# %&.. 

# #n~ UNITED STATES ENVIRONMENTAL PROTECTION AGENCY 

# gw: b %> 

### P NATIONAL VEHICLE AND FUEL EMISSIONS LABORATORY

4L WOlEG 2565 

### PLYMOUTH ROAD ANN ARBOR, MICHIGAN

### 48105-2498

OFFICEOF AIR AND RADIATION 

## March 11, 2004 CCD-04-06 (LDVLDT) Dear Manufacturer: 

## Subject:Updated Analytically Derived Fuel Economy 

# (ADFE) Policy for 

## 2005 MY and Later Attached to this letter arerevised guidelines applicable to the use of analytically derivedfuel economy (ADFE). Use of ADFE has been available from the beginningof the fuel economy program. Theprovisionsof 40 CFR 600.006-89(e)allow EPA to accept analytical expressions to generate fuel economy data. 

## In the early 1980’s,a fuel economy sensitivity equation was developedand was used in 

## conjunctionwith EPA Advisory Circular 83A to implementthe 

## ADFE program. 

## On May 12, 1995,EPA published guidance letter number CD-95-08 which substantially expandedthe use of 

## ADFE and provided new sensitivity equations which included a 

## statistical confidence factor for the first time. 

## On April 24, 

## 2000, EPA published guidance letter CD-00-04which provided an interim method to use the existingADFE equations for testing conductedon a singleroll dynamometerusing the three-term road force equation. The guidance in CD-00-04was set to expire afterthe 2004 

## model year, by which time EPA anticipatedthat 

## a new equation would be developedusing only single roll dynamometer data. This letterprovides that updated equation. The updates presentedin this letter are based in large part 

## on discussionswith and data submittedby the Alliance of AutomobileManufacturers (Alliance). The changes include updated

## ADFE equation coefficients, to allow data from all drivetraintypes 

## (2WD,4WD and AWD) to be pooled together under specific conditions, to allow manufacturers to submit their ADFE documentationupon EPA request, and to expandthe maximum fuel economy allowed from 10percent to 20percent from the baseline test. All other previous provisions for ADFE usage will continue to apply. The full details about the sensitivity coefficients, baselinetest selection, restrictions,and required documentationare containedin the Enclosure 1. 

## Enclosure 2 

## containsthe details of the regression analysisused to calculatethe ADFE equation coefficientswhich are containedin 

## this letter. This enclosurewas providedby the Alliance. The analytical equation and procedures enclosedwith this letter are effectiveimmediately for model year 2005 

### and later vehicles, and 

### replace 

### the 

## guidance on 

### ADFE presented in 

### EPA 

## guidance letters numbers CD-95-08 and 

## CCD-00-04. A manufacturermay optionallyuse these guidelinesand equations for model years prior to 

## 2005. EPA retainsthe right to order actual

@ Printed on Recycled Paper 

## BQ

.-

## confirmatory testing 

## if necessary to assure 

## the integrity

## of the fuel economyprogram or if there is a concern about emissions compliance. 

## EPA believes theseupdated 

## ADFE guidelines represent a reasonable balancebetween the need

## for accurate fuel economy data and the need to contain the 

## cost of testingfor both 

## industryand EPA. 

## Please contact Mr. Eldert Bontekoeat 

## (734)2144442 oryour Certification Team Representativeif you any questions related to the ADFE process. Sincerely,

Merrylin Zaw-Mon, Director Certification and Compliance Division Office of Transportation and Air Quality

Enclosures 

## (2)

# Enclosure 1

# to CCD-04-06 Updated AnalyticallyDerived Fuel Economy (ADFE) Guidelines 1. Without prior EPA approval, manufacturers may select the baseline test to be used for an ADFE, providing the following guidelines are followed:

a. Vehicles considered for selection for the baseline test must pass all applicable emission standards in the model year associated with the ADFE. b. All official tests (which pass all applicable standards) of the same or equivalent basic engine, transmission class, engine code, transmission code, engine horsepower, dynamometer drive wheels, ahd compression ratio as the ADFE subconfiguration must be included in 

## the pool 

## of tests which will be considered forbaseline selection.

c. In order to minimize the mpg adjustment, the manufacturer may supplement the pool with tests associated with worse case engine or transmission codes and carryover or carry-across engine families. In these cases, all the data which qualifies for inclusion using the elected worse-case substitution (or carryover or carry-across) must be included in 

## the pool as supplemental data (i.e., individual test vehicles may not be selected for inclusion). Once the manufacturer decides to supplement the pool in 

## this manner, the supplemental data must be included in 

## all subsequent pools, where applicable. d. 

## To limit the effect of an "above average" test, tests previously used during the subject model year as baseline tests in five other ADFE subconfigurations must be eliminated from the pool.

e. All remaining tested subconfigurations in the pool must be evaluated against the target 

## ADFE subconfiguration by using the new three-parameter composite mpg coefficient including the 95% confidence limits. f. The tested subconfiguration with the smallest net combined fuel economy adjustment (Le., smallest absolute value of (ADFE
- 

## test 

## FE))for combined fuel economy) will be selected as the baseline test for the target ADFE subconfiguration and used for both city and highway adjustments. 2. Any proposed baseline test not selected according to the provisions of paragraph 1 (above), must be reviewed and approvedby EPA on a case-by-case basis. 3. 

## The ADFE will be calculated using the three-parameter 

## 95% confidence limits as listed on the following table. The result shall be rounded to a tenth of an mpg. The upward Page 1 of 

## 3

## adjustment of

# ADFE from the baseline shall be limited to 20% over the baseline fuel economy (i.e., baseline fuel economyX 

## 1.2). The downward adjust is not limited.

CityFuel Economy Highway Fuel Economy Parameter parameter parameter parameter parameter increases decreases increases decreases ETW -0.532 -0.449 -0.308 -0.239 

## NIV -0.173 -0.117 -0.274 -0.228 

## TRLHP -0.213 -0.149 -0.460 -0.407

4. Manufacturers may not submit an ADFE if an actual test has been run on the target subconfiguration during the certificationprocess or on a development vehicle which is eligible be declared as a fuel economy data vehicle. 5. Tomaintain the integrity of the fuel economy program, manufacturers may not use ADFE under the following circumstances:

a. For Passenger Automobile labels 

# - manufacturers may not use any ADFE with a combined fuel economy of less than 1.0mpg above the Gas Guzzler Tax $0 

## threshold (currently this limit is 23.5 mpg
- 

## see 40 CFR 600.513-91). b. 

## For Passenger Automobiles and Light Truck labels
- 

## manufacturers may not use any ADFE with a combined fuel economy greater than or equal to the leader in the applicable Vehicle Classification Class based on the previous model year's unadjusted general label values rounded to a whole mpg. If manufacturers are unaware of these values they must contact their Certification Team Representative before using ADFE. 6. To limit the impact of ADFE on CA&, no more than 20 percent of the subconfigurations tested 

## in a manufacturer's final CAF@may be represented by ADFE. For example, if the manufacturer has 100 subconfigurationswhich are tested (or represented through data substitutions and equivalencies), only 20 of the 100may be based on 

## ADFE calculations (or represented through data substitutions or equivalencies from ADFE generated data points). 7. The manufacturers must retain for five years (under the provisions of 40 

## CFR 600.005- 

## 81(a)(3))the pool of tests, the vehicle description and tests chosen as the baseline and the basis for its selection, the target ADFE subconfiguration and the calculated city and highway adjusted fuel economy. EPA may request this information as part of an audit.
Page 2 of 

## 3

## 8. If EPA determinesthat it is necessary to assure the integrityof the fuel economy database or if 

## EPA has 

## concerns about compliancewith 

## emission standards,EPA 

## retains the right to order a confirmatorytest 

## of the subconfiguration covered by the ADFE. 

## If the manufacturer chooses,EPA 

## will accept a temporary Fuel EconomyLabel based on 

## the ADFE while a suitabledata vehicle

## isbeing procured. However,if the confirmatory test value results in a lowerrounded fuel economy value (city,highway, or combined) for any model type the label must be updated. Theupdated label value shallbe used on all vehicles produced more than 

## 15days following its submission. 

## 9. EPA 

## is presenting this option as a manufacturer self-approval process. EPA 

## will not be responding to routine submissionsof 

## ADFE data indicating our acceptanceof the calculationor waiver of 

## confirmatory testing. If EPA later discoversthat the procedures for self-approval were not followed, EPA may rescind the use of ADFE data and require actual test databe generated and require recalculationof labels and CAFE values.

Page 

## 3 of 

## 3

### Enclosure 

### 2 to 

### CCD-04-06

# -- ADFE Equation Development General Note: The development ofthe ADFE coefficients mirrors the process used to develop the 1996 ADFE equation and coefficients. 

### Dataset Single roll tests fromthe 2000-2004 test car lists through September 2003 were included in the original database. 

### Only official data is contained in

### the EPAtest car lists. Dataset only includes tests on gasoline test fuel (6272 tests) ADFE were deleted 

### (570) Duplicate tests were deleted (1724) HEV, AFV, 91 Octane tests were deleted (252) Suspect tests were deleted (147) 0 

### Suspected high or low TRLHP
0 

### Frontal area DPA 0 

### Three 

### known outliers Unique vehicle tests were deleted (1 62) 12 cylinder engines 0 

### Prowler 0 

### Rotary engine Engine horsepower greater then 380 Suspect dual rolls tests (127) Total tests removed from the dataset: 

### 2624 Total tests in the dataset: 3642, approximately half city and halfhighway Test parameters on several tests were corrected based on manufacturer information. The drive data was corrected and 4WD and AWD information was converted to either FWD or RWD, based on how the vehicle was tested. 

### Data Analvsis An initial regression was performed which considered most ofthe vehicle parameters in the test car list and a number of technologies including valves per cylinder, VVT, turbo or supercharging. The following parameters were selected based on this analysis: ETW, TRLHP,

### NN,CID, HP, 

### drive and car and truck indicators. Regressions were run to verify that the In function gave a better correlation than an analysis based on the straight values ofthe parameters (the In function was used in the development 

### ofthe original coefficients) Stepwise regression was used to verify the significant factors. Multiple regressions were run to identify whether separate equations shouldbe established based on the significant factors and that use of a city TRLHP at 20 mph would not improve correlation ofthe data. Results Using the 

## Infunction resulted in a better correlation, and therefore was preferred over the use ofthe straight values. 0 

### There was no improvement in the correlation if separate equations were developed for car and truck, or front or rear wheel drive or by using the TRLHP at 20 mph for the city tests over a TRLHP at 

### 50mph. 0 

### Car and truck, drive, cid, hp, VVTi were all considered significant in the development ofthe coefficients and therefore remained in the final analysis.

Parameter City Fuel Economy Highway Fuel Economy parameter increases parameter decreases parameter increases parameter decreases ETW -.532 -.449 -.308 -.239 

### ” 

## -.173 -.117 -.274 -.228 TRLHP -.213 -.

### 149 -.460 

### -.407

Submitted by The Alliance of Automobile Manufacturers- Peg GutrnandMGutmann Page 1 of 6 Date IE 

### -1403061.doc Date Revised: 

### 3/12/20044 Residuals Versus the FittedValues 10 xi FmedValue (R1JPO"V is I" mpg1

T I 25 30 35 Fitted Value

3 - 2-
1 - 0 - 1- 4-J 2- 

# . 

# /-'

3 - 'y I 8 ' I I I I 5 0 5 10 2 0 Resdual E -1 

# . '/"' 

## = 2 4 I I I I I


### Test of 

### appropriate analysis method straight values In of

### values



## RegressionAnalysis: mpg versus etw, clt, drive, cid, hplcid, nlv,trlhp (All data) The regression equation 

### is mpg = 74.6 - 0.00216 etw - 1.14 c/t + 0.155 drive - 0.0449 cid - 2.87 hp/cid Submitted byThe Alliance of Automobile Manufacturers

### - Peg GutmannlMGutmann Page 2 of 6 Date I$ 

### -1403061 .doc Date Revised: 

### 3/12/2004- 0.227 n/v - 0.803 trlhp Predictor Coef SE Coef T P Constant 74.5554 0.9617 77.52 0.000 etw 0.0021638 0.0001989 -10.88 0.000 c/t drive -1.1414 0.15463 0.2334 0.05704 -4.89 2.71 0.000 0.007 cid -0.044870 0.002050 -21.89 0.000 hp/cid -2.8660 0.2995 -9.57 0.000 trlhp n/v -0.22660 -0.80292 0.01496 0.04296 -15.15 -18.69 0.000 0.000 S = 2.442 R-Sq = 85.4% R-Sq(adj) = 85.4% Analysis of Variance Source DF 

## ss MS 

### F P Regression Residual Error 7 1806 63066.4 10771.8 9009.5 6.0 1510.52 0.000 Total 1813 73838.2 

### Thecorrelation using the In method is better at 92.6% 

### and the normal probability plots and residuals vs. 

### fits indicate that the In function better represents the population.

Submitted by The Alliance of Automobile Manufacturers
- Peg GutmannlMGutmann Page 3 of 6 Date 

### IE 

### -1403061 .doc Date Revised: 

### 3/12/2004

### Citv Data 

### Stepwise Regression: In mpg versus clt, drive, 

# ... Alpha-to-Enter: 0.15 Alpha-to-Remove: 0.15 Response is In mpg on 8 predictors, with N = 1833 Step Const ant 1 10.462 2 10.137 3 9.923 4 9.625 5 9.450 6 9.505 In n/v 0.028 -0.159 -0.168 -0.163 -0.145 -0.145 T-Value 1.73 -10.31 -11.37 -11.45 -10.27 -10.27 P-Value 0.085 0.000 0.000 0.000 0.000 0.000 In etw -0.863 -0.582 -0.497 -0.460 -0.486 -0.490 T-Value -38.07 -26.73 -22.78 -21.68 -23.05 -23.21 P-Value 0.000 0.000 0.000 0.000 0.000 0.000 In trlhp -0.142 -0.113 -0.170 -0.177 -0.155 -0.181 T-Value -9.63 -9.03 -13.40 -14.39 -12.61 -11.24 P-Value 0.000 0.000 0.000 0.000 0.000 0.000 In cid -0.270 -0.200 -0.196 -0.158 -0.160 

### T- Va lue -27.05 -18.29 -18.66 -13.97 -14.09 P-Value 0.000 0.000 0.000 0.000 0.000 In hp 0.1277 0.1327 -0.1299 0.1226 T -Value -13.22 -14.25 -14.19 -12.76 P -Value 0.000 0.000 0.000 0.000 WTI 0.0818 0.0818 0.0809 T-Value 11.92 12.13 11.99 P-Value 0.000 0.000 0.000 drive 0.0333 0.0336 T -Value 8.27 8.33 P-Value 0.000 0.000 c/t T-Value 0.0150 2.48 

### P-Value 0.013 S 0.0830 0.0701 0.0670 0.0646 0.0634 0.0633 R-Sq 81.66 86.90 88.05 88.91 89.31 89.35 R-Sq(adj ) 81.63 86.87 88.01 88.87 89.27 89.30 C-P 1314.7 419.1 225.4 79.7 13.1 9.0 

### Conclusion

# - all significant except c/t, correlation improves with the addition 

### of the indicators. 

### RegressionAnalysis: In mpg versus In etw, In n/v, 

# ... (all parameters) The regression equation is In mpg = 9.51 - 0.490 In etw - 0.181 

### In trlhp

- 0.145 In n/v 

### + 0.0150 c/t 

### + 0.0336 drive
- 0.160 In cid

- 0.123 In hp 

### + 0.0809 WTI Predictor Coef SE Coef T P Constant 9.5054 0.1566 60.69 0.000 In etw -0.49040 0.02113 -23.21 0.000 In trlhp -0.18127 0.01613 -11.24 0.000 In n/v -0.14482 0.01411 -10.27 0.000 c/t 0.015014 0.006055 2.48 0.013 drive 0.033561 0.004027 8.33 0.000 In cid -0.15956 0.01132 -14.09 0.000 In hp -0.122576 0.009607 -12.76 0.000 WTI 0.080855 0.006741 11.99 0.000 S = 0.06334 R-Sq = 89.3% R-Sq(adj) = 89.3% Submittedby The Alliance of Automobile Manufacturers

### - Peg Gutmann/MGutmann Page4 of 6 Date I: 

### -140306 1

### .doc Date Revised: 

### 3/12/2004Analysis 

### of Variance Source DF 

### ss MS F P Regression 8 61.3597 7.6700 1911.91 0.000 Residual Error 1824 7.3173 0.0040 Total 1832 68.6770 Source DF Seq SS In etw 1 55.4431 In trlhp 1 0.6180 In n/v 1 0.0205 C/ t 1 0.4107 drive 1 1.8484 In cid 1 1.8583 In hp 1 0.5837 W TI 1 0.5771

Regression Statistics Multiple R 0.94522351 R Square 0.893447484 Adjusted R Square 0.8929801 48 Standard Error 0.063339575 0bservations 1833 ANOVA df 

### ss MS F Significance F Rearession 8 61.35930737 7.6699134 1911.79 0 Residual 1824 7.317708865 0.0040119

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% InterceDt 9.507 0.157 60.672 0.000 9.199 9.814 cit 0.01 5 0.006 2.468 0.014 0.003 0.027 drive 0.034 0.004 8.329 0.000 0.026 0.041 In cid -0.160 0.011 -14.097 0.000 -0.182 -0.137 In hp -0.123 0,010 -12.768 0.000 -0.141 -0.104 In nlv -0.145 0.014 -10.272 0.000 -0.173 -0.117 In etw -0.490 0.021 -23.206 0.000 -0.532 

### -0.449 Intrlhp -0.181 0.016 -11.227 0.000 -0.213 -0.149 WTI 0.081 0.007 11.998 0.000 0.068 0.094

SubmittedbyThe Allianceof Automobile Manufacturers

### - Peg GutmannlMGutmann Page 5 of 6 Date 

### IE -1403061 .doc Date Revised: 3/12/2004

### Highway 

### data 

### Stepwise Regression: In mpg versus clt, drive, 

# ... Alpha-to-Enter: 0.15 Alpha-to-Remove: 0.15 Response is In rnpg on 8 predictors, with N = 1810 Step 3 4 5 6 7 Constant 5.153 7.434 9.423 9.235 9.082 8.999 8.949 

### In n/v 0.100 -0.231 -0.272 -0.253 -0.249 -0.252 -0.252 T-Value 6.90 -17.79 -22.14 -20.97 -20.98 -21.36 -21.40 P-Value 0.000 0.000 0.000 0.000 0.000 0.000 0.000 In trlhp 0.7635 -0.5620 0.4519 0.4309 -0.4335 -0.4545 -0.4323 T-Value -80.45 -67.68 -44.99 -43.30 -44.20 -43.80 -32.03 P-Value 0.000 0.000 0.000 0.000 0.000 0.000 0.000 In cid -0.3145 0.2506 0.2067 -0.2064 -0.1834 -0.1822 T-Value -41.84 -31.66 -23.64 -23.98 -19.48 -19.35 P-Value 0.000 0.000 0.000 0.000 0.000 0.000 In etw -0.298 -0.325 -0.307 -0.276 -0.272 T-Va lue -17.08 -18.96 -18.05 -15.54 -15.26 P-Value 0.000 0.000 0.000 0.000 0.000 drive 0.0363 0.0359 0.0351 0.0349 T-Value 10.56 10.59 10.44 10.40 P-Value 0.000 0.000 0.000 0.000 WTI 0.0440 0.0456 0.0466 T-Value 7.54 7.87 8.05 P-Value 0.000 0.000 0.000 In hp T-Value -0.0438 -5.77 -0.0500 -6.28 P-Value 0.000 0.000 c/t T-Value -0.0129 -2.56 P-Value 0.010 S 0.0840 0.0599 0.0556 0.0540 0.0531 0.0527 0.0526 R-Sq 82.14 90.93 92.19 92.65 92.87 93.00 93.03 R-Sq (ad] ) 82.12 90.92 92.17 92.63 92.85 92.97 92.99 C-P 2808.4 540.2 216.3 101.0 44.9 13.6 9.0 Conclusion, all parameters are significant, correlation improves with addition of parameters. 

### RegressionAnalysis: In mpg versus In etw, c/t, ...( all parameters) The regression equation is In mpg = 8.95 - 0.272 In etw - 0.0129 c/t 

### + 0.0349 drive
- 0.182 In cid

- 0.252 In n/v - 0.432 In trlhp - 0.0500 In hp 

### + 0.0466 WTI Predictor Coef SE Coef T P Constant 8.9491 0.1321 67.76 0.000 In etw -0.27157 0.01780 -15.26 0.000 c/t -0.012949 0.005053 -2.56 0.010 drive 0.034914 0.003358 10.40 0.000 In cid -0.182196 0.009417 -19.35 0.000 In n/v -0.25205 0.01178 -21.40 0.000 In trlhp -0.43230 0.01350 -32.03 0.000 In hp -0.050031 0.007963 -6.28 0.000 WT I 0.046623 0.005792 8.05 0.000 Submitted byThe Alliance of Automobile Manufacturers

### - Peg Gutmann/MGutmann Page 6 of 6 Date 

### IC -1403061 

### .doc Date Revised: 3/12/2004S = 0.05259 R-Sq = 93.0% R-Sq(adj) = 93.0% Analysis of Variance Source DF 

### ss MS F P Regression 8 66.4320 8.3040 3002.89 0.000 Residual Error 1801 4.9804 0.0028 Total 1809 71.4124 Source 

### DF Seq 

### SS

In etw 1 54.6247 drive 

### c/t 1 1 3.5881 2.6664 In cid 1 0.7294 In n/v 1 1.7560 In trlhp 

### In hp 1 1 2.7965 0.0917 W TI 1 0.1792

SUMMARY OUTPUT Regression Statistics Multiple R 0.96460 R Square 0.93045 Adjusted R Square 0.93014 Standard Error 0.05247 Observations 1810 ANOVA df 

### ss MS F SignificanceF Regression 8 66.325 8.291 3011.906 0 Residual 1801 4.957 0.003 Total 1809 71.282 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 8.948 0.132 68.002 0.000 8.690 9.206 clt -0.012 0.005 -2.442 0.015 -0.022 -0.002 drive 0.035 0.003 10.454 0.000 0.028 0.042 In cid -0.180 0.009 -19.151 0.000 -0.1 98 -0.161 In etw -0.274 0.018 -15.427 0.000 -0.308 -0.239 In nlv -0.251 0.012 -21.369 0.000 -0.274 -0.228 In trlhp -0.434 0.013 -32.135 0.000 -0.460 -0.407 In hp -0.049 0.008 -6.1 86 0.000 -0.065 -0.034 WTI 0.047 0.006 8.181 0.000 0.036 0.059

Submittedby The Alliance of Automobile Manufacturers

### - Peg GutmannlMGutmann Page 7 of 6 Date I: -1403061.doc Date Revised: 

### 3/12/2004