based on
additional work conducted over the last year. Further improvements may
be made based on comments received to this proposal, the 2021 NAS
Report,\19\ and other additional 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.
---------------------------------------------------------------------------
\19\ National Academies of Sciences, Engineering, and Medicine
(NASEM), 2021. Assessment of Technologies for Improving Fuel Economy
of Light-Duty Vehicles--2025-2035, Washington, DC: The National
Academies Press (hereafter, ``2021 NAS Report''). Available at
https://www.nationalacademies.org/our-work/assessment-of-technologies-for-improving-fuel-economy-of-light-duty-vehicles-phase-3 and for hard-copy review at DOT headquarters.
---------------------------------------------------------------------------
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
fleet'' containing, among other things, production volumes and fuel
economy levels of specific configurations of specific vehicle models
produced for sale in the U.S. Two examples of estimates include (1)
forecasts of future GDP growth used, with other estimates, to forecast
future vehicle sales volumes and (2) the ``retail price equivalent''
(RPE) factor used to estimate the ultimate cost to consumers of a given
fuel-saving technology, given accompanying estimates of the
technology's ``direct cost,'' as adjusted to account for estimated
``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 and CO2 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 rulemaking regarding heavy-duty pickup and van
fuel consumption and CO2 emissions also used the CAFE Model
for analysis (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, and economic externalities. In a highly-summarized form,
Figure III-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 preamble presents these details, and
Chapter 1 of the TSD contains a more detailed version of this flow
diagram for readers who are interested.
BILLING CODE 4910-59-P
[[Page 49624]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.029
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 the basis for comparing between
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 and truck regulatory classes, and stringency of the
CAFE standards for each model year to be analyzed. For example, a
regulatory scenario may define CAFE standards that increase in
stringency by 8 percent per year for 3 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 \20\ initial forecast of the vehicle models
offered for sale during the simulation period. The compliance
simulation then attempts to bring each manufacturer into compliance
with the standards \21\ defined by the regulatory scenario contained
within an input file developed by the user.
---------------------------------------------------------------------------
\20\ 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 file that contains the
forecast used for this proposal is available on NHTSA's website.
\21\ 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
[[Page 49625]]
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, operating costs, and vehicle
price on consumer demand for passenger cars and light trucks. Both
basic analytical elements involve the 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 MOVES model to estimate ``tailpipe'' (a.k.a.
``vehicle'' or ``downstream'') emission factors for criteria
pollutants,\22\ 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. The
agency uses the DOE Energy Information Administration's (EIA's)
National Energy Modeling System (NEMS) to estimate fuel prices,\23\ and
uses Argonne's Greenhouse gases, Regulated Emissions, and Energy use in
Transportation (GREET) model to estimate emissions rates from fuel
production and distribution processes.\24\ DOT also sponsored DOE/
Argonne to use Argonne's Autonomie full-vehicle modeling and simulation
system to estimate the fuel economy impacts for roughly a million
combinations of technologies and vehicle types.25 26 The TSD
and PRIA describe details of the agency's use of these models. In
addition, as discussed in the SEIS accompanying this NPRM, DOT relied
on a range of climate models to estimate impacts on climate, air
quality, and public health. The SEIS discusses and describes the use of
these models.
---------------------------------------------------------------------------
\22\ See https://www.epa.gov/moves. This proposal uses version
MOVES3, available at https://www.epa.gov/moves/latest-version-motor-vehicle-emission-simulator-moves.
\23\ See https://www.eia.gov/outlooks/aeo/info_nems_archive.php.
This proposal uses fuel prices estimated using the Annual Energy
Outlook (AEO) 2021 version of NEMS (see https://www.eia.gov/outlooks/aeo/pdf/02%20AEO2021%20Petroleum.pdf).
\24\ Information regarding GREET is available at https://greet.es.anl.gov/index.php. This NPRM uses the 2020 version of
GREET.
\25\ As part of the Argonne simulation effort, individual
technology combinations simulated in Autonomie were paired with
Argonne'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 Argonne's BatPaC model is available at https://www.anl.gov/cse/batpac-model-software.
\26\ 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-suite-applications/propulsion-systems/gt-power-engine-simulation-software.
---------------------------------------------------------------------------
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 comments, made since early
2020 include:
Inclusion of 400- and 500-mile BEVs;
Inclusion of high compression ratio (HCR) engines with
cylinder deactivation;
Accounting for manufacturers' responses to both CAFE and
CO2 standards jointly (rather than only separately)
Accounting for the ZEV mandates applicable in California
and the ``Section 177'' states;
Accounting for some vehicle manufacturers' (BMW, Ford,
Honda, VW, and Volvo) voluntary agreement with the State of California
to continued annual national-level reductions of vehicle greenhouse gas
emissions through MY 2026, with greater rates of electrification than
would have been required under the 2020 Federal final rule; \27\
---------------------------------------------------------------------------
\27\ For more information on the Framework Agreements for Clean
Cars, including the specific agreements signed by individual
manufacturers, see https://ww2.arb.ca.gov/news/framework-agreements-clean-cars.
---------------------------------------------------------------------------
[cir] Inclusion of CAFE civil penalties in the ``effective cost''
metric used when simulating manufacturers' potential application of
fuel-saving technologies;
[cir] Refined procedures to estimate health effects and
corresponding monetized damages attributable to criteria pollutant
emissions;
[cir] New procedures to estimate the impacts and corresponding
monetized damages of highway vehicle crashes that do not result in
fatalities;
[cir] Procedures to ensure that modeled technology application and
production volumes are the same across all regulatory alternatives in
the earliest model years; and
[cir] Procedures to more precisely focus application of EPCA's
``standard setting constraints'' (i.e., regarding the consideration of
compliance credits and additional dedicated alternative fueled
vehicles) to only those model years for which NHTSA is proposing or
finalizing new standards.
These changes reflect DOT's long-standing commitment to ongoing
refinement of its approach to estimating the potential impacts of new
CAFE standards.
NHTSA underscores that this analysis exercises 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 face the
combination of CAFE standards, EPA CO2 standards, and ZEV
mandates, and for five manufacturers, the voluntary agreement with
California to more stringent CO2 reduction requirements
(also applicable to these manufacturers' total production for the U.S.
market) through model year 2026. These regulations and contracts have
important structural and other differences that affect the strategy a
manufacturer could use to comply with each of the above.
As explained, the analysis is designed to reflect a number of
statutory and regulatory requirements applicable to CAFE and tailpipe
CO2 standard-setting. EPCA contains a number of requirements
governing the scope and nature of CAFE standard setting. Among these,
some 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. EPCA/EISA requirements regarding the technical characteristics of
CAFE standards and the analysis thereof include, but are not limited
to, the following, and the analysis reflects these requirements as
summarized:
Corporate Average Standards: The provision at 49 U.S.C. 32902
requires standards that apply to the average fuel economy levels
achieved by each corporation's fleets of vehicles produced for sale in
the U.S.\28\ The CAFE Model calculates the CAFE and CO2
levels of each manufacturer's fleets based on estimated production
volumes and characteristics, including fuel economy levels, of distinct
vehicle models that could be produced for sale in the U.S.
---------------------------------------------------------------------------
\28\ This differs from safety standards and traditional
emissions standards, which apply separately to each vehicle. 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 standards. Rather, each manufacturer is
required to produce a mix of vehicles that, taken together, achieve
an average fuel economy level no less than the applicable minimum
level.
---------------------------------------------------------------------------
Separate Standards for Passenger Cars and Light Trucks: The
provision at 49 U.S.C. 32902 requires the Secretary of Transportation
to set CAFE standards separately for passenger cars and light trucks.
The CAFE Model accounts separately for passenger cars and light trucks
when it analyzes CAFE or CO2 standards, including
differentiated standards and compliance.
[[Page 49626]]
Attribute-Based Standards: The provision at 49 U.S.C. 32902
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. This means that for a given
manufacturer's fleet of vehicles produced for sale in the U.S. in a
given regulatory class and model year, the applicable minimum CAFE
requirement (i.e., the numerical value of the 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: The provision at
49 U.S.C. 32902 requires the Secretary to set CAFE standards
(separately for passenger cars and light trucks \29\) at the maximum
feasible levels in each model year. The CAFE Model represents each
model year explicitly, and accounts for the production relationships
between model years.\30\
---------------------------------------------------------------------------
\29\ 49 U.S.C. chapter 329 uses the term ``non-passenger
automobiles,'' while NHTSA uses the term ``light trucks'' in its
CAFE regulations. The terms' meanings are identical.
\30\ For example, a new engine first applied to given vehicle
model/configuration in model year 2020 will most likely be ``carried
forward'' to model year 2021 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:
The provision at 49 U.S.C. 32904 requires the EPA Administrator to
determine CAFE compliance separately for each manufacturers' 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. 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 CO2
standards (because EPA does not have separate standards for domestic
and imported passenger cars).
Minimum CAFE Standards for Domestic Passenger Car Fleets: The
provision at 49 U.S.C. 32902 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 for CAFE standards and sets this requirement aside
for CO2 standards.
Civil Penalties for Noncompliance: The provision at 49 U.S.C. 32912
(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 CAFE standard for a given fleet in
a given model year, 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 for CAFE shortfalls
and provides means to estimate that a manufacturer might stop adding
fuel-saving technologies once continuing to do so would be effectively
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
CO2 standards.
Dual-Fueled and Dedicated Alternative Fuel Vehicles: For purposes
of calculating 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
through MY 2020. After MY 2020, methods for calculating alternative
fuel vehicle (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 alternative fuel vehicle (AFV) models when
NHTSA determines what levels of CAFE standards are maximum feasible.
The CAFE Model therefore has an option to be run in a manner that
excludes the additional application of dedicated AFV technologies in
model years for which maximum feasible standards are under
consideration. As allowed under NEPA for analysis appearing in EISs
informing decisions regarding CAFE standards, the CAFE Model can also
be run without this analytical constraint. The CAFE Model does account
for dual- and alternative fuel vehicles when simulating manufacturers'
potential responses to CO2 standards. For natural gas
vehicles, both dedicated and dual-fueled, EPA has a multiplier of 2.0
for model years 2022-2026.\31\
---------------------------------------------------------------------------
\31\ While EPA is proposing changes to this and other
flexibility provisions in its separate NPRM, for purposes of this
NPRM, the CAFE Model only reflects the current EPA regulatory
flexibilities.
---------------------------------------------------------------------------
ZEV Mandates: The CAFE Model can simulate manufacturers' compliance
with ZEV mandates applicable in California and ``Section 177'' \32\
states. The approach involves identifying specific vehicle model/
configurations that could be replaced with PHEVs or BEVs, and
immediately making these changes in each model year, before beginning
to consider the potential that other technologies could be applied
toward compliance with CAFE or CO2 standards.
---------------------------------------------------------------------------
\32\ 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: The provision at 49 U.S.C.
32903 provides that manufacturers may earn CAFE ``credits'' by
achieving a CAFE level beyond that required of a given fleet in a given
model year, 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 model years, transferred between regulated
classes (domestic passenger cars, imported passenger cars, and light
trucks), and traded between manufacturers. However, credit use is also
subject to specific statutory limits. For example, CAFE compliance
credits can be carried forward a maximum of five model years and
carried back a maximum of three model years. Also, EPCA/EISA caps the
amount of credit 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 explicitly
simulates manufacturers' potential use of credits carried forward from
prior model years or transferred from other fleets.\33\ The provision
at 49
[[Page 49627]]
U.S.C. 32902 prohibits consideration of manufacturers' potential
application of CAFE compliance credits when setting maximum feasible
CAFE standards. The CAFE Model can be operated in a manner that
excludes the application of CAFE credits for a given model year under
consideration for standard setting. For modeling CO2
standards, the CAFE Model does not limit transfers. Insofar as the CAFE
Model can be exercised in a manner that simulates trading of
CO2 compliance credits, such simulations treat trading as
unlimited.\34\
---------------------------------------------------------------------------
\33\ The CAFE Model does not explicitly simulate the potential
that manufacturers would carry CAFE or CO2 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 currently elected not to limit credit trading, the
CAFE Model can be exercised in a manner that simulates unlimited
(a.k.a. ``perfect'') CO2 compliance credit trading
throughout the industry (or, potentially, within discrete trading
``blocs''). NHTSA believes there is significant uncertainty in how
manufacturers may choose to employ 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 those credits rather than
continuing to make technology improvements, it is harder to assume
with confidence that 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 the uncertainty just
discussed, 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 considers borrowing and
trading to involve sufficient risk that it is prudent to support
this proposal with analysis that sets aside the potential that
manufacturers could come to depend widely on borrowing and trading.
While compliance costs in real life may be somewhat different from
what is modeled today as a result of this analytical 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 possibly being lower.
\34\ 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: The provision at 49 U.S.C. 32902
requires the Secretary to set CAFE standards at the maximum feasible
levels, 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. EPCA/EISA authorizes
the Secretary 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 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: In addition, NEPA requires the
Secretary to issue an EIS that documents the estimated impacts of
regulatory alternatives under consideration. The SEIS accompanying this
NPRM 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 SEIS, of impacts on the
global climate, on tropospheric air quality, and on human health.
Other Aspects of Compliance: Beyond these statutory requirements
applicable to DOT and/or EPA are a number of specific technical
characteristics of CAFE and/or CO2 regulations that are also
relevant to the construction of this analysis. For example, EPA has
defined procedures for calculating average CO2 levels, and
has revised procedures for calculating CAFE levels, to reflect
manufacturers' application of ``off-cycle'' technologies that increase
fuel economy (and reduce CO2 emissions). Although too little
information is available to account for these provisions explicitly in
the same way that the agency has accounted for other technologies, the
CAFE Model does include and makes use of inputs reflecting the agency'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 CO2 levels
(not CAFE) based on the use of air conditioner refrigerants with lower
global warming potential (GWP), or on the application of technologies
to reduce refrigerant leakage. In addition, the CAFE Model accounts for
EPA ``multipliers'' for certain alternative fueled vehicles, 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.
Besides the updates to the 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
reflect better the current state of the world and the best current
estimates of future conditions.
A number of assumptions have been updated since the 2020 final rule
for this proposal. While NHTSA would have made these updates as a
matter of course, we note that that the COVID-19 pandemic has been
profoundly disruptive, including in ways directly material to major
analytical inputs such as fuel prices, gross domestic product (GDP),
vehicle production and sales, and highway travel. As discussed below,
NHTSA has updated its ``analysis fleet'' from a model year 2017
reference to a model year 2020 reference, updated estimates of
manufacturers' compliance credit ``holdings,'' updated fuel price
projections to reflect the U.S. Energy Information Administration's
(EIA's) 2021 Annual Energy Outlook (AEO), updated projections of GDP
and related macroeconomic measures, and updated projections of future
highway travel. In addition, through Executive Order 13990, President
Biden has required the formation of an Interagency Working Group (IWG)
on the Social Cost of Greenhouse Gases and charged this body with
updating estimates of the social costs of carbon, nitrous oxide, and
methane. As discussed in the TSD, NHTSA has applied the IWG's interim
guidance, which contains cost estimates (per ton of emissions)
considerably greater than those applied in the analysis supporting the
2020 SAFE rule. These and other updated analytical inputs are discussed
in detail in the TSD. NHTSA seeks comment on the above discussion.
B. What is NHTSA analyzing?
As in the CAFE and CO2 rulemakings in 2010, 2012, and
2020, NHTSA is proposing to set attribute-based CAFE standards defined
by a mathematical function of vehicle footprint, which has observable
correlation with fuel economy. 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.\35\ Thus, the
proposed standards (and regulatory alternatives) 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. Chapter 1.2.3 of the TSD discusses
in detail NHTSA's continued
[[Page 49628]]
reliance on footprint as the relevant attribute in this proposal.
---------------------------------------------------------------------------
\35\ 49 U.S.C. 32902(a)(3)(A).
---------------------------------------------------------------------------
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,\36\ based upon the footprints
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, generally
speaking, smaller vehicles are more capable of achieving higher levels
of fuel economy, mostly because they tend not to have to work as hard
(and therefore require as much energy) to perform their driving task.
Although a manufacturer's fleet average standards could be estimated
throughout the model year 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 production figures. A manufacturer's
calculation of its fleet average standards, as well as its fleets'
average performance at the end of the model year, will thus be based on
the production-weighted average target and performance of each model in
its fleet.\37\
---------------------------------------------------------------------------
\36\ 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.
\37\ 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).
---------------------------------------------------------------------------
For passenger cars, consistent with prior rulemakings, NHTSA is
proposing to define fuel economy targets as shown in Equation III-1.
[GRAPHIC] [TIFF OMITTED] TP03SE21.030
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 per square foot, or gpm, per
square foot) of a line relating fuel 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 III-2.
BILLING CODE 4910-59-P
[[Page 49629]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.031
For light trucks, also consistent with prior rulemakings, NHTSA is
proposing to define fuel economy targets as shown in Equation III-2.
[GRAPHIC] [TIFF OMITTED] TP03SE21.032
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 III-3.
[[Page 49630]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.033
BILLING CODE 4910-59-C
Although the general model of the target function equation is the
same for each vehicle category (passenger cars and light trucks) and
each model year, 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 IV.B of this preamble.
As has been the case since NHTSA began establishing attribute-based
standards, no vehicle need meet the specific applicable fuel economy
target, because compliance with CAFE standards is determined based on
corporate average fuel economy. In this respect, CAFE standards are
unlike, for example, Federal Motor Vehicle Safety Standards (FMVSS) and
certain vehicle criteria pollutant emissions standards where each car
must meet the requirements. CAFE standards apply to the average fuel
economy levels achieved by manufacturers' entire fleets of vehicles
produced for sale in the U.S. Safety standards apply on a vehicle-by-
vehicle basis, such that every single vehicle produced for sale in the
U.S. must, on its own, comply with minimum FMVSS. When first mandating
CAFE standards in the 1970s, Congress specified a more flexible
averaging-based approach that allows some vehicles to ``under comply''
(i.e., fall short of the overall flat standard, or fall short of their
target under attribute-based standards) as long as a manufacturer's
overall fleet is in compliance.
The required CAFE level applicable to a given fleet in a given
model year 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 III-3.
[[Page 49631]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.034
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.
Chapter 1 of the TSD describes the use of attribute-based
standards, generally, and explains the specific decision, in past rules
and for the current rule, to continue to use vehicle footprint as the
attribute over which to vary stringency. That chapter also discusses
the policy in selecting the specific mathematical function; the
methodologies used to develop the current attribute-based standards;
and methodologies previously used to reconsider the mathematical
function for CAFE standards. NHTSA refers readers to the TSD for a full
discussion of these topics.
While Chapter 1 of the TSD explains why the proposed standards for
MYs 2024-2026 continue to be footprint-based, the question has arisen
periodically of whether NHTSA should instead consider multi-attribute
standards, such as those that also depend on weight, torque, power,
towing capability, and/or off-road capability. To date, every time
NHTSA has considered options for which attribute(s) to select, the
agency has concluded that a properly-designed footprint-based approach
provides the best means of achieving the basic policy goals (i.e., by
increasing the likelihood of improved fuel economy across the entire
fleet of vehicles; by reducing disparities between manufacturers'
compliance burdens; and by reducing incentives for manufacturers to
respond to standards in ways that could compromise overall highway
safety) involved in applying an attribute-based standard. At the same
time, footprint-based standards need also to be structured in a way
that furthers the energy and environmental policy goals of EPCA without
creating inappropriate incentives to increase vehicle size in ways that
could increase fuel consumption or compromise safety. That said, as
NHTSA moves forward with the CAFE program, and continues to refine our
understanding of the light-duty vehicle market and trends in vehicle
and highway safety, NHTSA will also continue to revisit whether other
approaches (or other ways of applying the same basic approaches) could
foreseeably provide better means of achieving policy goals.
For example, in the 2021 NAS Report, the committee recommended that
if Congress does not act to remove the prohibition at 49 U.S.C.
32902(h) on considering the fuel economy of dedicated alternative fuel
vehicles (like BEVs) in determining maximum feasible CAFE standards,
then NHTSA should account for the fuel economy benefits of ZEVs by
``setting the standard as a function of a second attribute in addition
to footprint--for example, the expected market share of ZEVs in the
total U.S. fleet of new light-duty vehicles--such that the standards
increase as the share of ZEVs in the total U.S. fleet increases.'' \38\
DOE seconded this suggestion in its comments during interagency review
of this proposal. Chapter 1 of the TSD contains an examination of this
suggestion, and NHTSA seeks comment on whether and how NHTSA might
consider adding electrification as an attribute on which to base CAFE
standards.
---------------------------------------------------------------------------
\38\ National Academies of Sciences, Engineering, and Medicine,
2021. Assessment of Technologies for Improving Fuel Economy of
Light-Duty Vehicles--2025-2035, Washington, DC: The National
Academies Press (hereafter, ``2021 NAS Report''), at Summary
Recommendation 5. Available at https://www.nationalacademies.org/our-work/assessment-of-technologies-for-improving-fuel-economy-of-light-duty-vehicles-phase-3 and for hard-copy review at DOT
headquarters.
---------------------------------------------------------------------------
Changes in the market that have occurred since NHTSA last examined
the appropriateness of the footprint curves have been, for the most
part, consistent with the trends that the agency identified in 2018.
For the most part, the fleet has continued to grow somewhat in vehicle
size, as vehicle manufacturers have continued over the past several
years to reduce their offerings of smaller footprint vehicles and
increase their sales of larger footprint vehicles and continue to sell
many small to mid-size crossovers and SUVs, some of which are
classified as passenger cars and some of which are light trucks.
Although this trend has had the effect of reducing the achieved fuel
economy of the fleet (and thus increasing its carbon dioxide emissions)
as compared to if vehicles had instead remained the same size or gotten
smaller, NHTSA does not believe that there have been sufficiently major
changes in the relationship between footprint and fuel economy over the
last three years to warrant a detailed re-examination of that
relationship as part of this proposal. Moreover, changes to the
footprint curves can significantly affect manufacturers' ability to
comply. Given the available lead time between now and the beginning of
MY 2024, NHTSA believes it is unlikely any potential benefit of
changing the shape of the footprint curves (when we are already
proposing to change standard stringency) would outweigh the costs of
doing so.
NHTSA seeks comment on the choice of footprint as the attribute on
which the proposed standards are based, and particularly seeks comment
on the 2021 NAS report recommendation described above. If commenters
wish to provide comments on possible changes to the attribute(s) on
which fuel economy standards should be based, including approaches for
considering vehicle electrification in ways that would further a zero
emissions fleet as discussed in Chapter 1 of the TSD, NHTSA would
appreciate commenters including a discussion of the timeframe in which
those changes should be made--for example, whether and how much lead
time would be preferable for making such changes, particularly
recognizing the available lead time for MY 2024. NHTSA also seeks
comment on whether, to the extent that vehicle upsizing trends and fuel
economy curves are causally related instead of correlated, it is the
curve shape versus the choice of footprint that creates this
relationship (or, alternatively, whether the relationship if any
derives from vehicle classification). Again, if commenters wish to
provide comments on possible changes to the curve shapes, NHTSA would
appreciate commenters including a discussion of the timeframe in which
those changes should be made.
NHTSA seeks comment on the discussion above and in the TSD.
[[Page 49632]]
C. What inputs does the compliance analysis require?
The CAFE Model applies various technologies to different vehicle
models in each manufacturer's product line to simulate how each
manufacturer might make progress toward compliance with the specified
standard. Subject to a variety of user-controlled constraints, the
model applies technologies based on their relative cost-effectiveness,
as determined by several input assumptions regarding the cost and
effectiveness of each technology, the cost of compliance (determined by
the change in CAFE or CO2 credits, CAFE-related civil
penalties, or value of CO2 credits, depending on the
compliance program being evaluated), and the value of avoided fuel
expenses. For a given manufacturer, the compliance simulation algorithm
applies technologies either until the manufacturer runs out of cost-
effective technologies,\39\ until the manufacturer exhausts all
available technologies, or, if the manufacturer is assumed to be
willing to pay civil penalties or acquire credits from another
manufacturer, until paying civil penalties or purchasing credits
becomes more cost-effective than increasing vehicle fuel economy. At
this stage, the system assigns an incurred technology cost and updated
fuel economy to each vehicle model, as well as any civil penalties
incurred/credits purchased by each manufacturer. This compliance
simulation process is repeated for each model year included in the
study period (through model year 2050 in this analysis).
---------------------------------------------------------------------------
\39\ Generally, the model considers a technology cost-effective
if it pays for itself in fuel savings within 30 months. Depending on
the settings applied, the model can continue to apply technologies
that are not cost-effective rather than choosing other compliance
options; if it does so, it will apply those additional technologies
in order of cost-effectiveness (i.e., most cost-effective first).
---------------------------------------------------------------------------
At the conclusion of the compliance simulation for a given
regulatory scenario the system transitions between compliance
simulation and effects calculations. This is the point where the system
produces a full representation of the registered light-duty vehicle
population in the United States. The CAFE Model then uses this fleet to
generate estimates of the following (for each model year and calendar
year included in the analysis): Lifetime travel, fuel consumption,
carbon dioxide and criteria pollutant emissions, the magnitude of
various economic externalities related to vehicular travel (e.g.,
congestion and noise), and energy consumption (e.g., the economic costs
of short-term increases in petroleum prices, or social damages
associated with GHG emissions). The system then uses these estimates to
measure the benefits and costs associated with each regulatory
alternative (relative to the no-action alternative).
To perform this analysis, the CAFE Model uses millions of data
points contained in several input files that have been populated by
engineers, economists, and safety and environmental program analysts at
both NHTSA and the DOT's Volpe National Transportations Systems Center
(Volpe). In addition, some of the input data comes from modeling and
simulation analysis performed by experts at Argonne National Laboratory
using their Autonomie full vehicle simulation model and BatPaC battery
cost model. Other inputs are derived from other models, such as the
U.S. Energy Information Administration's (EIA's) National Energy
Modeling System (NEMS), Argonne's ``GREET'' fuel-cycle emissions
analysis model, and U.S. EPA's ``MOVES'' vehicle emissions analysis
model. As NHTSA and Volpe are both organizations within DOT, we use DOT
throughout these sections to refer to the collaborative work performed
for this analysis.
This section and Section III.D describe the inputs that the
compliance simulation requires, including an in-depth discussion of the
technologies used in the analysis, how they are defined in the CAFE
Model, how they are characterized on vehicles that already exist in the
market, how they can be applied to realistically simulate
manufacturer's decisions, their effectiveness, and their cost. The
inputs and analyses for the effects calculations, including economic,
safety, and environmental effects, are discussed later in Sections
III.C through III.H. NHTSA seeks comment on the following discussion.
1. Overview of Inputs to the Analysis
As discussed above, the current analysis involves estimating four
major swaths of effects. First, the analysis estimates how the
application of various combinations of technologies could impact
vehicles' costs and fuel economy levels (and CO2 emission
rates). Second, the analysis estimates how vehicle manufacturers might
respond to standards by adding fuel-saving technologies to new
vehicles. Third, the analysis estimates how changes in new vehicles
might impact vehicle sales and operation. Finally, the analysis
estimates how the combination of these changes might impact national-
scale energy consumption, emissions, highway safety, and public health.
There are several CAFE Model input files important to the
discussion these first two steps, and these input files are discussed
in detail later in this section and in Section III.D. The Market Data
file contains the detailed description of the vehicle models and model
configurations each manufacturer produces for sale in the U.S. The file
also contains a range of other inputs that, though not specific to
individual vehicle models, may be specific to individual manufacturers.
The Technologies file identifies about six dozen technologies to be
included in the analysis, indicates when and how widely each technology
can be applied to specific types of vehicles, provides most of the
inputs involved in estimating what costs will be incurred, and provides
some of the inputs involved in estimating impacts on vehicle fuel
consumption and weight.
The CAFE Model also makes use of databases of estimates of fuel
consumption impacts and, as applicable, battery costs for different
combinations of fuel saving technologies.\40\ These databases are
termed the FE1 and FE2 Adjustments databases (the main database and the
database specific to plug-in hybrid electric vehicles, applicable to
those vehicles' operation on electricity) and the Battery Costs
database. DOT developed these databases using a large set of full
vehicle and accompanying battery cost model simulations developed by
Argonne National Laboratory. The Argonne simulation outputs, battery
costs, and other reference materials are also discussed in the
following sections.\41\
---------------------------------------------------------------------------
\40\ To be used as files provided separately from the model and
loaded every time the model is executed, these databases are
prohibitively large, spanning more than a million records and more
than half a gigabyte. To conserve memory and speed model operation,
DOT has integrated the databases into the CAFE Model executable
file. When the model is run, however, the databases are extracted
and placed in an accessible location on the user's disk drive.
\41\ The Argonne workbooks included in the docket for this
proposal include ten databases that contain the outputs of the
Autonomie full vehicle simulations, two summary workbooks of
assumptions used for the full vehicle simulations, a data
dictionary, and the lookup tables for battery costs generated using
the BatPaC battery cost model.
---------------------------------------------------------------------------
The following discussion in this section and in Section III.D
expands on the inputs used in the compliance analysis. Further detail
is included in Chapters 2 and 3 of the TSD accompanying this proposal,
and all input values relevant to the compliance analysis can be seen in
the Market Data, Technologies, fuel consumption and battery cost
database files, and Argonne
[[Page 49633]]
summary files included in the docket for this proposal. As previously
mentioned, other model input files underlie the effects analysis, and
these are discussed in detail in Sections III.C through III.H. NHTSA
seeks comment on the above discussion.
2. The Market Data File
The Market Data file contains the detailed description of the
vehicle models and model configurations each manufacturer produces for
sale in the U.S. This snapshot of the recent light duty vehicle market,
termed the analysis fleet, or baseline fleet, is the starting point for
the evaluation of different stringency levels for future fuel economy
standards. The analysis fleet provides a reference from which to
project how manufacturers could apply additional technologies to
vehicles to cost-effectively improve vehicle fuel economy, in response
to regulatory action and market conditions.\42\ For this analysis, the
MY 2020 light duty fleet was selected as the baseline for further
evaluation of the effects of different fuel economy standards. The
Market Data file also contains a range of other inputs that, though not
specific to individual vehicle models, may be specific to individual
manufacturers.
---------------------------------------------------------------------------
\42\ The CAFE Model does not generate compliance paths a
manufacturer should, must, or will deploy. It is intended as a tool
to demonstrate a compliance pathway a manufacturer could choose. It
is almost certain all manufacturers will make compliance choices
differing from those projected by the CAFE Model.
---------------------------------------------------------------------------
The Market Data file is an Excel spreadsheet that contains five
worksheets. Three worksheets, the Vehicles worksheet, Engines
worksheet, and Transmissions worksheet, characterize the baseline fleet
for this analysis. The three worksheets contain a characterization of
every vehicle sold in MY 2020 and their relevant technology content,
including the engines and transmissions that a manufacturer uses in its
vehicle platforms and how those technologies are shared across
platforms. In addition, the Vehicles worksheet includes baseline
economic and safety inputs linked to each vehicle that allow the CAFE
Model to estimate economic and safety impacts resulting from any
simulated compliance pathway. The remaining two worksheets, the
Manufacturers worksheet and Credits and Adjustments worksheet, include
baseline compliance positions for each manufacturer, including each
manufacturer's starting CAFE credit banks and whether the manufacturer
is willing to pay civil penalties for noncompliance with CAFE
standards, among other inputs.
New inputs have been added for this analysis in the Vehicles
worksheet and Manufacturers worksheet. The new inputs indicate which
vehicles a manufacturer may reasonably be expected to convert to a zero
emissions vehicle (ZEV) at first redesign opportunity, to comply with
several States' ZEV program provisions. The new inputs also indicate if
a manufacturer has entered into an agreement with California to achieve
more stringent CO2 emissions reductions targets than those
promulgated in the 2020 final rule.
The following sections discuss how we built the Market Data file,
including characterizing vehicles sold in MY 2020 and their technology
content, and baseline safety, economic, and manufacturer compliance
positions. A detailed discussion of the Market Data file development
process is in TSD Chapter 2.2. NHTSA seeks comment on the below
discussion and the agency's approach to developing the Market Data file
for this proposal.
(a) Characterizing Vehicles and Their Technology Content
The Market Data file integrates information from many sources,
including manufacturer compliance submissions, publicly available
information, and confidential business information. At times, DOT must
populate inputs using analyst judgment, either because information is
still incomplete or confidential, or because the information does not
yet exist.\43\ For this analysis DOT uses mid-model year 2020
compliance data as the basis of the analysis fleet. The compliance data
is supplemented for each vehicle nameplate with manufacturer
specification sheets, usually from the manufacturer media website, or
from online marketing brochures.\44\ For additional information about
how specification sheets inform MY 2020 vehicle technology assignments,
see the technology specific assignments sections in Section III.D.
---------------------------------------------------------------------------
\43\ Forward looking refresh/redesign cycles are one example of
when analyst judgement is necessary.
\44\ The catalogue of reference specification sheets (broken
down by manufacturer, by nameplate) used to populate information in
the market data file is available in the docket.
---------------------------------------------------------------------------
DOT uses the mid-model year 2020 compliance data to create a row on
the Vehicles worksheet in the Market Data file for each vehicle (or
vehicle variant \45\) that lists a certification fuel economy, sales
volume, regulatory class, and footprint. DOT identifies which
combination of modeled technologies reasonably represents the fuel
saving technologies already on each vehicle, and assigns those
technologies to each vehicle, either on the Vehicles worksheet, the
Engines worksheet, or the Transmissions worksheet. The fuel saving
technologies considered in this analysis are listed in Table III-1.
---------------------------------------------------------------------------
\45\ The market data file often includes a few rows for vehicles
that may have identical certification fuel economies, regulatory
classes, and footprints (with compliance sales volumes divided out
among rows), because other pieces of information used in the CAFE
Model may be dissimilar. For instance, in the reference materials
used to create the Market Data file, for a nameplate curb weight may
vary by trim level (with premium trim levels often weighing more on
account of additional equipment on the vehicle), or a manufacturer
may provide consumers the option to purchase a larger fuel tank size
for their vehicle. These pieces of information may not impact the
observed compliance position directly, but curb weight (in relation
to other vehicle attributes) is important to assess mass reduction
technology already used on the vehicle, and fuel tank size is
directly relevant to saving time at the gas pump, which the CAFE
Model uses when calculating the value of avoided time spent
refueling.
---------------------------------------------------------------------------
BILLING CODE 4910-59-P
[[Page 49634]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.035
[[Page 49635]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.036
[[Page 49636]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.037
BILLING CODE 4910-59-C
For additional information on the characterization of these
technologies (including the cost, prevalence in the 2020 fleet,
effectiveness estimates, and considerations for their adoption) see the
appropriate technology section in Section III.D or TSD Chapter 3.
DOT also assigns each vehicle a technology class. The CAFE Model
uses the technology class (and engine class, discussed below) in the
Market Data file to reference the most relevant technology costs for
each vehicle, and fuel saving technology combinations. We assign each
vehicle in the fleet a technology class using a two-step algorithm that
takes into account key characteristics of vehicles in the fleet
compared to the baseline characteristics of each technology class.\46\
As discussed further in Section III.C.4.b), there are ten technology
classes used in the CAFE analysis that span five vehicle types and two
performance variants. The
[[Page 49637]]
technology class algorithm and assignment process is discussed in more
detail in TSD Chapter 2.4.2.
---------------------------------------------------------------------------
\46\ Baseline 0 to 60 mph accelerations times are assumed for
each technology class as part of the Autonomie full vehicle
simulations. DOT calculates class baseline curb weights and
footprints by averaging the curb weights and footprints of vehicles
within each technology class as assigned in previous analyses.
---------------------------------------------------------------------------
We also assign each vehicle an engine technology class so that the
CAFE Model can reference the powertrain costs in the Technologies file
that most reasonably align with the observed vehicle. DOT assigns
engine technology classes for all vehicles, including electric
vehicles. If an electric powertrain replaces and internal combustion
engine, the electric motor specifications may be different (and hence
costs may be different) depending on the capabilities of the internal
combustion engine it is replacing, and the costs in the technologies
file (on the engine tab) account for the power output and capability of
the gasoline or electric drivetrain.
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 simulates part sharing by
implementing shared engines, shared transmissions, and shared mass
reduction platforms. Vehicles sharing a part (as recognized in the CAFE
Model), will adopt fuel saving technologies affecting that part
together. To account for parts sharing across products, vehicle model/
configurations that share engines are assigned the same engine
code,\47\ vehicle model/configurations that share transmissions have
the same transmission code, and vehicles that adopt mass reduction
technologies together share the same platform. For more information
about engine codes, transmission codes, and mass reduction platforms
see TSD Chapter 3.
---------------------------------------------------------------------------
\47\ Engines (or transmissions) may not be exactly identical, as
specifications or vehicle integration features may be different.
However, the architectures are similar enough that it is likely the
powertrain systems share research and development (R&D), tooling,
and production resources in a meaningful way.
---------------------------------------------------------------------------
Manufacturers often introduce fuel saving technologies at a major
redesign of their product or adopt technologies at minor refreshes in
between major product redesigns. To support the CAFE Model accounting
for new fuel saving technology introduction as it relates to product
lifecycle, the Market Data file includes a projection of redesign and
refresh years for each vehicle. DOT projects future redesign years and
refresh years based on the historical cadence of that vehicle's product
lifecycle. For new nameplates, DOT considers the manufacturer's
treatment of product lifecycles for past products in similar market
segments. When considering year-by-year analysis of standards, the
sizing of redesign and refresh intervals will affect projected
compliance pathways and how quickly manufacturers can respond to
standards. TSD Chapter 2.2.1.7 includes additional information about
the product design cycles assumed for this proposal based on historical
manufacturer product design cycles.
The Market Data file also includes information about air
conditioning (A/C) and off-cycle technologies, but the information is
not currently broken out at a row level, vehicle by vehicle.\48\
Instead, historical data (and forecast projections, which are used for
analysis regardless of regulatory scenario) are listed by manufacturer,
by fleet on the Credits and Adjustments worksheet of the Market Data
file. Section III.D.8 shows model inputs specifying estimated
adjustments (all in grams/mile) for improvements to air conditioner
efficiency and other off-cycle energy consumption, and for reduced
leakage of air conditioner refrigerants with high global warming
potential (GWP). DOT estimated future values based on an expectation
that manufacturers already relying heavily on these adjustments would
continue do so, and that other manufacturers would, over time, also
approach the limits on adjustments allowed for such improvements.
---------------------------------------------------------------------------
\48\ Regulatory provisions regarding off-cycle technologies are
new, and manufacturers have only recently begun including related
detailed information in compliance reporting data. For this
analysis, though, such information was not sufficiently complete to
support a detailed representation of the application of off-cycle
technology to specific vehicle model/configurations in the MY 2020
fleet.
---------------------------------------------------------------------------
(b) Characterizing Baseline Safety, Economic, and Compliance Positions
In addition to characterizing vehicles and their technology
content, the Market Data file contains a range of other inputs that,
though not specific to individual vehicle models, may be specific to
individual manufacturers, or that characterize baseline safety or
economic information.
First, the CAFE Model considers the potential safety effect of mass
reduction technologies and crash compatibility of different vehicle
types. Mass reduction technologies lower the vehicle's curb weight,
which may improve crash compatibility and safety, or not, depending on
the type of vehicle. DOT assigns each vehicle in the Market Data file a
safety class that best aligns with the mass-size-safety analysis. This
analysis is discussed in more detail in Section III.H of this proposal
and TSD Chapter 7.
The CAFE Model also includes procedures to consider the direct
labor impacts of manufacturer's 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),\49\ and the dealership employment associated with new
vehicle sales. The Market Data file therefore includes baseline labor
information, by vehicle. Sales volumes also influence total estimated
direct labor projections in the analysis.
---------------------------------------------------------------------------
\49\ Percent U.S. content was informed by the 2020 Part 583
American Automobile Labeling Act Reports, appearing on NHTSA's
website.
---------------------------------------------------------------------------
We hold the percent U.S. content constant for each vehicle row for
the duration of the analysis. In practice, this may not be the case.
Changes to trade policy and tariff policy may affect percent U.S.
content in the future. Also, some technologies may be more or less
likely to be produced in the U.S., and if that is the case, their
adoption could affect future U.S. content. NHTSA does not have data at
this time to support varying the percent U.S. content.
We also hold the labor hours projected in the Market Data file per
unit transacted at dealerships, per unit produced for final assembly,
per unit produced for engine assembly, and per unit produced for
transmission assembly constant for the duration of the analysis, and
project that the origin of these activities to remain unchanged. In
practice, it is reasonable to expect that plants could move locations,
or engine and transmission technologies are replaced by another fuel
saving technology (like electric motors and fixed gear boxes) that
could require a meaningfully different amount of assembly labor hours.
NHTSA does not have data at this time to support varying labor hours
projected in the Market Data file, but we will continue to explore
methods to estimate the direct labor impacts of manufacturer's
responses to CAFE standards in future analyses.
As observed from Table III-2, manufacturers employ U.S. labor with
varying intensity. In many cases, vehicles certifying in the light
truck (LT) regulatory class have a larger percent U.S. content than
vehicles certifying in the passenger car (PC) regulatory class.
[[Page 49638]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.038
Next, manufacturers may over-comply with CAFE standards and bank
so-called over compliance credits. As discussed further in Section
III.C.7, manufacturers may use these credits later, sell them to other
manufacturers, or let them expire. The CAFE Model does not explicitly
trade credits between and among manufacturers, but staff have adjusted
starting credit banks in the Market Data file to reflect trades that
are likely to happen when the simulation begins (in MY 2020).
Considering information manufacturers have reported regarding
compliance credits, and considering recent manufacturers' compliance
positions, DOT estimates manufacturers' potential use of compliance
credits in earlier MYs. This aligns to an extent that represents how
manufacturers could deplete their credit banks rather than producing
high volume vehicles with fuel saving technologies in earlier MYs. This
also avoids the unrealistic application of technologies for
manufacturers in early analysis years that typically rely on credits.
For a complete discussion about how this data is collected and assigned
in the Market Data file, see TSD Chapter 2.2.2.3.
---------------------------------------------------------------------------
\50\ Tesla does not have internal combustion engines, or multi-
speed transmissions, even though they are identified as producing
engine and transmission systems in the United States in the Market
Data file.
---------------------------------------------------------------------------
The Market Data file also includes assumptions about a vehicle
manufacturer's preferences towards civil penalty payments. EPCA
requires that if a manufacturer does not achieve compliance with a CAFE
standard in a given model year and cannot apply credits sufficient to
cover the compliance shortfall, the manufacturer must pay civil
penalties (i.e., fines) to the Federal Government. If inputs indicate
that a manufacturer treats civil penalty payment as an economic choice
(i.e., one to be taken if doing so would be economically preferable to
applying further technology toward compliance), the CAFE Model, when
evaluating the manufacturer's response to CAFE standards in a given
model year, will apply fuel-saving technology only up to the point
beyond which doing so would be more expensive (after subtracting the
value of avoided fuel outlays) than paying civil penalties.
For this analysis, DOT exercises the CAFE Model with inputs
treating all manufacturers as treating civil penalty
[[Page 49639]]
payment as an economic choice through model year 2023. While DOT
expects that only manufacturers with some history of paying civil
penalties would actually treat civil penalty payment as an acceptable
option, the CAFE Model does not currently simulate compliance credit
trading between manufacturers, and DOT expects that this treatment of
civil penalty payment will serve as a reasonable proxy for compliance
credit purchases some manufacturers might actually make through model
year 2023. These input assumptions for model years through 2023 reduce
the potential that the model will overestimate technology application
in the model years leading up to those for which the agency is
proposing new standards. As in past CAFE rulemaking analyses (except
that supporting the 2020 final rule), DOT has treated manufacturers
with some history of civil penalty payment (i.e., BMW, Daimler, FCA,
Jaguar-Land Rover, Volvo, and Volkswagen) as continuing to treat civil
penalty payment as an acceptable option beyond model year 2023, but has
treated all other manufacturers as unwilling to do so beyond model year
2023.
Next, the CAFE Model uses an ``effective cost'' metric to evaluate
options to apply specific technologies to specific engines,
transmissions, and vehicle model configurations. Expressed on a $/
gallon basis, the analysis computes this metric by subtracting the
estimated values of avoided fuel outlays and civil penalties from the
corresponding technology costs, and then dividing the result by the
quantity of avoided fuel consumption. The analysis computes the value
of fuel outlays over a ``payback period'' representing the
manufacturer's expectation that the market will be willing to pay for
some portion of fuel savings achieved through higher fuel economy. Once
the model has applied enough technology to a manufacturer's fleet to
achieve compliance with CAFE standards (and CO2 standards
and ZEV mandates) in a given model year, the model will apply any
further fuel economy improvements estimated to produce a negative
effective cost (i.e., any technology applications for which avoided
fuel outlays during the payback period are larger than the
corresponding technology costs). As discussed above in Section III.A
and below in Section III.C, DOT anticipates that manufacturers are
likely to act as if the market is willing to pay for avoided fuel
outlays expected during the first 30 months of vehicle operation.
We seek comment on whether this expectation is appropriate, or
whether some other amount of time should be used. If commenters believe
a different amount of time should be used for the payback assumption,
it would be most helpful if commenters could define the amount of time,
provide an explanation of why that amount of time is preferable,
provide any data or information on which the amount of time is based,
and provide any discussion of how changing this assumption would
interact with other elements in the analysis.
In addition, the Market Data file includes two new sets of inputs
for this analysis. In 2020, five vehicle manufacturers reached a
voluntary commitment with the state of California to improve the fuel
economy of their future nationwide fleets above levels required by the
2020 final rule. For this analysis, compliance with this agreement is
in the baseline case for designated manufacturers. The Market Data file
contains inputs indicating whether each manufacturer has committed to
exceed Federal requirements per this agreement.
Finally, when considering other standards that may affect fuel
economy compliance pathways, DOT includes projected zero emissions
vehicles (ZEV) that would be required for manufacturers to meet
standards in California and Section 177 States, per the waiver granted
under the Clean Air Act. To support the inclusion of the ZEV program in
the analysis, DOT identifies specific vehicle model/configurations that
could adopt BEV technology in response to the ZEV program, independent
of CAFE standards, at the first redesign opportunity. These ZEVs are
identified in the Market Data file as future BEV200s, BEV300s, or
BEV400s. Not all announced BEV nameplates appear in the MY 2020 Market
Data file; in these cases, in consultation with CARB, DOT used the
volume from a comparable vehicle in the manufacturer's Market Data file
portfolio as a proxy. The Market Data file also includes information
about the portion of each manufacturer's sales that occur in California
and Section 177 states, which is helpful for determining how many ZEV
credits each manufacturer will need to generate in the future to comply
with the ZEV program with their own portfolio in the rulemaking
timeframe. These new procedures are described in detail below and in
TSD Chapter 2.3.
3. Simulating the Zero Emissions Vehicle Program
California's Zero Emissions Vehicle (ZEV) program is one part of a
program of coordinated standards that the California Air Resources
Board (CARB) has enacted to control emissions of criteria pollutants
and greenhouse gas emissions from vehicles. The program began in 1990,
within the low-emission vehicle (LEV) regulation,\51\ and has since
expanded to include eleven other states.\52\ These states may be
referred to as Section 177 states, in reference to Section 177 of the
Clean Air Act's grant of authority to allow these states to adopt
California's air quality standards,\53\ but it is important to note
that not all Section 177 states have adopted the ZEV program
component.\54\ In the following discussion of the incorporation of the
ZEV program into the CAFE Model, any reference to the Section 177
states refers to those states that have adopted California's ZEV
program requirements.
---------------------------------------------------------------------------
\51\ California Air Resource Board (CARB), Zero-Emission Vehicle
Program. California Air Resources Board. Accessed April 12, 2021.
https://ww2.arb.ca.gov/our-work/programs/zero-emission-vehicle-program/about.
\52\ At the time of writing, the Section 177 states that have
adopted the ZEV program are Colorado, Connecticut, Maine, Maryland,
Massachusetts, New Jersey, New York, Oregon, Rhode Island, Vermont,
and Washington. See Vermont Department of Environmental
Conservation, Zero Emission Vehicles. Accessed April 12, 2021.
https://dec.vermont.gov/air-quality/mobile-sources/
zev#:~:text=To%20date%2C%2012%20states%20have,ZEVs%20over%20the%20nex
t%20decade.
\53\ Section 177 of the Clean Air Act allows other states to
adopt California's air quality standards.
\54\ At the time of writing, Delaware and Pennsylvania are the
two states that have adopted the LEV standards, but not the ZEV
portion.
---------------------------------------------------------------------------
To account for the ZEV program, and particularly as other states
have recently adopted California's ZEV standards, DOT includes the main
provisions of the ZEV program in the CAFE Model's analysis of
compliance pathways. As explained below, incorporating the ZEV program
into the model includes converting vehicles that have been identified
as potential ZEV candidates into battery-electric vehicles (BEVs) at
the first redesign opportunity, so that a manufacturer's fleet meets
calculated ZEV credit requirements. Since ZEV program compliance
pathways happen independently from the adoption of fuel saving
technology in response to increasing CAFE standards, the ZEV program is
considered in the baseline of the analysis, and in all other regulatory
alternatives.
Through its ZEV program, California requires that all manufacturers
that sell cars within the state meet ZEV credit standards. The current
credit requirements are calculated based on manufacturers' California
sales volumes. Manufacturers primarily earn ZEV credits through the
production of BEVs, fuel cell vehicles (FCVs), and
[[Page 49640]]
transitional zero-emissions vehicles (TZEVs), which are vehicles with
partial electrification, namely plug-in hybrids (PHEVs). Total credits
are calculated by multiplying the credit value each ZEV receives by the
vehicle's volume.
The ZEV and PHEV/TZEV credit value per vehicle is calculated based
on the vehicle's range; ZEVs may earn up to 4 credits each and PHEVs
with a US06 all-electric range capability of 10 mi or higher receive an
additional 0.2 credits on top of the credits received based on all-
electric range.\55\ The maximum PHEV credit amount available per
vehicle is 1.10.\56\ Note however that CARB only allows intermediate-
volume manufacturers to meet their ZEV credit requirements through PHEV
production.\57\
---------------------------------------------------------------------------
\55\ US06 is one of the drive cycles used to test fuel economy
and all-electric range, specifically for the simulation of
aggressive driving. See Dynamometer Drive Schedules [verbar] Vehicle
and Fuel Emissions Testing [verbar] U.S. EPA for more information,
as well as Section III.C.4 and Section III.D.3.d).
\56\ 13 CCR 1962.2(c)(3).
\57\ 13 CCR 1962.2(c)(3).
---------------------------------------------------------------------------
DOT's method for simulating the ZEV program involves several steps;
first, DOT calculates an approximate ZEV credit target for each
manufacturer based on the manufacturer's national sales volumes, share
of sales in Section 177 states, and the CARB credit requirements. Next,
DOT identifies a general pathway to compliance that involves accounting
for manufacturers' potential use of ZEV overcompliance credits or other
credit mechanisms, and the likelihood that manufacturers would choose
to comply with the requirements with BEVs rather than PHEVs or other
types of compliant vehicles, in addition to other factors. For this
analysis, as discussed further below, DOT consulted with CARB to
determine reasonable assumptions for this compliance pathway. Finally,
DOT identifies vehicles in the MY 2020 analysis fleet that
manufacturers could reasonably adapt to comply with the ZEV standards
at the first opportunity for vehicle redesign, based on publicly
announced product plans and other information. Each of these steps is
discussed in turn, below, and a more detailed description of DOT's
simulation of the ZEV program is included in TSD Chapter 2.3.
The CAFE Model is designed to present outcomes at a national scale,
so the ZEV analysis considers the Section 177 states as a group as
opposed to estimating each state's ZEV credit requirements
individually. To capture the appropriate volumes subject to the ZEV
requirement, DOT calculates each manufacturer's total market share in
Section 177 states. DOT also calculates the overall market share of
ZEVs in Section 177 states, in order to estimate as closely as possible
the number of predicted ZEVs we expect all manufacturers to sell in
those states. These shares are then used to scale down national-level
information in the CAFE Model to ensure that we represent only Section
177 states in the final calculation of ZEV credits that we project each
manufacturer to earn in future years.
DOT uses model year 2019 National Vehicle Population Profile (NVPP)
from IHS Markit--Polk to calculate these percentages.\58\ 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, which allows staff to identify the different
types of ZEVs manufacturers sell in the Section 177 state group. DOT
may make use of future Polk data in updating the analysis for the final
rule and may include other states that join the ZEV program after the
publication of this proposal, if necessary.
---------------------------------------------------------------------------
\58\ National Vehicle Population Profile (NVPP) 2020, IHS
Markit--Polk. At the time of the analysis, model year 2019 data from
the NVPP contained the most current estimate of market shares by
manufacturer, and best represented the registered vehicle population
on January 1, 2020.
---------------------------------------------------------------------------
We calculate sales volumes for the ZEV credit requirement based on
each manufacturer's future assumed market share in Section 177 states.
DOT decided to carry each manufacturer's ZEV market shares forward to
future years, after examination of past market share data from model
year 2016, from the 2017 version of the NVPP.\59\ Comparison of these
data to the 2020 version showed that manufacturers' market shares
remain fairly constant in terms of geographic distribution. Therefore,
we determined that it was reasonable to carry forward the recently
calculated market shares to future years.
---------------------------------------------------------------------------
\59\ National Vehicle Population Profile (NVPP) 2017, IHS
Markit--Polk.
---------------------------------------------------------------------------
We calculate total credits required for ZEV compliance by
multiplying the percentages from CARB's ZEV requirement schedule by the
Section 177 state volumes. CARB's credit percentage requirement
schedule for the years covered in this analysis begins at 9.5% in 2020
and ramps up in increments to 22% by 2025.\60\ Note that the
requirements do not currently change after 2025.\61\
---------------------------------------------------------------------------
\60\ See 13 CCR 1962.2(b). The percentage credit requirements
are as follows: 9.5% in 2020, 12% in 2021, 14.5% in 2022, 17% in
2023, 19.5% in 2024, and 22% in 2025 and onward.
\61\ 13 CCR 1962.2(b).
---------------------------------------------------------------------------
We generate national sales volume predictions for future years
using the Compliance Report, a CAFE Model output file that includes
simulated sales by manufacturer, fleet, and model year. We use a
Compliance Report that corresponds to the baseline scenario of 1.5% per
year increases in standards for both passenger car and light truck
fleets. The resulting national sales volume predictions by manufacturer
are then multiplied by each manufacturer's total market share in the
Section 177 states to capture the appropriate volumes in the ZEV
credits calculation. Required credits by manufacturer, per year, are
determined by multiplying the Section 177 state volumes by CARB's ZEV
credit percentage requirement. These required credits are subsequently
added to the CAFE Model inputs as targets for manufacturer compliance
with ZEV standards in the CAFE baseline.
The estimated ZEV credit requirements serve as a target for
simulating ZEV compliance in the baseline. To achieve this, DOT
determines a modeling philosophy for ZEV pathways, reviews various
sources for information regarding upcoming ZEV programs, and inserts
those programs into the analysis fleet inputs. As manufacturers can
meet ZEV standards in a variety of different ways, using various
technology combinations, the analysis must include certain simplifying
assumptions in choosing ZEV pathways. We made these assumptions in
conjunction with guidance from CARB staff. The following sections
discuss the approach used to simulate a pathway to ZEV program
compliance in this analysis.
First, DOT targeted 2025 compliance, as opposed to assuming
manufacturers would perfectly comply with their credit requirements in
each year prior to 2025. This simplifying assumption was made upon
review of past history of ZEV credit transfers, existing ZEV credit
banks, and redesign schedules. DOT focused on integrating ZEV
technology throughout that timeline with the target of meeting 2025
obligations; thus, some manufacturers are estimated to over-comply or
under-comply, depending on their individual situations, in the years
2021-2024.
Second, DOT determined that the most reasonable way to model ZEV
compliance would be to allow under-compliance in certain cases and
assume that some manufacturers would not meet their ZEV obligation on
their own in 2025. Instead, these manufacturers were assumed to prefer
to purchase credits from another manufacturer with a credit surplus.
Reviews of past ZEV credit transfers between manufacturers informed the
decision to make this
[[Page 49641]]
simplifying assumption.\62\ CARB advised that for these manufacturers,
the CAFE Model should still project that each manufacturer meet
approximately 80% of their ZEV requirements with technology included in
their own portfolio. Manufacturers that were observed to have generated
many ZEV credits in the past or had announced major upcoming BEV
initiatives were projected to meet 100% of their ZEV requirements on
their own, without purchasing ZEV credits from other manufacturers.\63\
---------------------------------------------------------------------------
\62\ See https://ww2.arb.ca.gov/our/work/programs/advanced-clean-cars-program/zev-program-zero-emission-vehicle-credit-balances
for past credit balances and transfer information.
\63\ The following manufacturers were assumed to meet 100% ZEV
compliance: Ford, General Motors, Hyundai, Kia, Jaguar Land Rover,
and Volkswagen Automotive. Tesla was also assumed to meet 100% of
its required standards, but the analyst team did not need to add
additional ZEV substitutes to the baseline for this manufacturer.
---------------------------------------------------------------------------
Third, DOT agreed that manufacturers would meet their ZEV credit
requirements in 2025 though the production of BEVs. As discussed above,
manufacturers may choose to build PHEVs or FCVs to earn some portion of
their required ZEV credits. However, DOT projected that manufacturers
would rely on BEVs to meet their credit requirements, based on reviews
of press releases and industry news, as well as discussion with CARB.
Since nearly all manufacturers have announced some plans to produce
BEVs at a scale meaningful to future ZEV requirements, DOT agreed that
this was a reasonable assumption.\64\ Furthermore, as CARB only allows
intermediate-volume manufacturers to meet their ZEV credit requirements
through the production of PHEVs, and the volume status of these few
manufacturers could change over the years, assuming BEV production for
ZEV compliance is the most straightforward path.
---------------------------------------------------------------------------
\64\ See TSD Chapter 2.3 for a list of potential BEV programs
recently announced by manufacturers.
---------------------------------------------------------------------------
Fourth, to account for the new BEV programs announced by some
manufacturers, DOT identified vehicles in the 2020 fleet that closely
matched the upcoming BEVs, by regulatory class, market segment, and
redesign schedule. DOT made an effort to distribute ZEV candidate
vehicles by CAFE regulatory class (light truck, passenger car), by
manufacturer, in a manner consistent with the 2020 manufacturer fleet
mix. Since passenger car and light truck mixes by manufacturer could
change in response to the CAFE policy alternative under consideration,
this effort was deemed necessary in order to avoid redistributing the
fleet mix in an unrealistic manner. However, there were some exceptions
to this assumption, as some manufacturers are already closer to meeting
their ZEV obligation through 2025 with BEVs currently produced, and
some manufacturers underperform their compliance targets more so in one
fleet than another. In these cases, DOT deviated from keeping the LT/PC
mix of BEVs evenly distributed across the manufacturer's portfolio.\65\
---------------------------------------------------------------------------
\65\ The GM light truck and passenger car distribution is one
such example.
---------------------------------------------------------------------------
DOT then identified future ZEV programs that could plausibly
contribute towards the ZEV requirements for each manufacturer by 2025.
To obtain this information, DOT examined various sources, including
trade press releases, industry announcements, and investor reports. In
many cases, these BEV programs are in addition to programs already in
production.\66\ Some manufacturers have not yet released details of
future electric vehicle programs at the time of writing, but have
indicated goals of reaching certain percentages of electric vehicles in
their portfolios by a specified year. In these cases, DOT reviewed the
manufacturer's current fleet characteristics as well as the
aspirational information in press releases and other news in order to
make reasonable assumptions about the vehicle segment and range of
those future BEVs. DOT may reassign some manufacturer's ZEV programs in
the analysis fleet for the final rule based on stakeholder comments or
other public information releases that occur in time for the final rule
analysis.
---------------------------------------------------------------------------
\66\ Examples of BEV programs already in production include the
Nissan Leaf and the Chevrolet Bolt.
---------------------------------------------------------------------------
Overall, analysts assumed that manufacturers would lean towards
producing BEV300s rather than BEV200s, based on the information
reviewed and an initial conversation with CARB.\67\ Phase-in caps were
also considered, especially for BEV200, with the understanding that the
CAFE Model will always pick BEV200 before BEV300 or BEV400, until the
quantity of BEV200s is exhausted. See Section III.D.3.c) for details
regarding BEV phase-in caps.
---------------------------------------------------------------------------
\67\ BEV300s are 300-mile range battery-electric vehicles. See
Section III.D.3.b) for further information regarding electrification
fleet assignments.
---------------------------------------------------------------------------
BEVs, especially BEVs with smaller battery packs and less range,
are less likely to meet all the performance needs of traditional pickup
truck owners today. However, new markets for BEVs may emerge,
potentially in the form of electric delivery trucks and some light-duty
electric truck applications in state and local government. The extent
to which BEVs will be used in these and other new markets is difficult
to project. DOT did identify certain trucks as upcoming BEVs for ZEV
compliance, and these BEVs were expected to have higher ranges, due to
the specific performance needs associated with these vehicles. Outside
of the ZEV inputs described here, the CAFE Model does not handle the
application of BEV technology with any special considerations as to
whether the vehicle is a pickup truck or not. Comments from
manufacturers are solicited on this issue.
Finally, in order to simulate manufacturers' compliance with their
particular ZEV credits target, 142 rows in the analysis fleet were
identified as substitutes for future ZEV programs. As discussed above,
the analysis fleet summarizes the roughly 13.6 million light-duty
vehicles produced and sold in the United States in the 2020 model year
with more than 3,500 rows, each reflecting information for one vehicle
type observed. Each row includes the vehicle's nameplate and trim
level, the sales volume, engine, transmission, drive configuration,
regulatory class, projected redesign schedule, and fuel saving
technologies, among other attributes.
As the goal of the ZEV analysis is to simulate compliance with the
ZEV program in the baseline, and the analysis fleet only contains
vehicles produced during model year 2020, DOT identified existing
models in the analysis fleet that shared certain characteristics with
upcoming BEVs. DOT also focused on identifying substitute vehicles with
redesign years similar to the future BEV's introduction year. The sales
volumes of those existing models, as predicted for 2025, were then used
to simulate production of the upcoming BEVs. DOT identified a
combination of rows that would meet the ZEV target, could contribute
productively towards CAFE program obligations (by manufacturer and by
fleet), and would introduce BEVs in each manufacturer's portfolio in a
way that reasonably aligned with projections and announcements. DOT
tagged each of these rows with information in the Market Data file,
instructing the CAFE Model to apply the specified BEV technology to the
row at the first redesign year, regardless of the scenario or type of
CAFE or GHG simulation.
The CAFE Model does not optimize compliance with the ZEV mandate;
it relies upon the inputs described in this section in order to
estimate each
[[Page 49642]]
manufacturer's resulting ZEV credits. The resulting amount of ZEV
credits earned by manufacturer for each model year can be found in the
CAFE Model's Compliance file.
Not all ZEV-qualifying vehicles in the U.S. earn ZEV credits, as
they are not all sold in states that have adopted ZEV regulations. In
order to reflect this in the CAFE Model, which only estimates sales
volumes at the national level, the percentages calculated for each
manufacturer are used to scale down the national-level volumes.
Multiplying national-level ZEV sales volumes by these percentages
ensures that only the ZEVs sold in Section 177 states count towards the
ZEV credit targets of each manufacturer.\68\ See Section 5.8 of the
CAFE Model Documentation for a detailed description of how the model
applied these ZEV technologies and any changes made to the model's
programming for the incorporation of the ZEV program into the baseline.
---------------------------------------------------------------------------
\68\ The single exception to this assumption is Mazda, as Mazda
has not yet produced any ZEV-qualifying vehicles at the time of
writing. Thus, the percentage of ZEVs sold in Section 177 states
cannot be calculated from existing data. However, Mazda has
indicated its intention to produce ZEV-qualifying vehicles in the
future, so DOT assumed that 100% of future ZEVs would be sold in
Section 177 states for the purposes of estimating ZEV credits in the
CAFE Model.
---------------------------------------------------------------------------
As discussed above, DOT made an effort to distribute the newly
identified ZEV candidates between CAFE regulatory classes (light truck
and passenger car) in a manner consistent with the proportions seen in
the 2020 analysis fleet, by manufacturer. As mentioned previously,
there were a few exceptions to this assumption in cases where
manufacturers' regulatory class distribution of current or planned ZEV
programs clearly differed from their regulatory class distribution as a
whole.
In some instances, the regulatory distribution of flagged ZEV
candidates leaned towards a higher portion of PCs. The reasoning behind
this differs in each case, but there is an observed pattern in the 2020
analysis fleet of fewer BEVs being light trucks, especially pickups.
The 2020 analysis fleet contains no BEV pickups in the light truck
segment. The slow emergence of electric pickups could be linked to the
specific performance needs associated with pickup trucks. However, the
market for BEVs may emerge in unexpected ways that are difficult to
project. Examples of this include anticipated electric delivery trucks
and light-duty electric trucks used by state and local governments. Due
to these considerations, DOT tagged some trucks as BEVs for ZEV, and
expected that these would generally be of higher ranges.
TSD Chapter 2.3 includes more information about the process we use
to simulate ZEV program compliance in this analysis.
4. Technology Effectiveness Values
The next input we use to simulate manufacturers' decision-making
processes for the year-by-year application of technologies to specific
vehicles are estimates of how effective each technology would be at
reducing fuel consumption. For this analysis, we use full-vehicle
modeling and simulation to estimate the fuel economy improvements
manufacturers could make to a fleet of vehicles, considering the
vehicles' technical specifications and how combinations of technologies
interact. Full-vehicle modeling and simulation uses physics-based
models to predict how combinations of technologies perform as a full
system under defined conditions. We use full vehicle simulations
performed in Autonomie, a physics-based full-vehicle modeling and
simulation software developed and maintained by the U.S. Department of
Energy's Argonne National Laboratory.\69\
---------------------------------------------------------------------------
\69\ Islam, E. S., A. Moawad, N. Kim, R. Vijayagopal, and A.
Rousseau. A Detailed Vehicle Simulation Process to Support CAFE
Standards for the MY 2024-2026 Analysis. ANL/ESD-21/9 [hereinafter
Autonomie model documentation].
---------------------------------------------------------------------------
A model is a mathematical representation of a system, and
simulation is the behavior of that mathematical representation over
time. In this analysis, the model is a mathematical representation of
an entire vehicle,\70\ including its individual components 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 the model's behavior
over test cycles, including the 2-cycle laboratory compliance tests (or
2-cycle tests),\71\ to determine how the individual components
interact.
---------------------------------------------------------------------------
\70\ Each full vehicle model in this analysis is composed of
sub-models, which is why the full vehicle model could also be
referred to as a full system model, composed of sub-system models.
\71\ EPA's compliance test cycles are used to measure the fuel
economy of a vehicle. For readers unfamiliar with this process, it
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'' or ``HWFET''), and they have not changed substantively
since 1975. Each cycle is a designated speed trace (of vehicle speed
versus time) that all certified vehicles must follow during testing.
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 mph.
---------------------------------------------------------------------------
Using full-vehicle modeling and simulation to estimate technology
efficiency improvements has two primary advantages over using single or
limited point estimates. An analysis using single or limited point
estimates may assume that, for example, one fuel economy-improving
technology with an effectiveness value of 5 percent by itself and
another technology with an effectiveness value of 10 percent by itself,
when applied together achieve an additive improvement of 15 percent.
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. Any oversimplification of these
complex interactions leads to less accurate and often overestimated
effectiveness estimates.
In addition, because manufacturers often implement several fuel-
saving technologies simultaneously when redesigning a vehicle, it is
difficult to isolate the effect of individual technologies using
laboratory measurement of production vehicles alone. 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.
An important feature of this analysis is that the incremental
effectiveness of each technology and combinations of technologies
should be accurate and relative to a consistent baseline vehicle. For
this analysis, the baseline absolute fuel economy value for each
vehicle in the analysis fleet is based on CAFE compliance data for each
make and model.\72\ The absolute fuel economy values of the full
vehicle simulations are
[[Page 49643]]
used only to determine incremental effectiveness and are never used
directly to assign an absolute fuel economy value to any vehicle model
or configuration. For subsequent technology changes, we apply the
incremental effectiveness values of one or more technologies to the
baseline fuel economy value to determine the absolute fuel economy
achieved for applying the technology change.
---------------------------------------------------------------------------
\72\ See Section III.C.2 for further discussion of CAFE
compliance data in the Market Data file.
---------------------------------------------------------------------------
As an example, if a Ford F-150 2-wheel drive crew cab and short bed
in the analysis fleet has a fuel economy value of 30 mpg for CAFE
compliance, 30 mpg will be considered the reference absolute fuel
economy value. A similar full vehicle model node in the Autonomie
simulation may begin with an average fuel economy value of 32 mpg, and
with incremental addition of a specific technology X its fuel economy
improves to 35 mpg, a 9.3 percent improvement. In this example, the
incremental fuel economy improvement (9.3 percent) from technology X
would be applied to the F-150's 30 mpg absolute value.
We determine the incremental effectiveness of technologies as
applied to the thousands of unique vehicle and technology combinations
in the analysis fleet. Although, as mentioned above, full-vehicle
modeling and simulation reduces the work and time required to assess
the impact of moving a vehicle from one technology state to another, it
would be impractical--if not impossible--to build a unique vehicle
model for every individual vehicle in the analysis fleet. Therefore, as
discussed in the following sections, the Autonomie analysis relies on
ten vehicle technology class models that are representative of large
portions of the analysis fleet vehicles. The vehicle technology classes
ensure that key vehicle characteristics are reasonably represented in
the full vehicle models. The next sections discuss the details of the
technology effectiveness analysis input specifications and assumptions.
NHTSA seeks comment on the following discussion.
(a) Full Vehicle Modeling and Simulation
As discussed above, for this analysis we use Argonne's full vehicle
modeling tool, Autonomie, to build vehicle models with different
technology combinations and simulate the performance of those models
over regulatory test cycles. The difference in the simulated
performance between full vehicle models, with differing technology
combination, is used to determine effectiveness values. We consider
over 50 individual technologies as inputs to the Autonomie
modeling.\73\ These inputs consist of engine technologies, transmission
technologies, powertrain electrification, lightweighting, aerodynamic
improvements, and tire rolling resistance improvements. Section III.D
broadly discusses each of the technology groupings definitions, inputs,
and assumptions. A deeper discussion of the Autonomie modeled
subsystems, and how inputs feed the sub models resulting in outputs, is
contained in the Autonomie model documentation that accompanies this
analysis. The 50 individual technologies, when considered with the ten
vehicle technology classes, result in over 1.1 million individual
vehicle technology combination models. For additional discussion on the
full vehicle modeling used in this analysis see TSD Chapter 2.
---------------------------------------------------------------------------
\73\ See Autonomie model documentation; ANL--All
Assumptions_Summary_NPRM_022021.xlsx; ANL--Data Dictionary_January
2021.xlsx.
---------------------------------------------------------------------------
While Argonne built full-vehicle models and ran simulations for
many combinations of technologies, it did not simulate literally every
single vehicle model/configuration in the analysis fleet. Not only
would it be impractical to assemble the requisite detailed information
specific to each vehicle/model configuration, much of which would
likely only be provided on a confidential basis, doing so would
increase the scale of the simulation effort by orders of magnitude.
Instead, Argonne simulated ten different vehicle types, corresponding
to the five ``technology classes'' generally used in CAFE analysis over
the past several rulemakings, each with two performance levels and
corresponding vehicle technical specifications (e.g., small car, small
performance car, pickup truck, performance pickup truck, etc.).
Technology classes are a means of specifying common technology
input assumptions for vehicles that share similar characteristics.
Because each vehicle technology class has unique characteristics, the
effectiveness of technologies and combinations of technologies is
different for each technology class. Conducting Autonomie simulations
uniquely for each technology class provides a specific set of
simulations and effectiveness data for each technology class. In this
analysis the technology classes are compact cars, midsize cars, small
SUVs, large SUVs, and pickup trucks. In addition, for each vehicle
class there are two levels of performance attributes (for a total of 10
technology classes). The high performance and low performance vehicles
classifications allow for better diversity in estimating technology
effectiveness across the fleet.
For additional discussion on the development of the vehicle
technology classes used in this analysis and the attributes used to
characterize each vehicle technology class, see TSD Chapter 2.4 and the
Autonomie model documentation.
Before any simulation is initiated in Autonomie, Argonne must
``build'' a vehicle by assigning reference technologies and initial
attributes to the components of the vehicle model representing each
technology class. The reference technologies are baseline technologies
that represent the first step on each technology pathway used in the
analysis. For example, a compact car is built by assigning it a
baseline engine (DOHC, VVT, port fuel injection (PFI)), a baseline
transmission (AT5), a baseline level of aerodynamic improvement
(AERO0), a baseline level of rolling resistance improvement (ROLL0), a
baseline level of mass reduction technology (MR0), and corresponding
attributes from the Argonne vehicle assumptions database like
individual component weights. A baseline vehicle will have a unique
starting point for the simulation and a unique set of assigned inputs
and attributes, based on its technology class. Argonne collected over a
hundred baseline vehicle attributes to build the baseline vehicle for
each technology class. In addition, to account for the weight of
different engine sizes, like 4-cylinder versus 8-cylinder or
turbocharged versus naturally aspirated engines, Argonne developed a
relationship curve between peak power and engine weight based on the
A2Mac1 benchmarking data. Argonne uses the developed relationship to
estimate mass for all engines. For additional discussion on the
development and optimization of the baseline vehicle models and the
baseline attributes used in this analysis see TSD Chapter 2.4 and the
Autonomie model documentation.
The next step in the process is to run a powertrain sizing
algorithm that ensures the built vehicle meets or exceeds defined
performance metrics, including low-speed acceleration (time required to
accelerate from 0-60 mph), high-speed passing acceleration (time
required to accelerate from 50-80 mph), gradeability (the ability of
the vehicle to maintain constant 65 miles per hour speed on a six
percent upgrade), and towing capacity. Together, these performance
criteria are widely used by the automotive industry as metrics to
quantify vehicle performance attributes
[[Page 49644]]
that consumers observe and that are important for vehicle utility and
customer satisfaction.
As with conventional vehicle models, electrified vehicle models
were also built from the ground up. For MY 2020, the U.S. market has an
expanded number of available hybrid and electric vehicle models. To
capture improvements for electrified vehicles for this analysis, DOT
applied a mass regression analysis process that considers electric
motor weight versus electric motor power (similar to the regression
analysis for internal combustion engine weights) for vehicle models
that have adopted electric motors. Benchmarking data for hybrid and
electric vehicles from the A2Mac1 database were analyzed to develop a
regression curve of electric motor peak power versus electric motor
weight.\74\
---------------------------------------------------------------------------
\74\ See Autonomie model documentation, Chapter 5.2.10 Electric
Machines System Weight.
---------------------------------------------------------------------------
We maintain performance neutrality in the full vehicle simulations
by resizing engines, electric machines, and hybrid electric vehicle
battery packs at specific incremental technology steps. To address
product complexity and economies of scale, engine resizing is limited
to specific incremental technology changes that would typically be
associated with a major vehicle or engine redesign. This is intended to
reflect manufacturers' comments to DOT on how they consider engine
resizing and product complexity, and DOT's observations on industry
product complexity. A detailed discussion on powertrain sizing can be
found in TSD Chapter 2.4 and in the Autonomie model documentation.
After all vehicle class and technology combination models have been
built, Autonomie simulates the vehicles' performance on test cycles to
calculate the effectiveness improvement of adding fuel-economy-
improving technologies to the vehicle. Simulating vehicles' performance
using tests and procedures specified by Federal law and regulations
minimizes the potential variation in determining technology
effectiveness.
For vehicles with conventional powertrains and micro hybrids,
Autonomie simulates the vehicles per EPA 2-cycle test procedures and
guidelines.\75\ For mild and full hybrid electric vehicles and FCVs,
Autonomie simulates the vehicles using the same EPA 2-cycle test
procedure and guidelines, and the drive cycles are repeated until the
initial and final state of charge are within a SAE J1711 tolerance. For
PHEVs, Autonomie simulates vehicles per similar procedures and
guidelines as prescribed in SAE J1711.\76\ For BEVs Autonomie simulates
vehicles per similar procedures and guidelines as prescribed in SAE
J1634.\77\
---------------------------------------------------------------------------
\75\ 40 CFR part 600.
\76\ PHEV testing is broken into several phases based on SAE
J1711: Charge-sustaining on the city cycle and HWFET cycle, and
charge-depleting on the city and HWFET cycles.
\77\ SAE J1634. ``Battery Electric Vehicle Energy Consumption
and Range Test Procedure.'' July 12, 2017.
---------------------------------------------------------------------------
(b) Performance Neutrality
The purpose of the CAFE analysis is to examine the impact of
technology application that can improve fuel economy. When the fuel
economy-improving technology is applied, often the manufacturer must
choose how the technology will affect the vehicle. The advantages of
the new technology can either be completely applied to improving fuel
economy or be used to increase vehicle performance while maintaining
the existing fuel economy, or some mix of the two effects.
Historically, vehicle performance has improved over the years as more
technology is applied to the fleet. The average horsepower is the
highest that it has ever been; all vehicle types have improved
horsepower by at least 42 percent compared to the 1978 model year, and
pickup trucks have improved by 48 percent.\78\ Fuel economy has also
improved, but the horsepower and acceleration trends show that not 100
percent of technological improvements have been applied to fuel
savings. While future trends are uncertain, the past trends suggest
vehicle performance is unlikely to decrease, as it seems reasonable to
assume that customers will, at a minimum, demand vehicles that offer
the same utility as today's fleet.
---------------------------------------------------------------------------
\78\ ``The 2020 EPA Automotive Trends Report, Greenhouse Gas
Emissions, Fuel Economy, and Technology since 1975,'' EPA-420-R-21-
003, January 2021 [hereinafter 2020 EPA Automotive Trends Report].
---------------------------------------------------------------------------
For this rulemaking analysis, DOT analyzed technology pathways
manufacturers could use for compliance that attempt to maintain vehicle
attributes, utility, and performance. Using this approach allows DOT to
assess the costs and benefits of potential standards under a scenario
where consumers continue to get the similar vehicle attributes and
features, other than changes in fuel economy. The purpose of
constraining vehicle attributes is to simplify the analysis and reduce
variance in other attributes that consumers may value across the
analyzed regulatory alternatives. This allows for a streamlined
accounting of costs and benefits by not requiring the values of other
vehicle attributes that trade off with fuel economy.
To confirm minimal differences in performance metrics across
regulatory alternatives, DOT analyzed the sales-weighted average 0-60
mph acceleration performance of the entire simulated vehicle fleet for
MYs 2020 and 2029. The analysis compared performance under the baseline
standards and preferred alternative. This analysis identified that the
analysis fleet under no action standards in MY 2029 had a 0.77 percent
worse 0-60 mph acceleration time than under the preferred alternative,
indicating there is minimal difference in performance between the
alternatives. This assessment shows that for this analysis, the
performance difference is minimal across regulatory alternatives and
across the simulated model years, which allows for fair, direct
comparison among the alternatives. Further details about this
assessment can be found in TSD Chapter 2.4.5.
(c) Implementation in the CAFE Model
The CAFE Model uses two elements of information from the large
amount of data generated by the Autonomie simulation runs: Battery
costs, and fuel consumption on the city and highway cycles. DOT
combines the fuel economy information from the two cycles to produce a
composite fuel economy for each vehicle, and for each fuel used in dual
fuel vehicles. The fuel economy information for each simulation run is
converted into a single value for use in the CAFE Model.
In addition to the technologies in the Autonomie simulation, the
CAFE Model also incorporated a handful of technologies not explicitly
simulated in Autonomie. These technologies' performance either could
not be captured on the 2-cycle test, or there was no robust data usable
as an input for full-vehicle modeling and simulation. The specific
technologies are discussed in the individual technology sections below
and in TSD Chapter 3. To calculate fuel economy improvements
attributable to these additional technologies, estimates of fuel
consumption improvement factors were developed and scale
multiplicatively when applied together. See TSD Chapter 3 for a
complete discussion on how these factors were developed. The Autonomie-
simulated results and additional technologies are combined, forming a
single dataset used by the CAFE Model.
Each line in the CAFE Model dataset represents a unique combination
of technologies. DOT organizes the records using a unique technology
state vector,
[[Page 49645]]
or technology key (tech key), that describes the technology content
associated with each unique record. The modeled 2-cycle fuel economy
(miles per gallon) of each combination is converted into fuel
consumption (gallons per mile) and then normalized relative to a
baseline tech key. The improvement factors used by the model are a
given combination's fuel consumption improvement relative to the
baseline tech key in its technology class.
The tech key format was developed by recognizing that most of the
technology pathways are unrelated and are only logically linked to
designate the direction in which technologies are allowed to progress.
As a result, it is possible to condense the paths into groups based on
the specific technology. These groups are used to define the technology
vector, or tech key. The following technology groups defined the tech
key: Engine cam configuration (CONFIG), VVT engine technology (VVT),
VVL engine technology (VVL), SGDI engine technology (SGDI), DEAC engine
technology (DEAC), non-basic engine technologies (ADVENG), transmission
technologies (TRANS), electrification and hybridization (ELEC), low
rolling resistance tires (ROLL), aerodynamic improvements (AERO), mass
reduction levels (MR), EFR engine technology (EFR), electric accessory
improvement technologies (ELECACC), LDB technology (LDB), and SAX
technology (SAX). This summarizes to a tech key with the following
fields: CONFIG; VVT; VVL; SGDI; DEAC; ADVENG; TRANS; ELEC; ROLL; AERO;
MR; EFR; ELECACC; LDB; SAX. It should be noted that some of the fields
may be blank for some tech key combinations. These fields will be left
visible for the examples below, but blank fields may be omitted from
tech keys shown elsewhere in the documentation.
As an example, a technology state vector describing a vehicle with
a SOHC engine, variable valve timing (only), a 6-speed automatic
transmission, a belt-integrated starter generator, rolling resistance
(level 1), aerodynamic improvements (level 2), mass reduction (level
1), electric power steering, and low drag brakes, would be specified as
``SOHC; VVT; ; ; ; ; AT6; BISG; ROLL10; AERO20; MR1; ; EPS; LDB ; .''
\79\
---------------------------------------------------------------------------
\79\ In the example tech key, the series of semicolons between
VVT and AT6 correspond to the engine technologies which are not
included as part of the combination, while the gap between MR1 and
EPS corresponds to EFR and the omitted technology after LDB is SAX.
The extra semicolons for omitted technologies are preserved in this
example for clarity and emphasis and will not be included in future
examples.
---------------------------------------------------------------------------
Once a vehicle is assigned (or mapped) to an appropriate tech key,
adding a new technology to the vehicle simply represents progress from
a previous tech key to a new tech key. The previous tech key refers to
the technologies that are currently in use on a vehicle. The new tech
key is determined, in the simulation, by adding a new technology to the
combination represented by the previous state vector while
simultaneously removing any technologies that are superseded by the
newly added one.
For example, start with a vehicle with the tech key: SOHC; VVT;
AT6; BISG; ROLL10; AERO20; MR1; EPS; LDB. Assume the simulation is
evaluating PHEV20 as a candidate technology for application on this
vehicle. The new tech key for this vehicle is computed by removing
SOHC, VVT, AT6, and BISG technologies from the previous state
vector,\80\ and adding PHEV20, resulting a tech key that looks like
this: PHEV20; ROLL10; AERO20; MR1; EPS; LDB.
---------------------------------------------------------------------------
\80\ For more discussion of how the CAFE Model handles
technology supersession, see S4.5 of the CAFE Model Documentation.
---------------------------------------------------------------------------
From here, the simulation obtains a fuel economy improvement factor
for the new combination of technologies and applies that factor to the
fuel economy of a vehicle in the analysis fleet. The resulting
improvement is applied to the original compliance fuel economy value
for a discrete vehicle in the MY 2020 analysis fleet.
5. Defining Technology Adoption in the Rulemaking Timeframe
As discussed in Section III.C.2, starting with a fixed analysis
fleet (for this analysis, the model year 2020 fleet indicated in
manufacturers' early CAFE compliance data), the CAFE Model estimates
ways each manufacturer could potentially apply specific fuel-saving
technologies to specific vehicle model/configurations in response to,
among other things (such as fuel prices), CAFE standards,
CO2 standards, commitments some manufacturers have made to
CARB's ``Framework Agreement'', and ZEV mandates imposed by California
and several other States. The CAFE Model follows a year-by-year
approach to simulating manufacturers' potential decisions to apply
technology, accounting for multiyear planning within the context of
estimated schedules for future vehicle redesigns and refreshes during
which significant technology changes may most practicably be
implemented.
The modeled technology adoption for each manufacturer under each
regulatory alternative depends on this representation of multiyear
planning, and on a range of other factors represented by other model
characteristics and inputs, such as the logical progression of
technologies defined by the model's technology pathways; the
technologies already present in the analysis fleet; inputs directing
the model to ``skip'' specific technologies for specific vehicle model/
configurations in the analysis fleet (e.g., because secondary axle
disconnect cannot be applied to 2-wheel-drive vehicles, and because
manufacturers already heavily invested in engine turbocharging and
downsizing are unlikely to abandon this approach in favor of using high
compression ratios); inputs defining the sharing of engines,
transmissions, and vehicle platforms in the analysis fleet; the model's
logical approach to preserving this sharing; inputs defining each
regulatory alternative's specific requirements; inputs defining
expected future fuel prices, annual mileage accumulation, and valuation
of avoided fuel consumption; and inputs defining the estimated efficacy
and future cost (accounting for projected future ``learning'' effects)
of included technologies; inputs controlling the maximum pace the
simulation is to ``phase in'' each technology; and inputs further
defining the availability of each technology to specific technology
classes.
Two of these inputs--the ``phase-in cap'' and the ``phase-in start
year''--apply to the manufacturer's entire estimated production and,
for each technology, define a share of production in each model year
that, once exceeded, will stop the model from further applying that
technology to that manufacturer's fleet in that model year. The
influence of these inputs varies with regulatory stringency and other
model inputs. For example, setting the inputs to allow immediate 100%
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
[[Page 49646]]
all of these inputs are set at levels that do not limit the simulation
at all.
As discussed below, for the most advanced engines (advanced
cylinder deactivation, variable compression ratio, variable
turbocharger geometry, and turbocharging with cylinder deactivation),
DOT has specified phase-in caps and phase-in start years that limit the
pace at which the analysis shows the technology being adopted in the
rulemaking timeframe. For example, this analysis applies a 34% phase-in
cap and MY 2019 phase-in start year for advanced cylinder deactivation
(ADEAC), meaning that in MY 2021 (using a MY 2020 fleet, the analysis
begins simulating further technology application in MY 2021), the model
will stop adding ADEAC to a manufacturer's MY 2021 fleet once ADEAC
reaches more than 68% penetration, because 34% x (2021-2019) = 34% x 2
= 68%.
This analysis also applies phase-in caps and corresponding start
years to prevent the simulation from showing inconceivable rates of
applying battery-electric vehicles (BEVs), such as showing that a
manufacturer producing very few BEVs in MY 2020 could plausibly replace
every product with a 300- or 400-mile BEV by MY 2025. Also, as
discussed in Section III.D.4, 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 mass reduction
(20% and 28.2% 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.
6. Technology Costs
DOT estimates present and future costs for fuel-saving technologies
taking into consideration the type of vehicle, or type of engine if
technology costs vary by application. These cost estimates are based on
three main inputs. First, direct manufacturing costs (DMCs), or the
component and labor costs of producing and assembling the physical
parts and systems, are estimated assuming high volume production. DMCs
generally do not include the indirect costs of tools, capital
equipment, financing costs, engineering, sales, administrative support
or return on investment. DOT accounts for these indirect costs via a
scalar markup of direct manufacturing costs (the retail price
equivalent, or RPE). Finally, costs for technologies may change over
time as industry streamlines design and manufacturing processes. To
reflect this, DOT estimates potential cost improvements with learning
effects (LE). The retail cost of equipment 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 direct
manufacturing costs, is important to account for the real-world price
effects of a technology, as well as market realities. Absent a
Government mandate, motor vehicle manufacturers will not undertake
expensive development and production efforts to implement technologies
without realistic prospects of consumers being willing to pay enough
for such technology to allow for the manufacturers to recover their
investment.
(a) Direct Manufacturing Costs
Direct manufacturing costs (DMCs) are the component and assembly
costs of the physical parts and systems that make up a complete
vehicle. The analysis used agency-sponsored tear-down studies of
vehicles and parts to estimate the DMCs of individual technologies, in
addition to independent tear-down studies, other publications, and
confidential business information. In the simplest cases, the agency-
sponsored studies produced results that confirmed third-party industry
estimates and aligned with confidential information provided by
manufacturers and suppliers. In cases with a large difference between
the tear-down study results and credible independent sources, DOT
scrutinized the study assumptions, and sometimes revised or updated the
analysis accordingly.
Due to the variety of technologies and their applications, and the
cost and time required to conduct detailed tear-down analyses, the
agency did not sponsor teardown studies for every technology. In
addition, some fuel-saving technologies were considered that are pre-
production or are sold in very small pilot volumes. For those
technologies, DOT could not conduct a tear-down study to assess costs
because the product is not yet in the marketplace for evaluation. In
these cases, DOT relied upon third-party estimates and confidential
information from suppliers and manufacturers; however, there are some
common pitfalls with relying on confidential business information to
estimate costs. The agency and the source may have had incongruent or
incompatible definitions of ``baseline.'' The source may have provided
DMCs at a date many years in the future, and assumed very high
production volumes, important caveats to consider for agency analysis.
In addition, a source, under no contractual obligation to DOT, may
provide incomplete and/or misleading information. In other cases,
intellectual property considerations and strategic business
partnerships may have contributed to a manufacturer's cost information
and could be difficult to account for in the CAFE Model as not all
manufacturers may have access to proprietary technologies at stated
costs. The agency carefully evaluates new information in light of these
common pitfalls, especially regarding emerging technologies.
While costs 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, DOT uses the best information available at the
time of the analysis and will continue to update cost assumptions for
any future analysis. The discussion of each category of technologies in
Section III.D (e.g., engines, transmissions, electrification) and
corresponding TSD Chapter 3 summarizes the specific cost estimates DOT
applied for this analysis.
(b) Indirect Costs (Retail Price Equivalent)
As discussed above, direct costs represent the cost associated with
acquiring raw materials, fabricating parts, and assembling vehicles
with the various technologies manufacturers are expected to use to meet
future CAFE standards. They include materials, labor, and variable
energy costs required to produce and assemble the vehicle. However,
they do not include overhead costs required to develop and produce the
vehicle, costs incurred by manufacturers or dealers to sell vehicles,
or the profit manufacturers and dealers make from their investments.
All of these items contribute to the price consumers ultimately pay for
the vehicle. These components of retail prices are illustrated in Table
III-3 below.
[[Page 49647]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.039
To estimate the impact of higher vehicle prices on consumers, both
direct and indirect costs must be considered. To estimate total
consumer costs, DOT multiplies direct manufacturing costs by an
indirect cost factor to represent the average price for fuel-saving
technologies at retail.
Historically, the method most commonly used to estimate indirect
costs of producing a motor vehicle has been the retail price equivalent
(RPE). 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.
Figure III-4 indicates that 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. 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 exceeded
1.6 or fallen below 1.4.\81\ 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. Figure III-4
illustrates the historical relationship between retail prices and
direct manufacturing costs.\82\
---------------------------------------------------------------------------
\81\ 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.
\82\ Rogozhin, A., Gallaher, M., & McManus, W., 2009, Automobile
Industry Retail Price Equivalent and Indirect Cost Multipliers.
Report by RTI International to Office of Transportation Air Quality.
U.S. Environmental Protection Agency, RTI Project Number
0211577.002.004, February, Research Triangle Park, NC.
Spinney, B.C., Faigin, B., Bowie, N., & St. Kratzke, 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, U.S. Department of Transportation.
---------------------------------------------------------------------------
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.
[[Page 49648]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.040
It is also important to note that direct costs associated with any
specific technology will change over time as some combination of
learning and resource price changes occurs. Resource costs, such as the
price of steel, can fluctuate over time and can experience real long-
term trends in either direction, depending on supply and demand.
However, the normal learning process generally reduces direct
production costs as manufacturers refine production techniques and seek
out less costly parts and materials for increasing production volumes.
By contrast, this learning process does not generally influence
indirect costs. The implied RPE for any given technology would thus be
expected to grow over time as direct costs decline relative to indirect
costs. The RPE for any given year is based on direct costs of
technologies at different stages in their learning cycles, and that may
have different implied RPEs than they did in previous years. 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
learning effects on direct costs, a higher average in later years.
The RPE has been used in all NHTSA safety and most previous CAFE
rulemakings to estimate costs. In 2011, the National Academy of
Sciences recommended RPEs of 1.5 for suppliers and 2.0 for in-house
production be used to estimate total costs.\83\ The Alliance of
Automobile Manufacturers also advocates these values as appropriate
markup factors for estimating costs of technology changes.\84\ In their
2015 report, the National Academy of Sciences recommend 1.5 as an
overall RPE markup.\85\ An RPE of 2.0 has also been adopted by a
coalition of environmental and research groups (Northeast States Center
for a Clean Air Future (NESCCAF), International Council on Clean
Transportation (ICCT), Southwest Research Institute, and TIAX-LLC) in a
report on reducing heavy truck emissions, and 2.0 is recommended by the
U.S. Department of Energy for estimating the cost of hybrid-electric
and automotive fuel cell costs (see Vyas et al. (2000) in Table III-4
below). Table III-4 below also lists other estimates of the RPE. Note
that all RPE estimates vary between 1.4 and 2.0, with most in the 1.4
to 1.7 range.
---------------------------------------------------------------------------
\83\ Effectiveness and Impact of Corporate Average Fuel Economy
Standards, Washington, DC--The National Academies Press; NRC, 2011.
\84\ Communication from Chris Nevers (Alliance) to Christopher
Lieske (EPA) and James Tamm (NHTSA), http://www.regulations.gov
Docket ID Nos. NHTSA-2018-0067; EPA-HQ-OAR-2018-0283, p.143.
\85\ National Research Council 2015. Cost, Effectiveness, and
Deployment of Fuel Economy Technologies for Light Duty Vehicles.
Washington, DC: The National Academies Press. https://doi.org/10.17226/21744 [hereinafter 2015 NAS report].
---------------------------------------------------------------------------
Table III-4--Alternate Estimates of the RPE \86\
---------------------------------------------------------------------------
\86\ Duleep, K.G. 2008 Analysis of Technology Cost and Retail
Price. Presentation to Committee on Assessment of Technologies for
Improving Light Duty Vehicle Fuel Economy, January 25, Detroit, MI.;
Jack Faucett Associates, September 4, 1985. Update of EPA's Motor
Vehicle Emission Control Equipment Retail Price Equivalent (RPE)
Calculation Formula. Chevy Chase, MD--Jack Faucett Associates;
McKinsey & Company, October 2003. Preface to the Auto Sector Cases.
New Horizons--Multinational Company Investment in Developing
Economies, San Francisco, CA.; NRC (National Research Council),
2002. Effectiveness and Impact of Corporate Average Fuel Economy
Standards, Washington, DC--The National Academies Press; NRC, 2011.
Assessment of Fuel Economy Technologies for Light Duty Vehicles.
Washington, DC--The National Academies Press; Cost, Effectiveness,
and Deployment of Fuel Economy Technologies in Light Duty Vehicles.
Washington, DC--The National Academies Press, 2015; Sierra Research,
Inc., November 21, 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, Sacramento,
CA--Sierra Research, Inc.; Vyas, A. Santini, D., & Cuenca, R. 2000.
Comparison of Indirect Cost Multipliers for Vehicle Manufacturing.
Center for Transportation Research, Argonne National Laboratory,
April. Argonne, Ill.
---------------------------------------------------------------------------
[[Page 49649]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.041
The RPE has thus enjoyed widespread use and acceptance by a variety
of governmental, academic, and industry organizations.
In past rulemakings, a second type of indirect cost multiplier has
also been examined. Known as the ``Indirect Cost Multiplier'' (ICM)
approach, ICMs were first examined alongside the RPE approach in the
2010 rulemaking regarding standards for MYs 2012-2016 (75 FR 25324, May
7, 2010). Both methods have been examined in subsequent rulemakings.
Consistent with the 2020 final rule, we continue to employ the RPE
approach to account for indirect manufacturing costs. The RPE accounts
for indirect costs like engineering, sales, and administrative support,
as well as other overhead costs, business expenses, warranty costs, and
return on capital considerations. A detailed discussion of indirect
cost methods and the basis for our use of the RPE to reflect these
costs is available in the Final Regulatory Impact Analysis (FRIA) for
the 2020 final rule.\87\
---------------------------------------------------------------------------
\87\ Final Regulatory Impact Analysis, The Safer Affordable
Fuel-Efficient (SAFE) Vehicles Rule for Model Year 2021-2026
Passenger Cars and Light Trucks, USDOT, EPA, March 2020, at 354-76.
---------------------------------------------------------------------------
(c) Stranded Capital Costs
The idea behind stranded capital is that 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.
As DOT has 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 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. The agency will monitor these
trends to assess the role of stranded capital moving forward.
(d) Cost Learning
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. Typically, a representation of this cost
learning, or learning curves, reflects initial learning rates that are
relatively high, followed by slower learning as additional improvements
are made and production efficiency peaks. This eventually produces an
asymptotic shape to the learning curve, as small percent decreases are
applied to gradually declining cost levels. These learning curve
estimates are applied to various technologies that are used to meet
CAFE standards.
We estimate cost learning by considering methods established by
T.P. Wright and later expanded upon by J.R. Crawford.88 89
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 rate or progress ratio, where a lower rate implies faster
learning as cumulative
[[Page 49650]]
production increases. J.R. Crawford expanded upon Wright's learning
curve theory to develop a single unit cost model, that 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.
---------------------------------------------------------------------------
\88\ Wright, T.P., Factors Affecting the Cost of Airplanes.
Journal of Aeronautical Sciences, Vol. 3 (1936), at 124-25.
Available at http://www.uvm.edu/pdodds/research/papers/others/1936/wright1936a.pdf.
\89\ Crawford, J.R., Learning Curve, Ship Curve, Ratios, Related
Data, Burbank, California-Lockheed Aircraft Corporation (1944).
---------------------------------------------------------------------------
As pictured in Figure III-5, Wright's learning curve shows the
first unit is produced at a cost of $1,000. Initially cost per unit
falls rapidly for each successive unit produced. However, as production
continues, cost falls more gradually at a decreasing rate. For each
doubling of cumulative production at any level, cost per unit declines
20 percent, so that 80 percent of cost is retained. The CAFE Model uses
the basic approach by Wright, where cost reduction is estimated by
applying a fixed percentage to the projected cumulative production of a
given fuel economy technology.
[GRAPHIC] [TIFF OMITTED] TP03SE21.042
The analysis accounts for learning effects with model year-based
cost learning forecasts for each technology that reduces direct
manufacturing costs over time. We evaluate the historical use of
technologies, and reviews industry forecasts to estimate future volumes
to develop the model year-based technology cost learning curves.
The following section discusses the development of model year-based
cost learning forecasts for this analysis, including how the approach
has evolved from the 2012 rulemaking for MY 2017-2025 vehicles, and how
the progress ratios were developed for different technologies
considered in the analysis. Finally, we discuss how these learning
effects are applied in the CAFE Model.
(1) Time Versus Volume-Based Learning
For the 2012 joint CAFE and GHG rulemaking, DOT developed learning
curves as a function of vehicle model year.\90\ Although the concept of
this methodology is derived from Wright's cumulative production volume-
based learning curve, its application for CAFE technologies was more of
a function of time. More than a dozen learning curve schedules were
developed, varying between fast and slow learning, and assigned to each
technology corresponding to its level of complexity and maturity. The
schedules were applied to the base year of direct manufacturing cost
and incorporate a percentage of cost reduction by model year, declining
at a decreasing rate through the technology's production life. Some
newer technologies experience 20 percent cost reductions for
introductory model years, while mature or less complex technologies
experience 0-3 percent cost reductions over a few years.
---------------------------------------------------------------------------
\90\ 77 FR 62624 (Oct. 15, 2012).
---------------------------------------------------------------------------
In their 2015 report to Congress, the National Academy of Sciences
(NAS) recommended NHTSA should ``continue to conduct and review
empirical evidence for the cost reductions that occur in the automobile
industry with volume, especially for large-volume technologies that
will be relied on to meet the CAFE/GHG standards.'' \91\
---------------------------------------------------------------------------
\91\ National Research Council 2015. Cost, Effectiveness, and
Deployment of Fuel Economy Technologies for Light-Duty Vehicles.
Washington, DC: The National Academies Press. https://doi.org/10.17226/21744.
---------------------------------------------------------------------------
In response, we incorporated statically projected cumulative volume
production data of fuel economy-improving technologies, representing an
improvement over the previously used time-based method. Dynamic
projections of cumulative production are not feasible with current CAFE
Model capabilities, so one set of projected cumulative production data
for most vehicle technologies was developed for the purpose of
determining cost impact. We obtained historical cumulative production
data for many technologies produced and/or sold in the U.S. to
establish a starting point for learning schedules. Groups of similar
technologies or technologies of similar complexity may share identical
learning schedules.
The slope of the learning curve, which determines the rate at which
cost reductions occur, has been estimated using research from an
extensive literature review and automotive cost tear-down reports (see
below). The slope of the learning curve is derived from the progress
ratio of manufacturing automotive and other mobile source technologies.
(2) Deriving the Progress Ratio Used in This Analysis
Learning curves vary among different types of manufactured
products. Progress ratios can range from 70 to 100
[[Page 49651]]
percent, where 100 percent indicates no learning can be achieved.\92\
Learning effects tend to be greatest in operations where workers often
touch the product, while effects are less substantial in operations
consisting of more automated processes. As automotive manufacturing
plant processes become increasingly automated, a progress ratio towards
the higher end would seem more suitable. We incorporated findings from
automotive cost-teardown studies with EPA's 2015 literature review of
learning-related studies to estimate a progress ratio used to determine
learning schedules of fuel economy-improving technologies.
---------------------------------------------------------------------------
\92\ Martin, J., ``What is a Learning Curve?'' Management and
Accounting Web, University of South Florida, available at: https://www.maaw.info/LearningCurveSummary.htm.
---------------------------------------------------------------------------
EPA's literature review examined and summarized 20 studies related
to learning in manufacturing industries and mobile source
manufacturing.\93\ The studies focused on many industries, including
motor vehicles, ships, aviation, semiconductors, and environmental
energy. Based on several criteria, EPA selected five studies providing
quantitative analysis from the mobile source sector (progress ratio
estimates from each study are summarized in Table III-5, below).
Further, those studies expand on Wright's learning curve function by
using cumulative output as a predictor variable, and unit cost as the
response variable. As a result, EPA determined a best estimate of 84
percent as the progress ratio in mobile source industries. However, of
those five studies, EPA at the time placed less weight on the Epple et
al. (1991) study, because of a disruption in learning due to incomplete
knowledge transfer from the first shift to introduction of a second
shift at a North American truck plant. While learning may have
decelerated immediately after adding a second shift, we note that unit
costs continued to fall as the organization gained experience operating
with both shifts. We recognize that disruptions are an essential part
of the learning process and should not, in and of themselves, be
discredited. For this reason, the analysis uses a re-estimated average
progress ratio of 85 percent from those five studies (equally
weighted).
---------------------------------------------------------------------------
\93\ Cost Reduction through Learning in Manufacturing Industries
and in the Manufacture of Mobile Sources, United States
Environmental Protection Agency (2015). Prepared by ICF
International and available at https://19january2017snapshot.epa.gov/sites/production/files/2016-11/documents/420r16018.pdf.
[GRAPHIC] [TIFF OMITTED] TP03SE21.043
In addition to EPA's literature review, this progress ratio
estimate was informed based on findings from automotive cost-teardown
studies. NHTSA routinely performs evaluations of costs of previously
issued Federal Motor Vehicle Safety Standards (FMVSS) for new motor
vehicles and equipment. NHTSA engages contractors to perform detailed
engineering ``tear-down'' analyses for representative samples of
vehicles, to estimate how much specific FMVSS add to the weight and
retail price of a vehicle. As part of the effort, the agency examines
cost and production volume for automotive safety technologies. In
particular, we estimated costs from multiple cost tear-down studies for
technologies with actual production data from the Cost and weight added
by the Federal Motor Vehicle Safety Standards for MY 1968-2012
passenger cars and LTVs (2017).\99\
---------------------------------------------------------------------------
\94\ Argote, L., Epple, D., Rao, R. D., & Murphy, K., The
acquisition and depreciation of knowledge in a manufacturing
organization--Turnover and plant productivity, Working paper,
Graduate School of Industrial Administration, Carnegie Mellon
University (1997).
\95\ Benkard, C. L., Learning and Forgetting--The Dynamics of
Aircraft Production, The American Economic Review, Vol. 90(4), at
1034-54 (2000).
\96\ Epple, D., Argote, L., & Devadas, R., Organizational
Learning Curves--A Method for Investigating Intra-Plant Transfer of
Knowledge Acquired through Learning by Doing, Organization Science,
Vol. 2(1), at 58-70 (1991).
\97\ Epple, D., Argote, L., & Murphy, K., An Empirical
Investigation of the Microstructure of Knowledge Acquisition and
Transfer through Learning by Doing, Operations Research, Vol. 44(1),
at 77-86 (1996).
\98\ Levitt, S. D., List, J. A., & Syverson, C., Toward an
Understanding of Learning by Doing--Evidence from an Automobile
Assembly Plant, Journal of Political Economy, Vol. 121 (4), at 643-
81 (2013).
\99\ Simons, J. F., 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). Washington, DC--National Highway
Traffic Safety Administration (November 2017), at 30-33.
---------------------------------------------------------------------------
We chose five vehicle safety technologies with sufficient data to
estimate progress ratios of each, because these technologies are large-
volume technologies and are used by almost all vehicle manufacturers.
Table III-6 includes these five technologies and yields an average
progress rate of 92 percent.
[[Page 49652]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.044
For the final progress ratio used in the CAFE Model, the five
progress rates from EPA's literature review and five progress rates
from NHTSA's evaluation of automotive safety technologies results were
averaged. This resulted in an average progress rate of approximately 89
percent. We placed equal weight on progress ratios from all 10 sources.
More specifically, we placed equal weight on the Epple et al. (1991)
study, because disruptions have more recently been recognized as an
essential part in the learning process, especially in an effort to
increase the rate of output.
(3) Obtaining Appropriate Baseline Years for Direct Manufacturing Costs
DOT obtained direct manufacturing costs for each fuel economy-
improving technology from various sources, as discussed above. To
establish a consistent basis for direct manufacturing costs in the
rulemaking analysis, we adjusted each technology cost to MY 2018
dollars. For each technology, the DMC is associated with a specific
model year, and sometimes a specific production volume, or cumulative
production volume. The base model year is established as the MY in
which direct manufacturing costs were assessed (with learning factor of
1.00). With the aforementioned data on cumulative production volume for
each technology and the assumption of a 0.89 progress ratio for all
automotive technologies, we can solve for an implied cost for the first
unit produced. For some technologies, we used modestly different
progress ratios to match detailed cost projections if available from
another source (for instance, batteries for plug-in hybrids and battery
electric vehicles).
This approach produces reasonable estimates for technologies
already in production, and some additional steps are required to set
appropriate learning rates for technologies not yet in production.
Specifically, for technologies not yet in production in MY 2017, the
cumulative production volume in MY 2017 is zero, because manufacturers
have not yet produced the technologies. For pre-production cost
estimates in previous CAFE rulemakings, we often relied on confidential
business information sources to predict future costs. Many sources for
pre-production cost estimates include significant learning effects,
often providing cost estimates assuming high volume production, and
often for a timeframe late in the first production generation or early
in the second generation of the technology. Rapid doubling and re-
doubling of a low cumulative volume base with Wright's learning curves
can provide unrealistic cost estimates. In addition, direct
manufacturing cost projections can vary depending on the initial
production volume assumed. Accordingly, we carefully examined direct
costs with learning, and made adjustments to the starting point for
those technologies on the learning curve to better align with the
assumptions used for the initial direct cost estimate.
(4) Cost Learning Applied in the CAFE Model
For this analysis, we applied learning effects to the incremental
cost over the null technology state on the applicable technology tree.
After this step, we calculated year-by-year incremental costs over
preceding technologies on the tech tree to create the CAFE Model
inputs.\100\ The shift from incremental cost accounting to absolute
cost accounting in recent CAFE analyses made cost inputs more
transparently relatable to detailed model output, and relevant to this
discussion, made it easier to apply learning curves in the course of
developing inputs to the CAFE Model.
---------------------------------------------------------------------------
\100\ These costs are located in the CAFE Model Technologies
file.
---------------------------------------------------------------------------
We grouped certain technologies, such as advanced engines, advanced
transmissions, and non-battery electric components and assigned them to
the same learning schedule. While these grouped technologies differ in
operating characteristics and design, we chose to group them based on
their complexity, technology integration, and economies of scale across
manufacturers. The low volume of certain advanced technologies, such as
hybrid and electric technologies, poses a significant issue for
suppliers and prevents them from producing components needed for
advanced transmissions and other technologies at more efficient high
scale production. The technology groupings consider market
availability, complexity of technology integration, and production
volume of the technologies that can be implemented by manufacturers and
suppliers. For example, technologies like ADEAC and VCR are grouped
together; these technologies were not in production or were only in
limited introduction in MY 2017 and are planned to be introduced in
limited production by a few manufacturers. The details of these
technologies are discussed in Section III.D.
In addition, we expanded model inputs to extend the explicit
simulation of technology application through MY 2050. Accordingly, we
updated the learning curves for each technology group to cover MYs
through 2050. For MYs 2017-2032, we expect incremental improvements in
all technologies, particularly in electrification technologies because
of increased production volumes, labor efficiency, improved
manufacturing methods, specialization, network building, and other
factors. While these and other factors contribute to continual cost
learning, we believe that many fuel economy-improving technologies
considered in this rule will approach a flat learning level by the
early 2030s. Specifically, older and less complex internal combustion
engine technologies and transmissions will reach a flat learning curve
sooner when compared to electrification technologies, which have more
opportunity for improvement. For batteries and non-battery
electrification components, we estimated a steeper learning curve that
[[Page 49653]]
will gradually flatten after MY 2040. For a more detailed discussion of
the electrification learning curves, see Section III.D.3.
Each technology in the CAFE Model is assigned a learning schedule
developed from the methodology explained previously. For example, the
following chart shows learning rates for several technologies
applicable to midsize sedans, demonstrating that while we estimate that
such learning effects have already been almost entirely realized for
engine turbocharging (a technology that has been in production for many
years), we estimate that significant opportunities to reduce the cost
of the greatest levels of mass reduction (e.g., MR5) remain, and even
greater opportunities remain to reduce the cost of batteries for HEVs,
PHEVs, BEVs. In fact, for certain advanced technologies, we determined
that the results predicted by the standard learning curves progress
ratio was not realistic, based on unusual market price and production
relationships. For these technologies, we developed specific learning
estimates that may diverge from the 0.89 progress rate. As shown in
Figure III-6, these technologies include: turbocharging and downsizing
level 1 (TURBO1), variable turbo geometry electric (VTGE), aerodynamic
drag reduction by 15 percent (AERO15), mass reduction level 5 (MR5), 20
percent improvement in low-rolling resistance tire technology (ROLL20)
over the baseline, and battery integrated starter/generator (BISG).
[GRAPHIC] [TIFF OMITTED] TP03SE21.045
(e) Cost Accounting
To facilitate specification of detailed model inputs and review of
detailed model outputs, the CAFE Model continues to use absolute cost
inputs relative to a known base component cost, such that the estimated
cost of each technology is specified relative to a common reference
point for the relevant technology pathway. For example, the cost of a
7-speed transmission is specified relative to a 5-speed transmission,
as is the cost of every other transmission technology. Conversely, in
some earlier versions of the CAFE Model, incremental cost inputs were
estimated relative to the technology immediately preceding on the
relevant technology pathway. For our 7-speed transmission example, the
incremental cost would be relative to a 6-speed transmission. This
change in the structure of cost inputs does not, by itself, change
model results, but it does make the connection between these inputs and
corresponding outputs more transparent. The CAFE Model Documentation
accompanying our analysis presents details of the structure for model
cost inputs.\101\ The individual technology sections in Section III.D
provide a detailed discussion of cost accounting for each technology.
---------------------------------------------------------------------------
\101\ CAFE Model Documentation, S4.7.
---------------------------------------------------------------------------
7. Manufacturer's Credit Compliance Positions
This proposed rule involves a variety of provisions regarding
``credits'' and other compliance flexibilities. Some regulatory
provisions allow a manufacturer to earn ``credits'' that will
[[Page 49654]]
be counted toward a vehicle's rated CO2 emissions level, or
toward a fleet's rated average CO2 or CAFE level, without
reference to required levels for these average levels of performance.
Such flexibilities effectively modify emissions and fuel economy test
procedures or methods for calculating fleets' CAFE and average
CO2 levels. Other provisions (for CAFE, statutory
provisions) allow manufacturers to earn credits by achieving CAFE or
average CO2 levels beyond required levels; these provisions
may hence more appropriately be termed ``compliance credits.'' We
described in the 2020 final rule how the CAFE Model simulates these
compliance credit provisions for both the CAFE program and for EPA's
CO2 standards.\102\ For this analysis, we modeled the no-
action and action alternatives as a set of CAFE standards in place
simultaneously with EPA baseline (i.e., 2020 final) CO2
standards, related CARB agreements with five manufacturers, and ZEV
mandates in place in California and some other states. The modeling of
CO2 standards and standard-like contractual obligations
includes our representation of applicable credit provisions.
---------------------------------------------------------------------------
\102\ See 85 FR 24174, 24303 (April 30, 2020).
---------------------------------------------------------------------------
EPCA has long provided that, by exceeding the CAFE standard
applicable to a given fleet in a given model year, a manufacturer may
earn corresponding ``credits'' that the same manufacturer may, within
the same regulatory class, apply toward compliance in a different model
year. EISA amended these provisions by providing that manufacturers
may, subject to specific statutory limitations, transfer compliance
credits between regulatory classes and trade compliance credits with
other manufacturers. The CAA provides the EPA with broad standard-
setting authority for the CO2 program, with no specific
directives regarding CO2 standards or CO2
compliance credits.
EPCA also specifies that NHTSA may not consider the availability of
CAFE credits (for transfer, trade, or direct application) toward
compliance with new standards when establishing the standards
themselves.\103\ Therefore, this analysis excludes model years 2024-
2026 from those in which carried-forward or transferred credits can be
applied for the CAFE program.
---------------------------------------------------------------------------
\103\ 49 U.S.C. 32902(h)(3).
---------------------------------------------------------------------------
The ``unconstrained'' perspective acknowledges that these
flexibilities exist as part of the program and, while not considered by
NHTSA in setting standards, are nevertheless important to consider when
attempting to estimate the real impact of any alternative. Under the
``unconstrained'' perspective, credits may be earned, transferred, and
applied to deficits in the CAFE program throughout the full range of
model years in the analysis. The Draft Supplemental Environmental
Impact Statement (SEIS) accompanying this proposed rule, like the
corresponding SEIS analysis, presents ``unconstrained'' modeling
results. Also, because the CAA provides no direction regarding
consideration of any CO2 credit provisions, this analysis
includes simulation of carried-forward and transferred CO2
credits in all model years.
The CAFE Model, therefore, does provide means to simulate
manufacturers' potential application of some compliance credits, and
both the analysis of CO2 standards and the NEPA analysis of
CAFE standards do make use of this aspect of the model. On the other
hand, 49 U.S.C. 32902(h) prevents NHTSA from, in its standard setting
analysis, considering the potential that manufacturers could use
compliance credits in model years for which the agency is establishing
maximum feasible CAFE standards. Further, as discussed below, we also
continue to find it appropriate for the analysis largely to refrain
from simulating two of the mechanisms allowing the use of compliance
credits.
The CAFE Model's approach to simulating compliance decisions
accounts for the potential to earn and use CAFE credits as provided by
EPCA/EISA. The model similarly accumulates and applies CO2
credits when simulating compliance with EPA's standards. Like past
versions, the current CAFE Model can simulate credit carry-forward
(i.e., banking) between model years and transfers between the passenger
car and light truck fleets but not credit carry-back (i.e., borrowing)
from future model years or trading between manufacturers.
While NHTSA's ``unconstrained'' evaluation can consider the
potential to carry back compliance credits from later to earlier model
years, past examples of failed attempts to carry back CAFE credits
(e.g., a MY 2014 carry back default leading to a civil penalty payment)
underscore the riskiness of such ``borrowing.'' Recent evidence
indicates manufacturers are disinclined to take such risks, and we find
it reasonable and prudent to refrain from attempting to simulate such
``borrowing'' in rulemaking analysis.
Like the previous version, the current CAFE Model provides a basis
to specify (in model inputs) CAFE credits available from model years
earlier than those being explicitly simulated. For example, with this
analysis representing model years 2020-2050 explicitly, credits earned
in the model year 2015 are made available for use through the model
year 2020 (given the current five-year limit on carry-forward of
credits). The banked credits are specific to both the model year and
fleet in which they were earned.
To increase the realism with which the model transitions between
the early model years (MYs 2020-2023) and the later years that are the
subject of this action, we have accounted for the potential that some
manufacturers might trade credits earned prior to 2020 to other
manufacturers. However, the analysis refrains from simulating the
potential that manufacturers might continue to trade credits during and
beyond the model years covered by this action. In 2018 and 2020, the
analysis included idealized cases simulating ``perfect'' (i.e., wholly
unrestricted) trading of CO2 compliance credits by treating
all vehicles as being produced by a single manufacturer. Even for
CO2 compliance credit trading, these scenarios were not
plausible, because it is exceedingly unlikely that some pairs of
manufacturers would trade compliance credits. NHTSA did not include
such cases for CAFE compliance credits, because EPCA provisions (such
as the minimum domestic passenger car standard requirement) make such
scenarios impossible. At this time, we remain concerned that any
realistic simulation of such trading would require assumptions
regarding which specific pairs of manufacturers might trade compliance
credits, and the evidence to date makes it clear that the credit market
is far from fully ``open.''
We also remain concerned that to set standards based on an analysis
that presumes the use of program flexibilities risks making the
corresponding actions mandatory. Some flexibilities--credit carry-
forward (banking) and transfers between fleets in particular--involve
little risk because they are internal to a manufacturer and known in
advance. As discussed above, credit carry-back involves significant
risk because it amounts to borrowing against future improvements,
standards, and production volume and mix. Similarly, credit trading
also involves significant risk, because the ability of manufacturer A
to acquire credits from manufacturer B depends not just on manufacturer
B actually earning the expected amount of credit, but also on
manufacturer B being willing to trade with manufacturer A, and on
potential interest by other manufacturers. Manufacturers' compliance
plans have
[[Page 49655]]
already evidenced cases of compliance credit trades that were planned
and subsequently aborted, reinforcing our judgment that, like credit
banking, credit trading involves too much risk to be included in an
analysis that informs decisions about the stringency of future
standards.
As discussed in the CAFE Model Documentation, the model's default
logic attempts to maximize credit carry-forward--that is, to ``hold
on'' to credits for as long as possible. If a manufacturer needs to
cover a shortfall that occurs when insufficient opportunities exist to
add technology to achieve compliance with a standard, the model will
apply credits. Otherwise, the manufacturer carries forward credits
until they are about to expire, at which point it will use them before
adding technology that is not considered cost-effective. The model
attempts to use credits that will expire within the next three years as
a means to smooth out technology applications over time to avoid both
compliance shortfalls and high levels of over-compliance that can
result in a surplus of credits. Although it remains impossible
precisely to predict the manufacturer's actual earning and use of
compliance credits, and this aspect of the model may benefit from
future refinement as manufacturers and regulators continue to gain
experience with these provisions, this approach is generally consistent
with manufacturers' observed practices.
NHTSA introduced the CAFE Public Information Center (PIC) to
provide public access to a range of information regarding the CAFE
program,\104\ including manufacturers' credit balances. However, there
is a data lag in the information presented on the CAFE PIC that may not
capture credit actions across the industry for as much as several
months. Furthermore, CAFE credits that are traded between manufacturers
are adjusted to preserve the gallons saved that each credit
represents.\105\ The adjustment occurs at the time of application
rather than at the time the credits are traded. This means that a
manufacturer who has acquired credits through trade, but has not yet
applied them, may show a credit balance that is either considerably
higher or lower than the real value of the credits when they are
applied. For example, a manufacturer that buys 40 million credits from
Tesla may show a credit balance in excess of 40 million. However, when
those credits are applied, they may be worth only 1/10 as much--making
that manufacturer's true credit balance closer to 4 million than 40
million (e.g., when another manufacturer uses credits acquired from
Tesla, the manufacturer may only be able to offset a 1 mpg compliance
shortfall, even though the credits' ``face value'' suggests the
manufacturer could offset a 10 mpg compliance shortfall).
---------------------------------------------------------------------------
\104\ CAFE Public Information Center, https://one.nhtsa.gov/cafe_pic/cafe_pic_home.htm (last visited May 11, 2021).
\105\ CO2 credits for EPA's program are denominated
in metric tons of CO2 rather than gram/mile compliance
credits and require no adjustment when traded between manufacturers
or fleets.
---------------------------------------------------------------------------
Specific inputs accounting for manufacturers' accumulated
compliance credits are discussed in TSD Chapter 2.2.2.3.
In addition to the inclusion of these existing credit banks, the
CAFE Model also updated its treatment of credits in the rulemaking
analysis. EPCA requires that NHTSA set CAFE standards at maximum
feasible levels for each model year without consideration of the
program's credit mechanisms. However, as recent CAFE rulemakings have
evaluated the effects of standards over longer time periods, the early
actions taken by manufacturers required more nuanced representation.
Accordingly, the CAFE Model now provides means to exclude the simulated
application of CAFE compliance credits only from specific model years
for which standards are being set (for this analysis, 2024-2026), while
allowing CAFE credits to be applied in other model years.
In addition to more rigorous accounting of CAFE and CO2
compliance credits, the model also accounts for air conditioning
efficiency and off-cycle adjustments. NHTSA's program considers those
adjustments in a manufacturer's compliance calculation starting in MY
2017, and specific estimates of each manufacturer's reliance on these
adjustments are discussed above in Section III.C.2.a). Because air
conditioning efficiency and off-cycle adjustments are not credits in
NHTSA's program, but rather adjustments to compliance fuel economy,
they may be included under either a ``standard setting'' or
``unconstrained'' analysis perspective.
The manner in which the CAFE Model treats the EPA and CAFE A/C
efficiency and off-cycle credit programs is similar, but the model also
accounts for A/C leakage (which is not part of NHTSA's program). When
determining the compliance status of a manufacturer's fleet (in the
case of EPA's program, PC and LT are the only fleet distinctions), the
CAFE Model weighs future compliance actions against the presence of
existing (and expiring) CO2 credits resulting from over-
compliance with earlier years' standards, A/C efficiency credits, A/C
leakage credits, and off-cycle credits.
The model currently accounts for any off-cycle adjustments
associated with technologies that are included in the set of fuel-
saving technologies explicitly simulated as part of this proposal (for
example, start-stop systems that reduce fuel consumption during idle or
active grille shutters that improve aerodynamic drag at highway speeds)
and accumulates these adjustments up to the cap. As discussed further
in Section III.D.8, this analysis considers that some manufacturers may
apply up to 15.0 g/mi of off-cycle credit by MY 2032. We considered the
potential to model the application of off-cycle technologies
explicitly. However, doing so would require data regarding which
vehicle models already possess these improvements as well as the cost
and expected value of applying them to other models in the future. Such
data are currently too limited to support explicit modeling of these
technologies and adjustments.
When establishing maximum feasible fuel economy standards, NHTSA is
prohibited from considering the availability of alternatively fueled
vehicles,\106\ and credit provisions related to AFVs that significantly
increase their fuel economy for CAFE compliance purposes. Under the
``standard setting'' perspective, these technologies (pure battery
electric vehicles and fuel cell vehicles \107\) are not available in
the compliance simulation to improve fuel economy. Under the
``unconstrained'' perspective, such as is documented in the SEIS, the
CAFE Model considers these technologies in the same manner as other
available technologies and may apply them if they represent cost-
effective compliance pathways. However, under both perspectives, the
analysis continues to include dedicated AFVs that could be produced in
response to CAFE standards outside the model years for which standards
are being set, or for other reasons (e.g., ZEV mandates, as accounted
for in this analysis).
---------------------------------------------------------------------------
\106\ 49 U.S.C. 32902(h).
\107\ Dedicated compressed natural gas (CNG) vehicles should
also be excluded in this perspective but are not considered as a
compliance strategy under any perspective in this analysis.
---------------------------------------------------------------------------
EPCA also provides that CAFE levels may, subject to limitations, be
adjusted upward to reflect the sale of flexible fuel vehicles (FFVs).
Because these adjustments ended in model year 2020, this analysis
assumes no manufacturer
[[Page 49656]]
will earn FFV credits within the modeling horizon.
Also, the CAA provides no direction regarding consideration of
alternative fuels, and EPA has provided that manufacturers selling
PHEVs, BEVs, and FCVs may, when calculating fleet average
CO2 levels, ``count'' each unit of production as more than a
single unit. The CAFE Model accounts for these ``multipliers.'' For
example, under EPA's current regulation, when calculating the average
CO2 level achieved by its MY 2019 passenger car fleet, a
manufacturer may treat each 1,000 BEVs as 2,000 BEVs. When calculating
the average level required of this fleet, the manufacturer must use the
actual production volume (in this example, 1,000 units). Similarly, the
manufacturer must use the actual production volume when calculating
compliance credit balances.
There were no natural gas vehicles in the baseline fleet, and the
analysis did not apply natural gas technology due to cost
effectiveness. The application of a 2.0 multiplier for natural gas
vehicles for MYs 2024-2026 would have no impact on the analysis because
given the state of natural gas vehicle refueling infrastructure, the
cost to equip vehicles with natural gas tanks, the outlook for
petroleum prices, and the outlook for battery prices, we have little
basis to project more than an inconsequential response to this
incentive in the foreseeable future.
D. Technology Pathways, Effectiveness, and Cost
Vehicle manufacturers meet increasingly more stringent fuel economy
standards by applying increasing levels of fuel-economy-improving
technologies to their vehicles. An appropriate characterization of the
technologies available to manufacturers to meet fuel economy standards
is, therefore, an important input required to assess the levels of
standards that manufacturers can achieve. Like previous CAFE standards
analyses, this proposal considers over 50 fuel-economy-improving
technologies that manufacturers could apply to their MY 2020 fleet of
vehicles to meet proposed levels of CAFE standards in MYs 2024-2026.
The characterization of these technologies, the technology
effectiveness values, and technology cost assumptions build on work
performed by DOT, EPA, the National Academy of Sciences, and other
Federal and state government agencies including the Department of
Energy's Argonne National Laboratory and the California Air Resources
Board.
After spending approximately a decade refining the technology
pathways, effectiveness, and cost assumptions used in successive CAFE
Model analyses, DOT has developed guiding principles to ensure that the
CAFE Model's simulation of manufacturer compliance pathways results in
impacts that we would reasonably expect to see in the real world. These
guiding principles are as follows:
Even though the analysis considers over 50 individual technologies,
the fuel economy improvement from any individual technology must be
considered in conjunction with the other fuel-economy-improving
technologies applied to the vehicle. For example, there is an obvious
fuel economy benefit that results from converting a vehicle with a
traditional internal combustion engine to a battery electric vehicle;
however, the benefit of the electrification technology depends on the
other road load reducing technologies (i.e., mass reduction,
aerodynamic, and rolling resistance) on the vehicle.
Technologies added in combination to a vehicle will not result in a
simply additive fuel economy improvement from each individual
technology. As discussed in Section III.C.4, full vehicle modeling and
simulation provides the required degree of accuracy to project how
different technologies will interact in the vehicle system. For
example, as discussed further in Sections III.D.1 and III.D.3, a
parallel hybrid architecture powertrain improves fuel economy, in part,
by allowing the internal combustion engine to spend more time operating
at efficient engine speed and load conditions. This reduces the
advantage of adding advanced internal combustion 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 reduced effectiveness
improvement when the technologies are added to each other.
The effectiveness of a technology depends on the type of vehicle
the technology is being applied to. For example, applying mass
reduction technology results in varying effectiveness as the absolute
mass reduced is a function of the starting vehicle mass, which varies
across technology classes. See Section III.D.4 for more details.
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 manufacturer's 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 further in
Section III.D.1.d) 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.
The following sections discuss the engine, transmission,
electrification, mass reduction, aerodynamic, tire rolling resistance,
and other vehicle technologies considered in this analysis. Each
section discusses how we define the technology in the CAFE Model,\108\
how we assigned the technology to vehicles in the MY 2020 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.
---------------------------------------------------------------------------
\108\ 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.
---------------------------------------------------------------------------
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 on or also
applied at the same time to 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 FE_1 and FE_2
Adjustments files that are integrated in the CAFE Model executable
file. Similarly, the technology costs provided in each section are
examples of absolute costs seen in specific model years (MYs 2020,
2025, and 2030 for most technologies), for specific vehicle classes. To
see all absolute technology costs used in the analysis across all model
years, see the Technologies file.
[[Page 49657]]
NHTSA seeks comment on the following discussion.
1. Engine Paths
For this analysis, the extensive variety of light duty vehicle
internal combustion (IC) engine technologies are classified into
discrete engine technology paths. These paths are used to model the
most representative characteristics, costs, and performance of the
fuel-economy improving technologies most likely available during the
rulemaking time frame, MYs 2024-2026. Due to uncertainties in the cost
and capabilities of emerging technologies, some new and pre- production
technologies are not part of this analysis. We did not include
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.
The following sections discuss IC engine technologies considered in
this analysis, general technology categories used by the CAFE Model,
and how the engine technologies are assigned in the MY 2020 analysis
fleet. The following sections also discuss adoption features applicable
to engine technologies, engine technologies' effectiveness when
combined in a full vehicle model, and the engine technologies' costs.
(a) Engine Modeling in the CAFE Model
DOT models IC engine technologies that manufacturers can use to
improve fuel economy. Some engine technologies can be incorporated into
existing engines with minor or moderate changes to the engines, but
many engine technologies require an entirely new engine architecture.
We divide engine technologies into two categories, ``basic engine
technologies'' and ``advanced engine technologies.'' ``Basic engine
technologies'' refer to technologies adaptable to an existing engine
with minor or moderate changes to the engine. ``Advanced engine
technologies'' refer to technologies that generally require significant
changes or an entirely new engine architecture. The words ``basic'' and
``advanced'' are not meant to confer any information about the level of
sophistication of the technology. Many advanced engine technology
definitions also include some basic engine technologies, and these
basic technologies are accounted for in the costs and effectiveness
values of the advance engine. Figure III-7 shows how the basic and
other engines are laid out on pathways evaluated in the compliance
simulation. Each engine technology is briefly described, below. It is
important to note the ``Basic Engine Path'' shows that every engine
starts with VVT and can add one, some, or all the technologies in the
dotted box, as discussed in Section III.D.1.a)(1).
[GRAPHIC] [TIFF OMITTED] TP03SE21.046
(1) Basic Engines
In the CAFE Model, basic engine technologies may be applied
individually or in combination with other basic engine technologies.
The basic engine technologies include variable valve timing (VVT),
variable valve lift (VVL), stoichiometric gasoline direct injection
(SGDI), and cylinder deactivation. Cylinder deactivation includes a
basic level (DEAC) and an advanced level (ADEAC). DOT applies the basic
engine technologies across two engine architectures: dual over-head
camshaft (DOHC) engine architecture and single over-head camshaft
(SOHC) engine architecture.
VVT: Variable valve timing is a family of valve-train designs that
dynamically adjusts the timing of the intake valves, exhaust valves, or
both, in relation to piston position. VVT can reduce pumping losses,
provide increased engine torque and horsepower over a broad engine
operating range, and allow unique operating modes, such as Atkinson
cycle operation, to further enhance efficiency.\109\ VVT is nearly
universally used in the MY 2020 fleet. VVT enables more control of in-
cylinder
[[Page 49658]]
air flow for exhaust scavenging and combustion relative to fixed valve
timing engines. Engine parameters such as volumetric efficiency,
effective compression ratio, and internal exhaust gas recirculation
(iEGR) can all be enabled and accurately controlled by a VVT system.
---------------------------------------------------------------------------
\109\ 2015 NAS report, at 31.
---------------------------------------------------------------------------
VVL: Variable valve lift dynamically adjusts the distance a valve
travels from the valve seat. The dynamic adjustment can optimize
airflow over a broad range of engine operating conditions. The
technology can increase effectiveness by reducing pumping losses and by
affecting the fuel and air mixture motion and combustion in-
cylinder.\110\ VVL is less common in the MY 2020 fleet than VVT, but
still prevalent. Some manufacturers have implemented a limited,
discrete approach to VVL. The discrete approach allows only limited
(e.g., two) valve lift profiles versus allowing a continuous range of
lift profiles.
---------------------------------------------------------------------------
\110\ 2015 NAS report, at 32.
---------------------------------------------------------------------------
SGDI: Stoichiometric gasoline direct injection sprays fuel at high
pressure directly into the combustion chamber, which provides cooling
of the in-cylinder charge via in-cylinder fuel vaporization to improve
spark knock tolerance and enable an increase in compression ratio and/
or more optimal spark timing for improved efficiency.\111\ SGDI is
common in the MY 2020 fleet, and the technology is used in many
advanced engines as well.
---------------------------------------------------------------------------
\111\ 2015 NAS report, at 34.
---------------------------------------------------------------------------
DEAC: Basic cylinder deactivation disables intake and exhaust
valves and turns off fuel injection for the deactivated cylinders
during light load operation. DEAC is characterized by a small number of
discrete operating configurations.\112\ The engine runs temporarily as
though it were a smaller engine, reducing pumping losses and improving
efficiency. DEAC is present in the MY 2020 baseline fleet.
---------------------------------------------------------------------------
\112\ 2015 NAS report, at 33.
---------------------------------------------------------------------------
ADEAC: Advanced cylinder deactivation systems, also known as
rolling or dynamic cylinder deactivation systems, allow a further
degree of cylinder deactivation than the base DEAC. ADEAC allows the
engine to vary the percentage of cylinders deactivated and the sequence
in which cylinders are deactivated, essentially providing
``displacement on demand'' for low load operations. A small number of
vehicles have ADEAC in the MY 2020 baseline fleet.
Section III.D.1.d) contains additional information about each basic
engine technology used in this analysis, including information about
the engine map models used in the full vehicle technology effectiveness
modeling.
(2) Advanced Engines
DOT defines advanced engine technologies in the analysis as
technologies that require significant changes in engine structure, or
an entirely new engine architecture.\113\ The advanced engine
technologies represent the application of alternate combustion cycles
or changes in the application of forced induction to the engine. Each
advanced engine technology has a discrete pathway for progression to
improved versions of the technology, as seen above in Figure III-7. The
advanced engine technology pathways include a turbocharged pathway, a
high compression ratio (Atkinson) engine pathway, a variable turbo
geometry (Miller Cycle) engine pathway, a variable compression ratio
pathway, and a diesel engine pathway. Although the CAFE Model includes
a compressed natural gas (CNG) pathway, that technology is a baseline-
only technology and was not included in the analysis; currently, there
are no dedicated CNG vehicles in the MY 2020 analysis fleet.
---------------------------------------------------------------------------
\113\ Examples of this include but are not limited to changes in
cylinder count, block geometry or combustion cycle changes.
---------------------------------------------------------------------------
TURBO: Forced induction engines, or turbocharged downsized engines,
are characterized by technology that can create greater-than-
atmospheric pressure in the engine intake manifold when higher 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. Increased specific power means the engine
can generate more power per unit of cylinder volume. The higher power
per cylinder volume allows the overall engine volume to be reduced,
while maintaining performance. The overall engine volume decrease
results in an increase in fuel efficiency by reducing parasitic loads
associated with larger engine volumes.\114\
---------------------------------------------------------------------------
\114\ 2015 NAS report, at 34.
---------------------------------------------------------------------------
Cooled exhaust gas recirculation is also part of the advanced
forced induction technology path. The basic recycling of exhaust gases
using VVT is called internal EGR (iEGR) and is included as part of the
performance improvements provided by the VVT basic engine technology.
Cooled EGR (cEGR) is a second method for diluting the incoming air that
takes exhaust gases, passes them through a heat exchanger to reduce
their temperature, and then mixes them with incoming air in the intake
manifold.\115\ As discussed in Section III.D.1.d), many advanced engine
maps include EGR.
---------------------------------------------------------------------------
\115\ 2015 NAS report, at 35.
---------------------------------------------------------------------------
Five levels of turbocharged engine downsizing technologies are
considered in this analysis: A `basic' level of turbocharged downsized
technology (TURBO1), an advanced turbocharged downsized technology
(TURBO2), an advanced turbocharged downsized technology with cooled
exhaust gas recirculation applied (cEGR), a turbocharged downsized
technology with basic cylinder deactivation applied (TURBOD), and a
turbocharged downsized technology with advanced cylinder deactivation
applied (TURBOAD).
HCR: Atkinson engines, or high compression ratio engines, represent
a class of engines that achieve a higher level of fuel efficiency by
implementing an alternate combustion cycle.\116\ Historically, the Otto
combustion cycle has been used by most gasoline-based spark ignition
engines. Increased research into improving fuel economy has resulted in
the development of alternate combustion cycles that allow for greater
levels of thermal efficiency. One such alternative combustion cycle is
the Atkinson cycle. Atkinson cycle operation is achieved by allowing
the expansion stroke of the engine to overextend allowing the
combustion products to achieve the lowest possible pressure before the
exhaust stroke.117 118 119
---------------------------------------------------------------------------
\116\ See the 2015 NAS report, Appendix D, for a short
discussion on thermodynamic engine cycles.
\117\ Otto cycle is a four-stroke cycle that has four piston
movements over two engine revolutions for each cycle. First stroke:
Intake or induction; seconds stroke: Compression; third stroke:
Expansion or power stroke; and finally, fourth stroke: Exhaust.
\118\ Compression ratio is the ratio of the maximum to minimum
volume in the cylinder of an internal combustion engine.
\119\ Expansion ratio is the ratio of maximum to minimum volume
in the cylinder of an IC engine when the valves are closed (i.e.,
the piston is traveling from top to bottom to produce work).
---------------------------------------------------------------------------
Descriptions of Atkinson cycle engines and Atkinson mode or
Atkinson-enabled engine technologies have been used interchangeably in
association with high compression ratio (HCR) engines, for past
rulemaking analyses. Both technologies achieve a higher thermal
efficiency than traditional Otto cycle-only engines, however, the two
engine types operate differently. For purposes of this analysis,
Atkinson technologies can be categorized into two groups to reduce
confusion: (1) Atkinson-enabled engines and (2) Atkinson engines.
Atkinson-enabled engines, or high compression ratio engines (HCR),
[[Page 49659]]
dynamically swing between operating closer to an Otto cycle or an
Atkinson cycle based on engine loads. During high loads the engine will
use the lower-efficiency, power-dense Otto cycle mode, while at low
loads the engine will use the higher-efficiency, lower power-dense
Atkinson cycle mode. The hybrid combustion cycle operation is used to
address the low power density issues that can limit the Atkinson-only
engine and allow for a wider application of the technology.
The level of efficiency improvement experienced by a vehicle
employing Atkinson cycle operation is directly related to how much of
the engine's operation time is spent in Atkinson mode. Vehicles that
can experience operation at a high load for long portions of their
operating cycle will see little to no benefit from this technology.
This limitation to performance results in manufacturers typically
limiting the application of this technology to vehicles with a use
profile that can take advantage of the technology's behavior.
Three HCR or Atkinson-enabled engines are available in the
analysis: (1) The baseline Atkinson-enabled engine (HCR0), (2) the
enhanced Atkinson enabled engine (HCR1), and finally, (3) the enhanced
Atkinson enabled engine with cylinder deactivation (HCR1D).
In contrast, Atkinson engines in this analysis are defined as
engines that operate full-time in the Atkinson cycle. The most common
method of achieving Atkinson operation is the use of late intake valve
closing. This method allows backflow from the combustion chamber into
the intake manifold, reducing the dynamic compression ratio, and
providing a higher expansion ratio. The higher expansion ratio improves
thermal efficiency but reduces power density. The low power density
generally relegates these engines to hybrid vehicle (SHEVPS)
applications only in this analysis. Coupling the engines to electric
motors and significantly reducing road loads can compensate for the
lower power density and maintain desired performance levels for the
vehicle.\120\ The Toyota Prius is an example of a vehicle that uses an
Atkinson engine. The 2017 Toyota Prius achieved a peak thermal
efficiency of 40 percent.\121\
---------------------------------------------------------------------------
\120\ Toyota. ``Under the Hood of the All-new Toyota Prius.''
Oct. 13, 2015. Available at https://global.toyota/en/detail/9827044.
Last accessed Nov. 22, 2019.
\121\ Matsuo, S., Ikeda, E., Ito, Y., and Nishiura, H., ``The
New Toyota Inline 4 Cylinder 1.8L ESTEC 2ZR-FXE Gasoline Engine for
Hybrid Car,'' SAE Technical Paper 2016-01-0684, 2016, https://doi.org/10.4271/2016-01-0684.
---------------------------------------------------------------------------
NHTSA seeks comment on whether and how to consider ``HCR2'' in the
analysis for the final rule.
VTG: The Miller cycle is another type of overexpansion combustion
cycle, similar to the Atkinson cycle. The Miller cycle, however,
operates in combination with a forced induction system that helps
address the impacts of reduced power density during high load operating
conditions. Miller cycle-enabled engines use a similar technology
approach as seen in Atkinson-enabled engines to effectively create an
expanded expansion stroke of the combustion cycle.
In the analysis, the baseline Miller cycle-enabled engine includes
the application of a variable turbo geometry technology (VTG). The
advanced Miller cycle enabled system includes the application of a 48V-
based electronic boost system (VTGE). VTG technology allows the system
to vary boost level based on engine operational needs. The use of a
variable geometry turbocharger also supports the use of cooled exhaust
gas recirculation.\122\ An electronic boost system has an electric
motor added to assist a turbocharger at low engine speeds. The motor
assist mitigates turbocharger lag and low boost pressure at low engine
speeds. The electronic assist system can provide extra boost needed to
overcome the torque deficits at low engine speeds.\123\
---------------------------------------------------------------------------
\122\ 2015 NAS report, at 116.
\123\ 2015 NAS report, at 62.
---------------------------------------------------------------------------
VCR: Variable compression ratio (VCR) engines work by changing the
length of the piston stroke of the engine to optimize the compression
ratio and improve thermal efficiency over the full range of engine
operating conditions. Engines using VCR technology are currently in
production, but appear to be targeted primarily towards limited
production, high performance applications. Nissan is the only
manufacturer to use this technology in the MY 2020 baseline fleet. Few
manufacturers and suppliers provided information about VCR
technologies, and DOT reviewed several design concepts that could
achieve a similar functional outcome. In addition to design concept
differences, intellectual property ownership complicates the ability to
define a VCR hardware system that could be widely adopted across the
industry. Because of these issues, adoption of the VCR engine
technology is limited to Nissan only.
ADSL: Diesel engines have several characteristics that result in
superior fuel efficiency over traditional gasoline engines. These
advantages include reduced pumping losses due to lack of (or greatly
reduced) throttling, high pressure direct injection of fuel, a more
efficient combustion cycle,\124\ and a very lean air/fuel mixture
relative to an equivalent-performance gasoline engine.\125\ However,
diesel technologies require additional enablers, such as a NOx
adsorption catalyst system or a urea/ammonia selective catalytic
reduction system, for control of NOx emissions.
---------------------------------------------------------------------------
\124\ Diesel cycle is also a four-stroke cycle like the Otto
Cycle, except in the intake stroke no fuel is injected and fuel is
injected late in the compression stroke at higher pressure and
temperature.
\125\ See the 2015 NAS report, Appendix D, for a short
discussion on thermodynamic engine cycles.
---------------------------------------------------------------------------
DOT considered three levels of diesel engine technology: the
baseline diesel engine technology (ADSL) is based on a standard 2.2L
turbocharged diesel engine; the more advanced diesel engine (DSLI)
starts with the ADSL system and incorporates a combination of low
pressure and high pressure EGR, reduced parasitic loss, friction
reduction, a highly-integrated exhaust catalyst with low temp light off
temperatures, and closed loop combustion control; and finally the most
advanced diesel system (DSLIAD) is the DSLI system with advanced
cylinder deactivation technology added.
EFR: Engine friction reduction technology is a general engine
improvement meant to represent future technologies that reduce the
internal friction of an engine. EFR technology is not available for
application until MY 2023. The future technologies do not significantly
change the function or operation of the engine but reduce the energy
loss due to the rotational or rubbing friction experienced in the
bearings or cylinder during normal operation. These technologies can
include improved surface coatings, lower-tension piston rings, roller
cam followers, optimal thermal management and piston surface
treatments, improved bearing design, reduced inertial loads, improved
materials, or improved geometry.
(b) Engine Analysis Fleet Assignments
As a first step in assigning baseline levels of engine technologies
in the analysis fleet, DOT used data for each manufacturer to determine
which platforms shared engines. Within each manufacturer's fleet, DOT
assigned unique identification designations (engine codes) based on
configuration, technologies applied, displacement, compression ratio,
and power output. DOT used power output to distinguish between engines
that might have the same displacement and configuration
[[Page 49660]]
but significantly different horsepower ratings.
The CAFE Model identifies leaders and followers for a
manufacturer's vehicles that use the same engine, indicated by sharing
the same engine code. The model automatically determines which engines
are leaders by using the highest sales volume row of the highest sales
volume nameplate that is assigned an engine code. This leader-follower
relationship allows the CAFE Model simulation to maintain engine
sharing as more technology is applied to engines.
DOT accurately represents each engine using engine technologies and
engine technology classes. The first step is to assign engine
technologies to each engine code. Technology assignment is based on the
identified characteristics of the engine being modeled, and based on
technologies assigned, the engine will be aligned with an engine map
model that most closely corresponds.
The engine technology classes are a second identifier used to
accurately account for engine costs. The engine technology class is
formatted as number of cylinders followed by the letter C, number of
banks followed by the letter B, and an engine head configuration
designator, which is _SOHC for single overhead cam, _ohv for overhead
valve, or blank for dual overhead cam. As an example, one variant of
the GMC Acadia has a naturally aspirated DOHC inline 4-cylinder engine,
so DOT assigned the vehicle to the `4C1B' engine technology class and
assigned the technology VVT and SGDI. Table III-7 shows examples of
observed engines with their corresponding assigned engine technologies
as well as engine technology classes.
[GRAPHIC] [TIFF OMITTED] TP03SE21.047
The cost tables for a given engine class include downsizing (to an
engine architecture with fewer cylinders) when turbocharging technology
is applied, and therefore, the turbocharged engines observed in the
2020 fleet (that have already been downsized) often map to an engine
class with more cylinders. For instance, an observed TURBO1 V6 engine
would map to an 8C2B (V8) engine class, because the turbo costs on the
8C2B engine class worksheet assume a V6 (6C2B) engine architecture.
Diesel engines map to engine technology classes that match the observed
cylinder count since naturally aspirated diesel engines are not found
in new light duty vehicles in the U.S. market. Similarly, as indicated
above, the TURBO1 I3 in the Ford Escape maps to the 4C1B_L (I4) engine
class, because the turbo costs on the 4C1B_L engine class worksheet
assume a I3 (3C1B) engine architecture. Some instances can be more
complex, including low horsepower variants for 4-cylinder engines, and
are shown in Table III-8.
For this analysis, we have allowed additional downsizing beyond
what has been previously modeled. We allow enhanced downsizing because
manufacturers have downsized low output naturally aspirated engines to
turbo engines with smaller architectures than traditionally
observed.126 127 128 To capture this new level of turbo
downsizing we created a new category of low output naturally aspirated
engines, which is only applied to 4-cylinder engines in the MY 2020
fleet. These engines use the costing tabs in the Technologies file with
the `L' designation and are assumed to downsize to turbocharged 3-
cylinder engines for costing purposes. We seek comment regarding the
expected further application of this technology to larger cylinder
count engines, such as 8-cylinder engines that may be turbo
[[Page 49661]]
downsized to 4-cylinder engines. We would also like comment on how to
define the characteristic of an engine that may be targeted for
enhanced downsizing.
---------------------------------------------------------------------------
\126\ Richard Truett, ``GM Brining 3-Cylinder back to North
America.'' Automotive News, December 01, 2019. https://www.autonews.com/cars-concepts/gm-bringing-3-cylinder-back-na.
\127\ Stoklosa, Alexander, ``2021 Mini Cooper Hardtop.'' Car and
Driver, December 2, 2014. https://www.caranddriver.com/reviews/a15109143/2014-mini-cooper-hardtop-manual-test-review/.
\128\ Leanse, Alex ``2020 For Escape Options: Hybrid vs. 3-
Cylinder EcoBoost vs. 4-Cylinder EcoBoost.'' MotorTrend, Sept 24,
2019. https://www.motortrend.com/news/2020-ford-escape-engine-options-pros-and-cons-comparison/.
[GRAPHIC] [TIFF OMITTED] TP03SE21.048
TSD Chapter 3.1.2 includes more details about baseline engine
technology assignment logic, and details about the levels of engine
technology penetration in the MY 2020 fleet.
(c) Engine Adoption Features
Engine adoption features are defined through a combination of (1)
refresh and redesign cycles, (2) technology path logic, (3) phase-in
capacity limits, and (4) SKIP logic. Figure III-7 above shows the
technology paths available for engines in the CAFE Model. Engine
technology development and application typically results in an engine
design moving from the basic engine tree to one of the advanced engine
trees. Once an engine design moves to the advanced engine tree it is
not allowed to move to alternate advanced engine trees. Specific path
logic, phase-in caps, and SKIP logic applied to each engine technology
are discussed by engine technology, in turn.
Refresh and redesign cycles dictate when engine technology can be
applied. Technologies applicable only during a platform redesign can be
applied during a platform refresh if another vehicle platform that
shares engine codes (uses the same engine) has already applied the
technology during a redesign. For example, models of the GMC Acadia and
the Cadillac XT4 use the same engine (assigned engine code 112011 in
the Market Data file); if the XT4 adds a new engine technology during a
redesign, then the Acadia may also add the same engine technology
during the next refresh or redesign. This allows the model to maintain
engine sharing relationships while also maintaining refresh and
redesign schedules.\129\ For engine technologies, DOHC, OHV, VVT, and
CNG engine technologies are baseline only, while all other engine
technologies can only be applied at a vehicle redesign.
---------------------------------------------------------------------------
\129\ See Section III.C.2.a) for more discussion on platform
refresh and redesign cycles.
---------------------------------------------------------------------------
Basic engine technologies in the CAFE Model are represented by four
technologies: VVT, VVL, SGDI, and DEAC. DOT assumes that 100% of basic
engine platforms use VVT as a baseline, based on wide proliferation of
the technology in the U.S. fleet. The remaining three technologies,
VVL, SGDI, and DEAC, can all be applied individually or in any
combination of the three. An engine can jump from the basic engines
path to any other engine path except the Alternative Fuel Engine Path.
Turbo downsizing allows manufacturers to maintain vehicle
performance characteristics while reducing engine displacement and
cylinder count. Any basic engine can adopt one of the turbo engine
technologies (TURBO1, TURBO2 and CEGR1). 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. Turbo technology
is a mutually exclusive technology in that it cannot be adopted for
HCR, diesel, ADEAC, or CNG engines.
Non-HEV Atkinson mode engines are a collection of engines in the
HCR engine pathway (HCR0, HCR1, HCR1D and HCR2). Atkinson 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. DOT
expanded the availability of HCR technology compared to the 2020 final
rule because of new observed applications in the market.\130\ However,
there are three categories of adoption features specific to the HCR
engine pathway: \131\
---------------------------------------------------------------------------
\130\ For example, the Hyundai Palisade and Kia Telluride have a
291 hp V6 HCR1 engine. The specification sheets for these vehicles
are located in the docket for this action.
\131\ See Section III.D.1.d)(1) Engine Maps, for a discussion of
why HCR2 and P2HCR2 were not used in the central analysis. ``SKIP''
logic was used to remove this engine technology from application,
however as discussed below, we maintain HCR2 and P2HCR2 in the model
architecture for sensitivity analysis and for future engine map
model updates.
---------------------------------------------------------------------------
DOT does not allow vehicles with 405 or more horsepower to
adopt HCR engines due to their prescribed duty cycle being more
demanding and likely not supported by the lower power density found in
HCR-based engines.\132\
---------------------------------------------------------------------------
\132\ Heywood, John B. Internal Combustion Engine Fundamentals.
McGraw-Hill Education, 2018. Chapter 5.
---------------------------------------------------------------------------
Pickup trucks and vehicles that share engines with pickup
trucks are
[[Page 49662]]
also excluded from receiving HCR engines; the duty cycle for these
heavy vehicles, particularly when hauling cargo or towing, are likely
unable to take full advantage of Atkinson cycle use, and would
ultimately spend the majority of operation as an Otto cycle engine,
negating the benefits of HCR technology.\133\
---------------------------------------------------------------------------
\133\ This is based on CBI conversation with manufacturers that
currently employ HCR-based technology but saw no benefit when the
technology was applied to truck platforms in their fleet.
---------------------------------------------------------------------------
HCR engine application is also restricted for some
manufacturers that are heavily performance-focused and have
demonstrated a significant commitment to power dense technologies such
as turbocharged downsizing.\134\
---------------------------------------------------------------------------
\134\ There are three manufacturers that met the criteria (near
100% turbo downsized fleet, and future hybrid systems are based on
turbo-downsized engines) described and were excluded: BMW, Daimler,
and Jaguar Land Rover.
---------------------------------------------------------------------------
NHTSA seeks comment on the appropriateness of these restrictions for
the final rule.
Advanced cylinder deactivation technology (ADEAC), or dynamic
cylinder deactivation (e.g., Dynamic Skip Fire), can be applied to any
engine with basic technology. This technology represents a naturally
aspirated engine with ADEAC. Additional technology can be applied to
these engines by moving to the Advanced Turbo Engine Path.
Miller cycle (VTG and VTGE) engines can be applied to any basic and
turbocharged engine. VTGE technology is enabled by the use of a 48V
system that presents an improvement from traditional turbocharged
engines, and accordingly VTGE includes the application of a mild hybrid
(BISG) system.
VCR engines can be applied to basic and turbocharged engines, but
the technology is limited to Nissan and Mitsubishi.\135\ VCR technology
requires a complete redesign of the engine, and in the analysis fleet,
only two of Nissan's models had incorporated this technology. The
agency does not believe any other manufacturers will invest to develop
and market this technology in their fleet in the rulemaking time frame.
---------------------------------------------------------------------------
\135\ Nissan and Mitsubishi are strategic partners and members
of the Renault-Nissan-Mitsubishi Alliance.
---------------------------------------------------------------------------
Advanced turbo engines are becoming more prevalent as the
technologies mature. TURBOD combines TURBO1 and DEAC technologies and
represents the first advanced turbo. TURBOAD combines TURBO1 and ADEAC
technologies and is the second and last level of advanced turbos.
Engines from either the Turbo Engine Path or the ADEAC Engine Path can
adopt these technologies.
Any basic engine technologies (VVT, VVL, SGDI, and DEAC) can adopt
ADSL and DSLI engine technologies. Any basic engine and diesel engine
can adopt DSLIAD technology in this analysis; however, DOT applied a
phase in cap and year for this technology at 34 percent and MY 2023,
respectively. In DOT's engineering judgement, this is a rather complex
and costly technology to adopt and it would take significant investment
for a manufacturer to develop. For more than a decade, diesel engine
technologies have been used in less than one percent of the total
light-duty fleet production and have been found mostly on medium and
heavy-duty vehicles.
Finally, DOT allows the CAFE Model to apply EFR to any engine
technology except for DSLI and DSLIAD. DSLI and DSLIAD inherently have
incorporated engine friction technologies from ADSL. In addition,
friction reduction technologies that apply to gasoline engines cannot
necessarily be applied to diesel engines due to the higher temperature
and pressure operation in diesel engines.
(d) Engine Effectiveness Modeling
Effectiveness values used for engine technologies were simulated in
two ways. The value was either calculated based on the difference in
full vehicle simulation results created using the Autonomie modeling
tool, or effectiveness values were determined using an alternate
calculation method, including analogous improvement or fuel economy
improvement factors.
(1) Engine Maps
Most effectiveness values used as inputs for the CAFE Model were
determined by comparing results of full vehicle simulations using the
Autonomie simulation tool. For a full discussion about how Autonomie
was used, see Section III.C.4 and TSD Chapter 2.4, in addition to the
Autonomie model documentation. Engine map models were the primary
inputs used to simulate the effects of different engine technologies in
the Autonomie full vehicle simulations.
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 brake mean effective pressure (BMEP) \136\
on the vertical axis. A third engine characteristic, such as brake-
specific fuel consumption (BSFC),\137\ is displayed 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. The engine maps
developed to model the behavior of the engines used in this analysis
are referred to as engine map models.
---------------------------------------------------------------------------
\136\ Brake mean effective pressure is an engineering measure,
independent of engine displacement, that indicates the actual work
an engine performs.
\137\ Brake-specific fuel consumption is the rate of fuel
consumption divided by the power being produced.
---------------------------------------------------------------------------
The engine map models used in this analysis are representative of
technologies that are currently in production or are expected to be
available in the rulemaking timeframe, MYs 2024-2026. The engine map
models were developed to be representative of the performance
achievable across industry for a given technology and are not intended
to represent the performance of a single manufacturer's specific
engine. The broadly representative performance level was targeted
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, DOT expects that the engine maps developed for this
analysis will differ from engine maps for manufacturers' specific
engines. However, DOT intends and expects 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.
The analysis never applies absolute BSFC levels from the engine
maps to any vehicle model or configuration for the rulemaking analysis.
The absolute fuel economy values from the full vehicle Autonomie
simulations are used only to determine incremental effectiveness for
switching from one technology to another technology. The incremental
effectiveness is applied to the absolute fuel economy of vehicles in
the analysis fleet, which are based on CAFE compliance data. For
subsequent
[[Page 49663]]
technology changes, incremental effectiveness is applied 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. However, achieving this
can be challenging.
For this analysis, DOT used a small number of baseline engine
configurations with well-defined BSFC maps, and then, in a very
systematic and controlled process, added 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 testing would need to be conducted 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. Modeling is an approach used by industry 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 the
differences in effectiveness among technologies to be carefully
identified and quantified.
The Autonomie model documentation provides a detailed discussion on
how the engine map models were used as inputs to the full vehicle
simulations performed using the Autonomie tool. The Autonomie model
documentation contains the engine map model topographic figures, and
additional engine map model data can be found in the Autonomie input
files.\138\
---------------------------------------------------------------------------
\138\ See additional Autonomie supporting materials in docket
number NHTSA-2021-0053 for this proposal.
---------------------------------------------------------------------------
Most of the engine map models used in this analysis were developed
by IAV GmbH (IAV) Engineering. 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.\139\ The primary outputs
of IAV's work for this analysis are engine maps that model the
operating characteristics of engines equipped with specific
technologies.
---------------------------------------------------------------------------
\139\ IAV Automotive Engineering, https://www.iav.com/en/.
---------------------------------------------------------------------------
The generated engine maps were validated against IAV's global
database of benchmarked data, engine test data, single cylinder test
data, prior modeling studies, technical studies, and information
presented at conferences.\140\ The effectiveness values from the
simulation results were also validated against detailed engine maps
produced from the Argonne engine benchmarking programs, as well as
published information from industry and academia, ensuring reasonable
representation of simulated engine technologies.\141\ The engine map
models used in this analysis and their specifications are shown in
Table III-9.
---------------------------------------------------------------------------
\140\ Friedrich, I., Pucher, H., and Offer, T., ``Automatic
Model Calibration for Engine-Process Simulation with Heat-Release
Prediction,'' SAE Technical Paper 2006-01-0655, 2006, https://doi.org/10.4271/2006-01-0655. Rezaei, R., Eckert, P., Seebode, J.,
and Behnk, K., ``Zero-Dimensional Modeling of Combustion and Heat
Release Rate in DI Diesel Engines,'' SAE Int. J. Engines 5(3):874-
885, 2012, https://doi.org/10.4271/2012-01-1065. 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.
\141\ Bottcher,. L, Grigoriadis, P. ``ANL--BSFC map prediction
Engines 22-26.'' IAV (April 30, 2019). 20190430_ANL_Eng 22-26
Updated_Docket.pdf.
---------------------------------------------------------------------------
BILLING CODE 4910-59-P
[[Page 49664]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.049
BILLING CODE 4910-59-C
Two engine map models shown in Table III-9, Eng24 and Eng25, were
not developed as part of the IAV modeling effort and only Eng24 is used
in this
[[Page 49665]]
analysis. The Eng24 and Eng25 engine maps are equivalent to the ATK and
ATK2 models developed for the 2016 Draft Technical Assessment Report
(TAR), EPA Proposed Determination, and Final Determination.\142\ The
ATK1 engine model is based directly on the 2.0L 2014 Mazda SkyActiv-G
(ATK) engine. The ATK2 represents an Atkinson engine concept based on
the Mazda engine, adding cEGR, cylinder deactivation, and an increased
compression ratio (14:1). In this analysis, Eng24 and Eng25 correspond
to the HCR1 and HCR2 technologies.
---------------------------------------------------------------------------
\142\ Ellies, B., Schenk, C., and Dekraker, P., ``Benchmarking
and Hardware-in-the-Loop Operation of a 2014 MAZDA SkyActiv 2.0L
13:1 Compression Ratio Engine,'' SAE Technical Paper 2016-01-1007,
2016, doi:10.4271/2016-01-1007.
---------------------------------------------------------------------------
The HCR2 engine map model application in this analysis follows the
approach of the 2020 final rule.\143\ The agency believes the use of
HCR0, HCR1, and the new addition of HCR1D reasonably represents the
application of Atkinson Cycle engine technologies within the current
light-duty fleet and the anticipated applications of Atkinson Cycle
technology in the MY 2024-2026 timeframe.
---------------------------------------------------------------------------
\143\ 85 FR 24425-27 (April 30, 2020).
---------------------------------------------------------------------------
We are currently developing an updated family of HCR engine map
models that will include cEGR, cylinder deactivation and a combination
thereof. The new engine map models will closely align with the baseline
assumptions used in the other IAV-based HCR engine map models used for
the agency's analysis. The updated engine map models will likely not be
available for the final rule associated with this proposal because of
engine map model testing and validation requirements but will be
available for future CAFE analyses. We believe the timing for including
the new engine map models is reasonable, because a manufacturer that
could apply this technology in response to CAFE standards is likely not
do so before MY 2026, as the application of this technology will
require an engine redesign. We also believe this is reasonable given
manufacturer's statements that there are diminishing returns to
additional conventional engine technology improvements considering
vehicle electrification commitments.
NHTSA seeks comment on whether and how to change our engine maps
for HCR2 in the analysis for the final rule.
(2) Analogous Engine Effectiveness Improvements and Fuel Economy
Improvement Factors
For some technologies, the effectiveness for applying an
incremental engine technology was determined by using the effectiveness
values for applying the same engine technology to a reasonably similar
base engine. An example of this can be seen in the determination of the
application of SGDI to the baseline SOHC engine. Currently there is no
engine map model for the SOHC+VVT+SGDI engine configuration. To create
the effectiveness data required as an input to the CAFE Model, first, a
pairwise comparison between technology configurations that included the
DOHC+VVT engine (Eng1) and the DOHC+VVT+SGDI (Eng18) engine was
conducted. Then, the results of that comparison were used to generate a
data set of emulated performance values for adding the SGDI technology
to the SOHC+VVT engine (Eng5b) systems.
The pairwise comparison is performed by finding the difference in
fuel consumption performance between every technology configuration
using the analogous base technology (e.g., Eng1) and every technology
configuration that only changes to the analogous technology (e.g.,
Eng18). The individual changes in performance between all the
technology configurations are then added to the same technology
configurations that use the new base technology (e.g., Eng5b) to create
a new set of performance values for the new technology (e.g.,
SOHC+VVT+SGDI). Table III-10 shows the engine technologies where
analogous effectiveness values were used.
[GRAPHIC] [TIFF OMITTED] TP03SE21.050
DOT also developed a static fuel efficiency improvement factor to
simulate applying an engine technology for some technologies where
there was either no appropriate analogous technology or there were not
enough data to create a full engine map model. The improvement factors
were generally developed based on literature review or confidential
business information (CBI) provided by stakeholders. Table III-11
provides a summary of the technology
[[Page 49666]]
effectiveness values simulated using improvement factors, and the value
and rules for how the improvement factors were applied. Advanced
cylinder deactivation (ADEAC, TURBOAD, DSLIAD), advanced diesel engines
(DSLIA) and engine friction reduction (EFR) are the three technologies
modeled using improvement factors.
The application of the advanced cylinder deactivation is
responsible for three of the five technologies using an improvement
factor in this analysis. The initial review of the advanced cylinder
deactivation technology was based on a technical publication that used
a MY 2010 SOHC VVT basic engine.\144\ Additional information about the
technology effectiveness came from a benchmarking analysis of pre-
production 8-cylinder OHV prototype systems.\145\ However, at the time
of the analysis no studies of production versions of the technology
were available, and the only available technology effectiveness came
from existing studies, not operational information. Thus, only
estimates of effect could be developed and not a full model of
operation. No engine map model could be developed, and no other
technology pairs were analogous.
---------------------------------------------------------------------------
\144\ Wilcutts, M., Switkes, J., Shost, M., and Tripathi, A.,
``Design and Benefits of Dynamic Skip Fire Strategies for Cylinder
Deactivated Engines,'' SAE Int. J. Engines 6(1):278-288, 2013,
available at https://doi.org/10.4271/2013-01-0359. Eisazadeh-Far, K.
and Younkins, M., ``Fuel Economy Gains through Dynamic-Skip-Fire in
Spark Ignition Engines,'' SAE Technical Paper 2016-01-0672, 2016,
available at https://doi.org/10.4271/2016-01-0672.
\145\ EPA, 2018. ``Benchmarking and Characterization of a Full
Continuous Cylinder Deactivation System.'' Presented at the SAE
World Congress, April 10-12, 2018. Retrieved from https://www.regulations.gov/document?D=EPA-HQ-OAR-2018-0283-0029.
---------------------------------------------------------------------------
To model the effects of advanced cylinder deactivation, an
improvement factor was determined based on the information referenced
above and applied across the engine technologies. The effectiveness
values for naturally aspirated engines were predicted by using full
vehicle simulations of a basic engine with DEAC, SGDI, VVL, and VVT,
and adding 3 percent or 6 percent improvement based on engine cylinder
count: 3 percent for engines with 4 cylinders or less and 6 percent for
all other engines. Effectiveness values for turbocharged engines were
predicted using full vehicle simulations of the TURBOD engine and
adding 1.5 percent or 3 percent improvement based on engine cylinder
count: 1.5 percent for engines with 4 cylinders or less and 3 percent
for all other engines. For diesel engines, effectiveness values were
predicted by using the DSLI effectiveness values and adding 4.5 percent
or 7.5 percent improvement based on vehicle technology class: 4.5
percent improvement was applied to small and medium non-performance
cars, small performance cars, and small non-performance SUVs. 7.5
percent improvement was applied to all other vehicle technology
classes.
The analysis modeled advanced engine technology application to the
baseline diesel engine by applying an improvement factor to the ADSL
engine technology combinations. A 12.8 percent improvement factor was
applied to the ADSL technology combinations to create the DSLI
technology combinations. The improvement in performance was based on
the application of a combination of low pressure and high pressure EGR,
reduced parasitic loss, advanced friction reduction, incorporation of
highly-integrated exhaust catalyst with low temp light off
temperatures, and closed loop combustion
control.146 147 148 149
---------------------------------------------------------------------------
\146\ 2015 NAS report, at 104.
\147\ Hatano, J., Fukushima, H., Sasaki, Y., Nishimori, K.,
Tabuchi, T., Ishihara, Y. ``The New 1.6L 2-Stage Turbo Diesel Engine
for HONDA CR-V.'' 24th Aachen Colloquium--Automobile and Engine
Technology 2015.
\148\ Steinparzer, F., Nefischer, P., Hiemesch, D., Kaufmann,
M., Steinmayr, T. ``The New Six-Cylinder Diesel Engines from the BMW
In-Line Engine Module.'' 24th Aachen Colloquium--Automobile and
Engine Technology 2015.
\149\ Eder, T., Weller, R., Spengel, C., B[ouml]hm, J., Herwig,
H., Sass, H. Tiessen, J., Knauel, P. ``Launch of the New Engine
Family at Mercedes-Benz.'' 24th Aachen Colloquium--Automobile and
Engine Technology 2015.
---------------------------------------------------------------------------
As discussed above, the application of the EFR technology does not
simulate the application of a specific technology, but the application
of an array of potential improvements to an engine. All reciprocating
and rotating components in the engine are potential candidates for
friction reduction, and minute improvements in several components can
add up to a measurable fuel economy
improvement.150 151 152 153 Because of the incremental
nature of this analysis, a range of 1-2 percent improvement was
identified initially, and narrowed further to a specific 1.39%
improvement. The final value is likely representative of a typical
value industry may be able to achieve in future years.
---------------------------------------------------------------------------
\150\ ``Polyalkylene Glycol (PAG) Based Lubricant for Light- &
Medium-Duty Axles,'' 2017 DOE Annual Merit Review. Ford Motor
Company, Gangopadhyay, A., Ved, C., Jost, N. https://energy.gov/sites/prod/files/2017/06/f34/ft023_gangopadhyay_2017_o.pdf.
\151\ ``Power-Cylinder Friction Reduction through Coatings,
Surface Finish, and Design,'' 2017 DOE Annual Merit Review. Ford
Motor Company. Gangopadhay, A. Erdemir, A. https://energy.gov/sites/prod/files/2017/06/f34/ft050_gangopadhyay_2017_o.pdf.
\152\ ``Nissan licenses energy-efficient engine technology to
HELLER,'' https://newsroom.nissan-global.com/releases/170914-01-e?lang=en-US&rss&la=1&downloadUrl=%2Freleases%2F170914-01-e%2Fdownload. Last accessed April 2018.
\153\ ``Infiniti's Brilliantly Downsized V-6 Turbo Shines,''
http://wardsauto.com/engines/infiniti-s-brilliantly-downsized-v-6-turbo-shines. Last Accessed April 2018.
---------------------------------------------------------------------------
[[Page 49667]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.051
(3) Engine Effectiveness Values
The effectiveness values for the engine technologies, for all ten
vehicle technology classes, are shown in Figure III-8. Each of the
effectiveness values shown is representative of the improvements seen
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. See Table III-12 for several
specific examples. It must be emphasized, the change in fuel
consumption values between entire technology keys is used,\154\ and not
the individual technology effectiveness values. Using the change
between whole technology keys captures the complementary or non-
complementary interactions among technologies.
---------------------------------------------------------------------------
\154\ Technology key is the unique collection of technologies
that constitutes a specific vehicle, see Section III.C.4.c).
[GRAPHIC] [TIFF OMITTED] TP03SE21.052
Some of the advanced engine technologies have values that indicate
seemingly low effectiveness. Investigation of these values shows the
low effectiveness was a result of applying the advanced engines to
existing SHEVP2 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 SHEVP2 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.
---------------------------------------------------------------------------
\155\ The full data set we used to generate this example can be
found in the FE_1 Improvements file.
---------------------------------------------------------------------------
[[Page 49668]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.053
(e) Engine Costs
The CAFE Model considers both cost and effectiveness in selecting
any technology changes. We have allocated considerable resources to
sponsoring research to determine direct manufacturing costs (DMCs) for
fuel saving technologies. As discussed in detail in TSD Chapter 3.1.5,
the engine costs used in this analysis build on estimates from the 2015
NAS report, agency-funded teardown studies, and work performed by non-
government organizations.\157\
---------------------------------------------------------------------------
\156\ The box shows the inner quartile range (IQR) of the
effectiveness values and whiskers extend out 1.5 x IQR. The dots
outside this range show effectiveness values outside those
thresholds. The data used to create this figure can be found in the
FE_1 Improvements file.
\157\ FEV prepared several cost analysis studies for EPA on
subjects ranging from advanced 8-speed transmissions to belt
alternator starters or start/stop systems. NHTSA contracted
Electricore, EDAG, and Southwest Research for teardown studies
evaluating mass reduction and transmissions. The 2015 NAS report
also evaluated technology costs developed based on these teardown
studies.
---------------------------------------------------------------------------
Absolute costs of the engine technology are used in this analysis
instead of relative costs, which were used prior to the 2020 final
rule. The absolute costs are used to ensure the full cost of the IC
engine is removed when electrification technologies are applied
specifically for the transition to BEVs. This analysis models the cost
of adoption of BEV technology by first removing the costs associated
with IC powertrain systems, then applying the BEV systems costs.
Relative costs can still be determined through comparison of the
absolute costs for the initial technology combination and the new
technology combination.
As discussed in detail in TSD Chapter 3.1.5, engine costs are
assigned based on the number of cylinders in the engine and whether the
engine is naturally aspirated or turbocharged and downsized. Table III-
13 below shows an example of absolute costs for engine technologies in
2018$. The example costs are shown for a straight 4-cylinder DOHC
engine and V-6-cylinder DOHC engine. The table shows costs declining
across successive years due to the learning rate applied to each engine
technology. For a full list of all absolute engine costs used in the
analysis across all model years, see the Technologies file.
[[Page 49669]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.054
2. Transmission Paths
For this analysis, DOT classified all light duty vehicle
transmission technologies into discrete transmission technology paths.
These paths are used to model the most representative characteristics,
costs, and performance of the fuel-economy improving transmissions most
likely available during the rulemaking time frame, MYs 2024-2026.
The following sections discuss how transmission technologies
considered in this analysis are defined, the general technology
categories used by the CAFE Model, and the transmission technologies'
relative effectiveness and costs. The following sections also provide
an overview of how the transmission technologies were assigned to the
MY 2020 fleet, as well as the adoption features applicable to the
transmission technologies.
(a) Transmission Modeling in the CAFE Model
DOT modeled two major categories of transmissions for this
analysis: Automatic and manual. Automatic transmissions are
characterized by automatically selecting and shifting between
transmission gears for the driver during vehicle operation. Automatic
transmissions are further subdivided into four subcategories:
Traditional automatic transmissions (AT), dual clutch transmissions
(DCT), continuously variable transmissions (CVT), and direct drive
transmissions (DD).
ATs and CVTs also employ different levels of high efficiency
gearbox (HEG) technology. HEG improvements for transmissions represent
incremental advancement 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. DOT considered three levels of HEG improvements
in this analysis, based on 2015 recommendations by the National Academy
of Sciences and CBI data.\158\ HEG efficiency improvements are applied
to ATs and CVTs, as those transmissions inherently have higher friction
and parasitic loads related to hydraulic control systems and greater
component complexity, compared to MTs and DCTs. HEG technology
improvements are noted in the transmission technology pathways by
increasing ``levels'' of a transmission technology; for example, the
baseline 8-speed automatic transmission is termed ``AT8'', while an AT8
with level 2 HEG technology is ``AT8L2'' and an AT8 with level 3 HEG
technology is ``AT8L3.''
---------------------------------------------------------------------------
\158\ 2015 NAS report, at 191.
---------------------------------------------------------------------------
AT: Conventional planetary gear automatic transmissions are the
most
[[Page 49670]]
popular transmission.\159\ ATs typically contain three or four
planetary gear sets that provide the various gear ratios. Gear ratios
are selected by activating solenoids which engage or release multiple
clutches and brakes as needed. ATs are packaged with torque converters,
which provide a fluid coupling between the engine and the driveline and
provide a significant increase in launch torque. When transmitting
torque through this fluid coupling, energy is lost due to the churning
fluid. These losses can be eliminated by engaging the torque convertor
clutch to directly connect the engine and transmission (``lockup'').
For the Draft TAR and 2020 final rule, EPA and DOT surveyed automatic
transmissions in the market to assess trends in gear count and
purported fuel economy improvements.\160\ Based on that survey, and
also EPA's more recent 2019 and 2020 Automotive Trends Reports,\161\
DOT concluded that modeling ATs with a range of 5 to 10 gears, with
three levels of HEG technology for this analysis was reasonable.
---------------------------------------------------------------------------
\159\ 2020 EPA Automotive Trends Report, at 57-61.
\160\ Draft TAR at 5-50, 5-51; Final Regulatory Impact Analysis
accompanying the 2020 final rule, at 549.
\161\ The 2019 EPA Automotive Trends Report, EPA-420-R-20-006,
at 59 (March 2020), https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100YVFS.pdf [hereinafter 2019 EPA Automotive
Trends Report]; 2020 EPA Automotive Trends Report, at 57.
---------------------------------------------------------------------------
CVT: Conventional continuously variable transmissions consist of
two cone-shaped pulleys, connected with a belt or chain. Moving the
pulley halves allows the belt to ride inward or outward radially on
each pulley, effectively changing the speed ratio between the pulleys.
This ratio change is smooth and continuous, unlike the step changes of
other transmission varieties.\162\ DOT modeled two types of CVT systems
in the analysis, the baseline CVT and a CVT with HEG technology
applied.
---------------------------------------------------------------------------
\162\ 2015 NAS report, at 171.
---------------------------------------------------------------------------
DCT: Dual clutch transmissions, like automatic transmissions,
automate shift and launch functions. DCTs use separate clutches for
even-numbered and odd-numbered gears, allowing the next gear needed to
be pre-selected, resulting in faster shifting. The use of multiple
clutches in place of a torque converter results in lower parasitic
losses than ATs.\163\ Because of a history of limited
appeal,164 165 DOT constrains application of additional DCT
technology to vehicles already using DCT technology, and only models
two types of DCTs in the analysis.
---------------------------------------------------------------------------
\163\ 2015 NAS report, at 170.
\164\ 2020 EPA Automotive Trends Report, at 57.
\165\ 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. https://doi.org/10.17226/26092, at 4-56 [hereinafter 2021 NAS
report].
---------------------------------------------------------------------------
MT: Manual transmissions are transmissions that require direct
control by the driver to operate the clutch and shift between gears. In
a manual transmission, gear pairs along an output shaft and parallel
layshaft are always engaged. Gears are selected via a shift lever,
operated by the driver. The lever operates synchronizers, which speed
match the output shaft and the selected gear before engaging the gear
with the shaft. During shifting operations (and during idle), a clutch
between the engine and transmission is disengaged to decouple engine
output from the transmission. Automakers today offer a minimal
selection of new vehicles with manual transmissions.\166\ As a result
of reduced market presence, DOT only included three variants of manual
transmissions in the analysis.
---------------------------------------------------------------------------
\166\ 2020 EPA Automotive Trends Report, at 61.
---------------------------------------------------------------------------
The transmission model paths used in this analysis are shown in
Figure III-9. Baseline-only technologies (MT5, AT5, AT7L2, AT9L2, and
CVT) are grayed and can only be assigned as initial vehicle
transmission configurations. Further details about transmission path
modeling can be found in TSD Chapter 3.2.
[GRAPHIC] [TIFF OMITTED] TP03SE21.055
[[Page 49671]]
(b) Transmission Analysis Fleet Assignments
The wide variety of transmissions on the market are classified into
discrete transmission technology paths for this analysis. These paths
are used to model the most representative characteristics, costs, and
performance of the fuel economy-improving technologies most likely
available during the rulemaking time frame.
For the 2020 analysis fleet, DOT gathered data on transmissions
from manufacturer mid-model year CAFE compliance submissions and
publicly available manufacturer specification sheets. These data were
used to assign transmissions in the analysis fleet and determine which
platforms shared transmissions.
Transmission type, number of gears, and high-efficiency gearbox
(HEG) level are all specified for the baseline fleet assignment. The
number of gears in the assignments for automatic and manual
transmissions usually match the number of gears listed by the data
sources, with some exceptions. Four-speed transmissions were not
modeled in Autonomie for this analysis due to their rarity and low
likelihood of being used in the future, so DOT assigned 2020 vehicles
with an AT4 or MT4 to an AT5 or MT5 baseline, respectively. Some dual-
clutch transmissions were also an exception; dual-clutch transmissions
with seven gears were assigned to DCT6.
For automatic and continuously variable transmissions, the
identification of the most appropriate transmission path model required
additional steps; this is because high-efficiency gearboxes are
considered in the analysis but identifying HEG level from specification
sheets alone was not always straightforward. DOT conducted a review of
the age of the transmission design, relative performance versus
previous designs, and technologies incorporated and used the
information obtained to assign an HEG level. No automatic transmissions
in the MY 2020 analysis fleet were determined to be at HEG Level 3. In
addition, no six-speed automatic transmissions were assigned HEG Level
2. However, DOT 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. Eight-speed automatic transmissions
developed after MY 2017 are assigned HEG Level 2. All other
transmissions are assigned to their respective transmission's baseline
level. The baseline (HEG level 1) technologies available include AT6,
AT8, and CVT.
DOT assigned any vehicle in the analysis fleet with a hybrid or
electric powertrain a direct drive (DD) transmission. This designation
is for informational purposes; if specified, the transmission will not
be replaced or updated by the model.
In addition to technology type, gear count, and HEG level,
transmissions are characterized in the analysis fleet by drive type and
vehicle architecture. Drive types considered in the analysis include
front-, rear-, all-, and four-wheel drive. The definition of drive
types in the analysis does not always align with manufacturers' drive
type designations; see the end of this subsection for further
discussion. These characteristics, supplemented by information such as
gear ratios and production locations, showed that manufacturers use
transmissions that are the same or similar on multiple vehicle models.
Manufacturers have told the agency they do this to control component
complexity and associated costs for development, manufacturing,
assembly, and service. If multiple vehicle models share technology
type, gear count, drive configuration, internal gear rations, and
production location, the transmissions are treated as a single group
for the analysis. Vehicles in the analysis fleet with the same
transmission configuration adopt additional fuel-saving transmission
technology together, as described in Section III.C.2.a).
Shared transmissions are designated and tracked in the CAFE Model
input files using transmission codes. Transmission codes are six-digit
numbers that are assigned to each transmission and encode information
about them. This information includes the manufacturer, drive
configuration, transmission type, and number of gears. TSD Chapter
3.2.2 includes more information on the transmission codes designated in
the MY 2020 analysis fleet.
Different transmission codes are assigned to variants of a
transmission that may have appeared to be similar based on the
characteristics considered in the analysis but are not mechanically
identical. DOT analysts distinguish among transmission variants by
comparing their internal gear ratios and production locations. For
example, several Ford nameplates carry a rear-wheel drive, 10-speed
automatic transmission. These nameplates comprise a wide variety of
body styles and use cases, and so DOT assigned different transmission
codes to these different nameplates. Because they have different
transmission codes, they are not treated as ``shared'' for the purposes
of the analysis and have the opportunity to adopt transmission
technologies independently.
Note that when determining the drive type of a transmission, the
assignment of all-wheel drive versus four-wheel drive is determined by
vehicle architecture. This assignment does not necessarily match the
drive type used by the manufacturer in specification sheets and
marketing materials. Vehicles with a powertrain capable of providing
power to all wheels and a transverse engine (front-wheel drive
architecture) are assigned all-wheel drive. Vehicles with power to all
four wheels and a longitudinal engine (rear-wheel drive architecture)
are assigned four-wheel drive.
(c) Transmission Adoption Features
Transmission 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. For a more detailed discussion of path logic applied in
the analysis, including technology supersession logic and technology
mutual exclusivity logic, please see CAFE Model Documentation S4.5
Technology Constraints (Supersession and Mutual Exclusivity).
Additionally, the CAFE Model prevents ``branch hopping'' to prevent
stranded capital associated with moving from one transmission
architecture to another. Stranded capital is discussed in Section
III.C.6.
Some technologies that are modeled in the analysis are not yet in
production, and therefore are not assigned in the baseline fleet.
Nonetheless, these technologies, which are projected to be available in
the analysis timeframe, are available for future adoption. For
instance, an AT10L3 is not observed in the baseline fleet, but it is
plausible that manufacturers that employ AT10L2 technology may improve
the efficiency of those AT10L2s in the rulemaking timeframe.
The following sections discuss specific adoption features applied
to each type of transmission technology.
When electrification technologies are adopted, the transmissions
associated with those technologies will supersede the existing
transmission on a vehicle. The transmission technology is superseded if
P2 hybrids, plug-in hybrids, or battery electric vehicle technologies
are applied. For more information, see Section III.D.3.c).
[[Page 49672]]
The automatic transmission path precludes adoption of other
transmission types once a platform progresses past an AT6. This
restriction is used 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
AT6 in the rulemaking timeframe.
Vehicles that did not start out with AT7L2 or AT9L2 transmissions
cannot adopt those technologies in the model. The agency observed that
MY 2017 vehicles with those technologies were primarily luxury
performance vehicles and concluded that other vehicles would likely not
adopt those technologies. DOT concluded that this was also a reasonable
assumption for the MY 2020 analysis fleet because vehicles that have
moved to more advanced automatic transmissions have overwhelmingly
moved to 8-speed and 10-speed transmissions.\167\
---------------------------------------------------------------------------
\167\ 2020 EPA Automotive Trends Report, at 64, figure 4.18.
---------------------------------------------------------------------------
CVT adoption is limited by technology path logic. CVTs cannot be
adopted by vehicles that do not originate with a CVT or by vehicles
with multispeed transmissions beyond AT6 in the baseline fleet.
Vehicles with multispeed transmissions greater than AT6 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. The analysis restricts the application of
CVT technology on larger vehicles because of the higher torque (load)
demands of those vehicles and CVT torque limitations based on
durability constraints. Additionally, this restriction is used to avoid
the significant level of stranded capital.
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.\168\
---------------------------------------------------------------------------
\168\ Ibid.
---------------------------------------------------------------------------
Manual transmissions can only move to more advanced manual
transmissions for this analysis, because other transmission types do
not provide a similar driver experience (utility). Manual transmissions
cannot adopt AT, CVT, or DCT technologies under any circumstance. Other
transmissions cannot move to MT because manual transmissions lack
automatic shifting associated with the other transmission types
(utility) and in recognition of the low customer demand for manual
transmissions.\169\
---------------------------------------------------------------------------
\169\ Ibid.
---------------------------------------------------------------------------
(d) Transmission Effectiveness Modeling
For this analysis, DOT used the Autonomie full vehicle simulation
tool to model the interaction between transmissions and the full
vehicle system to improve fuel economy, and how changes to the
transmission subsystem influence the performance of the full vehicle
system. The full vehicle simulation approach clearly defines the
contribution of individual transmission technologies and separates
those contributions from other technologies in the full vehicle system.
The modeling approach follows the recommendations of the National
Academy of Sciences in its 2015 light duty vehicle fuel economy
technology report to use full vehicle modeling supported by application
of collected improvements at the sub-model level.\170\ See TSD Chapter
3.2.4 for more details on transmission modeling inputs and results.
---------------------------------------------------------------------------
\170\ 2015 NAS report, at 292.
---------------------------------------------------------------------------
The only technology effectiveness results that were not directly
calculated using the Autonomie simulation results were for the AT6L2.
DOT determined that the model for this specific technology was
inconsistent with the other transmission models and overpredicted
effectiveness results. Evaluation of the AT6L2 transmission model
revealed an overestimated efficiency map was developed for the AT6L2
model. The high level of efficiency assigned to the transmission
surpassed benchmarked advanced transmissions.\171\ To address the
issue, DOT replaced the effectiveness values of the AT6L2 model. DOT
replaced the effectiveness for the AT6L2 technology with analogous
effectiveness values from the AT7L2 transmission model. For additional
discussion on how analogous effectiveness values are determined please
see Section III.D.1.d)(2).
---------------------------------------------------------------------------
\171\ Autonomie model documentation, Chapter 5.3.4. Transmission
Performance Data.
---------------------------------------------------------------------------
The effectiveness values for the transmission technologies, for all
ten vehicle technology classes, are shown in Figure III-10. Each of the
effectiveness values shown is representative of the improvements seen
for upgrading only the listed transmission technology for a given
combination of other technologies. In other words, the range of
effectiveness values seen for each specific technology, e.g., AT10L3,
represents the addition of the AT10L3 technology to every technology
combination that could select the addition of AT10L3. It must be
emphasized that the graph shows the change in fuel consumption values
between entire technology keys,\172\ and not the individual technology
effectiveness values. Using the change between whole technology keys
captures the complementary or non-complementary interactions among
technologies. In the graph, the box shows the inner quartile range
(IQR) of the effectiveness values and whiskers extend out 1.5 x IQR.
The dots outside of the whiskers show values for effectiveness that are
outside these bounds.
---------------------------------------------------------------------------
\172\ Technology key is the unique collection of technologies
that constitutes a specific vehicle, see Section III.C.4.c).
---------------------------------------------------------------------------
[[Page 49673]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.056
Note that the effectiveness for the MT5, AT5 and DD technologies
are not shown. The DD transmission does not have a standalone
effectiveness because it is only implemented as part of electrified
powertrains. The MT5 and AT5 also have no effectiveness values because
both technologies are baseline technologies against which all other
technologies are compared.
---------------------------------------------------------------------------
\173\ The data used to create this figure can be found the FE_1
Improvements file.
---------------------------------------------------------------------------
(e) Transmission Costs
This analysis uses transmission costs drawn from several sources,
including the 2015 NAS report and NAS-cited studies. TSD Chapter 3.2.5
provides a detailed description of the cost sources used for each
transmission technology. Table III-14 shows an example of absolute
costs for transmission technologies in 2018$ across select model years,
which demonstrates how cost learning is applied to the transmission
technologies over time. Note, because transmission hardware is often
shared across vehicle classes, transmission costs are the same for all
vehicle classes. For a full list of all absolute transmission costs
used in the analysis across all model years, see the Technologies file.
[[Page 49674]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.057
3. Electrification Paths
The electric paths include a large set of technologies that share
the common element of using electrical power for certain vehicle
functions that were traditionally powered mechanically by engine power.
Electrification technologies thus can range from electrification of
specific accessories (for example, electric power steering to reduce
engine loads by eliminating parasitic losses) to electrification of the
entire powertrain (as in the case of a battery electric vehicle).
The following subsections discuss how each electrification
technology is defined in the CAFE Model and the electrification
pathways down which a vehicle can travel in the compliance simulation.
The subsections also discuss how the agency assigned electrified
vehicle technologies to vehicles in the MY 2020 analysis fleet, any
limitations on electrification technology adoption, and the specific
effectiveness and cost assumptions used in the Autonomie and CAFE Model
analysis.
(a) Electrification Modeling in the CAFE Model
The CAFE Model defines the technology pathway for each type of
electrification grouping in a logical progression. Whenever the CAFE
Model converts a vehicle model to one of the available electrified
systems, both effectiveness and costs are updated according to the
specific components' modeling algorithms. Additionally, all
technologies on the different electrification paths are mutually
exclusive and are evaluated in parallel. For example, the model may
evaluate PHEV20 technology prior to having to apply 12-volt stop-start
(SS12V) or strong hybrid technology. The specific set of algorithms and
rules are discussed further in the sections below, and more detailed
discussions are included in the CAFE Model Documentation. The
specifications for each electrification technology used in the analysis
is discussed below.
The technologies that are included on the three vehicle-level paths
pertaining to the electrification and electric improvements defined
within the modeling system are illustrated in Figure III-11. As shown
in the Electrification path, the baseline-only CONV technology is
grayed out. This technology is used to denote whether a vehicle comes
in with a conventional powertrain (i.e., a vehicle that does not
include any level of hybridization) and to allow the model to properly
map to the Autonomie vehicle simulation database results. If multiple
branches converge on a single technology, the subset of technologies
that will be disabled from further adoption is extended only up the
point of convergence.
BILLING CODE 4910-59-P
[[Page 49675]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.058
BILLING CODE 4910-59-C
SS12V: 12-volt stop-start (SS12V), sometimes referred to as start-
stop, idle-stop, or a 12-volt micro hybrid system, is the most basic
hybrid system that facilitates idle-stop capability. In this system,
the integrated starter generator is coupled to the internal combustion
(IC) engine. When the vehicle comes to an idle-stop the IC engine
completely shuts off, and, with the help of the 12-volt battery, the
engine cranks and starts again in response to throttle to move the
vehicle, application or release of the brake pedal to move the vehicle.
The 12-volt battery used for the start-stop system is an improved unit
compared to a traditional 12-volt battery, and is capable of higher
power, increased life cycle, and capable of minimizing voltage drop on
restart. This technology is beneficial to reduce fuel consumption and
emissions when the vehicle frequently stops, such as in city driving
conditions or in stop and go traffic. 12VSS can be applied to all
vehicle technology classes.
BISG: The belt integrated starter generator, sometimes referred to
as a mild hybrid system or P0 hybrid, provides idle-stop capability and
uses a higher voltage battery with increased energy capacity over
conventional automotive batteries. These higher voltages allow the use
of a smaller, more powerful and efficient electric motor/generator
which replaces the standard alternator. In BISG systems, the motor/
generator is coupled to the engine via belt (similar to a standard
alternator). In addition, these motor/generators can assist vehicle
braking and recover braking energy while the vehicle slows down
(regenerative braking) and in turn can propel the vehicle at the
beginning of launch, allowing the engine to be restarted later. Some
limited electric assist is also provided during acceleration to improve
engine efficiency. Like the micro hybrids, BISG can be applied to all
vehicles in the analysis except for Engine 26a (VCR). We assume all
mild hybrids are 48-volt systems with engine belt-driven motor/
generators.
SHEVP2/SHEVPS: A strong hybrid vehicle is a vehicle that combines
two or more propulsion systems, where one uses gasoline (or diesel),
and the other captures energy from the vehicle during deceleration or
braking, or from the engine and stores that energy for later used by
the vehicle. This analysis evaluated the following strong hybrid
systems: Hybrids with ``P2'' parallel
[[Page 49676]]
drivetrain architectures (SHEVP2),\174\ and hybrids with power-split
architectures (SHEVPS). Both types provide start-stop or idle-stop
functionality, regenerative braking capability, and vehicle launch
assist. A SHEVPS has a higher potential for fuel economy improvement
than a SHEVP2, although its cost is also higher and engine power
density is lower.\175\
---------------------------------------------------------------------------
\174\ Depending on the location of electric machine (motor with
or without inverter), the parallel hybrid technologies are
classified as P0-motor located at the primary side of the engine,
P1-motor located at the flywheel side of the engine, P2-motor
located between engine and transmission, P3-motor located at the
transmission output, and P4-motor located on the axle.
\175\ Kapadia, J., Kok, D., Jennings, M., Kuang, M. et al.,
``Powersplit or Parallel--Selecting the Right Hybrid Architecture,''
SAE Int. J. Alt. Power. 6(1):2017, doi:10.4271/2017-01-1154.
---------------------------------------------------------------------------
P2 parallel hybrids (SHEVP2) are a type of hybrid vehicle that use
a transmission-integrated electric motor placed between the engine and
a gearbox or CVT, with a clutch that allows decoupling of the motor/
transmission from the engine. Although similar to the configuration of
the crank mounted integrated starter generator (CISG) system discussed
previously, a P2 hybrid is typically equipped with a larger electric
motor and battery in comparison to the CISG. Disengaging the clutch
allows all-electric operation and more efficient brake-energy recovery.
Engaging the clutch allows coupling of the engine and electric motor
and, when combined with a transmission, reduces gear-train losses
relative to power-split or 2-mode hybrid systems. P2 hybrid systems
typically rely on the internal combustion engine to deliver high,
sustained power levels. Electric-only mode is used when power demands
are low or moderate.
An important feature of the SHEVP2 system is that it can be applied
in conjunction with most engine technologies. Accordingly, once a
vehicle is converted to a SHEVP2 powertrain in the compliance
simulation, the CAFE Model allows the vehicle to adopt the conventional
engine technology that is most cost effective, regardless of relative
location of the existing engine on the engine technology path. For
example, a vehicle in the MY 2020 analysis fleet that starts with a
TURBO2 engine could adopt a TURBO1 engine with the SHEVP2 system, if
that TURBO1 engine allows the vehicle to meet fuel economy standards
more cost effectively.
The power-split hybrid (SHEVPS) is a hybrid electric drive system
that replaces the traditional transmission with a single planetary gear
set (the power-split device) and a motor/generator. This motor/
generator uses the engine either to charge the battery or to supply
additional power to the drive motor. A second, more powerful motor/
generator is connected to the vehicle's final drive and always turns
with the wheels. The planetary gear splits engine power between the
first motor/generator and the drive motor either to charge the battery
or to supply power to the wheels. During vehicle launch, or when the
battery state of charge (SOC) is high, the engine is turned off and the
electric motor propels the vehicle.\176\ During normal driving, the
engine output is used both to propel the vehicle and to generate
electricity. The electricity generated can be stored in the battery
and/or used to drive the electric motor. During heavy acceleration,
both the engine and electric motor (by consuming battery energy) work
together to propel the vehicle. When braking, the electric motor acts
as a generator to convert the kinetic energy of the vehicle into
electricity to charge the battery.
---------------------------------------------------------------------------
\176\ Autonomie model documentation, Chapter 4.13.2.
---------------------------------------------------------------------------
Table III-15 below shows the configuration of conventional engines
and transmissions used with strong hybrids for this analysis. The
SHEVPS powertrain configuration was paired with a planetary
transmission (eCVT) and Atkinson engine (Eng26). This configuration was
designed to maximize efficiency at the cost of reduced towing
capability and real-world acceleration performance.\177\ In contrast,
the SHEVP2 powertrains were paired with an advanced 8-speed automatic
transmissions (AT8L2) and could be paired with most conventional
engines.\178\
---------------------------------------------------------------------------
\177\ Kapadia, J., D, Kok, M. Jennings, M. Kuang, B. Masterson,
R. Isaacs, A. Dona. 2017. Powersplit or Parallel--Selecting the
Right Hybrid Architecture. SAE International Journal of Alternative
Powertrains 6 (1): 68-76. https://doi.org/10.4271/2017-01-1154.
\178\ We did not model SHEVP2s with VTGe (Eng23c) and VCR
(Eng26a).
[GRAPHIC] [TIFF OMITTED] TP03SE21.059
PHEV: Plug-in hybrid electric vehicles are hybrid electric vehicles
with the means to charge their battery packs from an outside source of
electricity (usually the electric grid). These vehicles have larger
battery packs with more energy storage and a greater capability to be
discharged than other non-plug-in hybrid electric vehicles. PHEVs also
generally use a control system that allows the battery pack to be
substantially depleted under electric-only or blended mechanical/
electric operation and batteries that can be cycled in charge-
sustaining operation at a lower state of charge than non-plug-in hybrid
electric vehicles. These vehicles generally have a greater all-electric
range than typical strong HEVs. Depending on how these vehicles are
operated, they can use electricity exclusively, operate like a
conventional hybrid, or operate in some combination of these two modes.
---------------------------------------------------------------------------
\179\ Engine 01, 02, 03, 04, 5b, 6a, 7a, 8a, 12, 12-DEAC, 13,
14, 17, 18, 19, 20, 21, 22b, 23b, 24, 24-Deac. See Section III.D.1
for these engine specifications.
---------------------------------------------------------------------------
[[Page 49677]]
There are four PHEV architectures included in this analysis that
reflect combinations of two levels of all-electric range (AER) and two
engine types. DOT selected 20 miles AER and 50 miles AER to reasonably
span the various AER in the market, and their effectiveness and cost.
DOT selected an Atkinson engine and a turbocharged downsized engine to
span the variety of engines in the market.
PHEV20/PHEV20H and PHEV50/PHEV50H are essentially a SHEVPS with a
larger battery and the ability to drive with the engine turned off. In
the CAFE Model, the designation for ``H'' in PHEVxH could represent
another type of engine configuration, but for this analysis DOT used
the same effectiveness values as PHEV20 and PHEV50 to represent PHEV20H
and PHEV50H, respectively. The PHEV20/PHEV20H represents a ``blended-
type'' plug-in hybrid, which can operate in all-electric (engine off)
mode only at light loads and low speeds, and must blend electric motor
and engine power together to propel the vehicle at medium or high loads
and speeds. The PHEV50/PHEV50H represents an extended range electric
vehicle (EREV), which can travel in all-electric mode even at higher
speeds and loads. Further discussion of engine sizing, batteries, and
motors for these PHEVs is discussed in Section III.D.3.d).
PHEV20T and PHEV50T are 20 mile and 50 mile AER vehicles based on
the SHEVP2 engine architecture. The PHEV versions of these
architectures include larger batteries and motors to meet performance
in charge sustaining mode at higher speeds and loads as well as similar
performance and range in all electric mode in city driving, at higher
speeds and loads. For this analysis, the CAFE Model considers these
PHEVs to have an advanced 8-speed automatic transmission (AT8L2) and
TURBO1 (Eng12) in the powertrain configuration. Further discussion of
engine sizing, batteries, and motors for these PHEVs is discussed in
Section III.D.3.d).
Table III-16 shows the different PHEV configurations used in this
analysis.
[GRAPHIC] [TIFF OMITTED] TP03SE21.060
BEV: Battery electric vehicles are equipped with all-electric drive
systems powered by energy-optimized batteries charged primarily by
electricity from the grid. BEVs do not have a combustion engine or
traditional transmission. Instead, BEVs rely on all electric
powertrains, with an advanced transmission packaged with the
powertrain. The range of battery electric vehicles vary by vehicle and
battery pack size.
DOT simulated BEVs with ranges of 200, 300, 400, and 500 miles in
the CAFE Model. BEV range is measured pursuant to EPA test procedures
and guidance.\180\ The CAFE Model assumes that BEVs transmissions are
unique to each vehicle (i.e., the transmissions are not shared by any
other vehicle) and that no further improvements are available.
---------------------------------------------------------------------------
\180\ BEV electric ranges are determined per EPA guidance
Document. ``EPA Test Procedure for Electric Vehicles and Plug-in
Hybrids.'' https://fueleconomy.gov/feg/pdfs/EPA%20test%20procedure%20for%20EVs-PHEVs-11-14-2017.pdf. November
14, 2017. Last Accessed May 3, 2021.
---------------------------------------------------------------------------
A key note about the BEVs offered in this analysis is that the CAFE
Model does not account for vehicle range when considering additional
BEV technology adoption. That is, the CAFE Model does not have an
incentive to build BEV300, 400, and 500s, because the BEV200 is just as
efficient as those vehicles and counts the same toward compliance, but
at a significantly lower cost because of the smaller battery. While
manufacturers have been building 200-mile range BEVs, those vehicles
have generally been passenger cars. Manufacturers have told DOT that
greater range is important for meeting the needs of broader range of
consumers and to increase consumer demand. More recently, there has
been a trend towards manufacturers building higher range BEVs in the
market, and manufacturers building CUV/SUV and pickup truck BEVs. To
simulate the potential relationship of BEV range to consumer demand,
DOT has included several adoption features for BEVs. These are
discussed further in Section III.D.3.c).
Fuel cell electric vehicle (FCEV): Fuel cell electric vehicles are
equipped with an all-electric drivetrain, but unlike BEVs, FCEVs do not
solely rely on batteries; rather, electricity to run the FCEV electric
motor is mainly generated by an onboard fuel cell system. FCEV
architectures are similar to series hybrids,\181\ but with the engine
and generator replaced by a fuel cell. Commercially available FCEVs
consume hydrogen to generate electricity for the fuel cell system, with
most automakers using high pressure gaseous hydrogen storage tanks.
FCEVs are currently produced in limited numbers and are available in
limited geographic areas where hydrogen refueling stations are
accessible. For reference, in MY 2020, only four FCV models were
offered for
[[Page 49678]]
sale, and since 2014 only 9,975 FCVs have been sold.182 183
---------------------------------------------------------------------------
\181\ Series hybrid architecture is a strong hybrid that has the
engine, electric motor and transmission in series. The engine in a
series hybrid drives a generator that charges the battery.
\182\ Argonne National Laboratory, ``Light Duty Electric Drive
Vehicles Monthly Sales Update.'' Energy Systems Division, https://www.anl.gov/es/light-duty-electric-drive-vehicles-monthly-sales-updates. Last Accessed May 4, 2021.
\183\ See the MY 2020 Market Data file. The four vehicles are
the Honda Clarity, Hyundai Nexo and Nexo Blue, and Toyota Mirai.
---------------------------------------------------------------------------
For this analysis, the CAFE Model simulates a FCEV with a range of
320 miles. Any type of powertrain could adopt a FCEV powertrain;
however, to account for limited market penetration and unlikely
increased adoption in the rulemaking timeframe, technology phase in
caps were used to control how many FCEVs a manufacturer could build.
The details of this concept are further discussed in Section
III.D.3.c).
(b) Electrification Analysis Fleet Assignments
DOT identified electrification technologies present in the baseline
fleet and used these as the starting point for the regulatory analysis.
These assignments were based on manufacturer-submitted CAFE compliance
information, publicly available technical specifications, marketing
brochures, articles from reputable media outlets, and data from Wards
Intelligence.\184\
---------------------------------------------------------------------------
\184\ ``U.S. Car and Light Truck Specifications and Prices, '20
Model Year.'' Wards Intelligence, 3 Aug. 2020,
wardsintelligence.informa.com/WI964244/US-Car-and-Light-Truck-Specifications-and-Prices-20-Model-Year.
---------------------------------------------------------------------------
Table III-17 gives the baseline fleet penetration rates of
electrification technologies eligible to be assigned in the baseline
fleet. Over half the fleet had some level of electrification, with the
vast majority of these being micro hybrids. BEVs represented less than
2% of MY 2020 baseline fleet; BEV300 was the most common BEV
technology, while no BEV500s were observed.
[GRAPHIC] [TIFF OMITTED] TP03SE21.061
Micro and mild hybrids refer to the presence of SS12V and BISG,
respectively. The data sources discussed above were used to identify
the presence of these technologies on vehicles in the fleet. Vehicles
were assigned one of these technologies only if its presence could be
confirmed with manufacturer brochures or technical specifications.
Strong hybrid technologies included SHEVPS and SHEVP2. Note that
P2HCR0, P2HCR1, P2HCR1D, and P2HCR2 are not assigned in the fleet and
are only available to be applied by the model. When possible,
manufacturer specifications were used to identify the strong hybrid
architecture type. In the absence of more sophisticated information,
hybrid architecture was determined by number of motors. Hybrids with
one electric motor were assigned P2, and those with two were assigned
power-split (PS). DOT seeks comment on additional ways the agency could
perform initial hybrid assignments based on publicly available
information.
Plug-in hybrid technologies PHEV20/20T and PHEV50/50T are assigned
in the baseline fleet. PHEV20H and PHEV50H are not assigned in the
fleet and are only available to be applied by the model. Vehicles with
an electric-only range of 40 miles or less were assigned PHEV20; those
with a range above 40 miles were assigned PHEV50. They were
respectively assigned PHEV20T/50T if the engine was turbocharged (i.e.,
if it would qualify for one of technologies on the turbo engine
technology pathway). DOT also had to calculate baseline fuel economy
values for PHEV technologies as part of the PHEV analysis fleet
assignments; that process is described in detail in TSD Chapter 3.3.2.
Fuel cell and battery electric vehicle technologies included
BEV200/300/400/500 and FCV. Vehicles with all-electric powertrains that
used hydrogen fuel were assigned FCV. The BEV technologies were
assigned to vehicles based on range thresholds that best account for
vehicles' existing range capabilities while allowing room for the model
to potentially apply more advanced electrification technologies.
[[Page 49679]]
For more detail about the electrification analysis fleet assignment
process, see TSD Chapter 3.3.2.
(c) Electrification Adoption Features
Multiple types of adoption features applied to the electrification
technologies. The hybrid/electric technology path logic dictated how
vehicles could adopt different levels of electrification technology.
Broadly speaking, more advanced levels of hybridization or
electrification superseded all prior levels, with certain technologies
within each level being mutually exclusive. The analysis modeled (from
least to most electrified) micro hybrids, mild hybrids, strong hybrids,
plug-in hybrids, and fully electric vehicles.
As discussed further below, SKIP logic--restrictions on the
adoption of certain technologies--applied to plug-in (PHEV) and strong
hybrid vehicles (SHEV). Some technologies on these pathways were
``skipped'' if a vehicle was high performance, required high towing
capabilities as a pickup truck, or belonged to certain manufacturers
who have demonstrated that their future product plans will more than
likely not include the technology. The specific criteria for SKIP logic
for each applicable electrification technology will be expanded on
later in this section.
This section also discusses the supersession of engines and
transmissions on vehicles that adopt SHEV or PHEV powertrains. To
manage the complexity of the analysis, these types of hybrid
powertrains were modeled with several specific engines and
transmissions, rather than in multiple configurations. Therefore, the
cost and effectiveness values SHEV and PHEV technologies take into
account these specific engines and transmissions.
Finally, phase-in caps limited the adoption rates of battery
electric (BEV) and fuel cell vehicles (FCV). These phase-in caps were
set by DOT, taking into account current market share, scalability, and
reasonable consumer adoption rates of each technology. TSD Chapter
3.3.3 discusses the electrification phase-in caps and the reasoning
behind them in detail.
The only adoption feature applicable to micro and mild hybrid
technologies was path logic. The pathway consists of a linear
progression starting with a conventional powertrain with no
electrification at all, which is superseded by SS12V, which in turn is
superseded by BISG. Vehicles could only adopt micro and mild hybrid
technology if the vehicle did not already have a more advanced level of
electrification.
The adoption features applied to strong hybrid technologies
included path logic, powertrain substitution, and vehicle class
restrictions. Per the defined technology pathways, SHEVPS, SHEVP2, and
the P2HCR technologies were 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 could still advance to one or more of the
plug-in hybrid technologies.
When the model applied any strong hybrid technology to a vehicle,
the transmission technology on the vehicle was superseded. Regardless
of the transmission originally present, P2 hybrids adopt an 8-speed
automatic transmission (AT8L2), and PS hybrids adopt a continuously
variable transmission (eCVT).
When the model applies the SHEVP2 technology, the model can
consider various engine options to pair with the SHEVP2 architecture
according to existing engine path constraints, taking into account
relative cost effectiveness. For SHEVPS technology, the existing engine
was replaced with Eng26, a full Atkinson cycle engine.
SKIP logic was also used to constrain adoption for SHEVPS, P2HCR0,
P2HCR1, and P2HCR1D. No SKIP logic applied to SHEVP2; P2HCR2 was
restricted from all vehicles in the 2020 fleet, as discussed further in
Section III.D.1.d)(1). These technologies were ``skipped'' for vehicles
with engines \185\ that met one of the following conditions:
---------------------------------------------------------------------------
\185\ This refers to the engine assigned to the vehicle in the
2020 baseline fleet.
---------------------------------------------------------------------------
The engine belonged to an excluded manufacturer; \186\
---------------------------------------------------------------------------
\186\ Excluded manufacturers included BMW, Daimler, and Jaguar
Land Rover.
---------------------------------------------------------------------------
The engine belonged to a pickup truck (i.e., the engine
was on a vehicle assigned the ``pickup'' body style);
The engine's peak horsepower was more than 405 HP; or if
The engine was on a non-pickup vehicle but was shared with
a pickup.
The reasons for these conditions are similar to those for the SKIP
logic applied to HCR engine technologies, discussed in more detail
above. In the real world, pickups and performance vehicles with certain
powertrain configurations cannot adopt the technologies listed above
and maintain vehicle performance without redesigning the entire
powertrain. SKIP logic was put in place to prevent the model from
pursuing compliance pathways that are ultimately unrealistic.
PHEV technologies superseded the micro, mild, and strong hybrids,
and could only be replaced by full electric technologies. Plug-in
hybrid technology paths were also mutually exclusive, with the PHEV20
technologies able to progress to the PHEV50 technologies.
The engine and transmission technologies on a vehicle were
superseded when PHEV technologies were applied to a vehicle. For all
plug-in technologies, the model applied an AT8L2 transmission. For
PHEV20/50 and PHEV20H/50H, the vehicle received a full Atkinson cycle
engine, Eng26. For PHEV20T/50T, the vehicle received a TURBO1 engine,
Eng12.
SKIP logic applied to PHEV20/20H and PHEV50/50H under the same four
conditions listed for the strong hybrid technologies in the previous
section, for the same reasons previously discussed.
For the analysis, the adoption of BEVs and FCEVs was limited by
both path logic and phase in caps. BEV200/300/400/500 and FCEV were
applied as end-of-path technologies that superseded previous levels of
electrification.
The main adoption feature applicable to BEVs and FCEVs is phase-in
caps, which are defined in the CAFE Model input files as 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
BEV200 costs less and has higher effectiveness values than other
advanced electrification technologies,\187\ the model will have
vehicles adopt it first, until it is restricted by the phase-in cap.
---------------------------------------------------------------------------
\187\ This is because BEV200 uses fewer batteries and weighs
less than BEVs with greater ranges.
---------------------------------------------------------------------------
Table III-18 shows the phase-in caps, phase-in year, and maximum
penetration rate through 2050 for BEV and FCEV technologies. For
comparison, the actual penetration rate of each technology in the 2020
baseline fleet is also listed in the fourth column from the left.
[[Page 49680]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.062
The BEV200 phase-in cap was informed by manufacturers' tendency to
move away from low-range vehicle offerings, in part because of consumer
hesitancy to adopt this technology. The advertised range on most
electric vehicles does not reflect extreme cold and hot real-world
driving conditions, affecting the utility of already low-range
vehicles.\188\ Many manufacturers have told DOT that the portion of
consumers willing to accept a vehicle with less than 300 miles of
electric range is extremely small, and many manufacturers do not plan
to offer vehicles with less than 300 miles of electric range. For
example, in February 2021, Tesla, the U.S.' highest-selling BEV
manufacturer, discontinued the Standard Range Model Y because its range
did not meet the company's ``standard of excellence.'' \189\ Tesla does
sell long-range versions of many of its vehicles.
---------------------------------------------------------------------------
\188\ AAA. ``AAA Electric Vehicle Range Testing.'' February
2019. https://www.aaa.com/AAA/common/AAR/files/AAA-Electric-Vehicle-Range-Testing-Report.pdf.
\189\ Baldwin, Roberto. ``Tesla Model Y Standard Range
Discontinued; CEO Musk Tweets Explanation.'' Car and Driver, 30 Apr.
2021, www.caranddriver.com/news/a35602581/elon-musk-model-y-discontinued-explanation/. Accessed May 20, 2020.
---------------------------------------------------------------------------
Furthermore, the average BEV range has steadily increased over the
past decade,\190\ perhaps in part as batteries become more cost
effective. EPA observed in its 2020 Automotive Trends Report that ``the
average range of new EVs has climbed substantially. In model year 2019
the average new EV is projected to have a 252-mile range, or about
three and a half times the range of an average EV in 2011. This
difference is largely attributable to higher production of new EVs with
much longer ranges.'' \191\ The maximum growth rate for BEV200 in the
model was set accordingly low to less than 0.1% per year. While this
rate is significantly lower than that of the other BEV technologies,
the BEV200 phase-in cap allows the penetration rate of low-range BEVs
to grow by a multiple of what is currently observed in the market.
---------------------------------------------------------------------------
\190\ 2020 EPA Automotive Trends Report, at 53, figure 4.14.
\191\ 2020 EPA Automotive Trends Report, at 53.
---------------------------------------------------------------------------
For BEV300, 400, and 500, phase-in caps are largely a reflection of
the challenges facing 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 availability.\192\ For example, Tesla has struggled
to scale production of new cells for its vehicles, and it remains a
bottleneck in the company's production capability.\193\ The Director of
Energy and Environmental Research at Toyota acknowledged in March 2021
that BEV adoption faces many challenges beyond battery availability,
including ``the cost of batteries, the need for national
infrastructure, long recharging times, limited driving range and the
need for consumer behavioral change.'' \194\ Incorporating battery
packs that provide greater amounts of electric range into vehicles also
poses its own engineering challenges. Heavy batteries and large packs
may be difficult to integrate for many vehicle configurations. 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. DOT selected the BEV400 and 500 phase-in caps
to reflect these concerns.
---------------------------------------------------------------------------
\192\ See, e.g., Cohen, Ariel. ``Manufacturers Are Struggling To
Supply Electric Vehicles With Batteries.'' Forbes, Forbes Magazine,
25 March 2020, www.forbes.com/sites/arielcohen/2020/03/25/manufacturers-are-struggling-to-supply-electric-vehicles-with-batteries. Accessed May 20, 2021.
\193\ Hyatt, Kyle. ``Tesla Will Build an Electric Van
Eventually, Elon Musk Says.'' Roadshow, CNET, 28 Jan. 2021,
www.cnet.com/roadshow/news/tesla-electric-van-elon-musk/. Accessed
May 20, 2021.
\194\ https://www.energy.senate.gov/services/files/E2EA0E4F-BAD9-452D-99CC-35BC204DE6F0.
---------------------------------------------------------------------------
The phase-in cap for FCEVs was assigned based on existing market
share as well as historical trends in FCEV production. FCEV production
share in the past five years has been extremely low, and DOT set the
phase-in cap accordingly.\195\ As with BEV200, however, the phase-in
cap still allows for the market share of FCVs to grow several times
over.
---------------------------------------------------------------------------
\195\ 2020 EPA Automotive Trends Report, at 52, figure 4.13.
---------------------------------------------------------------------------
(d) Electrification Effectiveness Modeling
For this analysis, DOT considers a range of electrification
technologies which, when modeled, result in varying levels of
effectiveness at reducing fuel consumption. As discussed above, the
modeled electrification technologies include micro hybrids, mild
hybrids, two different strong hybrids, two different plug-in hybrids
with two separate all electric ranges, full electric vehicles and
FCEVs. Each electrification technology consists of many complex sub-
systems with unique component
[[Page 49681]]
characteristics and operational modes. As discussed further below, the
systems that contribute to the effectiveness of an electrified
powertrain in the analysis include the vehicle's battery, electric
motors, power electronics, and accessory loads. Procedures for modeling
each of these sub-systems are broadly discussed below, in Section
III.C.4, and the Autonomie model documentation.
Argonne used 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 are intended to act as surrogates
predicting representative levels of effectiveness for each
electrification technology.
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 basic
building blocks that comprise an electrified powertrain in the analysis
include the 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, the electric traction
drive system (the electric machine and power electronics) and
mechanical power transmission devices. Or, for a SHEVP2, Autonomie
combines a very similar set of components to model the electric portion
of the hybrid powertrain, and then also includes the combustion engine
and related power for transmission components. See TSD Chapter 3.3.4
for a complete discussion of electrification component modeling.
As discussed earlier in Section III.C.4, 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, as discussed in Section III.C.4.196 197 198 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. This modeling approach
comports with the National Academy of Science 2015 recommendation to
use full vehicle modeling supported by application of lumped
improvements at the sub-model level.\199\ The approach allows the
isolation of technology effects in the analysis supporting an accurate
assessment.
---------------------------------------------------------------------------
\196\ See U.S. EPA, ``How Vehicles are Tested.'' https://www.fueleconomy.gov/feg/how_tested.shtml. Last accessed May 6, 2021.
\197\ See Autonomie model documentation, Chapter 6: Test
Procedures and Energy Consumption Calculations.
\198\ EPA Guidance Letter. ``EPA Test Procedures for Electric
Vehicles and Plug-in Hybrids.'' Nov. 14, 2017. https://www.fueleconomy.gov/feg/pdfs/EPA%20test%20procedure%20for%20EVs-PHEVs-11-14-2017.pdf. Last accessed May 6, 2021.
\199\ 2015 NAS report, at 292.
---------------------------------------------------------------------------
The range of effectiveness values for the electrification
technologies, for all ten vehicle technology classes, is shown in
Figure III-12. In the graph, the box shows the inner quartile range
(IQR) of the effectiveness values and whiskers extend out 1.5 x IQR.
The dots outside of the whiskers show values outside these bounds.
BILLING CODE 4910-59-P
[[Page 49682]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.063
BILLING CODE 4910-59-C
(e) Electrification Costs
The total cost to electrify a vehicle in this analysis is based on
the battery the vehicle requires, the non-battery electrification
component costs the vehicle requires, and the traditional powertrain
components that must be added or removed from the vehicle to build the
electrified powertrain.
---------------------------------------------------------------------------
\200\ The data used to create this figure can be found in the
FE_1 Adjustments file.
---------------------------------------------------------------------------
We worked collaboratively with the experts at Argonne National
Laboratory to generate battery costs using BatPaC, which is a model
designed to calculate the cost of a vehicle battery for a specified
battery power, energy, and type. Argonne used BatPaC v4.0 (October 2020
release) to create lookup tables for battery cost and mass that the
Autonomie simulations referenced when a vehicle received an electrified
powertrain. The BatPaC battery cost estimates are generated for a base
year, in this case for MY 2020. Accordingly, our BatPaC inputs
characterized the state of the market in MY 2020 and employed a widely
utilized cell chemistry (NMC622),\201\ average estimated battery pack
production volume per plant (25,000), and a plant efficiency or plant
cell yield value of 95%.
---------------------------------------------------------------------------
\201\ Autonomie model documentation, Chapter 5.9. Argonne
surveyed A2Mac1 and TBS teardown reports for electrified vehicle
batteries and of the five fully electrified vehicles surveyed, four
of those vehicles used NMC622 and one used NMC532. See also Georg
Bieker, A Global Comparison of the Life-Cycle Greenhouse Gas
Emissions of Combustion Engine and Electric Passenger Cars,
International Council on Clean Transportation (July 2021), https://theicct.org/sites/default/files/publications/Global-LCA-passenger-cars-jul2021_0.pdf (``For cars registered in 2021, the GHG emission
factors of the battery production are based on the most common
battery chemistry, NMC622-graphite batteries. . . .''); 2021 NAS
report, at 5-92 (``. . . NMC622 is the most common cathode chemistry
in 2019. . . .'').
---------------------------------------------------------------------------
For two specific electrified vehicle applications, BEV400 and
BEV500, we did not use BatPaC to generate battery pack costs. Rather,
we scaled the BatPaC-generated BEV300 costs to match the range of
BEV400 and BEV500 vehicles to compute a direct manufacturing cost for
those vehicles' batteries. We initially examined using BatPaC to model
the cost and weight of BEV400 and BEV500 packs, however, initial values
from the model could not be validated and were based on assumptions for
smaller sized battery packs. The initial results provided cost and
weight estimates for BEV400 battery packs out of alignment with current
examples of BEV400s in the market, and there are currently no examples
of BEV500 battery packs in the market against which to validate the
pack results.
Finally, to reflect how we expect batteries could fall in cost over
the timeframe considered in the analysis, we applied a learning rate to
the direct manufacturing cost. Broadly, the learning rate applied in
this analysis reflects middle-of-the-road year-over-year improvements
until MY 2032, and then the learning rates incrementally become
shallower as battery technology is expected to mature in MY 2033 and
beyond. Applying learning curves to the battery pack DMC in subsequent
analysis years lowers the cost such that the cost of a battery pack in
any future model year could be representative of the cost to
manufacture a battery pack, regardless of potentially diverse
parameters such as cell chemistry, cell format, or production volume.
[[Page 49683]]
TSD Chapter 3.3.5.1 includes more detail about the process we used
to develop battery costs for this analysis. In addition, all BatPaC-
generated direct manufacturing costs for all technology keys can be
found in the CAFE Model's Battery Costs file, and the Argonne BatPaC
Assumptions file includes the assumptions used to generate the costs,
and pack costs, pack mass, cell capacity, $/kW at the pack level, and
W/kg at the pack level for all vehicle classes.
Table III-19 and Table III-20 show an example of our battery pack
direct manufacturing costs per kilowatt hour for BEV300s for all
vehicle classes for the base year, MY 2020. The tables shown here
demonstrate how the cost per kWh varies with the size of the battery
pack. While the overall cost of a battery pack will go up for larger
kWh battery packs, the cost per kWh goes down. The amortization of
costs for components required in all battery packs across a larger
number of cells results in this reduced cost per kWh.
BILLING CODE 4910-59-P
[GRAPHIC] [TIFF OMITTED] TP03SE21.064
[[Page 49684]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.065
BILLING CODE 4910-59-C
A range of parameters can ultimately influence battery pack
manufacturing costs, including other vehicle improvements (e.g., mass
reduction technology, aerodynamic improvements, or tire rolling
resistance improvements all affect the size and energy of a battery
required to propel a vehicle where all else is equal), and the
availability of materials required to manufacture the
battery.202 203 Or, if manufacturers adopt more
electrification technology than projected in this analysis, increases
in battery pack production volume will likely lower actual battery pack
costs.
---------------------------------------------------------------------------
\202\ The cost of raw material also has a meaningful influence
on the future cost of the battery pack. As the production volume
goes up, the demand for battery critical raw materials also goes up,
which has an offsetting impact on the efficiency gains achieved
through economies of scale, improved plant efficiency, and advanced
battery cell chemistries. We do not consider future battery raw
material price fluctuations for this analysis, however that may be
an area for further exploration in future analyses.
\203\ See, e.g., Jacky Wong, EV Batteries: The Next Victim of
High Commodity Prices?, The Wall Street Journal (July 22, 2021),
https://www.wsj.com/articles/ev-batteries-the-next-victim-of-high-commodity-prices-11626950276.
---------------------------------------------------------------------------
Like the 2020 final rule, we compared our battery pack costs in
future years to battery pack costs from other sources that may or may
not account for some of these additional parameters, including varying
potential future battery chemistry and learning rates. As discussed in
TSD Chapter 3.3.5.1.4, our battery pack costs in 2025 and 2030 fell
fairly well in the middle of other sources' cost projections, with
Bloomberg New Energy Finance (BNEF) projections presenting the highest
year-over-year cost reductions,\204\ and MIT's Insights into Future
Mobility report providing an upper bound of potential future
costs.\205\ ICCT presented a similar comparison of costs from several
sources in its 2019 working paper, Update on Electric Vehicle Costs in
the United States through 2030, and predicted battery pack costs in
2025 and 2030 would drop to approximately $104/kWh and $72/kWh,
respectively,\206\ which put their projections slightly higher than
BNEF's 2019 projections. BNEF's more recent 2020 Electric Vehicle
Outlook projected average pack cost to fall below $100/kWh by
2024,\207\ while the 2021 NAS report projected that pack costs are
projected to reach $90-115 kWh by 2025.\208\
---------------------------------------------------------------------------
\204\ See Logan Goldie-Scot, A Behind the Scenes Take on
Lithium-ion Battery Prices, Bloomberg New Energy Finance (March 5,
2019), https://about.bnef.com/blog/behind-scenes-take-lithium-ion-battery-prices/.
\205\ MIT Energy Initiative. 2019. Insights into Future
Mobility. Cambridge, MA: MIT Energy Initiative. Available at http://energy.mit.edu/insightsintofuturemobility.
\206\ Nic Lutsey and Michael Nicholas, Update on electric
vehicle costs in the United States through 2030, ICCT (April 2,
2019), available at https://theicct.org/publications/update-US-2030-electric-vehicle-cost.
\207\ Bloomberg New Energy Finance (BNEF), ``Electric Vehicle
Outlook 2020,'' https://about.bnef.com/electric-vehicle-outlook/,
last accessed July 29, 2021.
\208\ 2021 NAS report, at 5-121. The 2021 NAS report assumed a 7
percent cost reduction per year from 2018 through 2030.
---------------------------------------------------------------------------
That our projected costs seem to fall between several projections
gives us some confidence that the costs in this NPRM could reasonably
represent future battery pack costs across the industry during the
rulemaking time frame. That said, we recognize that battery technology
is currently under intensive development, and that characteristics such
as cost and capability are rapidly changing. These advances are
reflected in recent aggressive projections, like those from ICCT, BNEF,
and the 2021 NAS report. As a result, we would like to seek comments,
supported by data elements as outlined below, on these characteristics.
We seek comment on the input assumptions used to generate battery
pack costs in BatPaC and the BatPaC-generated direct manufacturing
costs for the base year (MY 2020). If commenters believe that different
input assumptions should be used for battery chemistry,\209\
[[Page 49685]]
plant manufacturing volume, or plant efficiency in MY 2020, they should
provide data or other information validating such assumptions. In
addition, commenters should explain how these assumptions reasonably
represent applications across the industry in MY 2020. This is
important to align with our guiding principles to ensure that the CAFE
Model's simulation of manufacturer compliance pathways results in
impacts that we would reasonably expect to see in the real world. As
discussed above, 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 manufacturer's 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. In this case, vehicle and battery manufacturers use
different chemistries, cell types, and production processes to
manufacture electric vehicle battery packs. Any proposed alternative
costs for base year direct manufacturing costs should be able to
represent the range of costs across the industry in MY 2020 based on
different manufacturers using different approaches.
---------------------------------------------------------------------------
\209\ Note that stakeholders had commented to the 2020 final
rule that batteries using NMC811 chemistry had either recently come
into the market or was imminently coming into the market, and
therefore DOT should have selected NMC811 as the appropriate
chemistry for modeling battery pack costs. Similar to the other
technologies considered in this analysis, DOT endeavors to use
technology that is a reasonable representation of what the industry
could achieve in the model year or years under consideration, in
this case the base DMC year of 2020, as discussed above. At the time
of this current analysis, the referenced A2Mac1 teardown reports and
other reports provided the best available information about the
range of battery chemistry actually employed in the industry. At the
time of writing, DOT still has not found examples of NMC811 in
commercial application across the industry in a way that DOT
believes selecting NMC811 would have represented industry average
performance in MY 2020. As discussed in TSD Chapter 3.3.5.1.4, DOT
did analyze the potential future cost of NMC811 in the composite
learning curve generated to ensure the battery learning curve
projections are reasonable.
---------------------------------------------------------------------------
We also seek comment on the scaling used to generate direct
manufacturing costs for BEV400 and BEV500 technologies. If commenters
have additional data or information on the relationship between cost
and weight for heavier battery packs used for these higher-range BEV
applications, particularly in light truck vehicle segments, that would
be helpful as well.
In addition, we seek comment on the learning rates applied to the
battery pack costs and on the battery pack costs in future years.
Recognizing that any battery pack cost projections for future years
from our analysis or external analyses will involve assumptions that
may or may not come to pass, it would be most helpful if commenters
thoroughly explained the basis for any recommended learning rates,
including references to publicly available data or models (and if such
models are peer reviewed) where appropriate. Similarly, it would be
helpful for commenters to note where external analyses may or may not
take into account certain parameters in their battery pack cost
projections, and whether we should attempt to incorporate those
parameters in our analysis. For example, as discussed above, our
analysis does not consider raw material price fluctuations; however,
the price of battery pack raw materials will put a lower bound on NMC-
based battery prices.\210\
---------------------------------------------------------------------------
\210\ See, e.g., MIT Energy Initiative. 2019. Insights into
Future Mobility. Cambridge, MA: MIT Energy Initiative. Available at
http://energy.mit.edu/insightsintofuturemobility, at 78-9.
---------------------------------------------------------------------------
It would also be helpful if commenters explained how learning rates
or future cost projections could represent the state of battery
technology across the industry. Like other technologies considered in
this analysis, some battery and vehicle manufacturers have more
experience manufacturing electric vehicle battery packs, and some have
less, meaning that different manufacturers will be at different places
along the learning curve in future years. Note also that comments
should specify whether their referenced costs, either for MY 2020 or
for future years, are for the battery cell or the battery pack.
Ensuring our learning rates encompass these diverse parameters will
ensure that the analysis best predicts the costs and benefits
associated with future standards. We will incorporate any new
information received to the extent possible for the final rule and
future analyses.
Recognizing again that battery technology is a rapidly evolving
field and there are a range of external analyses that project battery
pack costs declining at different rates across the next decade, as
discussed above and further in the TSD, we performed four sensitivity
studies around battery pack costs that are described in PRIA Chapter
7.2.2.5. The sensitivity studies examined the impacts of increasing and
decreasing the direct cost of batteries and battery learning costs by
20 percent from central analysis levels, based on our survey of
external analyses' battery pack cost projections that fell generally
within +/-20% of our central analysis costs. We found that changing the
battery direct manufacturing costs in MY 2020 without changing the
learning rate did not produce meaningfully different outcomes for
electric vehicle technology penetration in later years, although it
resulted in the lowest technology costs. Keeping the same direct
manufacturing costs and using a steeper battery learning rate produced
slightly higher technology costs, compared to the sensitivity results
that changed battery pack direct manufacturing cost and kept learning
rate the same.
We seek comment on these conclusions, their implications for any
potential updates to battery pack costs for the final rule, and any
other external analyses that the agency should consider when validating
future battery pack cost projections.
Next, each vehicle powertrain type also receives different non-
battery electrification components. When researching costs for
different non-battery electrification components, DOT 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 vehicle's systems, or
even in the same vehicle type, depending the application.\211\ DOT
developed costs for the major non-battery electrification components on
a dollar per kilowatt hour basis using the costs presented in two
reports. DOT used a $/kW cost metric for non-battery components to
align with the normalized costs for a system's peak power rating as
presented in U.S. DRIVE's Electrical and Electronics Technical Team
(EETT) Roadmap report.\212\ This approach captures components in some
manufacturer's systems, but not all systems; however, DOT believes this
is a reasonable metric and approach to use for this analysis given the
differences in non-battery electrification component systems. This
approach allows us to scale the cost of non-battery electrification
components based on the requirements of the system. We also relied on a
teardown study of a MY 2016 Chevrolet Bolt for non-battery component
costs that were not explicitly estimated in the EETT Roadmap
report.\213\
---------------------------------------------------------------------------
\211\ For example, the MY 2020 Nissan Leaf does not have an
active cooling system whereas Chevy Bolt uses an active cooling
system.
\212\ U.S. DRIVE, Electrical and Electronics Technical Team
Roadmap (Oct. 2017), available at https://www.energy.gov/sites/prod/files/2017/11/f39/EETT%20Roadmap%2010-27-17.pdf.
\213\ Hummel et al., UBS Evidence Lab Electric Car Teardown--
Disruption Ahead?, UBS (May 18, 2017), https://neo.ubs.com/shared/d1wkuDlEbYPjF/.
---------------------------------------------------------------------------
[[Page 49686]]
To develop the learning curves for non-battery electrification
components, DOT used cost information from Argonne's 2016 Assessment of
Vehicle Sizing, Energy Consumption, and Cost through Large-Scale
Simulation of Advanced Vehicle Technologies report.\214\ The report
provided estimated cost projections from the 2010 lab year to the 2045
lab year for individual vehicle components.215 216 DOT
considered the component costs used in electrified vehicles, and
determined the learning curve by evaluating the year over year cost
change for those components. Argonne recently published a 2020 version
of the same report that included high and low cost estimates for many
of the same components, that also included a learning rate.\217\ DOT's
learning estimates generated using the 2016 report fall fairly well in
the middle of these two ranges, and therefore staff decided that
continuing to apply the learning curve estimates based on the 2016
report was reasonable. There are many sources that DOT staff could have
picked to develop learning curves for non-battery electrification
component costs, however given the uncertainty surrounding
extrapolating costs out to MY 2050, DOT believes these learning curves
provide a reasonable estimate.
---------------------------------------------------------------------------
\214\ Moawad, Ayman, Kim, Namdoo, Shidore, Neeraj, and Rousseau,
Aymeric. Assessment of Vehicle Sizing, Energy Consumption and Cost
Through Large Scale Simulation of Advanced Vehicle Technologies
(ANL/ESD-15/28). United States (2016). Available at https://www.autonomie.net/pdfs/Report%20ANL%20ESD-1528%20-%20Assessment%20of%20Vehicle%20Sizing,%20Energy%20Consumption%20and%20Cost%20through%20Large%20Scale%20Simulation%20of%20Advanced%20Vehicle%20Technologies%20-%201603.pdf.
\215\ ANL/ESD-15/28 at 116.
\216\ DOE's lab year equates to five years after a model year,
e.g., DOE's 2010 lab year equates to MY 2015.
\217\ Islam, E., Kim, N., Moawad, A., Rousseau, A. ``Energy
Consumption and Cost Reduction of Future Light-Duty Vehicles through
Advanced Vehicle Technologies: A Modeling Simulation Study Through
2050'', Report to the U.S. Department of Energy, Contract ANL/ESD-
19/10, June 2020 https://www.autonomie.net/pdfs/ANL%20-%20Islam%20-%202020%20-%20Energy%20Consumption%20and%20Cost%20Reduction%20of%20Future%20Light-Duty%20Vehicles%20through%20Advanced%20Vehicle%20Technologies%20A%20Modeling%20Simulation%20Study%20Through%202050.pdf.
---------------------------------------------------------------------------
Table III-21 shows an example of how the non-battery
electrification component costs are computed for the Medium Car and
Medium SUV non-performance vehicle classes.
BILLING CODE 4910-59-P
[GRAPHIC] [TIFF OMITTED] TP03SE21.066
[[Page 49687]]
TSD Chapter 3.3.5.2 contains more information about the non-battery
electrification components relevant to each specific electrification
technology and the sources used to develop these costs. We seek comment
on these costs, the appropriateness of the sources used to develop
these costs, and the $/kW metric used to size specific non-battery
electrification components. In addition, we seek comment on the
learning rate applied to non-battery electrification components.
Finally, the cost of electrifying a vehicle depends on the other
powertrain components that must be added or removed from a vehicle with
the addition of the electrification technology. Table III-22 below
provides a breakdown of each electrification component included for
each electrification technology type, as well as where to find the
costs in each CAFE Model input file.
[GRAPHIC] [TIFF OMITTED] TP03SE21.067
As shown in Table III-22, DOT used the cost of the CVTL2 as a proxy
for the cost of an eCVT used in PS hybrid vehicles. In its recent 2021
report, the NAS estimated the cost of eCVTs to be lower than DOT's cost
estimate for CVTL2.\218\ DOT is investigating the cost assumptions used
for the PS hybrid transmission and may update those costs for the final
rule depending on information submitted by stakeholders or other
research. DOT seeks comment on the appropriateness of the cost estimate
for eCVTs in the 2021 NAS report, or any other data that could be made
public on the costs of eCVTs.
---------------------------------------------------------------------------
\218\ A detailed cost comparison between our costs and the 2021
NAS report costs is discussed in TSD Chapter 3.3.5.3.3.
---------------------------------------------------------------------------
The following example in Table III-23 shows how the costs are
computed for a vehicle that progresses from a lower level to a higher
level of electrified powertrain. The table shows the components that
are removed and the components that are added as a GMC Acadia
progresses from a MY 2024 vehicle with only SS12V electrification
technology to a BEV300 in MY 2025. The total cost in MY 2025 is a net
cost addition to the vehicle. The same methodology could be used for
any other technology advancement in the electric technology tree
path.\219\
---------------------------------------------------------------------------
\219\ Please note that in this calculation the CAFE Model
accounts for the air conditioning and off-cycle technologies (g/
mile) applied to each vehicle model. The cost for the AC/OC
adjustments are located in the CAFE Model Scenarios file. The air
conditioning and off-cycle cost values are discussed further in TSD
Chapter 3.8.
---------------------------------------------------------------------------
[[Page 49688]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.068
BILLING CODE 4910-59-C
TSD Chapter 3.3.5.3 includes more details about how the costs
associated with the internal combustion engine, transmission, electric
machine(s), non-battery electrification components, and battery pack
for each electrified technology type are combined to create a full
electrification system cost.
4. Mass Reduction
Mass reduction is a relatively cost-effective means of improving
fuel economy, and vehicle manufacturers are expected to apply various
mass reduction technologies to meet fuel economy standards. Reducing
vehicle mass can be accomplished through several different techniques,
such as modifying and optimizing vehicle component and system designs,
part consolidation, and adopting lighter weight materials (advanced
high strength steel, aluminum, magnesium, and plastics including carbon
fiber reinforced plastics).
The cost for mass reduction depends on the type and amount of
materials used, the manufacturing and assembly processes required, and
the degree to which changes to plants and new manufacturing and
assembly equipment is needed. In addition, manufacturers may develop
expertise and invest in certain mass reduction strategies that may
affect the approaches for mass reduction they consider and the
associated costs. Manufacturers may also consider vehicle attributes
like noise-vibration-harshness (NVH), ride quality, handling, crash
safety and various acceleration metrics when considering how to
implement any mass reduction strategy. These are considered to be
aspects of performance, and for this analysis any identified pathways
to compliance are intended to maintain performance neutrality.
Therefore, mass reduction via elimination of, for example, luxury items
such as climate control, or interior vanity mirrors, leather padding,
etc., is not considered in the mass reduction pathways for this
analysis.
The automotive industry uses different metrics to measure vehicle
weight. Some commonly used measurements are vehicle curb weight,\220\
gross vehicle weight (GVW),\221\ gross vehicle weight rating
(GVWR),\222\ gross combined weight (GCVW),\223\ and equivalent test
weight (ETW),\224\ among others. The vehicle curb weight is the most
commonly used measurement when comparing vehicles. A vehicle's curb
weight is the weight of the vehicle including fluids, but without a
driver, passengers, and cargo. A vehicle's glider weight, which is
vehicle curb weight minus the powertrain weight, is used to track the
potential opportunities for weight reduction not including the
powertrain. A glider's subsystems may consist of the vehicle body,
chassis, interior, steering,
[[Page 49689]]
electrical accessory, brake, and wheels systems. The percentage of
weight assigned to the glider will remain constant for any given rule
but may change overall. For example, as electric powertrains including
motors, batteries, inverters, etc. become a greater percent of the
fleet, glider weight percentage will change compared to earlier fleets
with higher dominance of internal combustion engine (ICE) powertrains.
---------------------------------------------------------------------------
\220\ This is the weight of the vehicle with all fluids and
components but without the drivers, passengers, and cargo.
\221\ This weight includes all cargo, extra added equipment, and
passengers aboard.
\222\ This is the maximum total weight of the vehicle,
passengers, and cargo to avoid damaging the vehicle or compromising
safety.
\223\ This weight includes the vehicle and a trailer attached to
the vehicle, if used.
\224\ For the EPA two-cycle regulatory test on a dynamometer, an
additional weight of 300 lbs is added to the vehicle curb weight.
This additional 300 lbs represents the weight of the driver,
passenger, and luggage. Depending on the final test weight of the
vehicle (vehicle curb weight plus 300 lbs), a test weight category
is identified using the table published by EPA according to 40 CFR
1066.805. This test weight category is called ``Equivalent Test
Weight'' (ETW).
---------------------------------------------------------------------------
For this analysis, DOT considered six levels of mass reduction
technology that include increasing amounts of advanced materials and
mass reduction techniques applied to the glider. The mass change
associated with powertrain changes is accounted for separately. The
following sections discuss the assumptions for the six mass reduction
technology levels, the process used to assign initial analysis fleet
mass reduction assignments, the effectiveness for applying mass
reduction technology, and mass reduction costs.
(a) Mass Reduction in the CAFE Model
The CAFE Model considers six levels of mass reduction technologies
that manufacturers could use to comply with CAFE standards. The
magnitude of mass reduction in percent for each of these levels is
shown in Table III-24 for mass reductions for light trucks, passenger
cars and for gliders.
[GRAPHIC] [TIFF OMITTED] TP03SE21.069
For this analysis, DOT considers mass reduction opportunities from
the glider subsystems of a vehicle first, and then consider associated
opportunities to downsize the powertrain, which are accounted for
separately.\225\ As explained below, in the Autonomie simulations, the
glider system includes both primary and secondary systems from which a
percentage of mass is reduced for different glider weight reduction
levels; specifically, the glider includes the body, chassis, interior,
electrical accessories, steering, brakes and wheels. In this analysis,
DOT assumed the glider share is 71% of vehicle curb weight. The
Autonomie model sizes the powertrain based on the glider weight and the
mass of some of the powertrain components in an iterative process. The
mass of the powertrain depends on the powertrain size. Therefore, the
weight of the glider impacts the weight of the powertrain.\226\
---------------------------------------------------------------------------
\225\ When the mass of the vehicle is reduced by an appropriate
amount, the engine may be downsized to maintain performance. See
Section III.C.4 for more details.
\226\ Since powertrains are sized based on the glider weight for
the analysis, glider weight reduction beyond a threshold amount
during a redesign will lead to re-sizing of the powertrain. For the
analysis, the glider was used as a base for the application of any
type of powertrain. A conventional powertrain consists of an engine,
transmission, exhaust system, fuel tank, radiator and associated
components. A hybrid powertrain also includes a battery pack,
electric motor(s), generator, high voltage wiring harness, high
voltage connectors, inverter, battery management system(s), battery
pack thermal system, and electric motor thermal system.
---------------------------------------------------------------------------
DOT uses glider weight to apply non-powertrain mass reduction
technology in the CAFE Model and use Autonomie simulations to determine
the size of the powertrain and corresponding powertrain weight for the
respective glider weight. The combination of glider weight (after mass
reduction) and re-sized powertrain weight equal the vehicle curb
weight.
While there are a range of specific mass reduction technologies
that may be applied to vehicles to achieve each of the six mass
reduction levels, there are some general trends that are helpful to
illustrate some of the more widely used approaches. Typically, MR0
reflects vehicles with widespread use of mild steel structures and body
panels, and very little or no use of high strength steel or aluminum.
MR0 reflects materials applied to average vehicles in the MY 2008
timeframe. MR1-MR3 can be achieved with a steel body structure. In
going from MR1 to MR3, expect that mild steel to be replaced by high
strength and then advanced high strength steels. In going from MR3 to
MR4 aluminum is required. This will start at using aluminum closure
panels and then to get to MR4 the vehicle's primary structure will need
to be mostly made from aluminum. In the vast majority of cases, carbon
fiber technology is necessary to reach MR5, perhaps with a mix of some
aluminum. MR6 can really only be attained in anything resembling a
passenger car by make nearly every structural component from carbon
fiber. This mean the body structure and closure panels like hoods and
door skins are wholly made from carbon fiber. There may be some use of
aluminum in the suspension. TSD Chapter 3.4 includes more discussion of
the challenges involved with adopting large amounts of carbon fiber in
the vehicle fleet in the coming years.
As discussed further below, the cost studies used to generate the
cost curves assume mass can be reduced in levels that require different
materials and different components to be utilized, in a specific order.
DOT's mass reduction levels are loosely based on what materials and
components that would be required to be used for each percent of mass
reduction, based on the conclusions of those studies.
(b) Mass Reduction Analysis Fleet Assignments
To assign baseline mass reduction levels (MR0 through MR6) for
vehicles in the MY 2020 analysis fleet, DOT used previously developed
regression models to estimate curb weight for each vehicle based on
observable vehicle attributes.
[[Page 49690]]
DOT used these models to establish a baseline (MR0) curb weight for
each vehicle, and then determined the existing mass reduction
technology level by finding the difference between the vehicles actual
curb weight to the estimated regression-based value, and comparing the
difference to the values in Table III-24. DOT originally developed the
mass reduction regression models using MY 2015 fleet data; for this
analysis, DOT used MY 2016 and 2017 analysis fleet data to update the
models.
DOT believes the regression methodology is a technically sound
approach for estimating mass reduction levels in the analysis fleet.
For a detailed discussion about the regression development and use
please see TSD Chapter 3.4.2.
Manufacturers generally apply mass reduction technology at a
vehicle platform level (i.e., using the same components across multiple
vehicle models that share a common platform) to leverage economies of
scale and to manage component and manufacturing complexity, so
conducting the regression analysis at the platform level leads to more
accurate estimates for the real-world vehicle platform mass reduction
levels. The platform approach also addresses the impact of potential
weight variations that might exist for specific vehicle models, as all
the individual vehicle models are aggregated into the platform group,
and are effectively averaged using sales weighting, which minimizes the
impact of any outlier vehicle configurations.
(c) Mass Reduction Adoption Features
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 affect all vehicle
models that share a platform. In most cases, mass reduction
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. Similar to the application of engine and transmission
technologies, the CAFE Model defines a platform ``leader'' as the
vehicle variant of a given platform that has the highest level of
observed mass reduction present in the analysis fleet. If there is a
tie, the CAFE Model begins mass reduction technology on the vehicle
with the highest sales volume in model year 2020. If there remains a
tie, the model begins by choosing the vehicle with the highest
manufacturer suggested retail price (MSRP) in MY 2020. As the model
applies technologies, it effectively levels up all variants on a
platform to the highest level of mass reduction technology on the
platform. For example, if the platform leader model is already at MR3
in MY 2020, and a ``follower'' platform model starts at MR0 in MY 2020,
the follower platform model will get MR3 at its next redesign, assuming
no further mass reduction technology is applied to the leader model
before the follower models next redesign.
In addition to the platform-sharing logic employed in the model,
DOT applied phase-in caps for MR5 and MR6 (15 percent and 20 percent
reduction of a vehicle's curb weight, respectively), based on the
current state of mass reduction technology. As discussed above, for
nearly every type of vehicle, with the exception of the smallest sports
cars, a manufacturer's strategy to achieve mass reduction consistent
with MR5 and MR6 will require extensive use of carbon fiber
technologies in the vehicles' primary structures. For example, one way
of using carbon fiber technology to achieve MR6 is to develop a carbon
fiber monocoque structure. A monocoque structure is one where the outer
most skins support the primary loads of the vehicle. For example, they
do not have separate non-load bearing aero surfaces. All of the
vehicle's primary loads are supported by the monocoque. In the most
structurally efficient automotive versions, the monocoque is made from
multiple well-consolidated plies of carbon fiber infused with resin.
Such structures can require low hundreds of pounds of carbon fiber for
most passenger vehicles. Add to this another roughly equivalent mass of
petroleum-derived resins and even at aspirational prices for dry carbon
fiber of $10-20 per pound it is easy to see how direct materials alone
can easily climb into the five-figure dollar range per vehicle.
High CAFE stringency levels will push the CAFE Model to select
compliance pathways that include these higher levels of mass reduction
for vehicles produced in the mid and high hundreds of thousands of
vehicles per year. DOT assumes, based on material costs and
availability, that achieving MR6 levels of mass reduction will cost
tens of thousands of dollars per car. Therefore, application of such
technology to high volume vehicles is unrealistic today and will, with
certainty, remain so for the next several years.
The CAFE Model applies technologies to vehicles that provide a
cost-effective pathway to compliance. In some cases, the direct
manufacturing cost, indirect costs, and applied learning factor do not
capture all the considerations that make a technology more or less
costly for manufacturers to apply in the real world. For example, there
are direct labor, R&D overhead, manufacturing overhead, and amortized
tooling costs that will likely be higher for carbon fiber production
than current automotive steel production, due to fiber handling
complexities. In addition, R&D overhead will also increase because of
the knowledge base for composite materials in automotive applications
is simply not as deep as it is for steel and aluminum. Indeed, the
intrinsic anisotropic mechanical properties of composite materials
compared to the isotropic properties of metals complicates the design
process. Added testing of these novel anisotropic structures and their
associated costs will be necessary for decades. Adding up all these
contributing costs, the price tag for a passenger car or truck
monocoque would likely be multiple tens of thousands of dollars per
vehicle. This would be significantly more expensive than transitioning
to hybrid or fully electric powertrains and potentially less effective
at achieving CAFE compliance.
In addition, the CAFE Model does not currently enable direct
accounting for the stranded capital associated with a transition away
from stamped sheet metal construction to molded composite materials
construction. For decades, or in some cases half-centuries, car
manufacturers have invested billions of dollars in capital for
equipment that supports the industry's sheet metal forming paradigm. A
paradigm change to tooling and equipment developed to support molding
carbon fiber panels and monocoque chassis structures would leave that
capital stranded in equipment that would be rendered obsolete. Doing
this is possible, but the financial ramifications are not currently
reflected in the CAFE Model for MR5 and MR6 compliance pathways.
Financial matters aside, carbon fiber technology and how it is best
used to produce lightweight primary automotive structures is far from
mature. In fact, no car company knows for sure the best way to use
carbon fiber to make a passenger car's primary structure. Using this
technology in passenger cars is far more complex than using it in
racing cars where passenger egress, longevity, corrosion protection,
crash protection,
[[Page 49691]]
etc. are lower on the list of priorities for the design team. BMW may
be the manufacturer most able accurately opine on the viability of
carbon fiber technology for primary structure on high-volume passenger
cars, and even it decided to use a mixed materials solution for their
next generation of EVs (the iX and i4) after the i3, thus eschewing a
wholly carbon fiber monocoque structure.
Another factor limiting the application of carbon fiber technology
to mass volume passenger vehicles is indeed the availability of dry
carbon fibers. There is high global demand from a variety of industries
for a limited supply of carbon fibers. Aerospace, military/defense, and
industrial applications demand most of the carbon fiber currently
produced. Today, only roughly 10% of the global dry fiber supply goes
to the automotive industry, which translates to the global supply base
only being able to support approximately 70k cars.\227\
---------------------------------------------------------------------------
\227\ J. Sloan, ``Carbon Fiber Suppliers Gear up for Next
Generation Growth,'' compositesworld.com, February 11, 2020.
---------------------------------------------------------------------------
To account for these cost and production considerations, including
the limited global supply of dry carbon fiber, DOT applied phase-in
caps that limited the number of vehicles that can achieve MR5 and M6
levels of mass reduction in the CAFE Model. DOT applied a phase-in cap
for MR5 level technology so that 75 percent of the vehicle fleet
starting in 2020 could employ the technology, and the technology could
be applied to 100 percent of the fleet by MY 2022. DOT also applied a
phase-in cap for MR6 technology so that five percent of the vehicle
fleet starting in MY 2020 could employ the technology, and the
technology could be applied to 10 percent of the fleet by MY 2025.
To develop these phase-in caps, DOT chose a 40,000 unit thresholds
for both MR5 and MR6 technology (80,000 units total), because it
roughly reflects the number of BMW i3 cars produced per year
worldwide.\228\ As discussed above, the BMW i3 is the only high-volume
vehicle currently produced with a primary structure mostly made from
carbon fiber (except the skateboard, which is aluminum). Because mass
reduction is applied at the platform level (meaning that every car of a
given platform would receive the technology, not just special low
volume versions of that platform), only platforms representing 40,000
vehicles or less are eligible to apply MR5 and MR6 toward CAFE
compliance. Platforms representing high volume sales, like a Chevrolet
Traverse, for example, where hundreds of thousands are sold per year,
are therefore blocked from access to MR5 and MR6 technology. There are
no phase in caps for mass reduction levels MR1, MR2, MR3, or MR4.
---------------------------------------------------------------------------
\228\ However, even this number is optimistic because only a
small fraction of i3 cars are sold in the U.S. market, and combining
MR5 and MR6 allocations equates to 80k vehicles, not 40k.
Regardless, if the auto industry ever seriously committed to using
carbon fiber in mainstream high-volume vehicles, competition with
the other industries would rapidly result in a dramatic increase in
price for dry fiber. This would further stymie the deployment of
this technology in the automotive industry.
---------------------------------------------------------------------------
In addition to determining that the caps were reasonable based on
current global carbon fiber production, DOT determined that the MR5
phase-in cap is consistent with the DOT lightweighting study that found
that a 15 percent curb weight reduction for the fleet is possible
within the rulemaking timeframe.\229\
---------------------------------------------------------------------------
\229\ Singh, Harry. (2012, August). Mass Reduction for Light-
Duty Vehicles for Model Years 2017-2025. (Report No. DOT HS 811
666). Program Reference: DOT Contract DTNH22-11-C-00193. Contract
Prime: Electricore, Inc, at 356, Figure 397.
---------------------------------------------------------------------------
These phase-in caps appropriately function as a proxy for the cost
and complexity currently required (and that likely will continue to be
required until manufacturing processes evolve) to produce carbon fiber
components. Again, MR6 technology in this analysis reflects the use of
a significant share of carbon fiber content, as seen through the BMW i3
and Alfa Romeo 4c as discussed above.
Given the uncertainty and fluid nature of knowledge around higher
levels of mass reduction technology, DOT welcomes comments on how to
most cost effectively use carbon fiber technology in high-volume
passenger cars. Financial implementation estimates for this technology
are equally as welcome.
(d) Mass Reduction Effectiveness Modeling
As discussed in Section III.C.4, Argonne developed a database of
vehicle attributes and characteristics for each vehicle technology
class that included over 100 different attributes. Some examples from
these 100 attributes include frontal area, drag coefficient, fuel tank
weight, transmission housing weight, transmission clutch weight, hybrid
vehicle components, and weights for components that comprise engines
and electric machines, tire rolling resistance, transmission gear
ratios, and final drive ratio. Argonne used these attributes to
``build'' each vehicle that it used for the effectiveness modeling and
simulation. Important for precisely estimating the effectiveness of
different levels of mass reduction is an accurate list of initial
component weights that make up each vehicle subsystem, from which
Autonomie considered potential mass reduction opportunities.
As stated above, glider weight, or the vehicle curb weight minus
the powertrain weight, is used to determine the potential opportunities
for weight reduction irrespective of the type of powertrain.\230\ This
is because weight reduction can vary depending on the type of
powertrain. For example, an 8-speed transmission may weigh more than a
6-speed transmission, and a basic engine without variable valve timing
may weigh more than an advanced engine with variable valve timing.
Autonomie simulations account for the weight of the powertrain system
inherently as part of the analysis, and the powertrain mass accounting
is separate from the application and accounting for mass reduction
technology levels that are applied to the glider in the simulations.
Similarly, Autonomie also accounts for battery and motor mass used in
hybrid and electric vehicles separately. This secondary mass reduction
is discussed further below.
---------------------------------------------------------------------------
\230\ Depending on the powertrain combination, the total curb
weight of the vehicle includes glider, engine, transmission and/or
battery pack and motor(s).
---------------------------------------------------------------------------
Accordingly, in the Autonomie simulations, mass reduction
technology is simulated as a percentage of mass removed from the
specific subsystems that make up the glider, as defined for that set of
simulations (including the non-powertrain secondary mass systems such
as the brake system). For the purposes of determining a reasonable
percentage for the glider, DOT in consultation with Argonne examined
glider weight data available in the A2Mac1 database,\231\ in addition
to the NHTSA MY 2014 Chevrolet Silverado lightweighting study
(discussed further below). Based on these studies, DOT assumed that the
glider weight comprised 71 percent of the vehicle curb weight. TSD
Chapter 3.4.4 includes a detailed breakdown of the components that DOT
considered to arrive at the conclusion that a glider, on average,
represents 71% of a vehicle's curb weight.
---------------------------------------------------------------------------
\231\ A2Mac1: Automotive Benchmarking, https://a2mac1.com.
---------------------------------------------------------------------------
Any mass reduction due to powertrain improvements is accounted for
separately from glider mass reduction. Autonomie considers several
components for powertrain mass reduction, including engine downsizing,
[[Page 49692]]
and transmission, fuel tank, exhaust systems, and cooling system
lightweighting.
The 2015 NAS report suggested an engine downsizing opportunity
exists when the glider mass is lightweighted by at least 10%. The 2015
NAS report also suggested that 10% lightweighting of the glider mass
alone would boost fuel economy by 3% and any engine downsizing
following the 10% glider mass reduction would provide an additional 3%
increase in fuel economy.\232\ The 2011 Honda Accord and 2014 Chevrolet
Silverado lightweighting studies applied engine downsizing (for some
vehicle types but not all) when the glider weight was reduced by 10
percent. Accordingly, this analysis limited engine resizing to several
specific incremental technology steps as in the 2018 CAFE NPRM (83 FR
42986, Aug. 24, 2018) and 2020 final rule; important for this
discussion, engines in the analysis were only resized when mass
reduction of 10% or greater was applied to the glider mass, or when one
powertrain architecture was replaced with another architecture.
---------------------------------------------------------------------------
\232\ National Research Council. 2015. Cost, Effectiveness, and
Deployment of Fuel Economy Technologies for Light-Duty Vehicles.
Washington, DC--The National Academies Press. https://doi.org/10.17226/21744.
---------------------------------------------------------------------------
Specifically, we allow engine resizing upon adoption of 7.1%,
10.7%, 14.2%, and 20% curb weight reduction, but not at 3.6% and
5.3%.\233\ Resizing is also allowed upon changes in powertrain type or
the inheritance of a powertrain from another vehicle in the same
platform. The increments of these higher levels of mass reduction, or
complete powertrain changes, more appropriately match the typical
engine displacement increments that are available in a manufacturer's
engine portfolio.
---------------------------------------------------------------------------
\233\ These curb weight reductions equate to the following
levels of mass reduction as defined in the analysis: MR3, MR4, MR5
and MR6, but not MR1 and MR2; additional discussion of engine
resizing for mass reduction can be found in Section III.C.4 and TSD
Chapter 2.4.
---------------------------------------------------------------------------
Argonne performed a regression analysis of engine peak power versus
weight for a previous analysis based on attribute data taken from the
A2Mac1 benchmarking database, to account for the difference in weight
for different engine types. For example, to account for weight of
different engine sizes like 4-cylinder versus 8-cylinder, Argonne
developed a relationship curve between peak power and engine weight
based on the A2Mac1 benchmarking data. We use this relationship to
estimate mass for all engine types regardless of technology type (e.g.,
variable valve lift and direct injection). DOT applied weight
associated with changes in engine technology by using this linear
relationship between engine power and engine weight from the A2Mac1
benchmarking database. When a vehicle in the analysis fleet with an 8-
cylinder engine adopted a more fuel-efficient 6-cylinder engine, the
total vehicle weight would reflect the updated engine weight with two
less cylinders based on the peak power versus engine weight
relationship.
When Autonomie selects a powertrain combination for a lightweighted
glider, the engine and transmission are selected such that there is no
degradation in the performance of the vehicle relative to the baseline
vehicle. The resulting curb weight is a combination of the
lightweighted glider with the resized and potentially new engine and
transmission. This methodology also helps in accurately accounting for
the cost of the glider and cost of the engine and transmission in the
CAFE Model.
Secondary mass reduction is possible from some of the components in
the glider after mass reduction has been incorporated in primary
subsystems (body, chassis, and interior). Similarly, engine downsizing
and powertrain secondary mass reduction is possible after certain level
of mass reduction is incorporated in the glider. For the analysis, the
agencies include both primary mass reduction, and when there is
sufficient primary mass reduction, additional secondary mass reduction.
The Autonomie simulations account for the aggregate of both primary and
secondary glider mass reduction, and separately for powertrain mass.
Note that secondary mass reduction is integrated into the mass
reduction cost curves. Specifically, the NHTSA studies, upon which the
cost curves depend, first generated costs for lightweighting the
vehicle body, chassis, interior, and other primary components, and then
calculated costs for lightweighting secondary components. Accordingly,
the cost curves reflect that, for example, secondary mass reduction for
the brake system is only applied after there has been sufficient
primary mass reduction to allow the smaller brake system to provide
safe braking performance and to maintain mechanical functionality.
DOT enhanced the accuracy of estimated engine weights by creating
two curves to represent separately naturally aspirated engine designs
and turbocharged engine designs.\234\ This achieves two benefits.
First, small naturally aspirated 4-cylinder engines that adopted
turbocharging technology reflected the increased weight of associated
components like ducting, clamps, the turbocharger itself, a charged air
cooler, wiring, fasteners, and a modified exhaust manifold. Second,
larger cylinder count engines like naturally aspirated 8-cylinder and
6-cylinder engines that adopted turbocharging and downsized
technologies would have lower weight due to having fewer engine
cylinders. For this analysis, a naturally aspirated 8-cylinder engine
that adopts turbocharging technology and is downsized to a 6-cylinder
turbocharged engine appropriately reflects the added weight of the
turbocharging components, and the lower weight of fewer cylinders.
---------------------------------------------------------------------------
\234\ See Autonomie model documentation, Chapter 5.2.9. Engine
Weight Determination.
---------------------------------------------------------------------------
The range of effectiveness values for the mass reduction
technologies, for all ten vehicle technology classes are shown in
Figure III-13. In the graph, the box shows the inner quartile range
(IQR) of the effectiveness values and whiskers extend out 1.5 x IQR.
The dots outside of the whiskers show a few values outside these
ranges. As discussed earlier, Autonomie simulates all possible
combinations of technologies for fuel consumption improvements. For a
few technology combinations mass reduction has minimal impact on
effectiveness on the regulatory 2-cycle test. For example, if an engine
is operating in an efficient region of the fuel map on the 2-cycle test
further reduction of mass may have smaller improvement on the
regulatory cycles. Figure III-13 shows the range improvements based on
the full range of other technology combinations considered in the
analysis.
[[Page 49693]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.070
(e) Mass Reduction Costs
The CAFE Model analysis handles mass reduction technology costs
differently than all other technology costs. Mass reduction costs are
calculated as an average cost per pound over the baseline (MR0) for a
vehicle's glider weight. While the definitions of glider may vary, DOT
referenced the same dollar per pound of curb weight to develop costs
for different glider definitions. In translating these values, DOT took
care to track units ($/kg vs. $/lb) and the reference for percentage
improvements (glider vs. curb weight).
DOT calculated the cost of mass reduction on a glider weight basis
so that the weight of each powertrain configuration could be directly
and separately accounted for. This approach provides the true cost of
mass reduction without conflating the mass change and costs associated
with downsizing a powertrain or adding additional advanced powertrain
technologies. Hence, the mass reduction costs in this proposal reflect
the cost of mass reduction in the glider and do not include the mass
reduction associated with engine downsizing. The mass reduction and
costs associated with engine downsizing are accounted for separately.
A second reason for using glider share instead of curb weight is
that it affects the absolute amount of curb weight reduction applied,
and therefore cost per pound for the mass reduction changes with the
change in the glider share. The cost for removing 20 percent of the
glider weight when the glider represents 75 percent of a vehicle's curb
weight is not the same as the cost for removing 20 percent of the
glider weight when the glider represents 50 percent of the vehicle's
curb weight. For example, the glider share of 79 percent of a 3,000-
pound curb weight vehicle is 2,370 lbs, while the glider share of 50
percent of a 3,000-pound curb weight vehicle is 1,500 lbs, and the
glider share of 71 percent of a 3,000-pound curb weight vehicle is
2,130 lbs. The mass change associated with 20 percent mass reduction is
474 lbs for 79 percent glider share (=[3,000 lbs x 79% x 20%]), 300 lbs
for 50 percent glider share (=[3,000 lbs x 50% x 20%]), and 426 lbs for
71 percent glider share (=[3,000 lbs x 71% x 20%]). The mass reduction
cost studies that DOT relied on to develop mass reduction costs for
this analysis show that the cost for mass reduction varies with the
amount of mass reduction. Therefore, for a fixed glider mass reduction
percentage, different glider share assumptions will have different
costs.
DOT considered several sources to develop the mass reduction
technology cost curves. Several mass reduction studies have used either
a mid-size passenger car or a full-size pickup truck as an exemplar
vehicle to demonstrate the technical and cost feasibility of mass
reduction. While the findings of these studies may not apply directly
to different vehicle classes, the cost estimates derived for the mass
reduction technologies identified in these studies can be useful for
formulating general estimates of costs. As discussed further below, the
mass reduction cost curves developed for this analysis are based on two
lightweighting studies, and DOT also updated the curves based on more
[[Page 49694]]
recent studies to better account for the cost of carbon fiber needed
for the highest levels of mass reduction technology. The two studies
used for MR1 through MR4 costs included the teardown of a MY 2011 Honda
Accord and a MY 2014 Chevrolet Silverado pickup truck, and the carbon
fiber costs required for MR5 and MR6 were updated based on the 2021 NAS
report.\235\
---------------------------------------------------------------------------
\235\ 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 and MR6) were the same for all segments.
---------------------------------------------------------------------------
Both teardown studies are structured to derive the estimated cost
for each of the mass reduction technology levels. DOT relied on the
results of those studies because they considered an extensive range of
material types, material gauge, and component redesign while taking
into account real world constraints such as manufacturing and assembly
methods and complexity, platform-sharing, and maintaining vehicle
utility, functionality and attributes, including safety, performance,
payload capacity, towing capacity, handling, NVH, and other
characteristics. In addition, DOT determined that the baseline vehicles
and mass reduction technologies assessed in the studies are still
reasonably representative of the technologies that may be applied to
vehicles in the MY 2020 analysis fleet to achieve up to MR4 level mass
reduction in the rulemaking timeframe. DOT adjusted the cost estimates
derived from the two studies to reflect the assumption that a vehicle's
glider weight consisted of 71% of the vehicle's curb weight, and mass
reduction as it pertains to achieving MR0-MR6 levels would only come
from the glider.
As discussed above, achieving the highest levels of mass reduction
often necessitates extensive use of advanced materials like higher
grades of aluminum, magnesium, or carbon fiber. For the 2020 final
rule, DOT provided a survey of information available regarding carbon
fiber costs compared to the costs DOT presented in the final rule based
on the Honda Accord and Chevrolet Silverado teardown studies. In the
Honda Accord study, the estimated cost of carbon fiber was $5.37/kg,
and the cost of carbon fiber used in the Chevy Silverado study was
$15.50/kg. The $15.50 estimate closely matched the cost estimates from
a BMW i3 teardown analysis,\236\ the cost figures provided by Oak Ridge
National Laboratory for a study from the IACMI Composites
Institute,\237\ and from a Ducker Worldwide presentation at the CAR
Management Briefing Seminar.\238\
---------------------------------------------------------------------------
\236\ Singh, Harry, FSV Body Structure Comparison with 2014 BMW
i3, Munro and Associates for World Auto Steel (June 3, 2015).
\237\ IACMI Baseline Cost and Energy Metrics (March 2017),
available at https://iacmi.org/wp-content/uploads/2017/12/IACMI-Baseline-Cost-and-Energy-Metrics-March-2017.pdf.
\238\ Ducker Worldwide, The Road Ahead--Automotive Materials
(2016), https://societyofautomotiveanalysts.wildapricot.org/resources/Pictures/SAA%20Sumit%20slides%20for%20Abey%20Abraham%20of%20Ducker.pdf.
---------------------------------------------------------------------------
For this analysis, DOT relied on the cost estimates for carbon
fiber construction that the National Academies detailed in the 2021
Assessment of Technologies for Improving Fuel Economy of Light-Duty
Vehicles--Phase 3 recently completed by the National Academies.\239\
The study indicates that the sum of direct materials costs plus
manufacturing costs for carbon fiber composite automotive components is
$25.97 per pound in high volume production. In order to use this cost
in the CAFE Model it must be put in terms of dollars per pound saved.
Using an average vehicle curb weight of 4000 lbs, a 71% glider share
and the percent mass savings associated with MR5 and MR6, it is
possible to calculate the number of pounds to be removed to attain MR5
and MR6. Also taken from the NAS study is the assertion that carbon
fiber substitution for steel in an automotive component results in a
50% mass reduction. Combining all this together, carbon fiber
technology offers weight savings at $24.60 per pound saved. This dollar
per pound savings figure must also be converted to a retail price
equivalent (RPE) to account for various commercial costs associated
with all automotive components. This is accomplished by multiplying
$24.60 by the factor 1.5. This brings the cost per pound saved for
using carbon fiber to $36.90 per pound saved.\240\ The analysis uses
this cost for achieving MR5 and MR6.
---------------------------------------------------------------------------
\239\ 2021 NAS report, at 7-242-3.
\240\ See MR5 and MR6 CFRP Cost Increase Calculator.xlsx in the
docket for this action.
---------------------------------------------------------------------------
Table III-25 and Table III-26 show the cost values (in dollars per
pound) used in the CAFE Model with MR1-4 costs based on the cost curves
developed from the MY 2011 Honda Accord and MY 2014 Chevrolet Silverado
studies, and the updated MR5 and MR6 values that account for the
updated carbon fiber costs from the 2021 NAS report. Both tables assume
a 71% glider share.
[GRAPHIC] [TIFF OMITTED] TP03SE21.071
[GRAPHIC] [TIFF OMITTED] TP03SE21.072
[[Page 49695]]
There is a dramatic increase in cost going from MR4 to MR5 and MR6
for all classes of vehicles. However, while the increase in cost going
from MR4 to MR5 and MR6 is dramatic, the MY 2011 Honda Accord study,
the MY 2014 Chevrolet Silverado study, and the 2021 NAS report all
included a steep increase to achieve the highest levels of mass
reduction technology. As noted above, DOT seeks comment on any
additional information about the costs of achieving the highest levels
of mass reduction technology, including from publicly available sources
or data that could be made publicly available.
Table III-27 provides an example of mass reduction costs in 2018$
over select model years for the medium car and pickup truck technology
classes as a dollar per pound value. The table shows how the $/lb value
for each mass reduction level decreases over time because of cost
learning. For a full list of the $/lb mass reduction costs used in the
analysis across all model years, see the Technologies file.
[GRAPHIC] [TIFF OMITTED] TP03SE21.073
5. Aerodynamics
The energy required to overcome aerodynamic drag accounts for a
significant portion of the energy consumed by a vehicle and can become
the dominant factor for a vehicle's energy consumption at high speeds.
Reducing aerodynamic drag can, therefore, be an effective way to reduce
fuel consumption and emissions.
Aerodynamic drag is proportional to the frontal area (A) of the
vehicle and coefficient of drag (Cd), such that aerodynamic
performance is often expressed as the product of the two values,
CdA, which is also known as the drag area of a vehicle. The
coefficient of drag (Cd) is a dimensionless value that
essentially represents the aerodynamic efficiency of the vehicle shape.
The frontal area (A) is the cross-sectional area of the vehicle as
viewed from the front. It acts with the coefficient of drag as a sort
of scaling factor, representing the relative size of the vehicle shape
that the coefficient of drag describes. The force imposed by
aerodynamic drag increases with the square of vehicle velocity,
accounting for the largest contribution to road loads at higher speeds.
Aerodynamic drag reduction can be achieved via two approaches,
either by reducing the drag coefficient or reducing vehicle frontal
area, with two different categories of technologies, passive and active
aerodynamic technologies. Passive aerodynamics refers to aerodynamic
attributes that are inherent to the shape and size of the vehicle,
including any components of a fixed nature. Active aerodynamics refers
to technologies that variably deploy in response to driving conditions.
These include technologies such as active grille shutters, active air
dams, and active ride height adjustment. It is important to note that
manufacturers may employ both passive and active aerodynamic
technologies to achieve aerodynamic drag values.
The greatest opportunity for improving aerodynamic performance is
during a vehicle redesign cycle when significant changes to the shape
and size of the vehicle can be made. Incremental improvements may also
be achieved during mid-cycle vehicle refresh using restyled exterior
components and add-on devices. Some examples of potential technologies
applied during mid-cycle refresh are restyled front and rear fascia,
modified front air dams and rear valances, addition of rear deck lips
and underbody panels, and low-drag exterior mirrors. While
manufacturers may nudge the frontal area of the vehicle during
redesigns, large changes in frontal area are typically not possible
without impacting the utility and interior space of the vehicle.
Similarly, manufacturers may improve Cd by changing the
frontal shape of the vehicle or lowering the height of the vehicle,
among other approaches, but the form drag of certain body styles and
airflow needs for engine cooling often limit how much Cd may
be improved.
The following sections discuss the four levels of aerodynamic
improvements considered in the CAFE Model, how the agency assigned
baseline aerodynamic technology levels to vehicles in the MY 2020
fleet, the effectiveness improvements for the addition of aerodynamic
technologies to vehicles, and the costs for adding that aerodynamic
technology.
(a) Aerodynamic Technologies in the CAFE Model
DOT bins aerodynamic improvements into four levels--5%, 10%, 15%
and 20% aerodynamic drag improvement values over a baseline computed
for each vehicle body style--which correspond to AERO5, AERO10, AERO15,
and AERO20, respectively.
The aerodynamic improvements technology pathway consists of a
linear progression, with each level superseding all previous levels, as
seen in Figure III-14.
[[Page 49696]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.074
While the four levels of aerodynamic improvements are technology-
agnostic, DOT built a pathway to compliance for each level based on
aerodynamic data from a National Research Council (NRC) of Canada-
sponsored wind tunnel testing program. The program included an
extensive review of production vehicles utilizing these technologies,
and industry comments.241 242 Again, these technology
combinations are intended to show a potential way for a manufacturer to
achieve each aerodynamic improvement level; however, in the real world,
manufacturers may implement different combinations of aerodynamic
technologies to achieve a percentage improvement over their baseline
vehicles.
---------------------------------------------------------------------------
\241\ Larose, G., Belluz, L., Whittal, I., Belzile, M. et al.,
``Evaluation of the Aerodynamics of Drag Reduction Technologies for
Light-duty Vehicles--a Comprehensive Wind Tunnel Study,'' SAE Int.
J. Passeng. Cars--Mech. Syst. 9(2):772-784, 2016, https://doi.org/10.4271/2016-01-1613.
\242\ Larose, Guy & Belluz, Leanna & Whittal, Ian & Belzile,
Marc & Klomp, Ryan & Schmitt, Andreas. (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. 10.4271/2016-01-
1613.
---------------------------------------------------------------------------
Table III-28 and Table III-29 show the aerodynamic technologies
that could be used to achieve 5%, 10%, 15% and 20% improvements in
passenger cars, SUVs, and pickup trucks. As discussed further in
Section III.D.5.c, AERO20 cannot be applied to pickup trucks in the
model, which is why there is no pathway to AERO20 shown in Table III-
29. While some aerodynamic improvement technologies can be applied
across vehicle classes, like active grille shutters (used in the 2015
Chevrolet Colorado),\243\ DOT determined that there are limitations
that make it infeasible for vehicles with some body styles to achieve a
20% reduction in the coefficient of drag from their baseline. This
technology path is an example of how a manufacturer could reach each
AERO level, but they would not necessarily be required to use the
technologies.
---------------------------------------------------------------------------
\243\ Chevrolet Product Information, available at https://media.chevrolet.com/content/media/us/en/chevrolet/vehicles/colorado/2015/_jcr_content/iconrow/textfile/file.res/15-PG-Chevrolet-Colorado-082218.pdf.
---------------------------------------------------------------------------
[[Page 49697]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.075
[GRAPHIC] [TIFF OMITTED] TP03SE21.076
BILLING CODE 4910-59-C
As discussed further in Section III.D.8, this analysis assumes
manufacturers apply off-cycle technology at rates defined in the Market
Data file. While the AERO levels in the analysis are technology-
agnostic, achieving AERO20 improvements does assume the use of active
grille shutters, which is an off-cycle technology.
(b) Aerodynamics Analysis Fleet Assignments
DOT uses a relative performance approach to assign an initial level
of aerodynamic drag reduction technology to each vehicle. Each AERO
level represents a percent reduction in a vehicle's aerodynamic drag
coefficient (Cd) from a baseline value for its body style.
For a vehicle to achieve AERO5, the Cd must be at least 5%
below the baseline for the body style; for AERO10, 10% below the
baseline, and so on. Baseline aerodynamic assignment is therefore a
three step process: Each vehicle in the fleet is assigned a body style,
the average drag coefficient is calculated for each body style, and the
drag coefficient for each vehicle model is compared to the average for
the body style.
Every vehicle in the fleet is assigned a body style; available body
styles included convertible, coupe, sedan, hatchback, wagon, SUV,
pickup, minivan, and van. These assignments do not necessarily match
the body styles used by manufacturers for marketing purposes. Instead,
they are assigned based on analyst judgement, taking into account how a
vehicle's AERO and vehicle technology class assignments are affected.
Different body styles offer different utility and have varying levels
[[Page 49698]]
of baseline form drag. In addition, frontal area is a major factor in
aerodynamic forces, and the frontal area varies by vehicle. This
analysis considers both frontal area and body style as utility factors
affecting aerodynamic forces; therefore, the analysis assumes all
reduction in aerodynamic drag forces come from improvement in the drag
coefficient.
Average drag coefficients for each body style were computed using
the MY 2015 drag coefficients published by manufacturers, which were
used as the baseline values in the analysis. DOT harmonizes the
Autonomie simulation baselines with the analysis fleet assignment
baselines to the fullest extent possible.\244\
---------------------------------------------------------------------------
\244\ See TSD Chapter 2.4.1 for a table of vehicle attributes
used to build the Autonomie baseline vehicle models. That table
includes a drag coefficient for each vehicle class.
---------------------------------------------------------------------------
The drag coefficients used for each vehicle in the MY 2020 analysis
fleet are sourced from manufacturer specification sheets, when
possible. However, drag coefficients for the MY 2020 vehicles were not
consistently reported publicly. If no drag coefficient was reported,
analyst judgment is sometimes used to assign an AERO level. If no level
was manually assigned, the drag coefficient obtained from manufacturers
to build the MY 2016 fleet,\245\ was used, if available. The MY 2016
drag coefficient values may not accurately reflect the current
technology content of newer vehicles but are, in many cases, the most
recent data available.
---------------------------------------------------------------------------
\245\ See 83 FR 42986 (Aug. 24, 2018). The MY 2016 fleet was
built to support the 2018 NPRM.
---------------------------------------------------------------------------
(c) Aerodynamics Adoption Features
As already discussed, DOT engineers use a relative performance
approach to assign current aerodynamic technology (AERO) level to a
vehicle. For some body styles with different utility, such as pickup
trucks, SUVs and minivans, frontal area can vary, and this can affect
the overall aerodynamic drag forces. In order to maintain vehicle
utility and functionality related to passenger space and cargo space,
we assume all technologies that improve aerodynamic drag forces do so
by reducing Cd while maintaining frontal area.
Technology pathway logic for levels of aerodynamic improvement
consists of a linear progression, with each level superseding all
previous ones. Technology paths for AERO are illustrated in Figure III-
14.
The highest levels of AERO are not considered for certain body
styles. In these cases, this means that AERO20, and sometimes AERO15,
can neither be assigned in the baseline fleet nor adopted by the model.
For these body styles, there are no commercial examples of drag
coefficients that demonstrate the required AERO15 or AERO20 improvement
over baseline levels. DOT also deemed the most advanced levels of
aerodynamic drag simulated as not technically practicable given the
form drag of the body style and costed technology, especially given the
need to maintain vehicle functionality and utility, such as interior
volume, cargo area, and ground clearance. In short, DOT `skipped'
AERO15 for minivan body styles, and `skipped' AERO20 for convertible,
minivan, pickup, and wagon body styles.
DOT also does not allow application of AERO15 and AERO20 technology
to vehicles with more than 780 horsepower. There are two main types of
vehicles that informed this threshold: performance internal combustion
engine (ICE) vehicles and high-power battery electric vehicles (BEVs).
In the case of the former, the agency recognizes 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 internal combustion
engines without reducing horsepower. The baseline fleet includes 1,655
units of sales volume with limited application of aerodynamic
technologies because of ICE vehicle performance.\246\
---------------------------------------------------------------------------
\246\ Market Data file.
---------------------------------------------------------------------------
In the case of high-power battery electric vehicles, the 780-
horsepower threshold is set above the highest peak system horsepower
present on a BEV in the 2020 fleet. BEVs have different aerodynamic
behavior and considerations than ICE vehicles, allowing for features
such as flat underbodies that significantly reduce drag.\247\ 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. Note that the CAFE Model does not force high levels
of AERO adoption; rather, higher AERO levels are usually adopted
organically by BEVs because significant drag reduction allows for
smaller batteries and, by extension, cost savings. BEVs represent
252,023 units of sales volume in the baseline fleet.\248\
---------------------------------------------------------------------------
\247\ 2020 EPA Automotive Trends Report, at 227.
\248\ Market Data file.
---------------------------------------------------------------------------
(d) Aerodynamics Effectiveness Modeling
To determine aerodynamic effectiveness, the CAFE Model and
Autonomie used individually assigned road load technologies for each
vehicle to appropriately assign initial road load levels and
appropriately capture benefits of subsequent individual road load
improving technologies.
The current analysis included four levels of aerodynamic
improvements, AERO5, AERO10, AERO15, and AERO20, representing 5, 10,
15, and 20 percent reduction in drag coefficient (Cd),
respectively. DOT assumed that aerodynamic drag reduction could only
come from reduction in Cd and not from reduction of frontal
area, to maintain vehicle functionality and utility, such as passenger
space, ingress/egress ergonomics, and cargo space.
The effectiveness values for the aerodynamic improvement levels
relative to AERO0, for all ten vehicle technology classes, are shown in
Figure III-15. Each of the effectiveness values shown is representative
of the improvements seen for upgrading only the listed aerodynamic
technology level for a given combination of other technologies. In
other words, the range of effectiveness values seen for each specific
technology (e.g., AERO 15) represents the addition of AERO15 technology
(relative to AERO0 level) for every technology combination that could
select the addition of AERO15. It must be emphasized that the change in
fuel consumption values between entire technology keys is used,\249\
and not the individual technology effectiveness values. Using the
change between whole technology keys captures the complementary or non-
complementary interactions among technologies. The box shows the inner
quartile range (IQR) of the effectiveness values and whiskers extend
out 1.5 x IQR. The dots outside the whiskers show effectiveness values
outside those thresholds.
---------------------------------------------------------------------------
\249\ Technology key is the unique collection of technologies
that constitutes a specific vehicle, see TSD Chapter 2.4.7 for more
detail.
---------------------------------------------------------------------------
[[Page 49699]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.077
(e) Aerodynamics Costs
This analysis uses the AERO technology costs established in the
2020 final rule that are based on confidential business information
submitted by the automotive industry in advance of the 2018 NPRM,\251\
and on DOT's assessment of manufacturing costs for specific aerodynamic
technologies.\252\ DOT received no additional comments from
stakeholders regarding the costs established in the 2018 NPRM, and
continued to use the established costs for the 2020 final rule and this
analysis.
---------------------------------------------------------------------------
\250\ The data used to create this figure can be found in the
FE_1 Improvements file.
\251\ See the PRIA accompanying the 2018 NPRM, Chapter
6.3.10.1.2.1.2 for a discussion of these cost estimates.
\252\ See the FRIA accompanying the 2020 final rule, Chapter
VI.C.5.e.
---------------------------------------------------------------------------
Table III-30 shows examples of costs for AERO technologies as
applied to the medium car and pickup truck vehicle classes in select
model years. The cost to achieve AERO5 is relatively low, as most of
the improvements can be made through body styling changes. The cost to
achieve AERO10 is higher than AERO5, due to the addition of several
passive aerodynamic technologies, and the cost to achieve AERO15 and
AERO20 is higher than AERO10 due to use of both passive and active
aerodynamic technologies. For a full list of all absolute aerodynamic
technology costs used in the analysis across all model years see the
Technologies file.
[[Page 49700]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.078
6. Tire Rolling Resistance
Tire rolling resistance is a road load force that arises primarily
from the energy dissipated by elastic deformation of the tires as they
roll. Tire design characteristics (for example, materials,
construction, and tread design) have a strong influence on the amount
and type of deformation and the energy it dissipates. Designers can
select these characteristics to minimize rolling resistance. However,
these characteristics may also influence other performance attributes,
such as durability, wet and dry traction, handling, and ride comfort.
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.
Low rolling resistance tires are increasingly specified by OEMs in new
vehicles and are also increasingly available from aftermarket tire
vendors. They commonly include attributes such as higher inflation
pressure, material changes, tire construction optimized for lower
hysteresis, geometry changes (e.g., reduced aspect ratios), and reduced
sidewall and tread deflection. These changes are commonly accompanied
by additional changes to vehicle suspension tuning and/or suspension
design to mitigate any potential impact on other performance attributes
of the vehicle.
DOT continues to assess the potential impact of tire rolling
resistance changes on vehicle safety. DOT has been following the
industry developments and trends in application of rolling resistance
technologies to light duty vehicles. As stated in the National
Academies Press (NAP) special report on Tires and Passenger Vehicle
Fuel Economy,\253\ national crash data does not provide data about tire
structural failures specifically related to tire rolling resistance,
because the rolling resistance of a tire at a crash scene cannot be
determined. However, other metrics like brake performance compliance
test data are helpful to show trends like that stopping distance has
not changed in the last ten years,\254\ during which time many
manufacturers have installed low rolling resistance tires in their
fleet--meaning that manufacturers were successful in improving rolling
resistance while maintaining stopping distances through tire design,
tire materials, and/or braking system improvements. In addition, NHTSA
has addressed other tire-related issues through rulemaking,\255\ and
continues to research tire problems such as blowouts, flat tires, tire
or wheel deficiency, tire or wheel failure, and tire degradation.\256\
However, there are currently no data connecting low rolling resistance
tires to accident or fatality rates.
---------------------------------------------------------------------------
\253\ Tires and Passenger Vehicle Fuel Economy: Informing
Consumers, Improving Performance--Special Report 286 (2006),
available at https://www.nap.edu/read/11620/chapter/6.
\254\ See, e.g., NHTSA Office of Vehicle Safety Compliance,
Compliance Database, https://one.nhtsa.gov/cars/problems/comply/index.cfm.
\255\ 49 CFR 571.138, Tire pressure monitoring systems.
\256\ Tire-Related Factors in the Pre-Crash Phase, DOT HS 811
617 (April 2012), available at https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/811617.
---------------------------------------------------------------------------
[[Page 49701]]
NHTSA conducted tire rolling resistance tests and wet grip index
tests on original equipment tires installed on new vehicles. The tests
showed that there is no degradation in wet grip index values (no
degradation in traction) for tires with improved rolling resistance
technology. With better tire design, tire compound formulations and
improved tread design, tire manufacturers have tools to balance
stopping distance and reduced rolling resistance. Tire manufacturers
can use ``higher performance materials in the tread compound, more
silica as reinforcing fillers and advanced tread design features'' to
mitigate issues related to stopping distance.\257\
---------------------------------------------------------------------------
\257\ Jesse Snyder, A big fuel saver: Easy-rolling tires (but
watch braking) (July 21, 2008), https://www.autonews.com/article/20080721/OEM01/307219960/a-big-fuel-saver-easy-rolling-tires-but-watch-braking. Last visited December 3, 2019.
---------------------------------------------------------------------------
The following sections discuss levels of tire rolling resistance
technology considered in the CAFE Model, how the technology was
assigned in the analysis fleet, adoption features specified to maintain
performance, effectiveness, and cost.
(a) Tire Rolling Resistance in the CAFE Model
DOT continues to consider two levels of improvement for low rolling
resistance tires in the analysis: The first level of low rolling
resistance tires considered reduced rolling resistance 10 percent from
an industry-average baseline rolling resistance coefficient (RRC)
value, while the second level reduced rolling resistance 20 percent
from the baseline.\258\
---------------------------------------------------------------------------
\258\ To achieve ROLL10, the tire rolling resistance must be at
least 10 percent better than baseline (.0081 or better). To achieve
ROLL20, the tire rolling resistance must be at least 20 percent
better than baseline (.0072 or better).
---------------------------------------------------------------------------
DOT selected the industry-average RRC baseline of 0.009 based on a
CONTROLTEC study prepared for the California Air Resources Board,\259\
in addition to confidential business information submitted by
manufacturers prior to the 2018 NPRM analysis. The average RRC from the
CONTROLTEC study, which surveyed 1,358 vehicle models, was 0.009.\260\
CONTROLTEC also compared the findings of their survey with values
provided by Rubber Manufacturers Association (renamed as USTMA-U.S.
Tire Manufacturers Association) for original equipment tires. The
average RRC from the data provided by RMA was 0.0092,\261\ compared to
average of 0.009 from CONTROLTEC.
---------------------------------------------------------------------------
\259\ Technical Analysis of Vehicle Load Reduction by CONTROLTEC
for California Air Resources Board (April 29, 2015).
\260\ 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.
\261\ Technical Analysis of Vehicle Load Reduction by CONTROLTEC
for California Air Resources Board (April 29, 2015) at page 40.
---------------------------------------------------------------------------
In past agency actions, commenters have argued that based on
available data on current vehicle models and the likely possibility
that there would be additional tire improvements over the next decade,
DOT should consider ROLL30 technology, or a 30 percent reduction of
tire rolling resistance over the baseline.\262\
---------------------------------------------------------------------------
\262\ NHTSA-2018-0067-11985.
---------------------------------------------------------------------------
As stated in the Joint TSD for the MY 2017-2025 final rule (77 FR
62624, Oct. 15, 2012) and 2020 final rule, tire technologies that
enable rolling resistance improvements of 10 and 20 percent have been
in existence for many years.\263\ Achieving improvements of up to 20
percent involves optimizing and integrating multiple technologies, with
a primary contributor being the adoption of a silica tread technology.
Tire suppliers have indicated that additional innovations are necessary
to achieve the next level of low rolling resistance technology on a
commercial basis, such as improvements in material to retain tire
pressure, tread design to manage both stopping distance and wet
traction, and development of carbon black material for low rolling
resistance without the use of silica to reduce cost and weight.\264\
---------------------------------------------------------------------------
\263\ EPA-420-R-12-901, at page 3-210.
\264\ 2011 NAS report, at 103.
---------------------------------------------------------------------------
The agency believes that the tire industry is in the process of
moving automotive manufacturers towards higher levels of rolling
resistance technology in the vehicle fleet. Importantly, as shown
below, the MY 2020 fleet does include a higher percentage of vehicles
with ROLL20 technology than the MY 2017 fleet. However, DOT believes
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,\265\ among other technologies, will not be available
for widespread commercial adoption in the fleet during the rulemaking
timeframe. As a result, the agency continues to not to incorporate 30
percent reduction in rolling resistance technology. DOT will consider
adding an advanced level of tire rolling resistance technology to
future analyses, and invites comment on any updated information on
manufacturers' capabilities to add tires with higher levels of rolling
resistance to their vehicles, and consumers' willingness to accept
these tires on their vehicles.
---------------------------------------------------------------------------
\265\ Mohammad Mehdi Davari, Rolling resistance and energy loss
in tyres (May 20, 2015), available at https://www.sveafordon.com/media/42060/SVEA-Presentation_Davari_public.pdf. Last visited
December 30, 2019.
---------------------------------------------------------------------------
(b) Tire Rolling Resistance Analysis Fleet Assignments
Tire rolling resistance is not a part of tire manufacturers'
publicly released specifications and thus it is difficult to assign
this technology to the analysis fleet. Manufacturers also often offer
multiple wheel and tire packages for the same nameplates, further
increasing the complexity of this assignment. DOT employed an approach
consistent with previous rulemaking in assigning this technology. DOT
relied on previously submitted rolling resistance values that were
supplied by manufacturers in the process of building older fleets and
bolstered it with agency-sponsored tire rolling testing by
Smithers.\266\
---------------------------------------------------------------------------
\266\ See memo to Docket No. NHTSA-2021-0053, Evaluation of
Rolling Resistance and Wet Grip Performance of OEM Stock Tires
Obtained from NCAP Crash Tested Vehicles Phase One and Two. NHTSA
used tire rolling resistance coefficient values from this project to
assign baseline tire rolling resistance technology in the MY 2020
analysis fleet and is therefore providing the draft project
appendices for public review and comment.
---------------------------------------------------------------------------
DOT carried over rolling resistance assignments for nameplates
where manufacturers had submitted data on the vehicles' rolling
resistance values, even if the vehicle was redesigned. If Smithers data
was available, DOT replaced any older or missing values with that
updated data. Those vehicles for which no information was available
from either previous manufacturer submission or Smithers data were
assigned to ROLL0. All vehicles under the same nameplate were assigned
the same rolling resistance technology level even if manufacturers do
outfit different trim levels with different wheels and tires.
The MY 2020 analysis fleet includes the following breakdown of
rolling resistance technology: 44% at ROLL0, 20% at ROLL10, and 36% at
ROLL20, which shows that the majority of the fleet has now adopted some
form of improved rolling resistance technology. The majority of the
change from the MY 2017 analysis fleet has been in implementing ROLL20
technology. There is likely more proliferation of rolling resistance
technology, but we would need further information from manufacturers in
order to account for it. DOT invites comment from manufacturers on
whether these rolling
[[Page 49702]]
resistance values are still applicable, or any updated rolling
resistance values that could be incorporated in a publicly available
analysis fleet. If manufacturers submit updated information on baseline
rolling resistance assignments DOT may update those assignments for the
final rule.
(c) Tire Rolling Resistance Adoption Features
Rolling resistance technology can be adopted with either a vehicle
refresh or redesign. In some cases, low rolling resistance tires can
affect traction, which may adversely impact acceleration, braking, and
handling characteristics for some high-performance vehicles. Similar to
past rulemakings, the agency recognizes that to maintain performance,
braking, and handling functionality, some high-performance vehicles
would not adopt low rolling resistance tire technology. For cars and
SUVs with more than 405 horsepower (hp), the agency restricted the
application of ROLL20. For cars and SUVs with more than 500 hp, the
agency restricted the application of any additional rolling resistance
technology (ROLL10 or ROLL20). The agency developed these cutoffs based
on a review of confidential business information and the distribution
of rolling resistance values in the fleet.
(d) Tire Rolling Resistance Effectiveness Modeling
As discussed above, the baseline rolling resistance value from
which rolling resistance improvements are measured is 0.009, based on a
thorough review of confidential business information submitted by
industry, and a review of other literature. To achieve ROLL10, the tire
rolling resistance must be at least 10 percent better than baseline
(.0081 or better). To achieve ROLL20, the tire rolling resistance must
be at least 20 percent better than baseline (.0072 or better).
DOT determined effectiveness values for rolling resistance
technology adoption using Autonomie modeling. Figure III-16 below shows
the range of effectiveness values used for adding tire rolling
resistance technology to a vehicle in this analysis. The graph shows
the change in fuel consumption values between entire technology
keys,\267\ and not the individual technology effectiveness values.
Using the change between whole technology keys captures the
complementary or non-complementary interactions among technologies. In
the graph, the box shows the interquartile range (IQR) of the
effectiveness values and whiskers extend out 1.5 x IQR. The dots
outside of the whiskers show values for effectiveness that are outside
these bounds.
---------------------------------------------------------------------------
\267\ Technology key is the unique collection of technologies
that constitutes a specific vehicle, see TSD Chapter 2.4.7 for more
information.
---------------------------------------------------------------------------
The data points with the highest effectiveness values are almost
all exclusively BEV and FCV technology combinations for medium sized
nonperformance cars. The effectiveness for these vehicles, when the low
rolling resistance technology is applied, is amplified by a
complementary effect, where the lower rolling resistance reduces road
load and allows a smaller battery pack to be used (and still meet range
requirements). The smaller battery pack reduces the overall weight of
the vehicle, further reducing road load, and improving fuel efficiency.
This complimentary effect is experience by all the vehicle technology
classes, but the strongest effect is on the midsized vehicle non-
performance classes and is only captured in the analysis through the
use of full vehicle simulations, demonstrating the full interactions of
the technologies.
[[Page 49703]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.079
(e) Tire Rolling Resistance Costs
DOT continues to use the same DMC values for ROLL technology that
were used for the 2020 final rule which are based on NHTSA's MY 2011
CAFE final rule (74 FR 14196, March 30, 2009) and the 2006 NAS/NRC
report.\268\ Table III-31 shows the different levels of tire rolling
resistance technology cost for all vehicle classes across select model
years, which shows how the learning rate for ROLL technologies impacts
the cost. For all ROLL absolute technology costs used in the analysis
across all model years see the Technologies file.
---------------------------------------------------------------------------
\268\ ``Tires and Passenger Vehicle Fuel Economy,''
Transportation Research Board Special Report 286, National Research
Council of the National Academies, 2006, Docket No. EPA-HQ-OAR-2009-
0472-0146.
[GRAPHIC] [TIFF OMITTED] TP03SE21.080
7. Other Vehicle Technologies
Four other vehicle technologies were included in the analysis--
electric power steering (EPS), improved accessory devices (IACC), low
drag brakes (LDB), and secondary axle disconnect (SAX). The
effectiveness of these technologies was applied directly in the CAFE
Model with unique effectiveness values for each technology and for each
technology class, rather than using Autonomie effectiveness estimates.
This methodology was used in these four cases because the effectiveness
of these technologies varies little with combinations of other
technologies. Also, applying these technologies directly in the CAFE
Model significantly reduces the number of Autonomie simulations that
are needed.
(a) Electric Power Steering
Electric power steering reduces fuel consumption by reducing load
on the engine. Specifically, it reduces or eliminates the parasitic
losses associated with engine-driven power
[[Page 49704]]
steering pumps, which pump hydraulic fluid continuously through the
steering actuation system even when no steering input is present. By
selectively powering the electric assist only when steering input is
applied, the power consumption of the system is reduced in comparison
to the traditional ``always-on'' hydraulic steering system. Power
steering may be electrified on light duty vehicles with standard 12V
electrical systems and is also an enabler for vehicle electrification
because it provides power steering when the engine is off (or when no
combustion engine is present).
Power steering systems can be electrified in two ways.
Manufacturers may choose to eliminate the hydraulic portion of the
steering system and provide electric-only power steering (EPS) driven
by an independent electric motor, or they may choose to move the
hydraulic pump from a belt-driven configuration to a stand-alone
electrically driven hydraulic pump. The latter system is commonly
referred to as electro-hydraulic power steering (EHPS). As discussed in
the rulemakings, manufacturers have informed DOT that full EPS systems
are being developed for all types of light-duty vehicles, including
large trucks.
DOT described in past rulemakings that, like low drag brakes, EPS
can be difficult to observe and assign to the analysis fleet, however,
it is found more frequently in publicly available information than low
drag brakes. Based on comments received during the 2020 rulemaking, the
agency increased EPS application rate to nearly 90 percent for the 2020
final rule. The agency is maintaining this level of EPS fleet
penetration for this analysis, recognizing that some specialized,
unique vehicle types or configurations still implement hydraulically
actuated power steering systems for the baseline fleet model year.
The effectiveness of both EPS and EHPS is derived from the
decoupling of the pump from the crankshaft and is considered to be
practically the same for both. Thus, a single effectiveness value is
used for both EPS and EHPS. As indicated in the following table, the
effectiveness of EPS and EHPS varies based on the vehicle technology
class it is being applied to. This variance is a direct result of
vehicle size and the amount of energy required to turn the vehicle's
two front wheels about their vertical axis. More simply put, more
energy is required for vehicles that weigh more and, typically, have
larger tire contact patches.
[GRAPHIC] [TIFF OMITTED] TP03SE21.081
(b) Improved Accessories
Engine accessories typically include the alternator, coolant pump,
cooling fan, and oil pump, and are traditionally mechanically driven
via belts, gears, or directly by other rotating engine components such
as camshafts or the crankshaft. These can be replaced with improved
accessories (IACC), which may include high efficiency alternators,
electrically driven (i.e., on-demand) coolant pumps, electric cooling
fans, variable geometry oil pumps, and a mild regeneration strategy.
Replacing lower-efficiency and/or mechanically-driven components with
these improved accessories results in a reduction in fuel consumption,
as the improved accessories can conserve energy by being turned on/off
``on demand'' in some cases, driven at partial load as needed, or by
operating more efficiently.
For example, electric coolant pumps and electric powertrain cooling
fans provide better control of engine cooling. Flow from an electric
coolant pump can be varied, and the cooling fan can be shut off during
engine warm-up or cold ambient temperature conditions, reducing warm-up
time, fuel enrichment requirements, and, ultimately reducing parasitic
losses.
IACC technology is difficult to observe and therefore there is
uncertainty in assigning it to the analysis fleet. As in the past, DOT
relies on industry-provided information and comments to assess the
level of IACC technology applied in the fleet. DOT believes there
continues to be opportunity for further implementation of IACC. The MY
2020 analysis fleet has an IACC fleet penetration of approximately
eight percent compared to the six percent value in the MY 2017 analysis
fleet used for the 2020 final rule analysis.
The agency believes improved accessories may be incorporated in
coordination with powertrain related changes occurring at either a
vehicle refresh or vehicle redesign. This coordination with powertrain
changes enables related design and tooling changes to be implemented
and systems development, functionality and durability testing to be
conducted in a single product change program to efficiently manage
resources and costs.
This analysis carries forward work on the effectiveness of IACC
systems conducted in the Draft TAR and EPA Proposed Determination that
is originally founded in the 2002 NAS Report \269\ and confidential
manufacturer data. This work involved gathering information by
monitoring
[[Page 49705]]
press reports, holding meetings with suppliers and OEMs, and attending
industry technical conferences. The resulting effectiveness estimates
we use are shown below. As indicated in the following table, the
effectiveness of IACC is simulated with differing values based on the
vehicle technology class it is being applied to. This variance, like
EPS, is a direct result of vehicle size and the amount of energy
required perform the work necessary for the vehicle to operate as
expected. This variance is related to the amount energy generated by
the alternator, the size of the coolant pump to the cool the necessary
systems, the size of the cooling fan required, among other
characteristics and it directed related to a vehicle size and mass.
---------------------------------------------------------------------------
\269\ National Research Council 2002. Effectiveness and Impact
of Corporate Average Fuel Economy (CAFE) Standards. Washington, DC:
The National Academies Press. https://doi.org/10.17226/10172.
[GRAPHIC] [TIFF OMITTED] TP03SE21.082
(c) Low Drag Brakes
Since 2009, for the MY 2011 CAFE final rule, DOT has defined low
drag brakes (LDB) as brakes that reduce the sliding friction of disc
brake pads on rotors when the brakes are not engaged because the brake
pads are pulled away from the rotating disc either by mechanical or
electric methods.\270\ DOT estimated the effectiveness of LDB
technology to be a range from 0.5-1.0 percent, based on CBI data. DOT
applied a learning curve to the estimated cost for LDB, but noted that
the technology was considered high volume, mature, and stable. DOT
explained that confidential manufacturer comments in response to the
NPRM for MY 2011 (73 FR 24352, May 2, 2008) indicated that most
passenger cars have already adopted LDB technology, but ladder frame
trucks have not.
---------------------------------------------------------------------------
\270\ Final Regulatory Impact Analysis, Corporate Average Fuel
Economy for MY 2011 Passenger Cars and Light Trucks (March 2009), at
V-135.
---------------------------------------------------------------------------
DOT and EPA continued to use the same definition for LDB in the MY
2012-2016 rule (75 FR 25324, May 7, 2010), with an estimated
effectiveness of up to 1 percent based on CBI data.\271\ DOT only
allowed LDB technology to be applied to large car, minivan, medium and
large truck, and SUV classes because the agency determined the
technology was already largely utilized in most other subclasses. The
2011 NAS committee also utilized NHTSA and EPA's definition for LDB and
added that most new vehicles have low-drag brakes.\272\ The committee
confirmed that the impact over conventional brakes may be about a 1
percent reduction of fuel consumption.
---------------------------------------------------------------------------
\271\ Final Regulatory Impact Analysis, Corporate Average Fuel
Economy for MY 2012-MY 2016 Passenger Cars and Light Trucks (March
2010), at 249.
\272\ 2011 NAS report, at 104.
---------------------------------------------------------------------------
For the MY 2017-2025 rule, however, DOT and EPA updated the
effectiveness estimate for LDB to 0.8 percent based on a 2011 Ricardo
study and updated lumped-parameter model.\273\ The agencies considered
LDB technology to be off the learning curve (i.e., the DMC does not
change year-over-year). The 2015 NAS report continued to use the
agencies' definition for LDB and commented that the 0.8 percent
effectiveness estimate is a reasonable estimate.\274\ The 2015 NAS
committee did not opine on the application of LDB technology in the
fleet. The agencies used the same definition, cost, and effectiveness
estimates for LDB in the Draft TAR, but also noted the existence of
zero drag brake systems which use electrical actuators that allow brake
pads to move farther away from the rotor.\275\ However, the agencies
did not include zero drag brake technology in either compliance
simulation. EPA continued with this approach in its first 2017 Final
Determination that the standards through 2025 were appropriate.\276\
---------------------------------------------------------------------------
\273\ Joint Technical Support Document: Final Rulemaking for
2017-2025 Light-Duty Vehicle Greenhouse Gas Emission Standards and
Corporate Average Fuel Economy Standards (August 2012), at 3-211.
\274\ 2015 NAS report, at 231.
\275\ Draft TAR, at 5-207.
\276\ EPA Proposed Determination TSD, at 2-422.
---------------------------------------------------------------------------
In the 2020 final rule, the agencies applied LDB sparingly in the
MY 2017 analysis fleet using the same cost and effectiveness estimates
from the 2011 Ricardo study, with approximately less than 15% of
vehicles being assigned the technology. In addition, DOT noted the
existence of zero drag brakes in production for some BEVs, similar to
the summary in the Draft TAR, but did not opine on the existence of
zero drag brakes in the fleet. Some stakeholders commented to the 2020
final rule that other vehicle technologies, including LDB, were
actually overapplied in the analysis fleet.
For this action, DOT considered the conflicting statements that LDB
were both universally applied in new vehicles and that the new vehicle
fleet still had space to improve LDB technology. DOT determined that
LDB technology as previously defined going back to the MY 2011 rule (74
FR 14196, March 30, 2009) was universally
[[Page 49706]]
applied in the MY 2020 fleet. However, DOT determined that zero drag
brakes, the next level of brake technology, was sparingly applied in
the MY 2020 analysis fleet. Currently, DOT does not believe that zero
drag brake systems will be available for wide scale application in the
rulemaking timeframe and did not include it as a technology for this
analysis. DOT will consider how to define a new level of low drag brake
technology that either encompasses the definition of zero drag brakes
or similar technology in future rulemakings. We invite comment on the
issue, and any available data regarding use of such systems on current
and forthcoming production vehicles, any available data regarding
system costs and efficacy in reducing drag (i.e., force at different
speeds) and vehicle fuel economy levels (i.e., through coastdown
testing).
(d) Secondary Axle Disconnect
All-wheel drive (AWD) and four-wheel drive (4WD) vehicles provide
improved traction by delivering torque to the front and rear axles,
rather than just one axle. When a second axle is rotating, it tends to
consume more energy because of additional losses related to lubricant
churning, seal friction, bearing friction, and gear train
inefficiencies.\277\ Some of these losses may be reduced by providing a
secondary axle disconnect function that disconnects one of the axles
when driving conditions do not call for torque to be delivered to both.
---------------------------------------------------------------------------
\277\ Pilot Systems, ``AWD Component Analysis'', Project Report,
performed for Transport Canada, Contract T8080-
150132, May 31, 2016.
---------------------------------------------------------------------------
The terms AWD and 4WD are often used interchangeably, although they
have also developed a colloquial distinction, and are two separate
systems. The term AWD has come to be associated with light-duty
passenger vehicles providing variable operation of one or both axles on
ordinary roads. The term 4WD is often associated with larger truck-
based vehicle platforms providing a locked driveline configuration and/
or a low range gearing meant primarily for off-road use.
Many 4WD vehicles provide for a single-axle (or two-wheel) drive
mode that may be manually selected by the user. In this mode, a primary
axle (usually the rear axle) will be powered, while the other axle
(known as the secondary axle) is not. However, even though the
secondary axle and associated driveline components are not receiving
engine power, they are still connected to the non-driven wheels and
will rotate when the vehicle is in motion. This unnecessary rotation
consumes energy,\278\ and leads to increased fuel consumption that
could be avoided if the secondary axle components were completely
disconnected and not rotating.
---------------------------------------------------------------------------
\278\ Any time a drivetrain component spins it consumes some
energy, primarily to overcome frictional forces.
---------------------------------------------------------------------------
Light-duty AWD systems are often designed to divide variably torque
between the front and rear axles in normal driving to optimize traction
and handling in response to driving conditions. However, even when the
secondary axle is not necessary for enhanced traction or handling, in
traditional AWD systems it typically remains engaged with the driveline
and continues to generate losses that could be avoided if the axle was
instead disconnected. The SAX technology observed in the marketplace
disengages one axle (typically the rear axle) for two-wheel drive (2WD)
operation but detects changes in driving conditions and automatically
engages AWD mode when it is necessary. The operation in 2WD can result
in reduced fuel consumption. For example, Chrysler has estimated the
secondary axle disconnect feature in the Jeep Cherokee reduces friction
and drag attributable to the secondary axle by 80% when in disconnect
mode.\279\
---------------------------------------------------------------------------
\279\ Brooke, L. ``Systems Engineering a new 4x4 benchmark'',
SAE Automotive Engineering, June 2, 2014.
---------------------------------------------------------------------------
Observing SAX technology on actual vehicles is very difficult.
Manufacturers do not typically identify the technology on technical
specifications or other widely available information. The agency
employed an approach consistent with previous rulemaking in assigning
this technology. Specifically, the agency assigned SAX technology based
on a combination of publicly available information and previously
submitted confidential information. In the analysis fleet, 38% of the
vehicles that had AWD or 4WD are determined to have SAX technology. All
vehicles in the analysis fleet with front-wheel drive (FWD) or rear-
wheel drive (RWD) have SAX skipped since SAX technology is a way to
emulate FWD or RWD in AWD and 4WD vehicles, respectively. The agency
does not allow for the application of SAX technology to FWD or RWD
vehicles because they do not have a secondary driven axle to
disconnect.
SAX technology can be adopted by any vehicle in the analysis fleet,
including those with a HEV or BEV powertrain,\280\ which was identified
as having AWD or 4WD. It does not supersede any technology or result in
any other technology being excluded for future implementation for that
vehicle. SAX technology can be applied during any refresh or redesign.
DOT seeks comment on whether it is appropriate for SAX technology to be
allowed to be applied to BEVs, or if the technology only provides
benefits to ICE vehicles.
---------------------------------------------------------------------------
\280\ The inefficiencies addressed on ICEs by SAX technology may
not be similar enough, or even present, in HEVs or BEVs.
---------------------------------------------------------------------------
This analysis carries forward work on the effectiveness of SAX
systems conducted in the Draft TAR and EPA Proposed Determination.\281\
This work involved gathering information by monitoring press reports,
holding meetings with suppliers and OEMs, and attending industry
technical conferences. DOT does not simulate SAX effectiveness in the
Autonomie modeling because, similar to LDB, IACC, and EFR, the fuel
economy benefits from the technology are not fully captured on the two-
cycle test. The secondary axle disconnect effectiveness values, for the
most part, have been accepted as plausible based on the rulemaking
record and absence of contrary comments. As such, the agency has
prioritized its extensive Autonomie vehicle simulation work toward
other technologies that are emerging or considered more critical for
total system effectiveness. The resulting effectiveness estimates we
use are shown below. The agency welcomes comment on these effectiveness
values and will consider any material data providing revised, or
confirmatory, values for those being used in the analysis.
---------------------------------------------------------------------------
\281\ Draft TAR, at 5-412; Proposed Determination TSD, at 2-422.
---------------------------------------------------------------------------
[[Page 49707]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.083
(e) Other Vehicle Technology Costs
The cost estimates for EPS, IACC, SAX, and LDB \282\ rely on
previous work published as part of past rulemakings with learning
applied to those cost values which is founded in the 2002 NAS
report.\283\ The cost values are the same values that were used for the
Draft TAR and 2020 final rule, updated to 2018 dollars. Table III-35
shows examples of costs for these technologies across select model
years. Note that these costs are the same for all vehicle technology
classes. For all absolute EPS, IACC, LDB, and SAX technology costs
across all model years, see the Technologies file.
---------------------------------------------------------------------------
\282\ Note that because LDB technology is applied universally as
a baseline technology in the MY 2020 fleet, there is functionally
zero costs for this technology associated with this proposed
rulemaking.
\283\ National Research Council 2002. Effectiveness and Impact
of Corporate Average Fuel Economy (CAFE) Standards. Washington, DC:
The National Academies Press. https://doi.org/10.17226/10172.
[GRAPHIC] [TIFF OMITTED] TP03SE21.084
8. Simulating Air Conditioning Efficiency and Off-Cycle Technologies
Off-cycle and air conditioning (A/C) efficiency technologies can
provide fuel economy benefits in real-world vehicle operation, but
those benefits cannot be fully captured by the traditional 2-cycle test
procedures used to measure fuel economy.\284\ Off-cycle technologies
include technologies like high efficiency alternators and high
efficiency exterior lighting.\285\ A/C efficiency technologies are
technologies that reduce the operation of or the loads on the
compressor, which pressurizes A/C refrigerant. The less the compressor
operates or the more efficiently it operates, the less load the
compressor places on the engine, resulting in better fuel efficiency.
---------------------------------------------------------------------------
\284\ 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.'').
\285\ 40 CFR 86.1869-12(b)--Credit available for certain off-
cycle technologies.
---------------------------------------------------------------------------
Vehicle manufacturers have the option to generate credits for off-
cycle technologies and improved A/C 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,\286\ but the 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 fuel economy reported to NHTSA.\287\
[[Page 49708]]
FCIVs are only calculated and applied at a fleet level for a
manufacturer and are based on the volume of the manufacturer's fleet
that contain qualifying technologies.\288\
---------------------------------------------------------------------------
\286\ Unlike, for example, the statutory overcompliance credits
prescribed in 49 U.S.C. 32903.
\287\ 49 U.S.C. 32904(c)-(e). EPCA granted EPA authority to
establish fuel economy testing and calculation procedures. See
Section VII for more information.
\288\ 40 CFR 600.510-12(c).
---------------------------------------------------------------------------
There are three pathways that can be used to determine the value of
A/C efficiency and off-cycle adjustments. First, manufacturers can use
a predetermined list or ``menu'' of g/mi values that EPA established
for specific off-cycle technologies.\289\ Second, manufacturers can use
5-cycle testing to demonstrate off-cycle CO2 benefit; \290\
the additional tests allow emissions benefits to be demonstrated over
some elements of real-world driving not captured by the 2-cycle
compliance tests, including high speeds, rapid accelerations, hot
temperatures, and cold temperatures. Third, manufacturers can seek EPA
approval, through a notice and comment process, to use an alternative
methodology other than the menu or 5-cycle methodology for determining
the off-cycle technology improvement values.\291\ For further
discussion of the A/C and off-cycle compliance and application process,
see Section VII.
---------------------------------------------------------------------------
\289\ See 40 CFR 86.1869-12(b). The TSD for the 2012 final rule
for MYs 2017 and beyond provides technology examples and guidance
with respect to the potential pathways to achieve the desired
physical impact of a specific off-cycle technology from the menu and
provides the foundation for the analysis justifying the credits
provided by the menu. The expectation is that manufacturers will use
the information in the TSD to design and implement off-cycle
technologies that meet or exceed those expectations in order to
achieve the real-world benefits of off-cycle technologies from the
menu.
\290\ See 40 CFR 86.1869-12(c). EPA proposed a correction for
the 5-cycle pathway in a separate technical amendments rulemaking.
See 83 FR 49344 (Oct. 1, 2019). EPA is not approving credits based
on the 5-cycle pathway pending the finalization of the technical
amendments rule.
\291\ See 40 CFR 86.1869-12(d).
---------------------------------------------------------------------------
DOT and EPA have been collecting data on the application of these
technologies since implementing the A/C and off-cycle
programs.292 293 Most manufacturers are applying A/C
efficiency and off-cycle technologies; in MY 2019, 17 manufacturers
employed A/C efficiency technologies and 20 manufacturers employed off-
cycle technologies, though the level of deployment varies by
manufacturer.\294\
---------------------------------------------------------------------------
\292\ See 77 FR at 62832, 62839 (Oct. 15, 2012). EPA introduced
A/C and off-cycle technology credits for the CO2 program
in the MY 2012-2016 rule and revised the program in the MY 2017-2025
rule and NHTSA adopted equivalent provisions for MYs 2017 and later
in the MY 2017-2025 rule.
\293\ Vehicle and Engine Certification. Compliance Information
for Light-Duty Gas (GHG) Standards. Compliance Information for
Light-Duty Greenhouse Gas (GHG) Standards [verbar] Certification and
Compliance for Vehicles and Engines [verbar] U.S. EPA. Last Accessed
May 24, 2021.
\294\ See 2020 EPA Automotive Trends Report, at 91.
---------------------------------------------------------------------------
Manufacturers have only recently begun including detailed
information on off-cycle and A/C efficiency technologies equipped on
vehicles in compliance reporting data. For this analysis, though, such
information was not sufficiently complete to support a detailed
representation of the application of off-cycle technology to specific
vehicle model/configurations in the MY 2020 fleet. To account for the
A/C and off-cycle technologies equipped on vehicles and the potential
that manufacturers will apply additional A/C and off-cycle technologies
in the rulemaking timeframe, DOT specified model inputs for A/C
efficiency and off-cycle fuel consumption improvement values in grams/
mile for each manufacturer's fleet in each model year. DOT estimated
future values based on an expectation that manufacturers already
relying heavily on these adjustments would continue do so, and that
other manufacturers would, over time, also approach the limits on
adjustments allowed for such improvements.
The next sections discuss how the CAFE Model simulates the
effectiveness and cost for A/C efficiency and off-cycle technology
adjustments.
(a) A/C and Off-Cycle Effectiveness Modeling in the CAFE Model
In this analysis, the CAFE Model applies A/C and off-cycle
flexibilities to manufacturer's CAFE regulatory fleet performance in a
similar way to the regulation.\295\ In the analysis and after the first
MY, A/C efficiency and off-cycle FCIVs apply to each manufacturer's
regulatory fleet after the CAFE Model applies conventional technologies
for a given standard. That is, conventional technologies are applied to
each manufacturers' vehicles in each MY to assess the 2-cycle sales
weighted harmonic average CAFE rating. Then, the CAFE Model assesses
the CAFE rating to use for a manufacturer's compliance value after
applying the A/C efficiency and off-cycle FCIVs designated in the
Market Data file. This assessment of adoption of conventional
technology and the A/C efficiency and off-cycle technology occurs on a
year-by-year basis in the CAFE Model. The CAFE Model attempts to apply
technologies and flexibilities in a way that both minimizes cost and
allows the manufacturer to meet their standards without over or under
complying.
---------------------------------------------------------------------------
\295\ 49 CFR 531.6 and 49 CFR 533.6 Measurement and Calculation
procedures.
---------------------------------------------------------------------------
To determine how manufacturers might adopt A/C efficiency and off-
cycle technologies in the rulemaking timeframe, DOT began with data
from EPA's 2020 Trends Report and CBI compliance material from
manufacturers.296 297 DOT used manufacturer's MY 2020 A/C
efficiency and off-cycle FCIVs as a starting point, and then
extrapolated values in each MY until MY 2026, for light trucks to the
proposed regulatory cap, for each manufacturer's fleets by regulatory
class.
---------------------------------------------------------------------------
\296\ Vehicle and Engine Certification. Compliance Information
for Light-Duty Gas (GHG) Standards. Compliance Information for
Light-Duty Greenhouse Gas (GHG) Standards [verbar] Certification and
Compliance for Vehicles and Engines [verbar] U.S. EPA. Last Accessed
May 24, 2021.
\297\ 49 U.S.C. 32907.
---------------------------------------------------------------------------
To determine the rate at which to extrapolate the addition of A/C
and off-cycle technology adoption for each manufacturer, DOT reviewed
historical A/C and off-cycle technology applications, each
manufacturer's fleet composition (i.e., breakdown between passenger
cars (PCs) and light trucks (LTs)), availability of A/C and off-cycle
technologies that manufacturers could still use, and CBI compliance
data. Different manufacturers showed different levels of historical A/C
efficiency and off-cycle technology adoption; therefore, different
manufacturers hit the proposed regulatory caps for A/C efficiency
technology for both their PC and LT fleets, and different manufacturers
hit caps for off-cycle technologies in the LT regulatory class. DOT
declined to extrapolate off-cycle technology adoption for PCs to the
proposed regulatory cap for a few reasons. First, past EPA Trends
Reports showed that many manufacturers did not adopt off-cycle
technology to their passenger car fleets. Next, manufacturers limited
PC offerings in MY 2020 as compared to historical trends. Last, CBI
compliance data available to DOT indicated a lower adoption of menu
item off-cycle technologies to PCs compared to LTs. DOT accordingly
limited the application of off-cycle FCIVs to 10 g/mi for PCs but
allowed LTs to apply 15 g/mi of off-cycle FCIVs. The inputs for A/C
efficiency technologies were set to 5 g/mi and 7.2 g/mi for PCs and
LTs, respectively. DOT allowed A/C efficiency technologies to reach the
regulatory caps by MY 2024, which is the first year of standards
assessed in this analysis.
DOT decided to apply the FCIVs in this way because the A/C and off-
cycle
[[Page 49709]]
technologies are generally more cost-effective than other technologies.
The details of this assessment (and the calculation) are further
discussed in the CAFE Model Documentation.\298\ The A/C efficiency and
off-cycle adjustment schedules used in this analysis are shown in TSD
Chapter 3.8 and in the Market Data file's Credits and Adjustments
worksheet.
---------------------------------------------------------------------------
\298\ CAFE Model Documentation, S5.
---------------------------------------------------------------------------
(b) A/C and Off-Cycle Costs
For this analysis, A/C and off-cycle technologies are applied
independently of the decision trees using the extrapolated values shown
above, so it is necessary to account for the costs of those
technologies independently. Table III-36 shows the costs used for A/C
and off-cycle FCIVs in this analysis. The costs are shown in dollars
per gram of CO2 per mile ($ per g/mile). The A/C efficiency
and off-cycle technology costs are the same costs used in the EPA
Proposed Determination and described in the EPA Proposed Determination
TSD.\299\
---------------------------------------------------------------------------
\299\ EPA PD TSD. EPA-420-R-16-021. November 2016. At 2-423-2-
245. https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100Q3L4.pdf. Last
accessed May 24, 2021.
---------------------------------------------------------------------------
To develop the off-cycle technology costs, DOT selected the 2nd
generic 3 gram/mile package estimated to cost $170 (in 2015$) to apply
in this analysis in $ per gram/mile. DOT updated the costs used in the
Proposed Determination TSD from 2015$ to 2018$, adjusted the costs for
RPE, and applied a relatively flat learning rate. We seek comment on
whether these costs are still appropriate, or whether a different $ per
gram/mile cost should be used. If commenters believe a different $ per
gram/mile cost should be used, we request commenters provide any data
or information on which any alternative costs are based. This should
include a description of how the alternative costs are representative
of costs across the industry, and whether the $ per gram/mile estimate
is based on a package of specific off-cycle technologies.
Similar to off-cycle technology costs, DOT used the cost estimates
from EPA Proposed Determination TSD for A/C efficiency technologies
that relied on the 2012 rulemaking TSD.\300\ DOT updated these costs to
2018$ and adjusted for RPE for this analysis, and applied the same
mature learning rate that DOT applied for off-cycle technologies.
---------------------------------------------------------------------------
\300\ Joint NHTSA and EPA 2012 TSD, see Section 5.1.
[GRAPHIC] [TIFF OMITTED] TP03SE21.085
E. Consumer Responses to Manufacturer Compliance Strategies
The previous subsections in Section III 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 CAFE 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 CAFE standards are
private benefits that accrue to the buyers of new cars and trucks,
produced in the model years 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
external benefits are also derived from how consumers use--or do not
use--vehicles. The next few subsections walk through how the analysis
models consumer responses to changing vehicles and prices. NHTSA
requests comment on the following discussion.
1. Macroeconomic and Consumer Behavior Assumptions
This proposal includes a comprehensive economic analysis of the
impacts of altering the CAFE 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 demand, and yet they determine how much fuel efficiency
technology manufacturers will apply to U.S.-bound 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
CAFE standards. Constructing these forecasts requires robust
projections of macroeconomic variables that span the timeframe of the
analysis, including real U.S. Gross Domestic Product (GDP), consumer
confidence, U.S. population, and real disposable personal income.
In order to ensure internal consistency within the analysis,
relevant economic assumptions are derived from the same source. The
analysis presented in this analysis employs forecasts developed by DOT
using the U.S. Energy Information Administration's (EIA's) National
Energy Model System (NEMS). EIA is an agency within the U.S. Department
of Energy (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 Annual Energy Outlook (AEO), which presents forecasts of
future fuel prices, among many other energy-related variables. The
analysis employs forecasts of fuel prices, real U.S. GDP, real
disposable personal income, U.S. population, and fuel prices from the
AEO 2021 Reference Case. The agency also uses a forecast of consumer
confidence to project sales from the IHS Markit Global Insight long-
term macroeconomic model. The IHS Markit Global Insight model is also
used by EIA for the AOE.
While these macroeconomic assumptions are some of the most critical
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 sensitivity analyses. The purpose of the sensitivity
analyses, discussed in greater
[[Page 49710]]
detail in PRIA Chapter 6 and PRIA Chapter 7, 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 2020, 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 relatively rapid climb
back to pre-pandemic growth rates (in all the regulatory alternatives).
See TSD Chapter 4.1 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
efficiency offers vehicle owners significant savings; in fact, the
analysis shows that fuel savings exceed the technology cost to comply
with even the most stringent standards analyzed by this proposal at a
3% discount rate. It would be reasonable to assume that consumers value
the full value of fuel savings as they would be better off not having
to spend more of their disposable income on fuel. If consumers did
value the full amount of fuel savings, fuel-efficient vehicles would
functionally be cheaper for consumers to own when considering both
purchasing and operational costs, and thus making the vehicles offered
under the stricter alternatives more attractive than similar models
offered in the baseline. Recent econometric research remains divided
between studies that conclude has shown that consumers may value most,
if not all of potential fuel savings, and those that conclude that
consumers significantly undervalue expected fuel savings (NASEM, 2021,
p. 11-351).301 302 303
---------------------------------------------------------------------------
\301\ There is a great deal of work attempting to test the
question whether consumers are adequately informed about, and
sufficiently attentive to, potential fuel savings at the time of
purchase. The existing research is not conclusive and leaves many
open questions. On the one hand, there is significant support for
the proposition that consumers are responsive to changes in fuel
costs. See, e.g., Busse et al.; Sallee, et al. On the other hand,
there is also support for the proposition that many consumers do
not, in fact, give full or sufficient attention to potential savings
from fuel-efficient vehicles, and thus make suboptimal decisions.
See Duncan et al.; Gillingham et al.
\302\ Allcott, H. and C. Knittel, 2019. ``Are Consumers Poorly
Informed about Fuel Economy? Evidence from Two Experiments'', AEJ:
Economic Policy, 11(1): 1-37.
\303\ D. Duncan, A. Ku, A. Julian, S. Carley, S. Siddiki, N.
Zirogiannis and J. Graham, 2019. ``Most Consumers Don't Buy Hybrids:
Is Rational Choice a Sufficient Explanation?'', J. of Benefit-Cost
Analysis, 10(1): 1-38.
---------------------------------------------------------------------------
If buyers fully value the savings in fuel costs that result from
higher fuel economy, manufacturers would be expected to supply the
improvements that buyers demand, and vehicle demand would be expected
to fully consider both future fuel cost savings consumers would realize
from owning--and potentially re-selling--more fuel-efficient models and
increased cost of vehicles due to technological and design changes made
to increase fuel economy. If instead, consumers systematically
undervalue future fuel savings, the result would be an underinvestment
in fuel-saving technology. In that case, more stringent fuel economy
standards would also lead manufacturers to adopt improvements in fuel
economy that improve consumer welfare (e.g., Allcott et al., 2014;
Heutel, 2015).
There is substantial evidence that consumers do not fully value
lifetime fuel savings. Even though the average fuel economy of new
vehicles reached an all-time high in MY 2020 of 25.7 MPG,\304\ this is
still significantly below the fuel economy of the fleet's most
efficient vehicles that are readily available to consumers.\305\
Manufacturers have repeatedly informed the agency that consumers only
value between 2 to 3 years-worth of fuel savings when making purchasing
decisions. The potential for car buyers voluntarily to 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 predictions of
economic consumer model (e.g., Dellavigna, 2009).
---------------------------------------------------------------------------
\304\ See EPA 2020 Automotive Trends Report at 6, available at
https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P1010U68.pdf.
\305\ Id. At 9.
---------------------------------------------------------------------------
A behavioral explanation of such `undervaluation' of the savings
from purchasing higher-mpg models is myopia or present bias; consumers
may give undue focus to short-term costs and insufficient attention to
long-term benefits.\306\ This situation could arise because they are
unsure of the fuel savings that will be achieved in real-world driving,
what future fuel prices will be, how long they will own a new vehicle,
whether they will drive it enough to realize the promised savings. As a
consequence, they may view choosing to purchase or not purchase a fuel-
efficient technology as a risky bet; behavioral economics has
demonstrated that faced with the decision to accept or reject a risky
choice, some consumers weigh potential losses approximately twice as
heavily as potential gains, significantly undervaluing the choice
relative to its expected value (e.g., Kahneman and Tversky, 1979;
Kahneman, 2011). In the context of a choice to pay more for a fuel-
saving technology, loss aversion has been shown to have the potential
to cause undervaluation of future fuel savings similar to that reported
by manufacturers (Greene, 2011; Greene et al., 2013).\307\ The
behavioral model holds that consumers' decisions are affected by the
context, or framing, of choices. As explained in NASEM (2021), Ch.
11.3.3, it is possible that consumers respond to changes in fuel
economy regulations differently than they respond to manufacturers
voluntarily offering the option to purchase fuel economy technology to
new car buyers. We explain this differential more thoroughly in TSD
Chapter 4.2.1.1, but here is the contextual explanation for the
differential valuation. If a consumer is thinking about buying a new
car and is looking at two models, one that includes voluntarily added
fuel economy technology and is more expensive and another that does
not, she may buy the cheaper, less fuel efficient version even if the
more expensive model will save
[[Page 49711]]
money in the long run. But if, instead, the consumer is faced with
whether to buy a new car at all as opposed to keeping an older one, if
all new cars contain technology to meet fuel economy standards, then
she may view the decision differently. Will, for example, an extra
$1,000 for a new car--a $1,000 that the consumer will more than recoup
in fuel savings--deter her from buying the new car, especially when
most consumers finance cars over a number of years rather than paying
the $1,000 cost up front (therefore any increase in monthly payment
would be partly or entirely offset with lower fuel costs)? In additon,
the fact that standards generally increase gradually over a period of
years allows time for consumers and other information sources to verify
that fuel savings are real and of substantial value.
---------------------------------------------------------------------------
\306\ Gillingham et al., 2021, which is an AEJ: Economic Policy
paper, just published on consumer myopia in vehicle purchases; a
standard reference on present bias generally is O'Donoghue and
Rabin, AER: Papers and Proceedings, 2015.
\307\ Application of investment under uncertainty will yield
similar results as costs may be more certain and up front while the
fuel savings or benefits of the investment may be perceived as more
uncertain and farther into future, thereby reducing investments in
fuel saving technologies.
---------------------------------------------------------------------------
Another alternative is that consumers view the increase in
immediate costs associated with fuel economy technology in the context
of tradeoffs they must make amongst their purchasing decisions.
American households must choose how to spend their income amongst many
competing goods and services, including how much to spend on a new
vehicle. They may also decide to opt for another form of
transportation. While a consumer may recognize and value the potential
long-term value of fuel savings, they may also prefer to spend their
money on other items, either in the form of other vehicle attributes--
such as picking a truck with a larger flatbed or upgrading to a more
luxurious trim package--or other unrelated goods and services. The same
technologies that can be used to increase fuel economy can also be used
to enable increased vehicle power or weight while maintaining fuel
economy. While increased fuel efficiency will free up disposable income
throughout the lifetime of the vehicle (and may even exceed the
additional upfront costs to purchase a more expensive fuel-efficient
vehicle), the value of owning a different good sooner may provide
consumers even more benefit.
As explained more thoroughly in TSD Chapter 4.2.1.1, the analysis
assumes that potential car and light truck buyers value only the
undiscounted savings in fuel costs from purchasing a higher-mpg model
they expect to realize over the first 30 months they own it. Depending
on the discount rate 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 car and light truck prices that the agency estimates will be
required for manufacturers to recover their increased costs for making
required improvements to fuel economy. The agency 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. If NHTSA is incorrect about the undervaluation
of fuel economy in the context of regulatory standards and its effect
on car sales, correcting the assumption should result in improved
safety outcomes and additional declines in conventional air pollutants.
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, provide any data or information on which
the amount of time is based, and provide any discussion of how changing
this assumption would interact with other elements in the analysis.
2. Fleet Composition
The composition of the on-road fleet--and how it changes in
response to CAFE standards--determines many of the costs and benefits
of the proposal. For example, how much fuel the light-duty consumes is
dependent on the number of new vehicles sold, older (and less
efficient) vehicles retired, and how much those vehicles are driven.
Prior to the 2020 CAFE standards, 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 model
year under both the least stringent alternative (typically the
baseline) and the most stringent alternative considered (intended to
represent ``maximum technology'' scenarios in some cases). To the
extent that an alternative matched the assumptions made in the
production of the proprietary forecast, using a static fleet based upon
those assumptions may have been warranted.
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. A number of 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
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 now 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--changes in response to regulatory alternatives,
and the influence of economic and regulatory factors on vehicle
retirement (otherwise known as scrappage). Below are brief descriptions
that of how the agency models sales and scrappage. For a full
explanation, refer to TSD Chapter 4.2. Particularly given the broad
uncertainty discussed in TSD Chapter 4.2, 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 baseline in each year, and a fleet share model that
produces differences in the passenger car and light truck market share
in each alternative. The nominal forecast does not include price and is
merely a (continuous) function of several macroeconomic variables that
are provided to the model as inputs. The price elasticity is also
specified as an
[[Page 49712]]
input, but this analysis assumes a unit elastic response of -1.0--
meaning that a one percent increase in the average price of a new
vehicle produces a one percent decrease in total sales. NHTSA seeks
comment on this assumption. The price change on which the elasticity
acts is calculated net of some portion of the future fuel savings that
accrue to new vehicle buyers (2.5 years' worth, in this analysis, as
discussed in the previous section).
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 inputs) that
determines the size of the new vehicle market in each calendar year 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. Past reviewers expressed concerns about the possibility
of econometrically estimating an industry average price elasticity in a
way that isolates the causal effect of new vehicle prices on new
vehicle sales (and properly addresses the issue of endogeneity between
sales and price). 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. The economic response to the
pandemic has created uncertainty, particularly in the near-term, around
pace at which the market for automobiles will recover--and the scale
and timing of the recovery's peak--before returning to its long-term
trend. DOT will continue to monitor macroeconomic data and new vehicle
sales and update its baseline forecast as appropriate.
The second component of the sales response model captures how price
changes affect the number of vehicles sold. The price elasticity is
applied 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 2019 (the last historical year
before the simulation begins) plus the average regulatory cost
associated with the baseline alternative.\308\ The central analysis in
this proposal simulates multiple programs simultaneously (CAFE final
standards, EPA final greenhouse gas 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 model year. 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
unit elasticity is applied in this analysis represents the residual
price change between scenarios after accounting for 2.5 years' worth of
fuel savings to the new vehicle buyer.
---------------------------------------------------------------------------
\308\ 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.
---------------------------------------------------------------------------
The third and final component of the sales model 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, which
was internally consistent. The reality, however, has been quite
different. The CAFE Model includes the DFS model in an attempt to
address these market realities.
The DFS distributes the total industry sales 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 obviously cars--
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. The DFS uses two functions
from the National Energy Modeling System (NEMS) used in 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.
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 2020 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
2020 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.
The DFS model show passenger car styles gaining share with higher
fuel prices and losing them when prices are decline. Similarly, as fuel
economy increases in light truck models, which offer consumers other
desirable attributes beyond fuel economy (ride height or interior
volume, for example) their relative share increases. However, this
approach does not suggest that consumers dislike fuel economy in
passenger cars, but merely recognizes
[[Page 49713]]
the fact that fuel economy has diminishing returns in terms of fuel
savings. As the fuel economy of light trucks increases, the tradeoff
between passenger car and light truck purchases increasingly involves a
consideration of other attributes. The coefficients also show a
relatively stronger preference for power improvements in cars than
light trucks because that is an attribute where trucks have typically
outperformed cars, just as cars have outperformed trucks for fuel
economy.
For years, some commenters encouraged the agency to consider
vehicle attributes beyond price and fuel economy when estimating a
sales response to fuel economy standards, and suggested that a more
detailed representation of the new vehicle market would allow the
agency to simulate strategic mix shifting responses from manufacturers
and diverse attribute preferences among consumers. Doing so would have
required a discrete choice model (at some level). Discrete models are
highly sensitive on their inputs and typically fit well on a single
year of data (a cross-section of vehicles and buyers). This approach
misses relevant trends that build over time, such as rising GDP or
shifting consumer sentiment toward emerging technologies and are better
used for analysis as opposed to prediction. While the agency believes
that these challenges provide a reasonable basis for not employing a
discrete choice model in the current CAFE Model, the agency also
believes these challenges are not insurmountable, and that some
suitable variant of such models may yet be developed for use in future
fuel economy rulemakings. The agency has not abandoned the idea and
plans to continue experimenting with econometric specifications that
address heterogeneous consumer preferences in the new vehicle market as
they further refine the analytical tools used for regulatory analysis.
The agency seeks suggestions on how to incorporate other vehicle
attributes into the current analysis, or, alternatively, methods to
implement a discrete choice model that can capture changing
technologies and consumer trends over an extended time-period.
(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.
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 is less than the value of the vehicle as scrap metal, plus the
cost to maintain or repair the vehicle. 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 first owner.
While scrappage decisions are made at the household level, the
agency is unaware of sufficient household data to sufficiently capture
scrappage at that level. Instead, the agency 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. It is more likely that manufacturers will defray a portion of
the increased regulatory cost across its vehicles or to other
manufacturers' buyers through the sale of credits.
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 model year vintage, which
the agency uses proprietary vehicle registration data from IHS/Polk to
collect vehicle age and durability. Other factors include fuel economy
and new vehicle prices. For historical data on new vehicle transaction
prices, the agency uses National Automobile Dealers Association (NADA)
Data.\309\ The data consists of the average transaction price of all
light-duty vehicles; 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.
---------------------------------------------------------------------------
\309\ 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 shows that the durability of successive
model years 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.\310\ The agency uses fixed effects to
capture potential changes in durability across model years and to
ensure that vehicles approaching the end of their life are scrapped in
the analysis, the agency applies a decay function to vehicles after
they reach age 30. The macroeconomic conditions variables discussed
above are included
[[Page 49714]]
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) are included which generates differing
scrappage rates across the alternatives.
---------------------------------------------------------------------------
\310\ 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.
---------------------------------------------------------------------------
In addition to the variables included in the scrappage model, the
agency 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.
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, otherwise known as
scrappage. 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.
It is the agency'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 CAFE 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); however, the difference could conceivably be
small. Based on the structure of the CAFE Model, the combined effect of
the sales and scrappage responses would 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 benefit analysis. 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 predict total
VMT within a scenario.
To ensure that travel demand remains consistent across the
different regulatory scenarios, the CAFE Model begins with a model of
aggregate VMT developed by the Federal Highway Administration (FHWA)
that is used to produce their official annual VMT forecasts. These
estimates provide the aggregate VMT of all model years and body styles
for any given calendar year and are same across regulatory alternatives
for each year in the analysis.
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 CAFE alternatives, it is necessary to partition miles by
age and body type. The agency 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. The agency 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 calendar
year to preserve the non-rebound VMT 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 CAFE standards than the baseline level will lead to
comparatively higher fuel economy for new cars and light trucks, thus
decreasing the amount of fuel consumed and increasing the amount of
travel in which new car and truck buyers engage. The agency 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 CAFE standards in this
proposal. We also note that the rebound effect diminishes the economic
and environmental benefits associated with increased fuel efficiency.
The agency 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 they 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. The central tendency of this range appears to be at or
slightly above its midpoint, which is 30 percent. Considering only
those studies that the agency 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 their estimates falling in the 15-30 percent
range.
A case can also be made to support values of the rebound effect
falling in the 5-15 percent range. There is empirical evidence
supported by theory, that the rebound effect has been declining over
time due to factors such as increasing income that affects the value of
time, increasing fuel economy that makes the fuel cost of driving a
smaller share of the total costs of vehicle travel, as well as
diminishing impacts of increased car ownership and rates of license
holding on vehicle travel. Lower rebound estimates are associated with
studies that include recently published analyses using U.S. data, and
to accord the most weight to research that relies on measures of
vehicle use derived from odometer readings, controls for the potential
endogeneity of fuel economy, and estimates the response of vehicle use
to variation in fuel economy itself, rather than to fuel cost per
distance driven or fuel prices. This approach suggests that the rebound
effect is likely in the range from 5-15 percent and is more likely to
lie toward the lower end of that range.
The agency selected a rebound magnitude of 15% for the analysis
because it was well-supported by the totality of the evidence and
aligned well with FHWA's estimated elasticity for
[[Page 49715]]
travel (14.6%). However, recognizing the uncertainty surrounding the
rebound value, we also examine the sensitivity of estimated impacts to
values of the rebound ranging from 10 percent to 20 percent. NHTSA
seeks comment on the above discussion, and whether to consider a
different value for the rebound effect for the final rule analysis.
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 light-duty VMT in a given
calendar year), and bottom-up (where the composition and utilization of
the on-road fleet determines a base level of VMT in a calendar year,
which is constrained to match the FHWA model). While the agency and the
model developers agree that 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 policy simulation, 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, the agency requests comment on alternative
approaches to simulate VMT demand.
See TSD Chapter 4.3 for a complete accounting of how the agency
models VMT.
4. Changes to Fuel Consumption
The agency uses the fuel economy and age and body-style VMT
estimates to determine changes in fuel consumption. The agency 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 Environmental Impacts of Regulatory Alternatives
This proposal includes the adoption of electric vehicles and other
fuel-saving technologies, which produce additional co-benefits. These
co-benefits include reduced vehicle tailpipe emissions during operation
as well as reduced upstream emissions during petroleum extraction,
transportation, refining, and finally fuel transportation, storage, and
distribution. This section provides an overview of how we developed
input parameters for criteria pollutants, greenhouse gases, and air
toxics. This section also describes how we generated estimates of how
these emissions could affect human health, in particular criteria
pollutants known to cause poor air quality and damage human health when
inhaled.
The rule implements an emissions inventory methodology for
estimating impacts. Vehicle emissions inventories are often described
as three-legged stools, comprised of activity (i.e., miles traveled,
hours operated, or gallons of fuel burned), population (or number of
vehicles), and emission factors. An emissions factor is a
representative rate that attempts to relate the quantity of a pollutant
released to the atmosphere per unit of activity.\311\
---------------------------------------------------------------------------
\311\ USEPA, Basics Information of Air Emissions Factors and
Quantification, https://www.epa.gov/air-emissions-factors-and-quantification/basic-information-air-emissions-factors-and-quantification.
---------------------------------------------------------------------------
In this rulemaking, upstream emission factors are on a fuel volume
basis and tailpipe emission factors are on a distance basis. Simply
stated, the rule's upstream emission inventory is the product of the
per-gallon emission factor and the corresponding number of gallons of
gasoline or diesel consumed. Similarly, the tailpipe emission inventory
is the product of the per-mile emission factor and the appropriate
miles traveled estimate. The only exceptions are that tailpipe sulfur
oxides (SOX) and carbon dioxide (CO2) also use a
per-gallon emission factor in the CAFE Model. The activity levels--both
miles traveled and fuel consumption--are generated by the CAFE Model,
while the emission factors have been incorporated from other Federal
models.
For this rule, vehicle tailpipe (downstream) and upstream emission
factors and subsequent inventories were developed independently from
separate data sources. Upstream emission factors are estimated from a
lifecycle emissions model developed by the U.S. Department of Energy's
(DOE) Argonne National Laboratory, the Greenhouse gases, Regulated
Emissions, and Energy use in Transportation (GREET) Model.\312\
Tailpipe emission factors are estimated from the regulatory highway
emissions inventory model developed by the U.S. Environmental
Protection Agency's (EPA) National Vehicle and Fuel Emissions
Laboratory, the Motor Vehicle Emission Simulator (MOVES3). Data from
GREET and MOVES3 have been utilized to update the CAFE Model for this
rulemaking.
---------------------------------------------------------------------------
\312\ U.S. Department of Energy, Argonne National Laboratory,
Greenhouse gases, Regulated Emissions, and Energy use in
Transportation (GREET) Model, Last Update: 9 Oct. 2020, https://greet.es.anl.gov/.
---------------------------------------------------------------------------
The changes in adverse health outcomes due to criteria pollutants
emitted, such as differences in asthmatic episodes and hospitalizations
due to respiratory or cardiovascular distress, are generally reported
in incidence per ton values. Incidence values were developed using
several EPA studies and recently updated from the 2020 final rule to
better account for the emissions source sectors used in the CAFE Model
analysis.
Chapter 5 of the TSD accompanying this proposal includes the
detailed discussion of the procedures we used to simulate the
environmental impact of regulatory alternatives, and the implementation
of these procedures into the CAFE Model is discussed in detail in the
CAFE Model Documentation. Further discussion of how the health impacts
of upstream and tailpipe criteria pollutant emissions have been
monetized in the analysis can be found in Section III.G.2.b)(2). The
Supplemental Environmental Impact Statement accompanying this analysis
also includes a detailed discussion of both criteria pollutant and GHG
emissions and their impacts. NHTSA
[[Page 49716]]
seeks comment on the following discussion.
1. Activity Levels Used To Calculate Emissions Impacts
Emission inventories in this rule vary by several key activity
parameters, especially relating to the vehicle's model year and
relative age. Most importantly, the CAFE Model accounts for vehicle
sales, turnover, and scrappage as well as travel demands over its
lifetime. Like other models, the CAFE Model includes procedures to
estimate annual rates at which new vehicles are purchased, driven, and
subsequently scrapped. Together, these procedures result in, for each
vehicle model in each model year, estimates of the number remaining in
service in each calendar year, as well as the annual mileage
accumulation (i.e., VMT) at each age. Inventories by model year are
derived from the annual mileage accumulation rates and corresponding
emission factors.
As discussed in Section III.C.2, for each vehicle model/
configuration in each model year from 2020 to 2050 for upstream
estimates and 2060 for tailpipe estimates, the CAFE Model estimates and
records the fuel type (e.g., gasoline, diesel, electricity), fuel
economy, and number of units sold in the U.S. The model also makes use
of an aggregated representation of vehicles sold in the U.S. during
1975-2019. The model estimates the numbers of each cohort of vehicles
remaining in service in each calendar year, and the amount of driving
accumulated by each such cohort in each calendar year.
The CAFE Model estimates annual vehicle-miles of travel (VMT) for
each individual car and light truck model produced in each model year
at each age of their lifetimes, which extend for a maximum of 40 years.
Since a vehicle's age is equal to the current calendar year minus the
model year in which it was originally produced, the age span of each
vehicle model's lifetime corresponds to a sequence of 40 calendar years
beginning in the calendar year corresponding to the model year it was
produced.\313\ These estimates reflect the gradual decline in the
fraction of each car and light truck model's original model year
production volume that is expected to remain in service during each
year of its lifetime, as well as the well-documented decline in their
typical use as they age. Using this relationship, the CAFE Model
calculates fleet-wide VMT for cars and light trucks in service during
each calendar year spanned in this analysis.
---------------------------------------------------------------------------
\313\ In practice, many vehicle models bearing a given model
year designation become available for sale in the preceding calendar
year, and their sales can extend through the following calendar year
as well. However, the CAFE Model does not attempt to distinguish
between model years and calendar years; vehicles bearing a model
year designation are assumed to be produced and sold in that same
calendar year.
---------------------------------------------------------------------------
Based on these estimates, the model also calculates quantities of
each type of fuel or energy, including gasoline, diesel, and
electricity, consumed in each calendar year. By combining these with
estimates of each model's fuel or energy efficiency, the model also
estimates the quantity and energy content of each type of fuel consumed
by cars and light trucks at each age, or viewed another way, during
each calendar year of their lifetimes. As with the accounting of VMT,
these estimates of annual fuel or energy consumption for each vehicle
model and model year combination are combined to calculate the total
volume of each type of fuel or energy consumed during each calendar
year, as well as its aggregate energy content.
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 calendar year, together with the
sources of its estimates of their survival rates and average use at
each age, are described in detail in Section III.E.2. The data and
procedures it 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 calendar years, are also described in detail in that same
section.
The model documentation accompanying this NPRM describes these
procedures in detail.\314\ The quantities of travel and fuel
consumption estimated for the cross section of model years and calendar
years constitutes a set of ``activity levels'' based on which the model
calculates emissions. The model does so by multiplying activity levels
by emission factors. As indicated in the previous section, the
resulting estimates of vehicle use (VMT), fuel consumption, and fuel
energy content are combined with emission factors drawn from various
sources to estimate emissions of GHGs, criteria air pollutants, and
airborne toxic compounds that occur throughout the fuel supply and
distribution process, as well as during vehicle operation, storage, and
refueling. Emission factors measure the mass of each GHG or criteria
pollutant emitted per vehicle-mile of travel, gallon of fuel consumed,
or unit of fuel energy content. The following sections identifies the
sources of these emission factors and explains in detail how the CAFE
Model applies them to its estimates of vehicle travel, fuel use, and
fuel energy consumption to estimate total annual emissions of each GHG,
criteria pollutant, and airborne toxic.
---------------------------------------------------------------------------
\314\ CAFE Model documentation is available at https://www.nhtsa.gov/corporate-average-fuel-economy/compliance-and-effects-modeling-system.
---------------------------------------------------------------------------
2. Simulating Upstream Emissions Impacts
Building on the methodology for simulating upstream emissions
impacts used in prior CAFE rules, this analysis uses emissions factors
developed with the U.S. Department of Energy's Greenhouse gases,
Regulated Emissions, and Energy use in Transportation (GREET) Model,
specifically GREET 2020.\315\ The analysis includes emissions impacts
estimates for regulated criteria pollutants,\316\ greenhouse
gases,\317\ and air toxics.\318\
---------------------------------------------------------------------------
\315\ U.S. Department of Energy, Argonne National Laboratory,
Greenhouse gases, Regulated Emissions, and Energy use in
Transportation (GREET) Model, Last Update: 9 Oct. 2020, https://greet.es.anl.gov/.
\316\ Carbon monoxide (CO), volatile organic compounds (VOCs),
nitrogen oxides (NOX), sulfur oxides (SOX),
and particulate matter with 2.5-micron ([micro]m) diameters or less
(PM2.5).
\317\ Carbon dioxide (CO2), methane (CH4),
and nitrous oxide (N2O).
\318\ Acetaldehyde, acrolein, benzene, butadiene, formaldehyde,
diesel particulate matter with 10-micron ([micro]m) diameters or
less (PM10).
---------------------------------------------------------------------------
The upstream emissions factors included in the CAFE Model input
files include parameters for 2020 through 2050 in five-year intervals
(e.g., 2020, 2025, 2030, and so on). For gasoline and diesel fuels,
each analysis year includes upstream emissions factors for the four
following upstream emissions processes: Petroleum extraction, petroleum
transportation, petroleum refining, and fuel transportation, storage,
and distribution (TS&D). In contrast, the upstream electricity
emissions factor is only a single value per analysis year. We briefly
discuss the components included in each upstream emissions factor here,
and a more detailed discussion is included in Chapter 5 of the TSD
accompanying this proposal and the CAFE Model Documentation.
The first step in the process for calculating upstream emissions
includes any emissions related to the extraction, recovery, and
production of petroleum-based feedstocks, namely conventional crude
oil, oil sands, and shale oils. Then, the petroleum transportation
process accounts for the transport
[[Page 49717]]
processes of crude feedstocks sent for domestic refining. The petroleum
refining calculations are based on the aggregation of fuel blendstock
processes rather than the crude feedstock processes, like the petroleum
extraction and petroleum transportation calculations. The final
upstream process after refining is the transportation, storage, and
distribution (TS&D) of the finished fuel product.
The upstream gasoline and diesel emissions factors are aggregated
in the CAFE Model based on the share of fuel savings leading to reduced
domestic oil fuel refining and the share of reduced domestic refining
from domestic crude oil. The CAFE Model applies a fuel savings
adjustment factor to the petroleum refining process and a combined fuel
savings and reduced domestic refining adjustment to both the petroleum
extraction and petroleum transportation processes for both gasoline and
diesel fuels and for each pollutant. These adjustments are consistent
across fuel types, analysis years, and pollutants, and are unchanged
from the 2020 final rule. Additional discussion of the methodology for
estimating the share of fuel savings leading to reduced domestic oil
refining is located in Chapter 6.2.4.3 of the TSD. NHTSA seeks comment
on the methodology used and specifically whether all of the change in
refining would happen domestically, rather than the current division
between domestic and non-domestic refining.
Upstream electricity emissions factors are also calculated using
GREET 2020. GREET 2020 projects a national default electricity
generation mix for transportation use from the latest Annual Energy
Outlook (AEO) data available from the previous year. As discussed
above, the CAFE Model uses a single upstream electricity factor for
each analysis year.
3. Simulating Tailpipe Emissions Impacts
Tailpipe emission factors are generated using the latest regulatory
model for on-road emission inventories from the U.S. Environmental
Protection Agency, the Motor Vehicle Emission Simulator (MOVES3),
November 2020 release. MOVES3 is a state-of-the-science, mobile-source
emissions inventory model for regulatory applications.\319\ New MOVES3
tailpipe emission factors have been incorporated into the CAFE
parameters, and these updates supersede tailpipe data previously
provided by EPA from MOVES2014 for past CAFE analyses. MOVES3 accounts
for a variety of processes related to emissions impacts from vehicle
use, including running exhaust, start exhaust, refueling displacement
vapor loss, brakewear, and tirewear, among others.
---------------------------------------------------------------------------
\319\ U.S. Environmental Protection Agency, Office of
Transportation and Air Quality, Motor Vehicle Emission Simulator
(MOVES), Last Updated: March 2021, https://www.epa.gov/moves/latest-version-motor-vehicle-emission-simulator-moves.
---------------------------------------------------------------------------
The CAFE Model uses tailpipe emissions factors for all model years
from 2020 to 2060 for criteria pollutants and air toxics. To maintain
continuity in the historical inventories, only emission factors for
model years 2020 and after were updated; all emission factors prior to
MY 2020 were unchanged from previous CAFE rulemakings. In addition, the
updated tailpipe data in the current CAFE reference case no longer
account for any fuel economy improvements or changes in vehicle miles
traveled from the 2020 final rule. In order to avoid double-counting
effects from the previous rulemaking in the current rulemaking, the new
tailpipe baseline backs out 1.5% year-over-year stringency increases in
fuel economy, and 0.3% VMT increases assumed each year (20% rebound on
the 1.5% improvements in stringency). Note that the MOVES3 data do not
cover all the model years and ages required by the CAFE Model, MOVES
only generates emissions data for vehicles made in the last 30 model
years for each calendar year being run. This means emissions data for
some calendar year and vehicle age combinations are missing. To remedy
this, we take the last vehicle age that has emissions data and forward
fill those data for the following vehicle ages. Due to incomplete
available data for years prior to MY 2020, tailpipe emission factors
for MY 2019 and earlier have not been modified and continue to utilize
MOVES2014 data.
For tailpipe CO2 emissions, these factors are defined
based on the fraction of each fuel type's mass that represents carbon
(the carbon content) along with the mass density per unit of the
specific type of fuel. To obtain the emission factors associated with
each fuel, the carbon content is then multiplied by the mass density of
a particular fuel as well as by the ratio of the molecular weight of
carbon dioxide to that of elemental carbon. This ratio, a constant
value of 44/12, measures the mass of carbon dioxide that is produced by
complete combustion of mass of carbon contained in each unit of fuel.
The resulting value defines the emission factor attributed to
CO2 as the amount of grams of CO2 emitted during
vehicle operation from each type of fuel. This calculation is repeated
for gasoline, E85, diesel, and compressed natural gas (CNG) fuel types.
In the case of CNG, the mass density and the calculated CO2
emission factor are denoted as grams per standard cubic feet (scf),
while for the remainder of fuels, these are defined as grams per gallon
of the given fuel source. Since electricity and hydrogen fuel types do
not cause CO2 emissions to be emitted during vehicle
operation, the carbon content, and the CO2 emission factors
for these two fuel types are assumed to be zero. The mass density,
carbon content, and CO2 emission factors for each fuel type
are defined in the Parameters file.
The CAFE Model calculates CO2 tailpipe emissions
associated with vehicle operation of the surviving on-road fleet by
multiplying the number of gallons (or scf for CNG) of a specific fuel
consumed by the CO2 emissions factor for the associated fuel
type. More specifically, the amount of gallons or scf of a particular
fuel are multiplied by the carbon content and the mass density per unit
of that fuel type, and then applying the ratio of carbon dioxide
emissions generated per unit of carbon consumed during the combustion
process.\320\
---------------------------------------------------------------------------
\320\ Chapter 3, Section 4 of the CAFE Model Documentation
provides additional description for calculation of CO2
tailpipe emissions with the model.
---------------------------------------------------------------------------
4. Estimating Health Impacts From Changes in Criteria Pollutant
Emissions
The CAFE Model computes select health impacts resulting from three
criteria pollutants: NOX, SOX,\321\ 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 low and high mortality
estimates, and are measured by the number of instances predicted to
occur per ton of emitted pollutant.\322\ The model reports total health
impacts by multiplying the estimated tons of each criteria pollutant by
the corresponding health incidence per ton value. The inputs that
inform the calculation of the total tons of emissions resulting from
criteria pollutants are discussed above. This section discusses how the
health
[[Page 49718]]
incidence per ton values were obtained. See Section III.G.2.b)(2) and
Chapter 6.2.2 of the TSD accompanying this proposal for information
regarding the monetized damages arising from these health impacts.
---------------------------------------------------------------------------
\321\ Any reference to SOX in this section refers to
the sum of sulfur dioxide (SO2) and sulfate particulate
matter (pSO4) emissions, following the methodology of the
EPA papers cited.
\322\ The complete list of morbidity impacts estimated in the
CAFE Model is as follows: Acute bronchitis, asthma exacerbation,
cardiovascular hospital admissions, lower respiratory symptoms,
minor restricted activity days, non-fatal heart attacks, respiratory
emergency hospital admissions, respiratory emergency room visits,
upper respiratory symptoms, and work loss days.
---------------------------------------------------------------------------
The SEIS that accompanies this proposal also includes a detailed
discussion of the criteria pollutants and air toxics analyzed and their
potential health effects. In addition, consistent with past analyses,
NHTSA will perform full-scale photochemical air quality modeling and
present those results in the Final SEIS associated with the final rule.
That analysis will provide additional assessment of the human health
impacts from changes in PM2.5 and ozone associated with this
rule. NHTSA will also consider whether such modeling could practicably
and meaningfully be included in the FRIA, noting that compliance with
CAFE standards is based on the average performance of manufacturers'
production for sale throughout the U.S., and that the FRIA will involve
sensitivity analysis spanning a range of model inputs, many of which
impact estimates of future emissions from passenger cars and light
trucks. Chapter 6 of the PRIA includes a discussion of overall changes
in health impacts associated with criteria pollutant changes across the
different rulemaking scenarios.
In previous rulemakings, health impacts were split into two
categories based on whether they arose from upstream emissions or
tailpipe emissions. In the current analysis, these health incidence per
ton values have been updated to reflect the differences in health
impacts arising from each emission source sector, according to the
latest publicly available EPA reports. Five different upstream emission
source sectors (Petroleum Extraction, Petroleum Transportation,
Refineries, Fuel Transportation, Storage and Distribution, and
Electricity Generation) are now represented. 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.\323\
---------------------------------------------------------------------------
\323\ See Environmental Protection Agency (EPA). 2018.
Estimating the Benefit per Ton of Reducing PM2.5
Precursors from 17 Sectors. https://www.epa.gov/sites/production/files/2018-02/documents/sourceapportionmentbpttsd_2018.pdf.
---------------------------------------------------------------------------
The CAFE Model health impacts inputs are based partially on the
structure of 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),\324\ which
reported benefit per ton values for the years 2016, 2020, 2025, and
2030.\325\ For the years in between the source years used in the input
structure, the CAFE Model applies values from the closest source year.
For instance, 2020 values are applied for 2020-2022, and 2025 values
are applied for 2023-2027. For further details, see the CAFE Model
documentation, which contains a description of the model's computation
of health impacts from criteria pollutant emissions.
---------------------------------------------------------------------------
\324\ Environmental Protection Agency (EPA). 2018. Estimating
the Benefit per Ton of Reducing PM2.5 Precursors from 17
Sectors. https://www.epa.gov/sites/production/files/2018-02/documents/sourceapportionmentbpttsd_2018.pdf.
\325\ As the year 2016 is not included in this analysis, the
2016 values were not used.
---------------------------------------------------------------------------
Despite efforts to be as consistent as possible between the
upstream emissions sectors utilized in the CAFE Model with the 2018 EPA
source apportionment TSD, the need to use up-to-date sources based on
newer air quality modeling updates led to the use of multiple papers.
In addition to the 2018 EPA source apportionment TSD used in the 2020
final rule, DOT used additional EPA sources and conversations with EPA
staff to appropriately map health incidence per ton values to the
appropriate CAFE Model emissions source category.
We understand that uncertainty exists around the contribution of
VOCs to PM2.5 formation in the modeled health impacts from
the petroleum extraction sector; however, based on feedback to the 2020
final rule we believe that the updated health incidence values specific
to petroleum extraction sector emissions may provide a more appropriate
estimate of potential health impacts from that sector's emissions than
the previous approach of applying refinery sector emissions impacts to
the petroleum extraction sector. That said, we are aware of work that
EPA has been doing to address concerns about the BPT estimates, and
NHTSA will work further with EPA to update and synchronize approaches
to the BPT estimates.
The basis for the health impacts from the petroleum extraction
sector was a 2018 oil and natural gas sector paper written by EPA staff
(Fann et al.), which estimated health impacts for this sector in the
year 2025.\326\ This paper defined the oil and gas sector's emissions
not only as arising from petroleum extraction but also from
transportation to refineries, while the CAFE/GREET component is
composed of only petroleum extraction. After consultation with the
authors of the EPA paper, it was determined that these were the best
available estimates for the petroleum extraction sector,
notwithstanding this difference. Specific health incidence per
pollutant were not reported in the paper, so EPA staff sent BenMAP
health incidence files for the oil and natural gas sector upon request.
DOT staff then calculated per ton values based on these files and the
tons reported in the Fann et al. paper.\327\ The only available health
impacts corresponded to the year 2025. Rather than trying to
extrapolate, these 2025 values were used for all the years in the CAFE
Model structure: 2020, 2025, and 2030.\328\ This simplification implies
an overestimate of damages in 2020 and an underestimate in 2030.\329\
---------------------------------------------------------------------------
\326\ Fann, N., Baker, K. R., Chan, E., Eyth, A., Macpherson,
A., Miller, E., & Snyder, J. (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), 8095-8103 (hereinafter Fann et al.).
\327\ Nitrate-related health incidents were divided by the total
tons of NOX projected to be emitted in 2025, sulfate-
related health incidents were divided by the total tons of projected
SOX, and EC/OC (elemental carbon and organic carbon)
related health incidents were divided by the total tons of projected
EC/OC. Both Fann et al. and the 2018 EPA source apportionment TSD
define primary PM2.5 as being composed of elemental
carbon, organic carbon, and small amounts of crustal material. Thus,
the EC/OC BenMAP file was used for the calculation of the incidents
per ton attributable to PM2.5.
\328\ These three years are used in the CAFE Model structure
because it was originally based on the estimate provided in the 2018
EPA source apportionment TSD.
\329\ See EPA. 2018. Estimating the Benefit per Ton of Reducing
PM2.5 Precursors from 17 Sectors. https://www.epa.gov/sites/production/files/2018-02/documents/sourceapportionmentbpttsd_2018.pdf p.9.
---------------------------------------------------------------------------
The petroleum transportation sector and fuel TS&D sector did not
correspond to any one EPA source sector in the 2018 EPA source
apportionment TSD, so a weighted average of multiple different EPA
sectors was used to determine the health impact per ton values for
those sectors. We used a combination of different EPA mobile source
sectors from two different papers, the 2018 EPA source apportionment
TSD,\330\ and a 2019 mobile source sectors paper (Wolfe et al.)\331\ to
generate these values. The health incidence per ton values associated
with the refineries sector and
[[Page 49719]]
electricity generation sector were drawn solely from the 2018 EPA
source apportionment TSD.
---------------------------------------------------------------------------
\330\ Environmental Protection Agency (EPA). 2018. Estimating
the Benefit per Ton of Reducing PM2.5 Precursors from 17
Sectors. https://www.epa.gov/sites/production/files/2018-02/documents/sourceapportionmentbpttsd_2018.pdf.
\331\ Wolfe et al. 2019. Monetized health benefits attributable
to mobile source emissions reductions across the United States in
2025. https://pubmed.ncbi.nlm.nih.gov/30296769/.
---------------------------------------------------------------------------
The CAFE Model follows a similar process for computing health
impacts resulting from tailpipe emissions as it does for calculating
health impacts from upstream emissions. Previous rulemakings used the
2018 EPA source apportionment TSD as the source for the health
incidence per ton, matching the CAFE Model tailpipe emissions inventory
to the ``on-road mobile sources sector'' in the TSD. However, a more
recent EPA paper from 2019 (Wolfe et al.) \332\ computes monetized
damage costs per ton values at a more disaggregated level, separating
on-road mobile sources into multiple 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.
---------------------------------------------------------------------------
\332\ Wolfe et al. 2019. Monetized health benefits attributable
to mobile source emissions reductions across the United States in
2025. https://pubmed.ncbi.nlm.nih.gov/30296769/.
---------------------------------------------------------------------------
The methodology for generating values for each emissions category
in the CAFE Model is discussed in detail in Chapter 5 of the TSD
accompanying this proposal. The Parameters file contains all of the
health impact per ton of emissions values used in this proposal.
G. Simulating Economic Impacts of Regulatory Alternatives
This section describes the agency's approach for measuring the
economic costs and benefits that will result from establishing
alternative CAFE standards for future model years. The benefit and cost
measures the agency uses are important considerations, because as
Office of Management and Budget (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.\333\ For CAFE
standards, those include vehicle manufacturers, buyers of new cars and
light trucks, owners of used vehicles, and suppliers of fuel, all of
whose behavior is likely to respond in complex ways to the level of
CAFE standards that DOT establishes for future model years.
---------------------------------------------------------------------------
\333\ White House Office of Management and Budget, Circular A-4:
Regulatory Analysis, September 17, 2003 (https://obamawhitehouse.archives.gov/omb/circulars_a004_a-4/), Section E.
---------------------------------------------------------------------------
It is important to report the benefits and costs of this proposed
action in a format that conveys useful information about how those
impacts are generated and also distinguishes the impacts of those
economic consequences for private businesses and households from the
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, and shows how the economy-wide
or ``social'' benefits and costs of the proposed action are composed of
its direct effects on vehicle producers, buyers, and users, plus the
indirect or ``external'' benefits and costs it creates for the general
public.
Table III-37 and Table III-38 present the incremental economic
benefits and costs of the proposed action and the alternatives
(described in detail in Section IV) to increase CAFE standards for
model years 2024-26 at three percent and seven percent discount rates
in a format that is intended to meet these objectives. The tables
include costs which are transfers between different economic actors--
these will appear as both a cost and a benefit in equal amounts (to
separate affected parties). Societal cost and benefit values shown
elsewhere in this document do not show costs which are transfers for
the sake of simplicity but report the same net societal costs and
benefits. The proposed action and the alternatives would increase costs
to manufacturers for adding technology necessary to enable new cars and
light trucks to comply with fuel economy and emission regulations. It
may also increase fine payments by manufacturers who would have
achieved compliance with the less demanding baseline standards.
Manufacturers are assumed to transfer these costs on to buyers by
charging higher prices; although this reduces their revenues, on
balance, the increase in compliance costs and higher sales revenue
leaves them financially unaffected. Since the analysis assumes that
manufacturers are left in the same economic position regardless of the
standards, they are excluded from the tables.
BILLING CODE 4910-59-P
[[Page 49720]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.086
---------------------------------------------------------------------------
\334\ A portion of Reduced Fuel Costs represent the benefit to
consumers of not having to pay taxes on avoided gasoline
consumption. This amount offsets the Loss in Fuel Tax Revenue in
External Costs. For example, the $47.9 billion in Reduced Fuel Costs
in alternative 1 represents $11 billion of avoided fuel taxes and
$36.9 billion in gasoline savings.
---------------------------------------------------------------------------
[[Page 49721]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.087
BILLING CODE 4910-59-C
Compared to the baseline standards, if the preferred alternative is
finalized, the analysis shows that buyers of new cars and light trucks
will incur higher purchasing prices and financing costs, which will
lead to some buyers dropping out of the new vehicle market. Drivers of
new vehicles will also experience a slight uptick in the risk of being
injured in a crash because of mass reduction technologies employed to
meet the increased standards. While this effect is not statistically
significant, NHTSA provides these results for transparency, and to
demonstrate that their inclusion does not affect NHTSA's proposed
policy decision. Because of the increasing price of new vehicles, some
owners may delay retiring and replacing their older vehicles with newer
models. In effect, this will transfer some driving that would have been
done in newer vehicles under the baseline scenario to older models
within the legacy fleet, thus increasing costs for injuries (both fatal
and less severe) and property damages sustained in motor vehicle
crashes. This stems from the fact that cars and light trucks have
become progressively more protective in crashes over time (and also
slightly less prone to certain types of crashes, such as rollovers).
Thus, shifting some travel from newer to older models would increase
injuries and damages sustained by drivers and passengers because they
are traveling in less safe vehicles and not because it changes the risk
profiles of drivers themselves. These costs are largely driven by
assumptions regarding consumer valuation of fuel efficiency and an
assumption that more fuel-efficient vehicles are less preferable to
consumers than their total cost to improve fuel economy. These are
issues on which we seek comments.
In exchange for these costs, consumers will benefit from new cars
and light trucks with better fuel economy. Drivers will experience
lower costs as a consequence of new vehicles' decreased fuel
consumption, and from fewer refueling stops required because of their
increased driving range. They will experience mobility benefits as they
use newly purchased cars and light trucks more in response to their
lower operating costs. On balance, consumers of new cars and light
trucks produced during the model years subject to this proposed action
will experience significant economic benefits.
Table III-37 and Table III-38 also show that the changes in fuel
consumption and vehicle use resulting
[[Page 49722]]
from this proposed action will in turn generate both benefits and costs
to society writ large. These impacts are ``external,'' in the sense
that they are by-products of decisions by private firms and individuals
that alter vehicle use and fuel consumption but are experienced broadly
throughout society rather than by the firms and individuals who
indirectly cause them. In terms of costs, additional driving by
consumers of new vehicles in response to their lower operating costs
will increase the external costs associated with their contributions to
traffic delays and noise levels in urban areas, and these additional
costs will be experienced throughout much of the society. While most of
the risk of additional driving or delaying purchasing a newer vehicle
are internalized by those who make those decisions, a portion of the
costs are borne by other road users. Finally, since owners of new
vehicles will be consuming less fuel, they will pay less in fuel taxes.
Society will also benefit from more stringent standards. Increased
fuel efficiency will reduce the amount of petroleum-based fuel consumed
and refined domestically, which will decrease the emissions of carbon
dioxide and other greenhouse gases that contribute to climate change,
and, as a result, the U.S. (and the rest of world) will avoid some of
the economic damages from future changes in the global climate.
Similarly, reduced fuel production and use will decrease emissions of
more localized air pollutants (or their chemical precursors), and the
resulting decrease in the U.S. population's exposure to harmful levels
of these pollutants will lead to lower costs from its adverse effects
on health. Decreasing consumption and imports of crude petroleum for
refining lower volumes of gasoline and diesel will also accrue some
benefits throughout to the U.S., in the form of potential gains of
energy security as businesses and households that are dependent on fuel
are subject to less sudden and sharp changes in energy prices.
On balance, Table III-37 and Table III-38 show that both consumers
and society as a whole will experience net economic benefits from the
proposed action. The following subsections will briefly describe the
economic costs and benefits considered by the agency. For a complete
discussion of the methodology employed and the results, see TSD Chapter
6 and PRIA Chapter 6, respectively. The safety implications of the
proposal--including the monetary impacts--are reserved for Section
III.H. NHTSA seeks comment on the following discussion.
1. Private Costs and Benefits
(a) Costs to Consumers
(1) Technology Costs
The proposed action and the alternatives would increase costs to
manufacturers for adding technology necessary to enable new cars and
light trucks to comply with fuel economy and emission regulations.
Manufacturers are assumed to transfer these costs on to buyers by
charging higher prices. See Section III.C.6 and TSD Chapter 2.5.
(2) Consumer Sales Surplus
Buyers who would have purchased a new vehicle with the baseline
standards in effect but decide not to do so in response to the changes
in new vehicles' prices due to more stringent standards in place will
experience a decrease in welfare. The collective welfare loss to those
``potential'' new vehicle buyers is measured by the foregone consumer
surplus they would have received from their purchase of a new vehicle
in the baseline.
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 the 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 elaborates that consumer
surplus values be monetized ``when they are significant.'' \335\
---------------------------------------------------------------------------
\335\ OMB Circular A-4, at 37-38.
---------------------------------------------------------------------------
Accounting for the portion of fuel savings that the average new
vehicle buyer demands, and holding all else equal, higher average
prices should depress new vehicle sales and by extension reduce
consumer surplus. The inclusion of consumer surplus is not only
consistent with OMB guidance, but with other parts of the regulatory
analysis. For instance, we calculate the increase in consumer surplus
associated with increased driving that results from the decrease in the
cost per mile of operation under more stringent regulatory
alternatives, as discussed in Section III.G.1.b)(3). The surpluses
associated with sales and additional mobility are inextricably linked
as they capture the direct costs and benefits accrued by purchasers of
new vehicles. The sales surplus captures the welfare loss to consumers
when they forego a new vehicle purchase in the presence of higher
prices and the additional mobility measures the benefit increased
mobility under lower operating expenses.
The agency 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 fuel economy. For additional
information about consumer sales surplus, see TSD Chapter 6.1.5.
(3) Ancillary Costs of Higher Vehicle Prices
Some costs of purchasing and owning a new or used vehicle scale
with the value of the vehicle. Where fuel economy standards increase
the transaction price of vehicles, they will affect both the absolute
amount paid in sales tax and the average amount of financing required
to purchase the vehicle. Further, where they increase the MSRP, they
increase the appraised value upon which both value-related registration
fees and a portion of insurance premiums are based. The analysis
assumes that the transaction price is a set share of the MSRP, which
allows calculation of these factors as shares of MSRP. For a detailed
explanation of how the agency estimates these costs, see TSD Chapter
6.1.1.
These costs are included in the consumer per-vehicle cost-benefit
analysis but are not included in the societal cost-benefit analysis
because they are assumed to be transfers from consumers to governments,
financial institutions, and insurance companies.
(b) Benefits to Consumers
(1) Fuel Savings
The primary benefit to consumers of increasing CAFE standards are
the additional fuel savings that accrue to new vehicle owners. Fuel
savings are calculated by multiplying avoided fuel consumption by fuel
prices. Each vehicle of a given body style is assumed to be driven the
same as all the others of a comparable age and body style in each
calendar year. The ratio of that cohort's VMT to its fuel efficiency
produces an estimate of fuel consumption. The difference between fuel
consumption in the baseline, and in each alternative, represents the
gallons (or energy) saved. Under this assumption, our estimates of fuel
consumption from increasing the fuel economy of each individual model
depend only on how much its fuel economy is increased, and do not
reflect whether its actual use differs from other
[[Page 49723]]
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
TSD Chapter 4.3.1.2). Consumers save money on fuel expenditures at the
average retail fuel price (fuel price assumptions are discussed in
detail in TSD Chapter 4.1.2), which includes all taxes and represents
an average across octane blends. For gasoline and diesel, the 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. 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
such as taxes.
See TSD Chapter 6.1.3 for additional details. In the TSD, the
agency considers the possibility that several of the assumptions made
about vehicle use could lead to misstating the benefits of fuel
savings. The agency notes that these assumptions are necessary to model
fuel savings and likely have minimal impact to the accuracy of this
analysis.
Technologies that can be used to improve fuel economy can also be
used to increase other vehicle attributes, especially acceleration
performance, weight, and energy-using accessories. While this is most
obvious for technologies that improve the efficiency of engines and
transmissions, it is also 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 the technology, 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. How consumers value
increased fuel economy and how fuel economy regulations affect
manufacturers' decisions about how to use efficiency improving
technologies can have important effects on the estimated costs,
benefits, and indirect impacts of fuel economy standards.
NHTSA's preliminary regulatory impact analysis assumes that
consumers will purchase, and manufacturers will supply, fuel economy
technologies in the absence of fuel economy standards if the technology
``pays for itself'' in fuel savings over the first 30 months vehicle
use. This assumption is based on statements manufacturers have made to
us and to NASEM CAFE committees and has been deployed in NHTSA's prior
analyses of fuel economy standards. However, classical economic
concepts suggest that deploying this assumption may be problematic when
the baseline standards are binding--meaning that they constrain
consumers' behavior to vehicles that are more fuel efficient than they
would have chosen in the absence of fuel economy standards. To
demonstrate this, we introduce a standard economic model of consumer
optimization subject to a budgetary constraint.\336\
---------------------------------------------------------------------------
\336\ Note that the following section examines whether consumers
are rational in their fuel economy consumption patterns. This
analysis could represent a scenario where consumers are rational, or
one in which the underweight future fuel savings in their car
purchasing decisions.
[GRAPHIC] [TIFF OMITTED] TP03SE21.088
Figure III-17 models consumer behavior when constrained by a
budget. Line B1 represents the consumer's original budget constraint.
Curve I1 is called an indifference curve, which shows each combination
of horsepower, which we use here to represent a variety of attributes
that could be traded-off for increased fuel economy, and fuel savings
between which a consumer is indifferent. The curvature of the
indifference curve reflects the principle of diminishing marginal
utility--the idea that consumers value consumption of the first unit of
any product greater than subsequent units. Curve I1 represents the
highest utility achievable when subject to budget constraint B1, as the
consumer may select the combination of performance and fuel economy
represented by point (HP1, FS1)--which is the point of tangency between
I1 and B1. When new technology becomes available that
[[Page 49724]]
makes either fuel economy or performance (or both) more affordable, the
consumer's budget constraint shifts from B1 to B2, and the consumer can
now achieve the point of tangency between I2 and B2 (HP2, FS2). In this
case, both fuel economy and performance are modeled as normal goods--
meaning that as they become more affordable, consumers will elect to
consume more of each.
[GRAPHIC] [TIFF OMITTED] TP03SE21.089
A different analysis is required when fuel economy standards also
bind on consumer decisions. Here, minimum fuel economy standards
eliminate some combinations of performance and fuel economy, creating a
corner solution in the budget constraint. Figure III-18 shows this
effect, as the consumer will elect the point of tangency with budget
constraint B1 at the corner solution at (HP1 and FS1), which is also
the minimum fuel economy standard. When new technology is introduced
(or becomes cheaper) which makes fuel economy and performance more
affordable, the consumer's budget constraint shifts from B1 to B2
again, but the existing fuel economy standard is still binding, so a
corner solution remains at FS1. The consumer will choose the corner
combination of fuel economy and performance again, where I2 is tangent
with B2, at point (FS1, HP2). Note that the consumer has elected to
improve performance from HP1 to HP2 but has not elected to improve fuel
economy.
This model implies that fuel economy standards prevent consumers
from achieving their optimal bundle of fuel economy and performance
given their current preferences, creating an opportunity cost to
consumers in the form of lost performance. The constrained optimization
model can be slightly tweaked to show this loss to consumers. In this
example, the y-axis uses the composite good M reflecting all other
goods and services, including performance. This makes the
interpretation of the y axis simpler, as it can be more easily
translated into dollars.
[[Page 49725]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.090
Figure III-19 shows the effect of new binding fuel economy
standards on consumer behavior. The consumer begins at point (M1, FS1)
on indifference curve I1. If more stringent fuel economy standards were
in place, the consumer would shift to the lower indifference curve I2--
reflecting a lower level of utility--and would consume at point (M2,
FS2). One concept from the economics literature for valuing the change
in welfare from a change in prices or quality (or in this case fuel
economy standards) is to look at the compensating variation between the
original and final equilibrium. The compensating variation is the
amount of money that a consumer would need to return to their original
indifference curve.\337\ It is found by finding the point of tangency
with the new indifference curve at the new marginal rate of
substitution between the two products and finding the equivalent point
on the old indifference curve. Figure III-19 shows this as the distance
between points A and B on the Y-axis.\338\
---------------------------------------------------------------------------
\337\ There is a very similar concept for valuing this
opportunity cost known as the equivalent variation. NHTSA presents
the compensating variation here for simplicity but acknowledges that
the equivalent variation is an equally valid approach.
\338\ Boardman, Greenberg, Vining, Weimer (2011). Cost-Benefit
Analysis; Concepts and Practice. Pgs. 69-73.
---------------------------------------------------------------------------
The above logic appears to explain the trends in fuel economy and
vehicle performance (measured by horsepower/pound) between 1986 and
2004, when gasoline prices fluctuated between $2.00 and $2.50 per
gallon and new light duty vehicle fuel economy standards remained
nearly constant Figure III-20. Over the same period numerous advanced
technologies with the potential to increase fuel economy were adopted.
However, the fuel economy of new light duty vehicles did not increase.
In fact, increases in the market share of light trucks caused fuel
economy to decline somewhat.
[[Page 49726]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.091
On the other hand, from 1986-2004 the acceleration performance of
light-duty vehicles increased by 45% (Figure III-21). Advances in
engine technology are reflected in the steadily increasing ratio of
power output to engine size, measured by displacement. Without
increased fuel economy standards, all the potential of advanced
technology appears to have gone into increasing performance and other
attributes (for example average weight also increased by 27% from 1986-
2004) and none to increasing fuel economy. Fuel economy remained nearly
constant at the levels required by the car and light truck standards,
consistent with the idea the standards were a binding constraint on the
fuel economy of new vehicles. The pattern for periods of price shocks
and increasing standards is different, however, as can be seen in
Figure III-20. In the early period up to 1986, there is almost no
change in performance and vehicle weight decreased. However, in the
more recent period post-2004, performance continued to increase
although apparently at a slower rate than during the 1986-2004 period
and vehicle weight changed very little. The large and rapid price
increases appear to have been an important factor. Even before
manufacturers can respond to prices and regulations by adding fuel
economy technologies to new vehicles, demand can respond by shifting
towards smaller, lighter and less powerful makes and models. The period
of voluntary increase in fuel economy is consistent with the
constrained optimization problem presented above if fuel economy
standards no longer constrained consumer behavior after the change in
fuel prices.
[[Page 49727]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.092
If this constrained optimization model is a reliable predictor of
consumer behavior for some substantive portion of the new vehicle
market, it would have important implications for how NHTSA models
baseline consumer choices. In this case, it would mean that as
technology that could improve fuel economy is added absent standards,
it would be primarily geared towards enhancing performance rather than
fuel economy. Depending on how consumers value future fuel savings, it
might be appropriate for NHTSA to change its methods of analysis to
reflect consumer preferences for performance, and to develop methods
for valuing the opportunity cost to consumers for constraining them to
more fuel efficient options. NHTSA seeks comment on the analysis
presented in this section and its implications for the assumptions that
consumers will add technologies that payback within thirty months. It
also seeks comment on possible approaches to valuing the opportunity
cost to consumers.
Potential Implications of Behavioral Theories for Fuel Economy
Standards
In this proposed rule, the cost-effectiveness of technology-based
fuel economy improvements is used to estimate fuel economy improvements
by manufacturers in the No-Policy case and to estimate components of
the benefits and costs of alternative increases in fuel economy
standards. In the interest of insuring that our theory and methods
reflect the best current understanding of how consumers perceive the
value of technology-based fuel economy improvements, we are seeking
comment on our current, and possible alternative representations of how
consumers value fuel economy when purchasing a new vehicle and while
owning and operating it, and how manufacturers decide to implement fuel
economy technologies.\339\ We are particularly interested in comments
on our assumption that in our Alternative 0 (no change in existing
standards) manufacturers will implement technologies to improve fuel
economy even if existing standards do not require them to do so,
provided that the first 30 months of fuel savings will be greater than
or equal to the cost of the technology. We are also interested in
comments concerning our use of the difference between the price
consumers pay for increased fuel economy and the value of fuel savings
over the first 30 month for estimating the impacts of the standards on
new and used vehicle markets. Finally, we are interested in comments on
when attributes that can be traded-off for increased fuel economy
should be considered opportunity costs of increasing fuel economy.
---------------------------------------------------------------------------
\339\ We are making a distinction between consumers choices when
presented with technology-based fuel economy improvements versus
consumers' choices among various makes and models of vehicles. The
latter topic is also of interest and is discussed in (see TSD, Ch.
4.2.1).
---------------------------------------------------------------------------
How manufacturers choose to implement technologies that can
increase fuel economy depends on consumers' willingness to pay (WTP)
for fuel economy and the other attributes the technologies can improve.
Consumers' WTP for increasing levels of an attribute defines the
consumers' demand function for that attribute. Here, we consider how
consumers' WTP for increased fuel economy (WTPFE) and for
performance (WTPHP), where FE stands for fuel
economy and HP stands for ``Horse Power''/performance, and
the cost of technology (C) affect manufacturers' decisions about how to
implement the technologies with and without fuel economy standards. For
the purpose of this discussion, it is convenient to think of fuel
economy in terms of its inverse, the rate of fuel consumption per mile.
While miles per gallon (mpg) delivers decreasing fuel savings per mpg,
decreasing fuel consumption delivers constant fuel savings per gallon
per mile (gpm) reduced. Thinking in terms of gpm is appropriate because
fuel economy standards are in fact defined in terms of the inverse of
fuel economy, i.e., gpm.
In the CAFE Model we typically assume that for a technology that
can improve fuel economy, consumers are willing to pay an amount equal
to the first thirty months of fuel savings (WTP30FE). This
is an important assumption for several reasons. The market will tend to
equilibrate the ratio of consumers' WTP for fuel economy
[[Page 49728]]
divided by its cost to the ratio of consumers' WTP for other attributes
divided by their cost. The value of the first thirty months of fuel
savings is typically about one-fourth of the value of savings over the
expected life of a vehicle, discounted at annual rates between 3% and
7%. Arguably, this represents an important undervaluing of technology-
based fuel economy improvement relative to its true economic value. Our
use of the 30-month payback assumption is based on statements
manufacturers have made to us and to NASEM CAFE committees. It is also
based on the fact that repeated assessments of the potential for
technology to improve fuel economy have consistently found a
substantial potential to cost-effectively increase fuel economy. But it
is also partly based on the fact that the substantial literature that
has endeavored to infer consumers' WTP for fuel economy is
approximately evenly divided between studies that support severe
undervaluation and those that support valuation at approximately full
lifetime discounted present value (e.g., Greene et al., 2018; Helfand
and Wolverton, 2011; Greene, 2010; for a more complete discussion see
TSD, Ch. 6.1.6). The most recent studies based on detailed data and
advanced methods of statistical inference have not resolved the issue
(NASEM, 2021, Ch. 11.3).
If consumers value technology-based fuel economy improvements at
only a small fraction of their lifetime present value and the market
equates WTP30FE/C to WTPHP/C, the market will
tend to oversupply performance relative to fuel economy (Allcott et
al., 2014; Heutel, 2015). The WTP30FE assumption also has
important consequences when fuel economy standards are in effect.
Alternative 0 in this proposed rule assumes not only that the SAFE
standards are in effect but that the manufacturers who agreed to the
California Framework will be bound by that agreement. If those existing
regulations are binding, it is likely that WTPHP >
WTP30FE. (For simplicity we assume that over the range of
fuel economy and performance achievable by the technology, both WTP
values are constant.)\340\ This outcome would be expected in a market
where consumers undervalue fuel savings in their normal car buying
decisions and standards require levels of fuel economy beyond what they
are willing to pay.\341\ This is illustrated in Figure III-22. The
initial consumer demand function for vehicles (D0) is
shifted upward by WTP30FE to represent the consumer demand
function for the increased fuel economy the technology could produce
(D30FE) and by WTPHP to represent the demand
function (DHP) for the potential increase in performance.
Because the technology has a cost (C), the manufacturers' supply
function (S0) shifts upward to S1 = S0
+ C.\342\ If the cost of the technology exceeds consumers' WTP for
either the fuel economy or the performance it can deliver, the
technology will not be adopted in the absence of regulations requiring
it. In Figure III-22 we show the case where C < WTP30FE <
WTPHP. In this case, using the technology to increase
performance provides the greatest increase in sales and revenues:
QHP > Q30FE > Q0. Since both WTP
values are assumed to be approximately constant over the range of
improvement the technology can provide, there is no possible
combination of fuel economy and performance improvement that would
produce a larger increase in sales than using the technology entirely
to increase performance.\343\ Importantly, as long as C <
WTPHP, the actual cost of the technology does not affect the
manufacturer's decision to use 100% of its potential to increase
performance and 0% to increase fuel economy. The technology's payback
period for the increase in fuel economy is irrelevant. If we reverse
the relative WTP values (i.e., WTP30FE > WTPHP),
then the manufacturer will choose to use 100% of the technology's
potential to increase fuel economy and 0% to increase performance,
assuming constant WTP values.\344\ This conclusion may contradict our
current method, which assumes that even with increasing fuel economy
standards in Alternative 0, manufacturers will adopt fuel economy
technologies with WTP30FE < C and use them to increase fuel
economy rather than performance.
---------------------------------------------------------------------------
\340\ Although there are diminishing returns to increased miles
per gallon, in terms of fuel savings in gallons or dollars, there
are not diminishing returns to reductions in fuel consumption per
mile, except due to decreasing marginal utility of income.
WTPHP likely decreases with increasing performance, but
if the changes are not too large, the assumption of constant WTP is
reasonable.
\341\ If there are no binding regulatory constraints and fuel
economy and other vehicle attributes are normal goods, consumers
will elect more of each in the event technological progress makes it
possible to afford them. This simplifying assumption is consistent
with a scenario where consumers' baseline vehicle choices are
constrained by regulatory standards. See above for more discussion.
\342\ The supply function for new cars is assumed to be
perfectly elastic for the sake of simplicity of exposition. Note
that if the cost of the technology exceeds consumers' WTP for both
fuel economy and performance, the technology will not be adopted in
the absence of regulations requiring it.
\343\ In fact, all that is required is that over the range of
increases achievable by the technology, WTPHP >
WTPFE.
\344\ However, as noted above, the market will tend to equate
WTPHP/C to WTPFE/C, so if there is sufficient
variation in WTPHP over the range of values achievable by
the technology, some of each will be provided.
---------------------------------------------------------------------------
[[Page 49729]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.093
Because the expected present value of fuel savings is several times
the 30-month value, it is quite possible that the WTP for performance
lies between the lifetime present value of fuel savings and the 30-
month value: WTPPVFE > WTPHP >
WTP30FE. This possibility is illustrated in Figure III-23,
in which there are three demand functions in addition to the initial
demand function, D0. In Figure III-23, if the consumer were
willing to pay for the full present value of fuel savings, the
technology would be applied 100% to increasing fuel economy, provided C
< WTPPVFE. But if standards were binding and the consumer
were willing to pay for only 30 months of fuel savings, the technology
would be applied 100% to increasing performance, provided C <
WTPHP. Suppose that the cost of the technology is not C, but
a much smaller value, say c < C and c < WTP30FE. Assuming
consumers value increased fuel economy at WTP30FE, it
remains the case that all the technology's potential will be applied to
increasing performance because that gives the greatest increase in
sales. The implication is that when there is a binding fuel economy
standard, as long as WTPHP > WTP30FE, no
technologies would be used to increase fuel economy in the absence of a
regulatory requirement to do so. If consumers' WTP for fuel economy is
WTP30FE and regulatory standards are binding,
WTPHP > WTPFE seems likely.
If WTP30FE < WTPHP (recalling that HP can
represent attributes in addition to fuel economy), the above analysis
of producer behavior contradicts the current operation of the CAFE
Model, which assumes that manufacturers will apply technologies whose
costs are less than WTP30FE to improving fuel economy in the
absence of regulations requiring them to do so. For the final rule,
NHTSA is considering changing the assumption that in the absence of
standards that require it, manufactures will adopt technologies to
improve fuel economy that have a payback period of 30 months or less,
in favor of the above analysis. We are interested in receiving comments
that specifically address the validity of the current and proposed
approach.
As discussed in TSD Chapter 4.2.1.1, there is no consensus in the
literature about how consumers value fuel economy improvements when
making vehicle purchases. In this and past analyses, we have assumed
that consumers value only the first 30 months of fuel savings when
making vehicle purchase decisions. This value is a small fraction,
approximately one fourth of the expected present value of future fuel
savings over the typical life of a light-duty vehicle, assuming
discount rates in the range of 3% to 7% per year. On the other hand,
when estimating the societal value of fuel economy improvements, we use
the full present value of discounted fuel savings over the expected
life of the vehicle because it represents a real resource savings.
However, the possibility that consumers' perceptions of utility at the
time of purchase (decision utility) may differ from the utility
consumers experience while consuming a good and that experienced
utility may be the preferrable metric for policy evaluation has been
raised in the economic literature (Kahneman and Sugden, 2005). In our
methods, we use WTP30FE to represent consumers' decision
utility. Gallons saved over the life of a vehicle, valued at the
current price of gasoline, and discounted to present value appears to
be an appropriate measure of experienced utility. The large difference
between our measure of decision utility and lifetime present value fuel
savings as a measure of experienced utility has potentially important
implications for how we estimate the impacts of fuel economy standards
on new vehicle sales and the used vehicle market. It seems plausible
that as consumers experience the fuel savings benefits of increased
fuel economy, their valuation of the fuel economy increases required by
regulation may adjust over time towards the full lifetime discounted
present value. In addition, behavioral economic theory accepts that
consumers' willingness to pay for fuel economy may change depending on
the context of consumers' car purchase decisions. The implications of
such possibilities are analyzed below. We are interested in
[[Page 49730]]
how they might affect our current methods for estimate the impacts of
standards on new vehicle sales and the used vehicle market, and whether
any changes to our current methods are appropriate.
The existence of fuel economy standards changes manufacturers'
decision making. First, if a standard is set at a level that requires
only part of the technological potential to increase fuel economy, if C
< WTPHP, and WTPHP > WTP30FE, the
remainder of the technology's potential will be used to provide some
increase in performance. This appears to have occurred post 2004 when
the rate of improvement in performance slowed while fuel economy
improved. Assuming that consumers value fuel economy improvement at
time of purchase at WTP30FE, there would be a consumers'
surplus cost of foregone performance equal to the cross-hatched
trapezoid in Figure III-23. The foregone performance cost will be less
than what it would have been if none of the technology's potential to
increase fuel economy were used to increase performance. Even if the
cost of the technology is less than WTP30FE, the technology
will be applied to improve fuel economy only up to the required level
and the remainder of its potential will be used to increase
performance. If the cost of applying enough of the technology to
achieve the fuel economy standard is greater than WTPHP,
there would be no cost of foregone performance since the cost of
applying the technology to increasing fuel economy exceeds its
opportunity cost when applied to increase performance.\345\ In that
case, the technology cost represents the full cost of the fuel economy
improvement, since that cost exceeds consumers' WTP for the performance
it could produce. On the other hand, if under regulatory standards
consumers valued fuel economy at WTPPVFE, there would also
be no opportunity cost of performance because WTPPVFE >
WTPHP.
---------------------------------------------------------------------------
\345\ This is because using the technology to increase
performance would not be the second-best use of the cost of
increasing fuel economy. The second-best use would instead be to
invest the cost at a market rate of return.
[GRAPHIC] [TIFF OMITTED] TP03SE21.094
Because the CAFE Model estimates the effects of standards on new
vehicle sales and scrappage based on the difference between the cost of
technology and the perceived value of fuel savings at the time a new
vehicle is purchased, whether consumers perceive the value differently
in regulated and unregulated markets is an important question.
Traditional utility theory of consumer decision making does not allow
that consumers' preference rankings depend on the context of the
choices they make. However, in addition to the theory of utility
maximizing rational economic behavior, modern economics includes the
insights and findings of behavioral economics, which has established
many examples of human decision making that differ in important ways
from the rational economic model. In particular, the behavioral model
allows the possibility that consumers' preferences and decision-making
processes often do change depending on the context or framing of
choices. The possibility that behavioral theories of decision making
may be useful for understanding how consumers value fuel economy and
for evaluating the costs and benefits of fuel economy standards was
noted in the most recent NASEM (2021) report. An explanation of the
different contexts helps to illustrate this point. If a consumer is
thinking about buying a new car and is looking at two models, one that
includes fuel economy technology and is more expensive and another that
does not, she may buy the cheaper, less fuel efficient version even if
the more expensive model will save
[[Page 49731]]
money in the long run. But if, instead, the consumer is faced with
whether to buy a new car at all as opposed to keeping an older one, if
all new cars contain technology to meet fuel economy standards then she
may view the decision differently. Will, for example, an extra $1,000
for a new car--a $1,000 that the consumer will more than recoup in fuel
savings--deter her from buying the new car, especially when most
consumers finance cars over a number of years rather than paying the
$1,000 cost up front and will therefore partly or entirely offset any
increase in monthly payment with lower fuel costs? In addition, the
fact that standards generally increase gradually over a period of years
allows time for consumers and other information sources to verify that
fuel savings are real and of substantial value.
The CAFE Model's representation of consumers' vehicle choices under
regulation reflects the ``Gruenspecht Effect'', the theory that
regulation will inevitably cause new vehicles to be less desirable than
they would have been in the absence of regulation, which will
inevitably lead to reduced new vehicle sales, higher prices for used
vehicles and slower turnover of the vehicle stock. However, if
consumers severely undervalue fuel savings at the time of vehicle
purchase, not only is that itself a market failure (a large discrepancy
between decision and experienced utility) but it raises important
questions about what causes such undervaluation and whether consumers'
perceptions may change as the benefits of increased fuel economy are
realized or whether the different framing of new vehicle choices in a
regulated market might partially or entirely mitigate that
undervaluation. The 2021 NASEM report asserts that if the behavioral
model is correct, consumers might value fuel savings at or near their
full lifetime discounted present value, potentially reversing the
Gruenspecht Effect.
``On the other hand, the Gruenspecht effect is not predicted by the
behavioral model, under which it is not only possible but likely that
if the fuel savings from increased fuel economy exceed its cost,
consumers will find the more fuel-efficient vehicles required by
regulation to be preferable to those that would otherwise have been
produced.'' ``It is possible that sales would increase rather than
decrease and likewise manufacturers' profits. In that case, increased
new vehicle sales would reduce used vehicle prices, benefiting buyers
of used vehicles and accelerating the turnover of the vehicle stock.''
\346\
---------------------------------------------------------------------------
\346\ NASEM, 2021, p. 11-357.
---------------------------------------------------------------------------
NHTSA is interested in comments that can help contribute to
resolving or improving our understanding of this issue and its
implications for how the costs and benefits of fuel economy standards
should be estimated.
(2) Refueling Benefit
Increasing CAFE standards, all else being equal, affect the amount
of time drivers spend refueling their vehicles in several ways. First,
they increase the fuel economy of ICE vehicles produced in the future,
which increases vehicle range and decreases the number of refueling
events for those vehicles. 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
which require more refueling events for the same amount of VMT driven.
Finally, sufficiently stringent standards may also change the number of
electric vehicles that are produced, and shift refueling to occur at a
charging station, rather than at the pump--changing per-vehicle
lifetime expected refueling costs.
The agency estimates these savings by calculating the amount of
refueling time avoided--including the time it takes to find, refuel,
and pay--and multiplying it by DOT's value of time of travel savings
estimate. For a full description of the methodology, refer to TSD
Chapter 6.1.4.
(3) Additional Mobility
Any increase in travel demand provides benefits that reflect the
value to drivers and other vehicle occupants of the added--or more
desirable--social and economic opportunities that become accessible
with additional travel. Under the alternatives in this analysis, the
fuel cost per mile of driving would decrease as a consequence of the
higher fuel economy levels they require, thus increasing the number of
miles that buyers of new cars and light trucks would drive as a
consequence of the well-documented fuel economy rebound effect.
The fact that drivers and their passengers elect to make more
frequent or longer trips to gain access to these opportunities when the
cost of driving declines demonstrates that the benefits they gain by
doing so exceed the costs they incur. At a minimum, the benefits must
equal the cost of the fuel consumed to travel the additional miles (or
they would not have occurred). The cost of that energy is subsumed in
the simulated fuel expenditures, so it is necessary to account for the
benefits associated with those miles traveled here. But the benefits
must 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 that occurs with
additional travel. The amount by which the benefits of this additional
travel exceeds its economic costs measures the net benefits drivers and
their passengers experience, usually referred to as increased consumer
surplus.
TSD Chapter 6.1.5 explains the agency's methodology for calculating
additional mobility.
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 impacts on other system users, just as they do not fully value
the emissions impacts of their own driving. Congestion and noise costs
are ``external'' to the vehicle owners whose decisions about how much,
where, and when to drive more--or less--in response to changes in fuel
economy result in these costs. Therefore, 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 rule's economic impact on
the broader society instead of as a cost or benefit 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 a cost to the society as a whole.
To estimate the economic costs associated with changes in
congestion and noise caused by differences in miles driven, the agency
updated the underlying components of the cost estimates of per-mile
congestion and noise costs from increased automobile and light truck
use provided in FHWA's 1997 Highway Cost Allocation Study. The agencies
previously relied on this study in the 2010, 2011, and 2012 final
rules, and updating the individual underlying components for congestion
[[Page 49732]]
costs in this analysis improves currency and internal consistency with
the rest of the analysis. See TSD Chapter 6.2 for details on how the
agency calculated estimate 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 III.G.1.b)(1), a portion of the fuel savings
experienced by consumers includes avoided fuel taxes. While fuel taxes
are treated as a transfer within the analysis and do not affect net
benefits, the agency provides an estimate here to show the potential
impact to state and local governments.
(b) Benefits
(1) Reduced Climate Damages
Extracting and transporting crude petroleum, refining it to produce
transportation fuels, and distributing fuel generate additional
emissions of GHGs and criteria air pollutants beyond those from cars'
and light trucks' use of fuel. By reducing the volume of petroleum-
based fuel produced and consumed, adopting higher CAFE 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.--and global, in the case of
climate damages--population, reducing them represents an external
benefit from requiring higher fuel economy.
NHTSA estimates the global social benefits of CO2,
CH4, and N2O emission reductions expected from
this proposed rule using the social cost of greenhouse gases (SC-GHG)
estimates presented in the Technical Support Document: Social Cost of
Carbon, Methane, and Nitrous Oxide Interim Estimates under Executive
Order 13990 (``February 2021 TSD''). These SC-GHG estimates are interim
values developed under Executive Order (E.O.) 13990 for use in benefit-
cost analyses until updated estimates of the impacts of climate change
can be developed based on the best available science and economics.
NHTSA uses the SC-GHG interim values to estimate the benefits of
decreased fuel consumption stemming from the proposal.
The SC-GHG estimates used in our analysis were developed over many
years, using transparent process, peer-reviewed methodologies, the best
science available at the time of that process, and with input from the
public. Specifically, in 2009, an interagency working group (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 social cost of carbon dioxide
(SC-CO2) values used across agencies. The IWG published SC-
CO2 estimates in 2010. These estimates were updated in 2013
based on new versions of each IAM. In August 2016 the IWG published
estimates of the social cost of methane (SC-CH4) and nitrous
oxide (SC-N2O) using methodologies that are consistent with
the methodology underlying the SC-CO2 estimates. Executive
Order 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, and
intergenerational equity''.\347\ The E.O. also instructed the IWG to
take into account the recommendations from the NAS committee convened
on this topic, published in 2017.\348\ The February 2021 TSD provides a
complete discussion of the IWG's initial review conducted under E.O.
13990.
---------------------------------------------------------------------------
\347\ Executive Order on Protecting Public Health and the
Environment and Restoring Science to Tackle the Climate Crisis.
(2021). Available at https://www.whitehouse.gov/briefing-room/presidential-actions/2021/01/20/executive-order-protecting-public-health-and-environment-and-restoring-science-to-tackle-climate-crisis/.
\348\ National Academies of Science (NAS). (2017). Valuing
Climate Damage: Updating Estimation of the Social Cost of Carbon
Dioxide. Available at https://www.nap.edu/catalog/24651/valuing-climate-damages-updating-estimation-of-the-social-cost-of.
---------------------------------------------------------------------------
NHTSA is using the IWG's interim values, published in February 2021
in a technical support document, for the CAFE analysis in this
NPRM.\349\ This approach is the same as that taken in DOT regulatory
analyses over 2009 through 2016. If the IWG issues new estimates before
the final rule, the agency 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.
---------------------------------------------------------------------------
\349\ Interagency Working Group on Social Cost of Greenhouse
Gases, United States Government. (2021). Technical Support Document:
Social Cost of Carbon, Methane, and Nitrous Oxide Interim Estimates
under Executive Order 13990, available at https://www.whitehouse.gov/wp-content/uploads/2021/02/TechnicalSupportDocument_SocialCostofCarbonMethaneNitrousOxide.pdf?source=email.
---------------------------------------------------------------------------
NHTSA notes that the primary analysis for this proposal estimates
benefits from reducing emissions of CO2 and other GHGs that
incorporate a 2.5% discount rate for distant future climate damages,
while discounting costs and non-climate related benefits using a 3%
rate. NHTSA also presents cost and benefits estimates in the primary
analysis that reflect a 3% discount rate for reductions in climate-
related damages while discounting costs and non-climate related
benefits at 7%. NHTSA believes this approach represents an appropriate
treatment of the intergenerational issues presented by emissions that
result in climate-related damages over a very-long time horizon, and is
within scope of the IWG's Technical Support Document: Social Cost of
Carbon, Methane, and Nitrous Oxide that recommends discounting future
climate damages at rates of 2.5%, 3%, and 5%.\350\
---------------------------------------------------------------------------
\350\ Interagency Working Group on Social Cost of Greenhouse
Gases, United States Government, Technical Support Document: Social
Cost of Carbon, Methane, and Nitrous Oxide, Interim Estimates under
Executive Order 13990, February 2021.
---------------------------------------------------------------------------
In addition, NHTSA emphasize the importance and value of
considering the benefits calculated using all four SC-GHG estimates for
each of three greenhouse gases. NHTSA includes the social costs of
CO2, CH4, and N2O calculated using the
four different estimates recommended in the February 2021 TSD (model
average at 2.5 percent, 3 percent, and 5 percent discount rates; 95th
percentile at 3 percent discount rate) in the PRIA.
The February 2021 TSD does not specify 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. Instead, it
provides agencies with broad flexibility in implementing the February
2021 TSD. However, the February 2021 TSD does identify 2.5% as the
``average certainty-equivalent rate using the mean-reverting and random
walk approaches from Newell and Pizer (2003) starting at a discount
rate of 3 percent.'' \351\ As such, NHTSA believes using a 2.5%
discount rate for climate-related damages is consistent with the IWG
guidance.
---------------------------------------------------------------------------
\351\ Ibid.
---------------------------------------------------------------------------
This section provides further discussion of the discount rates that
NHTSA uses in its regulatory analysis
[[Page 49733]]
and presents results of a sensitivity analysis using a 3% discount rate
for reductions in climate-related damages. NHTSA welcomes public
comment on its selection of 2.5% for climate-related damages and will
consider other discount rates for the final rule.
For a full discussion of the agency's quantification of GHGs, see
TSD Chapter 6.2.1 and the PRIA.
(a) Discount Rates Accounting for Intergenerational Impacts
A standard function of regulatory analysis is to evaluate tradeoffs
between impacts that occur at different points in time. Many, if not
most, 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.\352\ This is accomplished by
discounting impacts that occur further in the future more than impacts
that occur sooner.
---------------------------------------------------------------------------
\352\ This preference is observed in many market transactions,
including by savers that expect a return on their investments in
stocks, bonds, and other equities; firms that expect positive rates
of return on major capital investments; and banks that demand
positive interest rates in lending markets.
---------------------------------------------------------------------------
OMB Circular A-4 affirmed the appropriateness of accounting for the
social rate of time preference in regulatory analyses and prescribed
discount rates of 3% and 7% for doing so. The 3% discount rate 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 deferred to the future.
OMB Circular A-4 reports a real rate of return on 10-year Treasury
notes of 3.1% 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% rate reflects the opportunity cost of capital approach to
discounting, where the discount rate approximates the foregone return
on private investment if the regulation were to divert resources from
capital formation. OMB Circular A-4 cites pre-tax rates of return on
capital as part of its selection of the 7% rate.\353\ The IWG rejected
the use of the opportunity cost of capital approach to discounting
reductions in climate-related damages because ``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 IAMs used to estimate the SC-GHG (National
Academies 2017).'' \354\
---------------------------------------------------------------------------
\353\ OMB Circular A-4.
\354\ Interagency Working Group on Social Cost of Greenhouse
Gases, United States Government, Technical Support Document: Social
Cost of Carbon, Methane, and Nitrous Oxide, Interim Estimates under
Executive Order 13990, February 2021.
---------------------------------------------------------------------------
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 greenhouse gas under consideration.''\355\ OMB Circular A-
4 states that impacts occurring over such intergenerational time
horizons require special treatment:
---------------------------------------------------------------------------
\355\ Ibid.
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.\356\
---------------------------------------------------------------------------
\356\ OMB Circular A-4.
In addition to the ethical considerations, Circular A-4 also
identifies uncertainty in long-run interest rates as a potential
justification for using lower rates to discount intergenerational
impacts. As Circular A-4 states, ``Private 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.''\357\ 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 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% 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% discount rate. The
effect of such uncertainty about the correct discount rate can thus be
accounted for by using a lower ``certainty-equivalent'' rate to
discount distant future damages.
---------------------------------------------------------------------------
\357\ Ibid.
---------------------------------------------------------------------------
The IWG identifies ``a plausible range of certainty-equivalent
constant consumption discount rates: 2.5, 3, and 5 percent per year.''
The IWG's justification for its selection of these rates is summarized
in this excerpt from its 2021 guidance:
The 3 percent value was included as consistent with estimates
provided in OMB's Circular A-4 (OMB 2003) guidance for the consumption
rate of interest. . . .The upper value of 5 percent was included to
represent the possibility that climate-related damages are positively
correlated with market returns, which would imply a certainty
equivalent value higher than the consumption rate of interest. The low
value, 2.5 percent, was included to incorporate the concern that
interest rates are highly uncertain over time. It represents the
average certainty-equivalent rate using the mean-reverting and random
walk approaches from Newell and Pizer (2003) starting at a discount
rate of 3 percent. Using this approach, the certainty equivalent is
about 2.2 percent using the random walk model and 2.8 percent using the
mean reverting approach. Without giving preference to a particular
model, the average of the two rates is 2.5 percent. Additionally, a
rate below the consumption rate of interest would also be justified if
the return to investments in climate mitigation are negatively
correlated with the overall market rate of return. Use of this lower
value was also deemed responsive to certain judgments based on the
prescriptive or normative approach for selecting a discount rate and to
related ethical objections that have been raised about rates of 3
percent or higher.
Because the certainty-equivalent discount rate will lie
progressively farther below the best estimate of the current rate as
the time horizon when future impacts occur is extended, the IWG's
recent guidance also suggest that it may be appropriate to use a
discount rate that declines over time to account for interest rate
uncertainty, as has been recommended by the National Academies and
EPA's Science Advisory Board.\358\ The IWG mentioned that it will
consider these recommendations and the relevant academic literature on
declining rates in developing its final
[[Page 49734]]
guidance on the social cost of greenhouse gases.
---------------------------------------------------------------------------
\358\ Interagency Working Group on Social Cost of Greenhouse
Gases, United States Government, Technical Support Document: Social
Cost of Carbon, Methane, and Nitrous Oxide, Interim Estimates under
Executive Order 13990, February 2021.
---------------------------------------------------------------------------
The IWG 2021 interim guidance also presented new evidence on the
consumption-based discount rate suggesting that a rate lower than 3%
may be appropriate. For example, the IWG replicated OMB Circular A-4's
original 2003 methodology for estimating the consumption rate using the
average return on 10-year Treasury notes over the last 30 years and
found a discount rate close to 2%. They also presented rates over a
longer time horizon, finding an average rate of 2.3% from 1962 to the
present. Finally, they summarized results from surveys of experts on
the topic and found a ``surprising degree of consensus'' for using a 2%
consumption rate of interest to discount future climate-related
impacts.\359\
---------------------------------------------------------------------------
\359\ Ibid.
---------------------------------------------------------------------------
NHTSA expects that the Interagency Working Group will continue to
develop its final guidance on the appropriate discount rates to use for
reductions in climate damages as NHTSA develops its final rule. If new
guidance is issued in time for NHTSA's final rule, NHTSA will
incorporate the IWG's updated guidance in the final regulatory
analysis.
(b) Discount Rates Used in This Proposal for Climate-Related Benefits
As indicated above, NHTSA's primary analysis presents cost and
benefit estimates using a 2.5% discount rate for reductions in climate-
related damages and 3% for non-climate related impacts. NHTSA also
presents cost and benefits estimates using a 3% discount rate for
reductions in climate-related damages alongside estimates of non-
climate related impacts discounted at 7%. This latter pairing of a 3%
rate for discounting benefits from reducing climate-related damages
with a 7% discount rate for non-climate related impacts is consistent
with NHTSA's past practice.\360\ However, NHTSA's pairing of 2.5% for
climate-related damage reductions with 3% for non-climate related
impacts is novel in this proposal.
---------------------------------------------------------------------------
\360\ See, e.g., the 2012 and 2020 final CAFE rules.
---------------------------------------------------------------------------
As discussed above, the IWG's guidance indicates that uncertainty
in long-run interest rates suggests that a lower ``certainty-
equivalent'' discount rate is appropriate for intergenerational
impacts, and identifies 2.5%, 3%, and 5% as ``certainty-equivalent''
discount rates. NHTSA emphasizes the importance and value of
considering the benefits calculated using all four SC-GHG estimates for
each of three greenhouse gases. NHTSA includes the social costs of
CO2, CH4, and N2O calculated using the
four different estimates recommended in the February 2021 TSD (model
average at 2.5 percent, 3 percent, and 5 percent discount rates; 95th
percentile at 3 percent discount rate) in the PRIA. For presentation
purposes in this rule, NHTSA shows two primary estimates. NHTSA
believes that pairing OMB's 3% estimate of the consumption discount
rate for near-term costs and benefits with the IWG's lower certainty-
equivalent rate of 2.5% is consistent with current interim guidance in
the February 2021 TSD. NHTSA also believe that its pairing of the 3%
certainty-equivalent rate for climate-related benefits with OMB's 7%
discount rate is consistent with guidance from the February 2021 TSD
for GHGs and OMB Circular A-4 for other costs and benefits.
In addition, NHTSA presents a sensitivity analysis where both
distant future and nearer-term GHG impacts are discounted using the 3%
rate combined with all other costs and benefits discounted at 3%.
[GRAPHIC] [TIFF OMITTED] TP03SE21.095
[GRAPHIC] [TIFF OMITTED] TP03SE21.096
[[Page 49735]]
NHTSA seeks comment on the above discussion.
(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 III.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 to human health, and there exist several papers from the EPA
estimating the benefits per ton 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 benefit-per-ton estimates for
these. The CAFE Model computes the monetized impacts associated with
health damages from each pollutant by multiplying monetized health
impact per ton values by the total tons of these pollutants, which are
emitted from both upstream and tailpipe sources. Chapter 5 of the TSD
accompanying this proposal includes a detailed description of the
emission factors that inform the CAFE Model's calculation of the total
tons of each pollutant associated with upstream and tailpipe emissions.
These monetized health impacts per ton values are closely related
to the health incidence per ton values described above in Section III.F
and in detail in Chapter 5.4 of the 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, based on which papers contained the most up-to-date data.\361\
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.\362\ In those cases, we mapped multiple EPA sectors to a
single CAFE source category and computed a weighted average of the
health impact per ton values.
---------------------------------------------------------------------------
\361\ Environmental Protection Agency (EPA). 2018. Estimating
the Benefit per Ton of Reducing PM2.5 Precursors from 17
Sectors. https://www.epa.gov/sites/production/files/2018-02/documents/sourceapportionmentbpttsd_2018.pdf; Wolfe et al. 2019.
Monetized health benefits attributable to mobile source emissions
reductions across the United States in 2025. https://pubmed.ncbi.nlm.nih.gov/30296769/; Fann et al. 2018. Assessing Human
Health PM2.5 and Ozone Impacts from U.S. Oil and Natural
Gas Sector Emissions in 2025. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6718951/.
\362\ The CAFE Model's emission source sectors follow a similar
structure to the inputs from GREET. See Chapter 5.2 of the TSD
accompanying this proposal for further information.
---------------------------------------------------------------------------
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.\363\ EPA's 2018 technical support document,
``Estimating the Benefit per Ton of Reducing PM2.5
Precursors from 17 Sectors,'' \364\ (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, not avoided, unless the context
states otherwise.
---------------------------------------------------------------------------
\363\ Although EPA and DOT's VSL values differ, DOT staff
determined that using EPA's VSL was appropriate here, since it was
already included in these monetized health impact values, which were
best suited for the purposes of the CAFE Model.
\364\ See Environmental Protection Agency (EPA). 2018.
Estimating the Benefit per Ton of Reducing PM2.5
Precursors from 17 Sectors. https://www.epa.gov/sites/production/files/2018-02/documents/sourceapportionmentbpttsd_2018.pdf.
---------------------------------------------------------------------------
The CAFE Model health impacts inputs are based partially on the
structure 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 instance, the
model applies 2020 monetized health impact per ton values for calendar
years 2020-2022 and applies 2025 values for calendar years 2023-2027.
For some of the monetized health damage values, in order 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 2018 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
TSD accompanying this proposal. In addition, the CAFE Model
documentation contains more details of the model's computation of
monetized health impacts. 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 Externality
By amending existing standards, the proposal would decrease
domestic consumption of gasoline, producing a correspondingly decrease
in the Nation's demand for crude petroleum, a commodity that is traded
actively in a worldwide market. Although the U.S. accounts for a
sufficient (albeit diminishing) share of global oil consumption that
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 social costs of
increased U.S. demand for petroleum. 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. Although this transfer
is simply a shift of resources that produces no change in global
economic welfare, the financial drain it produces on the U.S. economy
is sometimes cited as an external cost of increased U.S. petroleum
consumption because consumers of petroleum products are unlikely to
consider it.
As the U.S. approaches 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, as
the U.S. becomes a larger net petroleum exporter, any transfer from
global consumers to petroleum producers would become 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
[[Page 49736]]
change in response to increased consumption.
Higher U.S. petroleum consumption can also increase domestic
consumers' exposure to oil price shocks and thus increase potential
costs to all U.S. petroleum users (including those outside the light
duty vehicle sector, 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.
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 to represent a
third category of external costs form increased U.S. petroleum
consumption. For example, NHTSA has received extensive comments to past
actions from the group Securing America's Energy Future on this topic.
Each of these three factors would be expected to decrease--albeit
by a limited magnitude--as a consequence of decrease in U.S. petroleum
consumption resulting from the proposed standards. TSD Chapter 6.2.4
provides a comprehensive explanation of the agency's analysis of these
three impacts.
(4) Changes in Labor
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, manufacturers may need
less labor to produce their fleet and 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.\365\ 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 impacts the quantity of estimated labor.
---------------------------------------------------------------------------
\365\ For the purposes of this analysis, DOT assumes a linear
relationship between labor and production volumes.
---------------------------------------------------------------------------
The analysis considers the direct labor effects that the CAFE
standards have across the automotive sector. The facets include (1)
dealership labor related to new light-duty vehicle 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. The labor
utilization analysis is intentionally narrow in its focus and does not
represent an attempt to quantify the overall labor or economic effects
of this rulemaking because adjacent employment factors and consumer
spending factors for other goods and services are uncertain and
difficult to predict. We do not consider how direct labor changes may
affect the macro economy and potentially change employment in adjacent
industries. For instance, we do not consider possible labor changes in
vehicle maintenance and repair, nor changes in labor at retail gas
stations. We also do not consider possible labor changes due to raw
material production, such as production of aluminum, steel, copper, and
lithium, nor does the agency consider possible labor impacts due to
changes in production of oil and gas, ethanol, and electricity.
All labor effects are estimated and reported at a national level,
in person-years, assuming 2,000 hours of labor per person-year.\366\
These labor hours are not converted into 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 2020 fleet. The agency 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.\367\ The analysis assumes the portion of parts
that are made in the U.S. will remain constant for each vehicle as
manufacturers add fuel-savings technologies. This should not be
misconstrued as a prediction that the percentage of U.S.-made parts--
and by extension U.S. labor--will remain constant, but rather that the
agency does not have a clear basis to project where future productions
may shift. The analysis also uses data from the National Automotive
Dealers Association (NADA) annual report to derive dealership labor
estimates.
---------------------------------------------------------------------------
\366\ The agencies recognize a few local production facilities
may contribute meaningfully to local economies, but the analysis
reports only on national effects.
\367\ 49 CFR part 583.
---------------------------------------------------------------------------
In sum, the analysis shows that the increased labor from production
of new technologies used to meet the preferred alternative will
outweigh any decreases attributable to the change in new vehicle sales.
For a full description of the process the agency uses to estimate labor
impacts, see TSD Chapter 6.2.5.
3. Costs and Benefits Not Quantified
In addition to the costs and benefits described above, Table III-37
and Table III-38 each include two line-items without values. The first
is maintenance and repair costs. Many of the technologies manufacturers
apply to vehicles to meet CAFE 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--which is likely either because the
materials used to produce the equipment are more expensive or the
equipment is significantly more complex than less fuel efficient
alternatives and requires more time and labor--then consumers will also
experience increased costs throughout the lifetime of the vehicle to
keep it operational. The agency does not calculate the additional cost
of repair and maintenance currently because it lacks a basis for
estimating the incremental change attributable to the standards. The
agency seeks comment on methods for estimating these costs.
The second item is the potential sacrifice in other vehicle
attributes. In addition to fuel economy, potential buyers of new cars
and light trucks value other features such as their seating and cargo-
carrying capacity, ride comfort, safety, and performance. Changing some
of these other features, however, can affect vehicles' fuel economy, so
manufacturers will carefully consider tradeoffs among them when
deciding how to comply with stricter CAFE standards. Currently the
analysis assumes that these vehicle attributes will not change as a
result of these rules,\368\ but in practice manufacturers may need to
make practical design changes to meet the standards. Even if
manufacturers are able to hold vehicles' other attributes at today's
levels while meeting higher fuel economy targets, manufacturers may
have to dedicate additional resources to comply with stricter CAFE
targets and forego improvements in other vehicle attributes. The
potential loss of other
[[Page 49737]]
vehicle attributes is an opportunity cost to consumers.
---------------------------------------------------------------------------
\368\ See TSD Chapter 2.4.5.
---------------------------------------------------------------------------
The agency has previously attempted to model the potential
sacrifice in other vehicle attributes in sensitivity analyses. In those
other rulemakings, the agency acknowledged that it is extremely
difficult to quantify the potential loss of other vehicle attributes.
To accurately do so requires extensive projections about which and how
much of other attributes will be sacrificed and a detailed accounting
of how much value consumers assigned to those attributes. The agency
modeled the loss 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 is unsure whether this is an
appropriate methodology since there is uncertainty about how much fuel
economy consumers are willing to pay for and how consumers value other
vehicle attributes. The agency seeks comment on alternative methods for
estimating the potential sacrifice in other vehicle attributes.
H. Simulating Safety Effects of Regulatory Alternatives
The primary objective of CAFE standards is to achieve maximum
feasible fuel economy, thereby reducing fuel consumption. In setting
standards to achieve this intended effect, the potential of the
standards to affect vehicle safety is also considered. As a safety
agency, the agency has long considered the potential for adverse safety
consequences when establishing CAFE standards.
This safety analysis includes the comprehensive measure of safety
impacts from three factors:
1. Changes in Vehicle Mass. Similar to previous analyses, the
agency calculates the safety impact of changes in vehicle mass made to
reduce fuel consumption and comply with the standards. Statistical
analysis of historical crash data indicates reducing mass in heavier
vehicles generally improves safety, while reducing mass in lighter
vehicles generally reduces safety. The agency'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.
2. Impacts of Vehicle Prices on Fleet Turnover. Vehicles have
become safer over time through a combination of new safety regulations
and voluntary safety improvements. The agency 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 to CAFE standards.
As discussed in Section III.E.2, technologies added to comply with
fuel economy 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 light-duty
fleet. As the safety provided by light trucks, SUVs and passenger cars
responds differently to technology that manufacturers employ to meet
the standards--particularly mass reduction--fleets with different
compositions of body styles will have varying numbers of fatalities, so
changing the share of each type of light-duty vehicle in the projected
future fleet impacts safety outcomes.
3. 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.
The contributions of the three factors described above generate the
differences in safety outcomes among regulatory alternatives.\369\ The
agency'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 value of a statistical
life (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.
---------------------------------------------------------------------------
\369\ The terms safety performance and safety outcome are
related but represent different concepts. When we use the term
safety performance, we are discussing the intrinsic safety of a
vehicle based on its design and features, while safety outcome is
used to describe whether a vehicle has been involved in an accident
and the severity of the accident. While safety performance
influences safety outcomes, other factors such as environmental and
behavioral characteristics also play a significant role.
---------------------------------------------------------------------------
All three factors influence predicted fatalities, but only two of
them--changes in vehicle mass and in the composition of the light-duty
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 benefit 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 accompanying
Technical Support Document, the benefits of rebound driving are
accounted for by offsetting a portion of the added safety costs.
The agency categorizes safety outcome through three measures of
light-duty vehicle safety: Fatalities to occupants occurring in
crashes, serious injuries sustained by occupants, and the number of
vehicles involved in crashes that cause property damage but no
injuries. Counts of fatalities to occupants of automobiles and light
trucks are obtained from the agency's Fatal Accident Reporting System
(FARS). Estimates of the number of serious injuries to drivers and
passengers of light-duty vehicles are tabulated from the agency's
General Estimates System (GES), an annual sampling of motor vehicle
crashes occurring throughout the U.S. 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 and light trucks involved in
property damage-only (PDO) crashes each year were also developed using
GES. NHTSA seeks comment on the following discussion.
1. Mass Reduction Impacts
Vehicle mass reduction can be one of the more cost-effective means
of improving fuel economy, 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 vehicle
[[Page 49738]]
mass to meet more stringent standards, and therefore, this expectation
is incorporated into the modeling analysis supporting the standards.
Safety trade-offs associated with mass-reduction have occurred in the
past, particularly before CAFE standards were attribute-based; past
safety trade-offs may have occurred because manufacturers chose at the
time, in response to CAFE standards, to build smaller and lighter
vehicles. In cases where fuel economy improvements were achieved
through reductions in vehicle size and mass, the smaller, lighter
vehicles did not fare as well in crashes as larger, heavier vehicles,
on average. Although The agency now uses attribute-based standards, in
part to reduce or eliminate the incentive to downsize vehicles to
comply with CAFE standards, the agency must be mindful of the
possibility of related safety trade-offs.
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.\370\ The agency utilized the relationships between
weight and safety from this analysis, expressed as percentage increases
in fatalities per 100-pound weight reduction (which is how mass
reduction is applied in the technology analysis; see Section III.D.4),
to examine the weight impacts applied in this CAFE analysis. The
effects of mass reduction on safety were estimated relative to
(incremental to) the regulatory baseline in the CAFE analysis, across
all vehicles for MY 2021 and beyond.
---------------------------------------------------------------------------
\370\ Puckett, S.M. and Kindelberger, J.C. (2016, June).
Relationships between Fatality Risk, Mass, and Footprint in Model
Year 2003-2010 Passenger Cars and LTVs--Preliminary Report. (Docket
No. 2016-0068). Washington, DC: National Highway Traffic Safety
Administration.
---------------------------------------------------------------------------
In computing the impact of changes in mass on safety, the agency is
faced with competing challenges. Research has consistently shown that
mass reduction affects ``lighter'' and ``heavier'' vehicles differently
across crash types. The 2016 Puckett and Kindelberger report found mass
reduction concentrated among the heaviest vehicles is likely to have a
beneficial effect on overall societal fatalities, while mass reduction
concentrated among the lightest vehicles is likely to have a
detrimental effect on fatalities. 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. Mass reduction in heavier vehicles is more
beneficial to the occupants of lighter vehicles than it is harmful to
the occupants of the heavier vehicles. Mass reduction 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, the agency 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 the agency 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.
Comments on the NPRM (83 FR 42986, August 24, 2018) for the 2020
CAFE rule included suggestions that the sample of LTVs in the analysis
should not include the medium- or heavy-duty (i.e., truck-based
vehicles with GVWR above 8,500 pounds) equivalents of light-duty
vehicles in the sample (e.g., Ford F-250 versus F-150, RAM 2500 versus
RAM 1500, Chevrolet Suburban 2500 versus Chevrolet Suburban 1500), or
Class 2b and 3 vehicles. For the proposal, NHTSA explored revising the
analysis consistent with such comments. The process involved two key
analytical steps: (1) Removing all case vehicles from the analysis
whose GVWR exceeded 8,500 pounds; and (2) re-classifying all crash
partners with GVWR above 8,500 pounds as heavy vehicles. The direct
effects of these changes are: (1) The range of curb weights in the LTV
sample is reduced, lowering the median curb weight from 5,014 pounds to
4,808 pounds; (2) the sample size of LTVs is reduced (the number of
case LTVs under this alternative specification is approximately 18
percent lower than in the central analysis); and (3) the relative
impact of crashes with LTVs on overall impacts on societal fatality
rates decreases, while the corresponding impact of crashes with heavy
vehicles increases.
The results from the exploratory analysis of this alternative
approach are provided in Table III-41. The agency seeks comment on this
alternative approach; public comment will inform the decision whether
to incorporate the results into the CAFE Model. The primary functional
change offered by the alternative approach is that the sample of
vehicles classified as LTVs would be restricted to vehicles that would
be subject to CAFE regulations. At the statistical level, the concerns
raised in the agency's response to comment on the 2018 CAFE NPRM
remain. In particular, including Class 2b and 3 vehicles in the
analysis to determine the relationship of vehicle mass on safety has
the added benefit of improving correlation constraints. Notably, curb
weight increases faster than footprint for large light trucks and Class
2b and 3 pickup trucks and SUVs, in part because the widths of vehicles
are constrained more tightly (i.e., due to lane widths) than their curb
weights. Including data from Class 2b and 3 pick-up truck and SUV fatal
crashes provides data over a wider range of vehicle weights, which
improves the ability to estimate the mass-crash fatality relationship.
That is, by extending the footprint-curb weight-fatality data to
include Class 2b and 3 trucks that are functionally and structurally
similar to corresponding \1/2\-ton models that are subject to CAFE
regulation, the sample size and ranges of curb weights and footprint
are improved. Sample size is a challenge for estimating relationships
between curb weight and fatality risk for individual crash types in the
main analysis; dividing the sample further or removing observations
makes it increasingly difficult to identify meaningful estimates and
the relationships that are present in the data, as shown in the
sensitivity analysis below. For the proposal, the agency has determined
that the benefit of the additional data points outweighs the concern
that some of the vehicles used to determine the mass-safety
coefficients are not regulated by CAFE vehicles.
The agency also explored three other alternative model
specifications that are presented in Table III-41. The first
alternative centers on aligning CUVs and minivans with the rest of the
sample, by splitting these vehicles into two weight classes. The key
factor restricting this change historically has been a low sample size
for these vehicles; the exploratory analysis examined whether the
current database (which, due to the range of CYs covered, contains a
smaller share of CUVs and
[[Page 49739]]
minivans than the current fleet) contains a sufficient sample size to
evaluate two weight classes for CUVs and minivans. A complicating
factor in this analysis is that minivans tend to have higher curb
weights than other CUVs, adding statistical burden in identifying
meaningful effects of mass on societal fatality rates after accounting
for body type in the weight class with the fewest minivans (i.e.,
lighter CUVs and minivans).
The second alternative centers on aligning passenger cars with the
rest of the sample by including cars that are equipped with all-wheel
drive (AWD). In previous analyses, passenger cars with AWD were
excluded from the analysis because they represented a sufficiently low
share of the vehicle fleet that statistical relationships between AWD
status and societal fatality risk were highly prone to being conflated
with other factors associated with AWD status (e.g., location, luxury
vehicle status). However, the share of AWD passenger cars in the fleet
has grown. Approximately one-quarter of the passenger cars in the
database have AWD, compared to an approximately five-percent share in
the MY 2000-2007 database. Furthermore, all other vehicle types in the
analysis include AWD as an explanatory variable. Thus, the agency finds
the inclusion of a considerable portion of the real-world fleet (i.e.,
passenger cars with AWD) to be a meaningful consideration.
The third alternative is a minor procedural question: Whether to
expand the CYs and MYs used to identify the distribution of fatalities
across crash types. The timing of the safety databases places the years
of the analysis used to establish the distribution of fatalities by
crash type firmly within the central years of the economic downturn of
the late 2000s and early 2010s. During these years, travel demand was
below long-term trends, resulting in fewer crashes. In turn, applying
the same window of CYs and MYs to the identification of the
distribution of fatalities across crash types results in notably fewer
crashes to incorporate into the analysis. The agency conducted
exploratory analysis on the question of whether to add CYs and MYs to
the range of crashes used to identify the distribution of fatalities
across crash types; this analysis was conducted in concert with the two
alternatives discussed directly above. Results incorporating these
three alternatives are presented in Table III-41.
[GRAPHIC] [TIFF OMITTED] TP03SE21.097
Under the alternative specification excluding Class 2b and Class 3
truck-based vehicles as case vehicles, the median curb weight for LTVs
is 4,808 pounds, or 206 pounds lighter than in the central analysis.
When splitting CUVs and minivans into two weight classes, the median
curb weight for the vehicles is 3,955 pounds. Under this alternative
specification, where Class 2b and Class 3 truck-based crash partners
are shifted from truck-based LTVs to heavy-duty vehicles, the median
curb weight for LTV crash partners is 4,216 pounds, or 144 pounds
lighter than in the central analysis.
Re-classifying Class 2b and Class 3 truck-based vehicles has a
strong effect on the point estimate for heavier LTVs. Critically,
removing the heaviest trucks as case vehicles yields a much smaller
point estimate (reduction in societal fatality rates of between 0.16%
and 0.17% per 100-pound mass reduction, versus 0.61% in the central
analysis). This result is consistent with a relationship where a key
share of the sensitivity of fatality risk is attributed to the mass of
the heaviest vehicles in the fleet (i.e., supporting the role of mass
dispersion in societal fatality rates). Importantly, the point estimate
for lighter LTVs is not meaningfully different from the corresponding
estimate in the central analysis (increase in societal fatality rates
of between 0.26% and 0.29% per 100-pound mass reduction, versus 0.3% in
the central analysis). Considered in concert, these results indicate
that the most effective reductions in societal fatality rates via mass
reduction in truck-based vehicles would arise not from lightweighting
the heaviest vehicles subject to CAFE
[[Page 49740]]
regulation, but rather from lightweighting similar, medium- and heavy-
duty vehicles.
Including passenger cars with AWD in the analysis has little effect
on the point estimate for lighter passenger cars (increase in societal
fatality rates of approximately 1.1% per 100-pound mass reduction,
versus 1.2% in the central analysis). However, this revision has a
strong effect on the point estimate for heavier passenger cars
(increase in societal fatality rates of between 0.84% and 0.89% per
100-pound mass reduction, versus 0.42% in the central analysis). This
result supports a hypothesis that, after taking AWD status into
account, mass reduction in heavier passenger cars is a more important
driver of societal fatality rates than previously estimated. Although
this result could be spurious, estimated confidence bounds (presented
below) indicate that accounting for AWD status reduces uncertainty in
the point estimate. The agency seeks comment on the inclusion of
passenger cars with AWD when estimating the effects of mass reduction
on societal fatality rates.
Splitting CUVs and minivans into two vehicle classes yields point
estimates that are consistent with the point estimate for the
consolidated CUV-minivan vehicle class (an average decrease in societal
fatality rates of approximately 0.16% to 0.18% per 100-pound mass
reduction across the two vehicle classes, versus a decrease of 0.25% in
the central analysis). However, sample sizes half as large in the two
vehicle classes relative to the consolidated vehicle class lead to very
large estimated confidence bounds, as shown below. Due to this
uncertainty, The agency does not feel that the current databases
contain a large enough sample of CUVs and minivans to split these
vehicles into two classes in the analysis; however, this issue will be
re-examined when the next iteration of the databases is complete.
Extending the range of CYs and MYs used to establish the
distribution of fatalities across crash types has a negligible effect
on the point estimates. Based on the narrow ranges of results in Table
III-41, The agency finds evidence supporting a flexible approach in the
choice of CYs and MYs used in this manner. All else being equal,
extending the range helps to mitigate the potential for individual
crash types with large estimated effects to drive spurious effects on
overall estimates through unrepresentatively high estimated shares of
overall fatalities. As a hedge in this direction, the agency applied
the estimates from the alternative specification with two additional
CYs and MYs (i.e., the second column from the right in Table III-41)
when evaluating 95-percent confidence bounds for the alternative models
considered here. The agency seeks comment on this approach to
representing the distribution of fatalities across crash types.
A more detailed description of the mass-safety analysis can be
found in Chapter 7 of the accompanying 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.\371\ 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. This occurs because there is diminishing value to marginal
improvements in fuel economy (there are fewer gallons to be saved), and
as the difference in consumption between light trucks and passenger
cars diminishes, the other attributes of the trucks will likely lead to
increases in their market share--especially under lower gas prices.
Light trucks have higher rates of fatal crashes when interacting with
passenger cars and, as earlier discussed, different directional
responses to mass reduction technology based on the existing mass and
body style of the vehicle.
---------------------------------------------------------------------------
\371\ See Passenger Vehicle Occupant Injury Severity by Vehicle
Age and Model Year in Fatal Crashes, Traffic Safety Facts Research
Note, DOT-HS-812-528, National Highway Traffic Safety
Administration, April, 2018, and The Relationship Between Passenger
Vehicle Occupant Injury Outcomes and Vehicle Age or Model Year in
Police-Reported Crashes, Traffic Safety Facts Research Note, DOT-HS-
812-937, National Highway Traffic Safety Administration, March,
2020.
---------------------------------------------------------------------------
Any effects on fleet turnover (either from delayed vehicle
retirement or deferred sales of new vehicles) will affect the
distribution of both ages and model years present in the on-road fleet.
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 dynamic
fleet share model captures the changes in the 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, the agency 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: The agency uses the distribution of miles calculated in
TSD Chapter 4.3. 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.
The agency calculates the fatality risk of a vehicle based on the
vehicle's model year, age, and style, while controlling for factors
which are independent of the intrinsic nature of the vehicle, such as
behavioral characteristics. Using this same approach, the agency
designed separate models for fatalities, non-fatal injuries, and
property damaged vehicles.
The fatality risk projections described above capture the
historical evolution of safety. Given that modern technologies are
proliferating faster than ever and offer greater safety benefits than
traditional safety improvements, the agency augmented the fatality risk
projections with knowledge about forthcoming safety improvements. The
agency applied detailed empirical 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.\372\
---------------------------------------------------------------------------
\372\ These technologies included Forward Collision Warning
(FCW), Crash Imminent Braking (CIB), Dynamic Brake Support (DBS),
Pedestrian AEB (PAEB), Rear Automatic Braking, Semi-automatic
Headlamp Beam Switching, Lane Departure Warning (LDW), Lane Keep
Assist (LKA), and Blind Spot Detection (BSD). While Autonomous
vehicles offer the possibility of significantly reducing or
eventually even eliminating the effect of human error in crash
causation, a contributing factor in roughly 94% of all crashes,
there is insufficient information and certainty regarding autonomous
vehicles eventual impact to include them in this analysis.
---------------------------------------------------------------------------
The agency's approach to measuring these impacts is to derive
effectiveness rates for these advanced crash-avoidance technologies
from safety technology literature. The agency then applies these
effectiveness rates to specific crash target populations for
[[Page 49741]]
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 6
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
projections of safety impacts from advanced technologies is included in
Chapter 7 of the accompanying TSD.
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, the agencies
believe 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 consumers 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 TSD Chapter 7.4.
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
value of a statistical life (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
2018 dollars, and updated to reflect the official DOT guidance on the
value of a statistical life. 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,
the agency applied a KABCO \373\/maximum abbreviated injury scale
(MAIS) translator to GES KABCO based injury counts from 2010 through
2015. This produced the MAIS based injury profile. This profile was
used to weight nonfatal injury unit costs derived from Blincoe et al.,
adjusted to 2018 economics and updated to reflect the official DOT
guidance on the value of a statistical life. Property-damaged vehicle
costs were also taken from Blincoe et al. and adjusted to 2018
economics. VSL does not affect property damage. This gives societal
values of $10.8 million for each fatality, $132,000 for each nonfatal
injury, and $7,100 for each property damaged vehicle.
---------------------------------------------------------------------------
\373\ The ``KABCO'' injury scale also can be used for
establishing crash costs. This scale was developed by the National
Safety Council (NSC) and is frequently used by law enforcement for
classifying injuries: K--Fatal; A--Incapacitating injury; B--Non-
incapacitating injury; C--Possible injury; and O--No injury.
---------------------------------------------------------------------------
5. Impacts of the Proposal on Safety
Table III-42 through Table III-44 summarize the safety impacts of
the proposed standards on safety broken down by factor. These impacts
are summarized over the lifetimes of model year 1981 through 2029
vehicles for all light passenger vehicles (including passenger cars and
light trucks). Economic impacts are shown separately under both 3% and
7% discount rates. Model years 1981 through 2029 were examined because
they represent the model years that might be affected by shifts in
fleet composition due to the impact of higher new vehicle prices on
sales of new vehicles and retention of older vehicles. Earlier years
will be affected by slower scrappage rates and we expect the impacts of
these standards will be fully realized in vehicle designs by MY 2029.
BILLING CODE 4910-59-P
[[Page 49742]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.098
[[Page 49743]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.099
[[Page 49744]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.100
BILLING CODE 4910-59-C
As seen in the tables, all three safety factors--changes in mass,
fleet turnover, and rebound--increase as the standards become more
stringent. As expected, rebound fatalities grow at a constant rate as
vehicles become more fuel efficient and are used more frequently. Mass
reduction has a relatively minimal impact on safety and diminishes as
stringency increases. This may point to either the fleet becoming more
homogeneous and hence less mass disparate in crashes. Alternatively,
the model may be capturing that there's little room for more mass
reductions in particular models. The slowing of fleet turnover due to
higher vehicle prices has the largest impact of the three factors and
accelerates with higher alternatives. Of course, if the agency's
assumptions overstate the rebound effect and/or slower fleet turnover,
fatalities, injuries and property damage would be lower, and vice
versa.
PRIA Chapter 5.5 discusses the results of the analysis in more
detail and PRIA Chapter 5.6--Safety Impacts provides an overview of
sensitivity analyses performed to isolate the uncertainty parameters of
each of the three safety impacts.
IV. Regulatory Alternatives Considered in this NPRM
A. Basis for Alternatives Considered
Agencies typically consider regulatory alternatives in proposals as
a way of evaluating the comparative effects of different potential ways
of accomplishing their desired goal. NEPA requires agencies to compare
the potential environmental impacts of their proposed actions to those
of a reasonable range of alternatives. Executive Orders 12866 and
13563, as well as OMB Circular A-4, also encourage agencies to 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
regulatory action. This proposal includes a no-action alternative,
described below, and three ``action alternatives.'' The proposed
standards may, in places, be referred to as the ``preferred
alternative,'' which is NEPA parlance, but NHTSA intends ``proposal''
and ``preferred alternative'' to be used interchangeably for purposes
of this rulemaking.
Regulations regarding implementation of NEPA require agencies to
``rigorously explore and objectively evaluate all reasonable
alternatives, and for alternatives which were eliminated from detailed
study, briefly discuss the reasons for their having been eliminated.''
This does not amount to a requirement that agencies evaluate the widest
conceivable spectrum of alternatives. Rather, the range of alternatives
must be reasonable and consistent with the purpose and need of the
action.
The different regulatory alternatives 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 miles per gallon in one year equals 30.3 miles per
gallon 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 model year to the next). Under some
alternatives, the rate of change is the same from year to year, while
under others, it differs, and under some alternatives, the rate of
change is different for cars and for trucks. One action alternative is
more stringent than the proposal, while one is less stringent than the
proposal. The alternatives considered in this proposal represent a
reasonable range of possible final agency actions.
B. Regulatory Alternatives and Proposed CAFE Standards for MYs 2024-
2026
The regulatory alternatives for 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 which
define standards curves increasing at the given percentage rates and
will also further explain the basis for the alternatives selected.
[[Page 49745]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.101
As for past rulemaking analyses, NHTSA has analyzed each of the
regulatory alternatives in a manner that estimates manufacturers'
potential application of technology in response to the corresponding
CAFE requirements and the estimated market demand for fuel economy,
considering estimated fuel prices, estimated product development
cadence, and the estimated availability, applicability, cost, and
effectiveness of fuel-saving technologies. The analysis sometimes shows
that specific manufacturers could increase CAFE levels beyond
requirements in ways estimated to ``pay buyers back'' very quickly
(i.e., within 30 months) for the corresponding additional costs to
purchase new vehicles through avoided fuel outlays. Consistent with the
analysis published with the 2020 final rule, this analysis shows that
if battery costs decline as projected while fuel prices increase as
projected, BEVs should become increasingly attractive on this basis,
such that the modeled application of BEVs (and some other technologies)
clearly outstrips regulatory requirements after the mid-2030s.
The analysis accompanying the 2020 final rule presented such
results for CAFE standards as well as--separately--CO2
standards. New in this proposal, DOT has modified the CAFE Model to
account for the combined effect of both CAFE and CO2
standards, simulating technology application decisions each
manufacturer could possibly make when faced with both CAFE standards
and CO2 standards (and also estimated market demand for fuel
economy). This capacity was exercised for purposes of creating the
baseline against which alternatives were analyzed, but not for purposes
of modeling compliance with both agencies' proposals. Also, new for
this proposal, DOT has further modified the CAFE Model to account for
the ``Framework'' agreements California has reached with BMW, Ford,
Honda, Volkswagen, and Volvo, and for the ZEV mandate that California
and the ``Section 177'' states have adopted. The TSD elaborates on
these new model capabilities. Generally speaking, the model treats each
manufacturer as applying the following logic when making technology
decisions:
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 PHEVs or BEVs do I need to build in order to satisfy
the 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 in order to
respond to CAFE and CO2 standards?
All of the regulatory alternatives considered here include, for
passenger cars, the following coefficients defining the combination of
baseline Federal CO2 standards and the California Framework
agreement.
[GRAPHIC] [TIFF OMITTED] TP03SE21.102
Coefficients a, b, c, d, e, and f define the current Federal
CO2 standards for passenger cars. Analogous to coefficients
defining CAFE standards, coefficients a and b specify minimum and
maximum passenger car CO2 targets in each model year.
Coefficients c and d specify the slope and intercept of the linear
portion of the CO2 target function,
[[Page 49746]]
and coefficients e and f bound the region within which CO2
targets are defined by this linear form. Coefficients g, h, i, and j
define the CO2 targets applicable to BMW, Ford, Honda,
Volkswagen, and Volvo, pursuant to the agreement these manufacturers
have reached with California. Beyond 2026, the MY 2026 Federal
standards apply to all manufacturers, including these five
manufacturers. The coefficients shown in Table IV-3 define the
corresponding CO2 standards for light trucks.
[GRAPHIC] [TIFF OMITTED] TP03SE21.103
All of the regulatory alternatives considered here also include
NHTSA's estimates of ways each manufacturer could introduce new PHEVs
and BEVs in response to ZEV mandates. As discussed in greater detail
below, these estimates force the model to convert specific vehicle
model/configurations to either a BEV200, BEV300, or BEV400 at the
earliest estimated redesign. These ``ZEV Candidates'' define an
incremental response to ZEV mandates (i.e., beyond PHEV and BEV
production through MY 2020) comprise the following shares of
manufacturers' MY 2020 production for the U.S. market as shown in Table
IV-4.
[GRAPHIC] [TIFF OMITTED] TP03SE21.104
For example, while Tesla obviously need not introduce additional
BEVs to comply with ZEV mandates, our analysis indicates Nissan could
need to increase BEV offerings modestly to do so, and Mazda and some
other manufacturers may need to do considerably more than Nissan to
introduce new BEV offerings.
[[Page 49747]]
This representation of CO2 standards and ZEV mandates
applies equally to all regulatory alternatives, and NHTSA's analysis
applies the CAFE Model to examine each alternative treating each
manufacturer as responding jointly to the entire set of requirements.
This is distinct from model application of BEVs for compliance purposes
under the compliance simulations of the different action alternatives
which inform decision-makers regarding potential effects of the
standards.
Chapter 1 of the TSD contains extensive discussion of the
development of the No-Action Alternative, and explains the reasons for
and effect of apparent ``over-compliance'' with the No-Action
Alternative, which reduces costs and benefits attributable to the
proposed CAFE standards and other action alternatives. NHTSA seeks
comment broadly on that discussion and whether and how to change its
approach to developing the No-Action Alternative for the final rule.
NHTSA also specifically seeks comment on whether and how to add to the
No-Action Alternative for the final rule an estimation of GHG standards
that California and the Section 177 states might separately enforce if
California's waiver of CAA preemption was re-established.
1. No-Action Alternative
The No-Action Alternative (also sometimes referred to as
``Alternative 0'') applies the CAFE target curves set in 2020 for MYs
2024-2026, which raised stringency by 1.5 percent per year for both
passenger cars and light trucks.
BILLING CODE 4910-59-P
[GRAPHIC] [TIFF OMITTED] TP03SE21.105
[GRAPHIC] [TIFF OMITTED] TP03SE21.106
These equations are presented graphically in Figure IV-1 and Figure
IV-2, 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.
[[Page 49748]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.107
[[Page 49749]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.108
NHTSA must also set a minimum standard for domestically
manufactured passenger cars, which is often referred to as the
``MDPCS.'' Any time NHTSA establishes or changes a passenger car
standard for a model year, the MDPCS must also be evaluated or re-
evaluated and established accordingly, but for purposes of the No-
Action alternative, the MDPCS is as it was established in the 2020
final rule, as shown in Table IV-7.
[GRAPHIC] [TIFF OMITTED] TP03SE21.109
BILLING CODE 4910-59-C
As the baseline against which the Action Alternatives are measured,
the No-Action Alternative also includes several other actions that
NHTSA believes will occur in the absence of further regulatory action.
First, NHTSA has included California's ZEV mandate as part of the No-
Action Alternative. NHTSA has already proposed to rescind the 2019
``SAFE I'' rule,\374\ and EPA has reopened consideration of whether to
grant California a waiver to consider its ZEV mandate,\375\ although
California does not currently possess a waiver of preemption under the
CAA and NHTSA regulations currently purport to preempt the California
ZEV program. Although neither of these actions has yet been finalized,
it is reasonably foreseeable that manufacturers selling vehicles in
California and in the Section 177 states could be required to comply
with the ZEV mandate during the timeframe of this rulemaking. Second,
NHTSA has included the agreements made between California and BMW,
Ford, Honda, VWA, and Volvo, because these agreements by their terms
are contracts,
[[Page 49750]]
even though they were entered into voluntarily.\376\ NHTSA did so by
including EPA's baseline (i.e., 2020) GHG standards in its analysis,
and introducing more stringent GHG target functions during MYs 2022-
2026, but treating only these five manufacturers as subject to these
more stringent target functions. Because a significant portion of the
market voluntarily adopted the California framework, presumably because
the manufacturers who joined believed it could be met, and because that
adoption is contractually binding once entered into, it is reasonable
to assume that it will occur as expected during the rulemaking
timeframe, and thus, reasonable to include in the No-Action
Alternative. As in past analyses, NHTSA's analysis further assumes
that, beyond any technology applied in response to CAFE standards, EPA
GHG standards, California/OEM agreements, and ZEV mandates applicable
in California and the Section 177 states, manufacturers could also make
any additional fuel economy improvements estimated to reduce owners'
estimated average fuel outlays during the first 30 months of vehicle
operation by more than the estimated increase in new vehicle price.
---------------------------------------------------------------------------
\374\ 86 FR 25980 (May 12, 2021).
\375\ 86 FR 22421 (Apr. 28, 2021).
\376\ See https://ww2.arb.ca.gov/news/framework-agreements-clean-cars.
---------------------------------------------------------------------------
NHTSA accomplished much of this through expansion of the CAFE Model
after the prior rulemaking. The previous version of the model had been
extended to apply to GHG standards as well as CAFE standards but had
not been published in a form that simulated simultaneous compliance
with both sets of standards. As discussed at greater length in the
current CAFE Model documentation, the updated version of the model
simulates all the following simultaneously:
1. Compliance with CAFE standards
2. Compliance with GHG standards applicable to all manufacturers
3. Compliance with alternative GHG standards applicable to a subset of
manufacturers
4. Compliance with ZEV mandates
5. Further fuel economy improvements applied if sufficiently cost-
effective for buyers
Inclusion of these actions in the No-Action Alternative means that
they are necessarily included in each of the Action Alternatives. That
is, the impacts of all the alternatives evaluated in this proposal are
against the backdrop of these State and voluntary actions by
automakers. This is important to remember, because it means that
automakers will be taking actions to improve fuel economy even in the
absence of new CAFE standards, and that costs and benefits attributable
to those actions are therefore not attributable to possible future CAFE
standards.
2. Alternative 1
Alternative 1 would increase CAFE stringency for MY 2024 by 9.14%
for passenger cars and 11.02% for light trucks and increase stringency
in MYs 2025 and 2026 by 3.26% per year for both passenger cars and
light trucks. NHTSA calculates that the stringency of Alternative 1 in
each of MYs 2024-2026 is equivalent to the average stringency of the
California framework agreement applied to all manufacturers in those
model years. NHTSA calculated the stringency values using a
spreadsheet, shown in TSD Chapter 1, assuming manufacturers would
achieve a one percent reduction in stringency each model year under the
California framework through the application of ZEV vehicle
multipliers. The spreadsheet applies a normalized stringency value of
100 percent in MY 2021 for both CO2 standards and CAFE
standards.
Informed by these calculations, NHTSA defined Alternative 1 by
applying the CAFE equivalent stringency increases in MYs 2024-2026,
resulting in the coefficients listed in Table IV-8 and Table IV-9.
BILLING CODE 4910-59-P
[GRAPHIC] [TIFF OMITTED] TP03SE21.110
[GRAPHIC] [TIFF OMITTED] TP03SE21.111
These equations are represented graphically in Figure IV-4 and
Figure IV-4.
---------------------------------------------------------------------------
\377\ For this and other action alternatives, readers may note
that the cutpoint for large trucks is further to the right than in
the 2020 final rule. The 2020 final rule (and its preceding NPRM)
did not contain an adjustment to the right cutpoint that had been
finalized in 2012. Because comments were not received to the NPRM,
the lack of adjustment was finalized. Considering the question again
for this proposal, NHTSA believes that moving the cutpoint to the
right for large trucks (consistent with the intent and requirements
in 2012) is reasonable, given the rate of increase in stringency for
this proposal.
---------------------------------------------------------------------------
[[Page 49751]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.112
[[Page 49752]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.113
Under this alternative, the MDPCS is as shown in Table IV-10.
[GRAPHIC] [TIFF OMITTED] TP03SE21.114
NHTSA considered this alternative as a way to evaluate the effects
of industry-wide CAFE standards approximately harmonized with the
California framework agreement applied to signatory OEMs' production
for the U.S. market.\378\ The fact that five major manufacturers
voluntarily bound themselves to the framework levels, not just for MYs
2024-2026 but for MYs 2021-2026, is a relevant data point in terms of
their technological feasibility and economic practicability for the
fleet as a whole. NHTSA seeks comment on whether Alternative 1 (as
defined by the rate of increase and the curve coefficients)
appropriately captures its stated goal of approximating the fuel
savings that would occur under an industry-wide application of fuel
economy standards harmonized with the California framework, or whether
changes might be appropriate for the final rule. NHTSA asks that
commenters explain the specific technical basis for any requested
changes, as well as the basis for determining that the resultant CAFE
standards could meet EPCA's
[[Page 49753]]
requirement that NHTSA select the maximum feasible standard for each
fleet in each model year.
---------------------------------------------------------------------------
\378\ CAFE standards defining this alternative reflect the fact
that EPCA does not provide a basis for CAFE standards to include
``multipliers'' applicable to PHEV and/or BEV production volumes, as
well as the fact that EPCA's treatment of BEV energy consumption is
different from the ``0 grams/mile'' treatment for purposes of
determining compliance with GHG emissions standards.
---------------------------------------------------------------------------
3. Alternative 2
Alternative 2 would increase CAFE stringency at 8 percent per year,
which NHTSA calculates would result in total lifetime fuel savings from
vehicles produced during MYs 2021-2029 similar to total lifetime fuel
savings that would occur if the fuel economy standards harmonized with
California framework agreement had applied to all manufacturers during
MYs 2021-2026.
[GRAPHIC] [TIFF OMITTED] TP03SE21.115
[GRAPHIC] [TIFF OMITTED] TP03SE21.116
Under this alternative, the MDPCS is as shown in Table IV-13.
[GRAPHIC] [TIFF OMITTED] TP03SE21.117
NHTSA considered this alternative as a way to evaluate the effects
of CAFE standards that sought to achieve the fuel savings that would be
achieved if fuel economy standards harmonized with the California
framework agreement had been applied to all vehicle manufacturers from
its beginning the time the framework was agreed. As for Alternative 1,
the fact that five major manufacturers voluntarily bound themselves to
these levels, not just for MYs 2024-2026 but for MYs 2021-2026, is a
relevant data point in terms of their technological feasibility and
economic practicability for the fleet as a whole.\379\ NHTSA seeks
comment on whether Alternative 2 (as defined by the rate of increase
and the curve coefficients) appropriately captures its stated goal of
representing the fuel savings achievement that would be achieved if
fuel economy standards harmonized with the California framework
agreement were applied to all companies at a national level over MYs
2021-2026, or whether changes might be appropriate for the final rule.
NHTSA asks that commenters explain the specific technical basis for any
requested changes, as well as the basis for determining that the
resultant CAFE standards could meet EPCA's requirement that NHTSA
select the maximum feasible standard for each fleet in each model year.
---------------------------------------------------------------------------
\379\ Section VI discusses economic practicability in more
detail, including NHTSA's long-standing interpretation that economic
practicability need not mean that the standards are comfortably
achievable for every single manufacturer individually, as long as
they appear economically practicable for the fleet as a whole.
---------------------------------------------------------------------------
As another possibility, NHTSA could modify Alternative 2 by
increasing the stringency of CAFE standards by 10 percent between model
years 2025 and 2026, rather than by 8 percent. Shown graphically, this
possibility would look as shown in Figure IV-5.
[[Page 49754]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.118
NHTSA seeks comment on this option as well as on Alternative 2.
4. Alternative 3
Alternative 3 would increase CAFE stringency at 10 percent per
year, which NHTSA calculates would result in total lifetime fuel
savings from vehicles produced during MYs 2021-2029 similar to total
lifetime fuel savings that would have occurred if NHTSA had promulgated
final CAFE standards for MYs 2021-2025 at the augural levels announced
in 2012 and, in addition, if NHTSA had also promulgated MY 2026
standards that reflected a continuation of that average rate of
stringency increase (4.48% for passenger cars and 4.54% for light
trucks).
[GRAPHIC] [TIFF OMITTED] TP03SE21.119
[GRAPHIC] [TIFF OMITTED] TP03SE21.120
[[Page 49755]]
These equations are represented graphically in Figure IV-6 and
Figure IV-7.
[GRAPHIC] [TIFF OMITTED] TP03SE21.121
[[Page 49756]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.122
Under this alternative, the MDPCS is as follows in Table IV-16.
[GRAPHIC] [TIFF OMITTED] TP03SE21.123
BILLING CODE 4910-59-C
NHTSA considered this alternative as a way to evaluate the effects
of CAFE standards that would return to a fuel consumption trajectory
exemplified by the standards announced in 2012. NHTSA seeks comment on
whether Alternative 3 (as defined by the rate of increase and the curve
coefficients) appropriately captures this goal, or whether changes
might be appropriate for the final rule. NHTSA asks that commenters
explain the specific technical basis for any requested changes, as well
as the basis for determining that the resultant CAFE standards could
meet EPCA's requirement that NHTSA select the maximum feasible standard
for each fleet in each model year. While NHTSA believes that this
alternative may be beyond maximum feasible based on the information
currently before us, as discussed in more detail in Section VI, all
alternatives remain under consideration for the final rule. Moreover,
because Alternative 3 produces significant social benefits, NHTSA seeks
comment on whether to adopt a more stringent increase from MY 2025 to
MY 2026, as described above, that would parallel the year over year
increase Alternative 3 analyzes.
[[Page 49757]]
V. Effects of the Regulatory Alternatives
A. Effects on Vehicle Manufacturers
Each of the regulatory alternatives NHTSA has considered would
increase the stringency of both passenger car and light truck CAFE
standards in each of model years 2024-2026. To estimate the potential
impacts of each of these alternatives, NHTSA has, as for all recent
rulemakings, assumed that standards would continue unchanged after the
last model year (in this case, 2026) to be covered by newly issued
standards. 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 differ from NHTSA's projections,
average requirements could, therefore, also differ from NHTSA's
projections. At this time, NHTSA estimates that, under each of the
regulatory alternatives, average fuel economy requirements could
increase as summarized in the following three tables.
BILLING CODE 4910-59-P
[GRAPHIC] [TIFF OMITTED] TP03SE21.124
[GRAPHIC] [TIFF OMITTED] TP03SE21.125
[GRAPHIC] [TIFF OMITTED] TP03SE21.126
Manufacturers do not always comply exactly with each CAFE standard
in each model year. To date, some manufacturers have tended to
regularly exceed one or both requirements. 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 model year. Some manufacturers have paid civil penalties
(i.e., fines) required under EPCA when a fleet falls short of a
standard in a given model year and the manufacturer cannot provide
compliance credits sufficient to address the compliance shortfall. As
discussed in the accompanying PRIA and 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, setting aside the potential that any manufacturer would
respond to CAFE standards in model years 2024-2026 by applying CAFE
compliance credits or introducing new models of alternative fuel
vehicles. Many of these inputs are subject to uncertainty and, in any
event, as in all CAFE rulemakings, NHTSA's analysis merely illustrates
one set of ways manufacturers could potentially respond to each
regulatory alternative. At this time, NHTSA estimates that
manufacturers' responses to standards defining each alternative could
lead average fuel economy levels to increase through model year 2029 as
summarized in the following three tables. Changes are shown to occur in
MY 2023 even though NHTSA is not explicitly
[[Page 49758]]
proposing to regulate that model year because NHTSA anticipates that
manufacturers could make changes as early as that model year to affect
future compliance positions (i.e., multi-year planning).
[GRAPHIC] [TIFF OMITTED] TP03SE21.127
[GRAPHIC] [TIFF OMITTED] TP03SE21.128
[GRAPHIC] [TIFF OMITTED] TP03SE21.129
While these increases in average fuel economy account for 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
estimates.
At this time, NHTSA estimates that manufacturers' application of
advanced gasoline engines (i.e., gasoline engines with cylinder
deactivation, turbocharging, high or variable compression ratios) could
increase through MY 2029 under the no-action alternative and through at
least MY 2024 under each of the action alternatives. However, NHTSA
also estimates that in MY 2024, reliance on advanced gasoline engines
could begin to decline under the more stringent action alternatives, as
manufacturers shift toward electrification.
[GRAPHIC] [TIFF OMITTED] TP03SE21.130
[[Page 49759]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.131
[GRAPHIC] [TIFF OMITTED] TP03SE21.132
The aforementioned estimated shift to electrification under the
more stringent regulatory alternatives is the most pronounced for
hybrid-electric vehicles (i.e., ``mild'' ISG HEVs and ``strong'' P2 and
Power-Split HEVs).
[GRAPHIC] [TIFF OMITTED] TP03SE21.133
[GRAPHIC] [TIFF OMITTED] TP03SE21.134
[[Page 49760]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.135
Under the more stringent action alternatives, NHTSA estimates that
manufacturers could increase production of plug-in hybrid electric
vehicles (PHEVs) well over current rates.
[GRAPHIC] [TIFF OMITTED] TP03SE21.136
[GRAPHIC] [TIFF OMITTED] TP03SE21.137
[GRAPHIC] [TIFF OMITTED] TP03SE21.138
For this NPRM and accompanying PRIA, NHTSA's analysis excludes the
introduction of new alternative fuel vehicle (AFV) models during MY
2024-2026 as a response to CAFE standards.\380\ However, NHTSA's
analysis does consider the potential that manufacturers might respond
to CAFE standards by introducing new BEV models outside of MYs 2024-
2026, and NHTSA's analysis does account for the potential that ZEV
mandates could lead manufacturers to introduce new BEV models even
during MYs 2024-2026. Also accounting for shifts in fleet mix, NHTSA
projects increased production of BEVs through MY 2029.
---------------------------------------------------------------------------
\380\ The SEIS does not make this analytical exclusion.
---------------------------------------------------------------------------
[[Page 49761]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.139
[GRAPHIC] [TIFF OMITTED] TP03SE21.140
[GRAPHIC] [TIFF OMITTED] TP03SE21.141
The PRIA provides a wider-ranging 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 much more detailed and comprehensive results, and the
underlying CAFE Model output files provide all information, including
the specific combination of technologies estimated to be applied to
every specific vehicle model/configuration in each of model years 2020-
2050.\381\
---------------------------------------------------------------------------
\381\ See Appendices I and II of the accompanying PRIA and the
CAFE Model output files.
---------------------------------------------------------------------------
NHTSA's analysis shows manufacturers' regulatory costs for CAFE
standards, CO2 standards, and ZEV mandates increasing
through MY 2029, and (logically) increasing more under the more
stringent alternatives. Accounting for fuel-saving technologies
estimated to be added under each regulatory alternative (including air
conditioning improvements and other off-cycle technologies), and also
accounting for CAFE fines that NHTSA estimates some manufacturers could
elect to pay rather than achieving full compliance with CAFE standards
in some model years, NHTSA estimates that relative to the continued
application of MY 2020 technologies, manufacturers' cumulative costs
during MYs 2023-2029 could total $121b under the no-action alternative,
and $166b, $208b, and $251b under alternatives 1, 2, and 3,
respectively. 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 model year under each
regulatory alternative, and the underlying CAFE Model output files also
show results specific to manufacturers' domestic and imported car
fleets.
[[Page 49762]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.142
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 as in the past, NHTSA estimates
that the average costs to new vehicle purchasers could increase through
MY 2029 as summarized in Table V-20 through Table V-22.
[GRAPHIC] [TIFF OMITTED] TP03SE21.143
[GRAPHIC] [TIFF OMITTED] TP03SE21.144
[[Page 49763]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.145
Table V-23 shows how these costs could vary among manufacturers,
suggesting that disparities could decrease as the stringency of
standards increases.
[GRAPHIC] [TIFF OMITTED] TP03SE21.146
NHTSA estimates that although projected fuel savings under the more
stringent regulatory alternatives could tend to increase new vehicles
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. For example,
in the case of the ``unconstrained'' SEIS results, manufacturer costs
across alternatives are lower.
[[Page 49764]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.147
The TSD 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.
While these slight reductions in new vehicles sales tend to
slightly reduce projected automobile industry labor, 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 about the same under each of the four
regulatory alternatives.
[[Page 49765]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.148
The accompanying TSD discusses NHTSA's approach to estimating
automobile industry employment, and the accompanying RIA (and its
Appendices I and II) and CAFE Model output files provide more detailed
results of NHTSA's analysis.
B. Effects on New Car and Truck Buyers
As discussed above, NHTSA estimates that the average fuel economy
and purchase cost of new vehicles could increase between 2020 and 2029
and increase more quickly under each of the action alternatives than
under the baseline No-Action Alternative. On one hand, buyers could
realize the benefits of increase fuel economy: Spending less on fuel.
On the other, buyers could pay more for new vehicles, for some costs
tied directly to vehicle value (e.g., sales taxes and collision
insurance). Table V-24 reports sales-weighted MSRP values for the No-
Action Alternative and relative increases in MSRP for the three
regulatory alternatives.
[GRAPHIC] [TIFF OMITTED] TP03SE21.149
[[Page 49766]]
Table V-25 through Table V-27 presents projected consumer costs and
benefits along with net benefits for model year 2029 and 2039 vehicles
under the proposed alternatives. Results are shown in 2018 dollars,
without discounting and with benefits and costs discounted at annual
rates of 3% and 7%. The TSD and PRIA accompanying this NPRM discuss
underlying methods, inputs, and results in greater detail, and more
detailed tables and underlying results are contained in the
accompanying CAFE Data Book and CAFE Model output files. For all of the
action alternatives, avoided outlays for fuel purchases account for
most of the projected benefits to consumers, and increases in the cost
to purchase new vehicles account for most of the projected costs.
[GRAPHIC] [TIFF OMITTED] TP03SE21.150
[[Page 49767]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.151
[[Page 49768]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.152
BILLING CODE 4910-59-C
C. Effects on Society
Table V-28 and Table V-29 describe 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. In this analysis, we assume that those costs are fully passed
through to new car and truck buyers, in the form of higher prices.
Other assumptions are possible, but we do not currently have data to
support attempting to model cross-subsidization. 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 contribute
to the calculation of net benefits (and are omitted from the tables
below).
While incremental maintenance and repair costs would accrue to
buyers of new cars and trucks affected by more stringent CAFE
standards, we do not carry these costs in the analysis. They are
difficult to estimate for emerging
[[Page 49769]]
technologies but represent real costs (and benefits in the case of
alternative fuel vehicles that may require less frequent maintenance
events). They may be included in future analyses as data become
available to evaluate lifetime maintenance costs. 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 the 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.
In addition to private benefits and costs, there are purely
external benefits and costs that can be attributed to increases in CAFE
standards. These are benefits and costs that accrue to society more
generally, rather than to the specific individuals who purchase a new
vehicle that was produced under more stringent CAFE standards. Of the
external costs, the largest is the loss in fuel tax revenue that occurs
as a result of falling fuel consumption. While drivers of new vehicles
(purchased in years where CAFE stringency is increasing) save fuel
costs at retail prices, the rest of U.S. road users experience a
welfare loss, in two ways. First, the revenue generated by fuel taxes
helps to maintain roads and bridges, and improve infrastructure more
generally, and that loss in fuel tax revenue is a social cost. And
second, 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
impose a social cost to all road users.
Among the purely external benefits created when CAFE standards are
increased, the largest is the reduction in damages resulting from
greenhouse gas emissions. The estimates in Table V-28 assume a social
cost of GHG emissions based on a 2.5% discount rate, and those in Table
V-29 assume a social cost of GHG emissions based on a 3% discount rate.
The associated benefits related to reduced health damages from
conventional 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 overwhelming
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. This has been consistently
true in CAFE rulemakings.
The choice of discount rate also affects the resulting benefits and
costs. As the tables show, net social benefits are positive for
Alternative 1 and 2 at a 3% discount rate, but only for Alternative 1
when applying a 7% discount rate to benefits and costs. Alternative 3
has negative net benefits under both discount rates. As mentioned
above, the benefits of the regulatory alternatives, but especially
Alternative 3, are concentrated in later years where a higher discount
rate has a greater contracting effect.
BILLING CODE 4910-59-P
[[Page 49770]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.153
[[Page 49771]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.154
The following tables show the costs and benefits associated with
external effects to society. As seen in Table V-28 and Table V-29, the
external benefits are composed of reduced climate damages (Table V-30
and Table V-31), reduced health damages (Table V-32 and Table V-33),
and reduced petroleum market externalities (Table V-36). The external
costs to society include congestion and noise costs (Table V-34 and
Table V-35) and safety costs (Table V-37). We show the costs and
benefits by model year (1981-2029), in contrast to the tables above,
which present incremental and net costs and benefits over the lifetimes
of the entire fleet produced through 2029, beginning with model year
1981.
[[Page 49772]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.155
Table V-30 and Table V-31 present the total costs of GHGs in the
baseline scenario and the incremental costs relative to the baseline in
the other three alternatives. Negative incremental values indicate a
decrease in social costs of GHGs, while positive incremental values
indicate an increase in costs relative to the baseline for the given
model year. The GHG costs follow a similar pattern in all three
alternatives, decreasing across all model years, with the largest
reductions associated with 2025-2028 model years. The magnitude of
CO2 emissions is much higher than the magnitudes of
CH4 and N2O emissions, which is why the total
costs are so much larger for CO2.
[GRAPHIC] [TIFF OMITTED] TP03SE21.156
The CAFE Model calculates health costs attributed to criteria
pollutant emissions of NOX, SOX, and
PM2.5, shown in Table V-32 and Table V-33. These costs are
directly related to the tons of each pollutant emitted from
[[Page 49773]]
various upstream and downstream sources, including on-road vehicles,
electricity generation, fuel refining, and fuel transportation and
distribution. See Chapter 4 of the SEIS and Chapter 5.4 of the TSD for
further information regarding the calculations used to estimate health
impacts, and more details about the types of health effects. The
following section of the preamble, V.D, discusses the changes in tons
of emissions themselves across rulemaking alternatives, while the
current section focuses on the changes in social costs associated with
those emissions.
Criteria pollutant health costs (presented in Table V-32 and Table
V-35) increase slightly in earlier model years (1981-2023), but those
cost increases are offset by the decrease in health costs in later
model years. In Table V-32 and Table V-33, the costs in alternatives 1-
3 are shown in terms of percent of the baseline. For instance, the
total decrease in SOX costs in Alternative 2 is equivalent
to 0.2% of the total baseline SOX costs. The changes across
alternatives relative to the baseline are relatively minor, although
some impacts in later model years are more significant (e.g., 7.5%
decrease in PM2.5 in 2028, Alternative 3). Since the health
cost value per ton of emissions differs by pollutant, the pollutants
that incur the highest costs are not necessarily those with the largest
amount of emissions.
[GRAPHIC] [TIFF OMITTED] TP03SE21.157
[[Page 49774]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.158
NHTSA estimates social costs of congestion and noise across
regulatory alternatives, throughout the lifetimes of model years 1981-
2029. Congestion and noise are functions of VMT and fleet mix, and the
differences between alternatives are due mainly to differences in VMT
(see Section V.D). Overall, congestion and noise costs increase
relative to the baseline across all alternatives, but viewed from a
model year perspective, the congestion and noise costs associated with
later model years are negative relative to the baseline. It is
important to note that the overall increases in congestion and noise
costs are relatively small when compared to the total congestion and
noise costs in the baseline (No-Action Alternative). For further
details regarding congestion and noise costs, see Chapter 6.2.3 of the
TSD and Chapter 6.5 of the PRIA.
[GRAPHIC] [TIFF OMITTED] TP03SE21.159
[[Page 49775]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.160
The CAFE Model accounts for benefits of increased energy security
by computing changes in social costs of petroleum market externalities.
These social costs represent the risk to the U.S. economy incurred by
exposure to price shocks in the global petroleum market that are not
accounted for by oil prices and are a direct function of gallons of
fuel consumed. Chapter 6.2.4 of the accompanying TSD describes the
inputs involved in calculating these petroleum market externality
costs. Petroleum market externality costs decrease relative to the
baseline under all alternatives, regardless of the discount rate used.
This pattern occurs due to the decrease in gallons of fuel consumed
(see Section V.D) as the stringency of alternatives increases. Only the
earlier model year cohorts (1981-2023) contribute to slight increases
in petroleum market externality costs, but these are offset by the
decreases from later model years.
[GRAPHIC] [TIFF OMITTED] TP03SE21.161
NHTSA estimates various monetized safety impacts across regulatory
alternatives, including costs of fatalities, non-fatal crash costs, and
property damage costs. Table V-37 presents these social costs across
alternatives and discount rates. Safety effects are discussed at length
in the PRIA accompanying this NPRM (see Chapter 5 of the PRIA).
[[Page 49776]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.162
BILLING CODE 4910-59-C
D. Physical and Environmental Effects
NHTSA calculates estimates for the various physical and
environmental effects associated with the proposed standards. These
include quantities of fuel and electricity consumption, tons of
greenhouse gas (GHG) emissions and criteria pollutants, and health and
safety impacts.
In terms of fuel and electricity usage, NHTSA estimates that the
proposal would save about 50 billion gallons of gasoline and increase
electricity consumption by about 275 TWh over the lives of vehicles
produced prior to MY 2030, relative to the baseline standards (i.e.,
the No-Action Alternative). From a calendar year perspective, NHTSA's
analysis also estimates total annual consumption of fuel by the entire
on-road fleet from calendar year 2020 through calendar year 2050. On
this basis, gasoline and electricity consumption by the U.S. light-duty
vehicle fleet evolves as shown in the following two graphs, each of
which shows projections for the No-Action Alternative (Alternative 0,
i.e., the baseline), Alternative 1, Alternative 2 (the proposal), and
Alternative 3.
BILLING CODE 4910-59-P
[GRAPHIC] [TIFF OMITTED] TP03SE21.163
[[Page 49777]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.164
NHTSA estimates the greenhouse gas emissions (GHGs) attributable to
the light-duty on-road fleet, from both vehicles and upstream energy
sector processes (e.g., petroleum refining, fuel transportation and
distribution, electricity generation). Overall, NHTSA estimates that
the proposed rule would reduce greenhouse gases by about 465 million
metric tons of carbon dioxide (CO2), about 500 thousand
metric tons of methane (CH4), and about 12 thousand tons of
nitrous oxide (N2O). The following three graphs (Figure V-5,
Figure V-6, and Figure V-7) present NHTSA's estimate of how emissions
from these three GHGs could evolve over the years. Note that these
graphs include emissions from both vehicle and upstream processes. All
three GHG emissions follow similar trends in the years between 2020-
2050.
[[Page 49778]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.165
[[Page 49779]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.166
[[Page 49780]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.167
The figures presented here are not the only estimates NHTSA has
calculated regarding projected GHG emissions in future years. As
discussed in Section II, the accompanying SEIS uses an
``unconstrained'' analysis as opposed to the ``standard setting''
analysis presented in this NPRM and PRIA. 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 SEIS.
NHTSA also estimates criteria pollutant emissions resulting from
vehicle and upstream processes attributable to the light-duty on-road
fleet. NHTSA includes estimates for all of the criteria pollutants for
which EPA has issued National Ambient Air Quality Standards. Under each
regulatory alternative, NHTSA projects a dramatic decline in annual
emissions of carbon monoxide (CO), volatile organic compounds (VOC),
nitrogen oxide (NOX), and fine particulate matter
(PM2.5) attributable to the light-duty on-road fleet between
2020 and 2050. As exemplified in Figure V-8, emissions in any given
year could be very nearly the same under each regulatory alternative.
On the other hand, as discussed in the PRIA and SEIS accompanying
this NPRM, NHTSA projects that annual SO2 emissions
attributable to the light-duty 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). The adoption of actions--such as
actions prompted by President Biden's Executive order directing
agencies to develop a Federal Clean Electricity and Vehicle Procurement
Strategy--to reduce electricity generation emission rates beyond
projections underlying NHTSA's analysis (discussed in the TSD) could
dramatically reduce SO2 emissions under all regulatory
alternatives considered here.\382\
---------------------------------------------------------------------------
\382\ E.O. 14008, 86 FR 7619 (Feb. 1, 2021), https://www.whitehouse.gov/briefing-room/presidential-actions/2021/01/27/executive-order-on-tackling-the-climate-crisis-at-home-and-abroad/,
accessed June 17, 2021.
---------------------------------------------------------------------------
[[Page 49781]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.168
[[Page 49782]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.169
[[Page 49783]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.170
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. Figure V-11 shows the differences in select health impacts
relative to the baseline, across alternatives 1-3. These changes are
split between calendar year decades, with the largest differences
between the baseline and alternatives occurring between 2041-2050. The
magnitude of the differences relates directly to the changes in tons of
criteria pollutants emitted. See Chapter 5.4 of the TSD for information
regarding how the CAFE Model calculates these health impacts.
[[Page 49784]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.171
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 light-duty
on-road vehicles considered in the analysis. Chapter 5 in the PRIA
accompanying this NPRM contains an in-depth discussion on the effects
of the various alternatives on these safety measures, and TSD Chapter 7
contains information regarding the construction of the safety
estimates.
E. Sensitivity Analysis
The analysis conducted to support this proposal consists of data,
estimates, and assumptions, all applied within an analytical framework,
the CAFE Model. Just like in all past CAFE 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, if we are
going to try to analyze meaningfully the effects of something that will
happen in the future--i.e., the regulatory alternatives being
considered, that represent different possible CAFE standards for MYs
2024-2026. To get a sense of the effect that these assumptions have on
the analytical findings, we conducted additional model runs with
alternative assumptions, which explored a range of potential inputs and
the sensitivity of estimated impacts to changes in 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.\383\ A sensitivity analysis can identify two critical pieces of
information: How big an influence does each parameter exert on the
analysis, and how sensitive are the model results to that assumption?
---------------------------------------------------------------------------
\383\ 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 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
[[Page 49785]]
assumptions could affect costs and benefits of this proposal.
Table V-38 lists and briefly descries the cases that we examined in
the sensitivity analysis.
[GRAPHIC] [TIFF OMITTED] TP03SE21.172
[[Page 49786]]
Complete results for the sensitivity cases are summarized in
Chapter 7 of the accompanying PRIA, and detailed model inputs and
outputs for curious readers are available on NHTSA's website.\384\ For
purposes of this preamble, Figure V-12 below illustrates the relative
change of the sensitivity effect of selected inputs on the costs and
benefits that we estimate for the proposal.
---------------------------------------------------------------------------
\384\ https://www.nhtsa.gov/laws-regulations/corporate-average-fuel-economy.
[GRAPHIC] [TIFF OMITTED] TP03SE21.173
While Figure V-12 does not show precise values, it gives 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. Assuming a more-discounted or lower social cost of
carbon would have a relatively large effect, as would assuming a
different oil price, or doubling the assumed ``payback period.'' Making
very high levels of mass reduction unavailable in the modeling appears
to have a (relatively) very large effect on costs, but this is to some
extent an artifact of the ``standard setting'' runs used for the
preamble and PRIA analysis, where electrification is limited due to
statutory restrictions. On the other hand, assumptions about which
there has been significant disagreement in the past, like the rebound
effect or the sales-scrappage response, appear to cause only relatively
small changes in net benefits. Chapter 7 of the PRIA provides a much
fuller discussion of these findings, and presents net benefits
estimated under each of the cases included in the sensitivity analysis,
including the subset for which impacts are summarized in Figure V-13.
[[Page 49787]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.174
BILLING CODE 4910-59-C
The results presented in the earlier subsections of Section V and
discussed in Section VI reflect the agency'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. Policy-making in the
face of future uncertainty is inherently complex. Section VI explains
how NHTSA proposes to balance the statutory factors in light of the
analytical findings, the uncertainty that we know exists, and our
Nation's policy goals, to determine the CAFE standards that NHTSA
tentatively concludes are maximum feasible for MYs 2024-2026.
VI. Basis for NHTSA's Tentative Conclusion That the Proposed Standards
Are Maximum Feasible
In this section, NHTSA discusses the factors, data, and analysis
that the agency has considered in the tentative selection of the
proposed CAFE standards for MYs 2024-2026. The primary purpose of EPCA,
as amended by EISA, and codified at 49 U.S.C. chapter 329, is energy
conservation, and fuel economy standards help to conserve energy by
requiring automakers to make new vehicles travel a certain distance on
a gallon of fuel.\385\ The goal of the CAFE standards is to conserve
energy, while taking into account the statutory factors set forth at 49
U.S.C. 32902(f), as discussed below.
---------------------------------------------------------------------------
\385\ While individual vehicles need not meet any particular mpg
level, as discussed elsewhere in this preamble, fuel economy
standards do require vehicle manufacturers' fleets to meet certain
compliance obligations based on fuel economy levels target curves
set forth by NHTSA in regulation.
---------------------------------------------------------------------------
The provision at 49 U.S.C. 32902(f) states that when setting
maximum feasible CAFE standards for new passenger cars and light
trucks, the Secretary of Transportation\386\ ``shall consider
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.'' In previous rulemakings,
including the 2012 final rule issued during the Obama Administration
and the recent 2020 final rule, NHTSA considered technological
feasibility, including the availability of various fuel-economy-
improving technologies to be applied to new vehicles in the timeframe
of the standards depending on the ultimate stringency levels, and also
considered economic practicability, including the differences between a
range of regulatory alternatives in terms of effects on per-vehicle
costs, the ability of both the industry and individual manufacturers to
comply with standards at various levels, as well as effects on vehicle
sales, industry employment, and consumer demand. NHTSA also considered
how compliance with other motor vehicle standards of the Government
might affect manufacturers' ability to meet CAFE standards represented
by a range of regulatory alternatives, and how the need of the U.S. to
conserve energy could be more or less addressed under a range of
regulatory alternatives, in terms of considerations like costs to
consumers, the national balance of payments, environmental implications
like climate and smog effects, and foreign policy effects such as the
likelihood that U.S. military and other expenditures could change as a
result of more or less oil consumed by the U.S. vehicle fleet. These
elements are discussed in detail throughout this analysis. As will be
explained in greater detail below, while NHTSA is considering all of
the same factors in proposing revised CAFE standards for MYs 2024-2026
that it considered in previous rulemakings, the agency's balancing of
those factors has shifted, and NHTSA is therefore choosing to set CAFE
standards at a different level from what both the 2012 final rule and
the 2020 final rule set forth. Besides the factors specified in
32902(f), NHTSA has also historically considered the safety effects of
potential CAFE standards, and additionally considers relevant case law.
---------------------------------------------------------------------------
\386\ By delegation, the NHTSA Administrator.
---------------------------------------------------------------------------
NHTSA and EPA have coordinated in setting standards, and many of
the factors that NHTSA considers to set maximum feasible standards
complement factors that EPA considers under the Clean Air Act. The
balancing of competing factors by both EPA and NHTSA are consistent
with each agency's statutory authority and recognize the statutory
obligations the Supreme Court pointed to in Massachusetts v. EPA. NHTSA
also
[[Page 49788]]
considers the Ninth Circuit's decision in Center for Biological
Diversity v. NHTSA, which remanded NHTSA's 2006 final rule establishing
standards for MYs 2008-2011 light trucks and underscored that ``the
overarching purpose of EPCA is energy conservation.''\387\
---------------------------------------------------------------------------
\387\ 538 F.3d 1172 (9th Cir. 2008).
---------------------------------------------------------------------------
This proposal contains a range of regulatory alternatives for MYs
2024-2026, from retaining the 1.5 percent annual increases set in 2020,
up to a stringency increase of 10 percent annually. The analysis
supported this range of alternatives based on factors relevant to
NHTSA's exercise of its 32902(f) authority, such as fuel saved and
emissions reduced, the technologies available to meet the standards,
the costs of compliance for automakers and their abilities to comply by
applying technologies, the impact on consumers with respect to cost,
fuel savings, and vehicle choice, and effects on safety, among other
things.
NHTSA's tentative conclusion, after consideration of the factors
described below and information in the administrative record for this
action, is that 8 percent increases in stringency for MYs 2024-2026
(Alternative 2 of this analysis) are maximum feasible. The Biden
Administration is deeply committed to working aggressively to improve
energy conservation, and higher standards appear increasingly likely to
be economically practicable given almost-daily announcements by major
automakers about forthcoming new high-fuel-economy vehicle models, as
described below. Despite only one year having passed since the 2020
final rule, enough has changed in the U.S. and the world that
revisiting the CAFE standards for MYs 2024-2026, and raising their
stringency considerably, is both appropriate and reasonable.
The following sections discuss in more detail the statutory
requirements and considerations involved in NHTSA's tentative
determination of maximum feasible CAFE standards, and NHTSA's
explanation of its balancing of factors for this tentative
determination.
A. EPCA, as Amended by EISA
EPCA, as amended by EISA, contains a number of provisions regarding
how NHTSA must set CAFE standards. DOT (by delegation, NHTSA) \388\
must establish separate CAFE standards for passenger cars and light
trucks \389\ for each model year,\390\ and each standard must be the
maximum feasible that the Secretary (again, by delegation, NHTSA)
believes the manufacturers can achieve in that model year.\391\ 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.\392\ 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 and consumer
preferences. 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 before
NHTSA about the expected circumstances in the model years covered by
the rulemaking. The agency's decision must also be guided by the
overarching purpose of EPCA, energy conservation, while balancing these
factors.\393\
---------------------------------------------------------------------------
\388\ 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 CFR 1.95(a).
\389\ 49 U.S.C. 32902(b)(1) (2007).
\390\ 49 U.S.C. 32902(a) (2007).
\391\ Id.
\392\ 49 U.S.C. 32902(f) (2007).
\393\ 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.'').
---------------------------------------------------------------------------
Besides the requirement that the standards be maximum feasible for
the fleet in question and the model year in question, EPCA/EISA also
contain several other requirements, as follow.
1. Lead Time
EPCA requires that NHTSA prescribe new CAFE standards at least 18
months before the beginning of each model year.\394\ For amendments to
existing standards (as this NPRM proposes), EPCA requires that if the
amendments make an average fuel economy standard more stringent, at
least 18 months of lead time must be provided.\395\ Thus, if the first
year for which NHTSA is proposing to amend standards in this NPRM is MY
2024, NHTSA interprets this provision as requiring the agency to issue
a final rule covering MY 2024 standards no later than April 2022.
---------------------------------------------------------------------------
\394\ 49 U.S.C. 32902(a) (2007).
\395\ 49 U.S.C. 32902(g)(2) (2007).
---------------------------------------------------------------------------
2. Separate Standards for Cars and Trucks, and Minimum Standards for
Domestic Passenger Cars
As mentioned above, EPCA requires NHTSA to set separate standards
for passenger cars and light trucks for each model year.\396\ NHTSA has
long interpreted this requirement as preventing the agency from setting
a single combined CAFE standard for cars and trucks together, based on
the plain language of the statute. 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
characteristics.
---------------------------------------------------------------------------
\396\ 49 U.S.C. 32902(b)(1) (2007).
---------------------------------------------------------------------------
EPCA, as amended by EISA, also requires another separate standard
to be set for domestically-manufactured \397\ passenger cars. Unlike
the generally-applicable standards for passenger cars and light trucks
described above, the compliance obligation of the minimum domestic
passenger car standard (MDPCS for brevity) 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 model year, which projection shall be
published in the Federal Register when the standard for that model year
is promulgated in accordance with 49 U.S.C. 32902(b).\398\
---------------------------------------------------------------------------
\397\ 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 the 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 model year.
\398\ 49 U.S.C. 32902(b)(4) (2007).
---------------------------------------------------------------------------
Since that requirement was promulgated, the ``92 percent'' has
always been greater than 27.5 mpg, and foreseeably will continue to be
so in the future. While NHTSA published 92 percent MDPCSs for MYs 2024-
2026 at 49 CFR 531.5(d) as part of the 2020 final rule, the statutory
language is clear that
[[Page 49789]]
the MDPCS must be determined at the time an overall passenger car
standards is promulgated and published in the Federal Register. Thus,
any time NHTSA establishes or changes a passenger car standard for a
model year, the MDPCS must also be evaluated or re-evaluated and
established accordingly.
As in the 2020 final rule, NHTSA recognizes industry concerns that
actual total passenger car fleet standards have differed significantly
from past projections, perhaps more so when the agency has projected
significantly into the future. In that final rule, because the
compliance data showed that the standards projected in 2012 were
consistently more stringent than the actual standards, by an average of
1.9 percent. NHTSA stated that this difference indicated 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.\399\
---------------------------------------------------------------------------
\399\ See 85 FR at 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 MYs 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 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 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 2021-2026 timeframe to what had happened with the MDPCS over the
preceding model years, 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 model year, and
applied an offset based on the historical 1.9 percent difference
identified for MYs 2011-2018.
For this proposal, recognizing that we are proposing to increase
stringency considerably over the baseline standards and that civil
penalties have also recently increased, NHTSA remains concerned that
the MDPCS may pose a significant challenge to certain manufacturers. To
that end, NHTSA is proposing to retain the 1.9 percent offset for the
MDPCS for MYs 2024-2026, which we have appropriately recalculated based
on the current projections for passenger cars based on the current
analysis fleet. Table VI-1 shows the calculation values used to
determine the total passenger car fleet fuel economy value for each
model year for the preferred alternative.
BILLING CODE 4910-59-P
[GRAPHIC] [TIFF OMITTED] TP03SE21.175
Using this approach, the MDPCS under each regulatory alternative
would thus be as shown in Table VI-2.
[[Page 49790]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.176
NHTSA is also seeking comment on another approach to offsetting the
MDPCS. Recognizing that the analysis supporting this proposal does not
attempt to project how vehicle footprints may change in the future, nor
how that might affect the average fuel economy of passenger cars sold
in the U.S., NHTSA could instead attempt to make such a projection
explicitly.
Examination of the average footprints of passenger cars sold in the
U.S. from 2008, when EPA began reporting footprint data, to 2020
indicates a clear and statistically significant trend of gradually
increasing average footprint (Figure VI-1). The average annual increase
in passenger car footprint, estimated by ordinary least squares,
indicates that the passenger car footprints increased by an average of
0.1206 square feet annually over the 2008-2020 period. The estimated
average increase is statistically significant at the 0.000001 level,
with a 95 percent confidence interval of (0.0929, 0.1483).
[GRAPHIC] [TIFF OMITTED] TP03SE21.177
The alternate method for calculating an offset to the MDPCS would
be three steps, as follows:
1. Starting from the average footprint of passenger cars in 2020 as
reported by EPA, add 0.1206 square feet per year through 2026.
2. Calculate the estimated fuel economy of passenger cars using the
average projected footprint numbers calculated in step 1 and the
footprint functions that are the passenger car standards for the
corresponding model year, which then become ``the Secretary's projected
passenger car fuel economy numbers.''
3. Apply the 92 percent factor to calculate the MDPCS for 2024,
2025, and 2026.
The results of this approach are shown in Table VI-3.
[GRAPHIC] [TIFF OMITTED] TP03SE21.178
[[Page 49791]]
Comparing all of these, Table VI-4 shows (1) the unadjusted 92
percent MDPCS for MYs 2024-2026, (2) the proposed 1.9 percent-offset
MDPCS for MYs 2024-2026, and (3) the alternate approach offset MDPCS
for MYs 2024-2026.
[GRAPHIC] [TIFF OMITTED] TP03SE21.179
BILLING CODE 4910-59-C
While the CAFE Model analysis underlying this proposal, the PRIA,
and the Draft SEIS does not reflect an offset to the unadjusted 92
percent MDPCS, separate analysis that does reflect the change
demonstrates that doing so does not change estimated impacts of any of
the regulatory alternatives under consideration, despite the mpg values
being slightly different as shown in Table VI-4.
NHTSA seeks comment on the discussion above. To be clear, the
agency also seeks comment on whether to apply the MDPCS without any
modifier.
3. Attribute-Based and Defined by a Mathematical Function
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.'' \400\ Historically, NHTSA has based
standards on vehicle footprint, and proposes to continue to do so for
the reasons described in Section III.B of this preamble and Chapter 1
of the accompanying TSD. As in previous rulemakings, NHTSA is proposing
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. These footprint curves are discussed in more detail
in Section III.B and TSD Chapter 1. NHTSA seeks comment in Section
III.B both on the continued use of footprint as the relevant attribute
and on the continued use of the constrained linear curve shapes.
---------------------------------------------------------------------------
\400\ 49 U.S.C. 32902(b)(3)(A) (2007).
---------------------------------------------------------------------------
4. Number of Model Years for Which Standards May Be Set at a Time
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, model years.'' \401\ In this NPRM, NHTSA is proposing
to set CAFE standards for three model years, MYs 2024-2026. This
proposal fits squarely within the plain language of the statute.
---------------------------------------------------------------------------
\401\ 49 U.S.C. 32902(b)(3)(B) (2007).
---------------------------------------------------------------------------
5. Maximum Feasible Standards
As discussed above, EPCA requires NHTSA to consider four factors in
determining what levels of CAFE standards would be maximum feasible.
NHTSA presents in the sections below its understanding of the meanings
of those four factors.
(a) Technological Feasibility
``Technological feasibility'' refers to whether a particular method
of improving fuel economy is available for deployment in commercial
application in the model year 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 model/configuration, as well as the need to estimate
realistically the cost and fuel
[[Page 49792]]
economy impacts of each technology as applied to different vehicle
models/configurations. 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.\402\
---------------------------------------------------------------------------
\402\ 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.\403\ 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
`technological 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.'' \404\ NHTSA further stated
that ``. . . as the `maximum feasible' balancing may vary depending on
the circumstances at hand for the model year in which the standards are
set, the extent to which technological feasibility is simply met or
plays a more dynamic role may also shift.'' \405\ For purposes of this
proposal covering standards for MYs 2024-2026, NHTSA is certain that
sufficient technology exists to meet the standards--even for the most
stringent regulatory alternative. As will be discussed further below,
for this proposal, the question is more likely rather, given that the
technology exists, how much of it should be required to be added to new
cars and trucks in order to conserve more energy, and how to balance
that objective against the additional cost of adding that technology.
---------------------------------------------------------------------------
\403\ See 77 FR at 63015 (Oct. 12, 2012).
\404\ Id.
\405\ Id.
---------------------------------------------------------------------------
(b) 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.'' \406\ 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:
---------------------------------------------------------------------------
\406\ 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 will raise per-vehicle cost more than
we believe consumers are likely to accept, which could negatively
impact sales and employment in this 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. Elsewhere in this preamble, we seek comment
specifically on consumer valuation of fuel economy.
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 \407\ 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 responses 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.
---------------------------------------------------------------------------
\407\ 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. Many years ago, prior to the MYs 2005-2007
rulemaking under the non-attribute-based (fixed value) CAFE standards,
NHTSA sought to ensure the economic practicability of standards in part
by setting them at or near the capability of the ``least capable
manufacturer'' with a significant share of the market, i.e., typically
the manufacturer whose fleet mix was, on average, the largest and
heaviest, generally having the highest capacity and capability so as
not to limit the availability of those types of vehicles to consumers.
NHTSA rejected the ``least capable manufacturer'' approach several
rulemakings ago and no longer believes that it is 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, it seems 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.
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 significant, but not dispositive,
factor in the past for NHTSA's consideration of economic
practicability. Executive Order 12866, as amended by Executive Order
13563, states that agencies should ``select, in choosing among
alternative regulatory approaches, those approaches that maximize net
benefits . . .'' In practice, however, agencies, including NHTSA, must
consider that the modeling of net benefits does not capture all
considerations relevant to economic practicability. Therefore, as in
past rulemakings, NHTSA is considering net societal impacts, net
consumer impacts,
[[Page 49793]]
and other related elements in the consideration of economic
practicability. That said, it is well within the agency's discretion to
deviate from the level at which modeled net benefits are maximized if
the agency concludes that the level would not represent the maximum
feasible level for future CAFE standards. 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.
(c) 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 average fuel economy. 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 \408\ until recently, the effects of
such compliance on fuel economy capability over the history of the CAFE
program have been negative ones. For example, safety standards that
have the effect of increasing vehicle weight thereby lower fuel economy
capability, thus decreasing the level of average fuel economy that
NHTSA can determine to be feasible. NHTSA has also accounted for EPA's
``Tier 3'' standards for criteria pollutants in its estimates of
technology effectiveness in this proposal, and State emissions
standards (like California's) that address the tailpipe NOX,
NMOG, and CO emissions that occur during cold start.\409\
---------------------------------------------------------------------------
\408\ 43 FR 63184, 63188 (Dec. 15, 1977). See also 42 FR 33534,
33537 (Jun. 30, 1977).
\409\ For most ICE vehicles on the road today, the majority of
tailpipe NOX, NMOG, and CO emissions occur during ``cold
start,'' before the three-way catalyst has reached the very high
temperature (e.g., 900-1000 [deg]F) 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, tailpipe smog standards require the catalyst to be
brought to temperature extremely quickly, 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
Autonomie model documentation.
---------------------------------------------------------------------------
In other cases, the effect of other motor vehicle standards of the
Government 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 ``To 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.'' \410\ 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].''
\411\ 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 CO2 standards applicable to light-duty
vehicles 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 endeavors to create standards that meet our statutory obligations
and still avoid requiring manufacturers to build multiple fleets of
vehicles for the U.S. market.\412\ As in 2020, NHTSA has continued to
do all of these things with this proposal.
---------------------------------------------------------------------------
\410\ 77 FR 62624, 62669 (Oct. 15, 2012).
\411\ Id.
\412\ 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.'').
---------------------------------------------------------------------------
Similarly, NHTSA has considered and accounted for California's ZEV
mandate (and its adoption by the other Section 177 states) in
developing the baseline for this proposal. As discussed above, NHTSA
has not expressly accounted for California's GHG standards for the
model years subject to this rulemaking in the baseline analysis for
this proposal,\413\ but seeks comment on this approach for the final
rule. NHTSA notes again that no final decision has yet been made on the
CAA waiver for California.
---------------------------------------------------------------------------
\413\ As discussed elsewhere, however, NHTSA has sought to
account in the baseline for the California Framework Agreement with
BMW, Ford, Honda, VWA, and Volvo.
---------------------------------------------------------------------------
(d) 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.''
\414\
---------------------------------------------------------------------------
\414\ 42 FR 63184, 63188 (Dec. 15, 1977).
---------------------------------------------------------------------------
(1) 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 U.S. Energy Information Administration's (EIA)
Annual Energy Outlook (AEO) for 2021. Federal government agencies
generally use EIA's price projections in their assessment of future
energy-related policies.
In 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 proposed CAFE standards. In the
analysis supporting this proposal, NHTSA considers the energy
consumption and resulting emissions from the entire on-road fleet,
which already contains a number of plug-in hybrid and fully electric
vehicles. Higher CAFE standards encourage manufacturers to improve fuel
economy; concurrently, manufacturers will foreseeably seek to continue
to maximize profit (or minimize compliance cost), and some reliance on
electrification is a viable strategy for some manufacturers, even
though NHTSA does not consider it in determining maximum feasible CAFE
[[Page 49794]]
stringency. Under the more stringent CAFE alternatives in this
proposal, we see a greater reliance on electrification technologies in
the analysis in the years following the explicitly-regulated model
years, even though internal combustion engines continue to be the most
common powertrain across the industry in the action years of this
proposal.
While the current national average electricity price is
significantly higher than that of gasoline, on an energy equivalent
basis ($/MMBtu),\415\ electric motors convert energy into propulsion
much more efficiently than internal combustion engines. This means
that, even though the energy-equivalent prices of electricity are
higher, electric vehicles still produce fuel savings for their owners.
EIA also projects rising real gasoline prices over the next three
decades, while projecting real electricity prices to remain relatively
flat. As the reliance on electricity grows in the light-duty fleet,
NHTSA will continue to monitor the trends in electricity prices and
their implications for CAFE standards. Even if NHTSA is prohibited from
considering electrification as a technology during the model years
covered by the rulemaking, the consumer (and social) cost implications
of manufacturers otherwise switching to electrification may remain
relevant to the agency's considerations.
---------------------------------------------------------------------------
\415\ Source: AEO 2021, Table 3.
---------------------------------------------------------------------------
For now, gasoline is still the dominant fuel used in light-duty
transportation. As such, consumers, and the economy more broadly, are
subject to fluctuations in price that impact the cost of travel and,
consequently, the demand for mobility. Over the last decade, the U.S.
has become a stabilizing force in the global oil market and our
reliance on imported petroleum has decreased steadily. The most recent
Annual Energy Outlook, AEO 2021, projects the U.S. to be a net exporter
of petroleum and other liquids through 2050 in the Reference Case. Over
the last decade, EIA projections of real fuel prices have generally
flattened in recognition of the changing dynamics of the oil market and
slower demand growth, both in the U.S. and in developing markets. For
example, the International Energy Agency projects that global demand
for gasoline is unlikely to ever return to its 2019 level (before the
pandemic).\416\ However, vehicles are long-lived assets and the long-
term price uncertainty of petroleum still represents a risk to
consumers, albeit one that has decreased in the last decade. Continuing
to reduce the amount of money consumers spend on vehicle fuel thus
remains an important consideration for the need of the U.S. to conserve
energy.
---------------------------------------------------------------------------
\416\ International Energy Agency, Oil 2021, (p. 30), https://iea.blob.core.windows.net/assets/1fa45234-bac5-4d89-a532-768960f99d07/Oil_2021-PDF.pdf.
---------------------------------------------------------------------------
(2) 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 left the
U.S. economically vulnerable.\417\ As recently as 2009, nearly half the
U.S. trade deficit was driven by petroleum,\418\ yet this concern has
been less critical in more recent CAFE actions, in part because other
factors besides petroleum consumption have been playing a bigger role
in the U.S. trade deficit.\419\ While transportation demand is expected
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 timeframe.
---------------------------------------------------------------------------
\417\ For the earliest discussion of this topic, see 42 FR
63184, 63192 (Dec. 15, 1977) (``A major reason for this need [to
reduce petroleum consumption] is that the importation of large
quantities of petroleum creates serious balance of payments and
foreign policy problems. The United States currently spends
approximately $45 billion annually for imported petroleum. But for
this large expenditure, the current large U.S. trade deficit would
be a surplus.'').
\418\ See, Today in Energy: Recent improvements in petroleum
trade balance mitigate U.S. trade deficit, U.S. Energy Information
Administration (July 21, 2014). Available at https://www.eia.gov/todayinenergy/detail.php?id=17191 and in the docket for this
rulemaking, NHTSA-2021-0053.
\419\ Consumer products are the primary drivers of the trade
deficit. In 2020, the U.S. imported $2.4 trillion in consumer goods,
versus $116.4 billion of petroleum, which is the lowest amount since
2002. The 2020 goods deficit of $904.9 billion was the highest on
record, while the 2020 petroleum surplus of $18.1 billion was the
first annual surplus on record. See U.S. Census Bureau, ``Annual
2020 Press Highlights,'' at census.gov/foreign-trade/statistics/highlights/AnnualPressHighlights.pdf, and available in the docket
for this rulemaking. While 2020 was an unusual year for U.S.
transportation demand, given the global pandemic, this is consistent
with existing trends in which consumer products imports
significantly outweigh oil imports.
---------------------------------------------------------------------------
That said, the U.S. continues to rely on oil imports, and NHTSA
continues to recognize 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.
(3) 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 increases in
its emissions from vehicle use. Fuel savings from CAFE standards also
necessarily result in lower emissions of CO2, the main
greenhouse gas 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 the National Environmental Policy Act
(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,\420\ 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 concepts in its CAFE NPRMs and prepared
its first environmental assessment addressing that subject.\421\ 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.\422\
---------------------------------------------------------------------------
\420\ 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).
\421\ 53 FR 33080, 33096 (Aug. 29, 1988).
\422\ 53 FR 39275, 39302 (Oct. 6, 1988).
---------------------------------------------------------------------------
NHTSA also considers environmental justice issues as part of the
environmental considerations under the need of the U.S. to conserve
energy, per Executive Order 12898, ``Federal Actions to Address
Environmental Justice in Minority Populations'' \423\ and DOT Order
5610.2(c), ``U.S. Department of Transportation Actions to Address
Environmental Justice in Minority Populations and Low-Income
Populations.'' \424\ The affected environment for environmental justice
is nationwide, with a focus on areas that
[[Page 49795]]
could contain minority and low-income communities 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.
---------------------------------------------------------------------------
\423\ 59 FR 629 (Feb. 16, 1994).
\424\ Department of Transportation Updated Environmental Justice
Order 5610.2(c) (May 14, 2021).
---------------------------------------------------------------------------
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 that
are 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 differentially exposed to air
pollution and differentially 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, 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.
In the SEIS, Chapters 3, 4, 5, and 8 discuss the connections
between oil production, distribution, and consumption, and their health
and environmental impacts.
All of the action alternatives considered in this proposal 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 somewhat more complicated, for a variety of reasons, as
discussed in Section VI.C, although over time and certainly over the
lifetimes of the vehicles that would be subject to this proposal, these
emissions are currently forecast to fall significantly.
As discussed above, while the majority of light-duty vehicles will
continue to be powered by internal combustion engines in the near- to
mid-term under all regulatory alternatives, the more stringent
alternatives do appear in the analysis to lead to greater
electrification in the mid- to longer-term. While NHTSA is prohibited
from considering electric vehicles in determining maximum feasible CAFE
levels, electric vehicles (which appear both in the agency's baseline
and which may be produced in model years following the period of
regulation as an indirect effect of more stringent standards, or in
response to other standards or to market demand) produce few to zero
tailpipe emissions, and thus contribute meaningfully to the
decarbonization of the transportation sector, in addition to having
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 those
associated with reduced tailpipe emissions, upstream electricity
production, minerals extraction for battery components, and ability to
charge an electric vehicle. The upstream environmental effects of
extraction and refining for petroleum are well-recognized; minerals
extraction and refining can also have significant downsides. As one
example of documentation of these effects, the United Nations
Conference on Trade and Development issued a report in July 2020
describing acid mine drainage and uranium-laced dust associated with
cobalt mines in the DRC, along with child labor concerns; considerable
groundwater consumption and dust issues that harm miners and indigenous
communities in the Andes; issues with fine particulate matter causing
human health effects and soil contamination in regions near graphite
mines; and so forth.\425\ NHTSA's SEIS discusses these and other
effects (such as production and end-of-life issues) in more detail, and
NHTSA will continue to monitor these issues going forward insofar as
CAFE standards may increase electrification levels even if NHTSA does
not expressly 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.
---------------------------------------------------------------------------
\425\ UNCTAD, ``Commodities at a Glance: Special issue on
strategic battery raw materials,'' No. 13, Geneva, 2020, at 46.
Available at https://unctad.org/system/files/official-document/ditccom2019d5_en.pdf and in the docket for this rulemaking, NHTSA-
2021-0053.
---------------------------------------------------------------------------
NHTSA carefully considered the environmental effects of this
proposal, both quantitative and qualitative, as discussed in the SEIS
and in Sections VI.C and VI.D.
(4) 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
caused by sudden increases in the global price of oil and its resulting
impact of fuel prices faced by U.S. consumers, and (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. Reducing U.S. consumption of crude oil
or refined petroleum products (by reducing motor
[[Page 49796]]
fuel use) can reduce these external costs.\426\
---------------------------------------------------------------------------
\426\ 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. These costs include (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 ensure 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. Council on Foreign
Relations, National Security Consequences of U.S. Oil Dependency,
Independent Task Force Report No. 58, October 2006. Available at
https://cdn.cfr.org/sites/default/files/report_pdf/0876093659.pdf
and in the docket for this rulemaking, NHTSA-2021-0053. Brown and
Huntington (2015) find that these six costs are either implicitly
incorporated in the welfare-theoretic analysis, are not
externalities, or cannot be quantified. Brown, Stephen and Hillard
Huntington, Evaluating U.S. oil security and import reliance, Energy
Policy 108, 2015, at 512-523. Available at https://www.sciencedirect.com/science/article/abs/pii/S0301421515000026 and
for hard copy review at DOT headquarters. To the extent that these
costs are externalities that cannot be quantified, the measured
security costs of U.S. reliance on imported oil will be understated.
---------------------------------------------------------------------------
Stephen Brown, who has published extensively on price shock and
foreign policy risks associated with U.S. oil consumption, stated in a
recent paper that:
Over the past few years, world oil market conditions have
changed considerably (with the United States importing much less
oil), new estimates of the probabilities of world oil supply
disruptions have become available, and new estimates of the response
of U.S. real GDP to oil supply shocks and the short-run elasticity
of oil demand have become available. These developments suggest that
it is time to update the estimates of the security costs of U.S. oil
consumption. The new estimates of the oil security premiums suggest
that U.S. oil security may have become less of an issue than it was
in the past, mostly as a result of new estimates of the short-run
elasticity of demand and the response of U.S. real GDP to oil price
shocks.\427\
---------------------------------------------------------------------------
\427\ Brown, Stephen. ``New Estimates of the security costs of
U.S. oil consumption,'' Energy Policy, Vol. 113, Feb. 2018, at 172.
Available at https://www.sciencedirect.com/science/article/abs/pii/S0301421517307413 and for hard copy review at DOT headquarters.
Brown notes that ``Because we have not observed a modern economy
with large oil supply disruptions, we have no reliable method to
quantify the effects of these disruptions,'' and ``The result could
be an average of old and new results or estimation problems and a
poor fit.'' \428\ Geopolitical risk can still affect global oil
prices, of course, because oil is a global market, and thus can
affect U.S. oil prices, although possibly by less than in the
past.\429\ The U.S. still maintains a military presence in certain
parts of the world to help secure global access to petroleum
supplies. Chapter 6.2.4 of the TSD discusses this topic in more
detail. Brown concludes that:
---------------------------------------------------------------------------
\428\ Id. at 181.
\429\ Also in 2018, Beccue, Huntington, Leiby, and Vincent
reported on their findings of an expert panel on oil market
disruption risks and likelihoods, and stated that based on these
findings, during the period of 2016-2025, ``It is very likely that a
disruption greater than 2 MMBD will occur (81%). However, it is
unlikely that disruptions greater than 15 MMBD will occur (1%).''
They further state that ``. . . experts in the current study expect
that both gross shocks and excess capacity will be lower than
before, resulting in similar net disruptions [to what was estimated
in 2005]. Although turmoil remains high in these countries with the
ongoing Iraq war, tensions between Iran and its Arab neighbors, and
concern over the ability of terrorists to cut oil supply facilities,
these conditions do not produce larger oil market disruptions.''
They conclude that ``In general, this panel of energy security
experts has concluded that current world events and energy markets
have increased the likelihood of oil disruptions since 1996 but
demonstrated a similar risk profile compared to the 2005 period.
Moreover, their assessments indicate that lower oil price paths make
net disruptions of any given size more likely.'' Beccue et al., ``An
updated assessment of oil market disruption risks,'' Energy Policy,
Vol. 115, Apr. 2018, at 456. Available at https://www.sciencedirect.com/science/article/abs/pii/S0301421517308285 and
for hard copy review at DOT headquarters.
Nonetheless, only the highest estimates of the oil security
premiums suggest that U.S. oil security is nearly an equally
important issue to the environmental costs of oil use. The mid-
estimates from the model that may best represent how the world oil
market and the U.S. economy will respond to world oil supply
disruptions of various sizes . . . find U.S. consumption of imported
or domestic oil does yield important security costs, but those costs
are much lower than the estimated environmental costs of oil use.
Consistent with Brown and Huntington (2013), the substitution of
domestic oil for imported oil only slightly improves U.S. oil
security. Oil conservation is more effective than increased domestic
oil production at improving U.S. oil security.\430\
---------------------------------------------------------------------------
\430\ Brown, 2018, at 182.
NHTSA agrees both that oil conservation improves U.S. oil security,
and that the environmental costs of oil use are intertwined with the
security costs of oil use in some ways as climate change destabilizes
traditional geopolitical power structures over time. The effect of
climate change on natural resources inevitably has security
implications--population changes and shifts have already been forced in
some countries, which can create social and security effects at all
geopolitical levels--local, national, regional, and global. 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.
As standards and market demand move the U.S. light-duty vehicle
fleet toward electrification, different potential foreign policy
implications arise. Most vehicle electrification is enabled by lithium-
ion batteries. Lithium-ion battery global value chains have several
phases: Sourcing (mining/extraction); processing/refining; cell
manufacturing; battery manufacturing; installation in an EV; and
recycling.\431\ Because lithium-ion battery materials have a wide
global diversity of origin, accessing them can pose varying
geopolitical challenges.\432\ The U.S. International Trade Commission
(USITC) recently summarized 2018 data from the U.S. Geological Survey
on the production/sourcing of the four key lithium-ion battery
materials, as shown in Table VI-5.
---------------------------------------------------------------------------
\431\ Scott, Sarah, and Robert Ireland, ``Lithium-Ion Battery
Materials for Electric Vehicles and their Global Value Chains,''
Office of Industries Working Paper ID-068, U.S. International Trade
Commission, June 2020, at 7. Available at https://www.usitc.gov/publications/332/working_papers/gvc_overview_scott_ireland_508_final_061120.pdf and in the docket
for this rulemaking, NHTSA-2021-0053.
\432\ Id. at 8.
---------------------------------------------------------------------------
[[Page 49797]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.180
Of these sources, the USITC notes that while ``lithium has
generally not faced political instability risks,'' ``Because of the
[Democratic Republic of Congo's] ongoing political instability, as well
as poor labor conditions, sourcing cobalt faces significant
geopolitical challenges.'' \434\ Nickel is also used extensively in
stainless steel production, and much of what is produced in Indonesia
and the Philippines is exported to China for stainless steel
manufacturing.\435\ Obtaining graphite for batteries does not currently
pose geopolitical obstacles, but the USITC notes that Turkey has great
potential to become a large graphite producer, which would make
stability there a larger concern.\436\
---------------------------------------------------------------------------
\433\ Id., citing U.S. Geological Survey, Mineral Commodity
Summaries, Feb. 2019.
\434\ Id. at 8, 9.
\435\ Id at 9.
\436\ Id.
---------------------------------------------------------------------------
For materials processing and refining, China is the largest
importer of unprocessed lithium, which it then transforms into
processed or refined lithium,\437\ the leading producer of refined
cobalt (with Finland a distant second),\438\ one of the leading
producers of primary nickel products (along with Indonesia, Japan,
Russia, and Canada) and one of the leading refiners of nickel into
nickel sulfate, the chemical compound used for cathodes in lithium-ion
batteries,\439\ and one of the leading processors of graphite intended
for use in lithium-ion batteries as well.\440\ In all regions,
increasing attention is being given to vertical integration in the
lithium-ion battery industry from material extraction, mining and
refining, battery materials, cell production, battery systems, reuse,
and recycling. The United States is lagging in upstream capacity;
although the U.S. has some domestic lithium deposits, it has very
little capacity in mining and refining any of the key raw materials. As
mentioned elsewhere, however, there can be benefits and drawbacks in
terms of environmental consequences associated with increased mining,
refining, and battery production.
---------------------------------------------------------------------------
\437\ Id.
\438\ Id. at 10.
\439\ Id.
\440\ Id.
---------------------------------------------------------------------------
China and the European Union (EU) are also major consumers of
lithium-ion batteries, along with Japan, Korea, and others. Lithium-ion
batteries are used not only in light-duty vehicles, but in many
ubiquitous consumer goods, and are likely to be used eventually in
other forms of transportation as well. Thus, securing sufficient
batteries to enable large-scale shifts to electrification in the U.S.
light-duty vehicle fleet may face new issues as vehicle companies
compete with other new sectors. NHTSA will continue to monitor these
issues going forward.
President Biden has already issued an Executive Order on
``America's Supply Chains,'' aiming to strengthen the resilience of
America's supply chains, including those for automotive batteries.\441\
Reports are to be developed within one year of issuance of the
Executive Order, and NHTSA will monitor these findings as they develop.
---------------------------------------------------------------------------
\441\ Executive Order 14017, ``America's Supply Chains,'' Feb.
24, 2021. 86 FR 11849 (Mar. 1, 2021).
---------------------------------------------------------------------------
(e) 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 model year, 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.\442\ NHTSA cannot consider 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 cannot consider the
use of alternative fuels by dual fueled automobiles, nor the fuel
economy (i.e., the availability) of dedicated alternative fueled
automobiles--including battery-electric vehicles--in any model year.
EPCA encourages the production of alternative fuel vehicles by
specifying that their fuel economy is to be determined using a special
calculation procedure that results in those vehicles being assigned a
higher equivalent fuel economy level than they actually achieve.
---------------------------------------------------------------------------
\442\ 49 U.S.C. 32902(h).
---------------------------------------------------------------------------
The effect of the prohibitions against considering these statutory
flexibilities in setting the CAFE standards is that the flexibilities
remain voluntarily-employed measures. If NHTSA were instead to assume
manufacturer use of those flexibilities in setting new standards (as
NHTSA does in the ``EIS analysis,'' but not the ``standard setting
analysis''), compliance with higher standards would appear more cost-
effective and, potentially, more feasible, which would thus effectively
require manufacturers to use those flexibilities if NHTSA determined
that standards should be more stringent. By keeping NHTSA from
including them in our stringency determination, the provision ensures
that those statutory credits
[[Page 49798]]
remain true compliance flexibilities. However, the flip side of the
effect described above is that preventing NHTSA from assuming use of
dedicated alternative fuel vehicles for compliance makes it more
difficult for the CAFE program to facilitate a complete transition of
the U.S. light-duty fleet to full electrification.
In contrast, for the non-statutory fuel economy improvement value
program that NHTSA developed by regulation, NHTSA does not consider
these fuel economy adjustments subject to the 32902(h) prohibition on
considering flexibilities. The statute is very clear as to which
flexibilities are not to be considered. When the agency has introduced
additional flexibilities such as A/C efficiency and ``off-cycle''
technology fuel improvement values, NHTSA has considered those
technologies as available in the analysis. Thus, this analysis includes
assumptions about manufacturers' use of those technologies, as detailed
in Chapter 3.8 of the accompanying TSD.
NHTSA notes that one of the recommendations in the 2021 NAS Report
was for Congress to ``amend the statute to delete the [32902(h)]
prohibition on considering the fuel economy of dedicated alternative
fueled vehicles in setting CAFE standards.'' \443\ Recognizing that
changing statutory text is Congress' affair and not NHTSA's, the
committee further recommended that if Congress does not change the
statute, NHTSA should consider adding another attribute to the fuel
economy standard function, like ``the expected market share of ZEVs in
the total U.S. fleet of new light-duty vehicles--such that the
standards increase as the share of ZEVs in the total U.S. fleet
increases.'' \444\ NHTSA discusses this recommendation further in
Section III.B.
---------------------------------------------------------------------------
\443\ 2021 NAS Report, Summary Recommendation 5.
\444\ Id.
---------------------------------------------------------------------------
While NHTSA does not consider the prohibited items in its standard-
setting analysis or for making its tentative decision about what levels
of standards would be maximum feasible, NHTSA notes that it is informed
by the ``EIS'' analysis presented in the PRIA. The EIS analysis does
not contain these restrictions, and therefore accounts for credit
availability and usage, and manufacturers' ability to employ
alternative fueled vehicles, for purpose of conformance with E.O. 12866
and NEPA regulations. Under the EIS analysis, compliance generally
appears less costly. For example, this EIS analysis shows
manufacturers' costs averaging about $1,070 in MY 2029 under the
proposed standards, as compared to the $1,175 shown by the standard
setting analysis. Again, however, for purposes of tentatively
determining maximum feasible CAFE levels, NHTSA considers only the
standard setting analysis shown in the NPRM, consistent with Congress'
direction.
(f) 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.\445\ In this proposal, NHTSA has considered the safety
effects discussed in Section V of this preamble and in Chapter 5 of the
accompanying PRIA. NHTSA discusses its consideration of these effects
in Section VI.D.
---------------------------------------------------------------------------
\445\ 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 light truck CAFE rulemaking).
---------------------------------------------------------------------------
B. Administrative Procedure Act
The Administrative Procedure Act 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
the 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.'' \446\
---------------------------------------------------------------------------
\446\ Burlington Truck Lines, Inc. v. United States, 371 U.S.
156, 168 (1962).
---------------------------------------------------------------------------
Statutory interpretations included in an agency's rule are subject
to the two-step analysis of Chevron, U.S.A. v. Natural Resources
Defense Council.\447\ Under step one, where a statute ``has directly
spoken to the precise question at issue,'' id. at 842, the court and
the agency ``must give effect to the unambiguously expressed intent of
Congress.'' \448\ If the statute is silent or ambiguous regarding the
specific question, the court proceeds to step two and asks ``whether
the agency's answer is based on a permissible construction of the
statute.'' \449\ The APA also requires that agencies provide notice and
comment to the public when proposing regulations,\450\ as NHTSA is
doing in this proposal.
---------------------------------------------------------------------------
\447\ 467 U.S. 837 (1984).
\448\ Id. at 843.
\449\ Id.
\450\ 5 U.S.C. 553.
---------------------------------------------------------------------------
NHTSA recognizes that this proposal, like the 2020 final rule, is
reconsidering standards previously promulgated. NHTSA, like any other
Federal agency, is afforded an opportunity to reconsider prior views
and, when warranted, to adopt new positions. Indeed, as a matter of
good governance, agencies should revisit their positions when
appropriate, especially to ensure that their actions and regulations
reflect legally sound interpretations of the agency's authority and
remain consistent with the agency's views and practices. As a matter of
law, ``an Agency is entitled to change its interpretation of a
statute.'' \451\ Nonetheless, ``[w]hen an Agency adopts a materially
changed interpretation of a statute, it must in addition provide a
`reasoned analysis' supporting its decision to revise its
interpretation.'' \452\
---------------------------------------------------------------------------
\451\ Phoenix Hydro Corp. v. FERC, 775 F.2d 1187, 1191 (D.C.
Cir. 1985).
\452\ Alabama Educ. Ass'n v. Chao, 455 F.3d 386, 392 (D.C. Cir.
2006) (quoting Motor Vehicle Mfrs. Ass'n of U.S., Inc. v. State Farm
Mut. Auto. Ins. Co., 463 U.S. 29, 57 (1983)); see also Encino
Motorcars, LLC v. Navarro, 136 S Ct. 2117, 2125 (2016) (``Agencies
are free to change their existing policies as long as they provide a
reasoned explanation for the change.'') (citations omitted).
---------------------------------------------------------------------------
``Changing policy does not, on its own, trigger an especially
`demanding burden of justification.' '' \453\ Providing a reasoned
explanation ``would ordinarily demand that [the Agency] display
awareness that it is changing position.'' \454\ Beyond that, however,
``[w]hen an agency changes its existing position, it `need not always
provide a more detailed justification than what would suffice for a new
policy created on a blank slate.' '' \455\ While the agency ``must show
that there are good reasons for the new policy,'' the agency ``need not
demonstrate to a court's satisfaction that the reasons for the new
policy are
[[Page 49799]]
better than the reasons for the old one.'' \456\ ``[I]t suffices that
the new policy is permissible under the statute, that there are good
reasons for it, and that the Agency believes it to be better, which the
conscious change of course adequately indicates.'' \457\ For instance,
``evolving notions'' about the appropriate balance of varying policy
considerations constitute sufficiently good reasons for a change in
position.\458\ Moreover, it is ``well within an Agency's discretion''
to change policy course even when no new facts have arisen: Agencies
are permitted to conduct a ``reevaluation of which policy would be
better in light of the facts,'' without ``rely[ing] on new facts.''
\459\
---------------------------------------------------------------------------
\453\ See Mingo Logan Coal Co. v. EPA, 829 F.3d 710, 718 (D.C.
Cir. 2016) (quoting Ark Initiative v. Tidwell, 816 F.3d 119, 127
(D.C. Cir. 2016)).
\454\ FCC v. Fox Television Stations, Inc. 556 U.S. 502, 515
(2009) (emphasis in original) (``An agency may not, for example,
depart from a prior policy sub silentio or simply disregard rules
that are still on the books.'').
\455\ Encino Motorcars, LLC, 136 S Ct. at 2125-26 (quoting Fox
Television Stations, Inc. 556 U.S. at 515).
\456\ Fox Television Stations, Inc., 556 U.S. at 515 (emphasis
in original).
\457\ Id. (emphasis in original).
\458\ N. Am.'s Bldg. Trades Unions v. Occupational Safety &
Health Admin., 878 F.3d 271, 303 (D.C. Cir. 2017) (quoting the
agency's rule).
\459\ Nat'l Ass'n of Home Builders v. EPA, 682 F.3d 1032, 1037-
38 (D.C. Cir. 2012).
---------------------------------------------------------------------------
To be sure, providing ``a more detailed justification'' is
appropriate in some cases. ``Sometimes [the agency] must [provide a
more detailed justification than what would suffice for a new policy
created on a blank slate]--when, for example, its new policy rests upon
factual findings that contradict those which underlay its prior policy;
or when its prior policy has engendered serious reliance interests that
must be taken into account.'' \460\ This preamble, and the accompanying
TSD and PRIA, all provide extensive detail on the agency's updated
analysis, and Section VI.D contains the agency's explanation of how the
agency has considered that analysis and other relevant information in
tentatively determining that the proposed CAFE standards are maximum
feasible for MYs 2024-2026 passenger cars and light trucks.
---------------------------------------------------------------------------
\460\ See Fox Television Stations, Inc., 556 U.S. at 515 (2009).
---------------------------------------------------------------------------
C. National Environmental Policy Act
As discussed above, EPCA requires NHTSA to determine the level at
which to set CAFE standards for each model year 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 United States to conserve energy. The
National Environmental Policy Act (NEPA) directs that environmental
considerations be integrated into that process.\461\ To explore the
potential environmental consequences of this rulemaking action, NHTSA
has prepared a Supplemental Environmental Impact Statement (``SEIS'')
for this proposal.\462\ The purpose of an EIS is to ``provide full and
fair discussion of significant environmental impacts and [to] inform
decisionmakers and the public of the reasonable alternatives which
would avoid or minimize adverse impacts or enhance the quality of the
human environment.'' \463\
---------------------------------------------------------------------------
\461\ 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 1500-08.
\462\ Because this proposal revises CAFE standards established
in the 2020 final rule, NHTSA chose to prepare a SEIS to inform that
amendment of the MYs 2024-2026 standards. See the SEIS for more
details.
\463\ 40 CFR 1502.1.
---------------------------------------------------------------------------
When preparing an EIS, NEPA requires an agency to compare the
potential environmental impacts of its proposed action and a reasonable
range of alternatives. In the SEIS, NHTSA analyzed a No Action
Alternative and three action alternatives. The alternatives represent a
range of potential actions the agency could take, and they are
described more fully in Section IV of this preamble, Chapter 1 of the
TSD, and Chapter 2 of the PRIA. The 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.
To derive the direct and indirect impacts of the action
alternatives, NHTSA compared each action alternative to the No Action
Alternative, which reflects baseline trends that would be expected in
the absence of any further regulatory action. More specifically, the No
Action Alternative in the SEIS assumed that the CAFE standards set in
the 2020 final rule for MYs 2021-2026 passenger cars and light trucks
would remain in effect. In addition, the No Action Alternative also
includes several other actions that NHTSA believes will occur in the
absence of further regulatory action, as discussed in more detail in
Section IV above: (1) California's ZEV mandate; (2) the ``Framework
Agreements'' between California and BMW, Ford, Honda, VWA, and Volvo,
which NHTSA implemented by including EPA's baseline GHG standards
(i.e., those set in the 2020 final rule) and introducing more stringent
GHG target functions for those manufacturers; and (3) the assumption
that manufacturers will also make any additional fuel economy
improvements estimated to reduce owners' estimated average fuel outlays
during the first 30 months of vehicle operation by more than the
estimated increase in new vehicle price. The No Action Alternative
provides a baseline against which to compare the environmental impacts
of other alternatives presented in the SEIS.\464\
---------------------------------------------------------------------------
\464\ 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 analysis 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 National
Environmental Policy Act Regulations, 46 FR 18026 (Mar. 23, 1981).
---------------------------------------------------------------------------
For the SEIS, NHTSA analyzed three action alternatives,
Alternatives 1 through 3, which ranged from increasing CAFE stringency
for MY 2024 by 9.14 percent for passenger cars and 11.02 percent for
light trucks, and increase stringency in MYs 2025 and 2026 by 3.26
percent per year for both passenger cars and light trucks (Alternative
1) to increasing CAFE stringency for each year, for each fleet, at 10
percent per year (Alternative 3). The range of action alternatives, as
well as the No Action Alternative, encompass a spectrum of possible
standards NHTSA could determine was maximum feasible based on the
different ways the agency could weigh EPCA's four statutory factors.
Throughout the SEIS, estimated impacts were shown for all of these
action alternatives, as well as for the No Action Alternative. For a
more detailed discussion of the environmental impacts associated with
the alternatives, see Chapters 3-6 of the SEIS, as well as Section V of
this preamble.
NHTSA's SEIS 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, noise, and environmental justice.
The SEIS also describes how climate change resulting from global
greenhouse gas emissions (including CO2 emissions
attributable to the U.S. light-duty 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 SEIS, and the findings of that
analysis are summarized here.\465\
---------------------------------------------------------------------------
\465\ The impacts described in this section come from NHTSA's
SEIS, which is being publicly issued simultaneously with this NPRM.
As described above, the SEIS is based on ``unconstrained'' modeling
rather than ``standard setting'' modeling. NHTSA conducts modeling
both ways in order to reflect the various statutory requirements of
EPCA/EISA and NEPA. The preamble 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 this
preamble. However, NHTSA considers the impacts reported in the SEIS,
in addition to the other information presented in this preamble, the
TSD, and the PRIA, as part of its decision-making process.
---------------------------------------------------------------------------
[[Page 49800]]
As the stringency of the alternatives increases, total U.S.
passenger car and light truck fuel consumption for the period of 2020
to 2050 decreases. Total light-duty vehicle fuel consumption from 2020
to 2050 under the No Action Alternative is projected to be 3,510
billion gasoline gallon equivalents (GGE). Light-duty vehicle fuel
consumption from 2020 to 2050 under the action alternatives is
projected to range from 3,409 billion GGE under Alternative 1 to 3,282
billion GGE under Alternative 3. Under Alternative 2, light-duty
vehicle fuel consumption from 2020 to 2050 is projected to be 3,344
billion GGE. All of the action alternatives would decrease fuel
consumption compared to the No-Action Alternative, with fuel
consumption decreases that range from 100 billion GGE under Alternative
1 to 227 billion GGE under Alternative 3.
The relationship between stringency and criteria and air toxics
pollutant emissions is less straightforward, reflecting the complex
interactions among the tailpipe emissions rates of the various vehicle
types (passenger cars and light trucks, ICE vehicles and EVs, older and
newer vehicles, etc.), the technologies assumed to be incorporated by
manufacturers in response to CAFE 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.
The air quality analysis in the SEIS identified the following
impacts on criteria air pollutants.
For all criteria pollutants in 2025, emissions increase slightly
under the action alternatives compared to the No-Action Alternative.
The emission increases generally get larger (although they are still
small) from Alternative 1 through Alternative 3 (the most stringent
alternative in terms of required miles per gallon). This temporary
increase is largely due to new vehicle prices increasing in the short-
term, which slightly slows new-vehicle sales and encourages consumers
to buy used vehicles instead or retain existing vehicles for longer. As
the analysis timeframe progresses, the new, higher fuel-economy
vehicles become used vehicles, and the impacts of the standards change
direction. In 2025, across all criteria pollutants and action
alternatives, the smallest increase in emissions is 0.01 percent for
VOCs under Alternative 2; the largest increase is 0.6 percent and
occurs for SO2 under Alternative 3. We underscore that these
are fractions of a single percent.
In 2035 and 2050, emissions of CO, NOX,
PM2.5, and VOCs generally decrease under the action
alternatives compared to the No-Action Alternative, except for CO in
2035 under Alternative 1 (0.07 percent increase) and NOX in
2035 under Alternative 3 (0.5 percent increase) (again, these are
fractions of a single percent), with the more stringent alternatives
having the largest decreases, except for NOX and
PM2.5 in 2035 (emissions decrease less or increase with more
stringent alternatives) and NOX in 2050 (emissions increase
under Alternative 3 relative to Alternative 2, due primarily to
slightly higher upstream emissions associated with greater
electrification rates). SO2 emissions generally increase
under the action alternatives compared to the No-Action Alternative
(except in 2035 under Alternative 1), with the more stringent
alternatives having the largest increases. 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. In 2035 and 2050, across all criteria
pollutants and action alternatives, the smallest decrease in emissions
is 0.03 percent and occurs for NOX under Alternative 2; the
largest decrease is 11.9 percent and occurs for VOCs under Alternative
3. The smallest increase in emissions is 0.07 percent and occurs for CO
under Alternative 1; the largest increase is 4.8 percent and occurs for
SO2 under Alternative 3.
The air quality analysis identified the following impacts on toxic
air pollutants.
Under each action alternative in 2025 compared to the No-Action
Alternative, increases in emissions would occur for all toxic air
pollutants by as much as 0.5 (half of 1) percent, except for DPM, for
which emissions would decrease by as much as 0.5 percent. For 2025, the
largest relative increases in emissions would occur for benzene and
1,3-butadiene, for which emissions would increase by as much as 0.5
percent. Percentage increases in emissions of acetaldehyde, acrolein,
and formaldehyde would be even smaller.
Under each action alternative in 2035 and 2050 compared to the No-
Action Alternative, decreases in emissions would occur for all toxic
air pollutants, except for acetaldehyde, acrolein, and 1,3-butadiene in
2035 under Alternative 1 where emissions would increase by 0.2 (one-
fifth of 1), 0.01, and 0.1 percent, respectively, with the more
stringent alternatives having the largest decreases, except for benzene
(emissions increase in 2035 under Alternative 3 relative to Alternative
2). The largest relative decreases in emissions would occur for
formaldehyde, for which emissions would decrease by as much as 10.3
percent. Percentage decreases in emissions of acetaldehyde, acrolein,
benzene, 1,3-butadiene, and DPM would be less.
The air quality analysis identified the following health impacts.
In 2025, Alternative 3 would result in slightly increased adverse
health impacts (mortality, acute bronchitis, respiratory emergency room
visits, and other health effects) nationwide compared to the No-Action
Alternative as a result of increases in emissions of NOX,
PM2.5, and SO2. Alternative 2 would also result
in slightly increased adverse health impacts from mortality and non-
fatal heart attacks due to increases in NOX,
PM2.5, and SO2 emissions, while Alternative 1
would result in decreased adverse health impacts. The more stringent
alternatives are associated with the largest increases in adverse
health impacts, or the smallest decreases in impacts, relative to the
No-Action Alternative. Again, in the short-term, these slight changes
in health impacts are projected under the action alternatives as the
result of increases in the prices of new vehicles slightly delaying
sales of new vehicles and encouraging more VMT in older vehicles
instead, but this trend shifts over time as higher fuel-economy new
vehicles become used vehicles and older vehicles are removed from the
fleet.
In 2035 and 2050, all action alternatives would result in decreased
[[Page 49801]]
adverse health impacts nationwide compared to the No-Action Alternative
as a result of general decreases in emissions of NOX,
PM2.5, and DPM. The decreases in adverse health impacts get
larger from Alternative 1 to Alternative 3.
In terms of climate effects, all action alternatives would decrease
U.S. passenger car and light truck fuel consumption compared with the
No-Action Alternative, resulting in reductions in the anticipated
increases in global CO2 concentrations, temperature,
precipitation, and sea level, and increases in ocean pH that would
otherwise occur. The impacts of the action alternatives on 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.
The alternatives would have the following impacts related to GHG
emissions.
Passenger cars and light trucks are projected to emit 89,600
million metric tons of carbon dioxide (MMTCO2) from 2021
through 2100 under the No-Action Alternative. Alternative 1 would
decrease these emissions by 5 percent through 2100. Alternative 3 would
decrease these emissions by 10 percent through 2100. Emissions would be
highest under the No-Action Alternative, and emission reductions would
increase from Alternative 1 to Alternative 3.
Compared with total projected CO2 emissions of 984
MMTCO2 from all passenger cars and light trucks under the
No-Action Alternative in the year 2100, the action alternatives are
expected to decrease CO2 emissions from passenger cars and
light trucks in the year 2100 from 6 percent under Alternative 1 to 12
percent under Alternative 3.
The emission reductions in 2025 compared with emissions under the
No-Action Alternative are approximately equivalent to the annual
emissions from 1,284,000 vehicles under Alternative 1 to 2,248,000
vehicles under Alternative 3. For scale, a total of 253,949,000
passenger cars and light trucks are projected to be on the road in 2025
under the No-Action Alternative.
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 Global Change Assessment Model Reference
Scenario to represent the Reference Case emissions scenario (i.e.,
future global emissions assuming no comprehensive global actions to
mitigate GHG emissions).
Estimated CO2 concentrations in the atmosphere for 2100
would range from 788.33 pollutant per million parts (ppm) under
Alternative 3 to approximately 789.11 ppm under the No-Action
Alternative, indicating a maximum atmospheric CO2 decrease
of approximately 0.77 ppm compared to the No-Action Alternative.
Atmospheric CO2 concentration under Alternative 1 would
decrease by 0.37 ppm compared with the No-Action Alternative.
Global mean surface temperature is projected to increase by
approximately 3.48 [deg]C (6.27 [deg]F) under the No-Action Alternative
by 2100. Implementing the most stringent alternative (Alternative 3)
would decrease this projected temperature rise by 0.003 [deg]C (0.006
[deg]F), while implementing Alternative 1 would decrease projected
temperature rise by 0.002 [deg]C (0.003 [deg]F).
Projected sea-level rise in 2100 ranges from a high of 76.28
centimeters (30.03 inches under the No-Action Alternative to a low of
76.22 centimeters (30.01 inches) under Alternative 3. Alternative 3
would result in a decrease in sea-level rise equal to 0.06 centimeter
(0.03 inch) by 2100 compared with the level projected under the No-
Action Alternative compared to a decrease under Alternative 1 of 0.03
centimeter (0.01 inch) compared with the No-Action Alternative.
Global mean precipitation is anticipated to increase by 5.85
percent by 2100 under the No-Action Alternative. Under the action
alternatives, this increase in precipitation would be reduced by 0.00
to 0.01 percent.
Ocean pH is anticipated to be 8.2180 under Alternative 3, about
0.0004 more than the No-Action Alternative. Under Alternative 1, ocean
pH in 2100 would be 8.2178, or 0.0002 more than the No-Action
Alternative.
The action alternatives 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.
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 the Intergovernmental Panel on
Climate Change (IPCC), U.S. Global Change Research Program (GCRP), the
U.S. Climate Change Science Program (CCSP), the National Research
Council, 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
proposal, the following impacts are likely to be beneficially affected
to some degree by reduced emissions from the action alternatives:
Impacts on freshwater resources could include changes in
rainfall and streamflow patterns, warming temperatures and reduced
snowpack, changes in water availability paired with increasing water
demand for irrigation and other needs, and decreased water quality from
increased algal blooms. Inland flood risk could increase in response to
increasing intensity of precipitation events, drought, changes in
sediment transport, and changes in snowpack and the timing of snowmelt.
Impacts on terrestrial and freshwater ecosystems could
include shifts in the range and seasonal migration patterns of species,
relative timing of species' life-cycle events, potential extinction of
sensitive species that are unable to adapt to changing conditions,
increases in the occurrence of forest fires and pest infestations, and
changes in habitat productivity due to increased atmospheric
concentrations of CO2.
Impacts on ocean systems, coastal regions, and low-lying
areas could include the loss of coastal areas due to inundation,
submersion, or erosion from sea-level rise and storm surge, with
increased vulnerability of the built environment and associated
economies. Changes in key habitats (e.g., increased temperatures,
decreased oxygen, decreased ocean pH, increased
[[Page 49802]]
salinization) and reductions in key habitats (e.g., coral reefs) may
affect the distribution, abundance, and productivity of many marine
species.
Impacts on food, fiber, and forestry could include
increasing tree mortality, forest ecosystem vulnerability, productivity
losses in crops and livestock, and changes in the nutritional quality
of pastures and grazing lands in response to fire, insect infestations,
increases in weeds, drought, disease outbreaks, or extreme weather
events. Increased concentrations of CO2 in the atmosphere
can also stimulate plant growth to some degree, a phenomenon known as
the CO2 fertilization effect, but the impact varies by
species and location. Many marine fish species could migrate to deeper
or colder water in response to rising ocean temperatures, and global
potential fish catches could decrease. Impacts on food and agriculture,
including yields, food processing, storage, and transportation, could
affect food prices, socioeconomic conditions, and food security
globally.
Impacts on rural and urban areas could affect water and
energy supplies, wastewater and stormwater systems, transportation,
telecommunications, provision of social services, incomes (especially
agricultural), air quality, and safety. The impacts could be greater
for vulnerable populations such as lower-income populations,
historically underserved populations, some communities of color and
tribal and Indigenous communities, the elderly, those with existing
health conditions, and young children.
Impacts on human health could include increases in
mortality and morbidity due to excessive heat and other extreme weather
events, increases in respiratory conditions due to poor air quality and
aeroallergens, increases in water and food-borne diseases, increases in
mental health issues, and changes in the seasonal patterns and range of
vector-borne diseases. The most disadvantaged groups such as children,
the elderly, the sick, those experiencing discrimination, historically
underserved populations, some communities of color and tribal and
Indigenous communities, and low-income populations are especially
vulnerable and may experience disproportionate health impacts.
Impacts on human security could include increased threats
in response to adversely affected livelihoods, compromised cultures,
increased or restricted migration, increased risk of armed conflicts,
reduction in adequate essential services such as water and energy, and
increased geopolitical rivalry.
In addition to the individual impacts of climate change on various
sectors, compound events may occur more frequently. Compound events
consist of two or more extreme weather events occurring simultaneously
or in sequence when underlying conditions associated with an initial
event amplify subsequent events and, in turn, lead to more extreme
impacts. To the extent the action alternatives would result in
reductions in projected increases in global CO2
concentrations, this rulemaking would contribute to reducing the risk
of compound events.
NHTSA has considered the SEIS carefully in arriving at its
tentative conclusion that Alternative 2 is maximum feasible, as
discussed below. We seek comment on the SEIS associated with this NPRM.
D. Evaluating the EPCA Factors and Other Considerations To Arrive at
the Proposed Standards
Despite only one year having passed since the 2020 final rule,
enough has changed in the United States and in the world that
revisiting the CAFE standards for MYs 2024-2026 is reasonable and
appropriate. The global coronavirus pandemic, with all of its tragedy,
also demonstrated what happens to U.S. and global oil consumption (and
CO2 and other pollutant emissions) when driving demand
plummets. The Biden Administration committed itself in its earliest
moments to improving energy conservation and tackling climate change.
Nearly all auto manufacturers have announced forthcoming new advanced
technology, high-fuel-economy vehicle models, making strong public
commitments that mirror those of the Administration. Five major
manufacturers voluntarily bound themselves to stricter GHG national-
level requirements as part of the California Framework agreement. While
some facts on the ground remain similar to what was before NHTSA in the
prior analysis--gas prices remain relatively low in the U.S., for
example, and while light-duty vehicle sales fell sharply in MY 2020,
the vehicles that did sell tended to be, on average, larger, heavier,
and more powerful, all factors which increase fuel consumption--again,
enough has changed that a rebalancing of the EPCA factors is
appropriate for model years 2024-2026.
In the 2020 final rule, NHTSA interpreted the need of the U.S. to
conserve energy as less important than in previous rulemakings. This
was in part because of structural changes in global oil markets as a
result of shale oil drilling in the U.S., but also because in the
context of environmental effects, NHTSA interpreted the word
``conserve'' as ``to avoid waste.'' NHTSA concluded then that the
ultimate difference to the climate (among the regulatory alternatives)
of thousandths of a degree Celsius in 2100 did not represent a
``wasteful'' use of energy, given the other considerations involved in
the balancing of factors.
One of those factors was consumer demand for vehicles with higher
fuel economy levels. In the 2020 final rule, NHTSA expressed concern
that low gasoline prices and apparent consumer preferences for larger,
heavier, more powerful vehicles would make it exceedingly difficult for
manufacturers to achieve higher standards without negative consequences
to sales and jobs, and would cause consumer welfare losses. Since then,
however, more and more manufacturers are announcing more and more
vehicle models with advanced engines and varying levels of
electrification. It is reasonable to conclude that manufacturers (who
are all for-profit companies) would not be announcing plans to offer
these types of vehicles if they did not expect to be able to sell
them,\466\ and thus that manufacturers are more sanguine about consumer
demand for fuel efficiency and the market for fully electric vehicles
going forward than they have been previously.
---------------------------------------------------------------------------
\466\ To the extent that manufacturers are offering these
vehicles in response to expected regulations, NHTSA still believes
that they would not do so if they believed the vehicles were
unsaleable or unmanageably detrimental to profits. Vehicle
manufacturers are sophisticated corporate entities well able to
communicate their views to regulatory agencies.
---------------------------------------------------------------------------
Additionally, NHTSA no longer believes that it is reasonable or
appropriate to focus only on ``avoiding waste'' in evaluating the need
of the U.S. to conserve energy. EPCA's overarching purpose is energy
conservation. The need of the U.S. to conserve energy may be reasonably
interpreted as continuing to push the balancing toward greater
stringency.
The following sections will walk through the four statutory factors
in more detail and discuss NHTSA's decision-making process more
thoroughly. To be clear at the outset, however, the fundamental
balancing of factors for this proposal is different from the 2020 final
rule because the evidence suggests that manufacturers believe there is
a market for advanced technology vehicles with higher fuel economy, and
CAFE standards are likely to be maximum feasible if they are set at
levels that reflect that evidence.
[[Page 49803]]
We may begin with the need of the U.S to conserve energy, which as
stated is being considered more holistically in this proposal as
compared to in the 2020 final rule. According to the analysis presented
in Section V and in the accompanying PRIA and SEIS, Alternative 3 would
save consumers the most in fuel costs, and would achieve the greatest
reductions in climate change-causing CO2 emissions.
Alternative 3 would also maximize fuel consumption reductions, better
protecting consumers from international oil market instability and
price spikes. As discussed above, for now, gasoline is still the
dominant fuel used in light-duty transportation. As such, consumers,
and the economy more broadly, are subject to fluctuations in price that
impact the cost of travel and, consequently, the demand for mobility.
Vehicles are long-lived assets and the long-term price uncertainty of
petroleum still represents a risk to consumers. By increasing the fuel
economy of vehicles in the marketplace, more stringent CAFE standards
better insulate consumers against these risks over longer periods of
time. Fuel economy improvements that reduce demand for oil are a more
certain hedging strategy against price volatility than increasing U.S.
energy production. Continuing to reduce the amount of money consumers
spend on vehicle fuel thus remains an important consideration for the
need of the U.S. to conserve energy.
Additionally, the SEIS finds that overall, projected changes in
both upstream and downstream emissions of criteria and toxic air
pollutants are mixed, with emissions of some pollutants remaining
constant or increasing and emissions of some pollutants decreasing.
These increases are associated with both upstream and downstream
sources, and therefore, may disproportionately affect minority and low-
income populations that reside in proximity to these sources. However,
the magnitude of the change in emissions relative to the No-Action
alternative is minor for all action alternatives, and would not be
characterized as high or adverse; over time, adverse health impacts are
projected to decrease nationwide under each of the action alternatives.
For the other considerations that contribute to the need of the
U.S. to conserve energy, it follows reasonably that reducing fuel
consumption more would improve our national balance of payments more,
and our energy security, as discussed above. It is therefore likely
that Alternative 3 best meets the need of the U.S. to conserve energy.
During interagency review, the Department of Energy urged NHTSA to
propose Alternative 3, on the basis that ``a faster transition to
battery electric vehicles (BEVs) is feasible,'' because a variety of
market analysts and the National Academies of Sciences, Engineering,
and Medicine find that BEVs will reach cost parity with ICE vehicles by
or before 2025. DOE further commented that new BEV prices would drop
over time because ``DOE has set aggressive technology targets for
battery costs and electric drive technologies, . . . And DOE has a
consistent track record in meeting its technology targets: DOE met or
exceeded its technology cost and performance goals for battery and
electric drive technologies every year between 2012 and 2018.''
[citation omitted] While NHTSA appreciates this comment from DOE, as
stated repeatedly throughout this proposal, NHTSA is statutorily
prohibited from considering the fuel economy of dedicated alternative
fuel vehicles during the rulemaking time frame when determining what
levels of standards would be maximum feasible. NHTSA believes that
Alternative 3 could potentially end up being maximum feasible in the
final rule depending on a variety of factors, but NHTSA would be
prohibited from basing such a finding exclusively on the date by which
DOE estimates that BEVs will achieve cost parity with ICEs.
We next evaluate how the regulatory alternatives fare in terms of
economic practicability. NHTSA recognizes that the amount of lead time
available before MY 2024 is less than what was provided in the 2012
rule. As will be discussed further below, NHTSA believes that the
evidence suggests that the proposed standards are still economically
practicable, and not out of reach for a significant portion of the
industry. CAFE standards can help support industry by requiring ongoing
improvements even if demand for more fuel economy flags unexpectedly.
For the proposed standards, the annual rates of increase in the
passenger car and light truck standards represent increases over the
required levels in MY 2023 and are as shown in Table VI-6.
[GRAPHIC] [TIFF OMITTED] TP03SE21.181
Part of the way that we try to evaluate economic practicability,
and thus where the tipping point in the balancing of factors might be,
is through a variety of metrics, examined in more detail below. If the
amounts of technology or per-vehicle cost increases required to meet
the standards appear to be beyond what we believe the market could
bear; or sales and employment appear to be unduly impacted, the agency
may decide that the standards under consideration may not be
economically practicable. We underscore again, as throughout this
preamble, that the modeling analysis does not dictate the ``answer,''
it is merely one source of information among others that aids the
agency's balancing of the standards. We similarly underscore that there
is no single bright line beyond which standards might be economically
practicable, and that these metrics are not intended to suggest one;
they are simply ways to think about the information before us.
Economic practicability may be evaluated in terms of how much
technology manufacturers would have to apply to meet a given regulatory
[[Page 49804]]
alternative. 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 redesign cadence. While the need of the U.S. to
conserve energy may encourage the agency to be more technology-forcing
in its balancing, and while technological feasibility is not limiting
in this rulemaking given the state of technology in the industry,
regulatory alternatives that require extensive application of very
advanced technologies (that may have known or unknown consumer
acceptance issues) or that require manufacturers to apply additional
technology in earlier model years, in which meeting the standards is
already challenging, may not be economically practicable, and may thus
be beyond maximum feasible.
The first issue is timing of technology application. While the MY
2024 standards provide less lead time for an increase in stringency
than was provided by the standards set in 2012, NHTSA believes that the
standards for MYs 2021-2023 should provide a relative ``break'' for
compliance purposes. NHTSA does not believe that significant additional
technology application would be required by the CAFE standards in the
years immediately preceding the rulemaking time frame. That said, NHTSA
is aware of, and has accounted for, several manufacturers voluntarily
agreeing with CARB to increase their fuel economy during those model
years. Manufacturers would have to apply more technology than would be
required by the MYs 2021-2023 CAFE standards alone to meet those higher
fuel economy levels. Again, NHTSA interprets these agreements as
evidence that the participating companies believe that applying that
additional technology is practicable, because for-profit companies can
likely be relied upon to make decisions that maximize their profit.
Companies who did not agree with CARB to meet higher targets may not
increase their fuel economy levels by as much over MYs 2021-2023, but
they, too, will get the relative ``break'' in CAFE obligations
mentioned above, and have additional time to plan for the higher
stringency increases in subsequent years. Those manufacturers can opt
to employ more modest technologies to improve fuel economy (beyond
their standard) to generate credits to carry forward into more
challenging years, or concentrate limited research and development
resources on the next generation of higher fuel economy vehicles that
will be needed to meet the proposed standards in MYs 2024-2026 (and
beyond), rather investing in more modest improvements in the near-term.
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 model years until superseded by a more advanced
technology. NHTSA does not consider model years in isolation in the
analysis, because that is not consistent with how industry responds to
standards, and thus would not accurately reflect practicability. If
manufacturers are already applying technology widely and intensively to
meet standards in earlier years, requiring them to add yet more
technology in the model years subject to the rulemaking may be less
economically practicable; conversely, if the preceding model years
require less technology, more technology during the rulemaking time
frame may be more economically practicable. The tables below illustrate
how the agency has modeled that process of manufacturers applying
technologies in order to comply with different alternative standards.
The technologies themselves are described in detail in Chapters 2 and 3
of the accompanying TSD.
[GRAPHIC] [TIFF OMITTED] TP03SE21.182
[[Page 49805]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.183
Although NHTSA's analysis is intended to estimate ways
manufacturers could respond to new standards, not to predict how
manufacturers will respond to new standards, manufacturers have
indicated in meetings with the agency and in public announcements
(including the CARB Framework Agreements) that they do intend to
increase technology application over the coming years, and specifically
electrification technology which NHTSA does not model as part of its
standard-setting analysis, considered for decision-making, due to the
49 U.S.C. 32902(h) restrictions for MYs 2024-2026.
As the tables illustrate, both Alternative 2 and Alternative 3
appear to require rapid deployment of fuel efficiency technology across
a variety of vehicle systems--body improvements due to weight reduction
and improved aerodynamic drag, engine advancements, and
electrification.\467\ The aggressive application that is simulated to
occur between MY 2020 (which NHTSA observed and is the starting point
of this analysis) and MY 2023 occurs in all of the alternatives, for
both cars and light trucks. This reflects both the task presented to
signatories by the California Framework and existing compliance
positions (in some fleets) across the industry to improve fuel economy
in the near-term. In general, technology market shares for Alternative
3 look similar to those for Alternative 2, with the notable exception
of plug-in hybrids which differ by only a couple of percent for cars
and about 5 percent for light trucks. While still relatively small
differences on their own, the market share of plug-in hybrids is
currently less than one percent in total. While manufacturers could
certainly choose to produce fully electric vehicles instead of PHEVs,
fully electric vehicles are projected to grow by multiples of their
current market share as well. The market for high levels of
electrification is likely to continue growing but NHTSA acknowledges
that consumer demand, especially in the near-term, remains somewhat
unclear. If policy decisions are made to extend or expand incentives
for electric vehicle purchases, NHTSA could potentially consider the
greater reliance on electrification in Alternative 3 to be a smaller
risk.
---------------------------------------------------------------------------
\467\ While these technology pathways reflect NHTSA's statutory
restrictions under EPCA/EISA, it is worth noting that they represent
only one possible solution. In the simulations that support the
SEIS, PHEV market share grows by less, and is mostly offset by an
increase in BEV market share.
---------------------------------------------------------------------------
NHTSA's analysis seeks to account for manufacturers' capital and
resource constraints in several ways--through the restriction of
technology application to refreshes and redesigns, through the phase-in
caps applied to certain technologies, and through the explicit
consideration of vehicle components (like powertrains) and technologies
(like platforms based on advanced materials) that are shared by models
throughout a manufacturer's portfolio. NHTSA is aware that there is a
significant difference in the level of capital and resources required
to implement one or more new technologies on a single vehicle model,
and the level of capital and resources required to implement those same
technologies across the entire vehicle fleet. NHTSA realizes that it
would not be economically practicable to expand some of the most
advanced technologies to every vehicle in the fleet within the
rulemaking time frame, although it should be possible to increase the
application of advanced technologies across the fleet in a progression
that accounts for those resource constraints. That is what NHTSA's
analysis tries to do.
Another consideration for economic practicability is the extent to
which new standards could increase the average cost to acquire new
vehicles, because even insofar as the underlying application of
technology leads to reduced outlays for fuel over the useful lives of
the affected vehicles, these per-vehicle cost increases provide both a
measure of the degree of effort faced by manufacturers, and also the
degree of adjustment, in the form of potential vehicle price increases,
that will ultimately be required of vehicle
[[Page 49806]]
purchasers. Table VI-9 and Table VI-10 show the agency's estimates of
average cost increase under the Preferred Alternative for passenger
cars and light trucks, respectively. 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 elect to pay in lieu of achieving compliance with CAFE standards,
we report cost increases as estimated average increases in vehicle
price (as MSRP). 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. For example, a small
SUV that replaces an advanced internal combustion engine with a plug-in
hybrid system may incur additional production costs in excess of
$10,000, while a comparable SUV that replaces a basic engine with an
advanced internal combustion engine incurs a cost closer to $2,000.
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 confidential business information (CBI)) on which to base
such an attempt. To provide an indication of potential price increases
relative to today's vehicles, we report increases relative to the
market forecast using technology in the MY 2020 fleet--the most recent
actual fleet for which we have information sufficient for use in our
analysis. We provide results starting in MY 2023 in part to illustrate
the cost impacts in the first model year that we believe manufacturers
might actually be able to change their products in preparation for
compliance with standards in MYs 2024-2026.
[GRAPHIC] [TIFF OMITTED] TP03SE21.184
[[Page 49807]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.185
Relative to current vehicles (again, as represented here by
technology in the MY 2020 fleet, the most recent for which NHTSA has
adequate data), NHTSA judges these cost increases to be significant,
but not impossible for the market to bear. Cost increases will be
partially offset by fuel savings, which consumers will experience
eventually, if not concurrent with the upfront increase in purchase
price. And as discussed previously, nearly every manufacturer has
already indicated their intent to continue introducing advanced
technology vehicles between now and MY 2026. Again, NHTSA believes that
manufacturers introduce new vehicles (and technologies) expecting that
there is a market for them--if not immediately, then in the near
future. For-profit companies cannot afford to lose money indefinitely.
This trend suggests that manufacturers believe that at least some cost
increases should be manageable for consumers.
Relative to the Preferred Alternative, however, NHTSA notes
significant further cost increases for several major manufacturers
under Alternative 3. Table VI-11 and Table VI-12 show additional
technology costs estimated to be incurred under Alternative 3 as
compared to the Preferred Alternative.
[[Page 49808]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.186
[GRAPHIC] [TIFF OMITTED] TP03SE21.187
For example, Honda's light truck fleet appears to hit an inflection
point in cost where much more aggressive technology application is
required in order to comply with Alternative 3. In general, light truck
fleets appear to be pressed harder to comply with Alternative 3 than
passenger car fleets across the industry. For example, Ford's passenger
car compliance costs are estimated to increase minimally between
Alternative 2 and Alternative 3, but light truck compliance costs
increase by over 40 percent (in most years). A number of other
manufacturers are pushed in both
[[Page 49809]]
fleets (Honda, Toyota, and Kia, for example), and make significant
additional investments in fuel economy technology to reach compliance
with the standards in Alternative 3.
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. Fuel
costs (or savings) continue to be the largest source of benefits for
CAFE standards, and GHG reduction benefits, which are also part of the
need of the U.S. to conserve energy, are also increasing. E.O. 12866
and Circular A-4 also direct agencies to consider maximizing net
benefits in rulemakings whenever possible and consistent with
applicable law. Thus, because it can be relevant to balancing the
statutory factors and because it is directed by E.O. 12866 and OMB
guidance, NHTSA also considers the net benefits attributable to the
different regulatory alternatives, as shown in Table VI-13.
[GRAPHIC] [TIFF OMITTED] TP03SE21.188
While maximizing net benefits is a valid decision criterion for
choosing among alternatives, it is not the only reasonable decision
perspective. When NHTSA recognizes that the need of the U.S. to
conserve fuel weighs importantly in the overall balancing of factors,
it is reasonable to consider choosing the regulatory alternative that
produces the largest reduction in fuel consumption, while remaining net
beneficial. The benefit-cost analysis is not the sole factor that NHTSA
considers in determining the maximum feasible stringency, though it
supports NHTSA's tentative conclusion that Alternative 2 is the maximum
feasible stringency. While Alternative 1 produces higher net benefits,
it also continues to allow fuel consumption that could have been
avoided in a cost-beneficial manner. And while Alternative 3 achieves
greater reductions in fuel consumption than Alternative 2, it shows
relatively high negative net benefits under both discount rates.
While NHTSA estimates that new vehicle sales will be slightly lower
under Alternative 2 than under the No-Action Alternative, as a
consequence of the higher retail prices that result from additional
technology application, the difference is only about 1 percent over the
entire period covered by MYs 2020-2026. NHTSA does not believe that
this estimated change in new vehicle sales over the period covered by
the rule is a persuasive reason to choose another regulatory
alternative. Similarly, the estimated labor impacts within the
automotive industry provide no evidence that another alternative should
be preferred. While the change in sales is estimated to decrease
industry employment over the period, the decrease is even smaller than
the impact on new vehicle sales (about 0.1 percent). As NHTSA explained
earlier in defining economic practicability, standards simply should
avoid a significant loss of jobs, and may still be economically
practicable even though they appear to show a negative impact (here, a
very slight impact) on sales and employment.
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. 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 proposed
standards.
Looking at these cases more closely, the majority of both costs and
benefits that occur under the proposed standards accrue to buyers of
new cars and trucks, rather than society in general. It then follows
that the assumptions that exert the greatest influence over private
costs and benefits also exert the greatest influence over net
benefits--chief among these is the assumed trajectory of future fuel
prices, specifically gasoline. NHTSA considers the ``High Oil Price''
and ``Low Oil Price'' cases from AEO 2021 as bounding cases, though
they are asymmetrical (while the low case is only about 25 percent
lower than the Reference case on average, the high case is almost 50
percent higher on average). The sensitivity cases suggest that fuel
prices exert considerable influence on net benefits--where higher and
lower prices not only determine the dollar value of each gallon saved,
but also how market demand responds to higher levels of fuel economy in
vehicle offerings. Under the low case, net benefits become negative and
exceed $30 billion, but increase to almost (positive) $50 billion in
the high case (the largest increase among any sensitivity cases run for
this proposal). This suggests that the net benefits resulting from this
proposal are
[[Page 49810]]
dependent upon the future price of gasoline being at least as high as
the AEO 2021 Reference Case projects.
Another critical uncertainty that affects private benefits is the
future cost of advanced electrification technologies, specifically
batteries. These emerging technologies provide both the greatest fuel
savings to new car buyers and impose the highest technology costs (at
the moment). While the cost to produce large vehicle batteries has been
rapidly declining for years, they are still expensive relative to
advancements in internal combustion engines and transmissions. However,
the analysis projects continued cost learning over time and shows
battery electric vehicles reaching price parity with conventional
vehicles in the 2030s for most market segments--after which market
adoption of BEVs accelerates--although other estimates show price
parity occurring sooner and we seek comment on whether and how to use
those estimates in our analysis for the final rule. Electrification is
also a viable compliance strategy, as partially or fully electric
vehicles benefit from generous compliance incentives that improve their
estimated fuel economy relative to measured energy consumption. As
such, the assumption about future battery costs has the ability to
influence compliance costs to manufacturers and prices to consumers,
the rate of electric vehicle adoption in the market, and thus the
emissions associated with their operation. NHTSA considered two
different mechanisms to affect battery costs: Higher/lower direct
costs, and faster/slower cost learning rates. The two mechanisms that
reduce cost (whether by faster cost learning or lower direct costs)
both increase net benefits relative to the central case, though
lowering initial direct costs by 20 percent had a greater effect than
increasing the learning rate by 20 percent. Increasing cost (though
either mechanism) by 20 percent produced a similar effect, but in the
opposite direction (reducing net benefits). However, none of those
cases exerted a level of influence that compares to alternative fuel
price assumptions.
There is one assumption that affects the analysis without
influencing the benefits and costs that accrue to new car buyers: The
social cost of damages attributable to greenhouse gas emissions. While
there is no feedback in either the analysis or the policy between the
assumed social cost of GHGs and metric tons of GHGs emitted (or gallons
of fuel consumed), it directly controls the valuation of each metric
ton saved over time. The central analysis assumes a SC-GHG cost based
on the 2.5 percent discount rate for the 3 percent social discount
rate, and a SC-GHG cost based on the 3 percent discount rate in the 7
percent social discount rate case. However, this assumption directly
scales total benefits by increasing (or decreasing) the value of each
ton saved. Using the highest SCC-GHG, based on the 95th percentile
estimate, pushes net benefits above $30 billion under Alternative 2.
NHTSA does not independently develop the SC-GHG assumptions used in
this proposal but takes them from the interagency working group on the
social cost of GHGs. If future analyses by that group determine that
the SC-GHG should be different from what it currently is, NHTSA will
consider those values and whether to include them in subsequent
analyses. As the sensitivity cases illustrate, their inclusion could
exert enough influence on net benefits to suggest that a different
alternative could represent the maximum feasible stringency--at least
based on the decision criteria described in this section. As mentioned
above, NHTSA is seeking comment on the methodology employed by that
group for determining the SC-GHG.
Based on all of the above, NHTSA tentatively concludes that while
all of the action alternatives are technologically feasible,
Alternative 3 may be too costly to be economically practicable in the
rulemaking timeframe, even if choosing it could result in greater fuel
savings. NHTSA interprets the need of the U.S. to conserve energy as
pushing the balancing toward greater stringency--consumer savings on
fuel costs are estimated to be higher under Alternative 3 than under
Alternative 2, but the additional technology cost required to meet
Alternative 3 (as evidenced by the negative net benefits at both
discount rates) may yet make Alternative 3 too stringent for these
model years. Changes in criteria pollutants, health effects, and
vehicle safety effects are relatively minor under all action
alternatives, and thus not dispositive. NHTSA has considered the effect
of other motor vehicle standards of the Government by incorporating the
fuel economy effects of California's ZEV program into its baseline, and
calculating the costs and benefits of CAFE standards as above and
beyond those baseline costs and benefits. The additional costs of the
proposed standards are, on average, not far from what NHTSA estimated
in the 2012 final rule for standards in a similar timeframe; the
additional benefits are lower, but this is due to a variety of factors,
including significant addition of fuel-economy-improving technology to
new vehicles between then and now (including the growing market for
electric vehicles), and lower fuel price projections from EIA. To the
extent that higher prices for new vehicles as a result of the
technology required by the standards could translate to decreases in
new vehicle sales, we note that those effects appear small, as
discussed above. Moreover, improving the fuel efficiency of new
vehicles has effects over time, not just at point of first sale, on
consumer fuel savings. Somewhat-more-expensive-but-more-efficient new
vehicles eventually become more-efficient used vehicles, which may be
purchased by consumers who may be put off by higher new vehicle prices.
The benefits have the potential to continue across the fleet and over
time, for all consumers regardless of their current purchasing power.
NHTSA recognizes, again, that lead time for this proposal is less
than past rulemakings have provided, and that the economy and the
country are in the process of recovering from a global pandemic. NHTSA
also recognizes that at least parts of the industry are nonetheless
making announcement after announcement of new forthcoming advanced
technology, high-fuel-economy vehicle models, and does not believe that
they would be doing so if they thought there was no market at all for
them. Perhaps some of the introductions are driven by industry
perceptions of future regulation, but the fact remains that the
introductions are happening. CAFE standards can help to buttress this
momentum by continuing to require the fleets as a whole to improve
their fuel economy levels steadily over the coming years, so that a
handful of advanced technology vehicles do not inadvertently allow
backsliding in the majority of the fleet that will continue to be
powered by internal combustion for likely the next 5-10 years. CAFE
standards that increase steadily may help industry make this transition
more smoothly.
And finally, if the purpose of EPCA is energy conservation, and
NHTSA is interpreting the need to conserve energy to be largely driven
by fuel savings, energy security, and environmental concerns, then it
makes sense to interpret EPCA's factors as asking the agency to push
stringency as far as possible before benefits become negative. The
energy conservation benefits of Alternative 3 appear, under the current
analysis, to be highest, as discussed in the SEIS and in Section VI.C
above, and better protect consumers from international oil market
instability and price spikes. By
[[Page 49811]]
increasing the fuel economy of vehicles in the marketplace, more
stringent CAFE standards better insulate consumers against these risks
over longer periods of time. Fuel economy improvements that reduce
demand for oil are a more certain hedging strategy against price
volatility than increasing U.S. energy production. However, with
negative net benefits for Alternative 3 under both discount rates, it
may be that for the moment, the costs of achieving those benefits are
more than the market is willing to bear. NHTSA thus aims to help
bolster the industry's trajectory toward higher future standards, by
keeping stringency high in the mid-term, but not so high as to be
economically impracticable.
NHTSA therefore proposes that Alternative 2 is maximum feasible for
MYs 2024-2026. We seek comment on this tentative conclusion.
VII. Compliance and Enforcement
A. Introduction
1. Overview of the NHTSA Compliance Program
A manufacturer's fleet is divided into three compliance categories
of automobiles: Passenger vehicles manufactured domestically, passenger
vehicles not manufactured domestically; and non-passenger
automobiles.\468\ Each category has its own CAFE fleet mpg standard
that a manufacturer is required to meet. The CAFE standard is
determined for each model year by a combination of the production
volume of vehicles produced for sale, the footprint of those vehicles,
and the requisite CAFE footprint-based fuel economy target curves.
---------------------------------------------------------------------------
\468\ See 49 U.S. Code 32903.6. Passenger vehicles not
manufactured domestically are referenced as import passenger cars
and non-passenger automobiles as light trucks.
---------------------------------------------------------------------------
For each compliance category, manufacturers self-report data at the
end of each MY in the form of a Final Model Year Report, and once these
data are verified by EPA, NHTSA determines final compliance. Using
EPA's final verified data, a manufacturer fleet is determined to be
compliant if the 2-cycle CAFE performance of their fleet with the
addition of the Alternative Motor Fuels Act (AMFA) and AC/OC incentives
are equal to or greater than the CAFE fleet mpg standard. The
manufacturer fleet is out of compliance if its fleet mpg falls below
the CAFE mpg standard, in which case the manufacturer may resolve the
shortfall through civil penalties or the use of flexibilities.
Resolving a shortfall through flexibilities may include the application
of CAFE credits through trade, carry-forward, carry-back, or transfer
from within the manufacturer's fleet accounts or from another
manufacturer's fleet accounts.
The following sections provide a brief overview how CAFE standards
and compliance values are derived, what compliance flexibilities and
incentives are available to manufacturers, and the revisions to the
CAFE program NHTSA is proposing in this rulemaking. In summary, NHTSA
is proposing to: (1) Increase and clarify flexibilities for its off-
cycle program; (2) revive incentives for hybrid and electric full-size
pickup trucks through MY 2025; (3) modify its standardized templates
for CAFE reporting and credit transactions; and (4) add a new template
for manufacturers to report information on the monetary and non-
monetary costs associated with credit trades.
2. How Manufacturers' Target and Achieved Performances Are Calculated
Compliance begins each model year with manufacturers testing
vehicles on a dynamometer in a laboratory over pre-defined test cycles
and controlled conditions.\469\ EPA and manufacturers use two different
dynamometer test procedures--the Federal Test Procedure (FTP) and the
Highway Fuel Economy Test (HFET) to determine fuel economy. These
procedures originated in the early 1970s and were intended to generally
represent city and highway driving conditions, respectively. These two
tests are commonly referred to as the ``2-cycle'' test procedures for
CAFE. A machine is connected to the vehicle's tailpipe while it
performs the test cycle, which collects and analyzes exhaust gases,
such as CO2 quantities.\470\ Fuel economy is determined from
relating a derived emissions factor to the amount of observed
CO2 using a reference test fuel.\471\ Manufacturers continue
to test vehicles over the course of the model year and will test enough
vehicles to cover approximately 90 percent of the subconfigurations
within each model type. Manufacturers self-report this information to
EPA as part of their end-of-the-model year reports, which are due 90
days after the model year is completed. After manufacturers submit
their reports, EPA confirms and validates those results by testing a
random sample of vehicles at the National Vehicle and Fuel Emissions
Laboratory (NVFEL) in Ann Arbor, Michigan.
---------------------------------------------------------------------------
\469\ For readers unfamiliar with this process, the test is
similar to running a car on a treadmill following a program--or more
specifically, two programs. 49 U.S.C. 32904(c) states that, in
testing for fuel economy, EPA must ``use the same procedures for
passenger automobiles [that EPA] used for model year 1975 (weighted
55 percent urban cycle and 45 percent highway cycle), or procedures
that give comparable results.'' Thus, 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''), and they have not changed substantively since 1975.
Each cycle is a designated speed trace (of vehicle speed versus
time) that vehicles must follow during testing--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 mph.
The 2-cycle dynamometer test results differ somewhat from what
consumers will experience in the real-world driving environment
because of the lack of high speeds, rapid accelerations, and hot and
cold temperatures evaluations with the A/C operation. These added
conditions are more so reflected in the EPA 5-cycle test results
listed on each vehicle's fuel economy label and on the
fueleconomy.gov website.
\470\ Vehicles without tailpipe emissions, such as battery
electric vehicles, have their performance measured differently, as
discussed below.
\471\ Technically, for the CAFE program, carbon-based tailpipe
emissions (including CO2, CH4, and CO) are
measured, and fuel economy is calculated using a carbon balance
equation. EPA uses carbon-based emissions (CO2,
CH4, and CO, the same as for CAFE) to calculate the
tailpipe CO2 equivalent for the tailpipe portion of its
standards. CO2 is by far the largest carbon-based exhaust
constituent.
---------------------------------------------------------------------------
A manufacturer's fleet fuel economy performance (hereafter
referenced as Base CAFE) for a given model year is calculated through
the following steps:
Each vehicle model's mile per gallon (mpg) performance in
the city and highway test cycles are calculated based off the carbon
emitted during dynamometer testing. The vehicle's mpg performance is
combined at 55 percent city and 45 percent highway. Measurement
incentives for alternative fuel vehicles (such as for electricity,
counting 15 percent of the actual energy used to determine the gasoline
equivalent mpg) are applied as part of these procedures;
Performance improvements not fully captured through 2-
cycle dynamometer testing, such as eligible A/C and off-cycle
technologies are then added to the vehicle's mpg performance.
Incentives for full-size pickup trucks with mild or strong HEV
technology or other technologies that perform significantly better than
the vehicle's target value are also applied.
The quantity of vehicles produced of each model type
within a manufacturer's fleet is divided by its respective fuel economy
performance (mpg) including any flexibility/incentive increases; The
resulting numbers for each model type are summed;
The manufacturer's total production volume is then divided
by the summed value calculated in the previous step; and
[[Page 49812]]
That number, which is the harmonic average of the fleet's
fuel economy, is rounded to the nearest tenth of an mpg and represents
the manufacturer's achieved fuel economy.
The Base CAFE of each fleet is compared to the manufacturer's
unique fleet compliance obligation, which is calculated using the same
approach as the Base CAFE performance, except that the fuel economy
target value (based on the unique footprint of each vehicle within a
model type) is used instead of the measured fuel economy performance
values. The fuel economy target values of the model types within each
fleet and production volumes are used to derive the manufacturer's
fleet standard (also known as the obligation) which is the harmonic
average of these values.
To further illustrate how Base CAFE and fuel economy targets are
calculated, assume that a manufacturer produces two models of cars--a
hatchback and a sedan. Figure VII-1 shows the two vehicle models
imposed onto a fuel economy target function. From Figure VII-1, we can
see that the target function extends from about 30 mpg for the largest
cars to about 41 mpg for the smallest cars.
[GRAPHIC] [TIFF OMITTED] TP03SE21.189
The manufacturer's required CAFE obligation would be determined by
calculating the production-weighted harmonic average of the fuel
economy target values applicable at the hatchback and sedan footprints
(from the curve, about 41 mpg for the hatchback and about 33 mpg for
the sedan). The manufacturer's achieved Base CAFE level is determined
by calculating the production-weighted harmonic average of the
hatchback and sedan fuel economy levels (in this example the values
shown in the boxes in Figure VII-1, 48 mpg for the hatchback and 25 mpg
for the sedan). Depending on the relative mix of hatchbacks and sedans
produced, the manufacturer's fleet Base CAFE may be equal to the
standard, perform better than the standard (if the required fleet CAFE
is less than the achieved fleet Base CAFE) and thereby earn credits, or
perform worse than the standard (if the required fleet CAFE is greater
than achieved fleet Base CAFE) and thereby earn a credit shortfall
which would need to be made up using CAFE credits, otherwise the
manufacturer would be subject to civil penalties.
As illustrated by the example, the CAFE program's use of sales-
weighted harmonic averages makes compliance more intricate than
comparing a model to its target as not every model type needs to
precisely meet its target for a manufacturer to achieve compliance.
Consequently, if a manufacturer finds itself producing large numbers of
vehicles that fall well-short of its targets, a manufacturer can
attempt to equally balance its compliance by producing vehicles that
are excessively over-compliant. However, NHTSA understands that several
factors determine the ability of manufacturers to change their fleet-
mix mid-year. In response, the CAFE program is structured to provide
relief to manufacturers in offsetting any shortfalls by offering
several compliance flexibilities. Many manufacturers use these
flexibilities to avoid civil penalties.
3. The Use for CAFE Compliance Flexibilities and Incentives
The CAFE program offers several compliance flexibilities which
expand options for compliance, and incentives which encourage
manufacturers to build vehicles with certain technologies to achieve
longer range policy objectives. For example, since MY 2017,
manufacturers have had the flexibility to earn credits for air
conditioning
[[Page 49813]]
(A/C) systems with improved efficiency. These fuel economy improvements
are added to the 2-cycle performance results of the vehicle and
increases the calculation of a manufacturer's fleet Base CAFE in
determining compliance relative to standards.\472\
---------------------------------------------------------------------------
\472\ NHTSA characterizes any programmatic benefit manufacturers
can use to comply with CAFE standards that fully accounts for fuel
use as a ``flexibility'' (e.g., credit trading) and any benefit that
counts less than the full fuel use as an ``incentive'' (e.g.,
adjustment of alternative fuel vehicle fuel economy). NHTSA
flexibilities and incentives are discussed further in Section
VII.B.3.a).
---------------------------------------------------------------------------
Some CAFE flexibilities and incentives are codified by statute in
EPCA or EISA, while others have been implemented by the NHTSA through
regulations, consistent with the statutory scheme. Compliance
flexibilities and incentives have a great deal of theoretical
attractiveness: If designed properly, they can help reduce the overall
regulatory costs, while maintaining or improving programmatic benefits.
If designed poorly, they may create significant potential for market
distortion. Consequently, creating or revising compliance flexibilities
and incentives requires proper governmental and industry collaboration
for understanding upcoming technological developments and for
determining whether a technology is economically feasible for
compliance. When designing these programmatic elements, the agency must
be mindful to ensure flexibilities and incentives are provided with
long term benefits to the CAFE program while avoiding unintended
windfalls for only certain manufacturers or technologies.
Compliance incentives and flexibilities are structured to encourage
implementation of technology that will further increase fuel savings.
Some incentives are designed to encourage the development of
technologies that may have high initial costs but offer promising fuel
efficiency benefits in the long-term. Others are designed to bring low
cost technologies uniformly into the market that improve fuel economy
in the real-world but may be missed by the 2-cycle test, such as the
cost-effective off-cycle menu technologies included by EPA for CAFE
compliance.
Below is a summary of all the current and proposed changes to the
flexibilities and incentives for the CAFE and CO2 programs
in Table VII-1 through Table VII-4. Note that this proposal only covers
the CAFE program; the EPA program is listed here to demonstrate the
congruencies between the two programs. NHTSA is proposing to maintain
the bulk of its current program with a few modifications. One of the
changes raised in this proposal is to increase the off-cycle
flexibility technology benefit cap along with new technology
definitions as shown in the table. NHTSA is also proposing to reinstate
incentives for full-size hybrid and game changing advanced technology
pickup trucks for model years 2022 through 2026. NHTSA believes that
these incentives will increase the production of environmentally
beneficial technologies and help achieve economies of scale to reduce
costs that will enable more stringent CAFE standards in the future.
These proposals are explained in further detail in Section VII.B.
BILLING CODE 4910-59-P
[[Page 49814]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.190
[[Page 49815]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.191
[GRAPHIC] [TIFF OMITTED] TP03SE21.192
[[Page 49816]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.193
BILLING CODE 4910-59-C
4. Light Duty CAFE Compliance Data for MYs 2011-2020
NHTSA uses compliance data in part to identify industry trends. For
this proposal, NHTSA examined CAFE compliance data for model years 2011
through 2020 using final compliance data for MYs 2011 through
2017,\473\ projections from end-of-the-model year reports submitted by
manufacturers for MYs 2018 and 2019,\474\ and projections from
manufacturers' mid model year reports for MY 2020.\475\ Projections
from the mid-year and end-of-the-model year reports may differ from
EPA-verified final CAFE values either because of differing test results
or final sales-volume figures. MY 2011 was selected as the start of the
data because it represents the first compliance model year for which
manufacturers were permitted to trade and transfer credits.\476\ The
data go up to MY 2020, because this was the most recent year compliance
reports were available.
---------------------------------------------------------------------------
\473\ Final compliance data have been verified by EPA and are
published on the NHTSA's Public Information Center (PIC) site. MY
2017 is currently the most-recent model year verified by EPA.
\474\ MY 2018 data come from information received in
manufacturers' final reports submitted to EPA according to 40 CFR
600.512-12.
\475\ Manufacturers' mid-model year CAFE reports are submitted
to NHTSA in accordance with 49 CFR part 537. At the time of the
analysis, end of the model year data had not yet been submitted for
MY 2020.
\476\ 49 CFR 535.6(c).
---------------------------------------------------------------------------
Figure VII-2 through Figure VII-5 provide a graphical overview of
the actual and projected compliance data for MYs 2011 to 2020.\477\
---------------------------------------------------------------------------
\477\ As mentioned previously, the figures include estimated
values for certain model years based on the most up to date
information provided to NHTSA from manufacturers.
---------------------------------------------------------------------------
In the figures, an overview is provided for the total fuel economy
performance of the industry (the combination of all passenger cars and
light trucks produced for sale during the
[[Page 49817]]
model year) as a single fleet, and for each of the three CAFE
compliance fleets: Domestic passenger car, import passenger car, and
light truck fleets. For each of the graphs, a sale-production weighting
is applied to determine the average total or fleet Base CAFE
performances.478 479 480 The graphs do not include
adjustments for full-size pickup trucks because manufactures have yet
to bring qualifying products into production.
---------------------------------------------------------------------------
\478\ In the figures, the label ``2-Cycle CAFE'' represents the
maximum increase each year in the average fuel economy set to the
limitation ``cap'' for manufacturers attributable to dual-fueled
automobiles as prescribed in 49 U.S.C. 32906. The label ``AC/OC
contribution'' represents the increase in the average fuel economy
adjusted for A/C and off-cycle fuel consumption improvement values
as prescribed by 40 CFR 600.510-12.
\479\ Consistent with applicable law, NHTSA established
provisions starting in MY 2017 allowing manufacturers to increase
compliance performance based on fuel consumption benefits gained by
technologies not accounted for during normal 2-cycle EPA compliance
testing (called ``off-cycle technologies'' for technologies such as
stop-start systems) as well as for A/C systems with improved
efficiencies and for hybrid or electric full-size pickup trucks.
\480\ Adjustments for earned credits include those that have
been adjusted for fuel saving using the manufacturers CAFE values
for the model years in which they were earned and adjusted to the
average CAFE values for the fleets they exist within.
---------------------------------------------------------------------------
The figures also show how many credits remain in the market each
model year. One complicating factor for presenting credits is that the
mpg-value of a credit is contingent where it was earned and applied.
Therefore, the actual use of the credits for MYs 2018 and beyond will
be uncertain until compliance for those model years is completed. Also,
since credits can be retained for up to 6 MYs after they were earned or
applied retroactively to the previous 3 model years, it is impossible
to know the final application of credits for MY 2020 until MY 2023
compliance data are finalized. Instead of attempting to project how
credits would be generated and used, the agency opted to value each
credit based on its actual value when earned, by estimating the value
when applied assuming it was applied to the overall average fleet and
across all vehicles. In the figures, two different approaches were used
to represent the mpg value of credits used to offset shortages (shown
as CAFE after credit allocation in the figures). The mpg shortages for
MYs 2011 to 2017 are based upon actual compliance values from EPA and
the credit allocations or fines manufacturers instructed NHTSA to
adjust and apply to resolve compliance shortages. For MYs 2018 to 2020,
NHTSA used a different approach for representing the mpg shortages,
deriving them from projected estimates adjusted for fuel savings
calculated from the projected fleet average performances and standards
for each model year and fleet. To represent the mpg value of
manufacturers' remaining banked credits in the figures (shown as
Credits in the Market) the same weighting approach was also applied to
these credits based upon the fleet averages. For MYs 2011-2017, the
remaining banked credits include those currently existing in
manufacturers' credit accounts adjusted for fuel savings and
subtracting any expired credits for each year. This approach was taken
to represent these credits for the actual value that would likely exist
if the credits were applied for compliance purposes. Without adjusting
the banked credits, it would provide an unrealistic value of the true
worth of these credits when used for compliance. For MYs 2018-2020, the
mpg value of the remaining banked credits is shown slightly differently
where the value represents the difference between the adjusted credits
carried forward from previous model years (minus expiring credits) and
the projected earned credits minus any expected credit shortages. Since
all the credits in these model years were adjusted using the same
approach it was possible to subtract the credit amounts. However,
readers are reminded that for MYs 2018-2020 since the final CAFE
reports have yet to be issued, the credit allocation process has not
started, and the data shown in the graphs are a projection of potential
overall compliance. Consequently, the credits included for MYs 2018-
2020 are separated from earlier model years by a dashed line to
highlight that there is a margin of uncertainty in the estimated
values. Projecting how and where credits will be used is difficult for
a number of reasons such as not knowing which flexibilities
manufacturers will utilize and the fact that credits are not valued the
same across different fleets. As such, the agency reminds readers that
the projections may not align with how manufacturers will actually
approach compliance for these years.
Table VII-5 provides the numerical CAFE performance values and
standards for MYs 2011-2020 as shown in the figures.
BILLING CODE 4910-59-P
[[Page 49818]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.194
[GRAPHIC] [TIFF OMITTED] TP03SE21.195
[[Page 49819]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.196
[GRAPHIC] [TIFF OMITTED] TP03SE21.197
[[Page 49820]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.198
BILLING CODE 4910-59-C
As shown in Figure VII-2, manufacturers' fuel economy performance
(2-cycle CAFE plus AMFA) for the total fleet was better than the fleet-
wide target through MY 2015. On average, the total fleet exceeded the
standards by approximately 0.9 mpg for MYs 2011 to 2015. As shown in
Figure VII-3 through Figure VII-5, domestic and import passenger cars
exceeded standards on average by 2.1 mpg and 2.3 mpg, respectively. By
contrast, light truck manufacturers on average fell below the standards
by 0.3 mpg over the same time period.
For MYs 2016 through 2020, Figure VII-2 shows that the total fleet
Base CAFE (including 2-Cycle CAFE plus A/C and OC benefits) falls below
and appears to remain below the fleet CAFE standards for these model
years.\481\ The projected compliance shortfall (i.e. the difference
between CAFE performance values and the standards) remains constant and
reaches its greatest difference between MYs 2019 and 2020. Compliance
becomes even more complex when observing individual compliance fleets
over these years. Only domestic passenger car fleets collectively
appear to exceed CAFE standards while import passenger car fleets
appear to have the greatest compliance shortages. In MY 2020, the
import passenger car fleet appear to reach its highest compliance
shortfall equal to 3.3 mpg.
---------------------------------------------------------------------------
\481\ Until MY 2023 compliance, the last year where earned
credits can be retroactively applied to MY 2020, NHTSA will be
unable to make a determination about the fleet's overall compliance
over this timespan.
---------------------------------------------------------------------------
The graphs provide an overall representation of the average values
for each fleet, although they are less helpful for evaluating
compliance with the minimum domestic passenger car standards given
statutory prohibitions on manufacturers using traded or transferred
credits to meet those standards.\482\ Consequently, in MY 2020,
domestic passenger car manufacturers may improve their performance by
adding more AC/OC technology, allowing the domestic passenger car fleet
to once again exceed CAFE standards. However, NHTSA notes that several
manufacturers have already reported insufficient earned credits and may
have to make fine payments if they fail to reach the minimum domestic
passenger car standards.
---------------------------------------------------------------------------
\482\ In accordance with 49 CFR 536.9(c), transferred or traded
credits may not be used, pursuant to 49 U.S.C. 32903(g)(4) and
(f)(2), to meet the domestically manufactured passenger automobile
minimum standard specified in 49 U.S.C. 32902(b)(4) and in 49 CFR
531.5(d).
---------------------------------------------------------------------------
In summary, MY 2016 is the last compliance model year that
passenger cars complied with CAFE standards relying solely on Base CAFE
performance. Prior to this timeframe, passenger car manufacturers
especially those building domestic fleets could substantially exceed
CAFE standards. MY 2016 marked the first time in the history of the
CAFE program where compliance for passenger car manufacturers fell
below standards thereby increasing shortfalls and forcing the need for
manufacturers to rely heavily upon credit flexibilities. Despite higher
shortfalls, domestic passenger car manufacturers have continued to
generate credits and increase their total credit holdings. The
projections show that for MYs 2018-2020, domestic passenger car fleets
will transition from generating to using credits but will maintain
sizable amounts of banked credits sufficient to sustain compliance
shortfalls in other regulatory fleets. Figure VII-4 shows residual
available banked credits even as far as MY 2020. Domestic passenger car
credits and their off-cycle credits will play an important role in
sustaining manufacturers in complying with CAFE standards.
From the projections, it appears that based on the number of
remaining domestic passenger credits in the market and the rate at
which they are being used, there will be insufficient credits to cover
the shortfalls in other compliance fleets in years following MY 2020.
Figure VII-2 shows that the total remaining combined credits for the
industry is expected to decline starting in MY 2018. Import passenger
cars and light truck fleets will play a major role in the decline and
possible depletion of all available credits to resolve shortfalls after
MY 2020. Several factors exist that could produce this outcome. First,
increasing credit shortages are occurring in the import passenger car
and light truck fleets especially since the reduction and then
termination of AMFA incentives in MY 2019 (a major contributor for
light trucks). Next, residual banked credits for the light truck fleet
are expected to be exhausted starting in MY 2018 and for import
[[Page 49821]]
passenger cars in MY 2020. Finally, the use of AC/OC benefits for
import passenger cars and lights trucks is not a significant factor for
these fleets in complying with CAFE standards. Manufacturers will need
to change their production strategies or introduce substantially more
fuel saving technologies to sustain compliance in the future.
Figure VII-6 provides a historical overview of the industry's use
of CAFE credit flexibilities and fine payments for addressing
compliance shortfalls.\483\ As mentioned, MY 2017 is the last model
year for which CAFE compliance determinations are completed, and credit
application and civil penalty payment determinations finalized. As
shown in the figure, for MYs 2011-2015, manufacturers generally
resolved credit shortfalls by carrying forward earned credits from
previous years. However, since 2011, the rise in manufacturers
executing credit trades has become increasingly common and, in MY 2017,
credit trades were the most frequently used flexibility for achieving
compliance. Credit transfers have also become increasingly more
prevalent for manufacturers. As a note to readers, credit trades in the
figures can also involve credit transfers but are aggregated in the
figure as credit trades to simplify results. In MY 2016, credit
transfers constituted the highest contributor to credit flexibilities
but are starting to decline signifying that manufacturers are currently
exhausting credit transfers within their own fleets. Manufacturers only
occasionally carry back credits to resolve performance shortfalls.
NHTSA believes that trading credits between manufacturers and to some
degree transferring traded credit across fleets will be the most
commonly used flexibility in complying with future CAFE standards as
started in MY 2017.
---------------------------------------------------------------------------
\483\ The Figure includes all credits manufacturers have used in
credit transactions to date. Credits contained in carryback plans
yet to be executed or in pending enforcement actions are not
included in the Figure.
---------------------------------------------------------------------------
Credit trading has generally replaced civil penalty payments as a
compliance mechanism. Only a handful of manufacturers have made civil
penalty payments since the implementation of the credit trading
program. As previously shown, NHTSA believes that manufacturers have
sufficient credits to resolve any import passenger car and light truck
performance shortfalls expected through MY 2020. As of recent, the only
fine payments being made or expected in the future are those directly
resulting from manufacturers failing to comply with the minimum
domestic passenger car standards.\484\ There were two fine payments
made in MYs 2016 and 2017 which fit this exact case. By statute,
manufacturers cannot use traded or transferred credits to address
performance shortfalls for failing to meet the minimum domestic
passenger car standards.\485\ Because of this limitation, the fine
payments made in MY 2016 and 2017 came from one manufacturer that had
exhausted all of its earned domestic passenger credits and could not
carryback future credits.\486\ The same condition will occur for other
manufacturers in the future. NHTSA calculates that six manufacturers
will meet this same condition and have to make substantial civil
penalty payments for failing to comply with the minimum domestic
passenger cars standards in MYs 2018 through 2020.
---------------------------------------------------------------------------
\484\ Six manufacturers have paid CAFE civil penalties since
credit trading began in 2011. Fiat Chrysler paid the largest civil
penalty total over the period, followed by Jaguar Land Rover and
then Volvo. See Summary of CAFE Civil Penalties Collected, CAFE
Public Information Center, https://one.nhtsa.gov/cafe_pic/CAFE_PIC_Fines_LIVE.html.
\485\ Congress prescribed minimum domestic passenger car
standards for domestic passenger car manufacturers and unique
compliance requirements for these standards in 49 U.S.C. 32902(b)(4)
and 32903(f)(2).
\486\ Fiat Chrysler paid $77,268,702.50 in civil penalties for
MY 2016 and $79,376,643.50 for MY 2017 for failing to comply with
the minimum domestic passenger car standards for those MYs.
---------------------------------------------------------------------------
In Figure VII-8, additional information is provided on the credit
flexibilities exercised and fine payments made by manufacturers for MYs
2011-2017. The figure includes the gasoline gallon equivalent for these
credit flexibilities or for paying civil penalties. The figure shows
that manufacturers used carrying forward credits most often to resolve
shortfalls. Credit trades were the second leading benefit to
manufacturers in using credit flexibilities and then followed by credit
transfers. In summary, manufacturers used these flexibilities amounting
to the equivalent of 2,952,856 gallons of fuel by carrying forward
credits in 2017 and 583,720 gallons of fuel by trading credits in 2017.
[[Page 49822]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.199
---------------------------------------------------------------------------
\487\ For Figure VII-6; in each year some flexibilities were not
utilized by manufacturers. For example, carry backed credits were
not utilized in 2011, 2013, 2014, 2015, 2016, or 2017. Transfer
credits were not used in 2011, 2012 or 2013. No civil penalties were
paid in 2015.
---------------------------------------------------------------------------
[[Page 49823]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.200
Despite this compliance picture, NHTSA's analysis supporting this
NPRM shows some amount of overcompliance in the baseline/No-Action
Alternative for the model years subject to this proposal. This modeled
overcompliance occurs due to assumptions about a variety of factors,
including (1) a number of manufacturers voluntarily binding themselves
to the California Framework Agreements, (2) expected manufacturer
compliance with California's ZEV program, (3) expected manufacturer
compliance with the EPA GHG and NHTSA CAFE standards finalized in 2020,
(4) a small amount of market demand for increased fuel economy (due
mostly to projected fuel prices), (5) the projected affordability of
applying certain technologies that are eligible for compliance boosts
(like off-cycle adjustments), and so on. If these assumptions do not
come to pass in the real world, the difference between the compliance
picture over the last several model years and the one shown in the
analysis for the next several years would accordingly be smaller.
Overcompliance with the regulatory alternatives is much lower than what
was shown in the NPRM that preceded the 2020 final rule and is highly
manufacturer-dependent. NHTSA seeks comment on the amount of
overcompliance with the regulatory alternatives shown, if any, in light
of how the agency has described its modeling approach for this
proposal.
5. Shift in Sales Production From Passenger Cars to Light Trucks
The apparent stagnant growth in the automotive industry's CAFE
performance is likely related to a relative decrease in the share of
passenger cars, where manufacturers made the most gains in fuel economy
performance combined with an increase in the relative share of light
trucks purchased beginning with MY 2013. Light trucks experienced sharp
increases in sales, increasing by a total of 5 percent from MYs 2013 to
2014. In MY 2014, light trucks comprised approximately 41 percent of
the total sales production volume of automobiles and has continued to
grow ever since. In comparison, for model year 2014, domestic passenger
cars represented 36 percent of the total fleet and import passenger
cars represented 23 percent. Both domestic and import passenger car
sales have continued to fall every year since MY 2013. Figure VII-8
shows the sales production volumes of light trucks and domestic and
import passenger cars for MYs 2004 to 2020. Historically, light truck
fleets have fallen below their associated CAFE standards and have had
larger performance shortages than either import and domestic passenger
car fleets. For MY 2020, NHTSA expects even greater CAFE performance
shortages in the light truck and import passenger car fleets than in
prior model years, based upon manufacturer's mid-model year (MMY)
reports. MY 2020 light trucks are expected to comprise approximately 53
percent of the total. As mentioned previously, the combined effect of
these fuel economy shortages will likely require manufacturers to rely
on compliance flexibilities or pay civil penalties.
Out of 25 vehicle types listed in the EPA database, 5 vehicle
types--namely compact cars, midsize cars, small and standard SUVs with
4WD, and standard pickup trucks with 4WD have the highest volumes of
vehicles produced for sale in MYs 2012 to 2017. From 2012 to 2020,
there was a drastic decrease of 24% and 17% in the production of
compact cars and midsize cars,
[[Page 49824]]
respectively. On the other side, there was a significant increase in
the production of 4WD small and standard equaling approximately 41%
collectively of all sales. Standard pickup trucks with 4WD experienced
little change in the production volume throughout the years. As shown
in Figure VII-9, small SUVs, with 4WD and 2WD drivetrains, have
surpassed the sales production volumes of all other vehicle types over
these the given model years. The number of small and standard SUVs sold
in the U.S. for MY 2017 nearly doubled compared to sales in the U.S.
for MY 2012. During that same period, passenger car sales production as
a total of vehicle sales production decreased by approximately 11
percent. The combination of low gas prices and the increased utility
that SUVs provide, along with aggressive manufacturer marketing, may
explain the shift in sales production. Nonetheless, if the sales of
these small SUVs and pickup trucks continue to increase, there may be
continued stagnation in the CAFE performance of the overall fleet
unless manufacturers respond with greater adoption of fuel economy
technology in the SUV and pickup truck portion of their fleets.
[GRAPHIC] [TIFF OMITTED] TP03SE21.201
[GRAPHIC] [TIFF OMITTED] TP03SE21.202
6. Electrification
According to data submitted to EPA and NHTSA for MYs 2012 through
2017, the population of electrified vehicles in the passenger car fleet
has steadily increased. The percentage of petroleum-based passenger
cars in the market has decreased. While the nominal amount of electric
light trucks has increased, the percentage of electric light trucks has
decreased due to petroleum-based light trucks growing at
[[Page 49825]]
a faster rate. All electric passenger cars account for up to 3 percent
of the total production of light-duty vehicles each year. In
comparison, all electric light trucks account for about 0.2 percent of
the total fleet each year. The number of passenger cars using
alternative fuels has also steadily increased while the population of
alternative fuel light trucks has become non-existent. However,
comparing the total fleet, the population of electric and hybrid
vehicles is steadily increasing each year on average.
[GRAPHIC] [TIFF OMITTED] TP03SE21.203
Despite the small market share currently for electric and hybrid
trucks, manufacturers are making a strong effort to grow this market.
Starting in 2020, several manufacturers introduced several new models
of hybrid and PEV SUVs and crossovers.
---------------------------------------------------------------------------
\488\ 49 U.S. Code 538 discusses Flexible Fuel Vehicle.
\489\ Definition of Electricity/Hybrids can be found in 49 U.S.
Code 523.2.
\490\ If the fuel type is marked as Hybrid, for this table the
vehicles are automatically counted as Hybrid no matter what type of
fuel category they have. Flexible Fuel Vehicle is everything else
except where the fuel type is gasoline and electric/hybrid.
\491\ Complete data is only available through MY 2017.
---------------------------------------------------------------------------
NHTSA is considering new CAFE compliance strategies for electric
pickup trucks in this rulemaking. EPA and NHTSA previously provided
flexibilities for hybrid and electric pickup trucks adopted under the
2017-2025 CAFE and GHG final rule issued in 2012. These flexibilities
would have provided manufacturers with an incentive through MY 2025 to
build additional electric pickup trucks but in the 2020 final rule,
NHTSA and EPA decided to terminate these incentives early. Further
discussion of NHTSA's and EPA's incentive programs for hybrid and
electric pickup trucks is presented in Section B.3.e)(1). As a part of
the section, a new proposal is also included for EPA and NHTSA to
reconsider extending the incentives for pickup trucks back to their
original effective date ending in MY 2025.
7. Vehicle Classification
Vehicle classification, for purposes of the light-duty CAFE
program, refers to whether an automobile qualifies as a passenger
automobile (car) or a non-passenger automobile (light truck). Passenger
cars and light trucks are subject to different fuel economy standards
as required by EPCA/EISA and consistent with their different
capabilities.
Vehicles are designated as either passenger automobiles or non-
passenger automobiles. Vehicles ``capable of off-highway operation''
are, by statute, non-passenger automobiles.\492\ Determining ``off-
highway operation'' was left to NHTSA, and currently is a two-part
inquiry: First, does the vehicle either have 4-wheel drive or over
6,000 pounds gross vehicle weight rating (GVWR), and second, does the
vehicle have a significant feature designed for
[[Page 49826]]
off-highway operation.\493\ NHTSA's regulation on vehicle
classification contain requirements for vehicles to be classified as
light trucks either on the basis of off-highway capability or on the
basis of having ``truck-like characteristics.'' Over time, NHTSA has
refined the light truck vehicle classification by revising its
regulations and issuing legal interpretations. However, based on the
increase in crossover SUVs and advancements in vehicle design trends,
NHTSA has become aware of vehicle designs that complicate
classification determinations for the CAFE program. Throughout the past
decade, NHTSA has identified these changes in compliance testing, data
analysis, and has discussed the trend in rulemakings, publications, and
with stakeholders.
---------------------------------------------------------------------------
\492\ 49 U.S. Code 32902.
\493\ 49 U.S. Code 523.5(A)(5)(ii)(b).
---------------------------------------------------------------------------
NHTSA believes that an objective procedure for classifying vehicles
is paramount to the agency's continued oversight of the CAFE program.
When there is uncertainty as to how vehicles should be classified,
inconsistency in determining manufacturers' compliance obligations can
result, which is detrimental to the predictability and fairness of the
program. In the 2020 final rule, NHTSA attempted to resolve several
classification issues and committed to continuing research to resolve
others. NHTSA notified the public of its plans to develop a compliance
test procedure for verifying manufacturers' submitted classification
data. An objective standard would help avoid manufacturers having to
reclassify their vehicles, improve consistency and fairness across the
industry, and introduce areas within the criteria where uncertainties
existed and research could be conducted in the near future to resolve.
In this rulemaking, NHTSA is providing additional classification
guidance and seeking comments on several unknown aspects needed to
develop its compliance test procedure. Based upon the comments received
to this NPRM, NHTSA plans to release its draft test procedure later
this year. No changes are being made in this rulemaking that will
change how vehicles are classified.
(a) Clarifications for Classifications Based Upon ``Off-Road
Capability''
For a vehicle to qualify as off-highway (off-road) capable, in
addition to either having 4WD or a GVWR more than 6,000 pounds. The
vehicle must have four out of five characteristics indicative of off-
highway operation. These characteristics are:
An approach angle of not less than 28 degrees
A breakover angle of not less than 14 degrees
A departure angle of not less than 20 degrees
A running clearance of not less than 20 centimeters
Front and rear axle clearances of not less than 18 centimeters
each
(1) Production Measurements
NHTSA's regulations require manufacturers to measure vehicle
characteristics when a vehicle is at its curb weight, on a level
surface, with the front wheels parallel to the automobile's
longitudinal centerline, and the tires inflated to the manufacturer's
recommended cold inflation pressure.\494\ NHTSA clarified in the 2020
final rule that 49 CFR part 537 requires manufacturers to classify
vehicles for CAFE based upon their physical production characteristics.
The agency verifies reported values by measuring production vehicles.
Manufacturers must also use physical vehicle measurements as the basis
for values reported to the agency for purposes of vehicle
classification. It may be possible for certain vehicles within a model
type to qualify as light trucks while others would not because of their
production differences. Since issuing the 2020 final rule, NHTSA has
met with manufacturers to reinforce the use of production measurements
and clarifying here that manufacturers are only required to report
classification information for those physical measurements used for
qualification and can omit other measurements.
---------------------------------------------------------------------------
\494\ 49 U.S. Code 523.5(A)(5).
---------------------------------------------------------------------------
In the previous rulemaking, NHTSA also identified that certain
vehicle designs incorporate rigid (i.e., inflexible) air dams, valance
panels, exhaust pipes, and other components, equipped as manufacturers'
standard or optional equipment (e.g., running boards and towing
hitches), that likely do not meet the 20-centimeter running clearance
requirement. Despite these rigid features, some manufacturers are not
taking these components into consideration when making classification
decisions. Additionally, other manufacturers provide dimensions for
their base vehicles without considering optional or various trim level
components that may reduce the vehicle's ground clearance. Consistent
with our approach to other measurements, NHTSA believes that ground
clearance, as well as all the other off-highway criteria for a light
truck determination, should use the measurements from vehicles with all
standard and optional equipment installed, at the time vehicles are
shipped to dealerships. These views were shared by manufacturers in
response to the previous CAFE rulemaking.
The agency reiterates that the characteristics listed in 49 CFR
523.5(b)(2) are characteristics indicative of off-highway capability. A
fixed feature--such as an air dam that does not flex and return to its
original state or an exhaust that could detach--inherently interferes
with the off-highway capability of these vehicles. If manufacturers
seek to classify vehicles as light trucks under 49 CFR 523.5(b)(2) and
the vehicles have a production feature that does not meet the four
remaining characteristics to demonstrate off-highway capability, they
must be classified as passenger cars. NHTSA also clarifies that
vehicles that have adjustable ride height, such as air suspension, and
permit variable on-road or off-road running clearances should be
classified based upon the mode most commonly used or the off-road mode
for those with this feature. NHTSA seeks comments on how to define the
mode most commonly used for any adjustable suspensions. For the test
procedure, would it be more appropriate to allow manufacturers to
define the mode setting for vehicles with adjustable suspensions?
(2) Testing for Approach, Breakover, and Departure Angles
Approach angle, breakover angle, and departure angle are relevant
to determine off-highway capability. Large approach and departure
angles ensure the front and rear bumpers and valance panels have
sufficient clearance for obstacle avoidance while driving off-road. The
breakover angle ensures sufficient body clearance from rocks and other
objects located between the front and rear wheels while traversing
rough terrain. Both the approach and departure angles are derived from
a line tangent to the front (or rear) tire static loaded radius arc
extending from the ground near the center of the tire patch to the
lowest contact point on the front or rear of the vehicle. The term
``static loaded radius arc'' is based upon the definitions in SAE J1100
and J1544.\495\ The term is defined as the distance from wheel axis of
rotation to the supporting surface (ground) at a given load of the
vehicle and stated inflation pressure of
[[Page 49827]]
the tire (manufacturer's recommended cold inflation pressure).
---------------------------------------------------------------------------
\495\ See SAE J1100 published on May 26, 2012 and SAE J1544
published on Oct 25, 2011.
---------------------------------------------------------------------------
The static loaded radius arc is easy to measure, but the imaginary
line tangent to the static loaded radius arc is difficult to ascertain
in the field. The approach and departure angles are the angles between
the line tangent to the static loaded radius arc and the level ground
on which the test vehicle rests. For the compliance test procedure, a
substitute measurement will be used. A measurement that provides a good
approximation of the approach and departure angles involve using a line
tangent to the outside diameter or perimeter of the tire and extends to
the lowest contact point on the front or rear of the vehicle. This
approach provides an angle slightly greater than the angle derived from
the true static loaded radius arc. The approach also has the advantage
to allow measurements to be made quickly for measuring angles in the
field to verify data submitted by the manufacturers used to determine
light truck classification decisions. In order to comply, the vehicle
measurement must be equal to or greater than the required measurements
to be considered as compliant and if not, the reported value will
require an investigation which could lead to the manufacturer's vehicle
becoming reclassified as a passenger car.
(3) Running Clearance
NHTSA regulations define ``running clearance'' as ``the distance
from the surface on which an automobile is standing to the lowest point
on the automobile, excluding unsprung weight.'' Unsprung weight
includes the components (e.g., suspension, wheels, axles, and other
components directly connected to the wheels and axles) that are
connected and translate with the wheels. Sprung weight, on the other
hand, includes all components fixed underneath the vehicle that
translate with the vehicle body (e.g., mufflers and subframes). To
clarify these requirements, NHTSA previously issued a letter of
interpretation stating that certain parts of a vehicle--such as tire
aero deflectors that are made of flexible plastic, bend without
breaking, and return to their original position--would not count
against the 20-centimeter running clearance requirement. The agency
explained that this does not mean a vehicle with less than 20
centimeters running clearance could be elevated by an upward force that
bends the deflectors and still be considered compliant with the running
clearance criterion, as it would be inconsistent with the conditions
listed in the introductory paragraph of 49 CFR 523.5(b)(2). Further,
NHTSA explained that without a flexible component installed, the
vehicle must meet the 20-centimeter running clearance requirement along
its entire underside. This 20-centimeter clearance is required for all
sprung weight components. For its compliance test procedure, NHTSA will
include a list of the all the components under the vehicle considered
as unsprung components. NHTSA will update the list of unsprung
components as the need arises.
(4) Front and Rear Axle Clearance
NHTSA regulations state that front and rear axle clearances of not
less than 18 centimeters are another criterion that can be used for
designating a vehicle as off-highway capable.\496\ The agency defines
``axle clearance'' as the vertical distance from the level surface on
which an automobile is standing to the lowest point on the axle
differential of the automobile.
---------------------------------------------------------------------------
\496\ 49 U.S. Code 523.5(b)(2).
---------------------------------------------------------------------------
The agency believes this definition may be outdated because of
vehicle design changes, including axle system components and
independent front and rear suspension components. In the past,
traditional light trucks with and without 4WD systems had solid rear
axles with center-mounted differential on the axle. For these trucks,
the rear axle differential was closer to the ground than any other axle
or suspension system component. This traditional axle design still
exists today for some trucks with a solid chassis (also known as body-
on-frame configuration). Today, however, many SUVs and CUVs that
qualify as light trucks are constructed with a unibody frame and have
unsprung (e.g., control arms, tie rods, ball joints, struts, shocks,
etc.) and sprung components (e.g., the axle subframes) connected
together as a part of the axle assembly. These unsprung and sprung
components are located under the axles, making them lower to the ground
than the axles and the differential, and were not contemplated when
NHTSA established the definition and the allowable clearance for axles.
The definition also did not originally account for 2WD vehicles with
GVWRs greater than 6,000 pounds that had one axle without a
differential, such as the model year 2018 Ford Expedition. Vehicles
with axle components that are low enough to interfere with the
vehicle's ability to perform off-road would seem inconsistent with the
regulation's intent of ensuring off-highway capability.
In light of these issues, for the compliance test procedure, NHTSA
will ask manufacturers to identify those axle components that are
sprung or unsprung and provide sufficient justification as a part of
the testing setup request forms sent to manufacturers before testing.
In addition, for vehicles without a differential, NHTSA will request
the location each manufacturer used to establish its axle clearance
qualification. NHTSA will validate the location specified by the
manufacturer but will challenge any location on the vehicle's axle
found to be located at a lower elevation to the ground than the
designed location of its axle clearance measurement.
(5) 49 CFR 571.3 MPV Definition
The definition for multipurpose passenger vehicle (MPV) is defined
as a ``a motor vehicle with motive power, except a low-speed vehicle or
trailer, designed to carry 10 persons or less which is constructed
either on a truck chassis or with special features for occasional off-
road operation.'' \497\ The regulation is silent, however, in defining
special features for occasional off-road operation are qualified. In a
letter of interpretation dated May 31, 1979, the agency responded to a
question from Subaru requesting the agency's opinion whether a four-
wheel drive hatchback sedan could be classified as an MPV. NHTSA
responded stating that the agency interprets the definition as
requiring that the vehicle contain more than a single feature designed
for off-road use and that four-wheel drive would be useful in snow on
public streets, roads and highways, so this feature cannot be
determinative of the vehicle's classification if there are no features
for off-road use. The interpretation also stated that Subaru needed to
provide additional information (including, but not limited to, pictures
or drawings of the vehicle) concerning other special features of the
vehicle that would make it suitable for off-road operation. Finally,
the interpretation referenced 49 CFR 523.5(b)(2) for a description of
some of the characteristics that would be considered ``special
features'' for off-road operation although that section relates
primarily related to fuel economy. Considering that the definition for
MPVs does not list the ``special features,'' NHTSA is seeking comment
on whether manufacturers use ``special features'' other than those in
49 CFR 523.5(b)(2) to qualify vehicles as MPVs. Should NHTSA link the
definition of MPV in 49 CFR 571.3 (as it relates to special features
for occasional off-road operation) to 49 CFR
[[Page 49828]]
523.5(b)(2)? What drawbacks exist in linking both provisions? Using the
longstanding off-road features for fuel economy provides could clarify
the means for certifying that a vehicle meets the definition for MPV in
571.3 when manufacturers may otherwise be uncertain as to how to
classify a vehicle.
---------------------------------------------------------------------------
\497\ 49 CFR 571.3.
---------------------------------------------------------------------------
B. Complying With the NHTSA CAFE Program
1. Annual Compliance Process
Manufacturers' production decisions drive the mixture of
automobiles on the road. Manufacturers largely produce a mixture of
vehicles both to influence and meet consumer demand and address
compliance with CAFE standards though the application of fuel economy
improving technologies to those vehicles, and by using compliance
flexibilities and incentives that are available in the CAFE program. As
discussed earlier in this NPRM, each vehicle manufacturer is subject to
separate CAFE standards for passenger cars and light trucks, and for
the passenger car standards, a manufacturer's domestically-manufactured
and imported passenger car fleets are required to comply
separately.\498\ Additionally, domestically-manufactured passenger cars
are subject to a statutory minimum standard. Some CAFE program
flexibilities are described by statute. Other flexibilities are
established by NHTSA through regulation in accordance with the EPCA and
EISA, such as fuel economy improvements for air conditioning
efficiency, off-cycle, and pickup truck advanced technologies that are
not expressly specified by CAFE statute, but are implemented consistent
with EPCA's provisions regarding the calculation of fuel economy
authorized for EPA.
---------------------------------------------------------------------------
\498\ 49 U.S.C. 32904(b).
---------------------------------------------------------------------------
Compliance with the CAFE program begins each year with
manufacturers submitting required reports to NHTSA in advance and
during the model year that contain information, specifications, data,
and projections about their fleets.\499\ Manufacturers report early
product projections to NHTSA describing their efforts to comply with
CAFE standards per EPCA's reporting requirements.\500\ Manufacturers'
early projections are required to identify any of the flexibilities and
incentives manufacturers plan to use for air-conditioning (A/C)
efficiency, off-cycle and, through MY 2021, which this action proposes
to extend through MY 2026, full-size pickup truck advanced
technologies. EPA consults with NHTSA when reviewing and considering
manufacturers' requests for fuel consumption improvement values for A/C
and off-cycle technologies that improve fuel economy. NHTSA evaluates
and monitors the performance of the industry using compliance data.
NHTSA also audits manufacturers' projected data for conformance and
verifies vehicle conformance through measurements (e.g., vehicle
footprints) to ensure manufacturers are complying. After the model year
ends, manufacturers submit final reports to EPA, that include final
information on all the flexibilities and incentives allowed or approved
for the given model year.\501\ EPA then verifies manufacturers'
reported information and values and calculates the final fuel economy
level of each fleet produced by each manufacturer, and transmits that
information to NHTSA.\502\
---------------------------------------------------------------------------
\499\ 49 U.S.C. 32907(a); 49 CFR 537.7.
\500\ 49 U.S.C. 32907(a).
\501\ For example, alternative fueled vehicles get special
calculations under EPCA (49 U.S.C. 32905-06), and fuel economy
levels can also be adjusted to reflect air conditioning efficiency
and ``off-cycle'' improvements.
\502\ 49 U.S.C. 32904(c)-(e). EPCA granted EPA authority to
establish fuel economy testing and calculation procedures; EPA uses
a two-year early certification process to qualify manufacturers to
start selling vehicles, coordinates manufacturer testing throughout
the model year, and validates manufacturer-submitted final test
results after the close of the model year.
---------------------------------------------------------------------------
In previous years, the normal processes for CAFE compliance between
NHTSA and EPA have been effective at administering the CAFE program for
decades. EPA sends NHTSA its final CAFE results usually between
November to December after the given model year. In recent years, this
process has been disrupted by manufacturers submitting requests for A/C
and off-cycle benefits during the model year and at times well after
the end of the model year. As EPA cannot finalize CAFE results until
all A/C and off-cycle credits for a model year are accounted for, the
belated submissions have significantly delayed NHTSA receiving final
CAFE results for many manufacturers. Late submissions place significant
burdens on the agencies and complicate administering the CAFE program,
including delaying the exchange and use of credits. In the following
sections, NHTSA discusses the adverse impacts on the CAFE program
resulting from late and retro-active A/C and off-cycle requests and
proposes regulatory modifications to mitigate late submissions and help
expedite processes for future off-cycle requests.
After receiving EPA's final reports, NHTSA completes the remainder
of its compliance processes for manufacturers usually one to three
months after receiving EPA's final reports. The process starts with
NHTSA using EPA's final verified information to determine the CAFE
standard for each of the manufacturer's fleets, and each fleet's
compliance level. Those results are then used to determine credits,
credit shortfalls and credit balances, and NHTSA sends letters to
manufacturers stating the outcome of that assessment. Credit shortfall
letters specify the obligated credit deficiency a manufacturer must
resolve to comply with the applicable CAFE standard for the given model
year. Credit balance letters specify the official balance of credits
NHTSA has allotted to the manufacturer in each of its credit accounts
and a ledger of the credit transactions the manufacturer has executed.
Upon receipt of NHTSA's compliance letters, manufacturers are required
to submit plans explaining how they plan to resolve any shortfalls.
NHTSA periodically releases data and reports to the public through its
CAFE Public Information Center (PIC) based on information in the EPA
final reports for the given compliance model year and based on the
projections manufacturers provide to NHTSA for the next two model
years.\503\
---------------------------------------------------------------------------
\503\ The NHTSA Public Information Center (PIC) is located at
https://one.nhtsa.gov/cafe_pic/CAFE_PIC_Home.htm.
---------------------------------------------------------------------------
Some flexibilities are defined, and sometimes limited by statute--
for example, while Congress allowed manufacturers to transfer credits
earned for over-compliance from their car fleet to their truck fleet
and vice versa, Congress also limited the amount by which manufacturers
could increase their CAFE levels using those transfers.\504\ Consistent
with the limits Congress placed on certain statutory flexibilities and
incentives, NHTSA crafted and implemented credit transfer and trading
regulations authorized by EISA ensure that total fuel savings are
preserved when manufacturers exercise statutory compliance
flexibilities required by statute.
---------------------------------------------------------------------------
\504\ See 49 U.S.C. 32903(g).
---------------------------------------------------------------------------
NHTSA and EPA have previously developed other compliance
flexibilities and incentives for the CAFE program consistent with the
statutory provisions regarding EPA's calculation of manufacturers' fuel
economy levels. As discussed previously, NHTSA finalized in the 2012
final rule an approach for manufacturers' ``credits'' under EPA's
program to be applied as fuel economy
[[Page 49829]]
``adjustments'' or ``improvement values'' under NHTSA's program for:
(1) Technologies that cannot be measured or cannot be fully measured on
the 2-cycle test procedure, i.e., ``off-cycle'' technologies; and (2)
A/C efficiency improvements that also improve fuel economy but cannot
be measured on the 2-cycle test procedure. Additionally, both agencies'
programs give manufacturers compliance incentives through MY 2021, and
proposed to be extended to MY 2026 in this NPRM, for utilizing
specified technologies on full-size pickup trucks, such as
hybridization, or full-size pickup trucks that overperform their fuel
economy stringency target values by greater than a specified amount.
The following sections outline how NHTSA determines whether
manufacturers are in compliance with CAFE standards for each model
year, and how manufacturers may use compliance flexibilities, or
alternatively address noncompliance through civil penalties. Moreover,
it explains how manufacturers submit data and information to the
agency. This includes a detailed discussion of NHTSA's standardized
CAFE reporting template adopted as a part of the 2020 final rule, and
the standardized template for reporting credit transactions. In the
2020 final rule, NHTSA also adopted requirements for manufacturers to
provide information on terms of credit trades. In this rulemaking,
NHTSA is proposing to make changes to its reporting and credit
templates and to issue a new template to clarify the required reporting
information for credit trades. These new requirements were intended to
streamline reporting and data collection from manufacturers, in
addition to helping the agency use the best available data to inform
CAFE program decision makers.
2. How does NHTSA determine compliance?
(a) Manufacturers Submit Data to NHTSA and EPA and the Agencies
Validate Results
EPCA, as amended by EISA, in 49 U.S.C. 32907, requires
manufacturers to submit reports to the Secretary of Transportation
explaining how they will comply with the CAFE standards for the model
year for which the report is made; the actions a manufacturer has taken
or intends to take to comply with the standard; and other information
the Secretary requires by regulation.\505\ A manufacturer must submit a
report containing this information during the 30-day period before the
beginning of each model year, and during the 30-day period beginning
the 180th day of the model year.\506\ When a manufacturer determines it
is unlikely to comply with a CAFE standard, the manufacturer must
report additional actions it intends to take to comply and include a
statement about whether those actions are sufficient to ensure
compliance.\507\
---------------------------------------------------------------------------
\505\ 49 U.S.C. 32907(a).
\506\ Id.
\507\ Id.
---------------------------------------------------------------------------
To implement these reporting requirements, NHTSA issued 49 CFR part
537, ``Automotive Fuel Economy Reports,'' which specifies three types
of CAFE reports that manufacturers must submit.\508\ A manufacturer
must first submit a pre-model year (PMY) report containing the
manufacturer's projected compliance information for that upcoming model
year. By regulation, the PMY report must be submitted in December of
the calendar year prior to the corresponding model year.\509\
Manufacturers must then submit a mid-model year (MMY) report containing
updated information from manufacturers based upon actual and projected
information known midway through the model year. By regulation, the MMY
report must be submitted by the end of July for the applicable model
year.\510\ Finally, manufacturers must submit a supplementary report to
supplement or correct previously submitted information, as specified in
NHTSA's regulation.\511\
---------------------------------------------------------------------------
\508\ See 47 FR 34986, Aug. 12, 1982.
\509\ 49 CFR 537.5(b).
\510\ Id.
\511\ 49 CFR 537.8.
---------------------------------------------------------------------------
If a manufacturer wishes to request confidential treatment for a
CAFE report, it must submit both a confidential and redacted version of
the report to NHTSA. CAFE reports submitted to NHTSA contain estimated
sales production information, which may be protected as confidential
until the termination of the production period for that model
year.\512\ NHTSA protects each manufacturer's competitive sales
production strategies for 12 months, but does not permanently exclude
sales production information from public disclosure. Sales production
volumes are part of the information NHTSA routinely makes publicly
available through the CAFE PIC.
---------------------------------------------------------------------------
\512\ 49 CFR part 512, appx. B(2).
---------------------------------------------------------------------------
The manufacturer reports provide information on light-duty
automobiles such as projected and actual fuel economy standards, fuel
economy performance, and production volumes, as well as information on
vehicle design features (e.g., engine displacement and transmission
class) and other vehicle attribute characteristics (e.g., track width,
wheelbase, and other off-road features for light trucks). Beginning
with MY 2017, to obtain credit for fuel economy improvement values
attributable to additional technologies, manufacturers must also
provide information regarding A/C systems with improved efficiency,
off-cycle technologies (e.g., stop-start systems, high-efficiency
lighting, active engine warm-up), and full-size pickup trucks with
hybrid technologies or with fuel economy performance that is better
than footprint-based targets by specified amounts. This includes
identifying the makes and model types equipped with each technology,
the compliance category those vehicles belong to, and the associated
fuel economy improvement value for each technology.\513\ In some cases,
NHTSA may require manufacturers to provide supplementary information to
justify or explain the benefits of these technologies and their impact
on fuel consumption or to evaluate the safety implication of the
technologies. These details are necessary to facilitate NHTSA's
technical analyses and to ensure the agency can perform enforcement
audits as appropriate.
---------------------------------------------------------------------------
\513\ NHTSA collects model type information based upon the EPA
definition for ``model type'' in 40 CFR 600.002.
---------------------------------------------------------------------------
NHTSA uses manufacturer-submitted PMY, MMY, and supplementary
reports to assist in auditing manufacturer compliance data and
identifying potential compliance issues as early as possible.
Additionally, as part of its footprint validation program, NHTSA
conducts vehicle testing throughout the model year to confirm the
accuracy of the track width and wheelbase measurements submitted in the
reports.\514\ These tests help the agency better understand how
manufacturers may adjust vehicle characteristics to change a vehicle's
footprint measurement, and ultimately its fuel economy target. NHTSA
also includes a summary of manufacturers' PMY and MMY data in an annual
fuel economy performance report made publicly available on its PIC.
---------------------------------------------------------------------------
\514\ U.S. Department of Transportation, NHTSA, Laboratory Test
Procedure for 49 CFR part 537, Automobile Fuel Economy Attribute
Measurements (Mar. 30, 2009), available at http://www.nhtsa.gov/DOT/NHTSA/Vehicle%20Safety/Test%20Procedures/Associated%20Files/TP-537-01.pdf.
---------------------------------------------------------------------------
As mentioned, NHTSA uses EPA-verified final-model year (FMY) data
to evaluate manufacturers' compliance with CAFE program requirements
and draw conclusions about the performance of the industry. After
[[Page 49830]]
manufacturers submit their FMY data, EPA verifies the information,
accounting for NHTSA and EPA testing, and subsequently forwards the
final verified data to NHTSA.
(b) New CAFE Reporting Templates Adopted in the 2020 Final Rule
NHTSA adopted changes to its CAFE reporting requirements in the
2020 final rule with the intent of streamlining data collection and
reporting for manufacturers while helping the agency obtain the best
available data to inform CAFE program decision-makers. The agency
adopted two new standardized reporting templates for manufacturers.
NHTSA's goal was to adopt standardized templates to assist
manufacturers in providing the agency with all the necessary data to
ensure they comply with CAFE regulations.
The first template was designed for manufacturers to simplify
reporting CAFE credit transactions starting in model year 2021. The
template's purpose was to reduce the burden on credit account holders,
encourage compliance, and facilitate quicker NHTSA credit transaction
approval. Before the template, manufacturers would inconsistently
submit information required by 49 CFR 536.8, creating difficulties in
processing credit transactions. Using the template simplifies CAFE
compliance aspects of the credit trading process and helps to ensure
that trading parties follow the requirements for a credit transaction
in 49 CFR 536.8(a).\515\
---------------------------------------------------------------------------
\515\ Submitting a properly completed template and accompanying
transaction letter will satisfy the trading requirements in 49 CFR
part 536.
---------------------------------------------------------------------------
The second template was designed to standardize reporting for CAFE
PMY and MMY information, as specified in 49 CFR 537.7(b) and (c), as
well as supplementary information required by 49 CFR 537.8. The
template organizes the required data in a manner consistent with NHTSA
and EPA regulations and simplifies the reporting process by
incorporating standardized responses consistent with those provided to
EPA. The template collects the relevant data, calculates intermediate
and final values in accordance with EPA and NHTSA methodologies, and
aggregates all the final values required by NHTSA regulations in a
single summary worksheet. Thus, NHTSA believes that the standardized
templates will benefit both the agency and manufacturers by helping to
avoid reporting errors, such as data omissions and miscalculations, and
will ultimately simplify and streamline reporting. Manufacturers are
required to use the standardized template for all PMY, MMY, and
supplementary CAFE reports starting in MY 2023. The template also
allowed manufacturers to enter information to generate the required
confidential versions of CAFE reports specified in 49 CFR part 537 and
to produce automatically the required non-confidential versions by
clicking a button within the template.
The standardized CAFE reporting templates were made available on
the NHTSA website and through the DOT docket. Since then, manufacturers
have downloaded the templates and met with NHTSA to share
recommendations for changes, such as allowing the PMY and MMY reporting
templates to accommodate different types of alternative fueled vehicles
and to clarify and correct the methods for calculating CAFE values. The
proposed changes are discussed in the following sections. NHTSA plans
to host a series of workshops to implement the templates and to provide
an open dialogue for manufacturers to identify any further problems and
seek clarifications. NHTSA plans to announce the workshops through the
Federal Register later this year.
(1) Changes to the CAFE Reporting Template
The changes to the CAFE Reporting Template include several general
improvements made to simply the use and the effectiveness for
manufacturers. These include, but are not limited to; wording changes,
corrections to calculations and codes, and auto-populating fields
previously requiring manual entry.
More specifically, NHTSA is proposing to modify the CAFE Reporting
Template by adding filters and sorting functions to help manufacturers
connect the data definitions to the location of each of the required
data fields in the template. Additional information from other parts of
the CAFE Reporting Template would be pulled forward to display on the
summary tab. For the information that must be included pursuant to 49
CFR 537.7(b)(2), manufacturers can also compare the values the template
calculates to their own internally calculated CAFE values.
Additionally, we are proposing to expand the CAFE Reporting Template to
include more of the required information regarding vehicle
classification, and guidance provided to ease manufacturers reporting
burden by having them report only the data used for each vehicle's
qualification pathway ignoring other possible light truck
classification information.
NHTSA is also proposing that the CAFE Reporting Template be
modified to combine the footprint attribute information and model type
sub-configuration data for the purposes of matching. NHTSA uses this
information to match test data directly to fuel economy footprint
values for the purposes of modeling fuel economy standards. Features
were added to auto-populate redundant information from one worksheet to
another. The data gathered and the formulas coded within the proposed
worksheets have also been updated for the calculation of fuel economy
based on 40 CFR 600.510-12. The changes to the data and formulas will
allow data to more accurately represent the fuel economy of electric
and other vehicles using alternative fuels. NHTSA considers this
information critically important to forming a more complete picture of
the performances of dual fuel and alternative fuel vehicles.
We are also proposing several corrections so that manufacturers
will submit CAFE data at each of the different sub-configuration levels
they test and will combine CO2 and fuel economy data. As
mentioned, manufacturers test approximately 90-percent of their
vehicles within each model type. Each sub-configuration variant within
a model type has a unique CO2 and CAFE value. Manufacturers
combine other vehicles at the configuration, base level and then
finally at the model type level for determining CAFE performance. The
CAFE performance data for the sub-configurations have been added to the
proposed template. NHTSA determined that this level of data was needed
to verify manufacturers reported CAFE values.
Finally, we are proposing corrections to the CAFE Reporting
Template to collect information on off-cycle technologies. The proposed
changes match the format of the data with the EPA off-cycle database
system. For example, manufacturers report to EPA high efficiency
lighting as combination packages, so NHTSA is proposing to change its
form to reflect this same level of information.
Version 2.21 of the template is available on NHTSA's Public
Information Center (PIC) site.
(2) Credit Transactions Reporting Template
NHTSA established mandatory use of the CAFE credit template
starting on January 1, 2021. However, manufacturers identified several
calculation errors in the version of the credit reporting template
available on
[[Page 49831]]
the PIC site. Those calculation errors have been corrected and a new
version of the template is available for download on the NHTSA PIC.
Starting January 1, 2022, NHTSA will only accept its credit template as
the sole source for executing CAFE credit transactions. Until that
time, manufacturers can deviate from the generated language in the
NHTSA credit trade confirmation by adding qualifications but, at a
minimum, must include the core information generated by the template.
(3) Monetary and Non-Monetary Credit Trade Information
Credit trading became permissible in MY 2011.\516\ To date, NHTSA
has received numerous credit trades from entities, but has only made
limited information publicly available.\517\ As discussed earlier,
NHTSA maintains an online CAFE database with manufacturer and fleetwide
compliance information that includes year-by-year accounting of credit
balances for each credit holder. While NHTSA maintains this database,
the agency's regulations currently state that it will not publish
information on individual transactions, and NHTSA has not previously
required trading entities to submit information regarding the
compensation (whether financial, or other items of value) exchanged for
credits.518 519 Thus, NHTSA's PIC offers sparse information
to those looking to determine the value of a credit.
---------------------------------------------------------------------------
\516\ 49 CFR 536.6(c).
\517\ Manufacturers may generate credits, but non-manufacturers
may also hold or trade credits. Thus, the word ``entities'' is used
to refer to those that may be a party to a credit transaction.
\518\ 49 CFR 536.5(e)(1).
\519\ NHTSA understands that not all credits are exchanged for
monetary compensation. The proposal that NHTSA is adopting in this
proposed rule requires entities to report compensation exchanged for
credits and is not limited to reporting monetary compensation.
---------------------------------------------------------------------------
The lack of information regarding credit transactions means
entities wishing to trade credits have little, if any, information to
determine the value of the credits they seek to buy or sell.
Historically we have assumed that the civil penalty for noncompliance
with CAFE standards largely determines the upper value of a credit,
because it is logical to assume that manufacturers would not purchase
credits if it cost less to pay civil penalties instead, but it is
unknown how other factors affect the value. For example, a credit
nearing the end of its five-model-year lifespan would theoretically be
worth less than a credit within its full five-model-year lifespan. In
the latter case, the credit holder would likely value the credit more,
as it can be used for compliance purposes for a longer period of time.
NHTSA adopted requirements in the 2020 final rule requiring
manufacturers to submit all credit trade contracts, including cost and
transactional information, to the agency starting January 1, 2021.
NHTSA also adopted requirements allowing manufacturers to submit the
information confidentially, in accordance with 49 CFR part 512.\520\ As
stated in the final rule, NHTSA intended to use this information to
determine the true cost of compliance for all manufacturers. This
information would allow NHTSA to better assess the impact of its
regulations on the industry and provide more insightful information in
developing future rulemakings. This confidential information would be
held by secure electronic means in NHTSA's database systems. As for
public information, NHTSA would include more information on the PIC on
aggregated credit transactions, such as the combined flexibilities all
manufacturers used for compliance as shown in Figure VII-6, or
information comparable to the credit information EPA makes available to
the public. In the future, NHTSA will consider what information, if
any, can be meaningfully shared with the public on credit transactional
details or costs, while accounting for the concerns raised by the
automotive industry for protecting manufacturers' competitive sources
of information.
---------------------------------------------------------------------------
\520\ See also 49 U.S.C. 32910(c).
---------------------------------------------------------------------------
However, manufacturers continue to argue that disclosing trading
terms may not be as simple as a spot purchase at a given price. As
stated in the 2020 final rule, manufacturers contend a number of
transactions for both CAFE and CO2 credits involve a range
of complexity due to numerous factors that are reflective of the
marketplace, such as the volume of credits, compliance category, credit
expiration date, a seller's compliance strategy, and even the CAFE
penalty rate in effect at that time. In addition, automakers have a
range of partnerships and cooperative agreements with their own
competitors. Credit transactions can be an offshoot of these broader
relationships, and difficult to price separately and independently.
Since then, NHTSA has identified a series of non-monetary factors
that it believes to be important to the costs associated with credit
trading in the CAFE program.\521\ The agency believes this information
will allow for a better assessment of the true costs of compliance.
NHTSA further notes that greater government oversight is needed over
the CAFE credit market and it needs to understand the full range of
complexity in transactions, monetary and non-monetary, in addition to
the range of partnerships and cooperative agreements between credit
account holders--which may impact the price of credit trades.\522\
Therefore, using the identified series of non-monetary factors, NHTSA
has developed a new CAFE Credit Reporting Template (Form 1621) for
capturing the monetary and non-monetary terms of credit trading
contracts. NHTSA proposes that manufacturers start using the new
template starting September 1, 2022. The draft template can be viewed
and downloaded from the NHTSA PIC site.
---------------------------------------------------------------------------
\521\ UCS, Detailed Comments, NHTSA-2018-0067-12039; Jason
Schwartz, Detailed Comments, NHTSA-2018-0067-12162.
\522\ Honda, Detailed Comments, NHTSA-2018-0067-11819.
---------------------------------------------------------------------------
3. What compliance flexibilities and incentives are currently available
under the CAFE program and how do manufacturers use them?
Generating, trading, transferring, and applying CAFE credits is
governed by statute.\523\ Program credits are generated when a vehicle
manufacturer's fleet over-complies with its standard for a given model
year, meaning its vehicle fleet achieved a higher corporate average
fuel economy value than the amount required by the CAFE program for
that fleet in that model year. Conversely, if the fleet average CAFE
level does not meet the standard, the fleet incurs debits (also
referred to as a shortfall or deficit). A manufacturer whose fleet
generates a credit shortfall in a given model year can resolve its
shortfall using any one or combination of several credits
flexibilities, including credit carryback, credit carry-forward, credit
transfers, and credit trades, and if all credit flexibilities have been
exhausted, then the manufacturer must resolve its shortfall by making
civil penalty payments.\524\
---------------------------------------------------------------------------
\523\ 49 U.S.C. 32903.
\524\ Manufacturers may elect to pay civil penalties rather than
utilizing credit flexibilities at their discretion. For purposes of
the analysis, we assume that manufacturers will only pay penalties
when all flexibilities have been exhausted.
---------------------------------------------------------------------------
NHTSA has also promulgated compliance flexibilities and incentives
consistent with EPCA's provisions regarding calculation of fuel economy
levels for individual vehicles and for fleets.\525\ These compliance
flexibilities and incentives, which were first adopted in the 2012 rule
for MYs 2017 and later, include A/C efficiency improvement and off-
cycle adjustments,
[[Page 49832]]
and adjustments for advanced technologies in full-size pickup trucks,
including adjustments for mild and strong hybrid electric full-size
pickup trucks and performance-based incentives in full-size pickup
trucks. The fuel consumption improvement benefits of these technologies
measured by various testing methods can be used by manufacturers to
increase the CAFE performance of their fleets.
---------------------------------------------------------------------------
\525\ 49 U.S.C. 32904.
---------------------------------------------------------------------------
(a) Available Credit Flexibilities
Under NHTSA regulations, credit holders (including, but not limited
to manufacturers) have credit accounts with NHTSA where they can, hold
credits, and use them to achieve compliance with CAFE standards, by
carrying forward, carrying back, or transferring credits across
compliance categories, subject to several restrictions. Manufacturers
with excess credits in their accounts can also trade credits to other
manufacturers, who may use those credits to resolve a shortfall
currently or in a future model year. A credit may also be cancelled
before its expiration date if the credit holder so chooses. Traded and
transferred credits are subject to an ``adjustment factor'' to ensure
total oil savings are preserved.\526\
---------------------------------------------------------------------------
\526\ See Section VII.B.3.b) for details.
---------------------------------------------------------------------------
Credit ``carryback'' means that manufacturers are able to use
recently earned credits to offset a deficit that had accrued in a prior
model year, while credit ``carry-forward'' means that manufacturers can
bank credits and use them towards compliance in future model years.
EPCA, as amended by EISA, allows manufacturers to carryback credits for
up to three model years, and to carry-forward credits for up to five
model years.\527\ Credits expire the model year after which the credits
may no longer be used to achieve compliance with fuel economy
regulations.\528\ Manufacturers seeking to use carryback credits must
submit a carryback plan to NHTSA, for NHTSA's review and approval,
demonstrating their ability to earn sufficient credits in future MYs
that can be carried back to resolve the current MY's credit shortfall.
---------------------------------------------------------------------------
\527\ 49 U.S.C. 32903(a).
\528\ 49 CFR 536.3(b).
---------------------------------------------------------------------------
Credit ``trading'' refers to the ability of manufacturers or
persons to sell credits to, or purchase credits from, one another while
credit ``transfer'' means the ability to transfer credit between a
manufacturer's compliance fleets to resolve a credit shortfall. EISA
gave NHTSA discretion to establish by regulation a CAFE credit trading
program, to allow credits to be traded between vehicle manufacturers,
now codified at 49 CFR part 536.\529\ EISA prohibits manufacturers from
using traded credits to meet the minimum domestic passenger car CAFE
standard.\530\
---------------------------------------------------------------------------
\529\ 49 U.S.C. 32903(f).
\530\ 49 U.S.C. 32903(f)(2).
---------------------------------------------------------------------------
(b) Fuel Savings Adjustment Factor
Under NHTSA's credit trading regulations, a fuel savings adjustment
factor is applied when trading occurs between manufacturers and those
credits are used, or when a manufacturer transfers credits between its
compliance fleets and those credits are used, but not when a
manufacturer carries credits forward or backwards within the same
fleet.\531\
---------------------------------------------------------------------------
\531\ See Section III.C for details about carry forward and back
credits.
---------------------------------------------------------------------------
NHTSA is including in this proposal a restoration of certain
definitions that are part of the adjustment factor equation that had
been inadvertently deleted in the 2020 final rule. The 2020 final rule
had intended to add a sentence to the adjustment factor term in 49 CFR
536.4(c), simply to make clear that the figure should be rounded to
four decimal places. While the 2020 final rule implemented this change,
the amendatory instruction for doing so unintentionally deleted several
other definitions from that paragraph. NHTSA had not intended to modify
or delete those definitions, so they are simply being added back into
the paragraph.
(c) VMT Estimates for Fuel Savings Adjustment Factor
NHTSA uses VMT estimates as part of its fuel savings adjustment
equation. Including VMT is important as fuel consumption is directly
related to vehicle use, and in order to ensure trading credits between
fleets preserves oil savings, VMT must be considered.\532\ For MYs 2017
and later, NHTSA finalized VMT values of 195,264 miles for passenger
car credits, and 225,865 miles for light truck credits.\533\
---------------------------------------------------------------------------
\532\ See 49 CFR 536.4(c).
\533\ 77 FR 63130 (Oct. 15, 2012).
---------------------------------------------------------------------------
(d) Fuel Economy Calculations for Dual and Alternative Fueled Vehicles
As discussed at length in prior rulemakings, EPCA, as amended by
EISA, encouraged manufacturers to build alternative-fueled and dual-
(or flexible-) fueled vehicles by providing special fuel economy
calculations for ``dedicated'' (that is, 100 percent) alternative
fueled vehicles and ``dual-fueled'' (that is, capable of running on
either the alternative fuel or gasoline/diesel) vehicles.
Dedicated alternative-fuel automobiles include electric, fuel cell,
and compressed natural gas vehicles, among others. The statutory
provisions for dedicated alternative fuel vehicles in 49 U.S.C.
32905(a) state that the fuel economy of any dedicated automobile
manufactured after MY 1992 shall be measured ``based on the fuel
content of the alternative fuel used to operate the automobile. A
gallon of liquid alternative fuel used to operate a dedicated
automobile is deemed to contain 0.15 gallon of fuel.'' There are no
limits or phase-out for this special fuel economy calculation within
the statute.
EPCA's statutory incentive for dual-fueled vehicles at 49 U.S.C.
32906 and the measurement methodology for dual-fueled vehicles at 49
U.S.C. 32905(b) and (d) expired after MY 2019. In the 2012 final rule,
NHTSA and EPA concluded that it would be inappropriate and contrary to
the intent of EPCA/EISA to measure duel-fueled vehicles' fuel economy
like that of conventional gasoline vehicles with no recognition of
their alternative fuel capability. The agencies determined that for MY
2020 and later vehicles, the general statutory provisions authorizing
EPA to establish testing and calculation procedures provide discretion
to set the CAFE calculation procedures for those vehicles. The
methodology for EPA's approach is outlined in the 2012 final rule for
MYs 2017 and later at 77 FR 63128 (Oct. 15, 2012).
(e) Flexibilities for Air-Conditioning Efficiency, Off-Cycle
Technologies, and Full-Size Pickup Trucks
(1) Incentives for Advanced Technologies in Full-Size Pickup Trucks
Under its EPCA authority for CAFE and under its CAA authority for
GHGs, EPA established fuel consumption improvement values (FCIVs) for
manufacturers that hybridize a significant quantity of their full-size
pickup trucks, or that use other technologies that significantly reduce
fuel consumption of these full-sized pickup trucks. More specifically,
CAFE FCIVs were made available to manufacturers that produce full-size
pickup trucks with Mild HEV or Strong HEV technology, provided the
percentage of production with the technology is greater than specified
percentages.\534\ In addition, CAFE FCIVs were made available for
manufacturers that produce full-size pickups with other technologies
that enable full-size
[[Page 49833]]
pickup trucks to exceed their CAFE targets based on footprints by
specified amounts (i.e., electric vehicles and other electric
components).\535\ These performance-based incentives create a
technology-neutral path (as opposed to the other technology-encouraging
path) to achieve the CAFE FCIVs, which would encourage the development
and application of new technological approaches.
---------------------------------------------------------------------------
\534\ 77 FR 62651 (Oct. 15, 2012).
\535\ Id.
---------------------------------------------------------------------------
Large pickup trucks represent a significant portion of the overall
light duty vehicle fleet and generally have higher levels of fuel
consumption and GHG emissions than most other light duty vehicles.
Improvements in the fuel economy and GHG emissions of these vehicles
can have significant impact on the overall light-duty fleet fuel use
and GHG emissions. NHTSA believes that offering incentives could
encourage the deployment of technologies that can significantly improve
the efficiency of these vehicles and that also will foster production
of those technologies at levels that will help achieve economies of
scale, would promote greater fuel savings overall and make these
technologies more cost effective and available in the future model
years to assist in compliance with CAFE standards.
EPA and NHTSA also established limits on the eligibility for these
pickup trucks to qualify for incentives. A truck was required to meet
minimum criteria for bed size and towing or payload capacities and meet
minimum production thresholds (in terms of a percentage of a
manufacturer's full-size pickup truck fleet) in order to qualify for
these incentives. Under the provisions, Mild HEVs are eligible for a
per-vehicle CO2 credit of 10 g/mi (equivalent to 0.0011
gallon/mile for a gasoline-fueled truck) during MYs 2017-2021. To be
eligible a manufacturer would have to show that the Mild HEV technology
is utilized in a specified portion of its truck fleet beginning with at
least 20 percent of a company's full-size pickup production in MY 2017
and ramping up to at least 80 percent in MY 2021. Strong HEV pickup
trucks are eligible for a 20 g/mi credit (0.0023 gallon/mile) during
MYs 2017-2021, and in this rulemaking proposed to be extended through
MY 2026, if the technology is used on at least 10 percent of a
company's full-size pickups in that model year. EPA and NHTSA also
adopted specific definitions for Mild and Strong HEV pickup trucks,
based on energy flow to the high-voltage battery during testing.
Furthermore, to incentivize other technologies that can provide
significant reductions in GHG emissions and fuel consumption for full-
size pickup trucks, EPA also adopted, a performance-based fuel
consumption improvement value for full-size pickup trucks. Eligible
pickup trucks certified as performing 15 percent better than their
applicable CO2 target receive a 10 g/mi credit (0.0011
gallon/mile), and those certified as performing 20 percent better than
their target receive a 20 g/mi credit (0.0023 gallon/mile). The 10 g/mi
performance-based credit is available for MYs 2017 to 2021 and, once
qualifying; a vehicle model will continue to receive the credit through
MY 2021, provided its CO2 emissions level does not increase.
To be eligible a manufacturer would have to show that the technology is
utilized in a specified portion of its truck fleet beginning with at
least 20 percent of a company's full-size pickup production in MY 2017
and ramping up to at least 80 percent in MY 2021. The 20 g/mi
performance-based credit was available for a vehicle model for a
maximum of 5 years within the 2017 to 2021 model year period, and in
this rulemaking proposed to be extended through MY 2026, provided its
CO2 emissions level does not increase. To be eligible, the
technology must be applied to at least 10 percent of a company's full-
size pickups in for the model year.
The agencies designed a definition for full-size pickup truck based
on minimum bed size and hauling capability, as detailed in 40 CFR
86.1866-12(e). This definition ensured that the larger pickup trucks,
which provide significant utility with respect to bed access and
payload and towing capacities, are captured by the definition, while
smaller pickup trucks with more limited capacities are not covered. A
full-size pickup truck is defined as meeting requirements (1) and (2)
below, as well as either requirement (3) or (4) below.
(1) Bed Width--The vehicle must have an open cargo box with a
minimum width between the wheelhouses of 48 inches. And--
(2) Bed Length--The length of the open cargo box must be at least
60 inches. And--
(3) Towing Capability--the gross combined weight rating (GCWR)
minus the gross vehicle weight rating (GVWR) must be at least 5,000
pounds. Or--
(4) Payload Capability--the GVWR minus the curb weight (as defined
in 40 CFR 86.1803) must be at least 1,700 pounds.
In the 2020 CAFE rule, the agencies ended the incentives for full-
size pickup trucks after the end of model year 2021 believing expanded
incentives would likely not result in any further emissions benefits or
fuel economy improvements since an increase in sales volume was
unanticipated. At the time, no manufacturer had qualified to use the
full-size pickup truck incentives since they went into effect in MY
2017. One vehicle manufacturer introduced a mild hybrid pickup truck in
MY 2019 but was ineligible for the FCIV because it did not meet the
minimum production threshold. Other manufacturers had announced
potential collaborations or started designing future hybrid or electric
models, but none were expected to meet production requirements within
the time period of eligibility for these incentives.
Since the 2020 final rule, many manufacturers have publicly
announced several new model types of full-size electric pickup trucks
starting in MY 2022. NHTSA notes that historically its goal has always
been to promote electric vehicles due to their exceptional fuel saving
benefits. For this reason, even given the discontinuation in MY 2019 of
AMFA incentives for dual fueled vehicles, NHTSA retained its benefits
for alternative dedicated fueled vehicles to focus on the growth of
electric vehicles in the market. Therefore, after the careful
consideration of this new information and the potential role incentives
could play in increasing the production of these technologies, and the
associated beneficial impacts on fuel consumption, the agency is
proposing to extend the full-size pickup truck incentive through MY
2025 for strong hybrids and for full-size pickup trucks performing 20-
percent better than their target. Also, understanding the importance of
electric vehicles in the market, NHTSA is proposing to allow
manufacturers to combine both the incentives for alternative fueled
vehicles and full-size pickup trucks FCIVs when complying with the CAFE
program.
(2) Flexibilities for Air Conditioning Efficiency
A/C systems are virtually standard automotive accessories, and more
than 95 percent of new cars and light trucks sold in the U.S. are
equipped with mobile A/C systems. A/C system usage places a load on an
engine, which results in additional fuel consumption; the high
penetration rate of A/C systems throughout the light-duty vehicle fleet
means that more efficient systems can significantly impact the total
energy consumed. A/C systems also have non-CO2 emissions
associated with
[[Page 49834]]
refrigerant leakage.\536\ Manufacturers can improve the efficiency of
A/C systems though redesigned and refined A/C system components and
controls.\537\ That said, such improvements are not measurable or
recognized using 2-cycle test procedures since A/C is turned off during
2-cycle testing. Any A/C system efficiency improvements that reduce
load on the engine and improve fuel economy is therefore not measurable
on those tests.
---------------------------------------------------------------------------
\536\ Notably, manufacturers cannot claim CAFE-related benefits
for reducing A/C leakage or switching to an A/C refrigerant with a
lower global warming potential. While these improvements reduce GHG
emissions consistent with the purpose of the CAA, they generally do
not impact fuel economy and, thus, are not relevant to the CAFE
program.
\537\ The approach for recognizing potential A/C efficiency
gains is to utilize, in most cases, existing vehicle technology/
componentry, but with improved energy efficiency of the technology
designs and operation. For example, most of the additional A/C-
related load on an engine is because of the compressor, which pumps
the refrigerant around the system loop. The less the compressor
operates, the less load the compressor places on the engine
resulting in less fuel consumption. Thus, optimizing compressor
operation with cabin demand using more sophisticated sensors,
controls, and control strategies is one path to improving the
efficiency of the A/C system.
---------------------------------------------------------------------------
The CAFE program includes flexibilities to account for the real-
world fuel economy improvements associated with improved A/C systems
and to include the improvements for compliance.\538\ The total A/C
efficiency credits is calculated by summing the individual credit
values for each efficiency improving technology used on a vehicle, as
specified in the A/C credit menu. The total A/C efficiency credit sum
for each vehicle is capped at 5.0 grams/mile for cars and 7.2 grams/
mile for trucks. Additionally, the off-cycle credit program contains
credit earning opportunities for technologies that reduce the thermal
loads on a vehicle from environmental conditions (solar loads or parked
interior air temperature).\539\ These technologies are listed on a
thermal control menu that provides a predefined improvement value for
each technology. 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. Under its EPCA authority for CAFE, EPA calculates equivalent
FCIVs and applies them for the calculation of manufacturer's fleet CAFE
values. Manufacturers seeking credits beyond the regulated caps must
request the added benefit for A/C technology under the off-cycle
program discussed in the next section. The agency is not proposing to
change its A/C efficiency flexibility and will retain its provisions in
its current form.
---------------------------------------------------------------------------
\538\ See 40 CFR 86.1868-12.
\539\ See 40 CFR 86.1869-12(b).
---------------------------------------------------------------------------
(3) Flexibilities 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 (city, highway or correspondingly FTP, HFET) used to
determine compliance with the fleet average standards. The cycles are
effective in measuring improvements in most fuel economy improving
technologies; however, they are unable to measure or underrepresent
certain fuel economy improving technologies because of limitations in
the test cycles. For example, off-cycle technologies that improve
emissions and fuel economy 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 which improve
aerodynamics) receive less than their real-world benefits in the 2-
cycle compliance tests.
In the CAFE rule for MYs 2017-2025, EPA, in coordination with
NHTSA, established regulations extending the off-cycle technology
flexibility to the CAFE program starting with MY 2017. For the CAFE
program, EPA calculates off-cycle fuel consumption improvement values
(FCIVs) that are equivalent to the EPA CO2 credit values,
and applies them in the calculation of manufacturer's CAFE compliance
values for each fleet instead of treating them as separate credits as
for the EPA GHG program.
For determining benefits, EPA created three compliance pathways for
the off-cycle program. The first approach allows manufacturers to gain
credits using a predetermined approach or ``menu'' of credit values for
specific off-cycle technologies which became effective starting in MY
2014 for EPA.540 541 This pathway allows manufacturers to
use credit values established by EPA for a wide range of off-cycle
technologies, with minimal or no data submittal or testing
requirements.\542\ Specifically, EPA established a menu with a number
of technologies that have real-world fuel consumption benefits not
measured, or not fully measured, by the two-cycle test procedures, and
those benefits were reasonably quantified by the agencies at that time.
For each of the pre-approved technologies on the menu, EPA established
a menu value or approach that is available without testing
verifications. Manufacturers must demonstrate that they are in fact
using the menu technology, but not required to submit test results to
EPA to quantify the technology's effects, unless they wish to receive a
credit larger than the default value. The default values for these off-
cycle credits were largely determined from research, analysis, and
simulations, rather than from full vehicle testing, which would have
been both cost and time prohibitive. EPA generally used conservative
predefined estimates to avoid any potential credit windfall.\543\
---------------------------------------------------------------------------
\540\ See 40 CFR 86.1869-12(b). The first approach requires some
technologies to derive their pre-determined credit values through
EPA's established testing. For example, waste heat recovery
technologies require manufacturers to use 5-cycle testing to
determine the electrical load reduction of the waste heat recovery
system.
\541\ EPA implemented its off-cycle GHG program starting in MY
2012.
\542\ The Technical Support Document (TSD) for the 2012 final
rule for MYs 2017 and beyond provides technology examples and
guidance with respect to the potential pathways to achieve the
desired physical impact of a specific off-cycle technology from the
menu and provides the foundation for the analysis justifying the
credits provided by the menu. The expectation is that manufacturers
will use the information in the TSD to design and implement off-
cycle technologies that meet or exceed those expectations in order
to achieve the real-world benefits of off-cycle technologies from
the menu.
\543\ While many of the assumptions made for the analysis were
conservative, others were ``central.'' For example, in some cases,
an average vehicle was selected on which the analysis was conducted.
In that case, a smaller vehicle may presumably deserve fewer credits
whereas a larger vehicle may deserve more. Where the estimates are
central, it would be inappropriate for the agencies to grant greater
credit for larger vehicles, since this value is already balanced by
smaller vehicles in the fleet. The agencies take these matters into
consideration when applications are submitted for credits beyond
those provided on the menu.
---------------------------------------------------------------------------
For off-cycle technologies not on the pre-defined technology list,
EPA created a second pathway which allows manufacturers to use 5-cycle
testing to demonstrate off-cycle improvements.\544\ 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.\545\ As learned
through development of the ``five-cycle'' methodology and prior
rulemakings, there are technologies that provide real-world fuel
consumption improvements,
[[Page 49835]]
but those improvements are not fully reflected on the ``two-cycle''
test. EPA established this alternative for a manufacturer to
demonstrate the benefits of off-cycle technologies using 5-cycle
testing. The additional emissions test allows emission benefits to be
demonstrated over some elements of real-world driving not captured by
the two-cycle CO2 compliance tests including high speeds,
rapid accelerations, hot temperatures, and cold temperatures. Under
this pathway, manufacturers submit test data to EPA, and EPA determines
whether there is sufficient technical basis to approve the off-cycle
credits. No public comment period is required for manufacturers seeking
credits using the EPA menu or using 5-cycle testing.
---------------------------------------------------------------------------
\544\ See 40 CFR 86.1869-12(c). EPA proposed a correction for
the 5-cycle pathway in a separate technical amendments rulemaking.
See 83 FR 49344 (Oct. 1, 2019). EPA is not approving credits based
on the 5-cycle pathway pending the finalization of the technical
amendments rule.
\545\ https://www.epa.gov/vehicle-and-fuel-emissions-testing/dynamometer-drive-schedules.
---------------------------------------------------------------------------
The third pathway allows manufacturers to seek EPA review, through
a notice and comment process, to use an alternative methodology other
than the menu or 5-cycle methodology for determining the off-cycle
technology CO2 credits.\546\ 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 third pathway to apply for credits and FCIVs for menu
technologies where the manufacturer is able to demonstrate credits and
FCIVs greater than those provided by the menu.
---------------------------------------------------------------------------
\546\ See 40 CFR 86.1869-12(d).
---------------------------------------------------------------------------
(a) The Off-Cycle Process
In meetings with EPA and manufacturers, NHTSA examined the
processes for bringing off-cycle technologies into market. Two distinct
processes were identified: (1) The manufacturer's off-cycle pre-
production process, and; (2) the manufacturer's regulatory compliance
process. During the pre-production process, the off-cycle program for
most manufacturers begins as early as four to 6 years in advance of the
given model year. Manufacturers' design teams or suppliers identify
technologies to develop capable of qualifying for off-cycle credits
after careful considering of the possible benefits. Manufacturer then
identify the opportunities for the technologies finding the most
optimal condition for equipping the technology given the availability
in the production cycle of either new or multiple platforms
capitalizing on any commonalities to increase sales volumes and reduce
costs. After establishing their new or series platform development
plans, manufacturers have two processes for off-cycle technologies on
the pre-defined menu list or using 5-cycle testing and for those for
which benefits are sought using the alternative approval methodology.
For those on the menu list or 5-cycle testing, technologies whose
credit amounts are defined by EPA regulation, manufacturers confirm
that: (1) New candidate technologies meet regulatory definitions; and
(2) for qualifying technologies, there is real fuel economy (FE)
benefit based on good engineering judgement and/or testing. For these
technologies, manufacturers conduct research and testing independently
without communicating with EPA or NHTSA. For non-menu technologies,
those not defined by regulation, manufacturers pre-production processes
include: (1) Determining the credit amounts based on the effectiveness
of the technologies; (2) developing suitable test procedures; (3)
identifying any necessary studies to support effectiveness; (4) and
identifying the necessary equipment or vehicle testing using good
engineer judgement to confirm the vehicle platform benefits of the
technology.
While for the regulatory compliance process, the first step for
manufacturers begins by providing EPA with early notification in their
pre-model year GHG reports (e.g., 2025MY Pre-GHG are due in 2023CY) of
their intention to generate any off-cycle credits in accordance with 40
CFR 600.514-12. Next, manufacturers present a brief overview of the
technology concept and planned model types for their off-cycle
technologies as a part of annual pre-certification meetings with EPA.
Manufacturers typical hold their pre-certification meetings with EPA
somewhere between September through November two years in advance of
each model year. These meetings are designed to give EPA a holistic
overview of manufacturers planned product offerings for the upcoming
compliance model year and since 2012 information on the A/C and off-
cycle programs. Thus, a manufacturer complying in the 2023 compliance
model year would arrange its pre-certification meeting with EPA in
September 2021 and would be required to share information on the A/C
and off-cycle technologies its plans to equip during the model year.
After this, manufacturers report projected information on off-cycle
technologies as a part of their CAFE reports to NHTSA in accordance
with 49 CFR part 537 CAFE due by December 31st before the end of the
model year.
According to EPA and NHTSA regulations, eligibility to gain
benefits for off-cycle technologies only require manufacturers to
reporting information in advance of the model year notifying the
agencies of a manufacturer's intent to claim credits. More
specifically, manufacturers must notify EPA in their pre-model year
reports, and in their applications for certification, of their
intention to generate any A/C and off-cycle credits before the model
year, regardless of the methodology for generating credits. Similarly,
for NHTSA, manufacturers are also required to provide data in their
pre-model year reports required by 49 CFR part 537 including projected
information on A/C, off-cycle, and full-size pickup truck incentives.
These regulations require manufacturers to report information on
factors such as the approach for determining the benefit of the
technology, projected production information and the planned model
types for equipping the off-cycle technology.
If a manufacturer is pursuing credits for a non-menu off-cycle
technology, EPA also encourages manufacturers to seek early reviews for
the eligibility of a technology, the test procedure, and the model
types for testing in advance of the model year. EPA emphasizes the
critical importance for manufacturers to seek these reviews prior to
conducting testing or any analytical work. Yet, some manufacturers have
decided not to seek EPA's early reviews which resulted in significant
delays in the process as EPA has had to identify and correct multiple
testing and analytical errors after the fact. Consequently, EPA's goal
is to provide approvals for manufacturers as early as possible to
ensure timely processing of their credit requests. NHTSA shares the
same goals and views as EPA for manufacturers submissions but to-date
neither agency has created any required deadlines for these reviews.
For NHTSA, its only requirement is for manufacturers to submit copies
of all information sent to EPA at the same time.
The next step in the credit review process is for manufacturers to
submit an analytical plan defining the required testing to derive the
exact benefit of a non-menu off-cycle technology before the model year
begins and then to start testing. It is noted that some manufacturers
failed to seek EPA's early reviews which delayed finalizing their
analytical plans and then the start of their testing. These delays had
greater impacts depending upon the required testing for the technology.
For example, some manufacturers were required to conduct a four-season
testing methodology lasting almost a year to evaluate the performance
of a technology during all environmental conditions.
[[Page 49836]]
After completing testing, manufacturers are required to prepare an
official application requesting a certain amount of off-cycle credits
for the technology. In accordance with EPA regulations, the official
application request must include final testing data, details on the
methodology used to determine the off-cycle credit value, and the
official benefit value requested. EPA anticipated that these
submissions would be made prior to the end of the model year where the
off-cycle technology was applied.
Each manufacturers' application to EPA must then undergo a public
notice and comment process if the manufacturer uses a methodology to
derive the benefit of a technology not previously approved by EPA. Once
a methodology for a specific off-cycle technology has gone through the
public notice and comment process and is approved for one manufacturer,
other manufacturers may follow the same methodology to collect data on
which to base their off-cycle credits. Other manufacturers are only
required to submit applications citing the approved methodology, but
those manufacturers must provide their own necessary test data,
modeling, and calculations of credit value specific to their vehicles,
and any other vehicle-specific details pursuant to that methodology, to
assess an appropriate credit value. This is similar to what occurred
with the advanced A/C compressor, where one manufacturer applied for
credits with data collected through bench testing and vehicle testing,
and subsequent to the first manufacturer being approved, other
manufacturers applied for credits following the same methodology by
submitting test data specific for their vehicle models. Consequently,
as long as the testing is conducted using the previously-approved
methodology, EPA will evaluate the credit application and issue a
decision with no additional notice and comment, since the first
application that established the methodology was subject to notice and
comment. EPA issues a decision document regarding the manufacturer's
official application upon resolution of any public comments to the its
Federal Register notice and after consultation with NHTSA. Finally,
manufacturers submit information after the model year ends on off-cycle
technologies and the equipped vehicles in their final CAFE reports due
by March 30th and then in their final GHG Averaging, Banking, and
Trading (AB&T) reports due to EPA by April 30th.
During the 2020 rulemaking, the agencies and manufacturers both
agreed that responding to petitions before the end of a model year is
beneficial to manufacturers and the government. It allows manufacturers
to have a better idea of what credits they will earn, and for the
government, a timely and less burdensome completion of manufacturers'
end-of-the-year final compliance processes. EPA structured the A/C and
off-cycle programs to make it possible to complete the processes by the
end of the model year so manufacturers could submit their final reports
within the required deadline--90 days after the calendar year, when
CAFE final reports are due from manufacturers.\547\
---------------------------------------------------------------------------
\547\ 40 CFR 600.512(12).
---------------------------------------------------------------------------
However, at the time of the previous rulemaking, manufacturers were
submitting retroactive off-cycle petitions for review causing
significant delays to review and approval of novel technologies and
issuances of Federal Register notices seeking public comments, where
applicable. As a result, the agencies set a one-time allowance that
ended in May 2020 for manufacturers to ask for retroactive credits or
FCIVs for off-cycle technologies equipped on previously-manufactured
vehicles after the model year had ended. After that time, the agencies
denied manufacturers' late submissions requesting retroactive credits.
However, manufacturers who properly submitted information ahead of time
were allowed to make corrections to resolve inadvertent errors during
or after the model year.
Both EPA and NHTSA regulations fail to include specific deadlines
for manufacturers to meet in finalizing their off-cycle analytical
plans or the official applications to the agencies. The agencies
believed that enforcing the existing submission requirements would be
the most efficient approach to expedite approvals and set aside adding
any new regulatory deadlines or additional requirements in the previous
rulemaking. There were also concerns to provide manufacturers with
maximum flexibility and due to the uncertainties existing with the non-
menu off-cycle process. However, the agencies anticipated that any
timeliness problems would resolve themselves as the off-cycle program
reached maturity and more manufacturers began requesting benefits for
previously approved off-cycle technologies.
Despite the agencies expectations, the lack of deadlines for test
results or the official application has significantly delayed approvals
for non-menu off-cycle requests. In many cases, EPA has received off-
cycle non-menu application requests either late in the model year or
after the model year. This falls outside the agencies planned strategy
for the off-cycle non-menu review process whereas manufacturers would
seek approval and submit their official application requests either in
advance of the model year or early enough in the model year to allow
the agency to approve a manufacturer's credits before the end of the
model year.
(b) Proposed Changes to the Off-Cycle Program
(i) Review Process
The current review process for off-cycle technologies is causing
significant challenges in finalizing end-of-the-year compliance
processes for the agencies. The backlog of retro-active and pending
late off-cycle requests have delayed EPA from recalculating NHTSA's MY
2017 finals and from completing those for MYs 2018 and 2019. Fifty-four
off-cycle non-menu requests have been submitted to EPA to date.
Nineteen of the requests were submitted late and another seven apply
retroactively to previous model years starting as early as model year
2015. Since these requests represent potential credits or adjustments
that will influence compliance figures, CAFE final results cannot be
finalized until all off-cycle requests have been disposed. These
factors have so far delayed MY 2017 final CAFE compliance by 28 months,
MY 2018 by 15 months, and MY 2019 by 4 months.
These late reports amount to more than just a mere accounting
nuisance for the agencies; they are actively chilling the credit
market. Until EPA verifies final compliance numbers, manufacturers are
uncertain about either how many credits they have available to trade
or, conversely, how many credits are necessary for them to cover any
shortfalls.
For MY 2017, NHTSA will void manufacturers previous credit trades
pending the revised final calculations. Second, until late requests are
approved, credit sellers are unable to make trades with buyers having
pending approvals or credits are sold whereas the final balance of
credits is unknown. Because credit trades and transfers must be
adjusted for fuel savings anytime a change occurs in a manufacturer's
CAFE values, the resulting earned or purchased credits must be
recalculated. These recalculations are significantly burdensome on the
government to administer and places an undue risk on manufacturers
involved in CAFE credit trade transactions.
NHTSA met with EPA and manufacturers to better understand the
process for reviewing off-cycle non-menu technologies. From these
[[Page 49837]]
discussions, NHTSA identified several issues that may be influencing
late submissions. First, non-menu requests are becoming more complex
and are requiring unique reviews. Previously approved technologies are
also becoming more complex and are requiring either new testing, test
procedures or have evolved beyond the definitions which at one time
previously qualified them. Next, manufacturers identified the lack of
standardized test procedures approved by EPA or certainty from EPA on
which model types need to be tested as major sources for delays in
submitting their analytical plans. In addition, manufacturers claimed
there is significant uncertainty surrounding the necessary data sources
to substantiate the benefit of the technology. For example, the data
sources necessary to substantiate the usage rates certain technologies
in the market. Testing or extrapolating test results for variations in
model types can also be difficult and a source of delay. Manufacturers
are typically uncertain as to what configurations within a model type
must be tested and believe further guidance may be needed by EPA.
Manufacturers further claim that it is challenging to coordinate the
required testing identified by EPA for off-cycle in coordination with
other required certification and emissions testing. Several of these
issues were addressed in the 2020 final rule. In that rulemaking, the
agencies stated that developing a standardized test procedure
``toolbox'' may not be possible due to the development of new and
emerging technologies, and manufacturers' different approaches for
evaluating the benefits of the technologies. However, the agencies
committed to considering additional guidance, if feasible, as the
programs further matures in the review process of technologies and, if
possible, identify consistent methodologies that may help manufacturers
analyze off-cycle technologies.
Part of the issue is that the review process begins significantly
later than the development of technology. Typically, EPA only learns
about a new off-cycle technology during manufacturers' precertification
meetings, months or even years after manufacturers started to develop
the technology. NHTSA seeks comments on whether opportunities exist
during the initial development of off-cycle technologies for
manufacturers to start discussions with the agencies to identify
suitable test procedures or approval of the initial concept of a new
technology. After certification meetings, NHTSA also identified that in
many cases, manufacturers do not communicate with EPA seeking approvals
for their test procedures, test vehicles or credit calculations until
anywhere from 3-6 months after the initial development of the
technology. Delays in approving a suitable test procedure extends the
manufacturers ability to perform testing or to submit its formal
request for benefits until after the model year has ended. As
mentioned, testing can take up to 12 months after a suitable test
procedure and identifying which subconfigurations must be tested.
One manufacturer also stated that set submission deadlines are
impossible, agency approvals are variable based on OEM need and reply
timing is driven by the EPA. When questioned whether any deadlines
could be imposed manufacturers responded believing any deadlines would
need to be negotiated between the manufacturer and the government.
Please comment on any drawbacks associated with negotiating and
enforcing off-cycle process deadlines with manufacturers.
NHTSA is proposing to modify the eligibility requirements for non-
menu off-cycle technologies in the CAFE program starting in model year
2024. Manufacturers will be required to finalize their analytical plans
by December before the model years and their final official technology
credit requests by September during the model year. Manufacturers will
also be required to meet the proposed deadlines or be subject an
enforcement action. Unless an extension is granted by NHTSA for good
cause, a manufacturer will be precluded from claiming any off-menu
items not timely submitted. Failure to request extensions or meet
negotiated deadlines will be subject to enforcement action in
compliance with 49 U.S.C. 32912(a).
To further streamline the process of reviews, NHTSA also proposes
to work with EPA to create a quicker process for adding off-cycle
technologies to the predetermined menu list if widely approved for
multiple manufacturers. For example, the agencies added high-efficiency
alternators and advanced A/C compressors to the menu allowing
manufacturers to select the menu credit rather than continuing to seek
credits through the public approval process. High-efficiency
alternators were added to the off-cycle credits menu, and advanced A/C
compressors with a variable crankcase valve were added to the menu for
A/C efficiency credits. The credit levels are based on data previously
submitted by multiple manufacturers through the off-cycle credits
application process. The high efficiency alternator credit is scalable
with efficiency, providing an increasing credit value of 0.16 grams/
mile CO2 per percent improvement as the efficiency of the
alternator increases above a baseline level of 67 percent efficiency.
The advanced A/C compressor credit value is 1.1 grams/mile for both
cars and light trucks.\548\
---------------------------------------------------------------------------
\548\ For additional details regarding the derivation of these
credits, see EPA's Memorandum to Docket EPA-HQ-OAR-2018-0283
(``Potential Off-cycle Menu Credit Levels and Definitions for High
Efficiency Alternators and Advanced Air Conditioning Compressors'').
---------------------------------------------------------------------------
(ii) Safety Assessment
In the 2016 heavy-duty fuel economy rule (81 FR 73478, October 25,
2016), NHTSA adopted provisions preventing manufacturers from receiving
credits for technology that impair safety--whether due to a defect,
negatively affecting a FMVSS, or other safety reasons.\549\
Additionally, NHTSA clarified that technologies that do not provide
fuel savings as intended will also be stripped of credits. To harmonize
the light-duty and heavy-duty off-cycle programs, NHTSA is proposing to
adopt these provisions for the light-duty CAFE program. While the
agency encourages fuel economy innovations, safety remains NHTSA's
primary mission and any technology applied for CAFE-purposes should not
impair safety. Furthermore, adopting these requirements for the light-
duty fleet will harmonize it with the heavy-duty regulations.
---------------------------------------------------------------------------
\549\ See 49 CFR 535.7(f)(2)(iii).
---------------------------------------------------------------------------
(iii) Menu Credit Cap
Due to the uncertainties associated with combining menu
technologies and the fact that some uncertainty is introduced because
off-cycle credits are provided based on a general assessment of off-
cycle performance, as opposed to testing on the individual vehicle
models, EPA established caps that limit the amount of credits a
manufacturer may generate using the EPA menu list. Off-cycle technology
is capped at 10 grams/mile per year on a combined car and truck fleet-
wide average basis. In its concurrent proposal for MYs 2023-2026 GHG
standards (86 FR 43726, August 10, 2021), EPA is proposing to increase
the off-cycle menu cap from 10 grams CO2/mile to 15 grams
CO2/mile beginning with MY 2023. EPA also proposes to revise
the definitions for passive cabin ventilation and active engine and
transmission warm-up beginning in MY 2023, as discussed in the next
following sections. Furthermore, EPA is proposing, for MYs
[[Page 49838]]
2020-2022, to allow manufacturers to use the cap of 15 g/mi if the
revised definitions are met for these technologies. NHTSA is proposing
to adopt these same provisions for the CAFE programs as a part of this
rulemaking. No caps were established for technologies gaining credits
through the petitioning or 5-cycle approval methodologies and the
agency are not proposing to add caps in these areas.
(iv) Proposal To Update the Menu Technology Definitions
(a) Passive Cabin Ventilation
Some manufacturers have claimed off-cycle credits for passive
ventilation cabin technologies based on the addition of software logic
to their HVAC system that sets the dash vent to the open position when
the power to vehicle is turned off at higher ambient temperatures. The
manufacturers have indicated that the opening of the vent allows for
the flow of ambient temperature air into the cabin. While ensuring that
the interior of the vehicle is open for flow into the cabin, by only
opening the dash vent no other action is taken to improve the flow of
heated air out of the vehicle. This technology relies on the pressure
in the cabin to reach a sufficient level for the heated air in the
interior to flow out through body leaks or the body exhausters open and
vent heated air out of the cabin.
The credits for passive cabin ventilation were determined based on
an National Renewable Energy Laboratory (NREL) study that strategically
opened a sunroof to allow for the unrestricted flow of heated air to
exit the interior of the vehicle while combined with additional floor
openings to provide a minimally restricted entry for cooler ambient air
to enter the cabin.\550\ The modifications NREL performed on the
vehicle reduced the flow restrictions for both heated cabin air to exit
the vehicle and cooler ambient air to enter the vehicle, creating a
convective airflow path through the vehicle cabin.
---------------------------------------------------------------------------
\550\ Rugh, J., Chaney, L., Lustbader, J., and Meyer, J.,
``Reduction in Vehicle Temperatures and Fuel Use from Cabin
Ventilation, Solar-Reflective Paint, and a New Solar-Reflective
Glazing,'' SAE Technical Paper 2007-01-1194, 2007.
---------------------------------------------------------------------------
Analytical studies performed by manufacturers to evaluate the
performance of the open dash vent demonstrate that while the dash vent
may allow for additional airflow of ambient temperature air entering
the cabin, it does not reduce the existing restrictions on heated cabin
air exiting the vehicle. Opening the dash vent primarily relies on body
leaks and occasional venting of the heated cabin air through the body
exhausters for the higher temperature cabin air to be vented from the
vehicle. While this does provide some reduction in cabin temperatures
this technology is not as effective as the combination of vents used by
the NREL researchers to allow additional ambient temperature air to
enter the cabin and also to reduce the restriction of heated air
exiting the cabin.
As noted in the Joint Technical Support Document: Final Rulemaking
for 2017-2025 Light-Duty Vehicle Greenhouse Gas Emission Standards and
Corporate Average Fuel Economy Standards,\551\ pg. 584, ``For passive
ventilation technologies, such as opening of windows and/or sunroofs
and use of floor vents to supply fresh air to the cabin (which enhances
convective airflow), (1.7 grams/mile for LDVs and 2.3 grams/mile for
LDTs) a cabin air temperature reduction of 5.7 [deg]C can be
realized.'' The passive cabin ventilation credit values were based on
achieving the 5.7 [deg]C cabin temperature reduction.
---------------------------------------------------------------------------
\551\ ``Final Rulemaking for 2017-2025 Light-Duty Vehicle
Greenhouse Gas Emission Standards and Corporate Average Fuel Economy
Standards'' August 2012. NHTSA and EPA. https://www.nhtsa.gov/sites/nhtsa.gov/files/joint_final_tsd.pdf. Last Accessed June 6, 2021.
---------------------------------------------------------------------------
EPA and NHTSA have decided to revise the passive cabin ventilation
definition to make it consistent with the technology used to generate
the credit value. NHTSA supports EPA's proposal to revise the
definition of passive cabin ventilation to only include methods which
create and maintain convective airflow through the body's cabin by
opening windows or a sunroof, or equivalent means of creating and
maintaining convective airflow, when the vehicle is parked outside in
direct sunlight.
Current systems claiming the passive ventilation credit by opening
the dash vent would no longer meet the updated definition.
Manufacturers seeking to claim credits for the open dash vent system
will be eligible to petition the agency for credits for this technology
using the alternative EPA approved method outlined in Sec. 86.1869-
12(d).
(b) Active Engine and Transmission Warmup
NHTSA, in coordination with EPA, is proposing to revise the menu
definitions of active engine and transmission warm-up to no longer
allow systems that capture heat from the coolant circulating in the
engine block prior to the opening of the thermostat to qualify for the
Active Engine and Active Transmission warm-up menu credits. The agency
would allow credit for coolant systems that capture heat from a liquid-
cooled exhaust manifold if the system is segregated from the coolant
loop in the engine block. The agency would also allow system design
that captures and routes waste heat from the exhaust to the engine or
transmission as this was the basis for these two credits as originally
proposed in the NPRM to the 2017 to 2025 GHG rulemaking (76 FR 74854,
Dec. 1, 2011).
Manufacturers seeking to utilize their existing systems that
capture coolant heat before the engine is fully warmed-up and transfer
this heat to the engine oil and transmission fluid would remain
eligible to seek credits through the alternative method application
process outlined in Sec. 86.1869-12(d). These technologies may provide
some benefit, however, as noted above as these system designs remove
heat that is needed to warmup the engine may be less effective than
those that capture and utilize exhaust waste heat.
VIII. Public Participation
NHTSA requests comments on all aspects of this NPRM. This section
describes how you can participate in this process.
How do I prepare and submit comments?
Your comments must be written and in English.\552\ To ensure that
your comments are correctly filed in the docket, please include the
docket number NHTSA-2021-0053 in your comments. Your comments must not
be more than 15 pages long.\553\ 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.\554\ Please note that pursuant to
the Data Quality Act, in order for substantive data to be relied upon
and used by the agency, 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
[[Page 49839]]
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.
---------------------------------------------------------------------------
\552\ 49 CFR 553.21.
\553\ Id.
\554\ Optical character recognition (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.
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 any information under a claim
of confidentiality, you should submit three copies of your complete
submission, including the information you claim to be confidential
business information, to the Chief Counsel, NHTSA, at the address given
above under FOR FURTHER INFORMATION CONTACT. When you send a comment
containing confidential business information, you should include a
cover letter setting forth the information specified in 49 CFR part
512.
In addition, you should submit a copy from which you have deleted
the claimed confidential business information to the Docket by one of
the methods set forth above.
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 the
agency places in the docket after the issuance of the NPRM affects
their comments, they may submit comments after the closing date
concerning how the agency should consider that information for the
final rule. However, the agency'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. The agency will announce the specific date and web
address for the hearing in a supplemental Federal Register
notification. The agency will accept oral and written comments to the
rulemaking documents and will also accept comments to the Supplemental
Environmental Impact Statement (SEIS) at this hearing. The hearing will
start at 9 a.m. Eastern standard time and 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.
The Draft Supplemental Environmental Impact Statement (SEIS)
associated with this proposal has a unique public docket number and is
available in Docket No. NHTSA-2021-0054.
Comments on the Draft SEIS can be submitted electronically at
http://www.regulations.gov, in Docket No. NHTSA-2021-0054. 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-2021-0054), between 9 a.m. and 5
p.m., Monday through Friday, except on Federal holidays. To be sure
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 web at http://www.regulations.gov.
IX. Regulatory Notices and Analyses
A. Executive Order 12866, Executive Order 13563
Executive Order 12866, ``Regulatory Planning and Review'' (58 FR
51735, Oct. 4, 1993), as amended by Executive Order 13563, ``Improving
Regulation and Regulatory Review'' (76 FR 3821, Jan. 21, 2011),
provides 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 Executive
Order. Under these Executive orders, this action is an ``economically
significant regulatory action'' because it is likely to have an annual
effect on the economy of $100 million or more. Accordingly, NHTSA
submitted this action to OMB for review and any changes made in
response to OMB recommendations have been documented in the docket for
this action. The benefits and costs of this proposal are described
above and in the Preliminary Regulatory Impact Analysis (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
Department of Transportation's Regulatory Policies and Procedures. The
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
Executive Order 13990, ``Protecting Public Health and the
Environment and Restoring Science to Tackle the Climate Crisis'' (86 FR
7037, Jan. 25, 2021), directed the immediate review of ``The Safer
Affordable Fuel-Efficient (SAFE)
[[Page 49840]]
Vehicles Rule for Model Years 2021-2026 Passenger Cars and Light
Trucks'' (the 2020 final rule) by July 2021. The Executive order
directed that ``In considering whether to propose suspending, revising,
or rescinding that rule, the agency [i.e., NHTSA] should consider the
views of representatives from labor unions, States, and industry.''
This proposal follows the review directed in this Executive order.
Promulgated under NHTSA's statutory authorities, it proposes new CAFE
standards for the model years covered by the 2020 final rule for which
there is still available lead time to change, and it accounts for the
views provided by labor unions, States, and industry.
D. Environmental Considerations
1. National Environmental Policy Act (NEPA)
Concurrently with this NPRM, NHTSA is issuing a Supplemental
Environmental Impact Statement (SEIS), pursuant to the National
Environmental Policy Act, 42 U.S.C. 4321-4347, and implementing
regulations issued by the Council on Environmental Quality (CEQ), 40
CFR part 1500, and NHTSA, 49 CFR part 520. NHTSA prepared the SEIS to
analyze and disclose the potential environmental impacts of the
proposed CAFE standards and a range of alternatives. The SEIS analyzes
direct, indirect, and cumulative impacts and analyzes impacts in
proportion to their significance.
The SEIS 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, noise, and environmental justice.
The SEIS also describes how climate change resulting from global carbon
dioxide emissions (including CO2 emissions attributable to
the U.S. light-duty 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 SEIS.
NHTSA has considered the information contained in the SEIS as part
of developing this proposal. The SEIS 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 SEIS.
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 each 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 ([micro]g/
m\3\) 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. 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 Federal Implementation Plan after
EPA has approved or promulgated it.\555\ 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.\556\ 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, 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:
---------------------------------------------------------------------------
\555\ 42 U.S.C.7506(c)(1).
\556\ 42 U.S.C. 7506(c)(2).
---------------------------------------------------------------------------
(1) The Transportation Conformity Rule \557\ applies to
transportation plans, programs, and projects that are developed,
funded, or approved under title 23 or chapter 53 of title 49, U.S.C.
---------------------------------------------------------------------------
\557\ 40 CFR part 51, subpart T, and part 93, subpart A.
---------------------------------------------------------------------------
(2) The General Conformity Rule \558\ 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.\559\ If the net increases of direct and indirect
emissions exceed any of these thresholds, and the action is not
otherwise exempt, then a conformity 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.
---------------------------------------------------------------------------
\558\ 40 CFR part 51, subpart W, and part 93, subpart B.
\559\ 40 CFR 93.153(b).
---------------------------------------------------------------------------
The proposed CAFE standards and associated program activities are
not developed, funded, or approved under title 23 or chapter 53 of
title 49, U.S.C. Accordingly, this action and associated program
activities are not 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
[[Page 49841]]
below, NHTSA's proposed action results 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 area
and occur at the same time and place as the action and are reasonably
foreseeable.'' \560\ NHTSA's proposed action would set fuel economy
standards for light-duty vehicles. It therefore would not cause or
initiate direct emissions consistent with the meaning of the General
Conformity Rule.\561\ 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 economy prices and savings, which are at best
indirect.
---------------------------------------------------------------------------
\560\ 40 CFR 93.152.
\561\ Dep't of Transp. v. Pub. Citizen, 541 U.S. 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 MYs 2024-2026 passenger cars and light trucks; an
emissions increase, if any, would occur in a different place and
well after promulgation of an eventual final rule.
---------------------------------------------------------------------------
Indirect emissions under the General Conformity Rule are those
emissions of a criteria pollutant or its precursors: 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; that are reasonably foreseeable; that the agency can
practically control; and for which the agency has continuing program
responsibility.\562\ 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 standards would not be caused by NHTSA'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.'' \563\
---------------------------------------------------------------------------
\562\ 40 CFR 93.152.
\563\ Id.
---------------------------------------------------------------------------
As the CAFE program uses performance-based standards, NHTSA cannot
control the technologies vehicle manufacturers use to improve the fuel
economy of passenger cars and light trucks. Furthermore, NHTSA cannot
control consumer purchasing (which affects average achieved fleetwide
fuel economy) and driving behavior (i.e., operation of motor vehicles,
as measured by VMT). It is the combination of fuel economy
technologies, consumer purchasing, and driving behavior that results in
criteria pollutant or precursor emissions. For purposes of analyzing
the environmental impacts of the proposal and alternatives under NEPA,
NHTSA has made assumptions and estimates regarding all of these
factors. The agency's SEIS 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.\564\
---------------------------------------------------------------------------
\564\ See, e.g., Dep't of Transp. v. Pub. Citizen, 541 U.S. 752,
772-73 (2004); South Coast Air Quality Management District v.
Federal Energy Regulatory Commission, 621 F.3d 1085, 1101 (9th Cir.
2010).
---------------------------------------------------------------------------
In addition, NHTSA does not have the statutory authority to control
the actual VMT by drivers. As the extent of emissions depends directly
on the operation of motor vehicles, changes in any emissions that could
result from NHTSA's proposed standards are not changes the agency can
practically control or for which the agency has continuing program
responsibility. Therefore, the proposed 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 policies
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.\565\ NHTSA concludes that the NHPA is
not applicable to this proposal because the promulgation of CAFE
standards for light-duty vehicles 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
alternatives on historical and cultural resources in the SEIS.
---------------------------------------------------------------------------
\565\ Section 106 is 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, the Act 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.
5. Coastal Zone Management Act (CZMA)
The Coastal Zone Management Act (16 U.S.C. 1451 et seq.) provides
for the presentation, protection, development, and (where 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.\566\
---------------------------------------------------------------------------
\566\ 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 its SEIS of the related direct, indirect, and
cumulative impacts, positive or negative, of all the 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 or result in the destruction or adverse
[[Page 49842]]
modification of the designated critical habitat of these species.\567\
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 of the Department of the Interior and/or the National Oceanic
and Atmospheric Administration's National Marine Fisheries Service of
the Department of Commerce, 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.\568\ Under
this standard, the Federal agency taking action evaluates the possible
effects of its action and determines whether to initiate
consultation.\569\
---------------------------------------------------------------------------
\567\ 16 U.S.C. 1536(a)(2).
\568\ See 50 CFR 402.14.
\569\ See 51 FR 9926, 19949 (Jun. 3, 1986).
---------------------------------------------------------------------------
Pursuant to Section 7(a)(2) of the ESA, NHTSA has considered the
effects of the proposed standards and has 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 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. Executive Order 11988 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 sets forth DOT
policies and procedures for implementing Executive Order 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 SEIS.
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. Executive Order 11990 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 sets forth DOT policy for interpreting Executive Order 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 proposal. NHTSA has, however, conducted a
review of the alternatives on potentially affected resources, including
wetlands, in its SEIS.
9. Migratory Bird Treaty Act (MTBA), Bald and Golden Eagle Protection
Act (BGEPA), Executive Order 13186
The MTBA (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 for barter, barter, offer to purchase, purchase,
deliver for shipment, ship, export, import, cause to be shipped,
exported, or imported, deliver for transportation, carry or cause to be
carried, or receive for shipment, transportation, carriage, or export''
any migratory bird covered under the statute.\570\
---------------------------------------------------------------------------
\570\ 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.\571\ Executive Order
13186, ``Responsibilities of Federal Agencies to Protect Migratory
Birds,'' helps to further the purposes of the MBTA by requiring a
Federal agency to develop a Memorandum of Understanding (MOU) with the
Fish and Wildlife Service when it is taking an action that has (or is
likely to have) a measurable negative impact on migratory bird
populations.
---------------------------------------------------------------------------
\571\ 16 U.S.C. 668(a).
---------------------------------------------------------------------------
NHTSA concludes that the MBTA, BGEPA, and Executive Order 13186 do
not apply to this proposal 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) property results in a de minimis impact on the area.
NHTSA concludes that Section 4(f) does not apply to this proposal
because this rulemaking is not an approval of a transportation program
nor project that requires the use of any publicly owned land.
[[Page 49843]]
11. Executive Order 12898: ``Federal Actions To Address Environmental
Justice in Minority Populations and Low-Income Populations''
Executive Order 12898, ``Federal Actions to Address Environmental
Justice 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. A White House Environmental Justice
Interagency Council established under E.O. 14008, ``Tackling the
Climate Crisis at Home and Abroad,'' is expected to advise CEQ on ways
to update E.O. 12898, including the expansion of environmental justice
advice and recommendations. The White House Environmental Justice
Interagency Council will advise on increasing environmental justice
monitoring and enforcement.
Additionally, the 2021 DOT Order 5610.2(c), ``U.S. Department of
Transportation Actions to Address Environmental Justice in Minority
Populations and Low-Income Populations'' (May 14, 2021), describes the
process for DOT agencies to incorporate environmental justice
principles in programs, policies, and activities. The DOT's
Environmental Justice Strategy specifies that environmental justice 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 term minority and low-income in the
context of DOT's environmental justice 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 environmental justice strategy to ensure that it continues to
reflect its commitment to environmental justice principles and
integrating those principles into DOT programs, policies, and
activities.
Section VI and the SEIS discuss NHTSA's consideration of
environmental justice issues associated with this proposal.
12. Executive Order 13045: ``Protection of Children From Environmental
Health Risks and Safety Risks''
This action is subject to Executive Order 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
regulation on children and an explanation of why the planned regulation
is preferable to other potentially effect 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 SEIS discuss
air quality, climate change, and their related environmental and health
effects, noting where these would disproportionately affect children.
In addition, Section VI of this preamble explains why NHTSA believes
that the proposed standards are preferable to other alternatives
considered.
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 a notice
of proposed rulemaking 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 certifies that this proposed rule would
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.\572\ One of the criteria for
determining size is the number of employees in the firm. For
establishments primarily engaged in manufacturing or assembling
automobiles, as well as light duty trucks, the firm must have less than
1,500 employees to be classified as a small business. This rule would
affect motor vehicle manufacturers. As shown in Table IX-1, the agency
have identified 13 small manufacturers of passenger cars, light trucks,
and SUVs of electric, hybrid, and internal combustion engines. NHTSA
acknowledges that some newer manufacturers may not be listed. However,
those new manufacturers tend to have transportation products that are
not part of the light-duty vehicle fleet and have yet to start
production of light-duty vehicles. Moreover, NHTSA does not believe
that there are a ``substantial number'' of these newer companies.\573\
---------------------------------------------------------------------------
\572\ Classified in NAICS under Subsector 336--Transportation
Equipment Manufacturing for Automobile Manufacturing (336111), Light
Truck (336112), and Heavy Duty Truck Manufacturing (336120). https://www.sba.gov/document/support--table-size-standards.
\573\ 5 U.S.C. 605(b).
---------------------------------------------------------------------------
[[Page 49844]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.204
NHTSA believes that the proposed rulemaking would not have a
significant economic impact on the small vehicle manufacturers because
under 49 CFR part 525, passenger car manufacturers building fewer than
10,000 vehicles per year can petition NHTSA to have alternative
standards set for those manufacturers. Listed manufacturers producing
ICE vehicles do not currently meet the standard and must already
petition the agency 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, which is the
purpose of the Regulatory Flexibility Act, a regulatory flexibility
analysis was not prepared.
---------------------------------------------------------------------------
\574\ Estimated number of employees as of June 2021, source:
Linkedin.com and other websites reporting company profiles.
\575\ Rough estimate of light duty vehicle production for model
year 2020.
---------------------------------------------------------------------------
Further, small manufacturers of electric vehicles 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 rule
had a ``significant economic impact'' on these small EV manufacturers,
the amount of these companies is not ``a substantial number.'' \576\
For these reasons, their existence does not alter the agency's analysis
of the applicability of the Regulatory Flexibility Act.
---------------------------------------------------------------------------
\576\ 5 U.S.C. 605.
---------------------------------------------------------------------------
F. Executive Order 13132 (Federalism)
Executive Order 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. NHTSA has complied with the order's
requirements and consulted directly with the California Air Resources
Board in developing a number of elements of this proposal. This
proposal would not impose direct compliance costs on State or local
governments, because the only entities directly subject to the proposal
are vehicle manufacturers.
With regard to the federalism implications of the proposal, NHTSA
has spoken to this issue separately at 86 FR 25980 (May 12, 2021),
``Corporate Average Fuel Economy (CAFE) Preemption,'' notice of
proposed rulemaking. Comments on preemption of State and local laws
related to fuel economy standards that are received to this NPRM will
be deemed late comments to that NPRM (the comment period for which has
closed) and will be considered as time permits.
G. Executive Order 12988 (Civil Justice Reform)
Pursuant to Executive Order 12988, ``Civil Justice Reform'' (61 FR
4729, Feb. 7, 1996), NHTSA has considered whether this rulemaking 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
Executive Order 13175 (65 FR 67249, Nov. 9, 2000). This proposal, if
finalized, would be implemented at the Federal level and would impose
compliance costs only on vehicle manufacturers. Thus, Executive Order
13175, which requires consultation with Tribal officials when agencies
are developing policies that have ``substantial direct effects'' on
Tribes and Tribal interests, should 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
[[Page 49845]]
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 2018 results in $153 million
(110.296/71.868 = 1.53).\577\ Before 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 the agency publishes with the rule an
explanation of why that alternative was not adopted.
---------------------------------------------------------------------------
\577\ Bureau of Economic Analysis, National Income and Product
Accounts (NIPA), Table 1.1.9 Implicit Price Deflators for Gross
Domestic Product. https://bea.gov/iTable/index_nipa.cfm.
---------------------------------------------------------------------------
This proposal would not result in the expenditure by State, local,
or Tribal governments, in the aggregate, of more than $153 million
annually, but it will result in the expenditure of that magnitude by
vehicle manufacturers and/or their suppliers. In developing this
proposal, NHTSA considered alternative fuel economy standards both
lower and higher than the preferred alternative. NHTSA tentatively
concludes that the preferred alternative represents the least costly,
most cost-effective, and least burdensome alternative that achieves the
objectives of the proposal.
J. Regulation Identifier Number
The Department of Transportation 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 and EPA to 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.\578\
---------------------------------------------------------------------------
\578\ 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
(ASTM), the Society of Automotive Engineers (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
the reasons for not using such standards. There are currently no
consensus standards that NHTSA administers relevant to this proposed
CAFE standards.
L. Department of Energy Review
In accordance with 49 U.S.C. 32902(j)(1), NHTSA submitted this rule
to the Department of Energy for review. The Department of Energy
concluded that the standard would not adversely affect its conservation
goals.
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.
NHTSA is seeking OMB's approval for a revision to NHTSA's existing
information collection for its reporting requirements under the
Corporate Average Fuel Economy (CAFE) program (OMB control number 2127-
0019). These reporting requirements are necessary to ensure compliance
with its CAFE program. As described in this NPRM, NHTSA is proposing
changes to the CAFE program's standardized reporting templates for
manufacturers to submit information to NHTSA on their vehicle
production and CAFE credits used to comply with the CAFE standards.
These changes, if adopted, will result in additional burden to
respondents.
The Information Collection Request (ICR) for a revision of an
existing information collection described below has been forwarded to
OMB for review and comment. In compliance with the requirements of the
PRA, NHTSA asks for public comments on the following proposed
collection of information for which the agency is seeking approval from
OMB.
Title: Corporate Average Fuel Economy.
OMB Control Number: 2127-0019.
Form Numbers: NHTSA Form 1474 (CAFE Projections Reporting
Template), NHTSA Form 1475 (CAFE Credit Template) and NHTSA Form 1621
(CAFE Credit Trade Template).
Type of Request: Revision of a currently approved collection.
Type of Review Requested: Regular.
Requested Expiration Date of Approval: Three years from date of
approval.
Summary of the Collection of Information: As established by
Congress under EPCA, and later amended by EISA, and implemented through
NHTSA's regulations for automobile manufacturers complying with CAFE
standards prescribed in 49 U.S.C. 32902, many types of reporting
provisions exist as a part of the CAFE program. These reporting
provisions are necessary for NHTSA to ensure manufacturers comply with
CAFE standards and other CAFE requirements. Manufacturers are required
to submit information on CAFE standards, exemptions, vehicles,
technologies, and submit CAFE compliance test results. Manufacturers
also provide information on any of the flexibilities and incentives
they use during the model year to comply with CAFE standards.
More specifically, the current collection includes burden hours for
small volume manufacturers to request exemptions allowing them to
comply with lower alternative CAFE standards to accommodate mainly the
sale of exotic sportscars. It also includes hours for manufacturers
reporting information on corporate mergers and splits. Other required
reporting includes manufacturers submitting information to NHTSA on
CAFE credit transactions, plans and other documents associated with the
costs of credit trades. In the April 30, 2020, final rule, to help
manufacturers better organize credit information, NHTSA also issued a
new standardized template for manufacturers to report credit
transactions and to prepare credit trade documents. The template could
generate the necessary documents that both parties would sign
[[Page 49846]]
to facilitate credit trades as well as simplified the organization of
other types of credit transactions in addition to correctly performing
the necessary mathematical calculations. Finally, the current
collection also includes hours for manufacturers to provide pre-model
year (PMY) and mid-model year (MMY) CAFE reports to NHTSA and a
standardized reporting template adopted in the April 30, 2020, final
rule to help manufacturer submit these reports. PMY and MMY reports
contain early projections of manufacturers' vehicle and fleet level
data demonstrating how they intend to comply with CAFE standards.
As part of this rulemaking, NHTSA is amending its previously
approved collection for CAFE-related collections of information. NHTSA
is proposing making changes to its reporting template for PMY and MMY
reports and adding a new template for reporting the cost of credit
trades and is proposing to add the burden hours for these changes to
this collection.
Manufacturers identified several changes that were needed to the
CAFE reporting template to accommodate different types of vehicles
which NHTSA incorporated along with other functional changes.
Manufacturers have also expressed concern that disclosing trading
terms may not be as simple as a spot purchase at a given price. As
discussed in the April 30, 2020, final rule, manufacturers contend that
a number of transactions for both CAFE and CO2 credits
involve a range of complexity due to numerous factors that are
reflective of the marketplace, such as the volume of credits,
compliance category, credit expiration date, a seller's compliance
strategy, and even the CAFE penalty rate in effect at that time. In
addition, manufacturers have a range of partnerships and cooperative
agreements with their own competitors. Credit transactions can be an
offshoot of these broader relationships, and difficult to price
separately and independently. Thus, manufacturers argue that there may
not be a reasonable, or even meaningful, presentation of market
information in a transaction price. Therefore, NHTSA has developed a
new template for capturing the price of credit trades that includes
certain monetary and non-monetary terms of credit trading contracts.
NHTSA proposes that manufacturers start using the new template starting
September 1, 2022.
Description of the Need for the Information and the Proposed Use of
the Information: Regulated entities are required to respond to
inquiries covered by this collection. 49 U.S.C. 32907. 49 CFR parts
525, 534, 536, and 537.
Affected Public: Respondents are manufacturers of engines and
vehicles within the North American Industry Classification System
(NAICS) and use the coding structure as defined by NAICS including
codes 33611, 336111, 336112, 33631, 33631, 33632, 336320, 33635, and
336350 for motor vehicle and parts manufacturing.
Frequency of response: Variable, based on compliance obligation.
Please see PRA supporting documentation in the docket for more detailed
information.
Average burden time per response: Variable, based on compliance
obligation. Please see PRA supporting documentation in the docket for
more detailed information.
Number of respondents: 23.
1. Estimated Total Annual Burden Hours and Costs
[GRAPHIC] [TIFF OMITTED] TP03SE21.205
Public Comments Invited: You are asked to comment on any aspects of
this information collection, including (a) whether the proposed
collection of information is necessary for the proper performance of
the functions of the Department, including whether the information will
have practical utility; (b) the accuracy of the Department's estimate
of the burden of the proposed information collection; (c) ways to
enhance the quality, utility and clarity of the information to be
collected; and (d) ways to minimize the burden of the collection of
information on respondents, including the use of automated collection
techniques or other forms of information technology.
Please submit any comments, identified by the docket number in the
heading of this document, by the methods described in the ADDRESSES
section of this document to NHTSA and OMB. Although comments may be
submitted during the entire comment period, comments received within 30
days of publication are most useful.
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 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.
List of Subjects in 49 CFR Parts 531, 533, 536, and 537
Fuel economy, Reporting and recordkeeping requirements.
Regulatory Text
For the reasons discussed in the preamble, the National Highway
Traffic Safety Administration proposes to amend 49 CFR chapter V as
follows:
0
1. Revise part 531 to read as follows:
PART 531--PASSENGER AUTOMOBILE AVERAGE FUEL ECONOMY STANDARDS
Sec.
531.1 Scope.
531.2 Purpose.
531.3 Applicability.
531.4 Definitions.
531.5 Fuel economy standards.
531.6 Measurement and calculation procedures.
[[Page 49847]]
Appendix A to Part 531--Example of Calculating Compliance Under
Sec. 531.5(c)
Authority: 49 U.S.C. 32902; delegation of authority at 49 CFR
1.95.
Sec. 531.1 Scope.
This part establishes average fuel economy standards pursuant to
section 502 (a) and (c) of the Motor Vehicle Information and Cost
Savings Act, as amended, for passenger automobiles.
Sec. 531.2 Purpose.
The purpose of this part is to increase the fuel economy of
passenger automobiles by establishing minimum levels of average fuel
economy for those vehicles.
Sec. 531.3 Applicability.
This part applies to manufacturers of passenger automobiles.
Sec. 531.4 Definitions.
(a) Statutory terms. (1) The terms average fuel economy,
manufacture, manufacturer, and model year are used as defined in
section 501 of the Act.
(2) The terms automobile and passenger automobile are used as
defined in section 501 of the Act 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) Act means the Motor Vehicle Information and Cost Savings Act,
as amended by Pub. L. 94-163.
(2) [Reserved]
Sec. 531.5 Fuel economy standards.
(a) Except as provided in paragraph (f) 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:
[GRAPHIC] [TIFF OMITTED] TP03SE21.206
(b) 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 to this
[[Page 49848]]
paragraph (b) and the appropriate values in Table 2 to this paragraph
(b).
[GRAPHIC] [TIFF OMITTED] TP03SE21.207
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] TP03SE21.208
Where:
Parameters a, b, c, and d are defined in Table 2 of this paragraph
(b);
e = 2.718; and
x = footprint (in square feet, rounded to the nearest tenth) of the
vehicle model.
[GRAPHIC] [TIFF OMITTED] TP03SE21.209
(c) For model years 2012-2026, a manufacturer's passenger
automobile fleet shall comply with the fleet average fuel economy level
calculated for that model year according to Figure 2 to this paragraph
(c) and the appropriate values in Table 3 to this paragraph (c).
[GRAPHIC] [TIFF OMITTED] TP03SE21.210
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; and
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 to this paragraph (c)
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.
[[Page 49849]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.211
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.
[[Page 49850]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.212
(d) In addition to the requirements of paragraphs (b) and (c) of
this section, each manufacturer shall also meet the minimum fleet
standard for domestically manufactured passenger automobiles expressed
in Table 4 to this paragraph (d):
[[Page 49851]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.213
(e) The following manufacturers shall comply with the standards
indicated in paragraphs (e)(1) through (15) of this section for the
specified model years:
(1) Avanti Motor Corporation.
[[Page 49852]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.214
(2) Rolls-Royce Motors, Inc.
[GRAPHIC] [TIFF OMITTED] TP03SE21.215
[[Page 49853]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.216
[[Page 49854]]
(3) Checker Motors Corporation.
[GRAPHIC] [TIFF OMITTED] TP03SE21.217
(4) Aston Martin Lagonda, Inc.
[GRAPHIC] [TIFF OMITTED] TP03SE21.218
[[Page 49855]]
(5) Excalibur Automobile Corporation.
[GRAPHIC] [TIFF OMITTED] TP03SE21.219
(6) Lotus Cars Ltd.
[GRAPHIC] [TIFF OMITTED] TP03SE21.220
(7) Officine Alfieri Maserati, S.p.A.
[GRAPHIC] [TIFF OMITTED] TP03SE21.221
[[Page 49856]]
(8) Lamborghini of North America.
[GRAPHIC] [TIFF OMITTED] TP03SE21.223
(9) LondonCoach Co., Inc.
[GRAPHIC] [TIFF OMITTED] TP03SE21.224
(10) Automobili Lamborghini S.p.A./Vector Aeromotive Corporation.
[GRAPHIC] [TIFF OMITTED] TP03SE21.225
[[Page 49857]]
(11) Dutcher Motors, Inc.
[GRAPHIC] [TIFF OMITTED] TP03SE21.226
(12) MedNet, Inc.
[GRAPHIC] [TIFF OMITTED] TP03SE21.227
(13) Vector Aeromotive Corporation.
[GRAPHIC] [TIFF OMITTED] TP03SE21.228
[[Page 49858]]
(14) Qvale Automotive Group Srl.
[GRAPHIC] [TIFF OMITTED] TP03SE21.229
(15) Spyker Automobielen B.V.
[GRAPHIC] [TIFF OMITTED] TP03SE21.230
Sec. 531.6 Measurement and calculation procedures.
(a) The fleet average fuel economy performance of all passenger
automobiles that are manufactured by a manufacturer in a model year
shall be determined in accordance with procedures established by the
Administrator of the Environmental Protection Agency (EPA) under 49
U.S.C. 32904 and set forth in 40 CFR part 600.
(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 EPA set forth in 40 CFR part 600,
subpart F, including any adjustments to fuel economy the EPA allows,
such as for fuel consumption improvements related to air conditioning
efficiency and off-cycle technologies. Manufacturers must provide
reporting on these technologies as specified in 49 CFR 537.7 by the
required deadlines.
(1) Efficient air conditioning technologies. A manufacturer that
seeks to increase its fleet average fuel economy performance through
the use of technologies that improve the efficiency of air conditioning
systems must follow the requirements in 40 CFR 86.1868-12. Fuel
consumption improvement values resulting from the use of those air
conditioning systems must be determined in accordance with 40 CFR
600.510-12(c)(3)(i).
(2) Off-cycle technologies on EPA's predefined list or using 5-
cycle testing. A manufacturer that seeks to increase its fleet average
fuel economy performance through the use of off-cycle technologies must
follow the requirements in 40 CFR 86.1869-12. A manufacturer is
eligible to gain fuel consumption improvements for predefined off-cycle
technologies in accordance with 40 CFR 86.1869-12(b) or for
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).
(3) Off-cycle technologies using the alternative EPA-approved
methodology. A manufacturer is eligible 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)(3)(i)(A) through (C) of
this section. Paragraphs (b)(3)(i)(A), (B), and (D) of this section
apply starting in model year 2024.
(A) A manufacturer seeking to increase its fuel economy performance
using the alternative methodology for an off-cycle technology, if prior
to the applicable model year, must submit to EPA a detailed analytical
plan and be approved (i.e., for its planned test procedure and model
types for demonstration) 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 also
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) Manufacturer's plans, applications, and requests approved by
the EPA must be made in consultation with the National Highway Traffic
Safety Administration (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
[[Page 49859]]
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)(3)(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].
(ii) Review and approval process. NHTSA will provide its views on
the suitability of using the off-cycle technology to adjust the fuel
economy performance 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 identified
as a part of NHTSA's safety defects program, and technologies that are
not performing as intended, will have the values of approved off-cycle
credits removed from the manufacturer's credit balance or adjusted if
the manufacturers can remedy the defective technology. 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) (49 CFR part 571). 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.
Appendix A to Part 531--Example of Calculating Compliance Under Sec.
531.5(c)
Assume a hypothetical manufacturer (Manufacturer X) produces a
fleet of domestic passenger automobiles in MY 2012 as follows:
[[Page 49860]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.231
[[Page 49861]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.232
[[Page 49862]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.233
[GRAPHIC] [TIFF OMITTED] TP03SE21.234
[GRAPHIC] [TIFF OMITTED] TP03SE21.235
[[Page 49863]]
2. Revise part 533 to read as follows:
PART 533--LIGHT TRUCK FUEL ECONOMY STANDARDS
Sec.
533.1 Scope.
533.2 Purpose.
533.3 Applicability.
533.4 Definitions.
533.5 Requirements.
533.6 Measurement and calculation procedures.
Appendix A to Part 533--Example of Calculating Compliance Under
Sec. 533.5(i)
Authority: 49 U.S.C. 32902; delegation of authority at 49 CFR
1.95.
Sec. 533.1 Scope.
This part establishes average fuel economy standards pursuant to
section 502(b) of the Motor Vehicle Information and Cost Savings Act,
as amended, for light trucks.
Sec. 533.2 Purpose.
The purpose of this part is to increase the fuel economy of light
trucks by establishing minimum levels of average fuel economy for those
vehicles.
Sec. 533.3 Applicability.
This part applies to manufacturers of light trucks.
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 section 501 of the Act.
(2) The term automobile is used as defined in section 501 of the
Act and in accordance with the determinations in part 523 of this
chapter.
(3) The term domestically manufactured is used as defined in
section 503(b)(2)(E) of the Act.
(b) Other terms. As used in this part, unless otherwise required by
the context--
(1) Act means the Motor Vehicle Information Cost Savings Act, as
amended by Public Law 94-163.
(2) Light truck is used in accordance with the determinations in
part 523 of this chapter.
(3) Captive import means with respect to a light truck, one which
is not domestically manufactured but which is imported in the 1980
model year or thereafter by a manufacturer whose principal place of
business is in the United States.
(4) 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.
(5) 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.
(6) 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.
Sec. 533.5 Requirements.
(a) Each manufacturer of light trucks shall comply with the
following fleet average fuel economy standards, expressed in miles per
gallon, in the model year specified as applicable:
BILLING CODE 4910-59-P
[GRAPHIC] [TIFF OMITTED] TP03SE21.236
[[Page 49864]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.237
[[Page 49865]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.238
[GRAPHIC] [TIFF OMITTED] TP03SE21.239
[[Page 49866]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.240
Where:
N is the total number (sum) of light trucks produced by a
manufacturer;
Ni is the number (sum) of the ith light truck model type
produced by a manufacturer; and
Ti is the fuel economy target of the ith light truck
model type, which is determined according to the following formula,
rounded to the nearest hundredth:
[GRAPHIC] [TIFF OMITTED] TP03SE21.241
Where:
Parameters a, b, c, and d are defined in Table 5 to this paragraph
(a);
e = 2.718; and
x = footprint (in square feet, rounded to the nearest tenth) of the
model type.
[GRAPHIC] [TIFF OMITTED] TP03SE21.242
[GRAPHIC] [TIFF OMITTED] TP03SE21.243
Where:
CAFErequired is the fleet average fuel economy standard
for a given light truck fleet;
Subscript i is a designation of multiple groups of light trucks,
where each group's designation, i.e., i = 1, 2, 3, etc., represents
light trucks that share a unique model type and footprint within the
applicable fleet;
Productioni is the number of light trucks produced for
sale in the United States within each ith designation,
i.e., which share the same model type and footprint; and
TARGETi is the fuel economy target in miles per gallon (mpg)
applicable to the footprint of light trucks within each ith
designation, i.e., which share the same model type and footprint,
calculated according to either Figure 3 or Figure 4 to this
paragraph (a), as appropriate, 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.
[GRAPHIC] [TIFF OMITTED] TP03SE21.244
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 6 to this paragraph
(a); and
The MIN and MAX functions take the minimum and maximum,
respectively, of the included values.
[[Page 49867]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.245
[GRAPHIC] [TIFF OMITTED] TP03SE21.246
Where:
TARGET is the fuel economy target (in mpg) applicable to vehicles of
a given footprint (FOOTPRINT, in square feet);
Parameters a, b, c, d, e, f, g, and h are defined in Table 7 to this
paragraph (a); and
The MIN and MAX functions take the minimum and maximum,
respectively, of the included values.
[[Page 49868]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.247
(b)(1) For model year 1979, each manufacturer may:
(i) Combine its 2- and 4-wheel drive light trucks and comply with
the average fuel economy standard in paragraph (a) of this section for
2-wheel drive light trucks; or
(ii) Comply separately with the two standards specified in
paragraph (a) of this section.
(2) For model year 1979, the standard specified in paragraph (a) of
this section for 4-wheel drive light trucks applies only to 4-wheel
drive general utility vehicles. All other 4-wheel drive light trucks in
that model year shall be included in the 2-wheel drive category for
compliance purposes.
(c) For model years 1980 and 1981, manufacturers of limited product
line light trucks may:
(1) Comply with the separate standard for limited product line
light trucks; or
(2) Comply with the other standards specified in paragraph (a) of
this section, as applicable.
(d) For model years 1982-91, each manufacture may:
(1) Combine its 2- and 4-wheel drive light trucks (segregating
captive import and other light trucks) and comply with the combined
average fuel economy standard specified in paragraph (a) of this
section; or
(2) Comply separately with the 2-wheel drive standards and the 4-
wheel drive standards (segregating captive import and other light
trucks) specified in paragraph (a) of this section.
(e) For model year 1992, each manufacturer shall comply with the
average fuel economy standard specified in paragraph (a) of this
section (segregating captive import and other light trucks).
(f) For each model year 1996 and thereafter, each manufacturer
shall combine its captive imports with its other light trucks and
comply with the fleet average fuel economy standard in paragraph (a) of
this section.
(g) For model years 2008-2010, at a manufacturer's option, a
manufacturer's light truck fleet may comply with the fuel economy
standard calculated for each model year according to Figure 1 to
paragraph (a) of this section and the
[[Page 49869]]
appropriate values in Table 5 to paragraph (a) of this section, with
said option being irrevocably chosen for that model year and reported
as specified in Sec. 537.8 of this chapter.
(h) For model year 2011, a manufacturer's light truck fleet shall
comply with the fleet average fuel economy standard calculated for that
model year according to Figure 1 to paragraph (a) of this section and
the appropriate values in Table 5 to paragraph (a) of this section.
(i) For model years 2012-2016, 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 3 to paragraph (a) of
this section and the appropriate values in Table 6 to paragraph (a) of
this section.
(j) For model years 2017-2025, 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.
Sec. 533.6 Measurement and calculation procedures.
(a) Any reference to a class of light trucks manufactured by a
manufacturer shall be deemed--
(1) To include all light trucks in that class manufactured by
persons who control, are controlled by, or are under common control
with, such manufacturer; and
(2) To include only light trucks which qualify as non-passenger
vehicles in accordance with 49 CFR 523.5 based upon the production
measurements of the vehicles as sold to dealerships; and
(3) To exclude all light trucks in that class manufactured (within
the meaning of paragraph (a)(1) of this section) during a model year by
such manufacturer which are exported prior to the expiration of 30 days
following the end of such model year.
(b) The fleet average fuel economy performance of all light trucks
that are manufactured by a manufacturer in a model year shall be
determined in accordance with procedures established by the
Administrator of the Environmental Protection Agency (EPA) under 49
U.S.C. 32904 and set forth in 40 CFR part 600.
(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 EPA set forth in 40 CFR part 600,
subpart F, including any adjustments to fuel economy the EPA allows,
such as for fuel consumption improvements related to air conditioning
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 49 CFR 537.7 by
the required deadlines.
(1) Efficient air conditioning technologies. A manufacturer that
seeks to increase its fleet average fuel economy performance through
the use of technologies that improve the efficiency of air conditioning
systems must follow the requirements in 40 CFR 86.1868-12. Fuel
consumption improvement values resulting from the use of those air
conditioning systems must be determined in accordance with 40 CFR
600.510-12(c)(3)(i).
(2) Incentives for advanced full-size light-duty pickup trucks. The
eligibility of a manufacturer to increase its fuel economy using
hybridized and other performance-based technologies for full-size
pickup trucks must follow 40 CFR 86.1870-12 and the fuel consumption
improvement of these full-size pickup truck technologies must be
determined in accordance with 40 CFR 600.510-12(c)(3)(iii).
Manufacturers may also combine incentives for full size pickups and
dedicated alternative fueled vehicles when calculating fuel economy
performance values in 40 CFR 600.510-12.
(3) Off-cycle technologies on EPA's predefined list or using 5-
cycle testing. A manufacturer that seeks to increase its fleet average
fuel economy performance through the use of off-cycle technologies must
follow the requirements in 40 CFR 86.1869-12. A manufacturer is
eligible to gain fuel consumption improvements for predefined off-cycle
technologies in accordance with 40 CFR 86.1869-12(b) or for
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. A manufacturer is eligible 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)(4)(i)(A) through (C) of
this section. Paragraphs (c)(4)(i)(A) through (C) of this section apply
starting in model year 2024.
(A) A manufacturer seeking to increase its fuel economy performance
using the alternative methodology for an off-cycle technology, if prior
to the applicable model year, must submit to EPA a detailed analytical
plan and be approved (i.e., for its planned test procedure and model
types for demonstration) 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 also
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) Manufacturer's plans, applications and requests approved by the
EPA must be made in consultation with the National Highway Traffic
Safety Administration (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.
(ii) Review and approval process. NHTSA will provide its views on
the suitability of using the off-cycle technology to adjust the fuel
economy performance 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 identified
as a part of NHTSA's safety defects program, and technologies that are
not performing as intended, will have the values of approved off-cycle
credits removed from
[[Page 49870]]
the manufacturer's credit balance or adjusted if the manufacturers can
remedy the defective technology. 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) (49 CFR part 571). 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.
Appendix A to Part 533--Example of Calculating Compliance Under Sec.
533.5(i)
Assume a hypothetical manufacturer (Manufacturer X) produces a
fleet of light trucks in MY 2012 as follows:
BILLING CODE 4910-59-P
[GRAPHIC] [TIFF OMITTED] TP03SE21.248
[[Page 49871]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.249
[[Page 49872]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.250
[[Page 49873]]
[GRAPHIC] [TIFF OMITTED] TP03SE21.251
[GRAPHIC] [TIFF OMITTED] TP03SE21.252
[GRAPHIC] [TIFF OMITTED] TP03SE21.253
[[Page 49874]]
BILLING CODE 4910-59-C
0
3. Revise part 536 to read as follows:
PART 536--TRANSFER AND TRADING OF FUEL ECONOMY CREDITS
Sec.
536.1 Scope.
536.2 Application.
536.3 Definitions.
536.4 Credits.
536.5 Trading infrastructure.
536.6 Treatment of credits earned prior to model year 2011.
536.7 Treatment of carryback credits.
536.8 Conditions for trading of credits.
536.9 Use of credits with regard to the domestically manufactured
passenger automobile minimum standard.
536.10 Treatment of dual-fuel and alternative fuel vehicles--
consistency with 49 CFR part 538.
Authority: 49 U.S.C. 32903; delegation of authority at 49 CFR
1.95.
Sec. 536.1 Scope.
This part establishes regulations governing the use and application
of corporate average fuel economy (CAFE) credits up to three model
years before and five model years after the model year in which the
credit was earned. It also specifies requirements for manufacturers
wishing to transfer fuel economy credits between their fleets and for
manufacturers and other persons wishing to trade fuel economy credits
to achieve compliance with prescribed fuel economy standards.
Sec. 536.2 Application.
This part applies to all credits earned (and transferable and
tradable) for exceeding applicable average fuel economy standards in a
given model year for domestically manufactured passenger cars, imported
passenger cars, and light trucks.
Sec. 536.3 Definitions.
(a) Statutory terms. All terms defined in 49 U.S.C. 32901(a) are
used pursuant to their statutory meaning.
(b) Other terms. As used in the part:
Above standard fuel economy means, with respect to a compliance
category, that the automobiles manufactured by a manufacturer in that
compliance category in a particular model year have greater average
fuel economy (calculated in a manner that reflects the incentives for
alternative fuel automobiles per 49 U.S.C. 32905) than that
manufacturer's fuel economy standard for that compliance category and
model year.
Adjustment factor means a factor used to adjust the value of a
traded or transferred credit for compliance purposes to ensure that the
compliance value of the credit when used reflects the total volume of
oil saved when the credit was earned.
Below standard fuel economy means, with respect to a compliance
category, that the automobiles manufactured by a manufacturer in that
compliance category in a particular model year have lower average fuel
economy (calculated in a manner that reflects the incentives for
alternative fuel automobiles per 49 U.S.C. 32905) than that
manufacturer's fuel economy standard for that compliance category and
model year.
Compliance means a manufacturer achieves compliance in a particular
compliance category when:
(1)(i) The average fuel economy of the vehicles in that category
exceed or meet the fuel economy standard for that category; or
(ii) The average fuel economy of the vehicles in that category do
not meet the fuel economy standard for that category, but the
manufacturer proffers a sufficient number of valid credits, adjusted
for total oil savings, to cover the gap between the average fuel
economy of the vehicles in that category and the required average fuel
economy.
(2) A manufacturer achieves compliance for its fleet if the
conditions in paragraph (1)(i) or (ii) of this definition are
simultaneously met for all compliance categories.
Compliance category means any of three categories of automobiles
subject to Federal fuel economy regulations. The three compliance
categories recognized by 49 U.S.C. 32903(g)(6) are domestically
manufactured passenger automobiles, imported passenger automobiles, and
non-passenger automobiles (``light trucks'').
Credit holder (or holder) means a legal person that has valid
possession of credits, either because they are a manufacturer who has
earned credits by exceeding an applicable fuel economy standard, or
because they are a designated recipient who has received credits from
another holder. Credit holders need not be manufacturers, although all
manufacturers may be credit holders.
Credits (or fuel economy credits) means an earned or purchased
allowance recognizing that the average fuel economy of a particular
manufacturer's vehicles within a particular compliance category and
model year exceeds that manufacturer's fuel economy standard for that
compliance category and model year. One credit is equal to \1/10\ of a
mile per gallon above the fuel economy standard per one vehicle within
a compliance category. Credits are denominated according to model year
in which they are earned (vintage), originating manufacturer, and
compliance category.
Expiry date means the model year after which fuel economy credits
may no longer be used to achieve compliance with fuel economy
regulations. Expiry dates are calculated in terms of model years: For
example, if a manufacturer earns credits for model year 2011, these
credits may be used for compliance in model years 2008-2016.
Fleet means all automobiles that are manufactured by a manufacturer
in a particular model year and are subject to fuel economy standards
under 49 CFR parts 531 and 533. For the purposes of this part, a
manufacturer's fleet means all domestically manufactured and imported
passenger automobiles and non-passenger automobiles (``light trucks'').
``Work trucks'' and medium and heavy trucks are not included in this
definition for purposes of this part.
Light truck means the same as ``non-passenger automobile,'' as that
term is defined in 49 U.S.C. 32901(a)(17), and as ``light truck,'' as
that term is defined at 49 CFR 523.5.
Originating manufacturer means the manufacturer that originally
earned a particular credit. Each credit earned will be identified with
the name of the originating manufacturer.
Trade means the receipt by the National Highway Traffic Safety
Administration (NHTSA) of an instruction from a credit holder to place
one of its credits in the account of another credit holder. A credit
that has been traded can be identified because the originating
manufacturer will be a different party than the current credit holder.
Traded credits are moved from one credit holder to the recipient credit
holder within the same compliance category for which the credits were
originally earned. If a credit has been traded to another credit holder
and is subsequently traded back to the originating manufacturer, it
will be deemed not to have been traded for compliance purposes.
Transfer means the application by a manufacturer of credits earned
by that manufacturer in one compliance category or credits acquired be
trade (and originally earned by another manufacturer in that category)
to achieve compliance with fuel economy standards with respect to a
different compliance category. For example, a manufacturer may purchase
light truck credits from another manufacturer, and transfer them to
achieve compliance in the manufacturer's domestically manufactured
passenger car fleet. Subject to the credit transfer limitations of 49
U.S.C. 32903(g)(3), credits can also be transferred across compliance
categories and banked or saved in that category to be carried forward
or
[[Page 49875]]
backwards later to address a credit shortfall.
Vintage means, with respect to a credit, the model year in which
the credit was earned.
Sec. 536.4 Credits.
(a) Type and vintage. All credits are identified and distinguished
in the accounts by originating manufacturer, compliance category, and
model year of origin (vintage).
(b) Application of credits. All credits earned and applied are
calculated, per 49 U.S.C. 32903(c), in tenths of a mile per gallon by
which the average fuel economy of vehicles in a particular compliance
category manufactured by a manufacturer in the model year in which the
credits are earned exceeds the applicable average fuel economy
standard, multiplied by the number of vehicles sold in that compliance
category. However, credits that have been traded between credit holders
or transferred between compliance categories are valued for compliance
purposes using the adjustment factor specified in paragraph (c) of this
section, pursuant to the ``total oil savings'' requirement of 49 U.S.C.
32903(f)(1).
(c) Adjustment factor. When traded or transferred and used, fuel
economy credits are adjusted to ensure fuel oil savings is preserved.
For traded credits, the user (or buyer) must multiply the calculated
adjustment factor by the number of shortfall credits it plans to offset
in order to determine the number of equivalent credits to acquire from
the earner (or seller). For transferred credits, the user of credits
must multiply the calculated adjustment factor by the number of
shortfall credits it plans to offset in order to determine the number
of equivalent credits to transfer from the compliance category holding
the available credits. The adjustment factor is calculated according to
the following formula:
[GRAPHIC] [TIFF OMITTED] TP03SE21.254
Where:
A = Adjustment factor applied to traded and transferred credits. The
quotient shall be rounded to 4 decimal places.
VMTe = Lifetime vehicle miles traveled as provided in the following
table for the model year and compliance category in which the credit
was earned.
VMTu = Lifetime vehicle miles traveled as provided in the following
table for the model year and compliance category in which the credit
is used for compliance.
[GRAPHIC] [TIFF OMITTED] TP03SE21.255
MPGse = Required fuel economy standard for the originating (earning)
manufacturer, compliance category, and model year in which the
credit was earned.
MPGae = Actual fuel economy for the originating manufacturer,
compliance category, and model year in which the credit was earned.
MPGsu = Required fuel economy standard for the user (buying)
manufacturer, compliance category, and model year in which the
credit is used for compliance.
MPGau = Actual fuel economy for the user manufacturer, compliance
category, and model year in which the credit is used for compliance.
Sec. 536.5 Trading infrastructure.
(a) Accounts. NHTSA maintains ``accounts'' for each credit holder.
The account consists of a balance of credits in each compliance
category and vintage held by the holder.
(b) Who may hold credits. Every manufacturer subject to fuel
economy standards under 49 CFR part 531 or 533 is automatically an
account holder. If the manufacturer earns credits pursuant to this
part, or receives credits from another party, so that the
manufacturer's account has a non-zero balance, then the manufacturer is
also a credit holder. Any party designated as a recipient of credits by
a current credit holder will receive an account from NHTSA and become a
credit holder, subject to the following conditions:
(1) A designated recipient must provide name, address, contacting
information, and a valid taxpayer identification number or Social
Security number;
(2) NHTSA does not grant a request to open a new account by any
party other than a party designated as a recipient of credits by a
credit holder; and
(3) NHTSA maintains accounts with zero balances for a period of
time, but reserves the right to close accounts that have had zero
balances for more than one year.
(c) Automatic debits and credits of accounts. (1) To carry credits
forward, backward, transfer credits, or trade credits into other credit
accounts, a manufacturer or credit holder must submit a credit
instruction to NHTSA. A credit instruction must detail and include:
(i) The credit holder(s) involved in the transaction.
(ii) The originating credits described by the amount of the
credits, compliance category and the vintage of the credits.
(iii) The recipient credit account(s) for banking or applying the
originating credits described by the compliance category(ies), model
year(s), and if applicable the adjusted credit amount(s) and adjustment
factor(s).
(iv) For trades, a contract authorizing the trade signed by the
manufacturers or credit holders or by managers legally authorized to
obligate the sale and purchase of the traded credits.
(2) Upon receipt of a credit instruction from an existing credit
holder, NHTSA verifies the presence of sufficient credits in the
account(s) of the credit holder(s) involved as applicable and notifies
the credit holder(s) that the credits will be debited from and/or
[[Page 49876]]
credited to the accounts involved, as specified in the credit
instruction. NHTSA determines if the credits can be debited or credited
based upon the amount of available credits, accurate application of any
adjustment factors and the credit requirements prescribed by this part
that are applicable at the time the transaction is requested.
(3) After notifying the credit holder(s), all accounts involved are
either credited or debited, as appropriate, in line with the credit
instruction. Traded credits identified by a specific compliance
category are deposited into the recipient's account in that same
compliance category and model year. If a recipient of credits as
identified in a credit instruction is not a current account holder,
NHTSA establishes the credit recipient's account, subject to the
conditions described in paragraph (b) of this section, and adds the
credits to the newly-opened account.
(4) NHTSA will automatically delete unused credits from holders'
accounts when those credits reach their expiry date.
(5) Starting January 1, 2022, manufacturers or credit holders
issuing credit instructions or providing credit allocation plans as
specified in paragraph (d) of this section, must use and submit the
NHTSA Credit Template fillable form (Office of Management and Budget
(OMB) Control No. 2127-0019, NHTSA Form 1475). The NHTSA Credit
Template is available for download on NHTSA's website. If a credit
instruction includes a trade, the NHTSA Credit Template must be signed
by managers legally authorized to obligate the sale and/or purchase of
the traded credits from both parties to the trade. The NHTSA Credit
Template signed by both parties to the trade serves as an
acknowledgement that the parties have agreed to trade credits, and does
not dictate terms, conditions, or other business obligations of the
parties. Manufacturers must submit the template along with other
requested information through the CAFE email, [email protected]. NHTSA
reserves the right to request additional information from the parties
regarding the terms of the trade.
(6) Starting September 1, 2022, manufacturers or credit holders
trading credits must use and submit the NHTSA Credit Value Reporting
Template fillable form (OMB Control No. 2127-0019, NHTSA Form 1621).
The NHTSA Credit Template is available for download on NHTSA's website.
The template will provide NHTSA with the price paid for the credits
including a description of any other monetary or non-monetary terms
affecting the price of the traded credits, such as any technology
exchanged or shared for the credits, any other non-monetary payment for
the credits, or any other agreements related to the trade.
Manufacturers must submit the template along with other requested
information through the CAFE email, [email protected]. NHTSA reserves the
right to request additional information from the parties regarding the
terms of the trade.
(7) NHTSA will consider claims that information submitted to the
agency under this section is entitled to confidential treatment under 5
U.S.C. 552(b) and under the provisions of part 512 of this chapter if
the information is submitted in accordance with the procedures of part
512.
(d) Compliance. (1) NHTSA assesses compliance with fuel economy
standards each year, utilizing the certified and reported CAFE data
provided by the Environmental Protection Agency (EPA) for enforcement
of the CAFE program pursuant to 49 U.S.C. 32904(e). Credit values are
calculated based on the CAFE data from the EPA. If a particular
compliance category within a manufacturer's fleet has above standard
fuel economy, NHTSA adds credits to the manufacturer's account for that
compliance category and vintage in the appropriate amount by which the
manufacturer has exceeded the applicable standard.
(2) If a manufacturer's vehicles in a particular compliance
category have below standard fuel economy, NHTSA will provide written
notification to the manufacturer that it has failed to meet a
particular fleet target standard. The manufacturer will be required to
confirm the shortfall and must either: Submit a plan indicating how it
will allocate existing credits or earn, transfer and/or acquire
credits; or pay the appropriate civil penalty. The manufacturer must
submit a plan or payment within 60 days of receiving agency
notification.
(3) Credits used to offset shortfalls are subject to the three- and
five-year limitations as described in Sec. 536.6.
(4) Transferred credits are subject to the limitations specified by
49 U.S.C. 32903(g)(3) and this part.
(5) The value, when used for compliance, of any credits received
via trade or transfer is adjusted, using the adjustment factor
described in Sec. 536.4(c), pursuant to 49 U.S.C. 32903(f)(1).
(6) Credit allocation plans received from a manufacturer will be
reviewed and approved by NHTSA. Starting in model year 2022, use the
NHTSA Credit Template and the Credit Trade Cost Template (OMB Control
No. 2127-0019, NHTSA Forms 1475 and 1621) to record the credit
transactions and the costs for any credit trades requested in the
credit allocation plan. The template is a fillable form that has an
option for recording and calculating credit transactions for credit
allocation plans. The template calculates the required adjustments to
the credits. The credit allocation plan and the completed transaction
templates must be submitted to NHTSA. NHTSA will approve the credit
allocation plan unless it finds that the proposed credits are
unavailable or that it is unlikely that the plan will result in the
manufacturer earning sufficient credits to offset the subject credit
shortfall. If the plan is approved, NHTSA will revise the respective
manufacturer's credit account accordingly. If the plan is rejected,
NHTSA will notify the respective manufacturer and request a revised
plan or payment of the appropriate fine.
(e) Reporting. (1) NHTSA periodically publishes the names and
credit holdings of all credit holders. NHTSA does not publish
individual transactions, nor respond to individual requests for updated
balances from any party other than the account holder.
(2) NHTSA issues an annual credit status letter to each party that
is a credit holder at that time. The letter to a credit holder includes
a credit accounting record that identifies the credit status of the
credit holder including any activity (earned, expired, transferred,
traded, carry-forward and carry-back credit transactions/allocations)
that took place during the identified activity period.
Sec. 536.6 Treatment of credits earned prior to model year 2011.
(a) Credits earned in a compliance category before model year 2008
may be applied by the manufacturer that earned them to carryback plans
for that compliance category approved up to three model years prior to
the year in which the credits were earned, or may be applied to
compliance in that compliance category for up to three model years
after the year in which the credits were earned.
(b) Credits earned in a compliance category during and after model
year 2008 may be applied by the manufacturer that earned them to
carryback plans for that compliance category approved up to three years
prior to the year in which the credits were earned, or may be held or
applied for up to five model years after the year in which the credits
were earned.
(c) Credits earned in a compliance category prior to model year
2011 may not be transferred or traded.
[[Page 49877]]
Sec. 536.7 Treatment of carryback credits.
(a) Carryback credits earned in a compliance category in any model
year may be used in carryback plans approved by NHTSA, pursuant to 49
U.S.C. 32903(b), for up to three model years prior to the year in which
the credit was earned.
(b) For purposes of this part, NHTSA will treat the use of future
credits for compliance, as through a carryback plan, as a deferral of
penalties for non-compliance with an applicable fuel economy standard.
(c) If NHTSA receives and approves a manufacturer's carryback plan
to earn future credits within the following three model years in order
to comply with current regulatory obligations, NHTSA will defer levying
fines for non-compliance until the date(s) when the manufacturer's
approved plan indicates that credits will be earned or acquired to
achieve compliance, and upon receiving confirmed CAFE data from EPA. If
the manufacturer fails to acquire or earn sufficient credits by the
plan dates, NHTSA will initiate compliance proceedings.
(d) In the event that NHTSA fails to receive or approve a plan for
a non-compliant manufacturer, NHTSA will levy fines pursuant to
statute. If within three years, the non-compliant manufacturer earns or
acquires additional credits to reduce or eliminate the non-compliance,
NHTSA will reduce any fines owed, or repay fines to the extent that
credits received reduce the non-compliance.
(e) No credits from any source (earned, transferred and/or traded)
will be accepted in lieu of compliance if those credits are not
identified as originating within one of the three model years after the
model year of the confirmed shortfall.
Sec. 536.8 Conditions for trading of credits.
(a) Trading of credits. If a credit holder wishes to trade credits
to another party, the current credit holder and the receiving party
must jointly issue an instruction to NHTSA, identifying the quantity,
vintage, compliance category, and originator of the credits to be
traded. If the recipient is not a current account holder, the recipient
must provide sufficient information for NHTSA to establish an account
for the recipient. Once an account has been established or identified
for the recipient, NHTSA completes the trade by debiting the
transferor's account and crediting the recipient's account. NHTSA will
track the quantity, vintage, compliance category, and originator of all
credits held or traded by all account-holders.
(b) Trading between and within compliance categories. For credits
earned in model year 2011 or thereafter, and used to satisfy compliance
obligations for model year 2011 or thereafter:
(1) Manufacturers may use credits originally earned by another
manufacturer in a particular compliance category to satisfy compliance
obligations within the same compliance category.
(2) Once a manufacturer acquires by trade credits originally earned
by another manufacturer in a particular compliance category, the
manufacturer may transfer the credits to satisfy its compliance
obligations in a different compliance category, but only to the extent
that the CAFE increase attributable to the transferred credits does not
exceed the limits in 49 U.S.C. 32903(g)(3). For any compliance
category, the sum of a manufacturer's transferred credits earned by
that manufacturer and transferred credits obtained by that manufacturer
through trade must not exceed that limit.
(c) Changes in corporate ownership and control. Manufacturers must
inform NHTSA of corporate relationship changes to ensure that credit
accounts are identified correctly and credits are assigned and
allocated properly.
(1) In general, if two manufacturers merge in any way, they must
inform NHTSA how they plan to merge their credit accounts. NHTSA will
subsequently assess corporate fuel economy and compliance status of the
merged fleet instead of the original separate fleets.
(2) If a manufacturer divides or divests itself of a portion of its
automobile manufacturing business, it must inform NHTSA how it plans to
divide the manufacturer's credit holdings into two or more accounts.
NHTSA will subsequently distribute holdings as directed by the
manufacturer, subject to provision for reasonably anticipated
compliance obligations.
(3) If a manufacturer is a successor to another manufacturer's
business, it must inform NHTSA how it plans to allocate credits and
resolve liabilities per 49 CFR part 534.
(d) No short or forward sales. NHTSA will not honor any
instructions to trade or transfer more credits than are currently held
in any account. NHTSA will not honor instructions to trade or transfer
credits from any future vintage (i.e., credits not yet earned). NHTSA
will not participate in or facilitate contingent trades.
(e) Cancellation of credits. A credit holder may instruct NHTSA to
cancel its currently held credits, specifying the originating
manufacturer, vintage, and compliance category of the credits to be
cancelled. These credits will be permanently null and void; NHTSA will
remove the specific credits from the credit holder's account, and will
not reissue them to any other party.
(f) Errors or fraud in earning credits. If NHTSA determines that a
manufacturer has been credited, through error or fraud, with earning
credits, NHTSA will cancel those credits if possible. If the
manufacturer credited with having earned those credits has already
traded them when the error or fraud is discovered, NHTSA will hold the
receiving manufacturer responsible for returning the same or equivalent
credits to NHTSA for cancellation.
(g) Error or fraud in trading. In general, all trades are final and
irrevocable once executed, and may only be reversed by a new, mutually-
agreed transaction. If NHTSA executes an erroneous instruction to trade
credits from one holder to another through error or fraud, NHTSA will
reverse the transaction if possible. If those credits have been traded
away, the recipient holder is responsible for obtaining the same or
equivalent credits for return to the previous holder.
Sec. 536.9 Use of credits with regard to the domestically
manufactured passenger automobile minimum standard.
(a) Each manufacturer is responsible for compliance with both the
minimum standard and the attribute-based standard.
(b) In any particular model year, the domestically manufactured
passenger automobile compliance category credit excess or shortfall is
determined by comparing the actual CAFE value against either the
required standard value or the minimum standard value, whichever is
larger.
(c) Transferred or traded credits may not be used, pursuant to 49
U.S.C. 32903(g)(4) and (f)(2), to meet the domestically manufactured
passenger automobile minimum standard specified in 49 U.S.C.
32902(b)(4) and in 49 CFR 531.5(d).
(d) If a manufacturer's average fuel economy level for domestically
manufactured passenger automobiles is lower than the attribute-based
standard, but higher than the minimum standard, then the manufacturer
may achieve compliance with the attribute-based standard by applying
credits.
(e) If a manufacturer's average fuel economy level for domestically
manufactured passenger automobiles is lower than the minimum standard,
then the difference between the minimum
[[Page 49878]]
standard and the manufacturer's actual fuel economy level may only be
relieved by the use of credits earned by that manufacturer within the
domestic passenger car compliance category which have not been
transferred or traded. If the manufacturer does not have available
earned credits to offset a credit shortage below the minimum standard
then the manufacturer can submit a carry-back plan that indicates
sufficient future credits will be earned in its domestic passenger car
compliance category or will be subject to penalties.
Sec. 536.10 Treatment of dual-fuel and alternative fuel vehicles--
consistency with 49 CFR part 538.
(a) Statutory alternative fuel and dual-fuel vehicle fuel economy
calculations are treated as a change in the underlying fuel economy of
the vehicle for purposes of this part, not as a credit that may be
transferred or traded. Improvements in alternative fuel or dual fuel
vehicle fuel economy as calculated pursuant to 49 U.S.C. 32905 and
limited by 49 U.S.C. 32906 are therefore attributable only to the
particular compliance category and model year to which the alternative
or dual-fuel vehicle belongs.
(b) If a manufacturer's calculated fuel economy for a particular
compliance category, including any statutorily-required calculations
for alternative fuel and dual fuel vehicles, is higher or lower than
the applicable fuel economy standard, manufacturers will earn credits
or must apply credits or pay civil penalties equal to the difference
between the calculated fuel economy level in that compliance category
and the applicable standard. Credits earned are the same as any other
credits, and may be held, transferred, or traded by the manufacturer
subject to the limitations of the statute and this part.
(c) For model years (MYs) up to and including MY 2019, if a
manufacturer builds enough dual fuel vehicles (except plug-in hybrid
electric vehicles) to improve the calculated fuel economy in a
particular compliance category by more than the limits set forth in 49
U.S.C. 32906(a), the improvement in fuel economy for compliance
purposes is restricted to the statutory limit. Manufacturers may not
earn credits nor reduce the application of credits or fines for
calculated improvements in fuel economy based on dual fuel vehicles
beyond the statutory limit.
(d) For model years 2020 and beyond, a manufacturer must calculate
the fuel economy of dual fueled vehicles in accordance with 40 CFR
600.510-12(c).
0
4. Revise part 537 to read as follows:
PART 537--AUTOMOTIVE FUEL ECONOMY REPORTS
Sec.
537.1 Scope.
537.2 Purpose.
537.3 Applicability.
537.4 Definitions.
537.5 General requirements for reports.
537.6 General content of reports.
537.7 Pre-model year and mid-model year reports.
537.8 Supplementary reports.
537.9 Determination of fuel economy values and average fuel economy.
537.10 Incorporating documents into reports.
537.11 Public inspection of information.
537.12 Confidential information.
Authority: 49 U.S.C. 32907, delegation of authority at 49 CFR
1.95.
Sec. 537.1 Scope.
This part establishes requirements for automobile manufacturers to
submit reports to the National Highway Traffic Safety Administration
(NHTSA) regarding their efforts to improve automotive fuel economy.
Sec. 537.2 Purpose.
The purpose of this part is to obtain information to aid the
National Highway Traffic Safety Administration in valuating automobile
manufacturers' plans for complying with average fuel economy standards
and in preparing an annual review of the average fuel economy
standards.
Sec. 537.3 Applicability.
This part applies to automobile manufacturers, except for
manufacturers subject to an alternate fuel economy standard under
section 502(c) of the Act.
Sec. 537.4 Definitions.
(a) Statutory terms. (1) The terms average fuel economy standard,
fuel, manufacture, and model year are used as defined in section 501 of
the Act.
(2) The term manufacturer is used as defined in section 501 of the
Act and 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 section 501
of the Act 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 part 523.
(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) Act means the Motor Vehicle Information and Cost Savings Act
(Pub. L. 92-513), as amended by the Energy Policy and Conservation Act
(Pub. L. 94-163).
(ii) Administrator means the Administrator of the National Highway
Traffic Safety Administration or the Administrator's delegate.
(iii) 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.
(iv) Average means a production-weighted harmonic average.
(v) 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).
Sec. 537.5 General requirements for reports.
(a) For each current model year, each manufacturer shall submit a
pre-model year report, a mid-model year report, and, as required by
Sec. 537.8, supplementary reports.
(b)(1) The pre-model year report required by this part for each
current model year must be submitted during the month of December
(e.g., the pre-model year report for the 1983 model year must be
submitted during December, 1982).
(2) The mid-model year report required by this part for each
current model year must be submitted during the month of July (e.g.,
the mid-model year report for the 1983 model year must be submitted
during July 1983).
(3) Each supplementary report must be submitted in accordance with
Sec. 537.8(c).
[[Page 49879]]
(c) Each report required by this part must:
(1) Identify the report as a pre-model year report, mid-model year
report, or supplementary report as appropriate;
(2) Identify the manufacturer submitting the report;
(3) State the full name, title, and address of the official
responsible for preparing the report;
(4) Be submitted on CD-ROM for confidential reports provided in
accordance with Sec. 537.12 and by email for non-confidential (i.e.,
redacted) versions of reports. The content of reports must be provided
in a PDF or MS Word format except for the information required in Sec.
537.7 which must be provided in a MS Excel format. Submit 2 copies of
the CD-ROM to: Administrator, National Highway Traffic Administration,
1200 New Jersey Avenue SW, Washington, DC 20590, and submit reports
electronically to the following secure email address: [email protected];
(5) Identify the current model year;
(6) Be written in the English language; and
(7)(i) Specify any part of the information or data in the report
that the manufacturer believes should be withheld from public
disclosure as trade secret or other confidential business information.
(ii) With respect to each item of information or data requested by
the manufacturer to be withheld under 5 U.S.C. 552(b)(4) and 15 U.S.C.
2005(d)(1), the manufacturer shall:
(A) Show that the item is within the scope of sections 552(b)(4)
and 2005(d)(1);
(B) Show that disclosure of the item would result in significant
competitive damage;
(C) Specify the period during which the item must be withheld to
avoid that damage; and
(D) Show that earlier disclosure would result in that damage.
(d) Beginning with model year 2023, each manufacturer shall
generate reports required by this part using the NHTSA CAFE Projections
Reporting Template (Office of Management and Budget (OMB) Control No.
2127-0019, NHTSA Form 1474). The template is a fillable form.
(1) Report type selection. Select the option to identify the report
as a pre-model year report, mid-model year report, or supplementary
report as appropriate.
(2) Required information. Complete all required information for the
manufacturer and for all vehicles produced for the current model year
required to comply with corporate average fuel economy (CAFE)
standards. Identify the manufacturer submitting the report, including
the full name, title, and address of the official responsible for
preparing the report and a point of contact to answer questions
concerning the report.
(3) Report generation. Use the template to generate confidential
and non-confidential reports for all the domestic and import passenger
cars and light truck fleet produced by the manufacturer for the current
model year. Manufacturers must submit a request for confidentiality in
accordance with part 512 of this chapter to withhold projected
production sales volume estimates from public disclosure. If the
request is granted, NHTSA will withhold the projected production sales
volume estimates from public disclose until all the vehicles produced
by the manufacturer have been made available for sale (usually one year
after the current model year).
(4) Report submission. Submit confidential reports and requests for
confidentiality to NHTSA on CD-ROM in accordance with Sec. 537.12.
Email copies of non-confidential (i.e., redacted) reports to NHTSA's
secure email address: [email protected]. Requests for confidentiality must
be submitted in a PDF or MS Word format. Submit 2 copies of the CD-ROM
to: Administrator, National Highway Traffic Administration, 1200 New
Jersey Avenue SE, Washington, DC 20590, and submit emailed reports
electronically to the following secure email address: [email protected].
(5) Confidentiality requests. Manufacturers can withhold
information on projected production sales volumes under 5 U.S.C.
552(b)(4) and 15 U.S.C. 2005(d)(1). In accordance, the manufacturer
must:
(i) Show that the item is within the scope of sections 552(b)(4)
and 2005(d)(1);
(ii) Show that disclosure of the item would result in significant
competitive damage;
(iii) Specify the period during which the item must be withheld to
avoid that damage; and
(iv) Show that earlier disclosure would result in that damage.
(e) Each report required by this part must be based upon all
information and data available to the manufacturer 30 days before the
report is submitted to the Administrator.
Sec. 537.6 General content of reports.
(a) Pre-model year and mid-model year reports. Except as provided
in paragraph (c) of this section, each pre-model year report and the
mid-model year report for each model year must contain the information
required by Sec. 537.7(a).
(b) Supplementary report. Except as provided in paragraph (c) of
this section, each supplementary report for each model year must
contain the information required by Sec. 537.7(a)(1) and (2), as
appropriate for the vehicle fleets produced by the manufacturer, in
accordance with Sec. 537.8(b)(1), (2), (3), and (4) as appropriate.
(c) Exceptions. The pre-model year report, mid-model year report,
and supplementary report(s) submitted by an incomplete automobile
manufacturer for any model year are not required to contain the
information specified in Sec. 537.7(c)(4)(xv) through (xviii) and
(c)(5). The information provided by the incomplete automobile
manufacturer under Sec. 537.7(c) shall be according to base level
instead of model type or carline.
Sec. 537.7 Pre-model year and mid-model year reports.
(a) Report content. (1) Provide a report with the information
required by paragraphs (b) and (c) of this section for each domestic
and import passenger automobile fleet, as specified in part 531 of this
chapter, for the current model year.
(2) Provide a report with the information required by paragraphs
(b) and (c) of this section for each light truck fleet, as specified in
part 533 of this chapter, for the current model year.
(3) For model year 2023 and later, for passenger cars specified in
part 531 of this chapter and light trucks specified in part 533 of this
chapter, provide the information for pre-model and mid-model year
reports in accordance with the NHTSA CAFE Projections Reporting
Template (OMB Control No. 2127-0019, NHTSA Form 1474). The required
reporting template can be downloaded from NHTSA's website.
(b) Projected average and required fuel economy. (1) State the
projected average fuel economy for the manufacturer's automobiles
determined in accordance with Sec. 537.9 and based upon the fuel
economy values and projected sales figures provided under paragraph
(c)(2) of this section.
(2) State the projected final average fuel economy that the
manufacturer anticipates having if changes implemented during the model
year will cause that average to be different from the average fuel
economy projected under paragraph (b)(1) of this section.
(3) State the projected required fuel economy for the
manufacturer's passenger automobiles and light trucks determined in
accordance with
[[Page 49880]]
Sec. Sec. 531.5(c) and 533.5 of this chapter and based upon the
projected sales figures provided under paragraph (c)(2) of this
section. For each unique model type and footprint combination of the
manufacturer's automobiles, provide the information specified in
paragraphs (b)(3)(i) and (ii) of this section in tabular form. List the
model types in order of increasing average inertia weight from top to
bottom down the left side of the table and list the information
categories in the order specified in paragraphs (b)(3)(i) and (ii) of
this section from left to right across the top of the table. Other
formats, such as those accepted by the EPA, which contain all the
information in a readily identifiable format are also acceptable. For
model year 2023 and later, for each unique model type and footprint
combination of the manufacturer's automobiles, provide the information
specified in paragraphs (b)(3)(i) and (ii) of this section in
accordance with the CAFE Projections Reporting Template (OMB Control
No. 2127-0019, NHTSA Form 1474).
(i) In the case of passenger automobiles:
(A) Beginning model year 2013, base tire as defined in Sec. 523.2
of this chapter;
(B) Beginning model year 2013, front axle, rear axle, and average
track width as defined in Sec. 523.2 of this chapter;
(C) Beginning model year 2013, wheelbase as defined in Sec. 523.2
of this chapter; and
(D) Beginning model year 2013, footprint as defined in Sec. 523.2
of this chapter.
(E) The fuel economy target value for each unique model type and
footprint entry listed in accordance with the equation provided in part
531 of this chapter.
(ii) In the case of light trucks:
(A) Beginning model year 2013, base tire as defined in Sec. 523.2
of this chapter;
(B) Beginning model year 2013, front axle, rear axle, and average
track width as defined in Sec. 523.2 of this chapter;
(C) Beginning model year 2013, wheelbase as defined in Sec. 523.2
of this chapter; and
(D) Beginning model year 2013, footprint as defined in Sec. 523.2
of this chapter.
(E) The fuel economy target value for each unique model type and
footprint entry listed in accordance with the equation provided in part
533 of this chapter.
(4) State the projected final required fuel economy that the
manufacturer anticipates having if changes implemented during the model
year will cause the targets to be different from the target fuel
economy projected under paragraph (b)(3) of this section.
(5) State whether the manufacturer believes that the projections it
provides under paragraphs (b)(2) and (4) of this section, or if it does
not provide an average or target under paragraphs (b)(2) and (4), the
projections it provides under paragraphs (b)(1) and (3) of this
section, sufficiently represent the manufacturer's average and target
fuel economy for the current model year for purposes of the Act. In the
case of a manufacturer that believes that the projections are not
sufficiently representative for the purposes of the preceding sentence,
state the specific nature of any reason for the insufficiency and the
specific additional testing or derivation of fuel economy values by
analytical methods believed by the manufacturer necessary to eliminate
the insufficiency and any plans of the manufacturer to undertake that
testing or derivation voluntarily and submit the resulting data to the
Environmental Protection Agency under 40 CFR 600.509.
(c) Model type and configuration fuel economy and technical
information. (1) For each model type of the manufacturer's automobiles,
provide the information specified in paragraph (c)(2) of this section
in tabular form. List the model types in order of increasing average
inertia weight from top to bottom down the left side of the table and
list the information categories in the order specified in paragraph
(c)(2) of this section from left to right across the top of the table.
For model year 2023 and later, CAFE reports required by this part,
shall for each model type of the manufacturer's automobiles, provide
the information in specified in paragraph (c)(2) of this section in
accordance with the NHTSA CAFE Projections Reporting Template (OMB
Control No. 2127-0019, NHTSA Form 1474) and list the model types in
order of increasing average inertia weight from top to bottom.
(2)(i) Combined fuel economy; and
(ii) Projected sales for the current model year and total sales of
all model types.
(3) For pre-model year reports only through model year 2022, for
each vehicle configuration whose fuel economy was used to calculate the
fuel economy values for a model type under paragraph (c)(2) of this
section, provide the information specified in paragraph (c)(4) of this
section in accordance with the NHTSA CAFE Projections Reporting
Template (OMB Control No. 2127-0019, NHTSA Form 1474).
(4)(i) Loaded vehicle weight;
(ii) Equivalent test weight;
(iii) Engine displacement, liters;
(iv) SAE net rated power, kilowatts;
(v) SAE net horsepower;
(vi) Engine code;
(vii) Fuel system (number of carburetor barrels or, if fuel
injection is used, so indicate);
(viii) Emission control system;
(ix) Transmission class;
(x) Number of forward speeds;
(xi) Existence of overdrive (indicate yes or no);
(xii) Total drive ratio (N/V);
(xiii) Axle ratio;
(xiv) Combined fuel economy;
(xv) Projected sales for the current model year;
(xvi)(A) In the case of passenger automobiles:
(1) Interior volume index, determined in accordance with subpart D
of 40 CFR part 600; and
(2) Body style;
(B) In the case of light trucks:
(1) Passenger-carrying volume; and
(2) Cargo-carrying volume;
(xvii) Frontal area;
(xviii) Road load power at 50 miles per hour, if determined by the
manufacturer for purposes other than compliance with this part to
differ from the road load setting prescribed in 40 CFR 86.177-11(d);
and
(xix) Optional equipment that the manufacturer is required under 40
CFR parts 86 and 600 to have actually installed on the vehicle
configuration, or the weight of which must be included in the curb
weight computation for the vehicle configuration, for fuel economy
testing purposes.
(5) For each model type of automobile which is classified as a non-
passenger vehicle (light truck) under part 523 of this chapter, provide
the following data:
(i) For an automobile designed to perform at least one of the
following functions in accordance with Sec. 523.5(a) of this chapter
indicate (by ``yes'' or ``no'' for each function) whether the vehicle
can:
(A) Transport more than 10 persons (if yes, provide actual
designated seating positions);
(B) Provide temporary living quarters (if yes, provide applicable
conveniences as defined in Sec. 523.2 of this chapter);
(C) Transport property on an open bed (if yes, provide bed size
width and length);
(D) Provide, as sold to the first retail purchaser, greater cargo-
carrying than passenger-carrying volume, such as in a cargo van and
quantify the value which should be the difference between the values
provided in paragraphs (c)(4)(xvi)(B)(1) and (2) of this section; if a
vehicle is sold with a second-row seat, its cargo-carrying volume is
determined with that seat installed, regardless of whether the
manufacturer has described that seat as optional; or
[[Page 49881]]
(E) Permit expanded use of the automobile for cargo-carrying
purposes or other non-passenger-carrying purposes through:
(1) For non-passenger automobiles manufactured prior to model year
2012, the removal of seats to permit expanded use of the automobile for
cargo-carrying purposes or other non-passenger-carrying purposes
through means provided by the automobile's manufacturer or with simple
tools, such as screwdrivers and wrenches, so as to create a flat, floor
level, surface extending from the forward-most point of installation of
those seats to the rear of the automobile's interior; or
(2) For non-passenger automobiles manufactured in model year 2008
and beyond, for vehicles equipped with at least 3 rows of designated
seating positions as standard equipment, permit expanded use of the
automobile for cargo-carrying purposes or other nonpassenger-carrying
purposes through the removal or stowing of foldable or pivoting seats
so as to create a flat, leveled cargo surface extending from the
forward-most point of installation of those seats to the rear of the
automobile's interior.
(ii) For an automobile capable of off-highway operation, identify
which of the features below qualify the vehicle as off-road in
accordance with Sec. 523.5(b) of this chapter and quantify the values
of each feature:
(A) 4-wheel drive; or
(B) A rating of more than 6,000 pounds gross vehicle weight; and
(C) Has at least four of the following characteristics calculated
when the automobile is at curb weight, on a level surface, with the
front wheels parallel to the automobile's longitudinal centerline, and
the tires inflated to the manufacturer's recommended pressure. The
exact value of each feature should be quantified:
(1) Approach angle of not less than 28 degrees.
(2) Breakover angle of not less than 14 degrees.
(3) Departure angle of not less than 20 degrees.
(4) Running clearance of not less than 20 centimeters.
(5) Front and rear axle clearances of not less than 18 centimeters
each.
(6) The fuel economy values provided under paragraphs (c)(2) and
(4) of this section shall be determined in accordance with Sec. 537.9.
(7) Identify any air-conditioning (AC), off-cycle, and full-size
pick-up truck technologies used each model year to calculate the
average fuel economy specified in 40 CFR 600.510-12.
(i) Provide a list of each air conditioning efficiency improvement
technology utilized in your fleet(s) of vehicles for each model year.
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 air conditioning fuel consumption
improvement value in gallons/mile in accordance with the equation
specified in 40 CFR 600.510-12(c)(3)(i).
(ii) Provide a list of off-cycle efficiency improvement
technologies utilized in your fleet(s) of vehicles for each model year
that is pending or approved by the EPA. For each technology 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), 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) Provide a list of full-size pickup trucks in your fleet that
meet the mild and strong hybrid vehicle definitions as specified in 40
CFR 86.1803-01. For each mild and strong hybrid type, 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, 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).
Sec. 537.8 Supplementary reports.
(a)(1) Except as provided in paragraph (d) of this section, each
manufacturer whose most recently submitted semiannual report contained
an average fuel economy projection under Sec. 537.7(b)(2) or, if no
average fuel economy was projected under that section, under Sec.
537.7(b)(1), that was not less than the applicable average fuel economy
standard and who now projects an average fuel economy which is less
than the applicable standard shall file a supplementary report
containing the information specified in paragraph (b)(1) of this
section.
(2) Except as provided in paragraph (d) of this section, each
manufacturer that determines that its average fuel economy for the
current model year as projected under Sec. 537.7(b)(2) or, if no
average fuel economy was projected under Sec. 537.7(b)(2), as
projected under Sec. 537.7(b)(1), is less representative than the
manufacturer previously reported it to be under Sec. 537.7(b)(3), this
section, or both, shall file a supplementary report containing the
information specified in paragraph (b)(2) of this section.
(3) For model years through 2022, each manufacturer whose pre-model
or mid-model year report omits any of the information specified in
Sec. 537.7(b) or (c) shall file a supplementary report containing the
information specified in paragraph (b)(3) of this section.
(4) Starting model year 2023, each manufacturer whose pre-model or
mid-model year report omits any of the information shall resubmit the
information with other information required in accordance with the
NHTSA CAFE Projections Reporting Template (OMB Control No. 2127-0019,
NHTSA Form 1474).
(b)(1) The supplementary report required by paragraph (a)(1) of
this section must contain:
(i) Such revisions of and additions to the information previously
submitted by the manufacturer under this part regarding the automobiles
whose projected average fuel economy has decreased as specified in
paragraph (a)(1) of this section as are necessary--
(A) To reflect the decrease and its cause; and
(B) To indicate a new projected average fuel economy based upon
these additional measures.
(ii) An explanation of the cause of the decrease in average fuel
economy that led to the manufacturer's having to submit the
supplementary report required by paragraph (a)(1) of this section.
(2) The supplementary report required by paragraph (a)(2) of this
section must contain:
(i) A statement of the specific nature of and reason for the
insufficiency in the representativeness of the projected average fuel
economy;
(ii) A statement of specific additional testing or derivation of
fuel economy values by analytical methods believed by the manufacturer
necessary to eliminate the insufficiency; and
[[Page 49882]]
(iii) A description of any plans of the manufacturer to undertake
that testing or derivation voluntarily and submit the resulting data to
the Environmental Protection Agency under 40 CFR 600.509.
(3) The supplementary report required by paragraph (a)(3) of this
section must contain:
(i) All of the information omitted from the pre-model year report
under Sec. 537.6(c)(2); and
(ii) Such revisions of and additions to the information submitted
by the manufacturer in its pre-model year report regarding the
automobiles produced during the current model year as are necessary to
reflect the information provided under paragraph (b)(3)(i) of this
section.
(4) The supplementary report required by paragraph (a)(4) of this
section must contain:
(i) All information omitted from the pre-model or mid-model year
reports under Sec. 537.6(c)(2); and
(ii) Such revisions of and additions to the information submitted
by the manufacturer in its pre-model or mid-model year reports
regarding the automobiles produced during the current model year as are
necessary to reflect the information provided under paragraph (b)(4)(i)
of this section.
(c)(1) Each report required by paragraph (a)(1), (2), (3), or (4)
of this section must be submitted in accordance with Sec. 537.5(c) not
more than 45 days after the date on which the manufacturer determined,
or could have determined with reasonable diligence, that the report was
required.
(2) [Reserved]
(d) A supplementary report is not required to be submitted by the
manufacturer under paragraph (a)(1) or (2) of this section:
(1) With respect to information submitted under this part before
the most recent semiannual report submitted by the manufacturer under
this part; or
(2) When the date specified in paragraph (c) of this section
occurs:
(i) During the 60-day period immediately preceding the day by which
the mid-model year report for the current model year must be submitted
by the manufacturer under this part; or
(ii) After the day by which the pre-model year report for the model
year immediately following the current model year must be submitted by
the manufacturer under this part.
(e) For model years 2008, 2009, and 2010, each manufacturer of
light trucks, as that term is defined in 49 CFR 523.5, shall submit a
report, not later than 45 days following the end of the model year,
indicating whether the manufacturer is opting to comply with 49 CFR
533.5(f) or (g).
Sec. 537.9 Determination of fuel economy values and average fuel
economy.
(a) Vehicle subconfiguration fuel economy values. (1) For each
vehicle subconfiguration for which a fuel economy value is required
under paragraph (c) of this section and has been determined and
approved under 40 CFR part 600, the manufacturer shall submit that fuel
economy value.
(2) For each vehicle subconfiguration specified in paragraph (a)(1)
of this section for which a fuel economy value approved under 40 CFR
part 600, does not exist, but for which a fuel economy value determined
under 40 CFR part 600 exists, the manufacturer shall submit that fuel
economy value.
(3) For each vehicle subconfiguration specified in paragraph (a)(1)
of this section for which a fuel economy value has been neither
determined nor approved under 40 CFR part 600, the manufacturer shall
submit a fuel economy value based on tests or analyses comparable to
those prescribed or permitted under 40 CFR part 600 and a description
of the test procedures or analytical methods used.
(4) For each vehicle configuration for which a fuel economy value
is required under paragraph (c) of this section and has been determined
and approved under 40 CFR part 600, the manufacturer shall submit that
fuel economy value.
(b) Base level and model type fuel economy values. For each base
level and model type, the manufacturer shall submit a fuel economy
value based on the values submitted under paragraph (a) of this section
and calculated in the same manner as base level and model type fuel
economy values are calculated for use under subpart F of 40 CFR part
600.
(c) Average fuel economy. Average fuel economy must be based upon
fuel economy values calculated under paragraph (b) of this section for
each model type and must be calculated in accordance with subpart F of
40 CFR part 600, except that fuel economy values for running changes
and for new base levels are required only for those changes made or
base levels added before the average fuel economy is required to be
submitted under this part.
Sec. 537.10 Incorporating documents into reports.
(a) A manufacturer may incorporate by reference in a report
required by this part any document other than a report, petition, or
application, or portion thereof submitted to any Federal department or
agency more than two model years before the current model year.
(b) A manufacturer that incorporates by references a document not
previously submitted to the National Highway Traffic Safety
Administration shall append that document to the report.
(c) A manufacturer that incorporates by reference a document shall
clearly identify the document and, in the case of a document previously
submitted to the National Highway Traffic Safety Administration,
indicate the date on which and the person by whom the document was
submitted to this agency.
Sec. 537.11 Public inspection of information.
Except as provided in Sec. 537.12, any person may inspect the
information and data submitted by a manufacturer under this part in the
docket section of the National Highway Traffic Safety Administration.
Any person may obtain copies of the information available for
inspection under this section in accordance with the regulations of the
Secretary of Transportation in part 7 of this title.
Sec. 537.12 Confidential information.
(a) Granting confidential treatment. Information made available
under Sec. 537.11 for public inspection does not include information
for which confidentiality is requested under Sec. 537.5(c)(7), is
granted in accordance with section 505 of the Act and section 552(b) of
Title 5 of the United States Code and is not subsequently released
under paragraph (c) of this section in accordance with section 505 of
the Act.
[[Page 49883]]
(b) Denial of confidential treatment. When the Administrator denies
a manufacturer's request under Sec. 537.5(c)(7) for confidential
treatment of information, the Administrator gives the manufacturer
written notice of the denial and reasons for it. Public disclosure of
the information is not made until after the ten-day period immediately
following the giving of the notice.
(c) Release of confidential information. After giving written
notice to a manufacturer and allowing ten days, when feasible, for the
manufacturer to respond, the Administrator may make available for
public inspection any information submitted under this part that is
relevant to a proceeding under the Act, including information that was
granted confidential treatment by the Administrator pursuant to a
request by the manufacturer under Sec. 537.5(c)(7).
Issued on August 5, 2021, in Washington, DC, under authority
delegated in 49 CFR 1.95
Steven S. Cliff,
Acting Administrator.
[FR Doc. 2021-17496 Filed 8-27-21; 4:15 pm]
BILLING CODE 4910-59-P