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## A1 Appendix A: The B aseline and Reference V ehicle F leet

The passenger cars and light trucks sold currently in the United States, and those which are anticipated to be sold in the MY s 201 7

- 2025 time frame, are highly varied and satisfy a wide range of consumer needs. From two

- seater miniature cars to 11

- seater passenger vans to large extended cab pickup trucks, American consumers have a great number of vehicle options to accommodate their utility nee ds and preferences. Recent volatility in oil prices and the state of the economy have demonstrated that consumer demand and choice of vehicles within this wide range can be sensitive to these factors. Although it is impossible for anyone or any organizat ion to precisely predict the future, a characterization and quantification of the future fleet are required to assess the impacts of rules which would affect that future fleet. In order to do this, the various leading publicly

- available sources are examin ed , and a series of models are relied upon that help us to project the composition of a reference fleet. This appendix gives a high level over view of the process to accomplish this and a simple analysis of the fleet’s characteristics , drawing extensively from the joint final TSD for the MYs 2012

- 2016 final rule

.

A1.1 Why do the agencies establish a baseline and reference vehicle fleet?

In order to calculate the impacts of potential future EPA and NHTSA standards , it is necessary to estimate the composition of the future vehicle fleet absent those CAFE/GHG standards in order to conduct comparisons. EPA in consultation with NHTSA has developed a comparison fleet in two parts. The first step was to develop a basel ine fleet based on model year 2008 data. EPA and NHTSA create a baseline fleet in order to track the volumes and types of fuel economy

- improving and CO 2 - reducing technologies which are already present in today’s fleet. Creating a baseline fleet helps to keep, to some extent, the agencies’ models from adding technologies to vehicles that already have these technologies, which would result in “double counting” of technologies’ costs and benefits. The second step was to project the baseline fleet sales into MYs 201 7

- 20 25 . This is called the reference fleet, and it represents the fleet that would exist in MYs 201 7

- 20 25 absent any change from current regulations. The third step was to add technologies to that MY 2008 fleet such that each manufacturer’s

avera ge car and truck CO 2 levels are in compliance with their MY 201 6 CAFE standards. This final “reference fleet” is the light duty fleet estimated to exist in MYs 201 7

- 20 25 without

new CAFE/GHG standards . All of the agencies’ estimates of emission reduction s/fuel economy improvements, costs, and societal impacts for purposes of this Technical Assessment Report are developed in relation to th is reference fleet for MY 2016

. This Appendix describes the first two steps of the development of the baseline and ref erence fleets. The third step of technology addition is developed separately by each agency as the outputs of the OMEGA and Volpe models ; for purposes of this Technical Assessment Report, as discussed above, only the OMEGA model was employed for the main analysis, although both models will be run for the forthcoming federal rulemaking

. The overall process for developing baseline and reference fleets for the agencies’ modeling is described in the MYs 2012

- 2016 final rule in section II of the preamble and i n each agency’s respective RIA.Appendix A

A

- 2

A1.2 The 2008 baseline vehicle fleet

A1.2.1 Why did the agencies choose 2008 as the baseline model year?

A baseline vehicle fleet was developed by EPA in consultation with NHTSA for the 2012

- 2016 final rule . The b aseline for the 2012

- 2016 final rule is comprised of model year 2008 individual vehicle attribute data volumes along with projected volumes out to 2016

. M odel year 2 008 vehicle data was again chosen to be the basis of the baseline fleet, but for different reaso ns than the final rule

. M odel year 2008 is now the most recent model year for which the industry had normal sales. M o del year 2009 data was available, but the agencies believe that the model year was disrupted by the economic downturn and the bankruptci es of bo th General Motors and Chrysler. There was a significant reduction in the number of vehicles sold by both companies and the industry as a whole

. These abnormalities made the agencies conclude that 2009 data was unsuitable for projecting the future fleet. Therefore, the agencies chose to use model year 2008 as the baseline since it was the latest representative transparent data set available.

A1.2.1.1 On what data is the baseline vehicle fleet based?

A s part of the CAFE program, EPA measures vehicle CO 2 emissions and converts them to mpg and generates and maintains the federal fuel economy database. Most of the information about the 2008 vehicle fleet was gathered from EPA’s emission certification and fuel economy database , most of which is available to the public

. The data obtained from this source included vehicle production volume, fuel economy, carbon dioxide emissions, fuel type, number of engine cylinders, displacement, valves per cylinder, engine cycle, transmission type, drive, hybrid type, and aspiration. However, EPA’s certification database does not include a detailed description of the types of fuel economy

- improving/CO 2 - reducing technologies considered in this final rule , because this level of information is not necessary for emission certi fication or fuel economy testing. Thus, EPA augmented this description with publicly

- available data which includes more complete technology descriptions from Ward’s Automotive Group

. 1

, A In a few instances when required vehicle information was not availab le from these two sources (such as vehicle footprint), this information was obtained from publicly

- accessible internet sites such as Motortrend.com, Edmunds.com and other sources to a lesser extent (such as articles about specific vehicles revealed from in ternet search engine research. 2

, B

For details on how the 2008 baseline fleet was con structed for the 2012

- 2016 final rule , please see the Chapter 1 of the Joint Technical Supp ort Document for that rule

.

A Note that WardsAuto.com is a fee

- based service, but all information is public to subscribers.
B Motortrend.com and Edmunds.com are free, no

- fee internet sites.2017

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- 3 A1.3 The MY 201 7

- 20 25 Reference Fleet

The reference fleet aims to reflect the current market conditions and expectations about conditions of the vehicle fleet during the model years to which the agencies’ rules apply . Fundamentally, constructing this fleet involved projecting the MY 2008 base line fleet into the 201 7

- 20 25 model years. It also included the assumption that none of the models had changes during this period , in terms of both the technology present in the vehicles themselves, and the vehicles present in the fleet

. Projecting what the fleet will look like in the future is a process that is inherently uncertain

. NHTSA and EPA therefore relied on many sources of reputable information to make these projections.

A1.3.1 On what data is the reference vehicle fleet based ?

EPA and NHTSA have ba sed the projection of total car and light truck sales on recent projections made by the Energy Information Administration (EIA). EIA publishes a projection of national energy use annually called the Annual Energy Outlook (AEO)

. 3 EIA published its Annual Energy Outlook for 2010 in Ma y 2010

. Similar to the analyses supporting the MY s 2012

- 2016 rulemaking, the agencies have used the Energy Information Administration’s (EIA’s) National Energy Modeling System (NEMS) to estimate the future relative market shar es of passenger cars and light trucks. However, the version of NEMS supporting EIA’s Annual Energy Outlook 2010 (AEO2010) contains a “dummy variable” that forces the passenger car market share to increase after 2007, to facilitate projected compliance wit h EISA’s requirement that the overa ll fleet achieve 35 mpg by 2020 (the car and truck volumes based on this analysis are shown in Table A 1.3

- 1

. Because we use our market projection as a baseline relative to which we measure the effects of new standards, and we attempt to estimate the industry’s ability to comply with new standards without changing product mix, the AEO2010 projected shift in passenger car market share as a result of legislatively required fuel economy improvements creates a circular logic. Therefore, for the current analysis, a new projection of passenger car and li ght truck sales shares was developed by running scenarios from the AEO2010 reference case that first deactivate the above

mentioned dummy variable and holds post

- 2017 CAFE standards constant at MY 2016 levels. Incorporating these changes reduced the proje cted passenger car share of the light vehicle market by an average of about 5% during 2017

- 2025. This case is referred to as the Unforced Reference Case , and the values are shown below in Table A 1.3

- 2

.

Table A 1.3

- 1 AEO Original Reference Case Values

Model Year Cars Trucks Total Vehicles 2017 9,329,656 6,855,287 16,184,943 2018 9,375,428 6,595,148 15,970,576 2019 9,640,245 6,482,139 16,122,384 2020 10,105,479 6,436,088 16,541,566 2021 10,156,471 6,303,343 16,459,813 2022 10,178,345 6,166,611 16,344,956 2023 10,293,661 6,118,791 16,412,452 2024 10,516,662 6,166,036 16,682,698Appendix A

A

- 4 2025 10,761,857 6,204,297 16,966,155

Table A 1.3

- 2 AEO Unforced Reference Case Values

Model Year Cars Trucks Total Vehicles 2017 8,783,816 7,401,127 16,184,943 2018 8,728,990 7,241,586 15,970,576 2019 8,899,836 7,222,548 16,122,384 2020 9,230,279 7,311,287 16,541,566 2021 9,265,881 7,193,932 16,459,813 2022 9,282,884 7,062,072 16,344,956 2023 9,382,100 7,030,352 16,412,452 2024 9,588,366 7,094,332 16,682,698 2025 9,817,211 7,148,944 16,966,155

Using the unforced reference case , EIA projects that total light

- duty vehicle sales gradually recover from their currently depressed levels by roughly 2013. In 2017, car and light truck sales are projected to be 8 .8 and 7.4 million units, respectively. While the total leve l of sales of 16.1 million units is similar to pre

- 2008 levels, the fraction of car sales is projected to be higher than that existing in the 2000

- 2007 timeframe. Note that EIA’s definition of cars and trucks follows that used by NHTSA prior to the MY 201 1 CAFE final rule

. The MY 2011 CAFE final rule reclassified a number of 2

- wheel drive sport utility vehicles from the truck fleet to the car fleet. EIA’s sales projections of cars and trucks for the 201 7

- 20 25 model years under both the old NHTSA truck de finition are shown above in Table A 1.3

- 1 and Table A 1.3

- 2

. In addition to a shift towards more car sales, sales of segments within both the car and truck markets have also been changing and are expected to continue to change in the future. Manufact urers are continuing to introduce more crossover models which offer much of the utility of SUVs but use more car

- like designs and unibody structures. In order to reflect these changes in fleet makeup, EPA and NHTSA used a custom long range forecast purcha sed from CSM Worldwide (CSM). CSM Worldwide (CSM) 4 is a well

- known ind ustry analyst , that provide d the forecast used for the 2012

- 2016 final rule

. NHTSA and EPA decided to use the forecast from CSM for several reasons. One, CSM agreed to allow us to pu blish their high level data, on which the forecast is based, in the public domain. Two, it covered all the timeframe of greatest relevance to this analysis (201 7

- 20 2 5 model years). Three, it provided projections of vehicle sales both by manufacturer and by market segment. Four, it utilized market segments similar to those used in the EPA emission certification program and fuel economy guide. As discussed further below, the CSM forecast is combined with other data obt ained by NHTSA and EPA.2017

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- 5 A1.3.2 How do the a gencies develop the reference vehicle fleet?

The process of producing the 201 7

- 20 25 reference fleet involved combining the baseline fleet with the projection data described above. This was a complex multistep procedure, which is described in detail in the Joint Technical Support Document from the 2012

- 2016 final rule with an abbreviated discussion in this section

.

A1.3.2.1 How was the 2008 baseline data merged with the CSM data ?

M erging the 2008 baseline data with the 201 7

- 20 25 CSM data required a thorough mapping of certification vehicles to CSM vehicles by individual make and model. One challenge the agencies faced when determining a reference case fleet was that the sales data projected by CSM had different market segmentation than the data con tained in EPA’s internal database. In order to create a common segmentation between the two databases, side

by

- side comparison of the specific vehicle models in both datasets was performed, and an additional “CSM segment” modifier in the spreadsheet was c reated, thus mapping the two datasets. T he reference fleet sales based on the “CSM segmentation” was then projected.

In the combined EPA certification and CSM database, all of the 2008 vehicle models were assumed to continue out to 20 25 , though their volu mes changed in proportion to CSM projections. Also, any new models expected to be introduced within the 201 1

- 20 25 timeframe are not included in the data. These volumes are reassigned to the existing models. All MY 201 7

- 20 25 vehicles are mapped to the ex isting vehicles by a process of mapping to manufacturer market share and overall segment distribution.

A1.3.2.2 How were the CSM forecasts normalized to the AEO forecasts ?

T he projected CSM forecasts for relative sales of cars and trucks by manufacturer and by ma rket segment were normalized (set equal) to the total sales estimates of the AEO 2010 reference case . NHTSA and EPA used projected car and truck volumes for this period from AEO 20 10

. However, the AEO projects sales only at the car and truck level, not at the manufacturer and model

- specific level, which are needed for the analysis. The CSM data provided year

- by

- year percentages of cars and trucks sold by each manufacturer as well as the percentages of each vehicle segment. Using these percentages norma lized to the AEO

projected volumes then provided the manufacturer

- specific market share and model

- specific sales for model years 201 7

- 20 25 (it is worth clarifying that the agencies are not using the model

- specific sales volumes from CSM, only the volumes b y manufacturer and segment). This process is described in greater detail in Chapter 1 of the Joint Technical Support Document for the 2012

- 2016 final rule.

A1.3.3 What are the sales volumes and characteristics of the reference fleet ?

Table A 1.3

- 3 and Table A 1.3

- 6 belo w contain the sales volumes that result from the process above for MY 2008 and 2017

- 2020. Table A 1.3

- 4 and Table A 1.3

- 5 below contain the sales vol umes that result from the process above for MY 2021

- 2025.Appendix A

A

- 6 Table A 1.3

- 3 Vehicle Segment Volumes a

Reference Class Segment Actual and Projected Sales Volume

2008 2017 2018 2019 2020 LargeAuto 557,693 381,148 361,437 361,164 406,604 MidSizeAuto 3,097,859 3,472,360 3,456,168 3,501,241 3,603,571 CompactAuto 1,976,424 2,452,469 2,432,700 2,500,944 2,598,610 SubCmpctAuto 1,364,434 2,530,789 2,529,308 2,588,403 2,674,638 All Cars 6,971,256 8,783,816 8,728,990 8,899,836 9,230,279

LargePickup 1,581,880 1,521,906 1,452,047 1,404,242 1,413,451 SmallPickup 177,497 156,992 158,850 163,210 148,911 LargeSUV 2,783,949 3,210,047 3,168,335 3,226,391 3,266,435 MidSizeSUV 1,263,360 1,365,334 1,316,762 1,286,724 1,311,146 SmallSUV 285,355 148,962 150,791 157,027 165,874 MiniVan 642,055 758,207 743,808 727,994 728,384 CargoVan 110,858 186,730 200,370 205,042 223,940 All Trucks 6,870,108 7,401,127 7,241,586 7,222,548 7,311,287

a Volumes in this table are based on the pre

- 2011 NHTSA definition of Cars and Trucks.

Table A 1.3

- 4 Vehicle Segment Volumes a

Reference Class Segment Actual and Projected Sales Volume

2021 2022 2023 2024 2025 LargeAuto 384,191 353,301 352,705 345,006 356,435 MidSizeAuto 3,604,960 3,635,168 3,732,222 3,781,545 3,835,289 CompactAuto 2,629,933 2,645,629 2,651,598 2,756,463 2,847,781 SubCmpctAuto 2,704,376 2,708,913 2,708,098 2,770,523 2,843,941 All Cars 9,265,881 9,282,884 9,382,100 9,588,366 11,461,493

LargePickup 1,352,502 1,302,512 1,251,253 1,226,935 1,215,296 SmallPickup 148,400 142,033 145,507 149,188 149,308 LargeSUV 3,274,899 3,245,920 3,281,687 3,353,515 3,395,154 MidSizeSUV 1,266,485 1,238,672 1,219,552 1,247,145 1,258,695 SmallSUV 165,290 163,744 163,691 167,086 169,425 MiniVan 720,675 713,307 712,312 695,336 700,287 CargoVan 208,102 195,757 193,828 189,957 194,544 All Trucks 7,193,932 7,062,072 7,030,352 7,094,332 5,504,662

a Volumes in this table are based on the pre

- 2011 NHTSA definition of Cars and Trucks.

Table A 1.3

- 5 2011+ NHTSA Car and Truck Definition Based Volumes

Vehicle Type Actual and Projected Sales Volume

2008 2017 2018 2019 2020 Trucks 5,620,847 5,846,663 5,703,588 5,667,948 5,714,5862017

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- 7 Cars 8,220,517 10,338,280 10,266,989 10,454,435 10,826,981 Cars and Trucks 13,841,364 16,184,943 15,970,576 16,122,384 16,541,566

Table A 1.3

- 6 2011+ NHTSA Car and Truck Definition Based Volumes

Vehicle Type Actual and Projected Sales Volume

2021 2022 2023 2024 2025 Trucks 5,618,286 5,505,720 5,468,789 5,475,941 5,504,662 Cars 10,841,528 10,839,236 10,943,663 11,206,758 11,461,493 Cars and Trucks 16,459,813 16,344,956 16,412,452 16,682,698 16,966,155

Table A 1.3

- 7 also shows how the change in fleet make

- up may affect the footprint distributions over time. The resulting data indicate that footprint will not change significantly between 2008 and 20 25

. There will be an increase in the number of cars sold (as compared to trucks) , which will cause the average footprints for cars and trucks combined to be slightly smaller (about 2%). This is the result of AEO projecting an increased number of cars, and CSM predicting that most of that increase will be in the subcompact segment.

Table A 1.3

- 7 Production Foot Print Mean

Model Year Foot Print Mean

Cars Foot Print Mean for

Trucks Foot Print Mean for Cars & Trucks Combined 2008 45.45 54.12 48.97 2017 44.94 53.93 48.19 2018 44.93 53.85 48.12 2019 44.92 53.76 48.03 2020 44.95 53.89 48.04 2021 44.93 53.81 47.96 2022 44.91 53.78 47.90 2023 44.93 53.66 47.84 2024 44.92 53.51 47.74 2025 44.92 53.47 47.69

Table A 1.3

- 8 and Table A 1.3

- 9 below show the changes in engine cylinders over the model years. The current assumptions show that engines will be downsized over the model years to which these rules apply. The biggest projected shift occurs between MY 2008 and 2013. This shift is a projected consequence of the expected changes in class and segment mix as predicted by AEO and CSM, and does not represent engine downsizing attributable to the rules.Appendix A

A

- 8

Table A 1.3

- 8 Truck Percentages of 4, 6, 8 Cylinder Engines by Model Year

Model Year Perce ntage of 4

Cylinders Percentage of 6 Cylinders Percentage of 8 Cylinders 2008 10.33% 56.40% 33.27% 2017 10.94% 63.67% 25.39% 2018 10.65% 64.51% 24.84% 2019 10.42% 65.47% 24.12% 2020 10.29% 65.57% 24.14% 2021 10.28% 66.33% 23.39% 2022 10.26% 66.74% 23.00% 2023 10.26% 67.73% 22.01% 2024 10.47% 68.09% 21.44% 2025 10.52% 68.22% 21.26%

Table A 1.3

- 9 Car Percentages of 4, 6, 8 Cylinder Engines by Model Year

Model Year Percentage of 4

Cylinders Percentage of 6 Cylinders Percentage of 8 Cylinders 2008 56.99% 37.80% 5.20% 2017 60.63% 34.55% 4.82% 2018 60.70% 34.47% 4.83% 2019 60.72% 34.43% 4.85% 2020 60.39% 34.74% 4.87% 2021 60.75% 34.47% 4.78% 2022 61.19% 34.16% 4.65% 2023 61.05% 34.32% 4.63% 2024 61.12% 34.19% 4.68% 2025 61.20% 34.11% 4.69%

A1.3.4 How does manufacturer product plan data factor into the baseline ?

In the spring and fall of 2009, many manufacturers submitted product plans in response to NHTSA’s request . NHTSA and EPA both have access to these plans, and both agencies have reviewed them in detail. A small amount of product plan data was used in the development of the baseline. The specific pieces of data are:

Wheelbase Track Width Front Track Width Rear Curb Weight GVWR (Gross Vehicle Weight Rating)2017

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- 9 The track widths, wheelbase, curb weight, and GVWR for vehicles could have been looked up on the internet (159 were), but were taken from the product plans when available for convenience. To ensure accuracy, a sample from each product plan was used as a check against the numbers available from Motortrend.com. These numbers will be published in the baseline file since they can be easily looked up on the internet.Appendix A

A

- 10 Appendix A References

All references can be found in D ocket EPA

- HQ

- OAR

- 2009

- 0472

.

1 WardsAuto.com: Used as a source for engine specifications.

2 Motortrend.com and Edmunds.com: Used as a source for foot print and vehicle weight data.

3 Energy Information Administratio n’s 2009 Annual Energy Outlook.

4 CSM World Wide, CSM World Wide is a paid service provider.2017

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- 1 

## Appendix B: Package Cost and Effectiveness

B1 Explanation of Technology Packages

As discussed briefly at the end of Chapter 3, EPA believes that manufacturers are likely to bundle technologies into ―packages‖ to capture synergistic aspects and reflect progressively larger CO2 reductions with additions or changes to any given package. In addition, manufacturers typically apply new technologies in packages during model redesigns

— which occur once roughly every five years

— rather than adding new technologie s one at a time on an annual or biennial basis. This way, manufacturers can more efficiently make use of their redesign resources and more effectively plan for changes necessary to meet future standards.

Therefore, the approach taken by EPA for purposes o f this Technical Assessment Report is to group technologies into packages of increasing cost and effectiveness. While developing its analysis for the 2012

- 2016 rulemaking, EPA employed 19 different vehicle types for modeling the entire fleet. For the cur rent assessment, we have used the same 19 vehicle types, with the exception that vehicle type 15 was replaced with a different baseline engine to provide us with a more appropriate set of technologies and packages for large cars with baseline V8 overhead v alve engines. E ach of these 19 vehicle types is mapped into one of six classes of vehicles: Subcompact, Small car, Large car, Minivan, Small truck, and Large truck. Note that , for th e current assessment, EPA has created a new vehicle class called

― Subco mpact ‖ which allows for greater differentiation of costs for this growing class of vehicles (such as the Honda Fit, the Toyota Yaris, and the new Ford Fiesta). Note also that these 19 vehicle types span the range of vehicle footprints

— smaller footprints f or smaller vehicles and larger footprints for larger vehicles

— which served as the basis for the 2012

- 2016 GHG standards. The resultant 19 vehicle types, their baseline engines and their descriptions are shown in Table B1

- 1

.

Table B1

- 1 : List of 19 Vehicle Types used to Model the Light

- duty Fleet

Vehicle Type # Base Engine Base Trans Vehicle Class Description

1 1.5L 4V DOHC I4 4sp AT Subcompact Subcompact car I4 2 2.4L 4V DOHC I4 4sp AT Small car Compact car I4 3 2.4L 4V DOHC I4 4sp AT Small car Midsize car/Small MPV I4 4 3.0L 4V DOHC V6 4sp AT Minivan Compact car/Small MPV V6 5 3.3L 4V DOHC V6 4sp AT Large car Midsize/Large car V6 6 4.5L 4V DOHC V8 4sp AT Large car Midsize car/Large car V8 7 2.6L 4V DOHC I4 (I5) 4sp AT Minivan Midsize MPV/Small truck I4 8 3.7L 2V SOHC V6 4sp AT Small truck Midsize MPV/Small truck V6 9 4.0L 2V SOHC V6 4sp AT Minivan Large MPV V6 10 4.7L 2V SOHC V8 4sp AT Minivan Large MPV V8 11 4.2L 2V SOHC V6 4sp AT Large truck Large truck/van V6 12 3.8L 2V OHV V6 4sp AT Large truck Large truck/MPV V6 13 5.7L 2V OHV V8 4sp AT Large truck Large truck/van V8 14 5.4L 3V SOHC V8 4sp AT Large truck Large truck/van V8 15 5.7L 2V OHV V8 4sp AT Large car Large car V8 16 3.5L 4V DOHC V6 4sp AT Minivan Large MPV V6 17 4.6L 4V DOHC V8 4sp AT Minivan Large MPV V8Appendix B

B

- 2 18 4.0L 4V DOHC V6 4sp AT Large truck Large truck/van V6 19 5.6L 4V DOHC V8 4sp AT Large truck Large truck/van V8
To prepare inputs for the OMEGA model, EPA builds a ―master

- set‖ of technology packages. The master

- set of packages for each vehicle type are meant to reflect the most likely technology packages manufacturers would consider when determining their plans for complying with future standards (as well as technology pathways described in Chapter 3 and 6)

. In other w ords, they are meant to reflect the most cost effective groups of technologies

— those that provide the best trade

- off of costs versus fuel consumption improvements. This is done by grouping reasonable technologies in all possible permutations and ranking t hose groupings based on the Technology Application Ranking Factor (TARF). A Grouping ―reasonable technologies‖ simply means grouping those technologies that are complementary ( e.g ., turbocharging plus downsizing) and not grouping technologies that are not complementary ( e.g ., dual cam phasing and coupled cam phasing).

To generate the master

- set of packages for each of the vehicle types, EPA has built packages in a step

- wise fashion looking first at conventional gasoline technologies, then advanced gasoline technologies and then hybrid and other electrified vehicle technologies. This was done by presuming that auto makers w ould first concentrate efforts on conventional gasoline engine and transmission technologies paired with varying levels of mass reduction to improve fuel consumption. This is essentially the impact that the 2012

- 2016 rule will have as that rule did not re ly heavily on advanced gasoline technologies or hybridization /electrification of the fleet. The initial levels of mass reduction considered were up to 15%

. B Different pathways matched more intensive mass reductions with more advanced technologies.

Once the conventional gasoline engine and transmission technologies have been fully considered , we expect that auto makers would apply more complex (and costly) technologies such as advanced gasoline engines (turbocharged and cooled EGR technology for example) and further mass reduction (beyond 15%) in both the conventional and advanced gasoline packages.

From there, auto makers would most likely move to hybridization using one of two types of hybridization

– P2 or 2

- mode

— depending on the vehicle type. C These hybrids could

A The Technology Application Ranking Factor (TARF) is the factor used by the OMEGA model to rank packages and determine which are the most cost effective to apply. The TARF is calculated as the net incremental cost (or savings) of a package per kilogram of CO 2 reduced by the package relative to the previous package. The net incremental cost is calculated as the incremental cost of the technology package less the inc remental discounted fuel savings of the package over 5 years. The incremental CO 2 reduction is calculated as the incremental CO 2 /mile emission level of the package relative to the prior package multiplied by the lifetime miles travelled. More detail on t he TARF can be found in the OMEGA model supporting documentation (see EPA

- 420

- B

- 09

- 035).
B Importantly, the mass reduction associated for each of the 19 vehicle types was based on the vehicle

- type sales weighted average curb weight

. C For the current asses sment, we have considered P2 hybrids and 2

- mode hybrids and have not considered
power

- split or other hybrid technologies. The 2

- mode hybrid has been considered because it provides for hybridization of a vehicle while also maintaining acceptable towing cap ability. The P2 hybrid has been chosen2017

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- 3 employ either conventional or advanced gasoline engines and would be paired with varying levels of mass reduction ranging from 15% up to 30%.

Lastly, for some vehicle types, we anticipate that auto makers would move to more advanced electrif

ication in the form of both range extended electric vehicles (REEV) D and full electric vehicles (EV). These also would be paired with varying levels of mass reduction from 15% up to 30%. In general the packages are generated in order of increasing comple xity
or cost.

Focusing first on the conventional gasoline packages, the first step in creating these packages was to consider the 8 primary categories of conventional gasoline engine technologies. These are:

- Our ―anytime technologies‖ (ATT) which c onsist of low friction lubes, engine friction reduction, aggressive shift logic (automatic transmission only), early torque converter lock

- up (automatic transmission only), and low rolling resistance tires.

- Variable valve timing (VVT) consisting of coupl ed cam phasing ( CCP, for OHV and SOHC engines) and dual cam phasing ( DCP, for DOHC engines)

- Variable valve lift (VVL) consisting of discrete variable valve lift (DVVL, for DOHC engines)

- Cylinder deactivation (Deac, considered for OHV and SOHC V8 engines)

- Gasoline direct injection (GDI)

- Turbocharging and downsizing (TDS, which always includes a conversion to GDI )

- Stop

- start

- Mass reduction consisting, in this step, of 3%, 5%, 10% and 15%.

In this first step, we also considered the 3 primary transmission technologies. These

are:

- 6 speed automatic transmission (6sp AT)

- 6 speed dual clutch transmission with wet clutch (6sp wet

- DCT)

- 6 speed dual clutch transmission with dry clutch (6sp dry

- DCT)

In considering the transmissions, we had to first d etermine how each transmission could reasonably be applied

. DCTs, especially dry

- DCTs, cannot be applied to every vehicle type due to low end torque demands at launch. In addition , wet

- DCTs are more efficient than 6sp ATs, and dry

- DCTs are more efficient still. Further, each transmission has lower costs, respectively. Therefore, moving from 6sp AT to wet

- DCT to dry

- DCT as quickly as possible is preferable. Throughout this assess ment, each of these transmissions were allowed on each

because we believe that, in the timeframe of the current assessment, the P2 hybrid will provide the most cost effective approach to improving fuel consumption in vehicles that have no and/or comparatively low towing demands.
D We are using the term REEV synonymously with PHEV (plug

- in hybrid electric vehicle) for the purposes of this analysis.Appendix B

B

- 4

vehicle type giving consideration to the expected towing demands and curb weights as shown in Table B1

- 2 For example, vehicle type 5 is equipped with a 4 speed automatic transmission in the baseline. In a package consisting of a 3% to 20% mass reduction, we believe this vehicle type could convert to a wet

- DCT because the lighter weight results in reduced low end torque demands thus making the wet

- DCT feasible . Upon reaching 25% mass reduction, the

ve hicle type could employ a dry

- DCT because the even lighter weight results in further reduction in low end torque demands . We note that we have estimated that all vehicle types will employ DCTs rather than 6 speed automatic transmissions, because we believ e that the
wet

- DCT is capable of meeting the towing demands of the light

- duty fleet while providing better efficiency and lower costs than the 6 speed automatic transmission, and it is thus reasonable to assume that all manufacturers will choose to employ wet

- DCTs rather than 6 speed automatic s.

Table B1

- 2 : Application of Transmission Technologies in Building Packages

Vehicle Type # Vehicle

Class Base

Engine Mass Reduction

0% 3% 5% 10% 15% 20% 25% 30%

1 Subcompact I4 4spAT 6sp dry

- DCT

2 Small car I4 4spAT 6sp dry

- DCT

3 Small car I4 4spAT 6sp dry

- DCT

4 Minivan V6 4spAT 6sp wet

- DCT 6sp dry

- DCT

5 Large car V6 4spAT 6sp wet

- DCT 6sp dry

DCT
6 Large car V8 4spAT 6sp wet

- DCT

7 Minivan I4 4spAT 6sp dry

- DCT

8 Small truck V6 4spAT 6sp wet

- DCT

9 Minivan V6 4spAT 6sp wet

- DCT

10 Minivan V8 4spAT 6sp wet

- DCT

11 Large truck V6 4spAT 6sp wet

- DCT

12 Large truck V6 4spAT 6sp wet

- DCT

13 Large truck V8 4spAT 6sp wet

- DCT

14 Large truck V8 4spAT 6sp wet

- DCT

15 Large car V8 4spAT 6sp wet

- DCT

16 Minivan V6 4spAT 6sp wet

- DCT

17 Minivan V8 4spAT 6sp wet

- DCT

18 Large truck V6 4spAT 6sp wet

- DCT

19 Large truck V8 4spAT 6sp wet

- DCT

We start by first building a ―preliminary

- set‖ of conventional gasoline packages for each vehicle type consisting of combinations of each of these 8 primary engine technologies. The initial packages represent what we expect a manufacturer will most likely implement on all vehicles, including low rolling resistance tires, changes to accommodate low friction lubricants, engine friction reduction, aggressive shift logic, early torque converter lock

- up and improved electrical accessories. Subsequent packages include more sophisticated gasoline engine and tra nsmission technologies such as turbo/downsizing, GDI, increasing mass reduction and dual

- clutch transmissions. This preliminary

- set of conventional gasoline2017

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B

- 5 packages was ranked by its TARF for each vehicle type. The TARF ranking process eliminated some p ackages in favor of more cost effective packages. The packages that remained after the TARF ranking process were then included in the master

- set of packages for each vehicle type.

Once the preliminary

- set of conventional gasoline packages had been pared d own and moved into the master

- set of packages, the most effective ( i.e ., not the most cost effective, but simply the most effective) of the conventional gasoline packages was paired with increasing levels of mass reduction up to 30%. Also, the advanced gas oline packages come in

— note that all advanced gasoline packages are turbo/downsized GDI engines equipped with cooled EGR, dual cam phasing and discrete variable valve lift. We have built one advanced gasoline package without stop

- start technology and one with. Each of these is then paired with increasing levels of mass reduction up to 30%. Even though these advanced technologies are paired with increased mass reduction, the model is able to isolate the effect of these individually in order to examine the separate technology pathways described in Chapter 3 and 6 of the TAR. The master

- set of packages now consists of the most cost effective conventional gasoline packages with mass reductions ranging from 0% to 15%, the most effective conventional gasoline package with increasing levels of mass reduction up to 30%, and advanced gasoline packages (both with stop

- start and without) with mass reduction levels ranging from 15% to 30%.

The next packages after the conventional and advanced gasoline packages are th e HEVs. As noted, we have considered P2 and 2

- mode HEVs for this assessment as discussed in section B4 E . The agencies assumed that

, for some of the vehicles types ranging in size up to and including ―Large Car‖, ―Minivan‖ and ―Small Truck‖, towing capaci ty could be reduced to approximately 1

, 500 pounds F on HEV models and that these vehicles would use a P2 HEV configuration. As described in Chapter 3, i n some cases this reflects a loss in towing utility as compared to the baseline vehicle. For such vehic le types, consumers requiring greater towing capacity would select a non

- HEV powertrain. The agencies assumed that the HEV versions of most of the larger vehicle types would require the same towing capacity as the baseline vehicle and a 2

- mode HEV powertr ain was selected for these vehicle types. The breakdown of HEV application is shown in Table B1

- 3

.

Table B1

- 3 : Types of Hybridization Considered in this Assessment

Vehicle Type # Vehicle

Class Base Engine HEV Type

1 Subcompact I4 P2 2 Small car I4 P2 3 Small car I4 P2 4 Minivan V6 P2

E P2 hybrids are defined and described in Chapter 3 (sction 3.2.3)Appendix B

B

- 6 5 Large car V6 P2 6 Large car V8 P2 7 Minivan I4 P2 8 Small truck V6 P2 9 Minivan V6 2

- mode 10 Minivan V8 2

- mode 11 Large truck V6 2

- mode 12 Large truck V6 P2 13 Large truck V8 2

- mode 14 Large truck V8 2

- mode 15 Large car V8 P2 16 Minivan V6 P2 17 Minivan V8 2

- mode 18 Large truck V6 P2 19 Large truck V8 2

- mode

As done with conventional gasoline packages, we began with a preliminary

- set of HEV packages that paired the HEV powertrain with increasing levels of engine technologies. For example, the preliminary

- set of HEV packages would pair the HEV powertrain first with a very basic gasoline engine ( e.g., anytime technologies (ATT) and variable valve timing (VVT ), such as dual cam phasing (DCP) ), then a slightly more sophisticated gasoline engine ( e.g., ATT, DCP , GDI), then a more sophisticated gasoline engine ( e.g. , ATT, DCP , GDI, turbo/downsize), then an advanced gasoline engine ( e.g., ATT, DCP , variable valve lift, GDI, turbo/downsize, cooled EGR), etc. We then ranked the preliminary

- set of HEV packages according to TARF to generate the most cost effective set of HEV packages for each vehicle type that would then be included in the master

- set of packages.

In general, the result of the TARF ranking of the preliminary

- set of packages resulted in a master

- set of packages that included three versions of HEV for each v ehicle type. The first version employ s a simple conventional gasoline engine such as one equipped with anytime technologies and valve timing control. The second employ s a downsized/turbocharged gasoline engine and gasoline direct injection. The third em ploy s an advanced gasoline engine with turbo/downsizing, direct injection and cooled EGR. Each of these versions of HEV was then paired with mass reduction levels ranging from 15 % to 30%

. The last step was to build the REEVs and EVs for vehicle types 1 through 8 and 15. The other vehicle types were not considered for electrification beyond HEVs for purposes of the current analysis, either because of their expected towing demands or because of their high vehicle weight which would make the electrificatio n of the vehicle prohibitively expensive. We have developed 2 primary types of REEV packages and 3 primary types of EV packages all of which are included in the master

- set of packages . The REEVs consist of packages with battery packs capable of 20 miles of all electric operation (REEV20) and packages with battery packs capable of 40 miles of all electric operation (REEV40). For EVs, we have built packages capable of 75, 100 and 150 miles of all electric operation, EV75, EV100 and EV150, respectively. Th ese ranges were selected to represent an increasing selection of ranges (and costs) that consumers will require and that we believe will be available in the2017

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B

- 7 2020 timeframe. For each of these packages, we have estimated specific battery

- pack costs for syst ems placed in vehicles with 15% and 20% mass reduction to the ―glider‖ ( i.e., the vehicle less any powertrain elements) . We have then paired each REEV with 15%, 20% , 25% and 30% mass reduction and each EV with 15% and 20% mass reduction. Note that the RE EVs with 25% and 30% mass reduction are not assumed to be constructed with the smaller battery packs and electric motors that would be possible with the 30%

- lighter vehicle. This may make our estimates of cost effectiveness for REEVs with these higher mas s reduction s conservative since, while the higher mass reduction means lower fuel consumption and CO 2 emissions, those benefits are balanced against the higher costs of further mass reduction without accounting for the lower cost of a smaller battery pack and motor. The end result is a
master

- set of over 40 packages for those vehicle types with REEVs and EVs and as many as 30 packages for those vehicle types without REEVs and EVs. Because of the large number of total packages, Table B1

- 4 shows only the re sultant master

- set of packages for vehicle type 5, a large car with a V6 DOHC engine in the baseline. Note that a complete master

- set of packages for each vehicle type along with their costs and effectiveness estimates is contained in a memorandum to the docket for this report. 1 Importantly, for each level of mass reduction, there is some level of expected engine downsizing made possible due to the lower vehicle weight. The analysis does not account for any cost credit for downsizing that consists only o f minor displacement changes ( i.e., less than 20%)

— only because we have not yet developed estimated costs or savings of doing so

— even though the engine itself would contain somewhat less material. However, when a downsize occurs that consists of cylinders being removed (in the case of V8 to V6 and V6 to I4 downsizing) or a large displacement change (in the case of an I4 to smaller I4) , we do consider the cost implications of the downsizing because we have tear

- down data upon which to base our cost estimate s

.

Table B1

- 4 : Technology Packages used in OMEGA for Vehicle Type 5, Large Car V6

Tech Pkg # Mass Rdxn Package Technologies Transmission Description

500 0% 3.3L 4V DOHC V6 4sp AT Base line Package 501 3% 4V DOHC I4+ATT+DCP+GDI+TDS 6sp DCT

- wet ATT=Anytime tech s 502 5% 4V DOHC I4+ATT+DCP+GDI+TDS 6sp DCT

- wet DCP=dual cam phasing

503 15% 4V DOHC I4+ATT+DCP+GDI+TDS 6sp DCT

- wet GDI=gasoline direct injection, TDS=turbo/downsize

504 15% 4V DOHC I4+ATT+DCP+DVVL+GDI+TDS 6sp DCT

- wet DVVL=discrete variable valve lift 505 15% 4V DOHC I4+ATT+DCP+DVVL+GDI+TDS+SS 6sp DCT

- wet SS=stop

- start 506 15% 4V DOHC I4+ATT+DCP+DVVL+GDI+TDS+EGR 6sp DCT

- wet EGR=cooled EGR 507 15% 4V DOHC I4+ATT+DCP+DVVL+GDI+TDS+SS+EGR 6sp DCT

- wet 508 20% 4V DOHC I4+ATT+DCP+DVVL+GDI+TDS+SS 6sp DCT

- wet 509 25% 4V DOHC I4+ATT+DCP+DVVL+GDI+TDS+SS 6sp DCT

- dry 510 30% 4V DOHC I4+ATT+DCP+DVVL+GDI+TDS+SS 6sp DCT

- dry 511 20% 4V DOHC I4+ATT+DCP+DVVL+GDI+TDS+EGR 6sp DCT

- wet 512 25% 4V DOHC I4+ATT+DCP+DVVL+GDI+TDS+EGR 6sp DCT

- dry 513 30% 4V DOHC I4+ATT+DCP+DVVL+GDI+TDS+EGR 6sp DCT

- dry 514 20% 4V DOHC I4+ATT+DCP+DVVL+GDI+TDS+SS+EGR 6sp DCT

- wet 515 25% 4V DOHC I4+ATT+DCP+DVVL+GDI+TDS+SS+EGR 6sp DCT

- dry 516 30% 4V DOHC I4+ATT+DCP+DVVL+GDI+TDS+SS+EGR 6sp DCT

- dry

517 15% 4V DOHC I4+ATT+DCP+DS+HEV 6sp DCT

- wet HEV=P2 for this vehicle type 518 20% 4V DOHC I4+ATT+DCP+DS+HEV 6sp DCT

- wet 519 25% 4V DOHC I4+ATT+DCP+DS+HEV 6sp DCT

- dryAppendix B

B

- 8

520 30% 4V DOHC I4+ATT+DCP+DS+HEV 6sp DCT

- dry 521 15% 4V DOHC I4+ATT+DCP+GDI+TDS+HEV 6sp DCT

- wet 522 20% 4V DOHC I4+ATT+DCP+GDI+TDS+HEV 6sp DCT

- wet 523 25% 4V DOHC I4+ATT+DCP+GDI+TDS+HEV 6sp DCT

- dry 524 30% 4V DOHC I4+ATT+DCP+GDI+TDS+HEV 6sp DCT

- dry 525 15% 4V DOHC I4+ATT+DCP+DVVL+GDI+TDS+EGR+HEV 6sp DCT

- wet 526 20% 4V DOHC I4+ATT+DCP+DVVL+GDI+TDS+EGR+HEV 6sp DCT

- wet 527 25% 4V DOHC I4+ATT+DCP+DVVL+GDI+TDS+EGR+HEV 6sp DCT

- dry 528 30% 4V DOHC I4+ATT+DCP+DVVL+GDI+TDS+EGR+HEV 6sp DCT

- dry 529 15% 4V DOHC I4+ATT+GDI+DS+REEV20 6sp DCT

- wet 530 20% 4V DOHC I4+ATT+GDI+DS+REEV20 6sp DCT

- wet 531 30% 4V DOHC I4+ATT+GDI+DS+REEV20 6sp DCT

- dry 532 15% 4V DOHC I4+ATT+GDI+DS+REEV40 6sp DCT

- wet 533 20% 4V DOHC I4+ATT+GDI+DS+REEV40 6sp DCT

- wet 534 30% 4V DOHC I4+ATT+GDI+DS+REEV40 6sp DCT

- dry 535 15% EV75 (27kWh, 75 miles onroad @ 314 Wh/mi) N/A 536 20% EV75 (27kWh, 75 miles onroad @ 304 Wh/mi) N/A 537 15% EV100 (39kWh, 100 miles onroad @ 323 Wh/mi) N/A 538 20% EV100 (39kWh, 100 miles onroad @ 314 Wh/mi) N/A 539 15% EV150 (63kWh, 150 miles onroad @ 346 Wh/mi) N/A 540 20% EV150 (63kWh, 150 miles onroad @ 337 Wh/mi) N/A
To reiterate, some preliminary packages considered during the package creation
process were determined to not be cost

- effective when ranked with other packages for the given vehicle type

. For example, the packages shown in Table B1

- 4 move immediately from the baseline package to a rather complex turbo/downsized package in package number 501. This does not mean that we did not consider packages consisting only of, for e xample, DCP or DCP+GDI when generating our preliminary

- set of packages . Rather, it means that those packages simply were not as cost effective in this analysis, based on their Technology Application Ranking Factor (TARF), as was the package shown as #501. For that reason, the intermediate packages that were part of the preliminary

- set of packages have simply been eliminated from consideration and have not been included in the master

- set of packages since OMEGA will never pick them given the levels of pote ntial standards considered in this Technical Assessment Report.

Once the master

- set of packages is complete, they are all ranked once again based on TARF to generate the ―ranked

- set‖ of packages for each of the technology paths discussed in Section 3.3 of the main report. While the master

- set of packages is considered unchanging (at least in the context of this current analysis), the ranked

- set of packages is different for each technology pathway because each pathway has different levels of, for example, mass reduction caps. For a technology pathway with a mass reduction cap of 15%, those packages with mass reductions greater than 15% would be eliminated from consideration and would not be included in the ranked

- set of packages. Likewise, those packages having mass reductions greater than 20% would be eliminated in a technology pathway having a mass reduction cap of 20%. The package ranking also changes for each given year since technology costs and, hence, package costs change year

- to

- year. As a result , a ranked

- set of packages in 2020 may or may not include the same packages as a ranked

- set of packages in 2025 even if using the same mass reduction cap, and they may or may not be ranked in the same order.2017

- 2025 Technical Assessment

B

- 9 

## B2 Engine Technologies

B2.1 Updated Tear

- down Costs from FEV

As noted in Chapter 3, the agencies have reconsidered many of the costs used in the 2012

- 2016 joint final rule where those costs were based on tear

- down studies conducted by FEV under contract to EPA. We have reconsidered these costs because, in the 2012

- 2016 light

- duty final rule, the agencies relied on the FEV tear

- down study findings in part for estimating the cost of several technologies. However, for some of the technologies, NHTSA and EPA modified FEV’s actual estimated costs. This was done be cause FEV based their costs on the assumption that these technologies would be mature when produced in large volumes (450,000 units or more). The agencies believed that there was some uncertainty regarding each manufacturer’s near

- term ability to employ t he technology at the volumes assumed in the FEV analysis with fully learned costs. There was also the potential for near term (earlier than 2016) supplier

- level costs to be higher than those considered in the FEV analysis because existing equipment and fac ilities need to be converted to the production of new technologies and may lead to stranded capital if done too rapidly. G However, the agencies consider the FEV results to be valid for the 2017

- 2025 timeframe because the limitations considered in the 2012

- 2016 light

- duty rule should no longer exist and sales volumes of 450,000 units are likely by then due to, at least in part, the new GHG and fuel economy requirements.

We reiterate that the agencies believe that the best method to derive technology cost

e stimates is to conduct studies involving tear

- down and analysis of actual vehicle components. A tear

- down analysis involves breaking down a technology into its fundamental parts and manufacturing processes by completely disassembling vehicles and vehicle subsystems and precisely determining what would be required for its production. More details about tear

- down studies can be found in the studies supporting the 2012

- 2016 light

duty final rule as well as the FEV and Munro Associates report for EPA. 2 This tear

- down method of costing technologies is often used by manufacturers to benchmark their products against competitive products. Historically, vehicle and vehicle component tear

- down has not been done in large scale by researchers and regulators due to the expense required for such studies.

To date, such tear

- down studies have been completed on the five technologies listed below. These completed tear

- down studies provide a thorough evaluation of the component or system cost relative to their ba seline (or replaced) technologies. A more detailed description of these technologies can be found in the Technical Support Document prepared for the 2012

- 2016 light

- duty final rule. 3 For these technologies, the agencies have relied on the tear

- down data available and scaling methodologies used in EPA’s ongoing study with FEV.

G Stranded Capital is defined as manufacturing equipment and facilities that cannot be used in the production of a new technology.Appendix B

B

- 10

1. Stoichiometric gasoline direct injection and turbocharging with engine downsizing (TDS) for a large DOHC (dual overhead cam) 4 cylinder engine to a smaller DOHC 4 cylinder engine. 2. Stoichiometric gasoline direct injection and turbo charging with engine downsizing for a SOHC (single overhead cam) 3 valve/cylinder V8 engine to a SOHC V6 engine. 3. Stoichiometric gasoline direct injection and turbo charging with engine down sizing for a DOHC V6 engine to a DOHC 4 cylinder engine. 4. 6

- speed automatic transmission replacing a 5

- speed automatic transmission. 5. 6

- speed wet dual clutch transmission (DCT) replacing a 6

- speed automatic transmission.

FEV’s costing methodology for these studies has been published and has been peer reviewed. 4 Using this tear down costing methodology, FEV has developed costs for each of the above technologies. In addition, using the studies listed above, FEV and EPA were able
to extrapolate the engi ne downsizing costs for the following scenarios to estimate costs presented in the 2012

- 2016 rule :

1. Downsizing a SOHC 2 valve/cylinder V8 engine to a DOHC V6. 2. Downsizing a DOHC V8 to a DOHC V6. 3. Downsizing a SOHC V6 engine to a DOHC 4 cylinder engi ne. 4. Downsizing a DOHC 4 cylinder engine to a DOHC 3 cylinder engine.

The costs used in the 2012

- 2016 rule and the updated costs used in this assessment are shown in Table B2.1

- 1

.

Table B2.1

- 1 : Comparison of Stoichiometric Gasoline Direct Injection, Turb o/Downsizing and Transmission Costs , Inclusive of Markups, used in the 2012

- 2016 Rulemaking versus this Assessment

2012

- 2016 rulemaking; applicable to the 2012MY (2007 dollars) 2012

- 2016

rulemaking; applicable to the 2016MY (2007 dollars) Assessment

Report; applicable to the 2017MY (2008 dollars) Assessment

Report; applicable to the 2025MY (2008 dollars) Stoichiometric GDI (I3/I4) a $236 $209 $213 $181 Stoichiometric GDI (V6) a $341 $301 $370 $299 Stoichiometric GDI (V8) a $390 $346 $446 $360 Turbo/Downsize I4 DOHC to I3 DOHC b $395 $349 $287 $245

Turbo/Downsize I4 DOHC to smaller I4 DOHC b $441 $391 $365 $311

Turbo/Downsize V6 DOHC to I4 DOHC b $168 $149

- $27

- $3

Turbo/Downsize V6 SOHC to I4 DOHC b $365 $323 $110 $107

Turbo/Downsize V6 OHV to I4 DOHC b $872 $771 $754 $628

Turbo/Downsize V8 DOHC to V6 DOHC b $669 $592 $491 $428

Turbo/Downsize V8 SOHC $923 $816 $649 $5552017

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B

- 11 2V/cyl to V6 DOHC Turbo/Downsize V8 SOHC 3V/cyl to V6 DOHC b $832 $736 $590 $507

Turbo/Downsize V8 OHV to V6 DOHC b $1,242 $1,099 $1,101 $920
6 speed automatic transmission (from a 4 speed automatic transmission) a $112 $99

- $13

- $10

6 speed dual wet

- clutch transmission (from a 4 speed automatic transmission) a $104 $92

- $134

- $108

6 speed dual dry

- clutch transmission (from a 4 speed automatic transmission) a $53 $47

- $190

- $153

a Low complexity ICMs applied: 2012MY=1.11; 2016MY=1.11; 2017MY=1.17; 2025MY=1.13. The 2012MY and 2016MY ICMs differ from the 2017MY ICM

— all considered near term

— due to factors described in Section 3.2.5 of the main report. The 2025MY ICM is a long term ICM.
b Medium complexity ICMs applied: 2012MY=1.25; 2016MY=1.25; 2017MY=1.31; 2025MY=1.19. The 2012MY and 2016MY ICMs differ from the 2017MY ICM

— all considered near term

— due to factors described in Section 3.2.5 of the main report. The 2025MY ICM is a l ong term ICM.

B2.2 Advanced Gasoline Cost and Effectiveness

B2.2.1 Turbocharged/downsized Engines with Gasoline Direct Injection

In the 2012

- 2016 final rule, the agencies estimated the combined effectiveness of turbocharging, engine downsizing and GDI in reducing GHG emission to be 7%. Recent data supports GHG effectiveness in the range of 12 to 30% depending on the extent of engine downsizing for a given engine torque requirement. 5

, 6

, 7 Taking into consideration the availability of more recent published data and confidential business information , the Agencies estimate the effectiveness of a Turbocharged GDI with single

- stage turbocharging, dual cam

phasing and with downsizing consistent with a BMEP level of approximately 22

- 24 bar to be 15%.

B2.2.2 Cooled EGR

A new technology considered for this assessment was cooled EGR with turbocharging. This technology was described briefly in the 2012

- 2016 GHG and CAFE final rule but the technology was not used in the cost and effectiveness analys is. Cooled E GR can prevent combustion knock and thus allows for an increase in engine compression ratio and/or

more aggressive engine downsizing when combined with turbocharging and gasoline direct inject i on while maintaining torque output and vehicle performance. C o oled EGR with aggressive engine downsizing ( approximately 24

- bar BMEP)

, single

- stage turbocharging

, dual cam phasing and discrete variable valve lift has been estimated by Ricardo to reduce CO2 emissions over both the UDDS and highway fuel economy test by 23%. 8 The incremental e ffectiveness of cooled EGR relative to a downsized, turbocharged GDI enginesAppendix B

B

- 12

without EGR has been estimated to reduce BSFC by various sources to be approximately 5 to 13 %. 5

, 9

, 10

, 11 Based on the cited publically available data and confidential business information, the Agencies estimate the incremental effectiveness of cooled EGR with single

stage variable geometr y turbocharging and with downsizing consistent with approximately 24

- bar BMEP to be 6 % relative to turbocharging, downsizing and GDI without cooled EGR as described in section B2.2.1 ; and 20% relative to a baseline 2008 PFI engine

. We expect to update the effectiveness values of this technology for the NPRM based on vehicle simulation modeling currently being conducted under an EPA contract with Ricardo.

The co sts for the technology here build upon the costs presented in the 2012

- 2016 rule which showed costs of $75 for an EGR cooler, $20 for an EGR valve and $20 for associated piping for a total direct manufacturing cost of $115 (2007 dollars). We have updated each of those costs to 2008 dollars with the results being $ 7 7, $20 and $20, for a total of $117. To provide sufficient transient engine control, we have assumed that a dual

- loop EGR system will be used with both high and low pressure EGR loops. We have doubled EGR component costs to $235 to reflect components in both EGR loops and have added a $5 v enturi to provide for EGR flow from the low pressure exhaust system to the high pressure intake system , thus giving a total of $240 for the cooled EGR portion of the system. Because the system is expected to employ higher levels of boost over a broader range of flow conditions than the conventional gasoline turbocharged system, we have also included a 1.5x factor to t he turbocharger costs to cover the incremental cost increase of a variable geometry turbocharger

. In other words, the turbocharger system cost is 1.5x greater on engines with cooled EGR than

on downsized, turbocharged engines without cooled EGR

. This was estimated based on engineering judgment with input from suppliers. Therefore, to the $240 value, we have added $620 for I

- configuration engines (1.5x the single turbocharger cost of $413 equals $620) and $1,043 (1.5x the twin turbocharger cost of $695 equ als $1,043) for V

- configuration engines (one turbocharger per cylinder bank , which is conservative as it is possible that not all V

configuration engines will use twin turbochargers )

. The results being $859 ($240+$620) for I

- configuration engines and $1,2 83 ($240+$1,043) for V

- configuration engines (direct manufacturing costs, 2008 dollars, 2012MY). All of the costs stated thus far represent direct manufacturing costs in 2008 dollars and are applicable to the 2012 model year. We consider time based learn ing to be applicable to this advanced gasoline technology

. The resultant direct manufacturing cost and marked up costs are shown in Table B2.2

- 1 Importantly, these costs shown here do not represent package costs since they do not include the anytime tech nologies, H DCP, DVVL, GDI, or downsizing related costs or other technologies that might be included in an advanced gasoline package (such as stop

- start or hybridization).

Table B2.2

- 1 : Cooled EGR System Costs (2008 dollars)

Direct Mfg Costs Costs with ICM Year 2012 2020 2025 2012 2020 2025 I

- configuration engines $859 $701 $634 $1,125 $878 $754 V

- configuration engines $1,283 $1,048 $947 $1,681 $1,304 $1,127

H Anytime technologies are simpler technologies that can be added outside the normal redesign cycle, thus they can be implemented anytime. An example is low rolling resistance tire s.2017

- 2025 Technical Assessment

B

- 13 ICM applied 1.31 1.31 1.19



## B3 Transmission Technologies

B3.1 6, 7, and 8 speed Automatic Transmissions

As discussed in the 2012

- 2016 rule, m anufacturers can choose to replace 4

- and 5

- speed transmission with 6

- , 7

- , or 8

- speed automatic transmissions. Additional ratios allow for further optimization of engine operation over a wider range of conditions, but this is subject to diminishing returns as the number of speeds increases. As additional planetary gear sets are added (which may be necessary in some cases to achieve the higher number of ratios), additional weight and friction are introdu ced. Also, the additional shifting of such a transmission can be perceived as bothersome to some consumers, so manufacturers need to develop strategies for smooth shifts. Some manufacturers are replacing 4

- and 5

- speed automatics with 6

- speed automatics, and 7

- and 8

- speed automatics have also entered production, albeit in lower

- volume applications in luxury and performance oriented cars.

As discussed in the 2012

- 2016 rule , confidential manufacturer data projected that 6

- speed transmissions could incremen tally reduce fuel consumption by 0 to 5 percent from a baseline 4

- speed automatic transmission, while an 8

- speed transmission could incrementally reduce fuel consumption by up to 6 percent from a baseline 4

- speed automatic transmission. GM has publicly cl aimed a fuel economy improvement of up to 4 percent for its new 6

- speed automatic transmissions. 12 The 2008 EPA Staff Technical Report found a 4.5 to 6.5 percent fuel consumption improvement for a 6

- speed over a 4

- speed automatic transmission. 13 Based
on t his information, the agencies estimated that the conversion to a 6

- ,7

- and 8

- speed transmission from a 4 or 5

- speed automatic transmission with IATC would have an incremental fuel consumption benefit of 1.4 percent to 3.4 percent, for all vehicle classes. From a baseline 4 or 5 speed transmission without IATC, the incremental fuel consumption benefit would be approximately 3 to 6 percent, which is consistent with the EPA Staff Report estimate.

The agencies reviewed these effectiveness estimates and conclud ed that they remain
accurate. The GHG model estimates the packaged effectiveness of 4.5 to 6.5 percent.

The cost associated with 6 speed automatic transmissions has been updated for this assessment relative to the estimates presented in the 2012

- 2016 rule . These updated costs are presented above in Table B2.1

- 1 Dual Clutch Transmissions / Automated Manual Transmissions

. An Automated Manual Transmission (AMT) is mechanically similar to a conventional manual transmission, but shifting and launch functions are automatically controlled by the electronics . There are two basic types of AMTs, single

- clutch and dual

- clutch (DCT) . A single

- clutch AMT is essentially a manual transmission with automated clutch and shifting. Because of shift quality issues with si ngle

- clutch d esigns, DCT s will likely be far more

common in the U.S. and are the basis of the estimates that follow

. A DCT uses separate clutches (and separate gear shafts) for the even

- number ed gears and odd

- numbered gears. In this way, the next expecte d gear is pre

- selected

, which allows for faster and smoother shifting.Appendix B

B

- 14

For example, if the vehicle is accelerating in third gear, the shaft with gears one, three and five has gear three engaged and is transmitting power. The shaft with gears two, four, a nd six is idle, but has gear four engaged. When a shift is required , the controller disengages the odd

gear clutch while simultaneously engaging the even

- gear clutch, thus making a smooth shift. If, on the other hand, the driver slows down instead of continuing to accelerate, the transmission will have to change to second gear on the idling shaft to anticipate a downshift. This shift can be made quickly on the idling shaft since there is no torque being transferred on it.

In addition to single

- clutch and dual

- clutch AMTs, there are also wet clutch and dry clutch designs which are used for different types of vehicle applications. Wet clutch AMTs offer a higher torque capacity tha t comes from the use of a hydraulic system that cools the clutches. Wet clutch systems are less efficient than the dry clutch systems due to the losses associated with hydraulic pumping. Additionally, wet AMTs have a higher cost due to the additional hyd raulic hardware required.

Overall, DCT s likely offer the greatest pote ntial for effectiveness improvements among the various transmission options presented in this report because they offer the inherently lower losses of a manual transmission with the effi ciency and shift quality advantages of electronic control s . The lower losses stem from the elimination of the conventional lock

- up torque converter, and a greatly reduced need for high pressure hydraulic circuits to hold clutches or bands to maintain gear ratios in automatic transmissions. However, the lack of a torque converter will affect how the vehicle launches from rest, so a DCT will most likely be paired with an engine that offers sufficient torque at low engine speeds to allow for adequate launch performance.

Referring to the 2012

- 2016 rule, these transmissions offer an effectiveness of 9.5 to 14.5 percent over a 4

- speed automatic transmission. The agencies conclude that 8 to 13 percent effectiveness is still appropriate for this rule. The costs associated with 6 speed dual clutch transmissions have been updated for this assessment relative to the estimates presented in the 2012

- 2016 rule. These updated costs are presented above in Table B2.1

- 1 . EPA had hoped to include in this assess ment FEV

- generated tear

- down cost estimates for an 8 speed dual clutch transmission. Unfortunately, that work was not complete in time, but it is expected to be used in the upcoming federal NPRM

. 

## B4 Vehicle Technologies

B4.1 Aerodynamic Improvement Cost and Eff ectiveness

This can be achieved via two approaches, either reducing the drag coefficients or reducing vehicle frontal area. To reduce drag coefficients, skirts, air dams, underbody covers, and more aerodynamic side view mirrors can be applied , or the vehi cle ride height can be lowered . In addition to the standard aerodynamic treatments, the agencies have included a second level of aerodynamic technologies (Aero 2) which could include active grille shutters, rear visors, and larger under body panels. The G HG and fuel economy effectiveness of 2% is unchanged from estimates used for 2016 model year vehicles in the 2012

- 2016 final rule , and is based on a 10% assumed reduction in aerodynamic drag coefficient . This second level of2017

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- 15 aerodynamic technologies was n ot considered in the 2012

- 2016 light

- duty rule and, as such, the estimated costs are new and are presented i n Table B4.1

- 1 along with the first level (Aero 1) as used in the 2012

- 2016 rule

. Effectiveness for Aero 2 is based on an additional 10% reduction in aerodynamic drag coefficient from the 2008 baseline and provides another 2% reduction in GHG. Note that we apply time based learning to aerodynamic improvements.

Table B4.1

- 1 : Costs Associated with Aerodynamic Improvements (2008 dollars)

Direct Manufacturing Costs (applicable to the 2015MY)
Technology Quantity $/unit $/vehicle Low $/vehicle

High Aero 1 (incremental to base vehicle) Air dam 1 $15

- 20 $15 $20 Tire spats 4 $2.50 $10 Under body panels 1 $15

- 20 $15 $20 Total (Average=$40) $30 $50 Aero 2 (incremental to base vehicle) Under body panels 3, 4 $10

- 20 $30 $80 Active grill shutters 1 $25

- 40 $25 $40 Rear visors

– hood, liftgate, tailgate 1 $15

- 20 $15 $20 Low profile roof rack

– stowable cross bows 1 $30 $30 Total (Average=$120) $70 $170 Marked up costs Technology Year  2015 2020 2025 Aero 1 (ICM: Near term=1.17; Long term=1.13) $47 $40 $36 Aero 2 (ICM: Near term=1.31; Long term=1.19) $157 $128 $115

B4.2 Electrified Vehicle s Costing

– HEV, PHEV, and EV Vehicles

While the overall methodology for costing electrified vehicles has not changed from the 2012~2016 rule the scaling and cost basis for both batteries and electric motors has been modified. Specifically, cost information developed by Oak Ridge Nati onal Laboratory (ORNL) on electric motors has been applied, as well as battery costing information from Argonne National Laboratory (ANL). Refer to the Technical Support Document (TSD) 14 for the 2012

- 2016 rule for a full description of the electrified vehi cle costing methodology.

B4.2.1 Changes to the 201 7

- 2025 Electrified Vehicle Costing

Unless otherwise noted, the cost basis and scaling for electrified vehicles in the 2017

- 2025 analysis is identical to that used in the 2012

- 2016 rule. There are, however, seve ral changes to the cost basis due to various factors. The first was agreement within the agencies that the mass of electrified vehicles would continue to be reduced while energy densities of batteries are expected to increase. These trends made the curre nt battery and motor sizing strategies inappropriate for this analysis. In addition, recent data from ANL, which has been corroborated with battery manufacturer data, indicates that battery costs will be dependent on not only the annual production volume, but also the ratio of the power to energy. The agencies, once again, determined that the application of a fixed $/kW

- hr value was not appropriate going forward. One of the caveats in applying the ANL cost model was that itAppendix B

B

- 16

was highly dependent of produ ction volumes, volumes at which batteries will on be produced until approximately MY 2025. As such, the electrified vehicle costing model was to apply time based learning to the non

- battery costs, as those are based on the 2012

- 2016 rule, and treat the A NL battery costs as 2025 values. With regard to motor costs, the agencies leveraged a cost study performed by ORNL on the Toyota Prius 15 motor costs and applied the ORNL results directly. Further detail for each of these considerations is provided below.

B4.2.1.1 P2 Hybrid Electric Vehicles

A P2 hybrid is a vehicle with an electric drive motor coupled to the engine crankshaft via a clutch. The engine and the drive motor are mechanically independent of each other, allowing the engine or motor to power the vehicle separately or combined. This is similar to the Honda HEV architecture with the exception of the added clutch between the flywheel or flexplate and the electric motor, additional battery capacity, and increased electric motor power. Examples P2 hybrids in clude the 2011 Hyundai Sonata Hybrid, 2010 Hyundai Elantra LPI HEV (Korean market only), the 2011 Infinity G35 Hybrid and the 2011 Volkswagen Touareg Hybrid. The agencies believe that the P2 is an example of a ―strong‖ hybrid technology that is typical of what we will see in the timeframe of this rule. The agencies could have equally chosen the power

- split architecture as the representative HEV architecture. These two HEV’s have comparable average GHG effectiveness values (combined city and highway fuel economy), though the P2 systems may have lower cost due to reduced number of parts and complexity.

The Agencies estimate d the effectiveness of the P2 hybrid system to be 30% within our analysis. The effectiveness when combined with a DCT transmission is approximately 37%. The effectiveness used for vehicle packages with the P2 hybrid configuration within this analysis reflects a conservative estimate of system performance. Vehicle simulation modeling of technology packages using the P

- 2 hybrid configura tion is currently underway under contract with Ricardo Engineering. The agencies plan to update the effectiveness of hybrid electric vehicle packages using the new Ricardo vehicle simulation modeling runs prior to the NPRM.

Hybrid effectiveness was also a pplied differently across vehicle classes with in this analysis when compared to the 2012

- 2016 rule. Previously, the Agencies assumed less engine downsizing and reduced effectiveness with increasing vehicle size to preserve some light

towing capability for large cars, CUVs, minivans and small light trucks. For this analysis, P2 hybrid packages were only applied to vehicles with reduced towing capability (SAE Class I or less) and the relative effectiveness due to engine downsizing with the P2 hybrid packag e was applied equally across all vehicle categories capable of receiving the P2 hybrid package in the Omega model.2017

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- 17 Figure B4.2

- 1 : Functional schematic of P2 hybrid electric vehicle powertrain configuration (not to scale).

B4.2.1.2 Battery and Motor Sizing

Bas eline vehicle effective power

- to

- weight ratio I was used to approximate equivalent performance for EVs, PHEVs and P2 hybrids. Electric motors were sized based on maintaining this ratio for EV, PHEV and hybrid J vehicles. In addition, some level of mass red uction is expected to be realized for these types of vehicles, so the motor sizing was dependent on the final, mass reduced, vehicle . Motor size for PHEVs assumed full vehicle performance could be achieved on electric motor drive only. The Agencies scale d P2 hybrid motors to represent 20% of the vehicle’s (combined) effective power, as supported by manufacturer’s confidential information.

The battery packs were sized to provide 75, 100 or 150 mile on

- road K ranges in the case of EVs and 20 or 40 mile on

- ro ad ranges in the case of PHEVs. Battery sizing for EVs and PHEVs was based on a vehicle energy demand estimate (derived from EPA’s lumped parameter model) used to determine each vehicle ’s electric energy consumption, in Wh/mile, for future EV, PHEV and hy brid packages (which considers road load and weight reductions)

.

I To compare with conventional ICE

- powered vehicles, we use ―effective‖ vehicle power

- defined here as the peak combined power of the vehicle’s engine and electric motor. In the case of P2 hybrids it is assumed that the peak rated power values are addi tive, although this is not necessarily true for other architectures (such as power

split hybrids, where the engine and motor power peaks do not occur at the same operating speed)
J Vehicle weight reduction when applied to EVs and PHEVs was applied to the glider only (curb

- weight less electric drive components). Weight reduction was applied to the entire vehicle in the case of HEVs.
K EVs and PHEVs are assumed to experience an onroa d range shortfall of 30%, whereas HEVs are assumed to see a shortfall of 25%. In terms of energy consumption (and thus battery size), this represents an increase of 43% and 33% for EVs/PHEVs and HEVs, respectively.Appendix B

B

- 18

Additionally, battery usable state

- of

- charge (SOC) windows L were assumed at 80% for future EVs, 70% for future PHEVs and 50% for future HEVs

.

B4.2.1.3 Battery Cost

Battery costs were determined using a model developed by Argonne National Laboratory (ANL) which provides unique battery pack cost estimates for each of the three major types of electrified vehicles. Within the model, b attery pack costs are estimated based on a bill of materials deter mined by battery pack design criteria. The costs include materials, manufacturing processes, cost of capital equipment, plant area and labor for each manufacturing step. A basic description of the ANL Li

- ion battery cost model and initial modeling results for PHEV applications were published with in a peer

- reviewed technical paper presented at EVS

- 24 16

. ANL has extended modeling inputs and pack design criteria within the cost model to include analysis of manufacturing costs for EV and HEV battery packs in a ddition to the original work on PHEV battery costs

. 17 A thorough peer

- review of the ANL Li

- ion battery cost model and its inputs and results is pending. The agencies expect to continue to work with DOE and ANL (as well as manufacturers) to obtain the most up to date information for the upcoming NPRM.

Within the ANL battery cost model, a bill of materials for a battery pack is determined based on specific design criteria. The design criteria include a vehicle application’s power and energy storage capaci ty requirements, the battery’s cathode and anode chemistry, and the number of cells per module and modules per battery pack. The model assumes use of a laminated multi

- layer prismatic cell and battery modules consisting of double

- seamed rigid containers ( Figure B4.2

- 2 )

. The model also assumes that the battery modules are air

- cooled. The model takes into consideration the cost of capital equipment, plant area and labor for each step in the manufacturing process for battery packs and places relevant limits on electrode coating thicknesses and other processes limited by existing and near

- term manufacturing
processes. Figure B4.2

- 3 show s a basic schematic of the plant layout and production steps assumed within the model The ANL model also takes into consideration annual pack production volume and economies of scale for high

- volume production.

L On

- road range is defined as the percen tage of a battery pack’s useful operating range. For durability and safety reasons, electric vehicle batteries are not discharged completely, nor are they typically operated at fully charged levels. Because of this limitation, . Thus the nominal battery size required always larger than that which is used, and is calculated as the actual required capacity divided by the SOC window.2017

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- 19 Figure B4.2

- 2 : Prismatic Cell and Module Design for High Power

- to Energy HEV Battery Packs (provided courtesy of Argonne National Laboratory).Appendix B

B

- 20

Figure B4.2

- 3 : Lithium

- ion Battery Pack Manufacturing Plant Schematic Diagram

(provided courtesy of Argonne National Laboratory).

The cost outputs from the ANL model used by the Agencies to determine 2025 HEV, PHEV and EV battery costs assume 500, 000 pack/year producti on volume. We also assume d the use of a common cathode and anode chemistry, LiMn2O4

- spinel for the cathode and graphite for the anode. While it is expected that other Li

- ion battery chemistries will likely be available in the 2017

- 2025 timeframe, the spe cific chemistry used for the cost analysis was chosen to be consistent with publicly available information on current and near term HEV, PHEV and EV product offerings from Hyundai, GM and Nissan. 18

, 19

, 20

, 21 The battery designs used in the model also assumed fu ll power delivery at 80% of the open circuit voltage. For EVs, battery power was assumed to be sufficient to provide peak motor power for an application with 15% added to account for HVAC and other non

- motor electric loads. For HEVs and PHEVs, battery po wer was assumed to be sufficient to provide peak motor power for an application. The ANL battery cost model results for is compared to the costs used in the 2012

- 2016 final rule and to cost estimates compiled by EPA from OEM battery suppliers and auto OEM s in Figure B4.2

- 4

.2017

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- 21 Figure B4.2

- 4 : Comparison of direct manufacturing costs per unit of energy storage ($/kW

- hr) between the estimates used by EPA in the 2012

- 2016 GHG final rule , the ANL battery cost model results for PHEV 20, PHEV40, EV100 and EV1 5 0 packages and OEM battery suppliers (2008 dollars, markups not included)

. Multiple points shown for the ANL cost model results for PHEV 20, PHEV40, EV100 and EV150 reflect the range of energy

- specific costs for EPA’s subcompact through large

- car package categories (see Table B4.2

- 1 for details). A range of OEM estimated battery costs is also shown for comparison ( red bars) which may or may not reflect additional cost markups.

A PHEV and EV b attery c ost s ensitivity analysis is included in Chapter 6, sect ion 6.5 of the Technical Assessment. Th e analysis includes PHEV and EV battery pack costs approximately $100/kW

- hr higher and $50/kW

- hr lower than the costs estimates from the ANL battery cost model. The $100/kW

- hr higher cost is comparable to commodity pricing for high

- volume LiCoO2 cells for consumer applications. The $50/kW

- hr lower cost assumes a breakthrough in battery design that would approximately triple cell energy density.

B4.2.1.4 Motor Costing

The agencies agreed that based on a review of the techn ical literature the cost

- vs

power relationship should not be a constant $15/kW across motor sizes. A linear relationship was chosen based on 2007 Camry/Prius motor and generator costs (based on ORNL/EEA

estimated costs) and treated as near

- term (2012

- 2016 ) results. The motor sizing, determined as described above was then applied to the linear cost model developed by ORNL:

y (motor cost in USD) = 8.28 * (motor size in kW) + 181.43Appendix B

B

- 22

The final value is then learned down from 2012 to 2025 by applying time base d learning.

B4.2.1.5 Learning Applied to Battery and Non

- Battery Costs

As described above, the battery costs developed using the ANL model were considered the 2025 model year costs expressed in 2008 dollars. In contrast, the remaining parts of the hybrid or electrified vehicle system, termed the non

- battery costs, were considered the 2012 model year costs expressed in 2008 dollars. While the non

- battery systems are considered rather mature technologies for which time based learning is appropriate, the Li

- ion battery system is a new technology for which volume based learning is more appropriate. In fact, the agencies believe it is likely that battery technology will undergo several levels of volume based learning between 2012 and 2025 given the newness of the technology and the rapid pace of development. For this reason , we have generated a unique learning curve for the battery system technology that attempts to estimate costs back in time from the 2025 estimates discussed above. This allows us to estimate c osts in the 2020 timeframe for OMEGA as well as estimate those costs in each year between today and 2025. The learning curve we have generated is shown in Figure B4.2

- 5 . This learning curve consists of 5 full volume based learning steps each of which res ults in costs being reduced 20% relative to the prior step. These learning steps are shown occurring every two years beginning in 2012 until 2020 at which time a 5 year gap is imposed until 2025 when the ANL costs are reached and the learning curve factor equals 1. Beyond 2025, time based learning is applied at 3% cost reductions per year. The smooth line shows a logarithmic curve fit applied to the learning curve as EPA’s cost model would apply learning.

Figure B4.2

- 5 : Battery Pack Learning Curve

Using this learning curve, we can estimate the battery pack direct manufacturing costs for each year and for each type of battery pack. These details are shown in Table B4.2

- 1

0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00

2012 2016 2020 2024 2028 

## Battery Pack Learning Curve

Learning curve Log. (Learning curve)2017

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- 23 which shows, in the upper portion of the table, the estimated direct manufactur ing costs for each type of battery pack considered (for a large car in this example) and in the lower portion the $/kWh estimated in each year based on the learning curve shown in Figure B4.2

- 5

.

Table B4.2

- 1 : Direct Manufacturing Costs for Battery Pack s and Associated $/kWh for

Each, Costs for a Large Car (2008 dollars , markups not included )

Cost Element 2012 2015 2018 2019 2020 2021 2022 2023 2024 2025 Battery Pack Costs P2 batt ery pack $1,956 $1,565 $1,002 $1,002 $801 $801 $801 $801 $801 $641 REEV20 batt ery pack $7,120 $5,696 $3,645 $3,645 $2,916 $2,916 $2,916 $2,916 $2,916 $2,333

REEV40 batt ery pack $10,461 $8,368 $5,356 $5,356 $4,285 $4,285 $4,285 $4,285 $4,285 $3,428

EV75 batt ery pack $14,276 $11,421 $7,309 $7,309 $5,847 $5,847 $5,847 $5,847 $5,847 $4,678

EV100 batt ery pack $18,170 $14,536 $9,303 $9,303 $7,443 $7,443 $7,443 $7,443 $7,443 $5,954

EV150 batt ery pack $26,869 $21,495 $13,757 $13,757 $11,005 $11,005 $11,005 $11,005 $11,005 $8,804 Cost per Kilowatt

- hour $/kWh (P2) $2,964 $2,371 $1,518 $1,518 $1,214 $1,214 $1,214 $1,214 $1,214 $971 $/kWh (REEV20) $809 $647 $414 $414 $331 $331 $331 $331 $331 $265

$/kWh (REEV40) $581 $465 $298 $298 $238 $238 $238 $238 $238 $190
$/kWh (EV75) $501 $401 $256 $256 $205 $205 $205 $205 $205 $164 $/kWh (EV100) $464 $371 $237 $237 $190 $190 $190 $190 $190 $152

$/kWh (EV150) $426 $341 $218 $218 $174 $174 $174 $174 $174 $140

B4.2.1.6 In

- home Charger Costs

We have also estimated cost associated with in

- home chargers and installation of in

home chargers. Charger costs are covered in more detail in Section 4.2.3 of the main report. Here we summarize the actual costs used for developing EV and REEV package costs. We have estimated the cost of a level 1 charge cord at $30 (2008 dollars) based on typical cos ts of similar electrical equipment sold to consumers today and that for a level 2 charger at $200 (2008 dollars) . Labor associated with installing either of these chargers is estimated at $1,000 (2008 dollars) . Further, we have estimated that all REEV20 vehicles (REEVs with a 20 mile range) would be charged via a level 1 charger and that all EVs, regardless of range, would be charged via a level 2 charger. For the REEV40 vehicles (REEVs with a 40 mile range), we have estimated that: 25% of subcompacts wo uld be charged with a level 1 charger with the remainder charged via a level 2 charger; 10% of small cars would be charged with a level 1 charger with the remainder charged via a level 2 charger; and all remaining REEV 40 vehicles would be charged via a le vel 2 charger. All costs presented here are considered valid for the 2025 model year . W e have applied the learning curve presented above in Section B4.2.1.5 to the charger costs

. We have also applied our High 2 ICMs to these costs (1.70 through the 2021MY and 1.45 thereafter). Installation costs, being labor costs, have no learning impactsAppendix B

B

- 24

or ICM applied. The resultant costs for 2017, 2020 and 2025 are shown i n Table B4.2

- 2

. These costs are included in our package costs for all REEV and EV packages

.

Table B4.2

- 2 : In

- home Charger Related Costs for REEVs and EVs (2008 dollars)

Technology Vehicle Class 2017 2020 2025

REEV20

- Charger Subcompact

Small car Large car Minivan Small truck $100 $64 $44

REEV40

- Charger Subcompact $523 $335 $228

Small car $608 $389 $265 Large car Minivan Small truck $664 $425 $290

EV

- Charger Subcompact

Small car Large car Minivan Small truck $664 $425 $290

Labor Subcompact

Small car Large car Minivan Small truck $1,000 $1,000 $1,000

B4.3 Mass Reduction Cost Model

Application of mass reduction technologies for 2017

- 2025 vehicles has been discussed at length in meetings with vehicle manufacturers in preparation for this Technical Asses sment Report. One of the challenges the manufacturers identified with respect to mass reduction was the feasibility of substituting some lower density materials for higher density materials. These issues included material availability, forming, joining, painting, corrosion, reparability, and impact performance. The agencies agree that these issues need further study in order to determine the feasibility of certain types of mass reduction and the appropriateness of assuming their applicability in the MYs 2017

- 2025 timeframe for purposes of the upcoming federal rulemaking.

To begin to address these issues, the collaborative NHTSA, EPA, and DO E team described in Chapter 3 has focused on several tasks including a peer review of the Lotus Engineering report 22 regarding holistic vehicle mass reduction opportunities, a 2 nd phase of analysis by Lotus Engineering to assess the functional performance and safety of phase 1 designs and to modify designs as appropriate through computer aided engineering (CAE), and
two projects being conducted by DOE regarding, one regarding mass reduction feasibility and2017

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- 25 the other consisting of an actual vehicle build (Multi Material Vehicle

– MMV M ). NHTSA and EPA may also consider jointly funding a study to evaluate potentially feasi ble amounts of mass reduction and their accompanying cost for MY 2017

- 2025 separately from the study contracted to Lotus engineering by CARB. Computer Aided Engineering (CAE) tools would be used to analyze the structure of the vehicle. The proposed design should meet at least the same functional objectives as the baseline vehicle. If funded, this study would be designed to be finished in time for incorporation in the final rule analysis.

For the 2012

- 2016 final rule, NHTSA and EPA relied on a 2015 cost o f $1.32 (2007$) per pound of mass reduction, and the limit of mass reduction (penetration cap) was set to 10% based on our feasibility analysis

. 23 This cost was estimated by calculating an average of the costs estimated in three studies: 2002 NAS report (n ormalized estimated cost $1.50/lb) 24

, Sierra Research (normalized estimated cost $1.01/lb for 10% mass reduction with compounding) 25 , and MIT (normalized estimated cost $1.36/lb for 14% mass reduction without mass compounding). 26 The $1.32 per pound cost wou ld be $1.35 per pound in 2008 dollars. With a year of time

- based learning at 3% per year the cost would be $1.31 (2008$) per pound in 2016 and with 4 years of time

- based learning at 2% per year would be $1.20 (2008$) per pound in 2020.

However, in the 201 7

- 2025 timeframe, many of the OEMs indicated in meetings with the agencies over the summer that they will be capable of higher levels of mass reduction than 10 percent per vehicle. The OEMs also generally stated that there is some initial amount of

mass r eduction which can be accomplished with zero or very little cost (much lower than that estimated in the 2012

- 2016 rule of $1.32/lb ), but emphasized that higher percentages of mass reduction may result in higher costs and that these costs are likely to incr ease non

- linearly with increasing mass reduction levels. In response to this stakeholder feedback and based on our own preliminary analysis of the potential for vehicle mass reduction in the 2020 and 2025 timeframe, the agencies have begun updating our m ass reduction cost model to reflect this progressively increasing level of cost. A simple non

- linear cost model is introduced below that has been employed for purposes of this Technical Assessment Report, but EPA and NHTSA intend to rely on additional stu dies for the upcoming federal rulemaking that are expected to be complete before the NPRM and final rule. T he collaborative team has taken several actions to inform the cost model , including meeting with vehicle manufacturers, DOE’s update of their 2007 s tudy on feasibility and cost, and EPA funding a 3 rd party cost assessment of the Lotus Report.

The agencies developed the non

- linear cost model for mass reduction for purposes of this Technical Assessment Report by averaging the 2012

- 2016 linear cost for mass reduction in 2025 with the cost estimate for the High Development Case in the Lotus Engineering study, and then drawing a parabolic curve between $0 for 0 percent mass reduction and that average dollar value at 32 percent mass reduction. While the a gencies recognize that there have been a number of vehicle mass reductions studies conducted in the literature in the past 10 years 27

M DOE Notice of Intent to Issue Funding Opportunity Announcement N.:DE

- FOA

- 000239. http://www.netl.doe.gov/business/solicitat ions/NOTICE%20OF%20INTENT.pdfAppendix B

B

- 26

28 29 30 31 , a complete literature review is beyond the scope of the report, and thus the agencies believe that the mass reduct ion feasibility and cost study conducted by Lotus Engineering in 2010 is the most comprehensive vehicle mass reduction study conducted to date.

Lotus Engineering purchased a 2009 Toyota Venza (a crossover SUV, or CUV) and tore the vehicle down, analyzing every subsystem of the vehicle. The study split the mass reduction into two phases: ―low‖ and ―high‖ development, to represent different potential levels of mass reduction. For the low devel opment case, the majority of the body in white (BIW) weight reduction was accomplished by converting mild steel to high strength steel. In addition, all vehicle components and subsystems were compared to the best

- in

- class vehicle mass leaders and substitu ted (and scaled) to the Venza, which allowed significantly more weight reduction and the use of mass decompounding. This approach provided an extremely cost effective manner of reducing weight and cost compared to other studies in the literature that atte mpted to evaluate reducing similar amounts of mass. In the high development case, Lotus considered much more material substitution in the BIW, from steel to aluminum, magnesium, plastic and other materials, and relied extensively on completely novel (and smart) design of all possible components to reduce mass in all vehicle systems. Table B4.3

- 1 summarizes the cost results from this study:

Table B4.3

- 1 : Costs for Mass Reduction B ased on the Lotus Engineering Study*

Low Development (19% mass reduction) H igh Development (32% mass reduction)

Cost per vehicle Lower

bound

- $400 - $1600 $600 - $600
Upper bound $800 $1800

Cost per pound Lower

bound

- $0.55 - $2.20 $0.50 - $0.50
Upper bound $1.10 $1.49

* Estimates assume a total variable (or piece) cost of the Toyota Venza to be $20,000

The agencies note that some limitations exist for the Lotus study. First, Lotus analyzed these considerable levels of mass reduction based on a single vehicle. The agen cies acknowledge that most of the improvements described in the report can be applied across all vehicles to varying degrees, but due to the expense and time of the study, it is impractical for our current purposes to conduct similar studies across many di fferent vehicles. Second, Lotus’ cost estimates were based on manufacturer (OEM) piece costs due to the initial scope of the study, and only partially include d the manufacturer tooling and assembly plant costs. As mentioned earlier, follow

- up studies are being planned to improve these cost estimates. Third, the designs created by Lotus for the low and high development cases have not been shown to meet FMVSS safety regulations and voluntary NCAP and IIHS guidelines, or to achieve vehicle functional perfor mance similar to the baseline vehicle. Each of these issues is being addressed in the Phase 2 Lotus study, but was not addressed in time for this Technical Assessment Report.2017

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- 27 The Lotus study also shows that it is possible to take up to 19% of the mass out of the vehicle at no cost (cost savings in fact) by using less costly piece costs for many components based on their benchmarking analysis. The agencies agree that it may be possible to remove mass at a cost savings on many vehicles

– there are a number of other studies that have similar conclusions. However, the agencies are concerned about assigning a negative cost value at the higher ranges of what some of the manufacturers shared was the maximum feasible (approximately 20% mass reduction) within the 2017

- 2025 timeframe. Therefore, the agencies are pursuing further cost studies to confirm all of the costs (including manufacturing and tooling) before using the Lotus results directly. The agencies do acknowledge that the Lotus study included a high de gree of uncertainty in the cost estimates, and that some degree of mass reduction may be possible at a cost savings.

The agencies note that most manufacturers stated in stakeholder meetings over the summer that they anticipate that future safety and emis sion regulatory requirements will require increases in vehicle mass and, in addition, they intend to implement voluntary safety improvements that will increase vehicle mass. Net mass reduction for the 2017

- 2025 timeframe will thus actually be the mass red uction achieved through methods similar to those identified in studies discussed above, but offset by mass increases for safety and emission regulations and voluntary safety improvements. Manufacturers also frequently stated that they already have incorpo rated varying levels of mass reduction in current production vehicles. The agencies have not considered these baseline factors explicitly in estimating the cost for mass reduction that is being used for this assessment.

Thus, to model how mass reduction c osts could increase at a non

- linear rate for purposes of this Technical Assessment Report, the agencies have relied on a parabolic shape for the cost curve

– where the cost per pound increases as the square of the percentage mass reduction. To determine t he magnitude of the curvature, the parabola was calibrated to go through a designated ―high value‖ at 32% mass reduction. To determine this high value, the agencies averaged the $ 1.20 /lb (2008$ in the 2020MY) value developed using the 2012

- 2016 rule meth odology , with the Lotus high development cost figure of $0.50/lb at 32% mass reduction (as described above) . This averaging represents two factors. First, that the agencies believe that the cost used in the 2012

- 2016 rule appropriately captures the longe r timeframe and improved d esign optimization methods that are likely to lower costs in the 2017

- 2025 timeframe ; but on the other hand, that the agencies believe that a constant value, independent of the complexities involved with greater levels of mass red uction, is not realistic. And second, as described above, the agencies believe that the Lotus costs on their own are too low, due to the missing manufacturing and tooling costs. The averaging of the two costs offsets the missing Lotus costs. A variety o f non

- linear curves could have been employed, however, the 2 nd order polynomial defines the simplest model, which seemed reasonable for the current analysis. The curve has the shape shown in Figure B4.3

- 1

.Appendix B

B

- 28

Figure B4.3

- 1 : Mass R eduction C ost M odel in D ollars per P ound in M odel Y ear 2020

C ompared to the Lotus R esults and 2012

- 2016 Final Rule C ost.

Accounting for the indirect cost markup (ICM) on the mass reduction cost model, the agencies believe that it is appropriate to assign higher markups for the hi gher levels of mass reduction due to their increased complexity and lead time required. Descriptions of these different levels of ICM are in Chapter 3. Table B4.3

- 2 shows this increasing ICM with mass reduction levels.

Table B4.3

- 2: Indirect Cost Marku p F actors for I ncreasing L evels of M ass R eduction

Mass Reduction Complexity ICM Near Term ICM

Long Term 3% Low 1.17 1.13 5% Low 1.17 1.13 10% Low 1.17 1.13 15% Low 1.17 1.13 20% Medium 1.31 1.19 25% Medium 1.31 1.19 30% High 1 1.51 1.32

Accounting for the ICMs, the model with and without markup s is shown in Figure B4.3

- 2

.2017

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- 29 Figure B4.3

- 2 : Mass R eduction C ost M odel in 2008 D ollars per P ound in M odel Y ear

2020 W ith and W ithout I ndirect C ost M arkups

As mentioned earlier, the agencies continue to explore avenues of increasing the fidelity of the mass reduction cost model, and believe that there are studies that are currently or anticipated being conducted which will improve the fidelity of the points u sed to calibrate this model and which may be employed for the upcoming federal rulemaking.



## B5 Fuel Cell Vehicle Technology Cost , Effectiveness and Lead

time As s essment

B5.1 Technology Summary

The state of fuel cell vehicle (FCV) technology has seen significant p rogress towards the U.S. Department of Energy (DOE) 2015 performance targets over the last few years. Fuel cell stack durability has more than doubled since 2006 and high volume production system cost has been reduced by over 80% since 2002 (additional de tails are provided below). Progress is still required in the areas of fuel cell costs, durability, and on

- board hydrogen storage. However, the technology has matured sufficiently for commercialization, and production launch is feasible in the 2015

- 2017 t ime

- frame. First generation vehicles will likely require financial incentives to initiate the market (as is currently planned for battery technologies).

B5.2 Fuel Cell Costs

Based on the most recent fuel cell system cost analysis by Directed Technologies, In c (DTI 32 ), contracted by DOE, today’s fuel cell technology when produced at high volumes would have a cost of $51/kW (system net power). Additionally, projected 2015 technology at high volume production would cost $39/kW. For a 100kW system in a large car (vehicle type 5), this would equate to $3,945 (not including hydrogen storage). The analysis for this report

$0.00 $0.20 $0.40 $0.60 $0.80 $1.00 $1.20

0% 5% 10% 15% 20% 25% 30% $/pound

Mass Reduction Percentage Direct Mfr Cost
Markedup CostAppendix B

B

- 30

bundled the fuel cell system costs with the electric drive component costs consistent with how the EV and PHEV technology packages were developed . For FCVs, this analysis assumed a system sized for the large car platform (vehicle type 5), and included the HEV battery pack and hydrogen storage costs in addit ion to the system noted above.

The system costs noted above are the fully

- learned, high volu me production costs from DTI. However, these production volumes are not assumed to be achieved by 2025 for this analysis. FCV production levels of ~85,000 per year in the U.S. were assumed, representing approximately 0.5% of the U.S. LDV market in 2025. This is discussed further in Section B4.3.4. At these lower production levels, the incremental fuel cell system direct manufacturing cost is closer to +$4,800.

As part of this analysis, fuel cell vehicle production costs were developed by relying on the 2015 technology costs from DTI along with the non

- fuel cell electric drive component costs from the EPA OMEGA model. Figure B5.2

- 1 below shows the simulated production costs for a 100kW fuel cell system (average system size for larger vehicle platforms in this analysis). Note this is not the full FCV production cost which would include the full electric drive bill of material. Also not shown is the retail price markup (ICM); FCVs are assumed to have the same ICM as the EV and PHEV vehicle types, using th e high complexity ICM values noted earlier in Appendix B.

Figure B5.2

- 1 : FC Production Cost Curve for a 100kW sy stem (not including H2 storage)

(Sources: DTI (cost curve), extrapolation to 100kW)

Figure B5.2

- 2 shows the summary breakdown of vehicle cos ts at the high volume production level. The fuel cell system cost at this level is based on the DTI $39/kW high volume data point. Compared to the 2010 DTI system estimate, this 2015 production cost2017

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B

- 31 assumes system improvements, including the elimination of external humidification components, elimination of an air expander, and slightly higher membrane operating temperatures that allow the reductions in the radiator and cooling loop size. For fuel cell stack costs, DTI assumes platinum loadings of 0.15 mg /cm 2 . In addition to the fuel cell system, the battery pack modeled was the lithium

- ion battery assumed for HEVs in Table B4.2

- 1 . Balance of EV drive components include drive motors, controllers, DC/DC converters, electric AC and heating, and a few other components. Finally, as noted above, the hydrogen storage system cost was assumed to be $10/kWh, notably higher than the DOE 20 15 target given the lower production volumes.

Figure B5.2

- 2 : Detailed fuel cell system costs at high volume production

(Source: DTI, CARB)

Table B5.2

- 1 shows the resulting direct manufacturing costs for the 2020 and 2025 model years, highlighting the higher costs compared to the fully learned production levels at the far right of Figure B5.2

- 1

.

Table B5.2

- 1 : Fuel cell direct manufacturing costs at assumed production volumes

2020MY 2025MY
U.S. FCV Sales 20,000 85,000 Fuel cell system cost (100 kW) $ 5,900 $ 4,800

Hydrogen storage cost (4 kg @ $10/kWh) $1,320 $1,320Appendix B

B

- 32

Finally, as a reference, DOE’s analysis of various hydrogen storage systems was reviewed. The production costs for various on

- board hydrogen storage technology alternatives were analyzed by TIAX under contract to DOE 33 . This analysis assumed high pressure gaseous storage remained the technology choice in 2025, although the cryo

compressed alternative is receiving increased attention by major OEMs. The current DOE 2010 target is $4/kWh and the 2015 target is $2/kWh, al though DOE is planning to revise these targets soon. For the 2025 FCV simulated in this analysis, a storage cost of $10/kWh was assumed given production levels will not reach the fully mature point.

B5.3 Performance Status

Automakers are nearing DOE 2015 perf ormance targets and continue to push the technology toward commercial readiness, as documented in the DOE 2009 Report to Congress 34 . A few of the key accomplishments are listed below and further information can be found at DOE’s Hydrogen Program Accomplish ments webpage 35

. Significantly reduced the cost of automotive fuel cells (from $275/kW in 2002 to $51/kW in 2010 (DTI), based on projections of high

- volume manufacturing costs) Doubled the durability of fuel cell systems in vehicles operating under real

- world conditions (data in 2006 showed 950

- hour durability

— today, this number is 2500 hours, equivalent to approximately 75,000 miles of driving) Reduced the cost of producing hydrogen from both renewable resources and natural gas (hydrogen can now be produced by distributed reforming of natural gas at a projected high

- volume cost of $3.00/gallon gasoline equivalent; this does not take into account FCV efficiency gains over an ICE which would improve these operating costs further) Independently validate d a real

- world driving range of 450 miles for an FCV from one of the major OEMs.

The table below summarizes the cost, durability, and efficiency targets along with the status of today’s technology as assessed by DOE’s Technology Validation Program. 36

Table B5.3

- 1 : Current Status and U.S. DOE Targets for Automotive Fuel Cells

Fuel cell system volume and weight have been largely reduced and are expected to achieve the targets, allowing for marketable vehicle integration. For example, the Honda FCX 2009 (Current Status) 2010

(Cost Update) 2010

Target 2015

Target

System Efficiency 53

- 59% 60% 60% System Cost $61 /kW $51 /kW 37 $45 /kW $30 /kW Fuel Cell System Durability 2,500 hours

(~75,000 mi) 2,000 hours (~60,000 mi) 5,000 hours

(~150,000 mi) Vehicle Range 254 miles 38 250 miles 300 miles H2 Storage Costs $20 /kWh 39 $4 /kWh $2 /kWh2017

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- 33 Clarity’s fuel cell stack is 1/5 the weight and 1/4 the volume compared to the previous FCV model 40 . The weight and volume progress are a result of improvements in fuel ce ll materials (stamped metal flow plates, aromatic membrane structure, reductions in catalyst loading) and fuel cell simplification (part

- count reduction, improved manufacturing). A detailed summary of the performance of the Generation 2 FCVs being evaluat ed in the DOE Technology Validation Program can be found in the NREL presentation to the 2010 DOE Merit Review 41

. FCVs have achieved the DOE 2015 efficiency targets already, which translates into large energy and greenhouse gas reductions compared to conven tional vehicles. Although the full well

- to

- wheel (WTW) GHG reductions depend on the fuel source, hydrogen produced from natural gas and used in an FCV results in WTW GHG reductions of 50% compared to a projected internal combustion engine vehicle, and 20% compared to a projected hybrid vehicle 42 . Given that the vehicle powertrain is a zero emission technology, all emissions are generated from the fuel production and delivery stages.

B5.4 Hydrogen Storage

As noted above, the majority of FCV technology requirements necessary for a marketable vehicle have been addressed through continued R&D and demonstration. This includes rapid start

- up, cold

- start operation, stack power density, balance

- of

- plant (BOP)
ope ration, and efficiency. On

- board hydrogen storage is one of the remaining challenges that will require further development. This will not prevent the commercial launch of FCVs, however, as adequate storage systems are available for use in early commercia l vehicles. The storage technology chosen by the majority of OEMs for existing FCVs is high pressure (700 bar or 10,000 psi) gaseous storage. Although volumetric density, cost, and station dispensing complexity (a need for pre

- cooling) are not ideal, the technology is ready today.

Technologies under consideration by OEMs and energy companies for next generation vehicles include intermediate pressure gaseous storage (between 350 and 700 bar where pre

cooling won’t be required) and cryo

- compressed hydrogen storage. The latter has the promise of higher volumetric density, lower cost, and substantially reduced fuel boil

- off (in engine

- off mode) compared to liquid storage 43

. Additional FCV and hydrogen storage information can be found from the following DOE r esources.

2010 U.S. DOE Merit Review Proceedings, June 2010. http://www.hydrogen.energy.gov/annual_review10_proceedings.html 2009 U.S. DOE Hydrogen Program Annual Progress Repo rt, November 2009.

http://www.hydrogen.energy.gov/annual_progress09.html

B5.5 Commercialization Status

Production announcements have been made by at least three major OEMs for a 2015 launch. Production volumes will depend in part on the hydrogen infrastructure rollout in strategic locations where early customers are expected. In the U.S., this is likely to be inAppendix B

B

- 34

Southern California and New York where infrastructure is emerging. Based on two independent confidential surveys of OEMs and their FCV plans (conducted by the CaFCP 44 and CARB/CEC), up to 50,000 FCVs could be deployed in California by 2018 (cumulative

on

- road).

Hydrogen infrastructure continues to be a large challenge for FCVs in prepa ration for vehicle commercialization in 2015. Addressing this challenge requires stakeholder coordination and sustained commitments from both the public and private sectors. However, this activity is progressing in California, with actions coordinated by the CaFCP, CARB and CEC. The state is providing large cost

- share incentives for hydrogen stations (led by CEC), and strategic planning is relying on concepts outlined in the CaFCP’s 2009 Action Plan 45 and 2010 Progress and Next Steps, as well as the UC Da vis Roadmap

. 46

For the purposes of identifying production costs in this analysis, annual production volumes were estimated. Broadly based on California’s Zero Emission Vehicle Regulation as well as hydrogen infrastructure advancements in California and a f ew other states, it was assumed FCVs would comprise 0.5% of the U.S. LDV market in 2025. With a total assumed LDV market of 16.5 million vehicles, this equates to annual sales volumes of 85,000 nationally. Although these levels are lower than previous FC V scenarios by the DOE (ORNL 47 ) and the National Academies (NAS 48 ), they represent full commercial scale production volumes and should result in the needed FCV cost reductions such that market share could grow significantly beyond 2025.2017

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- 35 Appendix B References

1 Memorandum to Docket EPA

- HQ

- OAR

- 2010

- 0799 from Todd Sherwood dated September 16, 2010.

2 U.S. Environmental Protection Agency, ―Light

- Duty Technology Cost Analysis Pilot Study,‖ Contract No. EP

C

- 07

- 069, Work Assignment 1

- 3, December 2009, EPA

- 420

- R

- 09

- 020, Docket EPA

- HQ

- OAR

- 2009

- 0472

- 11282; peer review report dated November 6, 2009, is at EPA

- HQ

- OAR

- 2009

- 0472

- 11285; ―Light

- duty Technology Cost Analysis

– Report on Additional Case Studies,‖ EPA

- HQ

- OAR

- 2009

- 0472

- 11604

3 EPA

- 420

- R

- 10

- 901

4 U.S. Environmental Protection Agency, ―Light

- Duty Technology Cost Analysis Pilot Study,‖ Contract No. EP

C

- 07

- 069, Work Assignment 1

- 3, December 2009, EPA

- 420

- R

- 09

- 020, Docket EPA

- HQ

- OAR

- 2009

- 0472

- 11282; peer review report dated November 6 , 2009, is at EPA

- HQ

- OAR

- 2009

- 0472

- 11285; ―Light

- duty Technology Cost Analysis

– Report on Additional Case Studies,‖ EPA

- HQ

- OAR

- 2009

- 0472

- 11604.

5 Turner, J.W.G., Pearson, R.J., Curtis, R. Holland, B. ―Sabre: a cost effective engine technology combination for high efficiency, high performance and low CO 2 emissions,‖ Low Carbon Vehicles 2009: Institution of Mechanical Engineers conference proceedings, May 2009.

6 Lumsden, G. OudeNijeweme, D., Fraser, N., Blaxill, H. ―Development of a Turbocharged Direct Injection Downsizing Demonstrator Engine,‖ SAE Technical Paper Series, No. 2009

- 01

- 1503.

7 Yi., J., Wooldridge, S., Coulson, G., Hilditch, J., Iyer, C., Moilanen, P., Papaioannou, G., Reiche, D., Shelby, M. VanDerWege, B., Wearver, C., Xu, Z., Davis, D., H inds, B., Schamel, A. ―Development and Optimization of the Ford 3.5L V6 EcoBoost Combustion System,‖ SAE Technical Paper Series, No. 2009

- 01

- 1494.

8 Cruff, L., Kaiser, M., Krause, S., Harris, R., Krueger, U., Williams, M. ―EBDI

- Application of a Fully Fle xible High BMEP Downsized Spark Ignited Engine,‖ SAE Technical Paper Series, No. 2010

- 01

- 0587.

9 Taylor, J., Fraser, N., Wieske, P. ―Water Cooled Exhaust Manifold and Full Load EGR Technology Applied to a Downsized Direct Injection Spark Ignition Engine,‖ SAE Technical Paper Series, No. 2010

- 01

- 0356.

10 Kaiser, M., Krueger, U., Harris, R., Cruff, L. ―Doing More with Less

- The Fuel Economy Benefits of Cooled EGR on a Direct Injected Spark Ignited Boosted Engine,‖ SAE Technical Paper Series, No. 2010

- 01

- 0589.

11 Kapus, P.E., Fraidl, G.K., Prevedel, K., Fuerhapter, A. ―GDI Turbo

– The Next Steps,‖ JSAE Technical Paper No. 20075355, 2007.

12 General Motors, news release, ―From Hybrids to Six

- Speeds, Direct Injection And More, GM’s 2008 Global Powertrain Lineup Pro vides More Miles with Less Fuel‖ (released Mar. 6, 2007). Available at http://www.gm.com/experience/fuel_economy/news/2007/adv_engines/2008

- powertrain

- lineup

- 082707.jsp (last accessed Sept. 18, 2008).

13 ―EPA Staff Technical Report: Cost and Effectivenes s Estimates of Technologies Used to Reduce Light

- duty Vehicle Carbon Dioxide Emissions‖ Environmental Protection Agency, EPA420

- R

- 08

- 008, March 2008, at page 17, Docket EPA

- HQ

- OAR

- 2009

- 0472

- 0132.

14 Joint Technical Support Document: Rulemaking to Establish Light

- Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average Fuel Economy Standardsfor EPA and NHTSA 2012

- 2016 GHG and CAFE Rule. EPA

- 420

- R

- 10

- 901, April, 2010.

15 Olszewski, M., 2008. Evaluation of the 2007 Toyota Camry Hybrid Synergy Drive S ystem. Oak Ridge National Laboratory. ORNL/TM

- 2007/190. Oak Ridge, Tenesssee. April.Appendix B

B

- 36 16 Nelson, P.A., Santinit, D.J., Barnes, J. ―Factors Determining the Manufacturing Costs of Lithium

- Ion Batteries for PHEVs,‖ 24 th World Battery, Hybrid and Fuel Cell Ele ctric Vehicle Symposium and Exposition EVS

- 24, Stavenger, Norway, May 13

- 16, 2009 (www.evs24.org).

17 Santini, D.J., Gallagher, K.G., and Nelson, P.A. ―Modeling of Manufacturing Costs of Lithium

- Ion Batteries for HEVs, PHEVs, and EVs,‖ Paper to be presented at the 25 th World Battery, Hybrid and Fuel Cell Electric Vehicle Symposium and Exposition, EVS

- 25, Shenzhen, China, November 5

- 9, 2010 (www.evs25.org). Advance draft provided by D.J. Santini, Argonne National Laboratory, August 24, 2010.

18 ―Hyundai ups tech ante with Sonata Hybrid,‖ Automotive News, August 2, 2010.

19 ―Chevrolet Stands Behind Volt With Standard Eight

- Year, 100,000

- Mile Battery Warranty,‖ GM Press release (http://media.gm.com/content/media/us/en/news/news_detail.brand_gm.html /content/Pages/news/us/en/2010/Jul y/0714_volt_battery)

20 ―Nissan’s new 2012 hybrid system aims for 1.8

- L efficiency with a 3.5

- L V6,‖ SAE Automotive Engineering Online, February 15, 2010.

21 ―Lithium

- ion Battery,‖ Nissan Technological Development Activities ( http://www.nissan

global.com/EN/TECHNOLOGY/INTRODUCTION/DETAILS/LI

- ION

- EV/ ), 2009.

22 Lotus Engineering, Inc. ―An Assessment of Mass Reduction Opportunities for a 20 17

– 2020 Model Year Vehicle Program,‖ Published by the The International Council on Clean Transportation and available on the Internet at http://www.theicct.org/2010/03/lightweight

- future/

, March 30, 2010.

23 Joint Technical Support Document: Rulemaking to Establish Light

- Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average Fuel Economy Standardsfor EPA and NHTSA 2012

- 2016 GHG and CAFE Rule. EPA

- 420

- R

- 10

- 901, April, 2010.

24 Effectiveness and Impact of Corporate Fuel Economy Standards, NAS, 2002.

25 Basic Analysis of the Cost and Long

- Term Impact of the Energy Independence and Security Act Fuel Economy Standard, Sierra Research, 2008.

26 The Impact of Mass Decompounding on Asses sing the Value of Vehicle Lightweighting, MIT 2008.

27 Assessment of Fuel Economy Technologies for Light Duty Vehicles, NAS, 2010.

28 Analysis of Light Duty Vehicle Weight Reduction Potential, Energy and Environmental Analysis Inc, prepared for DOE, July, 20 07.

29 C ost

- E ffectiveness O f a 25% B ody and Chassis Weight

- Reduction Goal In Light

- Duty Vehicles, Das, Sujit, prepared for DOE, 2008/

30 C ost

- E ffectiveness O f a 40% B ody and Chassis Weight

- Reduction Goal In Light

- Duty Vehicles, Das, Sujit, prepared for DOE, 2009.

31 C ost

- E ffectiveness O f a 50% B ody and Chassis Weight

- Reduction Goal In Light

- Duty Vehicles, Das, Sujit, prepared for DOE, 2010.

32 Directed Technologies Inc (DTI), ―Mass

- Production Cost Estimation for Automotive Fuel Cell Systems,‖ 2010 U.S. DOE Meri t Review, FC018, June 7

- 11, 2010. http://www.hydrogen.energy.gov/pdfs/review10/fc018_james_2010_o_web.pdf2017

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- 37 33 TIAX LLC, ―Analysis of Hydrogen Storage Materials and On

- Board Systems,‖ 2010 U.S. DOE Merit Review, ST002, June 7

- 11, 2010. http://www.hydrogen.energy.gov/pdfs/review1 0/st002_lasher_2010_o_web.pdf

34 ―Hydrogen and Fuel Cell Activities, Progress, and Plans,‖ U.S. DOE Report to Congress, January 2009. http://www.hydrogen.energy.gov/program_records.html

35 http://www1.eere.energy.gov/hydrogenandfuelcells/accomplishments.html

36 Refer to Table 3.1 in the U.S. DOE 2009 Report to Congress and a year

- end summary by Dr. Sunita Satyap al, http://www1.eere.energy.gov/hydrogenandfuelcells/pdfs/ cng_h2_workshop_1_satyapal.pdf

37 DTI. Projected 2015 system cost = $39/kW. System cost does not include H2 storage assembly or electric drive components

38 Corresponds to vehicle fuel economy obse rvations of 43

- 58 mi/kg

- H2 as noted by the National Renewable Energy Laboratory (NREL) in ―Controlled Hydrogen Fleet and Infrastructure Analysis,‖ 2010 U.S. DOE Merit Review, TV001, June 10, 2010. www.hydrogen.energy.gov/pdfs/review10/tv001_wipke_2010_o_web.pdf

39 TIAX LLC, ―Analysis of Hydrogen Storage Materials and On

- Board Systems,‖ 2010 U.S. DOE Merit Review, ST002, June 7

- 11, 2010. http://www.hydrogen.energy.gov/pdfs/review10/st002_lasher_2010_o_web.pdf . (Based on 700 bar gaseous pressure system at 5.6 kg H2 storage)

40 Knight, Ben. Honda Motor Company. ―Fuel Cell Vehicle Technology Performance and Steps Ahead Presentation‖. CARB ZEV Symposium, September 21, 2009. http://www.arb.ca.gov/msprog/zevprog/2009symposium/2009program.htm

41 NREL, ―Controlled Hydro gen Fleet and Infrastructure Analysis,‖ 2010 US DOE Merit Review, TV001, June 10, 2010

42 ―Well

- to

- Wheels Greenhouse Gas Emissions and Petroleum Use,‖ U.S. DOE Hydrogen Program Record # 9002, March 25, 2009.

43 Argonne National Laboratory, ―System Level Anal ysis of Hydrogen Storage Options,‖ 2010 U.S. DOE Merit Review, ST001, June 7

- 11, 2010.

44 California Fuel Cell Partnership (CaFCP ), ―Hydrogen Fuel Cell Vehicle and Station Deployment Plan: A Strategy for Meeting the Challenge Ahead (Progress and Next Steps),‖ April 2010. http://www.fuelcellpartnership.org/re sources/print

- materials

45 CaFCP, ―Hydrogen Fuel Cell Vehicle and Station Deployment Plan: A Strategy for Meeting the Challenge Ahead (Action Plan),‖ February 2009. http://www.fuelc ellpartnership.org/resources/print

- materials

46 University of California, Davis, ―Roadmap for Hydrogen and Fuel Cell Vehicles in California: A Transition Strategy Through 2017,‖ a public

- private collaborative report following a series of workshops, December 2009.

47 Oak Ridge National Laboratory, ―Trans ition to Hydrogen Fuel Cell Vehicles & the Potential Hydrogen Energy Infrastructure Requirement,‖ ORNL/TM

- 2008/30, March 2008.

48 National Academies of Science, ―Transitions to Alternative Transportation Technologies: A Focus on Hydrogen,‖ Committee on Asse ssment of Resource Needs for Fuel Cell and Hydrogen Technologies, 2009.2017

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## Appendix C

- Reserved2017

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- 1 

## D1 Appendix D: Air Condition in g

D1.1 Overview

Over 95% of the new cars and light trucks in the United States are equipped with mobile air condition ing ( MAC or A/C ) systems. In the 1970s and 1980s, A/C systems were an optional (luxury) feature, but these systems are now standard on almost all new vehicle models. The A/C system is a unique and distinct technology on the automobile. It is different from the other technologies described in Chapter 3 of the joint Technical Support Document (TSD) to the recent MY 2012

- 2016 Final Rule in several ways. First, most of the technologies described in the joint TSD directly affect the efficiency of the engine, transmission, and vehicle systems. As such, thes e systems are almost always active while the vehicle is moving down the road or being tested on a dynamometer for the fuel economy and emissions test drive cycles. A/C on the other hand, is a parasitic load on the engine that only burdens the engine when the vehicle occupants demand it. Since it is not tested as a normal part of the fuel economy and emissions test drive cycles for compliance purposes , it is referred to as an “off

- cycle” effect. There are many other off

- cycle loads that can be switched

on by the occupant that affect the engine; these include lights, wipers, stereo systems, electrical defroster/defogger, heated seats, power windows, etc. However, these electrical loads individually amount to a very small effect on the engine (although toge ther they can be significant). The A/C system (by itself) adds a significantly higher load on the engine as described later in this chapter. Secondly, present A/C systems are capable of leak ing a powerful greenhouse gas (GHG) directly into the air

- even when the vehicle is not in operation. No other vehicle system has associated GHG leakage. Because of these factors, a distinct approach to control of MAC systems is justified, and a separate technical discussion is also warranted.

D1.2 Leakage

D1.2.1 Overview

Th is section describes a preliminary analysis of leakage emission reduction s in the 2025 timeframe. It is expected that this analysis will be reevaluated during the r ulemaking process. The technological basis for the expected leakage reductions is discusse d in detai l in the EPA‟s model year ( MY ) 2012

- 2016 L ight Duty G reenhouse Gas Final Rule (2016 FRM) RIA Chapter 2, and is summarized here.

M obile air conditioner ( MAC) systems leak a powerful greenhouse gas directly into the air

- even when the vehicle is not in operation. Because MAC emissions are not measured during certification testing for the GHG program, the 2016 final rule offered a compliance credit to enco urage manufacturers to reduce the leakage from MAC systems. The analysis discussed herein serves as an update to that analysis. As in the 2016 FRM, a 2008 vehicle is considered an unimproved system, and is the basis of the discussion shown here.

The h yd rofluorocarbon (HFC) refrigerant compound used in most model year 2008 vehicles is R134a (also known as 1,1,1,2

- Tetrafluoroethane , or HFC

- 134a). Based on theAppendix D

D

- 2

higher global warming potential (GWP) of HFC

- 134a , a small leakage of this refrigerant has a
grea ter global warming impact than a similar amount of emissions of some other mobile source GHGs

. R134a has a global warming potential of 1430, A which means that 1 gram of R134a has a warming potential equivalent to 1,430 grams of CO 2 (which has a GWP of 1). 1

The high pressure of an MAC system increases its propensity for leaks. In order for the A/C system to take advantage of the refrigerant‟s thermodynamic properties and to exchange heat properly, the system must be kept at high pressures even when not in operation. Typical static pressures can range from 50

- 80 psi depending on the temperature, and during operation, these pressures can get to several hundred psi. At these pressures l eakage can

occur through a variety of mechanisms. The refrigerant can leak slowly through seals, gaskets, and even small failures in the containment of the refrigerant . The rate of leakage may also increase over the course of normal wear and tear on the system. Leakage may also increase more quickly through rapid componen t deterioration such as during vehicle accidents

, maintenance or end

- of

- life vehicle scrappage (especially when refrigerant capture and recycling programs are less efficient). Small amounts of leakage can also occur continuously even in extremely “leak

- ti ght” systems by permeating through hose membranes. This last mechanism is not dissimilar to fuel permeation through porous fuel lines. Manufacturers may be able to reduce t he se leakage emissions through the implementation of technologies such as leak

- tig ht, non

- porous, durable components

. T he global warming impact of leakage emissions also can be addressed by using alternative refrigerants with lower global warming potential

. As MACs leak even when not being driven, it is most appropriate to determine their leakage based on a g/year or g/lifet ime. However, for purposes of an estimation of reductions , it is possible to divide lifetime leakage losses by lifetime vehicle miles traveled (VMT) in order to determine the appropriate average g/mile l eakage rate.

D1.2.2 Description of Vintaging Model Inputs and Data Sources

New data concerning HFC leakage has become available since the 2016 final rule analysis was completed. Most significantly, based on new data from the EPA Office of Atmospheric Programs ( OAP), EPA has decreased the average charge size and leakage assumed in its analysis as compared to the 2016 final rule analysis. The inputs used to derive the HFC reductions are drawn from the OAP Vintaging model and are shown below in Table D 1.2

- 1 . These values are discus sed in the following paragraphs, and are drawn from internal EPA documentation of the Vintaging model.

Table D 1.2

- 1 : Inputs for HFC Potential Reduction Calculation from Vintaging Model

A The global warmi ng potentials (GWP) used in this analysis are consistent with Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). At this time, the IPCC Second Assessment Report (SAR) global warming potential values have been agreed upon as the official U.S. framework for ad dressing climate change. The IPCC SAR GWP values are used in the official U.S. greenhouse gas inventory submission to the United Nations climate change framework.2017

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- 3 Car Truck 2008 MY Vehicle MAC Charge (g HFC) 550 780 Lifetime of a MAC system (years) 12 12 Fraction of Vehicles w/AC 99% 99% Recurring Annual Loss Rate (Service+Leaks) 18% 18% End of Life Loss 43% 43%

D1.2.2.1 Charge Size

The Vintaging model contains weighted average refrigerant charge sizes based on motor vehicle sales data and charge size data, by make, model, and year. 2008 Sales data is from Ward's US Light Vehicle Sales: 2005 through 2008 Calendar Years

. 2 Charge size data is from the Mobile Air Conditioning Society (MACS) Worldwide‟s A/C & Cooling System Specifications: 1996

- 2007

. 3 No assumptions are made regarding continued reductions in charge size beyond 2008

.

D1.2.2.2 AC System L ifetime

The Vintaging Model assumes that all light duty passenger vehicle AC systems (in the U.S.) last exactly 12 years. This is in agreement with the IPCC report IPCC/TEAP 2005 Safeguarding the Ozone Layer and the Global Climate System

– Issues Related to Hydrofluorocarbons and Perfluorocarbons, which indicates lifetimes (worldwide) of 9 to 12
years.

D1.2.2.3 Fraction of Vehicles with AC

Not all vehicles are sold with AC; Ward‟s vehicle sales data are adjusted based on the percentage of vehicles with AC, whi ch increases over time before reaching a maximum of 99% in 2002 (light trucks) and 2003 ( cars ) . The Vintaging Model assumes that 1% of vehicles continue to be sold without air conditi oning beyond 2003.

D1.2.2.4 Emission Rate s
The Vintaging Model assumes that losses occur from three events: leak, service, and disposal. Although vehicle ACs are serviced during discrete events and not usually every year, emissions from those events are averaged o ver the lifetime of the AC system. Leak and service emissions are considered “annual losses” and are applied every year; disposal is considered an “end of life loss” and is applied only once for each vintage of vehicles. Emission rates in the Vintaging model do improve over time, with the 2008 vehicle emission rates attributable to vehicles manufactured from 1998 to present.

Of note, t he Vintaging model assumes that charge loss is replaced every year; ie, a vehicle with a charge of 100 grams would lose a constant rate of 18 grams/year. While other emissions, such as fugitive emissions at a production facility, leaks from cylinders in storage, etc., are not explicitly modeled, such emissions are accounted for within the annual loss rate.Appendix D

D

- 4

D1.2.3 Calculation of the Lifetime HFC loss per vehicle

Several modifications were made to the Vintaging model outputs for the analysis of the potential HFC reductions . Most importantly, the charge size of the average car was increased as a result of the reclassification of a number of two wheel drive SUVs below 6,000 pounds as cars starting in MY 2011, as discussed in Appendix A . It was assumed that 20% of the new cars were classic trucks. As a result, the charge sizes were weighted together , with a weighting of 80% car and 2 0% truck in order to calculate the car charge under the revised MY 2011 and later definition

. The charge size of trucks was not adjusted. We also assume that only vehicles which have AC systems are eligible for the AC credit, increasing the 99% value
to 100%

Using this data, the total average lifetime losses from a n AC system can be calculated using Equation D 1.2

- 1 :

Total Lifetime HFC Emissions = (Average Charge Size) * (Average Annual Loss) * (Average Lifetime) + (End of Life Loss)

Equation D 1.2

- 1 : Calculation of Total Lifetime HFC Loss

Applying this equation results in an average per

- vehicle HFC loss of approximately 2.59 charges (18% loss of initial charge * 12 years + 43% loss at end of life.). This results in total lifetime losses of 1,543 g for cars and 2,020 grams for trucks.

D1.2.4 Calculation of the HFC Credit Maximum

T he maximum HFC credit is set so that the reduction in HFC emissions can be replaced by an equivalent amount of tailpipe CO 2 emissions. As CO 2 emissions are regulated on a gram/mile basis, the HFC emissions must be converted into an equivalent metric using Equation D 1.2

- 2

. Based on the MY 2012

- 2016 final r ule, t he total l ifetime VMT of cars and trucks is estimated at 195, 264 and 225, 865 respectively. These values are consistent with the MY 2012

- 2016 f

inal r ule , consistent with the early years of the time frame, and are slightly lower than the MY 2025 VMT estimated in this technical report

.

CO2eq g / mile = ( Total lifetime HFC emissions) / ( Total L if etime VMT) * (GWP)

Equation D 1.2

- 2 : Conversion of Lifetime HFC Emissions into CO2eq emissions

Finally, because a known 20% shortfall (the “on

- road” gap) exists between certification test CO 2 emissions and actual on

- road emissions, the CO 2 eq uivalent emissions calculated above were multiplied by 0.8 in order to appropriately offset the reduction in real emissions.

The maximum possible credit, calculated through this methodology, is shown below. Assuming that alternative refrigerant with a GWP of zero is used, the maximum potential credit would be based on removing the full lifetime emissions. As discussed in the 2016 final rule , if conventional HFC 134a were used in an AC system, the maximum potential leakage reduction is 50% of the annual emission leakage. No improvements would be expected to end2017

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- 5 of life emissions, so the total pos sible credit is approximately 45 % of the maximum credit with alternative refrigerant.

Table D 1.2

- 2 : Maximum Credit (g/mile CO 2 eq)

Car Truck Fleet

(MY 2025) Maximum Credit (Alternative Refrigerant w/ 0 GWP) 9.2 10.4 9.6

Maximum Credit (HFC 134a) 3.8 4.3 3.9 As the charges for the cars and light trucks differ, the mix of cars and trucks is significant to this analysis. MY 2025 is projected to have 67.5% cars and 2 wheel drive SUVs below 6,000 lbs.

D1.2.5 System Leakage Standards

In the timeframe considered in this Technical Assessment Report, EPA is considering a number of options to reduce A/C leakage emissions, including the setting of a refrigerant leakage standard for mobile A/C systems. The purpose of a leakage standard, as opposed to credits, is to assure that high

- quality, low

- leakage components are used in each air conditioning system design. EPA is considering a percent leakage per year standard curve, which is scaled to the refrigerant capacity of the system (i.e. small

- capacity systems would have a larger allowable leakage standard than those with larger capacity). Since refrigerant leakage past the compressor shaft seal is the dominant source of leakage in belt

- driven air conditioning systems, a single “percent refrigerant leakage per year” standard may not fairly addresses the range of system refrigerant capacities likely to be used in passenger cars, light duty trucks , and other vehicles . Since systems wi th less refrigerant may have a larger percentage of their annual leakage from the com pressor shaft seal than systems with more refrigerant capacity, their relative percent refrigerant leakage per year could be higher, and a more extensive application of leakage reducing technologies could be needed to meet a standard.

Manufacturers can choose to reduce A/C leakage emissions in two ways. First, they can utilize leak

- tight components. Second, manufacturers can largely eliminate the global warming impact of leakage emissions by adopting systems that use an alternative, low

- GWP refrigerant . EPA believes that reducing A/C system leakage is both highly cost

- effective and technologically feasible. The availability of low leakage components is being driven by the air conditioning program in the light duty GHG rule which apply to 2012 model ye ar and later vehicles. The cooperative industry and government Improved Mobile Air Conditioning (IMAC) program has demonstrated that new

- vehicle leakage emissions can be reduced by 50% by reducing the number and improving the quality of the components, fi ttings, seals, and hoses of the A/C system. All of these technologies are already in commercial use and exist on some of today‟s systems.

In the MY 2012

- 2016 rule, EPA required that manufacturers demonstrate improvements in their A/C system designs and components through a design

- based method. Th is method for calculating A/C Leakage is based closely on an industry

- consensus leakage scoring method, described below. This leakage scoring method is correlated to experimentally

- measured leakage rates from a number of vehicles using the differentAppendix D

D

- 6

available A/C components. Under th is approach, manufacturers would choose from a menu of A/C equipment and components used in their vehicles in order to establish leakage scores, which would characterize their A/C sys tem leakage performance and calculate the percent leakage per year as this score divided by the system refrigerant capacity.

Consistent with the Light Duty Vehicle Greenhouse Gas Emissions rulemaking, EPA is considering that a manufacturer would compare the components of its A/C system with a set of leakage

- reduction technologies and actions that is based closely on that being developed through IMAC and the Society of Automotive Engineers (as SAE Surface Vehicle Standard J2727, August 2008 version). See generally 75 FR at 25426. The J2727 approach was developed from laboratory testing of a variety of A/C related components, and EPA believes that the J2727 leakage scoring system generally represents a reasonable correlation with average real

- world leakage in new vehicles. Like the IMAC approach, our proposed approach would associate each component with a specific leakage rate in grams per year identical to the values in J2727 and then sum together the component leakage values to develop the total A/C syst em leakage. However, in this “percent system leakage per year” approach, the total A/C leakage score and is then divided the value by the total refrigerant system capacity to develop a percent leakage per year.

EPA believes that the design

- based approach would result in estimates of likely leakage emissions reductions that would be comparable to those that would eventually result from performance

- based testing (e.g. SAE J2763), and may consider allowing performance test results in lieu of design

- based resu lts, if a manufacturer can demonstrate that 100% of their vehicles systems are leak tested before the y leave the assembly plant . At the same time, comments are encouraged on all developments that may lead to a robust, practical, performance

- based test for measuring A/C refrigerant leakage emissions.

D1.3 Air conditioning Efficiency

D1.3.1 Overview

EPA estimates that the CO 2 emissions from A/C related load on the engine of a vehicle with an unimproved air conditioning system accounts for about 3.9% of total greenhouse gas emissions from passenger vehicles in the United States. This is equivalent to CO 2 emissions of approximately 1 4 .3 g/mi per vehicle. A complete discussion of this estimate is available in Chapter 2 of the EPA RIA to the MY 2012

- 2016 f inal r ule

.

In brief, m ost of the excess load on the engine comes from the compressor, which pumps the refrigerant around the system loop. Significant additional load on the engine may also come from electrical or hydraulic fan units used for heat exchange across the co ndenser and radiator. EPA believes that the controls which manufacturers would use to achieve improved A/C efficiency would focus primarily, but not exclusively, on the compressor

, electric motor controls, and system controls which reduce load on the A/C system (e.g. reduced „reheat‟ of the cooled air and increased use of recirculated cabin air).

The program EPA finaliz ed in the MY 2012

- 2016 f inal r ule encourage s the reduction of A/C CO 2 emissions from cars and trucks by up to 40% from 2008 baseline lev els through a2017

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- 7 credit system

. A 40% reduction would be equivalent to a reduction of 5.7 grams of CO 2 emissions per mile.

D1.3.2 A/C Efficiency Credits

Similar to the 2012

- to

- 2016 Light

- Duty GHG Rule, a design

- based approach to credits is being considered , altho ugh the number and type of items listed in the technology “menu”

– as well as the amount of credit assigned to each item

- may change as new methods of testing them in the vehicle develop. The design

- based approach used in the GHG Rule was used because it was not possible to accurately assess their effectiveness of these technologies using the A/C Idle Test.

D1.3.3 A/C Efficiency Test

A new test to measure the impact of the A/C system operation on emissions is being evaluated with input from USCAR, CARB, and the European Union. The primary goal in developing this new test is to create a test cycle and test conditions which reflect environmental and driving experience found in typical customer usage (rather than the extreme, hig h ambient temperature condition of the SC03 or the idle

- only condition of the A/C Idle Test). A secondary goal of this new test is to create a cycle which captures the effectiveness of advanced A/C technologies, and can demonstrate a fuel savings compared to a baseline technology. This new test may include a solar soak condition ( to mea sure the effectiveness of solar load reducing technologies such as solar glass and cabin ventilation), a transient drive cycle (to measure the dynamic performance of the syst em during cabin cool

down), and steady

- state cycles (to measure the effectiveness of the system under stabilized cabin temperature conditions).

If this new test cycle is able to accurately assess the efficiency of the A/C system and its components, it coul d be used to determine the level of credits available. But if the effectiveness of certain technologies cannot be measured on the new test, a design menu approach may be utilized.Appendix D

D

- 8 Appendix D References

1 IPCC. Chapter 2. Changes in Atmospheric Constituents and in Radiative Forcing. Sep tember 2007.

2 Ward‟s Automotive. Ward's US Light Vehicle Sales: 2005 through 2008 Calendar Years

.

3 Mobile Air Conditioning Society (MACS) Worldwide. A/C & Cooling System Specifications: 1996

- 2007

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## E1 Appendix E : Key Inputs to the Analysis

This section discusses the key inputs to the analysis which were jointly developed by the agencies for today’s Technical Assessment Report . These economic inputs incorporate a range of forecast information, economic estimates, and input parameters. This section describes the sources that the agencies relied upon for this information, the rationale underlying each assumption, and the agencies ’ estimates of specific parameter values. These common values were then used as inputs to the analyses presented in this Technical Assessment Report

.

Please note that there are additional economic and environmental impacts which were not considered in this assessment . A partial list includes: co

- pollutant impacts, health impacts, the social cost of carbon emissions, and energy security. The exclusion of these impacts from this Technical Assessment R eport does not suggest that these impacts should be disre garded

. As in the MY 2012

- 2016 f inal r ule, NHTSA and EPA will carefully consider other impacts of emission and fuel economy standards during the development of the upcoming Notice of Proposed Rulemaking (NPRM).

Many of the inputs used in this technical assessment are carried forward from the analyses conducted for the MY 2012

- 201 6 final rule. As part of developing the upcoming NPRM

, EPA and NHTSA wil l consider updating these inputs

.

E1.1 Vehicle Sales

As discussed in Chapter 6, the vehicle sales projection is based upon output from the National Energy Modeling System (NEMS) which is maintained by the Energy Information Administration (EIA) . As in the MY 2012

- 2016 f inal r ule, the car and truck split was drawn from NEMS, while market segmentation was drawn fr om CSM’s forecasting tool. Total market size is estimated in 2020 at 16.5 million vehicles (55.8 % cars) and in 2025 at 17.0 million vehicles (57.9% cars). Cars, in the context of NEMS, are defined using the pre

- MY 2011 CAFE definition

, as discussed abov e in Appendix A

.

For this analysis the DOT Volpe center produced a custom run of NEMS . This run generated the same overall vehicle sales as the reference case for AEO EIA A nnual Energy Outlook 2010 , but a different sales split between car s and l ight tru ck s . A detailed discussion on this topic is presented in Appendix A.

E1.2 On

- road Fuel Economy Shortfall

Fu el economy levels achieved by vehicles in on

- road driving fall significantly short of their levels measured by EPA under the laboratory test conditions used under the CAFE
program to establish its published fuel economy ratings. In analyzing the impacts from passenger car and light truck GHG and fuel efficiency standards, the agencies adjust the test fuel economy performance of each passenger car and light truck model downward from its rated value to reflect the expected size of this on

- road fuel economy differential

.Appendix E

E

- 2

The agencies note that in December 2006, EPA adopted changes to its regulations on fuel economy labeling, which were intended to bring vehicles’ rated fuel economy levels closer to their actual on

- road fuel economy levels. 1 Comparisons of on

- road and CAFE fuel economy levels developed by EPA as part of that final rule indicate that actu al on

- road fuel economy for light

- duty vehicles averages approximately 20 percent lower than published fuel economy levels. 2 While there is great heterogeneity among the population of drivers, as discussed in the referenced material, 20 percent represents the average for modeling a fleet. For example, if the overall EPA fuel economy rating of a light truck is 20 mpg, the on

- road fuel economy actually achieved by a typical driver of that vehicle is expected to be 16 mpg (20*.80). EPA and NHTSA both applie d this 20% differential in calculating the fuel savings of the MY 2012

– 2016 joint final rule

. In this technical assessment report, the agencies assume that the overall energy shortfall for the electric drivetrain is 30%. Specifically, this refers to a l arger shortfall relative to laboratory conditions while operating on electricity rather than liquid fuel. The 30% value is derived from engineering judgment based on several data points. Foremost among these

, during the stakeholder meetings conducted pri or to this technical assessment, confidential business information (CBI) was supplied by several manufacturers which indicated that electrically powered vehicles had greater variability in their on

- road energy consumption than vehicles powered by internal combustion engines. Further, d ata from the 2006 analysis of the “five cycle” label potentially supported a larger on

- road shortfall for vehicles with hybrid

electric drivetrains. 3 Finally, heavy accessory load, extreme temperatures, and aggressive drivin g have deleterious impacts of unknown magnitudes on battery performance. As a counterpoint, CBI provided by several other m anufacturers suggested that the on

road/laboratory differential attributable to electric operation should approach that of liquid fu el operation in the future. Consequently, 30% was judged a reasonable estimate for the current analysis.

E1.3 Fuel Prices

Federal government agencies generally use EIA’s projections in their assessments of future energy

- related policies. The retail fuel price forecasts presented in AEO 20 1 0 span the period from 200 7 through 203 5 . Measured in constant 2 008 dollars, the AEO 2010 Reference Case forecast of retail gasoline prices du ring calendar year 2020 is $3.3 4 per g allon, rising gradually to $3.91 by the year 2035 (these values include federal, state and local taxes). However, valuing fuel savings over the maximum lifetime s of passenger cars and light trucks used in this analysis requires fuel price forecasts that extend through 20 6 0, approximately the last y ear during which a significant number of MY 20 25 vehicles will remain in service. A To obtain fuel price forecasts for the years 203 6 through 20 6 0, the agency assumes that retail fuel prices will continue to increase after 2035 at the average annual rate (0.7%) projected for 20 08

- 2035 in the AEO 2010 Reference Case

. This assumption results in a projected retail pric e of gasoline that reaches $4.34 in 2050.

A The agency defines the maximum lifetime of vehicles as the highest age at which more than 2 percent of those originally produced during a model year remain in service. In the case of light

- duty trucks, for example, this age has typically been 36 years fo r recent model years.2017

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- 3 The value of fuel savings resulting from improved fuel economy and GHG emissions to buyers of li ght

- duty vehicles is determined by the retail price of fuel, which includes federal, state, and any local taxes imposed on fuel sales. Total taxes on gasoline, including federal, state, and local levies averaged $0.42 per gallon during 2008, while those l evied on diesel averaged $0.50. Because fuel taxes represent transfers of resources from fuel buyers to government agencies, however, rather than real resources that are consumed in the process of supplying or using fuel, their value must be deducted from retail fuel prices to determine the value of fuel savings resulting from more stringent fuel efficiency and GHG standards to the U.S. economy as a whole. 4 When calculating the costs to any individual driver, the taxes are included as part of the realized fuel savings. B

E1.4 Vehicle Lifetimes and Survival R ates

The agencies’ analys is of fuel savings and related benefits for this Technical Assessment Report begin s by estimat ing the resulting changes in fuel use over the entire lifetimes of cars and light trucks

. The change in total fuel consumption by vehicles produced during each of these model years is calculated as the difference in their lifetime fuel use under the reference and alternative assumptions.

The first step in estimating lifetime fuel con sumption by vehicles produced during a model year is to calculate the number of those vehicles expected to remain in service during each future calendar year after they are produced and sold. C This number is calculated by multiplying the number of vehicle s originally produced during a model year by the proportion expected to remain in service at the age they will have reached during each subsequent calendar year, often referred to as a “survival rate.”

The agencies used survival rate estimates from a NHTSA study 5 i n calculating fuel savings and other impacts from the analyzed scenarios

. The proportions of passenger cars and light trucks expected to remain in service at each age up to their maximum lifetimes are shown in Table E1.4

- 1

. D N ote that that these survival rates were calculated against the pre

MY 2011 definitions of cars and light trucks , because the NHTSA study has not been updated

B For society, the fuel taxes represent a transfer payment. By contrast, an individual realizes savings from not paying the additional money.
C Vehicles are defined to be of age 1 during the calendar year corresponding to the model year in which they are produced; thus for example, model year 2000 vehicles are considered to be of age 1 during calendar year 2000, age 1 during calendar year 2001, and to reach their maximum age of 26 years during calendar year 2025. NHTSA considers the maximum lifetime of vehicles to be the age after which less than 2 percent of the vehicles originally produced during a model year remain in service. Applying these conventions to vehicle registration data indicates that passenger cars have a maximum age of 26 years, while light trucks have a maximum lifetime of 36 years. See Lu, S., NHTSA, Regulatory Analysis and Evaluation Division, “Vehicle Survivability and Travel Mileage Schedules,” DOT HS 809 952, 8

- 11 (January 2006). Available at http://www

nrd.n htsa.dot.gov/Pubs/809952.pdf (last accessed August 25 , 2010)

. D T he maximum age of cars and light trucks was defined as the age when the number remaining in service has declined to approximately two percent of th ose originally produced. Based on an examin ation of recent registration data for previous model years, typical maximum ages appear to be 26 years for passenger cars and 36 years for light trucks.Appendix E

E

- 4

since 2006 . Because the agencies are unaware of a better data source, these values were used unchanged. No improvements in survival rates were explicitly projected into the future.

T he surviv al and annual mileage estimates reported in this section’s tables reflect the convention that vehicles are defined to be of age 1 during the calendar year that coincides with their model year Thus for example, model year 201 2 vehicles will be considered to be of age 1 during calendar year 201 2 . This convention is used in ord er to account for the fact that vehicles produced during a model year typical ly are first offered for sale in June through September of the preceding calendar year (for example, sales of a model year typically begin in June through September of the previou s calendar year, depending on manufacturer). Thus virtually all of the vehicles produced during a model year will be in use for some or all of the calendar year coinciding with their model year, and they are considered to be of age 1 during that year. E

E As an illustration, virtually the entire production of model year 20 12 cars and light trucks will have been sold by the end of calendar year 20 12 , so those vehicles are defined to be of age 1 during calendar year 20 12

. Model year 20 12 vehicles are subsequently defined to be of age 2 during calendar year 20 13 , age 3 during calendar year 201 4 , and so on . One complication arises because registration data are typically collected for July 1 of each calendar year, so not all vehicles produced during a model year will appear in registration data until the calendar year when they have reached age 2 (and somet imes age 3) under this convention.2017

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- 5 Table E 1

. 4

- 1 Survival Rates

VEHICLE AGE ESTIMATED SURVIVAL FRACTION CARS ESTIMATED

SURVIVAL FRACTION LIGHT TRUCKS 1 0.9950 0.9950 2 0.9900 0.9741 3 0.9831 0.9603 4 0.9731 0.9420 5 0.9593 0.9190 6 0.9413 0.8913 7 0.9188 0.8590 8 0.8918 0.8226 9 0.8604 0.7827 10 0.8252 0.7401 11 0.7866 0.6956 12 0.7170 0.6501 13 0.6125 0.6042 14 0.5094 0.5517 15 0.4142 0.5009 16 0.3308 0.4522 17 0.2604 0.4062 18 0.2028 0.3633 19 0.1565 0.3236 20 0.1200 0.2873 21 0.0916 0.2542 22 0.0696 0.2244 23 0.0527 0.1975 24 0.0399 0.1735 25 0.0301 0.1522 26 0.0227 0.1332 27 0 0.1165 28 0 0.1017 29 0 0.0887 30 0 0.0773 31 0 0.0673 32 0 0.0586 33 0 0.0509 34 0 0.0443 35 0 0.0385 36 0 0.0334Appendix E

E

- 6

E1.5 VMT

A critical element in estimating lifetime fuel use by the cars or light trucks produced during a future model year is to calculate the total number of miles that they will be driven during each year of their expected lifetimes. To estimate total miles dri ven, the number of cars and light trucks projected to remain in use during each future calendar year is multiplied by the average number of miles a surviving car or light truck is expected to be driven at each
age

. E stimates of average annual miles driven by MY 2001 cars and light trucks at each age were developed by NHTSA from the Federal Highway Administration’s 2001 National Household Transportation Survey ( Table E1.5

- 1 )

. These estimates represent the typical number of miles driven by a surviving light duty vehicle. To determine the miles driven by the average vehicle of a given vintage at a given age, one would multiply the mileage accumulation by the corresponding survival rate.2017

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- 7 Table E 1

. 5

- 1 MY 2001 Mileage Schedules based on NHTS Data

VEHICLE AGE ESTIMATED

VEHICLE MILES TRAVELED CARS ESTIMATED

VEHICLE MILES TRAVELED LIGHT TRUCKS 1 14,231 16,085
2 13,961 15,782 3 13,669 15,442
4 13,357 15,069 5 13,028 14,667
6 12,683 14,239
7 12,325 13,790 8 11,956 13,323
9 11,578 12,844 10 11,193 12,356
11 10,804 11,863
12 10,413 11,369 13 10,022 10,879
14 9,633 10,396 15 9,249 9,924 16 8,871 9,468 17 8,502 9,032 18 8,144 8,619 19 7,799 8,234 20 7,469 7,881
21 7,157 7,565
22 6,866 7,288 23 6,596 7,055
24 6,350 6,871 25 6,131 6,739 26 5,940 6,663 27 0 6,648 28 0 6,648 29 0 6,648 30 0 6,648 31 0 6,648 32 0 6,648 33 0 6,648 34 0 6,648 35 0 6,648 36 0 6,648Appendix E

E

- 8

E1.5.1 Adjusting vehicle use for future fuel prices

T he estimates of average annual miles driven by passenger cars and light trucks reported in Table E1.5

- 1 r eflect the historically low gasoline prices that prevailed at the time the 2001 NHTS was conducted

. Under the assumption that people tend to drive more as the
cost of driving decreases, the higher fuel prices in more recent projections leads to lower mileage schedules. For this report , the agencies updated the analysis with the forecasts of future gasoline prices reported in the AEO 20 10 reference case . T h is adjustment account s for the difference between the average retail price per gallon of fuel forecast during each calendar
year over the expected lifetimes of future model year passenger cars and light trucks

, and the average price that prevailed when the NHTS was conducted in 2001. The elasticity of annual vehicle use with respect to fuel cost per mile corresponding to the 10 percent fuel economy rebound effect used in this analysis ( i.e. , an elasticity of

- 0.10) was used in conjunction with th e difference between each future year’s fuel prices and those prevailing in 2001 to adjust the estimates of vehicle use derived from the NHTS to reflect the effect of higher future fuel prices. This procedure was applied to the NHTS derived mileage figures to adjust annual mileage by age during each calendar year of the expected lifetimes of future model year cars and light trucks.

E1.5.2 Ensuring consistency with growth in total vehicle use

T he estimates of annual miles driven by passenger cars and light trucks at each age were also adjusted t o reflect projected future growth in average vehicle use. Increases in the average number of miles cars and trucks are driven each year have been an important source of historical growth in total car and light truck use, and are expected to represent an i mportant source of future growth in total light

- duty vehicle travel as well. As an illustration of the importance of growth in average vehicle use, the total number of miles driven by passenger cars increased 35 percent from 1985 through 2005 , equivalent to a compound annual growth rate of 1.5 percent. 6 During that time, however, the total number of passenger cars registered for in the U.S. grew by only about 0.3 percent annually. F Thus growth in the average number of miles automobiles are driven each ye ar accounted for the remaining 1.2 percent (= 1.5 percent

- 0.3 percent) annual growth in total automobile use. G Further, the AEO 2010 Reference Case forecasts of total car and light truck use and of the number of cars and light trucks in use suggest that their average annual use will continue to increase gradually from 2010 through 2035.

In order to develop reasonable estimates of futu re growth in average car and light truck use, the agencies calculated the rate of growth in the mileage schedules necessary for

F A slight increase in the fraction of new passenger cars remaining in service beyond age 10 has accounted for a small share of growth in the U.S. automobile fleet. The fraction of new automobiles remaining in service to various ages was computed from R.L. Polk vehicle registration data for 1977 through 2005 by the agency’s Center for Statistical Analysis.
G See supra note k below.2017

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- 9 total car and light truck travel to increase at the rate forecast in the AEO 2010 Reference Case. The growth rate in average an nual car and light truck use produced by this calculation is approximately 1.15 percent per year. H This rate was applied to the mileage figures reported in Table E1.5

- 1 to estimate annual mileage by age during each calendar year of the expected lifetimes of cars and light trucks during all model years

. Separate adjustments for projected fuel prices and growth in vehicle use were made for each calendar year. Because th e effects of both fuel prices and cumulative growth in average vehicle use vary by year, these adjustments result in different VMT schedules for each future year. While the adjustment for future fuel prices generally reduces average mileage at each age fr om the 2001 values, the adjustment for expected future growth in average vehicle use increases it. The net impact is growth over time.

E1.5.3 Final VMT equation

Below, we show the equations used to determine the VMT schedules used in this analysis. This parti cular form of the equation uses a negative form of the rebound rate.

Where: V = CY 200 1 VMT from NHTSA analysis of NHTS data SGR = Secular Growth Rate YS = Years since 2001 RR= Rebound rate FCPM = Fuel Cost per mile

Where: EC = Electrical consumption per mile EP = Electricity Price GC = Gasoline Consumption per mile GP = Gasoline Price

H It was not possible to estimate separate growth rates in average annual use for cars and light trucks, because of the significant reclassification of light truck models as passenger cars discussed previously.Appendix E

E

- 10 Table E1.5

- 2 MY 2020 and 2025 Reference Mileage Schedules I

MY 2020 MY 2025

VEHICLE AGE ESTIMATED

VMT CARS ESTIMATED

VMT LIGHT TRUCKS ESTIMATED

VMT CARS ESTIMATED

VMT LIGHT TRUCKS

1 16,882 19,017 17,749 19,991 2 16,334 18,398 17,152 19,315 3 16,235 18,281 17,071 19,219 4 16,143 18,160 16,976 19,094 5 16,048 18,024 16,879 18,954 6 15,750 17,643 16,586 18,578 7 15,356 17,145 16,175 18,056 8 15,040 16,728 15,846 17,623 9 14,044 15,538 14,774 16,342 10 13,707 15,092 14,427 15,883 11 13,243 14,504 13,921 15,244 12 12,824 13,968 13,492 14,693 13 12,439 13,472 13,101 14,188 14 11,991 12,912 12,634 13,603 15 11,518 12,333 12,142 12,999 16 11,054 11,773 11,664 12,422 17 10,607 11,245 11,193 11,866 18 10,169 10,741 10,731 11,334 19 9,743 10,266 10,281 10,833 20 9,337 9,833 9,854 10,376 21 8,949 9,438 9,444 9,960 22 8,588 9,098 9,064 9,601 23 8,252 8,809 8,709 9,296 24 7,943 8,576 8,382 9,050 25 7,671 8,415 8,096 8,880 26 7,436 8,324 7,847 8,784 27 0 8,307 0 8,766 28 0 8,313 0 8,773 29 0 8,317 0 8,777 30 0 8,315 0 8,775 31 0 8,318 0 8,779 32 0 8,323 0 8,784 33 0 8,324 0 8,785 34 0 8,328 0 8,789 35 0 8,335 0 8,797 36 0 8,335 0 8,797

I VMT schedules differing by approximately 0.2% over the course of a vehicle lifetime were used in the estimation of costs and impac ts. The VMT schedules used in cost estimation are shown here.2017

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- 11 E1.5.4 Comparison to the VMT schedules in the MY 2012

- 2016 Final Rulemaking

The VMT schedules used in the MY 2012

- 2016 final rulemaking and this assessment report are compar e d below.

Table E1.5

- 3 Summary of Reference Expected Lifetime VMT

2001 NHTS in NHTSA Report MY 2012

- 2016

Final Rule MY 2020 MY 2025

Car 152,137 195,264 19 7

, 578 207,922 Trucks 179,954 225,865 23 1

, 856 24 4

, 026

E1.6 VMT Rebound

The VMT rebound effect refers to the fraction of fuel savings expected to result from an increase in vehicle fuel economy that is offset by additional vehicle use. The increase in vehicle use that stems from improved fuel economy occurs because vehicle owners respond to the resulting reducti on in vehicle fuel consumption and operating costs by driving more.

The magnitude of the rebound effect is one of the determinant s of the actual fuel savings that are likely to result from adopting stricter fuel economy or emissions standards, and thus is an important parameter affecting the evaluation of potential standards for future model years. It can be measured directly by estimating the elasticity of vehicle use with respect to fuel economy itself, or indirectly by the elasticity of vehicle use w ith respect to fuel cost per mile driven. J When expressed as a positive percentage, either of these parameters gives the fraction of fuel savings that would otherwise result from adopting stricter standards, but is offset by the increase in fuel consumption that results when vehicles with increas ed fuel economy are driven more.

The fuel economy rebound effect for light

- duty vehicles has been the subject of a large number of studies since the early 1980s. Although they have reported a wide range of estimates of its exact magnitude, these studies generally conclude that a significant rebound effect occurs when vehicle fuel efficiency improves. K The most common approach to

J F uel F uel cost per mile is equal to the price of fuel in dollars per unit divided by fuel economy in miles per unitunit , so this figure declines when a vehicle’s fuel economy increases.

K Some studies estimate that the long

- run rebound effect is significantly larger than the immediate response to increased fuel efficiency. Although their estimates of the adjustment period required for the rebound effect toAppendix E

E

- 12

estimating its magnitude has been to analyze household survey data on vehicle use, fuel consumption, fuel prices (often obtaine d from external sources), and other determinants of household travel demand to isolate the response of vehicle use to higher fuel economy. Other studies have relied on econometric analysis of annual U.S. data on vehicle use, fuel economy, fuel prices, and other variables to identify the response of total or average vehicle use to changes in fleet

- wide average fuel economy and its effect of fuel cost per mile driven. Two recent studies analyzed yearly variation in vehicle ownership and use, fuel prices, an d fuel economy among individual states over an extended time period in order to measure the response of vehicle use to changing fuel economy. L

Chapter Four of the Joint Technical Support Document to the recent MY s 2012

- 2016 final rule surveys these previo us studies, summarizes recent work on the rebound effect, and explains the basis for the 10 percent rebound effect EPA and NHTSA are using in the current technical analysis. 7 The use of a 10 percent rebound effect in this analysis reflects an assumption t hat the rebound effect applicable to the MY s 2012

- 2016 vehicles will remain

a pplicable throughout future time periods . The agencies plan to conduct new analysis of the expected rebound effect in this time frame in a future rulemaking.

E1.7 Estimating Emissions and Fuel Savings

A vehicle emission standard would reduce GHG emissions emitted directly from vehicles due to reduced fuel use and decreased leakage from air conditioning systems. In addition to these “downstream” emissions, reducing CO 2 emissions transla tes directly to reductions in the emissions associated with the processes involved in getting petroleum to the pump, including the extraction and transportation of crude oil, and the production and distribution of finished gasoline (termed “upstream” emiss ions). The agencies quantified these impacts using the inputs discussed in this section.

Table E1. 7

- 1 Processes Considered

PROCESS UPSTREAM / DOWNSTREA M Crude Oil Extraction Upstream Crude Oil Transport Upstream Oil Refining Upstream Fuel Transport and Distribution Upstream Fuel Tailpipe Emissions Downstream Air Conditioning System Leakage Downstream

reach its long

- run magnitude var y, this long

- run effect is most appropriate for evaluating the fuel savings and emissions reductions resulting from stricter standards that would apply to future model years.
L In effect, these studies treat U.S. states as a data “panel” by applying appro priate estimation procedures to data consisting of each year’s average values of these variables for the separate states.2017

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- 13 1.7.1 Estimating reductions in GHG emissions from vehicle use (downstream)

For the analysis documented in today’s Technical Assessment, the agencies used the OMEGA model to directly calculate CO 2 emissions based on g/mile rates. These CO 2 emissions were convert ed to gallons of fuel under the assumption that approximately the entire carbon content of liquid fu el is converted to CO 2 emissions during the combustion process. The weighted average CO 2 content of gasoline is estimated to be 8,887 grams per gallon, while that of diesel fuel is estimated to be approximately 10,200 grams per gallon. For details, please see EPA’s RIA and NHTSA’s RIA from the recent MY 2012

- 2016 Final Rule

. EPA estimated the increases in emissions of methane (CH 4 ) and nitrous oxide (N 2 O) due to increased vehicle use (“rebound driving”) by multiplying the increase in total miles driven by c ars and light trucks of each model year and age by emission rates per vehicle

- mile for these GHGs. These emission rates, which differ between cars and light trucks as well as between gasoline and diesel vehicles, were estimated by EPA using its Motor Vehic le Emission Simulator ( MOVES 2010 ) model

. The MOVES model assumes that the per

- mile
rates at w hich cars and light trucks emit these GHGs are determined by the efficiency of fuel combustion during engine operation and chemical reactions that occur during catalytic after

treatment of engine exhaust, and are thus independent of vehicles’ fuel consumption rates. Thus MOVES emission factors for these GHGs are assumed to be unaffected by changes in energy consumption. The CH 4 and N 2 O emission factors are the sa me as those used in the MY 2012

- 2016 Final Rule. The full derivation of these factors is available in Chapter 4 of the related Joint Technical Support Document.

The emission factors used for HFC leakage emissions are discussed in Appendix D to this report

.

E1.8 Upstream Emissions

In this analysis, we calculated upstream emission impacts for the greenhouse gases CH 4 , N 2 O, and CO 2 from both gasoline and electricity production. The upstream gasoline emission factor, expressed in the form of gram/gallon produced, is taken directly from the analysis supporting the MY s 2012

- 2016 f inal r ule. EPA derived the upstream gasoline emission factor from the Department of Energy’s GREET mod el, which provides separate estimates of air pollutant emissions that occur in four phases of fuel production and distribution: crude oil extraction, crude oil transportation and storage, fuel refining, and fuel distribution and storage. EPA modified the GREET model to change certain assumptions about emissions during crude petroleum extraction and transportation, as well as to update its emission rates to reflect adopted and pending EPA emission standards. The agency converted these emission rates from the mass per fuel energy content basis on which GREET reports them to mass per gallon of fuel supplied using the estimates of fuel energy content reported by GREET. Full details of this analysis are described in the MY s 2012

- 2016 rulemaking docket memo “C alculation of Upstream Emissions for the GHG Vehicle Rule.” The upstream gasoline emission factor does not change over time.Appendix E

E

- 14 Table E1.8

- 1 Gasoline Upstream Emission Factors

POLLUTANT GASOLINE ( g/gallon ) CO 2 2,161 CH 4 12.25 N 2 O 0.03 CO 2 eq 2477

In the MY 2012

- 2016 Final Rule analysis, we noted that there are many issues involved with projecting the electricity upstream GHG emissions

. Relevant i ssues associated with future EV and PHEV use include , but are not limited to, average versus marginal power generation, daytime versus nighttime vehicle charging, geographical differences, and changes in future electricity feedstocks.

For the present report, we rely upon the reference case projections produced by t he EPA Office of Atmospheric Programs for an analysis of the American Clean Energy and Security Act of 2009 (H.R. 2454)

. 8 This scenario assumes no new power sector regulations, but does assume construction of new plants to replace older retired plants. This results in a slight decrease (~10% compared to 2005) in the emission rate per kWh electricity produced, as newer plants tend to emit less than the plants which they have replaced. The H.R 2454 base case analysis indicates that 4,395 MWh of net genera tion will be produced in 2025, with 2462 million metric tons of CO 2 emissions resulting. This results in an emission factor of 555 grams CO 2 per kWh. Based on eGrid2005 9 , we estimate that approximately 0.01 grams of CH 4 and 0.01 grams of N 2 O are emitted per kilowatt hour. We assume that electricity emission factors do not change after 2025.

The upstream emission factor for electricity was adjusted upwards by six percent in order to properly capture the feedstock gathering that occurs upstr eam of the powerplant. M Feedstock gathering includes the gathering, transporting, and preparing fuel for electricity generation. This adjustment factor is consistent with those discussed in the MY 2012

- 2016 Final Rule. 10

It is important to carefully outl ine the frame of reference for electricity emission factors. For calculations of GHG emissions from electricity generation, the total energy consumed from the battery is divided by 0.9 to account for charging losses, and by 0.93 to account for losses duri ng transmission. The upstream emission factor is applied to total electricity production, rather than simply power consumed at the wheel. N O

M The factor of 1.06 to account for GHG emissions associated with feedstock extraction, transportation, and processing is based on Ar gonne National Laboratory’s The Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) Model, Version 1.8c.0, available at http://www.transportation.anl.gov/modeling_simulation/GREET/). EPA Docket EPA

- HQ

- OAR

- 2009

- 0472.
N By contra st, consumer electricity costs would not include the power lost during transmission. While consumers indirectly pay for this lost power through higher rates, this power does not appear on their electric
meter.2017

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- 15 POLLUTANT CY 2025

ELECTRICITY ( g/kWh ) CO 2 555 CH 4 0.01 N 2 O 0.01 CO 2 eq 558 CO2eq adjusted for feedstock gathering 591

E1.9 Global Warming Potentials

Increases in emissions of non

- CO 2 GHGs are converted to equivalent increases in CO 2 emissions using estimates of the Global Warming Potential (GWP) of hydrofluorocarbon 134a (HFC134a), methane and nitrous oxide. These GWPs are one way of accounting for the higher radiative forcing capacity and differing lifetimes of methane and nitrous oxide when they are released into the earth’s atmosphere, measured relative to that of CO 2
. Because these gases differ in atmosphe ric lifetimes, their relative damages are not constant over time. Impacts other than temperature change also vary across gases in ways that are not captured by GWP. For instance, CO 2 emissions, unlike methane and other greenhouse gases, contribute to

ocea n acidification. Methane contributes to health and ecosystem effects arising from increases in tropospheric ozone, while damages from methane emissions are not offset by the positive effect of CO2 fertilization. Noting these caveats, the CO 2 equivalents o f increases in emissions of these gases are then added to the increases in emissions of CO 2 to summarize the effect of the total increase in CO 2 - equivalent GHG emissions from vehicle use.

As in the final rule , the GWP values from the Intergovernmental Pan el on Climate Change Annual Report 4 are used. These are 1430 for HFC 134a , 298 for N 2 O, and 25 for CH 4
. 11

, P

O By contrast, consumer electricity costs w ould not include the power lost during transmission. While consumers indirectly pay for this lost power through higher rates, this power does not appear on their electric
meter.
P The global warming potentials (GWP) used in this rule are consistent with Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). Due to international agreement, the IPCC Second Assessment Report (SAR) GWP values are used in the official U.S. greenhouse gas inventory submission to the climate change framework.Appendix E

E

- 16 Appendix E References

1 EPA, Fuel Economy Labeling of Motor Vehicles: Revisions To Improve Calculation of Fuel Economy Estimates; Final Rule, 40 CFR Parts 86 and 600, Federal Register, Decembe r 27, 2006, pp. 77872

- 77969, http://www.epa.gov/fedrgstr/EPA

- AIR/2006/December/Day

- 27/a9749.pdf

.

2 EPA, Final Technical Support Document: Fuel Economy Labeling of Motor Vehi cle Revisions to Improve Calculation of Fuel Economy Estimates , Office of Transportation and Air Quality EPA420

- R

- 06

- 017 December 2006, Chapter II, http://www.epa.gov/fueleconomy/420r06017.pdf

.

3 EPA, Fuel Economy Labeling of Motor Vehicles: Revisions To Improve Calculation of Fuel Economy Estimates; Final Rule, 40 CFR Parts 86 and 600, Federal Register, December 27, 2006, pp. 77872

- 77969, http://www.epa.gov/fedrgstr/EPA

- AIR/2006/December/Day

- 27/a9749.pdf

.

4 OMB Circular A

- 4, September 17, 2003. http://www.whitehouse.gov/omb/assets/omb/circu lars/a004/a

- 4.pdf

5 Lu, S., NHTSA, Regulatory Analysis and Evaluation Division, “Vehicle Survivability and Travel Mileage Schedules,” DOT HS 809 952, 8

- 11 (January 2006). Available at http://www

- nrd.nhtsa.dot.gov/pdf/nrd

30/NCSA/Rpts/2006/809952.pdf (last accessed Feb. 15, 2010).

6 FHWA, Highway Statistics, Summary to 1995, Table vm201at http://www.fhwa.dot.gov /ohim/summary95/vm201a.xlw

, and annual editions 1996

- 2005, Table VM

- 1 at http://www.fhwa.dot.gov/policy/ohpi/hss/hsspubs.htm (last accessed Feb. 15, 2010).

7 Sorrell, S. and J. Dimitropoulos, 2007. “UKERC Review of Evidence for the Rebound Effect, Technical Report 2: Econometric Studies”, UKERC/WP/TPA/2007/010, UK Energy Research Centre, London, October and Greening, L.A., D.L. Greene and C. Difiglio, 2000. “E nergy Efficiency and Consumption

– The Rebound Effect

– A Survey”, Energy Policy, vol. 28, pp. 389

- 401.

8 EPA Office of Atmostpheric Programs. Analysis of HR2454. http://www.epa.gov/climatechange/economics/economicanalyses.html

9 U.S. EPA. 2009. eGrid200 7 dataset. http://www.epa.gov/cleanenergy/energyresources/

egrid/index.html. Accessed February 3, 2010. The Emissions & Generation Resource Integrated Database (eGRID) is a comprehensive inventory of environmental attributes of electric power systems. The preeminent source of air emissions data for the electric power sector, eGRID is based on available plant

- specific data for all U.S. electricity generating plants that provide power to the electric grid and report data to the U.S. government.

10 MY 2012

- 201 6 Final Rule, Section III.2.C

11 EPA. Final Rulemaking to Establish Light

- Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average Fuel Economy Standards. Joint Technical Support Document. Chapter 4. EPA

- 420

- R

- 10

- 901 http://www.epa.gov/otaq/climate/regulations/420r10901.pdf . Original data found in Intergovernmental Panel on Climate Change. Chapter 2. Changes in Atmospheric Constituents and in Radiative Forcing. September 2007. http://www.ipcc.ch/pdf/assessmentreport/ ar4/wg1/ar4

- wg1

- chapter2.pdf. Docket ID: EPA

- HQ

- OAR

- 2009

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- 1 

## F1 Appendix F : EPA Documentation of OMEGA model Analysis

F1.1 Overview of OMEGA

This Appendix provides the methodology underlying the technical assessment of the future vehicle scenarios presented in Chapter 6. As in the analysis of the MY 2012

- 2016 rule making , e valuating the feasibility of these scenarios included identifying potentially available technologies and assessing their effectiveness, cost, and impact on relevant aspects of vehicle performance and utility. The wide number of technologies which are av ailable and likely to be used in combination required a method to account for their combined cost and effectiveness. As described in Chapter 6, this included developing three distinct technology pathways which emphasized one or the other of the more advan ced technologies, such as hybrids, advanced gasoline engine, plug

- ins and battery EVs.

Applying these technologies efficiently to the wide range of vehicles produced by various manufacturers is a challenging task. In order to assist in this task, EPA ha s developed a computerized model called the Optimization Model for reducing Emissions of Greenhouse gases from Automobiles (OMEGA). Broadly, the model starts with a description of the future vehicle fleet, including manufacturer, sales, base CO 2 emissions, footprint and the extent to which emission control technologies are already employed. For the purpose of this Technical Assessment Report analysis, 6 3 generic vehicle platforms

— were used to capture i mportant differences in engine design , vehicle design and vehicle utility

. The model i s then provided with a list of technologies which are applicable to various types of vehicles, along with their cost and effectiveness and the maximum percentage of vehicle sales which can receive each technology. This list varies slightly depending on whether model year 2020 or 2025 standards are being evaluated and on the specific technology pathway being evaluated. The model combines this information with economic parameters, such as fuel prices and a discount rate, to p roject how manufacturers could apply available technology in order to meet specified levels of emission control. For th is Technical Assessment Report , as all vehicle sales have been combined into a single manufacturer, the model indicates how the industry when complying as a single manufacturer might use technology to reduce GHG emissions. The result ing output is a description of which technologies are added to each vehicle platform, along with the accompanying cost.

OMEGA includes several components, i ncluding a number of pre

- processors that assist users in prepar ing a baseline vehicle forecast, 1 creat ing and rank ing technology packages, 2 and calculat ing the degree to which technology is present on baseline vehicles. The OMEGA core model assembles this information and produces estimates of increases in vehicle cost and CO 2 reduction. Based on t he OMEGA core model output, the technology penetration of th e new vehicle mix and the scenario impacts (fuel savings, emission impacts, and other monetized benefits) are calculated by post

- processors. The pre

- and post

- processors are Microsoft Excel spreadsheets and visual basic programs , while the OMEGA core mod el is an executable program written in the C# language. The files used in this analysis, as well as the current version of OMEGA, are available in the TAR docket.Appendix F

F

- 2 Figure F 1.1

- 1 : Information Flow in the OM EGA Model

A detailed description of the OMEGA model, as well as the general modeling methodology is provided in the MY 2012

- 2016 rule preamble Section III.D. Consequently, the interested reader may find additional depth there, 3 or in the OMEGA user guide on the EPA website. 4 The remainder of this appendix assumes a basic knowledge of OMEGA’s operation, and focuses on the particular data sources and methodologies used in the scenario analysis described in Chapter 6

.

F1.2 Summary of Inputs

The inputs under lying the OMEGA analysis have significant impacts on the results

, and are described in detail elsewhere in this Assessment Report , as follows

. T he fleet projection used for this analy sis is described in Appendix A

. The vehicle technology packages are desc ribed in Chapter 3 and Appendix B. The inputs relating to ai r conditioning controls are outlined in A ppendix D. The other economic and environmental outputs are described in Appendix E. The detailed description of analytic scenarios, including the
stan dards modeled and the reasoning behind a single fleet analysis, is available in Chapter 6. Generally, the table of contents to this technical assessment is a useful guide to additional detail.

F1.3 Configuration of the Scenario File

The scenario file in OMEG A contains a directory of data input files

, a group of economic parameters
, and a set of CO 2 g/mile targets. For the Technical Assessment Report analysis , OMEGA was configured so that each technical pathway /model year combination was a single scenario file containing six runs. Four runs corresponding to each of the four emission control scenarios ( i.e

. , 3% per year, 4% per year, etc.) were included. Also included were a diagnostic run requir ing maximum application of technology, as well the reference case scenario of MY 2016 GHG standards from the recent MY 2012

- 2016 f inal r ule. As a2017

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- 3 result, six scenario files were created (2 MYs x 3 technical pathways), and each scenario file contained parameters for six OMEGA runs.

The emiss ion control scenarios were each configured with a flat standard corresponding to the appropriate stringency . No limit s were placed on credit transfer s between the car and truck fleets. As in the MY 2012

- 2016 f inal r ule analysis, EPA accounted for the emi ssion reductions and technology costs due to air conditioning control s outside of the OMEGA model. In the MY 202 5 timeframe, a ir conditioning remains a highly cost

effective technology to control GHG emissions, and consequently, EPA projects that the enti re market will convert to low leakage, high efficiency systems. In the time frame of MY 2020 and later, these emission reductions were assigned a statutory value of 20.6 grams in the reference scenario 5 and 15.3 grams in the control scenarios. 6 An example of the adjustments is shown in Table F 1.3

- 1

. The MY 2016 footprint curves and the flat standards were each adjusted by t he maximum potential AC credits to produce the credit adjusted targets. The agencies note, as discussed in Chapter 6 above, that the upcoming federal rulemaking analysis will consider fuel economy and emission control scenarios defined in terms of attribute

- based standards, but we belie ve the scenarios considered here are meaningful for purposes of this
assessment.

Table F 1.3

- 1 : Adjustment of Standards for Air Conditioning Credits

Scenario Sales

- Weighted

MY 2025 Target Projected AC

Credits 1 Sales

- Weighted MY

2025 Credit Adjusted Target Reference 248 .1 20.6 26 8.7 3% 190 .1 15.3 205 .4 4% 173 .1 15.3 188 .4 5% 15 7.6 15.3 173 .9 6% 143 .2 15.3 158 .5Appendix F

F

- 4

A further adjustment was made with respect to the credit adjusted targets listed above. The scenarios described in this document are defined by a sales weighted average of car and truck CO 2 emissions. When credit transfer is allowed between cars and trucks, OMEGA weight s the CO 2 average by both sales and vehicle miles traveled (VMT)

. A Light tru cks generally are driven more than cars, so the sales and VMT weighted CO2 emission average tends to be slightly lower than the sales

- weighted average. To account for this difference , the diagnosti c run was used to produce VMT and sales weighted targets t hat correspond ed to the sales weighted targets listed above. These calibrated targets can be seen in the scenario file s available in the TAR docket

.

We also update d the VMT ratios used in car/truck credit transfer to the appropriate MY lifetime values dis cussed in Appendix E

.

F1.4 Configuration of the Technology File

The technology input file defines the technology packages which the model can add to the vehicle fleet. A separate technology file was developed for each of the six technology pathway/model year combinations considered in this Technical Assessment Report

. While the individual technology costs were the same between technology pathways, they differed between MY 2020 and MY 2025 due to the learning effects discussed in the Appendix 3 and the MY 2012

- 2016 Final Rule Section II.E

. Due to the differ ent limits on maximum penetration s of severa l key technolog ies (discussed in Chapter 6), e ach of the technology pathways also required a separate t echnology f ile and model run. The change in those maximum penetration rates also slightly affected the set of most cost effective technolog y packages se lected for inclusion in the OMEGA model runs

. The processes to build and rank technology packages for the technology file are described in the Chapter 3 and Appendix B of this report. This section describes the configuration of the OMEGA Technology input file which occurs after the ranked packages are developed

.

F1.4.1 Multiple Fuel Tracking

OMEGA 1.0.2, which was used during the MY 2012

- 2016 rule analysis, tracked CO 2 emissions at the vehicle platform level. For the present analysis, an upgrade was made to the OMEGA model to track CO 2 emissions by fuel within each vehicle platform. As a result, a vehicle platform can be composed of sub

- vehicles, e ach with its own fuel, CO 2 emission rate and electricity consumption rate

. To facilitat e this tracking, e very technology is en coded with its operating fuel, as well as the fuel of the vehicles to which i t applies. In combination with technology specific caps, B this allows a vehicle platform to be split so that subsequent technologies can be appl ied to the specific subset s of the vehicle ( Table F 1.4

- 1 ). Thus, for example, a certain fraction of a vehicle ’s sales can be equipped with a diesel engine. Subs equent diesel

- based technologies can then be applied more simply and directly to this

A This practice is consistent with EPA’s MY 2012

- 2016 regulations allowing VMT weighted credit transfer between car and truck fleets

. B ―Cap‖ is a shorthand term for the maximum penetration rates for certain technologies which define the various technology paths.2017

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- 5 subset of sales. The model keeps track of the sales and CO 2 emission rate s of both the gasoline and diesel version s of the vehicle.

In the example below, Technology Package 3 is applied to the gasoline fuel vehicle created by the application of Technology Package 1. Technology Package 4 is applied to the diesel fuel vehicle created by the application of Technology Package 2.

Table F 1.4

- 1 : Example of Multiple Fuel Technology File

Tech Package Name Cap 1 Fuel of the Technology Fuel to which the

Technology Applies 1 GDI Gasoline Engine 100% Gasoline Gasoline 2 Diesel Engine 15% Diesel Gasoline 3 Gasoline Hybrid 100% Gasoline Gasoline 4 Improved Diesel 100% Diesel Diesel
1 Please note that OMEGA technology caps are relative to the population on that fuel, so a 100% cap on technology package four indicates that it applies to 100% of the 15% of vehicles which were conve rted to diesel in step

In the current TAR analysis, this model feature simplified the ability to apply several types of electric vehicle and plug

- in electric vehicle technology packages to the same baseline vehicle. In addition, we found it useful when a pplying certain advanced gasoline technology packages which had caps of less than 100%. For example, most of the technology paths limit the use of advanced (e.g., EGR

- boosted) gasoline engine technologies to less than 100%. In most cases, further technol ogy packages can be applied to both the vehicles which received this advanced gasoline technology and those that did not. By effectively treating ―advanced gasoline engines‖ as including a change in fuels, we were able to simplify the addition of subseque nt technologies to both the subset of vehicle sales with this technology and that without it. This could have been accomplished without taking advantage of the OMEGA model’s new fuel tracking capability, but the estimation of the cost and effectiveness of the subsequent technology packages would have had to consider the fact that they were being applied to a subset of the vehicle’s sales which did not have the average attributes of that vehicle at that stage of technology addition.

For example, if EGR bo ost technology is added to 50% of the sales of those vehicles operating on gasoline, it may be possible to hybridize both the vehicles with and without the EGR boost technology, with differing costs and effectiveness. It is possible to determine the

overa ll impact of hybridizing the non

- EGR vehicles first and then the EGR

- boosted vehicles and developing the appropriate OMEGA model inputs which accomplish both of these steps of technology addition . However, since we were not using all of the fuel types cur rently tracked in the OMEGA model (e.g. E10), it was easier to separate the EGR

- boosted vehicles from those without this technology by changing the former vehicles’ fuel to ― E10 ‖

. We simply made the fuel properties of E10 exactly the same as those for gas oline. Then for example, the incremental effect of hybridizing the non

- EGR boosted vehicles could be used directly in the model without the need to sales weight th is impact by including the fact that the emissions of the non

- EGR vehicles were not changing

.Appendix F

F

- 6

To further illustrate this issue, c onsider the case of Vehicle A, a gasoline vehicle with CO 2 emissions of 300 g/mile. In this example scenario, diesel packages are limited to 50% of the fleet because of concerns relative to production capacity

. C In this case, two sequential diesel packages should be applied to the same 50% subset of the vehicle ( Table F 1.4

- 2 ). As can be seen in this table, OMEGA 1.3 now mo re accurately attributes the reductions to the appropriate subset within the vehicle platform.

Table F 1.4

- 2 : Tracking CO 2 Step Package Fuel Maximum

Penetration Limit Reduction OMEGA 1.0.2

Applied to average vehicle. OMEGA 1.3

Applied to a specific fuel within a platform. CO 2 Avg CO 2

Avg CO 2 Gas CO 2 Diesel 300 300 300 N/A 1 Diesel 50% 10% 285 285 300 270 2 Diesel 50%/100% 10% 270.75 27 1 .5 300 24 3

1 The maximum penetration limit in the second step applies to 50% of the total vehicles (OMEGA 1.0.2) or 100% of the diesel vehicles (OMEGA 1.3)
In the analysis presented in this report, we encode limited technologies to different fuels so that the appropriate reductions are taken. As an example, plug

- in hybrids are coded to diesel fuel. The fuels input file was modified so that the appropriate gasoline fuel properties are attributed to ―diesel‖ fuel

.

F1.4.2 Tracking of Electricity

OMEGA 1.3 also tracks electrical consumption in kWh per mile. Each technology
pa ckage is now associated with an ―electricity conversion percentage‖ which refers to the increase in the energy consumed by the electric drivetrain relative to reduction in the consumption of energy from liquid fuel. Electricity is a highly refined form of energy which can be used quite efficiently to create kinetic energy. Thus, e lectric motors are much more efficient than liquid fuel eng ines. Consequently, the electric consumption percentage input in in the Technology File for plug

- in vehicles is genera lly well below than 100%. It may be possible that this percentage could exceed 100% under certain circumstances, for example when one type of plug

- in vehicle is being converted into another plug

- in vehicle and electricity consumption per mile is increasin g due to larger and heavier batteries, etc. However, that was not the case for any of the technologies evaluated in this analysis.

C Please note, this is just an e xample, and has no implications relative to actual maximum penetration rates for diesel vehicles.2017

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- 7 F1.5 Configuration of the Market File

F1.5.1 Creating the Generic Vehicles

As discussed in Section F1.4 above, vehicle manufacturers typically develop many different models by basing them on a smaller number of vehicle platforms. The platform typically consists of a common set of vehicle archi tecture and structural components. This allows for efficient use of design and manufacturing resources. In the MY 2012

- 2016 Final Rule, EPA created over 200 vehicle platforms which were used to capture the important differences in vehicle and engine desig n and utility of future vehicle sales of roughly 16 million units in the 2016 timeframe. For the current analysis, we are not differentiating between manufacturers, and consequently require fewer vehicle platforms for the analysis. The approximately six ty vehicle platforms are a result of mapping the 1130 vehicle fleet into the 19 engine based vehicle types ( Table F 1.5

- 1 ) and the 10 body size and str ucture based utility classes ( Table F 1.5

- 2 ). As not all vehicle types match to all utility types, the number of generic vehicles is less than the mul tiplicative maximum of the two tables.

Table F 1.5

- 1 : Vehicle Types in the TAR Analysis Vehicle Type # Name Cam Engine 1 Subcompact Car DOHC I4 2 Compact Car I4 DOHC I4 3 Midsize Car/Small MPV (unibody) DOHC I4 4 Compact Car/Small MPV (unibody) DOHC V6 5 Midsize/Large Car DOHC V6 6 Midsize Car/Large Car DOHC V8 7 Mid

- sized MPV (unibody)/Small Truck DOHC I4 8 Midsize MPV (unibody)/Small Truck SOHC V6 9 Large MPV (unibody) SOHC V8 10 Large MPV (unibody) SOHC V8 11 Large Truck (+ Van) SOHC V6 12 Large Truck + Large MPV OHV V6 13 Large Truck (+ Van) OHV V8 14 Large Truck (+Van) SOHC3V V8 15 Large Car OHV V8 16 Large MPV (unibody) DOHC V6 17 Large MPV (unibody) DOHC V8 18 Large Truck (+ Van) DOHC V6 19 Large Truck (+ Van) DOHC V8

Table F 1.5

- 2 : Vehicle Types in the Technical Assessment Analysis

Utility Class # Utility Class Vehicle Use 1 Footprint Criteria Structure Criteria

1 Subcompact Auto Car Footprint <43

-- 2 Compact Auto Car 43<=Footprint<46

-- 3 Mid Size Auto Car 46<=Footprint<53

--Appendix F

F

- 8

4 Large Auto Car 56<=Footprint

-- 5 Small SUV SUV 43<=Footprint<46

-- 6 Large SUV SUV 46<=Footprint

-- 7 Small Pickup Pickup Footprint < 50

-- 8 Large Pickup Pickup 50<=Footprint

-- 9 Cargo Van Van

-- Ladder Frame 10 Minivan Van

-- Unibody
1. Vehicle use type is based upon analysis of EPA certification data.

F1.5.2 Accounting for Technology already on the V ehicles

T he market data input file utilized by OMEGA, which characterizes the vehicle fleet, is designed to account for the fact that the 2008 model year vehicles which comprise our baseline fleet may already be equipped with one or more of the technologies availab le in general to reduce CO2 emissions. As described in Appendix B, EPA decided to apply technologies in packages , as opposed to one at a time. However, 2008 vehicles we re equipped with a wide range of technology combinations, many of which cut across the packages. Thus, EPA developed a method to account for the presence of the combinations of applied technologies in terms of their proportion of the EPA package s described in Chapter 3. This analysis can be broken down into four steps

The first step in t he updated process is to breakdown the available GHG control technologies into five groups: 1) engine

- related, 2) transmission

- related, 3) hybridization, 4) weight reduction and 5) other. Within each group we gave each individual technology a ranking whic h generally followed the degree of complexity, cost and effectiveness of the technologies within each group. More specifically, the ranking is based on the premise that a technology on a 2008 baseline vehicle with a lower ranking would be replaced by one with a higher ranking which was contained in one of the technology packages which we included in our OMEGA modeling. The corollary of this premise is that a technology on a 2008 baseline vehicle with a higher ranking would be not be replaced by one with a n equal or lower ranking which was contained in one of the technology packages which we chose to include in our OMEGA modeling. This ranking scheme can be seen in the TEB/CEB calc ulation macro, available in the docket

. In the second step of the process, w e used these rankings to estimate the complete list of technologies which would be present on each baseline vehicle after the application of each technology package. We then used the EPA lumped parameter model to estimate the total percentage CO2 emission reduction associated with the technology present on the baseline vehicle (termed package 0), as well as the total percentage reduction after application of each package. This process was repeated to determine the total cost of all of the technology
prese nt on the baseline vehicle and after the application of each applicable technology package.

The third step in this process is to determine the degree of each technology package’s incremental effectiveness and incremental cost is affected by the technolog y already present on the baseline vehicle. The degree to which a technology package’s incremental effectiveness is reduced by technology already present on the baseline vehicle is termed the2017

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- 9 technology effectiveness basis, or TEB, in the OMEGA model. The value of each vehicle’s TEB for each applicable technology package is determined as follows:

Where
TotalEffect v,i = Total effectiveness of all of the technologies present on the baseline vehicle after

application of technology package i TotalEffect v,i

- 1 = Total effectiveness of all of the technologies present on the baseline vehicle after

application of technology package i

- 1 TotalEffect p,i = Total effectiveness of all of the technologies included in technology package i Tot alEffect p,i

- 1 = Total effectiveness of all of the technologies included in technology package i

- 1
Equation 1.5

- 1

– TEB calculation

The degree to which a technology package’s incremental cost is reduced by technology already present on the baseline vehicle is termed the cost effectiveness basis, or CEB, in the OMEGA model. The value of each vehicle’s CEB for each applicable technology package is determined as follows:

CEB i = 1

– (TotalCost v,i – TotalCos t v,i

- 1 ) / (TotalCost p,i – TotalCost p,i

- 1 )

Where
TotalCost v = total cost of all of the technology present on the vehicle after addition

of package i or i

- 1 to baseline vehicle v TotalCost p = total cost of all of the technology included in package i or i

- 1 i = the technology package being evaluated i

- 1 = the previous technology package
Equation 1.5

- 2

– CEB calculation

The values of CEB and TEB are capped at 1.0 or less, since a vehicle cannot have

more than the entire package already present on it. In other words, the addition of a technology package cannot increase emissions nor reduce costs. (A value of 1.0 causes the OMEGA model to not change either the cost or CO2 emissions of a vehicle when that
t echnology package is added. ) The value of a specific TEB or CEB can be negative, however. This implies that the incremental effectiveness or the incremental cost of adding a package can be greater than that when adding the packages in sequence to a vehic le with no baseline technology.

An example of this is a baseline vehicle with a 6 speed manual transmission. All of our technology package effectiveness and cost estimates are estimated for specified baseline vehicles, all of which have 4 speed automati c transmissions. Our technology packages improve this transmission, sometimes to a 6 speed automatic transmission and then a dual clutch transmission and sometimes directly to a dual clutch transmission. SubsequentAppendix F

F

- 10

packages may then strongly hybridize th e vehicle. If a baseline vehicle has a 6 speed manual transmission, this transmission is unaffected by the technology packages which include either a 6 speed automatic transmission or a dual clutch transmission, since the manual transmission is both cheap er and/or more efficient than these other transmissions. However, when the vehicle is hybridized, this manual transmission is replaced. The incremental cost of changing this vehicle to a power

- split hybrid design, for example, is greater than that for a vehicle with a dual clutch transmission, since the credit for removing the manual transmission is less than that for the dual clutch transmission. The negative CEB causes the OMEGA model to apply a cost for this power

- split package which is slightly highe r than that for the typical baseline vehicle.

T he fourth step is to combine the fractions of the cost and effectiveness of each technology package already present on the individual 2008 vehicles models for each vehicle type . For cost, percentages of eac h package already present are combined using a simple sales

- weighting procedure, since the cost of each package is the same for each vehicle in a vehicle type . For effectiveness, the individual percentages are combined by weighting them by both sales and base CO 2 emission level. This appropriately weights vehicle models with either higher sales or CO 2 emissions within a vehicle type . Once again, this process prevents the model from adding technology which is already present on vehicles, and thus ensures that the model does not double count technology effectiveness and cost associa ted with complying with the reference standards or the CO 2 control scenarios

. For this analysis, we automated the process through a visual basic macro that both operates the lu mped parameter model and calculates the TEBs and CEBs. This macro

enabled excel file is available in the docket

.

F1.6 Post

- processing OMEGA

F1.6.1 A/C Credits

As noted above, A/C credits were simply subtracted off the OMEGA results for both the reference and control cases. A/C system costs were added into both cases. As a result, the delta between reference and control cases, both in terms of costs and environmental impact

, did not change.

F1.6.2 Calculating Technology Penetrations

Technology penetrations were calculated using the new ―techpacksales‖ output file of the OMEGA model. This output provides, for each of the approximately 60 vehicle platforms, the distribution of sales among the tech packs. In a post

- processing step, t his distribution is applied back to the 1 130 individual vehicles of the disaggregate baseline fleet projection so that we have the tech pack distribution of each vehicle. As discussed in the description of TEB/CEB calculations, we have already produced a file which contains the specific technolo gies on each vehicles with every possible technology package. By applying the technology pack distributions from the 60 vehicle platforms back against the 1130 vehicles in dissagregated fleet, we are able to determine the specific technologies on each veh icle in each scenario and tech pathway. As an example, this file would show what technologies are2017

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- 11 actually on a Ford F150 with technology package 1, 2, 3 etc. This file is combined with OMEGA’s tech nology pack distribution output to determine the penetr ation of each tracked technology.

F1.6.3 Impacts Calculations

Liquid fuel consumption, electricity consumption and emission impacts were calculated in a modified version of the post

- processor spreadsheet that was used in the MY 2012

- 2016 final rule. This sprea dsheet, available in the downloadable material accompanying this technical assessment report

, is the repository for the inputs discussed in Appendix E . The impacts calculations sequentially calculate light duty vehicle stock, VMT, and impacts for each MY and CY from 2010 through 2050. Outputs are available on either calendar year or model year basis. For this Technical Assessment Report , the VMT algorithm was integrated into the benefits calculations, electricity calculations were added, and the input s and outputs were restructured. Provided the same inputs, the current benefits spreadsheet would still provide the same outputs as the version used in the MY 2012

- 2016 Final Rule.

A detailed discussion of the benefits calculations algorithms is available i n the MY 2012

- 2016 Final Rule RIA chapter 5 and in the OMEGA users guide.

We note that the current analysis did not rely upon many of the outputs of the OMEGA benefits post

- processor. These outputs, such as co

- pollutant impacts, monetized emission impacts , the benefits of additional travel time, and dam ages due to noise, accidents, and congestion, may not produce accurate results in the context of the numerous input changes , and should not be used.Appendix F

F

- 12 Appendix F References

1 Appendix A

2 Appendix B

3 http://www.epa.gov/oms/climate/regulations.htm

4 http://www.epa.gov/oms/climate/models.htm

5 EPA. LD GHG MY 2012

- 2016 Rule, RIA Chapter 2 and 5.

6 Appendix D to this report.2017

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- 1 

## G1 Appendix G : Infrastructure

Appendix G contains a compilation of additional information to support Chapter 4, Infrastructure Assessment. Appendix G contains additional information covering the following topic areas:

DOE

- funded grants for electric drive demonstration and evaluation programs Estimates of costs of charging equipment Battery end of life value Voluntary standards Hydrogen Infrastructure

G1.1 American Recovery and Reinvestment Act: T ransportation Electrification Initiative

Through the American Recovery and Reinvestment Act of 2009 (ARRA), DOE has awarded cost

- shared grants to companies under the Transportation Electrification Initiative to establish development, demonstration, evalu ation, and education projects to accelerate the market introduction and penetration of advanced electric drive vehicles. The component projects of the Transportation Electrification Initiative and other DOE electric

- drive vehicle infrastructure activities are discussed below.

ECOtality North America

ECOtality North America has been awarded a cost

- shared grant of nearly $115 million to support ―The EV Project,‖ to deploy electric

- drive vehicles and charging infrastructure in sixteen major U.S. cities begi nning in 2010. Upon full deployment of vehicles and infrastructure under this project in 2011, approximately 8,500 electric drive vehicles and 14,850 Level 2 charging stations will be in service, providing a rich set of data regarding the operational and charging behavior of electric drive vehicle owners in a variety of markets.

The ECOtality project will install grid

- connected vehicle infrastructure in Phoenix, AZ; Tucson, AZ; San Diego, CA; Los Angeles, CA; Portland, OR; Eugene, OR; Salem, OR; Corvallis, OR; Seattle, WA; Dallas, TX; Fort Worth, TX; Houston, TX; Nashville, TN; Knoxville, TN; Chattanooga, TN; and Washington, DC. Residential Level 2 charging stations will be provided at no cost to purchasers of the Nissan LEAF EV and the Chevrolet Volt Exte nded Range Electric Vehicle (EREV) who subscribe to the program. Additionally, Level 3 DC ―fast‖ chargers will be installed along routes connecting neighboring cities

– such as Nashville/Knoxville/Chattanooga, Phoenix/Tucson, and Seattle/Portland/Eugene

– establishing a network of electric vehicle corridors between electric transportation hubs. More information about The EV Project is available at http://www.theevproject.com.

Coulomb TechnologiesAppendix G

G

- 2

Coulomb Technologies has been awarded a cost

- shared grant o f $15 million to support its ―ChargePoint America‖ project, to deploy electric

- drive vehicles and charging infrastructure in nine major metropolitan areas beginning in 2010. The project will result in the deployment of approximately 5,000 Level 2 charging stations at residential and commercial locations in Bellevue/Redmond, WA; Sacramento, CA; San Jose/San Francisco Bay, CA; Los Angeles, CA; Austin, TX; Detroit, MI; New York, NY; Washington, DC; and Orlando, FL. Residential chargers will be provided to pu rchase r s of the Chevrolet Volt EREV

– in some cases, at no cost

– and will also be deployed in conjunction with electric drive vehicles from Ford and S mart USA. More information about ChargePoint America is available at http://www.chargepointamerica.com.

Navistar

Navistar was awarded a cost

- shared grant of over $39 million to develop and demonstrate a fleet of all

- electric medium

- duty delivery trucks , which the company has named the eStar . These vehicles will be manufactured in Wakarusa, IN, and deployed through various fleet partners nationwide. In total, 950 Class 2c

- 3 electric trucks will be deployed in conjunction with 950 Level 2 charging stations, at locations specified by the respective fleet owners. Data collected from these vehicles and charging stations will provide valuable information regarding the performance and suitability of medium

- duty electric vehicles and the infrastructure required to support them. More information about eStar trucks is available at http://www.estar

- ev.com

.

General Mo tors

General Motors was awarded a cost

- shared grant of over $30 million to develop and deploy a fleet of Chevrolet Volt EREVs, and to gather data on vehicle performance and infrastructure requirements. A fleet of 125 Chevy Volts will be deployed in combin ation with over 650 Level 2 charging stations, through electric utility partners in several diverse geographic locations throughout the U.S. The project will include the installation, demonstration, and testing of charging infrastructure in residential, c ommercial, and public locations. Additionally, a comprehensive set of data will be collected from the vehicles and charging stations from December 2010 through 2012, and will contribute to a more complete understanding of typical vehicle usage and operati onal needs, supporting the next generation of vehicle designs and infrastructure planning. The project will also include an analysis of fast charging requirements and the development and demonstration of smart charging capabilities using General Motors‘ O nStar telematics service.

Smith Electric Vehicles

Smith Electric Vehicles has been awarded a $32 million cost

- shared grant to develop and demonstrate a fleet of all

- electric medium

- duty trucks. Approximately 500 vehicles will be built in Kansas City, MO, and deployed with 500 Level 2 charging stations through fleet partners representing a range of commercial and public

- sector markets in diverse geographic and climatic areas by the end of 2011. In addition, the project will include the collection of real

- w orld performance data using an automatic GPS

- based telemetry system. The Smith Electric Vehicles project, combined with the Navistar project, will provide valuable insight2017

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- 3 into the applicability of electric

- drive powertrains in medium

- duty trucks in a var iety of vocations. More information about Smith Electric Vehicles is available at http://www.smithelectric.com.

South Coast Air Quality Management District

SCAQMD was awarded a cost

- shared grant of over $45 million to develop, demonstrate, and evaluate a fleet of medium

- duty plug

- in hybrid electric trucks and shuttle buses. A total of 378 vehicles will be demonstrated nationwide, in combination with 378 Level 2 charging stations. The majority of the vehicles will be bucket trucks based on the Ford F

- 550 chassis, deployed through electric utility partners, while the shuttle buses, based on the Ford E

- 450, will be deployed via shuttle bus fleet operators. Data collected from the fleet will be analyzed in order to quantify the attributes of PHEV technologie s for Class 4/5 vehicles in terms of emissions, greenhouse gas reductions, and fossil fuel displacement. An additional goal of the project is to develop production ready smart charging capability for commercial applications. More information about the cu rrent status of this program is available at http://www.aqmd.gov/hb/2010/july/100710a.htm

. Chrysler Group LLC

Chrysler has been awarded a $48 million cost

- shared grant to develop and demonstrate 153 plug

- in hybrid electric Dodge Ram pickup trucks combined with Level 2 charging infrastructure. The trucks and charging stations will be deployed through partner fleets in diverse geographies and climates, spanning from North Dakota to Arizona, and from Hawaii to Massachusetts. Full deployment of the vehicles w ill be achieved in early 2011, followed by data collection and vehicle monitoring activities through 2013 in order to prove real

- world product viability and to quantify the benefits to consumers and to the nation. As part of this project Chrysler, with su pport from its project partners, will develop and demonstrate bi

directional charging capability.

Education Grants

Through the Transportation Electrification Initiative , ten grants totaling nearly $40 million were awarded to educational institutions to est ablish programs to train engineers, technicians, and emergency first responders, as well as to inform the general public, in preparation for the transition to vehicles with advanced electric drive technologies. At the university level, graduate and underg raduate engineering degree programs will be created to educate students in technologies related to electric drive vehicles and charging infrastructure. Several community colleges received grants to establish technical training courses and certificate prog rams to train service personnel and automotive technicians to properly service and maintain vehicles with electric drive powertrains. Similarly, electric vehicle safety training programs will be created to train emergency personnel in proper safety protoc ols related to electric vehicles and infrastructure , which will differ from current vehicles and infrastructure with which first responders are already familiar . Furthermore, consumer outreach and K

- 12 educational material s will be created to familiarize the general public with electric

- drive vehicle capabilities and infrastructure utilization. All of these activities will take place through projects supported by Transportation Electrification grants awarded to theAppendix G

G

- 4

University of Michigan, J. Sargeant Reyn olds Community College, West Virginia University/National Alternative Fuels Training Consortium, Michigan Technological University, Missouri University of Science and Technology, Wayne State University, Colorado State University, Purdue University, City Co llege of San Francisco, and the National Fire Protection Association.

G1.2 Charger Cost Estimates

The following list of charger cost estimates details the sources and the respective estimates pulled from each that were used in constructing the charger cost esti mate Table 4.2

- 2, ―Estimated Costs for Charging Stations‖. Here, the estimates are listed by source along with assumptions and context that are relevant to the cost estimate.

Level 1

1. Residential (Morrow, Karner and Francfort, 2008) 1

a. Charge cord + circuit installation, 20A $878
2. Public networked (May and Mattila, 2009) 2

a. 12A stations (Coulomb Technologies) $2500 each + $1000 for ―gateway‖ station
3. Public (May and Mattila, 2009) 3

a. 20 amp/4 vehicle (Shorepower Technologies/SynkroMotive) $2500

- $2900
4. Apartment complex, not networked (5 stations) (Morrow, Karner and Francfort, 2008) 4

a. 5 charge cords $1250
b. 5 20 amp circuits $2221

c. Installed $4165

Level 2, Residential or Fleet Depot

1. Residential, no service panel upgrade (ETEC, 2009) 5

a. 40 amp EVSE $780
b. Installed $227 2
2. Residential (Morrow, Karner and Francfort, 2008) 6

a. EVSE 32 amp $650
b. Charge cord $200

c. 40 amp circuit $1080
d. Installed $2146
3. Residential, no upgrade (May and Mattila, 2009) 7

a. 9

- 25 amp EVSE, output 3.3 kW (Brusa/Metric Mind) $3870

- $6353
4. Residential (Electrification Coalition, 2009) 8

a. No upgrade $500

- $1500
b. With upgrade, ―up to $2500‖)
5. Commercial Fleet (10 stations) (ETEC, 2009) 9

a. Distribution panel $650
b. EVSE 40 amp $780 * 10

c. EVSE Pedestal $450 * 10
d. Installed $31,3752017

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- 5 e. $3138/station
6. Apart ment complex, not networked (5 stations) (Morrow, Karner and Francfort, 2008) 10

a. 5 EVSEs $3250
b. 5 charge cords $1000

c. 5 circuits $2611 including labor costs for circuits and EVSEs
d. Installed $7597 for 5 stations

e. $1520/station

Level 2, Public

7. Public (2 chargers) (ETEC, 2009) 11

a. Distribution sub

- panel $250
b. EVSE 40 amp $780 * 2

c. EVSE Pedestal $450 * 2
d. Installed $12,875

e. $6438/station
8. Public networked (May and Mattila, 2009) 12

a. 32 amp stations (Coulomb Technologies) $3500 each + $1000 for ―gateway‖ station b. 120 amp stations, charges 4 vehicles (EV

- Charge America) $1200

- $1500

c. 16.8 kW smart station (GoSmart Technologies) $2200

- $3800
d. Above apparently are hardware only
9. Public stations (May and Mattila, 2009) 13

a. Pre

- assembled unit, $1400

- $1800/single 24

- 30 amp, $2800/60 amp double (eTec)
10. Public (Electrification Coalition, 2009) 14 : up to $5,000

Level 3 , Public Quick Charge

1. Public Level 3 (2 stations) (ETEC, 2009) 15

a. Distribution sub

- panel $650
b. Fast charger (30 kW) $25,000 * 2

c. Point of sale system $2500
d. I nstalled $64,158
2. Unspecified (Electrification Coalition, 2009) 16 $25,000

- $50,000
3. Nissan 50 kW Quick EV Charger, CHAdeMO standard, manufacturer‘s suggested retail price, not including installation $17,500

– 20,600 A

, 17

4. Confidential submission

, EVSE in high volume, direct manufacturing cost, not including
i nstallation $8,000 B

T he range in the costs for quick

- charge EVSEs reflects a difference between current, relatively low volume public quick

- charge EVSE s and a future EVSE incorporating multiple

A Lower cost is base unit, higher cost reflects options for hot or cold climate operation.
B Confidential information provided to EPA, ARB and NHTSA, August 2010. Manufacturing cost and general description of architecture cleared for release by the original source on September 10, 2010.Appendix G

G

- 6

cha rgers of the same type used for on

- vehicle charging in order to share economies of scale between EVSEs and components sourced in much higher volume for automobile production. This would be expected to provide a significant cost reduction for some of the m ost expensive components within public quick

- charge EVSEs.

G1.3 Battery End

- of

- Life Value Potential

Chapter 4.2.4 discusses issues surrounding the assessment of a secondary use value for EV/PHEV batteries. Work is underway to study this issue, including the ex tent of the market for secondary use batteries and the potential value to the original vehicle purchaser. This section summarizes one such study supported by DOE.

Accelerated development and market penetration of PHEVs and EVs is presently restricted by the high cost of lithium

- ion (Li

- Ion) batteries. In fact, it has been estimated that a ~50% reduction in battery costs is necessary to equalize the current economics of owning PHEVs and conventionally fueled vehicles. 18

One way to address this problem is t o recover a fraction of the battery cost via reuse in other applications after it is retired from service within the vehicle, where it may still have sufficient performance to meet the requirements of other energy storage applications. By extracting additi onal services and revenue from the battery in a post

- vehicle application, the total lifetime value of the battery is increased.

There are several current and emerging applications where the secondary use of PHEV and EV batteries may be beneficial. For example, the use of renewable solar and wind technologies to produce electricity is growing, and their increased market penetration requires energy storage to mitigate the intermittency of wind and solar energy. New trends in utility peak load reduction, e nergy efficiency, and load management also need energy storage. Smart grid, grid stabilization, low

- energy buildings, and utility reliability require energy storage as well. It is reasonable to suggest that some utility applications are capable of support ing 2010‘s new battery prices. 19 20 21 Assuming that battery prices fall faster than the value of these utility applications (not improbable, given the anticipated decline in battery prices and that the increased presence of renewable generation should drive utility application values higher), the same will be true in the 2017

- 2025 time frame.

Thus, substantial markets for used automotive batteries may exist, and given that the allowable battery costs for these applications will exceed new battery prices, battery salvage values must be determin ed relative to competing products rather than application values. Assuming that a primary competitor is new automotive Li

- Ion batteries, salvage values can be computed based upon anticipated future Li

- Ion prices. Additionally, the salvage value must be
gre ater than the ―competing‖ application of leaving the battery in the aging vehicle and accepting its reduced range capability or selling it to someone with reduced range requirements. Under these assumptions, it is reasonable to assume that the future salva ge value of a used PHEV/EV battery will be proportional to the cost of an equally capable new battery, taking into consideration the health of the used battery, the cost of collecting, refurbishing, and certifying the used battery, and a  ̳used‘ product dis count factor. Given efforts to ramp up automotive battery production between 2010 and 2015, it is reasonable to2017

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- 7 assume that such batteries will be a relatively mature product and that the majority of the benefits owed to economies of scale will be achieve d by 2017, leading to the following:

· Battery life will be improved such that 10 years of in

- vehicle life is common and significant health remains in the battery post automotive retirement

· Battery price reduction across the battery life will be relatively small

· Batteries will be treated as a commodity, thus used product discounts will be fairly low

· Recognizing the value of secondary use and leveraging advances in battery health monitoring, automotive batteries will be designed to minimize reconditioning costs

Based on the preceding conditions, one study estimates that net present salvage values for EV/PHEV batteries sold in the 2017

- 2025 time frame are approximately 20% of their ini tial purchase price. 22

G1.4 List of Volunta ry Standards

This list of voluntary standards illustrates the complexity and interrelationships due to the addition of communication to the interface between the vehicle and each major element of the consumer

- vehicle

- grid system. These efforts are to enha nce long

- term success; however, they are not a prerequisite for a successful near

- term market launch. It is worth noting that the SAE J1772 standard is complete, which is a significant development; many others are still under development.

SAE

– The follow ing existing standards were identified in the Phase 1 NIST Framework and Roadmap for Smart Grid Interoperability Standards C as standards that can be used now to support Smart Grid development:

SAE J1772 Electrical Connector between PEV D /EV and EVSE

o SAE J 1772 TM Electric Vehicle and Plug in Hybrid Electric Vehicle Conductive Charge Coupler

SAE J2293 Communications between PEVs and EVSE for DC Energy [Part 1, Part 2]

o SAE J2293/1 Energy Transfer System for Electric Vehicles:

Functional Requirements and Syste m Architectures

C Available at http://www.nist.gov/public_affairs/releases/upload/smartgrid_interoperability_final.pdf (last accessed Augus t 26, 2010).
D ―PEV‖ ( p lug

- in e lectric v ehicle) is SAE‘s language of choice for what is called a PHEV elsewhere in this document.Appendix G

G

- 8 o SAE J2293/1 Energy Transfer System for Electric Vehicles: Communication Requirements and Network Architecture

SAE J2836/1

- 3 Use Cases for PEV Interactions (in development) [Part 1, Part 2, Part 3]

o J2836/1 Use Cases for Communication betwee n Plug

- in Vehicles

and the Utility Grid

o J2836/2 Use Cases for Communication between Plug

- in Vehicles and the Supply Equipment (EVSE)

o J2836/3 Use Cases for Communication between Plug

- in Vehicles and the Utility Grid for Reverse Power Flow

o J2836/4 Use Cases for Diagnostic Communication for Plug

- in Vehicles

o J2836/5 Use Cases for Communication between Plug

- in Vehicles and their customers.

SAE J2847/1

- 3 Communications for PEV Interactions (in development) [Part 1, Part 2, Part 3]

o J2847/1 Communication between P lug

- in Vehicles and the Utility Grid

o J2847/2 Communication between Plug

- in Vehicles and the Supply Equipment (EVSE)

o J2847/3 Communication between Plug

- in Vehicles and the Utility Grid for Reverse Power Flow

o J2847/4 Diagnostic Communication for Plug

- in Vehi cles

o J2847/5 Communication between Plug

- in Vehicles and their
customers

J2894 Powe r Quality Requirements for Plug

- i n Vehicle Chargers

– Part 1: Requirements

J2894/2 Powe r Quality Requirements for Plug

- i n Vehicle Chargers

– Part 2: Test Methods

J2931/1 Power Line Carrier Communications for Plug

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- 9 IEEE

– Standards Coordinating Committee 21 (SCC21) sponsors the development of 1547 interconnection standards and the P2030 smart grid interoperability standards project.

IEEE 1547 Standard f

or Interconnecti ng Distributed Resources with Electric Power Systems

IEEE P2030 Guide for Smart Grid Interoperability of Energy Technology and Information Technology and Information Technology Operation with the Electric Power System (EPS) and End

- Use Appl ications and Loads

UL

– Underwriters Laboratories plays a critical role in the certification of hardware to be used in charging. UL offers certification for the many aspects of the EVSE, including the charge equipment (Levels 1

- 3), plugs, receptacles, cor d sets and personal protection equipment. Of particular interest are specifications with respect to grounding/isolation

.
NFPA

- NEC , part 625 , specifically addresses the installation of charging equipment. It is updated every 3 years ; currently NEC

- 2008 applies and input s /petitions for the next version ( NEC

- 2011 ) are closed. The draft national template project relies heavily on the NEC as it is the primary reference for permitting and installation in local municipalities.

International

- SAE and JARI agr ee on Level 2 charging standards (both countries use single

- phase current); though, high

- power Level 3 DC coupler standards for public charging differ substantially from those proposed in the U.S. (and Europe so far). The JARI Level 3 standards are promot ed by CHAdeMO, an association formed in Japan to promote global adoption of JARI EV infrastructure standards, and are used on the TEPCO charge equipment that will be deployed by the ARRA

- funded vehicle demonstration program (along with the Nissan Leaf EV); a U.S. Level 3 standard has yet to be developed. Though proposed charge coupler standards are constantly being refined, the following chart was recently developed to explain the differences at this time.Appendix G

G

- 10 Figure G 1.4

- 1 : International Charge Couple Comparison E

G1.5 Hydrogen Infrastructure

Section 4.3 in Chapter 4, Infrastructure Assessment, contains an overview of hydrogen refueling technology and availability. This section provides additional details about hydrogen infrastructure including costs, standards, and codes for hydrogen infrastructure installation.

G1.5.1 Cost of Hydrogen

This section summarizes slides taken from a presentation by Professor Joan Ogden of the Institute of Transportation Studies University of California, Davis

. 23

The slides indicate projected cost of hydrogen in various U.S. cities from 2014 to 2030, U.S. average delivered hydrogen cost through 2050 and hydrogen transition timing and
costs.

E Level 2 is up to 80 amp, but typically 16

- 32 amp2017

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- 11 Figure 1.5

- 1 : Cost of Hydrogen in Selected US Cities (UCD SSCHISM Model)

J. Ogden and C. Yang, "Build

- up of a hydrogen infrastructure in the US," Chapter 15, in The Hydrogen Economy: Opportunities and Challenges, edited by Dr Michael Ball and Dr Martin Wietschel, Cambridge University Press, 2009, pp.454

- 482.

In certain regions, such as Los Angeles, hydrogen cost for infrastructure is projected to decrease rapidly between 2015 and 2018 as FCEVs are rolled out.

Figure 1.5

- 2 : US Average Delivered Hydrogen Cost (NRC 2008), Electricity and Gasoline Price (EIA 2008)Appendix G

G

- 12

National Research Council, National Academies of Engineering, Transitions to Alternative Transportation Technologies: A Focus on Hydrogen, Pre

- publication version available from National Academies website http://www.nap.edu/catalog.php?record_id=12222

Studies by UC Davis indicate that hydrogen costs can be competitive with gasoline in 2020. Note that 1 kg of hydrogen has approximately the same energy content (lower heating value) as 1 gallon of gasoline (1kg hydrogen = 1 gallon gasoline equivalent (gge)

National Research Council, National Academies of Engineering, T ransitions to Alternative Transportation Technologies: A Focus on Hydrogen, Pre

- publication version available from National Academies website http://www.nap.edu/catalog.php?record_id=12222

In 20 08, the NRC‘s Committee on Assessment of Resource Needs for Fuel Cell and Hydrogen Technologies released the report, ―Transitions to Alternative Transportation Technologies

—

A Focus on Hydrogen,‖ which was required by the Energy Policy Act (2005) section 18 25. One of the committee's conclusions was that to accelerate the penetration of FCEVs, strong government policies will be required. The NRC estimated that the government cost to support a transition to FCEVs for the period from 2008 to 2023 would be app roximately $55 billion (this amounts to slightly more than $3.5 billion/year or about $10,000 per FCEV

— the committee compared this value to ethanol subsidies, which were $2.6 billion in 2006 and are expected to grow to $15 billion/year by 2015). The table shows details on government costs required for infrastructure.2017

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- 13 G1.5.2 Codes and Standards to Support Hydrogen and Fuel Cell Infrastructure

The United States and most countries in the world have established laws and regulations that require commercial products to meet all applicable codes and standards to demonstrate that they are safe, perform as designed and are compatible in the systems in which they are used. Hydrogen has an established history of industrial use as a chemical feedstock, but not as an energy ca rrier on a large

- scale commercial basis. The development and promulgation of codes and standards are essential to establish a market

- receptive environment for commercial, hydrogen

- based products and systems for energy use.

The key U.S. and international s tandards development organizations ( SDOs ) developing and publishing the majority of hydrogen codes and standards are shown in the table below. These organizations typically work with the public and private sectors to develop codes and standards.

The U.S. Department of Energy (DOE) conducts underlying safety R&D and works with domestic and international SDOs to facilitate the development of applicable codes and standards. These standards are then referenced by building and other codes to expedite regulator y approval of hydrogen technologies. This approach ensures that U.S. consumers can purchase products that are safe and reliable, regardless of their country of origin, and that U.S. companies can compete internationally. 24

Organizations Involved in Codes and Standards Development and Publication

Organization Responsibility

Domestic Codes and Standards

American Society for Testing and Materials Materials testing standards and protocols (ASTM)

American National Standards Institute (ANSI) Certifies consensus methodology of and serves a s clearinghouse for codes and standards development

American Petroleum Institute (API) Equipment standards

American Society of Heating, Refrigeration Equipment design and performance standards and Air Conditioning Engineers (ASHRAE)

American Society of Mechanical Engineers Equipment design and performance standards (ASME)

Compressed Gas Association (CGA) Equipment design and performance standards

CSA America (CSA) Equipment standardsAppendix G

G

- 14

U.S. Department of Transportation Vehicle standards and regulations

International Association of Plumbing and Mechanical building code Mechanical Officials (IAPMO)

Institute of Electrical and Electronic Engineers Electrical standards (IEEE)

National Fire Protection Association (NFPA) Model building codes, standards

Natural Gas Institute (NGI) Natural gas vehicle standards

Society of Automotive Engineers (SAE) Vehicle system and subsystem design and performance standards Underwriters Laboratories (UL) Equipment and performance testing standards International Electrotechnical Commission (IEC) International Performance Standards International Organization for Standardization (ISO) International Performance Standards

In February 2010, the National Renewable Energy Laboratory (NREL) published the Vehicle Codes and Standards: Overview and Gap Analysis

. The gap analysis includes a list of applicable codes and standards for alternative fuels including hydrogen infrastructure. The list of applicable codes and standards is below: 25

ANNUAL INSPECTIONS CGA G

- 5.4, Standard for Hydrogen Piping Systems at Consumer Locations (Compressed Gas Association 2005) CGA G

- 5.5, Hydrogen Vent Systems (Compressed Gas Association 2004) IFC (International Code Council 2006) NFPA 52, Vehicular Fuel Systems Code (Nation al Fire Protection Association 2006)

BALANCE OF PLANT Piping & Tubing ASME B31.12, Hydrogen Piping and Pipelines CGA G

- 5.4, Standard for Hydrogen Piping Systems at Consumer Locations (Compressed Gas Association 2005) IFC (International Code Council 20 06) International Fuel Gas Code (International Code Council 2006) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006) NFPA 55, Standard for Storage, Use and Handling of Compressed Gases and Cryogenic Fluids in Portable and Stationary Containers, Cylinders and Tanks (National Fire Protection Association 2005) CGA H

- 3 Cryogenic Hydrogen Storage (Compressed Gas Association 2006)

Pressure Relief CGA S

- 1.3, PRD Standards Part 3

- Stationary Storage Containers for Compressed Ga ses (Compressed Gas Association 2005) IFC (International Code Council 2006)2017

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- 15 International Fuel Gas Code (International Code Council 2006) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006) NFPA 55, Standard for Storage, Use and Handling of Compressed Gases and Cryogenic Fluids in Portable and Stationary Containers, Cylinders and Tanks (National Fire Protection Association 2005)

Valving and Fittings ASME B31.3, Process Piping (American Soc iety of Mechanical Engineers 2006) CGA G

- 5.4, Standard for Hydrogen Piping Systems at Consumer Locations (Compressed Gas Association 2005) IFC (International Code Council 2006) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 20 06)

Venting and Other Equipment CGA G

- 5.5, Hydrogen Vent Systems (Compressed Gas Association 2004) IFC (International Code Council 2006) International Fuel Gas Code (International Code Council 2006) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006) NFPA 55, Standard for Storage, Use and Handling of Compressed Gases and Cryogenic Fluids in Portable and Stationary Containers, Cylinders and Tanks (National Fire Protection Association 2005)

CANOPY TOPS International Building Code (International Code Council 2009) IFC (International Code Council 2006) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006)

COMPRESSED HYDROGEN GAS STORAGE Equip ment Location IFC (International Code Council 2006) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006) NFPA 55, Standard for Storage, Use and Handling of Compressed Gases and Cryogenic Fluids in Portable and Stationary Containers, Cylinders and Tanks (National Fire Protection Association 2005)

General Safety Requirements IFC (International Code Council 2 006) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006) NFPA 55, Standard for Storage, Use and Handling of Compressed Gases and Cryogenic Fluids in Portable and Stationary Containers, Cylinders and Tanks (National Fire Protec tion Association 2005)

Storage Containers CGA PS

- 20, Direct Burial of Gaseous Hydrogen Storage Tanks (Compressed Gas Association 2006) CGA PS

- 21, Adjacent Storage of Compressed Hydrogen and Other Flammable Gases (Compressed Gas Association 2005) IFC ( International Code Council 2006)Appendix G

G

- 16

NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006)

COMPRESSION SYSTEMS AND EQUIPMENT IFC (International Code Council 2006) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection As sociation 2006)

DESIGN Barrier Walls IFC (International Code Council 2006) Equipment

International Fire Code (International Code Council 2006) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006) Fuel Stations

IFC (International Code Council 2006) NFPA 30A, Code for Motor Fuel Dispensing Facilities and Repair Garages (National Fire Protection Association 2003) Equipment

International Fire Code (International Code Council 2006) NFPA 52, Vehicular Fuel System s Code (National Fire Protection Association 2006) Fuel Stations

IFC (International Code Council 2006) NFPA 30A, Code for Motor Fuel Dispensing Facilities and Repair Garages (National Fire Protection Association 2003) NFPA 52, Vehicular Fuel Systems C ode (National Fire Protection Association 2006) NFPA 55, Standard for Storage, Use and Handling of Compressed Gases and Cryogenic Fluids in Portable and Stationary Containers, Cylinders and Tanks (National Fire Protection Association 2005)

Weather Prote ction IFC (International Code Council 2006)

DISPENSING Electrical Equipment IFC (International Code Council 2006) NFPA 30A, Code for Motor Fuel Dispensing Facilities and Repair Garages (National Fire Protection Association 2003) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006)

Fuel Lines CGA G

- 5.4, Standard for Hydrogen Piping Systems at Consumer Locations (Compressed Gas Association 2005) IFC (International Code Council 2006) International Fue l Gas Code (International Code Council 2006)2017

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- 17 NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006)

Gaseous Dispensers IFC (International Code Council 2006) Facilities NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006)

Hoses and Connectors IFC (International Code Council 2006) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006)

Liquid Dispensers IFC (Inter national Code Council 2006) NFPA 30A, Code for Motor Fuel Dispensing Facilities and Repair Garages (National Fire Protection Association 2003) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006)

Vehicle Connectors NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006) SAE J2600, Compressed Hydrogen Surface Vehicle Refueling Connection Devices (Society of Automotive Engineers 2002)

DISPENSING, OPERATIONS, AND MAINTENANCE SAFETY Gaseous Hydrogen CGA G

- 5.5, Hydrogen Vent Systems (Compressed Gas Association 2004) IFC (International Code Council 2006) NFPA 30A, Code for Motor Fuel Dispensing Facilities and Repair Garages (National Fire Protection Association 2003) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006)

Liquid Hydrogen CGA G

- 5.5, Hydrogen Vent Systems (Compressed Gas Association 2004) IFC (International Code Council 2006) NFPA 30A, Code for Motor Fuel Dispensing Facilities and Repair Garages (National Fire Protection Association 2003) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006)

FIRE SAFETY Construction IFC (International Code Counci l 2006) International Fuel Gas Code (International Code Council 2006) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006) NFPA 55, Standard for Storage, Use and Handling of Compressed Gases and Cryogenic Fluids in Portable a nd Stationary Containers, Cylinders and Tanks (National Fire Protection Association 2005)

Equipment IFC (International Code Council 2006) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006)Appendix G

G

- 18

Signage IFC (International Cod e Council 2006) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006) NFPA 55, Standard for Storage, Use and Handling of Compressed Gases and Cryogenic Fluids in Portable and Stationary Containers, Cylinders and Tanks (National Fire Protection Association 2005)

LIQUID HYDROGEN STORAGE Equipment Location IFC (International Code Council 2006) NFPA 55, Standard for Storage, Use and Handling of Compressed Gases and Cryogenic Fluids in Portable and Stationary Containers, Cylinde rs and Tanks (National Fire Protection Association 2005)

General Safety Requirements IFC (International Code Council 2006) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006)

Storage Containers IFC (International Code Council 2006) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006) NFPA 55, Standard for Storage, Use and Handling of Compressed Gases and Cryogenic Fluids in Portable and Stationary Containers, Cylinde rs and Tanks (National Fire Protection Association 2005) CGA H

- 3 Cryogenic Hydrogen Storage (Compressed Gas Association 2006)

ON

- SITE HYDROGEN PRODUCTION IFC (International Code Council 2006) International Fuel Gas Code (International Code Council 200 6) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006)

OPERATION APPROVALS Dispensing IFC (International Code Council 2006) NFPA 30A, Code for Motor Fuel Dispensing Facilities and Repair Garages (National Fire Protection Association 2003) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006)

Fire And Emergency Planning IFC (International Code Coun cil 2006) NFPA 30A, Code for Motor Fuel Dispensing Facilities and Repair Garages (National Fire Protection Association 2003) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006) NFPA 55, Standard for Storage, Use and Handling of Compressed Gases and Cryogenic Fluids in Portable and Stationary Containers, Cylinders and Tanks (National Fire Protection Association 2005)2017

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- 19 Fuel Delivery IFC (International Code Council 2006) NFPA 30A, Code for Motor Fuel Dispensing Facilities and Repair Garages (National Fire Protection Association 2003) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006) NFPA 55, Standard for Storage, Use and Handling of Compressed Gases and Cryogenic Fluids in Portable and Stationa ry Containers, Cylinders and Tanks (National Fire Protection Association 2005)

Ignition Control IFC (International Code Council 2006) NFPA 55, Standard for Storage, Use and Handling of Compressed Gases and Cryogenic Fluids in Portable and Stationary Containers, Cylinders and Tanks (National Fire Protection Association 2005)

Personnel Issues and Training IFC (International Code Council 2006) NFPA 30A, Code for Motor Fuel Dispensing Facilities and Repair Garages (National Fire Protection Association 2003) NFPA 55, Standard for Storage, Use and Handling of Compressed Gases and Cryogenic Fluids in Portable and Stationary Containers, Cyli nders and Tanks (National Fire Protection Association 2005)

Signage IFC (International Code Council 2006) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006) NFPA 55, Standard for Storage, Use and Handling of Compressed Ga ses and Cryogenic Fluids in Portable and Stationary Containers, Cylinders and Tanks (National Fire Protection Association 2005)

Vehicle Access IFC (International Code Council 2006) NFPA 30A, Code for Motor Fuel Dispensing Facilities and Repair Garages (National Fire Protection Association 2003) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006) NFPA 55, Standard for Storage, Use and Handling of Compressed Gases and Cryogenic Fluids in Portable and Stationary Containers, C ylinders and Tanks (National Fire Protection Association 2005)

SETBACKS AND FOOTPRINTS Liquid Systems IFC (International Code Council 2006) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006) NFPA 55, Standard for Storage , Use and Handling of Compressed Gases and Cryogenic Fluids in Portable and Stationary Containers, Cylinders and Tanks (National Fire Protection Association 2005)

Outdoor Gaseous Systems IFC (International Code Council 2006)Appendix G

G

- 20

NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006) NFPA 55, Standard for Storage, Use and Handling of Compressed Gases and Cryogenic Fluids in Portable and Stationary Containers, Cylinders and Tanks (National Fire Protection Association 2005)

TRANSPORTATION Compressed Hydrogen Gas CGA P

- 1, Safe Handling of Compressed Gases in Containers (Compressed Gas Association 2006) IFC (International Code Council 2006) NFPA 55, Standard for Storage, Use and Handling of Compressed Ga ses and Cryogenic Fluids in Portable and Stationary Containers, Cylinders and Tanks (National Fire Protection Association 2005)

Liquid Hydrogen CGA P

- 12, Safe Handling of Cryogenic Liquids (Compressed Gas Association 2005) IFC (International Code Counc il 2006) NFPA 52, Vehicular Fuel Systems Code (National Fire Protection Association 2006) NFPA 55, Standard for Storage, Use and Handling of Compressed Gases and Cryogenic Fluids in Portable and Stationary Containers, Cylinders and Tanks (National Fire P rotection Association 2005)

Natural Gas ASME B31.8, Gas Transmission and Distribution Systems (American Society of Mechanical Engineers 2003)

VAPORIZERS IFC (International Code Council 2006) IFC (International Code Council 2006) NFPA 55, Standard for Storage, Use and Handling of Compressed Gases and Cryogenic Fluids in Portable and Stationary Containers, Cylinders and Tanks (National Fire Protection Association 2005)

The table below provides a summary of the identified Code and Standard s Gaps for the expanded use of h ydrogen as an alternative fuel. Also, the table presents the impacted document and proposed means to address the gap. It also illustrates the various areas of hydrogen codes and standards that require additional work in order to create a complete and standardized control strategy.

One key area that may require additional work is operations and maintenance requirements for fuel dispensing systems. This area is of particular conc ern because relatively little data for the use of vehicular hydrogen dispensing systems exists. As data is accrued, it may become apparent that additional safety measures are needed to address operations and maintenance. A second area of concern is poten tial releases of hydrogen in confined spaces such as indoor fueling operations, tunnels, and parking garages. The release characteristics and prevention and mitigation measures vary for these different locations, but many of the same analytical tools can b e used to characterize the hazards of these releases. A third area of co ncern is the potential energy contained in high

- pressure storage and dispensing systems. The following table lists several other important gaps that require further work.2017

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- 21 Codes and Standards Gaps for Hydrogen 2 5

Codes or Standard Gap Documents Impacted Gap Resolution

No final fuel quality standard ISO Fuel Quality Draft International Standard, ASTM analysis standards, SAE Technical Information Report (TIR) J2719 Provide data to ensure that draft standards become final standards

Potentially incomplete requirements for indoor hydrogen vehicle dispensing NFPA 52, IFC Evaluate indoor release characteristics and accident scenarios for potential application to code development Off road vehicle storage tank standards are incomplete CSA America Heavy Goods Vehicle (HGV) 4.3, SAE J2601 Support standards development work with direct committee involvement and data support Bulk liquefied hydrogen storage requirements lack technical basis documentation NFPA 55, NFPA 2, IFC Evaluate liquid release impacts and frequencies and provide this information to relevant technical committees to validate or revise bulk liquefied hydrogen storage requirements Requirements for tunnels, parking garages, and repair garages need review to determine whether additional requirements for hydrogen are needed [meeting with New York Port Authority January 2009] NFPA 505, IFC, NFPA 88B, NFPA 30A, IBC, International Mechan ical Code (IMC) Evaluate safety concerns in these environments and work with the technical committees to provide data required to address codes and standards requirementsAppendix G

G

- 22

Operations and maintenance procedures lack supporting operational history data [co nversation with Larry Fluer] NFPA 52, NFPA 30A, IFC Evaluate existing procedures to determine where they might be incomplete. Evaluate operations and maintenance history for similar fuels to determine whether useful information can be retrieved and appl ied to hydrogen Steam Methane Reformation (SMR) plants do not have a safety standard [conversation with Roger Smith] No current code specifically addresses SMR plants Develop a code or standard that addresses SMR plants

New storage systems, such as metal hydrides, are minimally addressed in codes and standards NFPA 55, CGA H

- 1 and H

2, IFC Determine whether new chemical storage systems are adequately addressed in codes and standards

Limited familiarity with relevant h ydrogen codes and standards among project developers and code officials [conversation with Larry Fluer] All hydrogen codes and standards Regional codes and standards workshops as well as web training and background information can help address this issue

Incomplete requirements for sensing technologies [Rivkin analysis of NFPA 52] NFPA 52, NFPA 55 Support the use of sensing technologies that replace odorants through evaluating sensing technologies and supporting code and standards development work in sensing technologies High

- pressure storage, handling, and use of hydrogen [David Farese DOE Safety Panel meeting] NFPA 52, NFPA 55, CGA H series of documents Evaluate codes and standards that address high

pressure storage to determine if requirements are adequate and if2017

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- 23 additional work is required

Global Technical Regulations (GTR) Coordination wi th SAE and DOT regulations Continue to represent the United States in GTR development meetings and evaluate impacts of GTR in domestic regulations, codes, and standards

Coordination of international (primarily ISO) standards and domestic codes and standards Multiple documents: SAE, CSA, UL, NFPA Evaluate component standards to ensure that there are not unnecessary conflicts The DOT guidance documents for incidents inv olving flammable gases are too general and prescriptive DOT Emergency Response Guide Add additional material to the DOT guide for hydrogen incidentsAppendix G

G

- 24 Appendix G References

1 Morrow, Karner, Francfort (2008). ―Plug

- in Hybrid Electric Vehicle Char ging Infrastructure Review‖, Battelle Energy Alliance, U.S. Department of Energy Idaho National Laboratory. Nov 2008.

2 May, James W. and Matt Mattila (2009). ―Plugging In: A Stakeholder Investment Guide for Public Electric

Vehicle Charging Infrastructure.‖ Rocky Mountain Institute. July 2009.

3 May and Mattila, 2009.

4 Morrow, Karner, Francfort, 2008.

5 Electric Transport ation Engineering Corporation (ETEC), 2009. Electric Vehicle Charging Infrastructure Deployment Guidelines British Columbia, July.

Also, Electric Transportation Engineering Corporation (2010), Electric Vehicle Charging Infrastructure Deployment Guidelines for the Central Puget Sound Area, May.

6 Morrow, Karner, Francfort, 2008.

7 May and Mattila, 2009..

8 Electrification Coalition (2009). ―Electrification Roadmap‖, Electrification Coalition. Nov 2009.

9 ETEC, 2009.

10 Morrow, Karner, Francfort, 2008.

11 ETEC , 2009.

12 May and Mattila, 2009.

13 May and Mattila, 2009.

14 Electrification Coalition, 2009.

15 ETEC, 2009.

16 Electrification Coalition, 2009.

17 Press release from Nissan, May 2010, accessed on the Internet at: http://www.nissan

global.com/EN/NEWS/2010/_STORY/100521

- 01

- e.html.

18 Brooker, et al (2010), ―Technology Improvement Pathways to Cost

- Effective Vehicle Electrification,‖ to be presented at the SAE 2010 World Congress, Detroit, MI, April 2010.

19 Energy Storage for the Electricity Grid: Benefits and Market Potential Assessment Guide, Sandia National Laboratories, Albuquerque, NM: 2010.

20 Kamath (2010), ―Lithium Ion Batteries in Utility Appl ications‖, Proceedings of the 27th International Battery Seminar and Exhibit, Ft. Lauderdale, FL, March 2010.

21 Market Feasibility for Nickel Metal Hydride and Other Advanced Electric Vehicle Batteries in Selected Stationary Applications, EPRI, Palo Alto, CA, and SMUD, Sacramento, CA: 2000.2017

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- 25 22 Neubauer, Jeremy and Ahmad Pesaran (2010), Preliminary EV/PHEV Battery Secondary Use Analysis in Support of EPA 2017

- 2025 Technical Assessment.

23 Slides from a Presentation by Prof Joan Ogden. ―What is needed to initi ate new fuel/vehicle pathways? Comparing Transition Costs for H2 FCVs, PHEVs and Biofuels.‖ Prof. Joan Ogden, Institute of Transportation Studies, University of California, Davis, June 14, 2010.

24 MYPP (Multi

- Year Research, Development, and Demonstrati on Plan) 2007. Hydrogen Codes and Standards

. Washington, D.C.: U.S. Department of Energy, Energy Efficiency and Renewable Energy. http://www1.eere.energy.gov/hydrogenandfuelcells/mypp/pdfs/codes.pdf

25 NREL (National Renewable Energy Laboratory) 2010. Vehicle Codes and Standards: Overview and Gap Analysis . Washington, D.C.: U.S. Department of Energy, Energy Efficiency and Renewab le Energy. www.nrel.gov/docs/fy10osti/47336.pdf