1 

 UNITED STATES ENVIRONMENTAL PROTECTION AGENCY 

 ANN ARBOR, MI 48105 

 

September 20, 2010 

 OFFICE OF 

AIR AND RADIATION 

MEMORANDUM

SUBJECT: Heavy-Duty Coastdown Test Procedure Development 

FROM: C. Sze, P. Gururaja, A. Kopin, Z. Guerra and L. Sanchez, Assessment and 

Standards Division 

L. Bachman, Transportation and Regional Programs Division 

C. Jackson and J. Davis, Compliance and Innovative Strategies Division 

TO: Docket EPA-HQ-OAR-2010 

Background

EPA has conducted several coastdown testing programs to evaluate the feasibility 

of heavy-duty truck coastdown. The first program was undertaken in Michigan and Ohio 

to develop the test procedure using two Class 4 pickup and delivery trucks, one Class 6 

truck, two Class 7 buses, and two Class 8 sleeper tractors, combined with either a flatbed 

or a box trailer at several payloads. The second program, done in California, was to 

apply our proposed test procedure to gather baseline aerodynamic data for one Class 7 

and twelve Class 8 tractor and trailer configurations. Coastdown testing was also 

performed in Texas for three SmartWay Class 8 sleeper tractors, each combined with a 

box trailer. 

Summary of Analyses

1) Coastdown Testing Procedure Development – Michigan and Ohio 

Test Vehicles and Instrumentation 

To assess the feasibility of using coastdown to determine road load characteristics 

for trucks, a number of heavy-duty trucks were tested. EPA, through the contractors 

URS Corporation1 (United Research Services, formerly EG&G Technical Services) and 

Transportation Research Center Inc.2 in Ohio (TRC), carried out coastdown testing using 

SAE test method J22633

 for two Class 4 and one Class 8 trucks.4,5 The EPA testing crew 

also coastdown tested multiple Class 8 truck configurations. We chose Route M-50 

between Dundee and Britton in Michigan, based on its favorable road condition, 

straightness, negligible grade, and ample distance between stop lights. Prior to 
2 

coastdown testing, the testing crew would monitor the forecast closely for low winds and 

no precipitation before departing for Route M-50. Testing was performed during 

overnight hours to minimize both traffic and wind. 

In general, we followed the SAE J2263 procedure, with a few modifications 

customized for our particular circumstances. We constructed a boom to be rigidly 

attached the hood of the tractor. The boom setup which we fabricated for two of our test 

vehicles is shown in Figure 1. This boom extended 2-3 meters in front of the heavy-duty 

vehicle where we fixed an ultrasonic anemometer that measured wind speed and wind 

direction. Table 1 lists the Class 6 and Class 8 truck configurations which we tested on 

Route M-50. 

Figure 1 – Boom Setup on a Bus and a Class 8 Truck for Coastdown Testing 

Each night, we coasted the vehicle down at least ten times (five in each direction) 

from an approximate top speed of 68 mph to an approximate low speed of 6 mph. In 

certain cases, we also ran partial or “knitting” runs from approximately 68 mph to 30 

mph and 40 mph to 6 mph. These knitting runs were to investigate the feasibility of 

partial coastdowns when road lengths are insufficient for full testing. 
3 

Table 1 – Truck Configurations Tested by EPA around Dundee, Michigan 

Date Tractor Trailer Payload Frontal Area 

[m2] 

Weight 

[lb] 

August 5, 2009 Freightliner FL60 N/A Full 9.2 (assumed) 20640 

August 6, 2009 Freightliner FL60 N/A Full 9.2 (assumed) 20640 

September 1, 2009 International 9200i Flatbed Full 9.2 77940 

September 2, 2009 International 9200i Flatbed Full 9.2 77940 

September 3, 2009 International 9200i Flatbed Full 9.2 77940 

September 18, 2009 International 9200i Flatbed Half 9.2 55240 

September 23, 2009 International 9200i Flatbed Empty 9.2 31380 

September 24, 2009 International 9200i 53-ft box Full 9.2 77780 

September 25, 2009 International 9200i 53-ft box Full 9.2 77780 

One of the modifications we made to the J2263 test procedure was regarding the 

order which test runs was completed. The SAE test procedure J2263 calls for the 

following test runs to be completed, “A minimum of 10 runs are made in alternating 

directions; 5 runs in each direction.” J2263 also specifies that after one run, the next run 

shall be in the opposite direction. However, in order to reduce our presence on state and 

county roads and perform more tests during core testing hours, we performed two to four 

consecutive runs in the same direction before turning around and running tests in the 

opposite direction as shown in Figure 2. This modification was then accounted for 

during data processing, for example, when using the SAE J2263 software program which 

looks for consecutively numbered files to be in opposite directions. We renumbered the 

files such that this was the case (e.g. when looking at Figure 2 below, Runs 1 & 8, 2 & 7, 

3 & 6, and 4 & 5 were matched consecutive pairs). We are requesting comment on the 

inclusion of this alternative to the SAE J2263 test procedure in our NPRM. 

Figure 2 – Modified Pair Testing 

EPA Data Quality Check Tool - Post Processor of Coastdown Data 

Upon data collection, the Race Technologies analysis software package outputs 

5hz “.csv” file which is subsequently quality checked using a LabView-based data 

quality check tool created by EPA that also organizes and outputs data in a format 

required by the SAE J2263 software program for generating coastdown coefficients. As 

each file is read using the EPA data quality check tool as shown in Figure 3, the user can 

look at three graphs along with multiple indicators to determine if the data gathered is 
4 

valid. Another feature of this tool is to allow the user to pick the proper data range to 

output for analysis. 

Of the three graphical displays, the first shows vehicle speed versus time. On this 

graph, there are two vertical lines setting the upper and lower boundaries of the vehicle 

speed data in “mph” that will be used for coastdown calculations. The next graph shows 

vehicle speed and uncorrected relative wind speed versus time. The purpose of this graph 

is to examine if the anemometer was working properly and if its measurement was 

affected by its position on the vehicle. The last graph displays the uncorrected yaw angle 

versus vehicle speed. This graph would reveal whether the anemometer reading was 

affected by any strong crosswind and/or passing traffic. The indicators display the 

following information: file name, heading direction (determined from the GPS signal), 

maximum yaw angle in degrees, maximum relative vertical wind direction in degrees, 

maximum road grade, maximum wind speed in meters per second, average relative wind 

direction at maximum speed in degrees, and the average, minimum and maximum 

ambient temperature, pressure and humidity. After the user looks over the indicators and 

graphs, the user can select if the data should be used for analysis. After the user goes 

through all of the individual files, the program will calculate the yaw angle offset and the 

anemometer correction. 

Figure 3 – Screenshot of Coastdown Data Quality Check Tool 

The purpose of the yaw angle offset is to correct the anemometer’s measurement 

of yaw for any error in mounting it not inline with the vehicle. The yaw offset is 

determined by taking the average yaw angle at maximum vehicle speed for each run and 

averaging all the runs in the same direction together and then averaging the average of 
5 

the East and West runs together. By averaging the runs in the same direction first, this 

practice insures that there is no bias due to more runs in one direction. The averages in 

each direction are averaged together to cancel out the wind effect. This method assumes 

that the wind is constant for all the runs that are processed together. 

The anemometer correction is used to account for how the wind piling up in front 

of the vehicle affects the relative wind speed measurement. If the anemometer is placed 

too close to the vehicle, the pressure in front of the vehicle due to the aerodynamic forces 

will cause the anemometer to read low. The anemometer correction is calculated by 

dividing the vehicle speed by the relative wind speed for each point and averaging all the 

points in one run together. All the runs going in the same direction are averaged together 

first and then the averages of each direction are averaged together. This method assumes 

that the wind is constant for all the runs that are processed together. 

The corrections are applied to each run and then the program shows the two 

corrections along with a graph of the vehicle speed and relative wind speed versus time 

and a graph of yaw angle versus time. The user can refer to these graphs and indicators 

to check if the correction looks reasonable. After the graphs for all the runs are shown, 

the program outputs a 5hz tab delimited file of the vehicle speed in miles per hour, 

corrected relative wind speed in miles per hour and corrected yaw angle in degrees along 

with a summary file of all the runs. The tab delimited files are labeled “DATA.#”. The 

“#” is set by the order in which the “.csv” files are selected. The west traveling coast 

down test will be labeled with an odd number and the east heading tests will be labeled 

with an even number. The reason for this is that the J2263 software program assumes 

that the coastdown runs are done in pairs with the next run being run in the opposite 

direction as the previous. 

Yaw offset 

1, 2,

1 2

1, 2,

1, , 2, ,

5 5

1 1

1 2

5 5

Yaw Offset = 

2

j k

j k

N N

N N j i k i

i N i N

j j

Yaw Yaw

N N

= − = −

= = +

∑ ∑

∑ ∑

Anemometer Correction (ß)

1, 2,

1 2

1, , 2, ,

1 1, , 1 2, ,

1 1, 1 2,

1 2

2

j k N N

j i k i

N N

i j i i k i

j j j k

VS VS

RW RW

N N

N N β

= =

= = +

=

∑ ∑

∑ ∑

1 = represents the tests going in one direction 

2 = represents the tests going in the opposite direction 

i = an indexing variable that represents each data point in a test 
6 

j = an indexing variable that represents each test run in the direction of “1” 

k = an indexing variable that represents each test run in the direction of “2” 

N1,j = the number of data points within the i-th test going in the direction of “1” 

N2,j = the number of data points within the i-th test going in the direction of “2” 

N1 = the number of tests going in the direction of “1” 

N2 = the number of tests going in the direction of “2” 

Yaw1,j,i = yaw angle for the i-th data point in the j-th test going in the 1st direction 

Yaw2,k,i = yaw angle for the i-th data point in the k-th test going in the 2nd direction 

VS1,j,i = vehicle speed for the i-th data point in the j-th test going in the 1st direction 

VS2,j,i = vehicle speed for the i-th data point in the j-th test going in the 2nd direction 

RW1,j,i = relative wind speed for the i-th data point in the j-th test going in the 1st 

direction 

RW2,k,i = relative wind speed for the i-th data point in the k-th test going in the 2nd 

direction. 

Because the SAE J2263 software program in some instances produced 

questionable output from vehicle coastdown data inputted (e.g., unrealistic Cd >1 or <0), 

the EPA also looked into alternative methodology of data analysis using statistical 

software, SAS® and equations provided in the SAE J2262 coastdown protocols to 

generate mixed models.6 

Use of Coastdown Data for Vehicle Modeling 

This section details the process which we undertook upon receiving raw 

coastdown data files. First, we determined which runs were valid, based on instrument 

readings, weather, and other criteria using the EPA data quality check tool. During 

travel, air will “pile up” near the front of the tractor. This causes our anemometer wind 

speed readings to be offset from actual wind speed. To correct for this, we calculated the 

ratio between the vehicle speed and measured wind speed at each time interval. We then 

averaged the ratio by run direction, followed by averaging each run direction’s ratio for 

each date and applied this ratio back to the measured wind speed to estimate actual wind 

speed. 

Equation 1 ∑ ∑ ⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ = dir i r meas dir i

dir i

i dir

r i r meas dir i V

V

n

V V

, , ,

,

,

, , , ,

1

2

1

We observed an offset to the anemometer’s wind direction measurements. We 

corrected this by assuming that at high speeds, wind direction is head-on (zero degrees). 

For each date, we averaged the first five seconds (25 measurements for 5-hz data) of 

wind direction for each run direction. We then averaged the two directions’ average. We 

then subtracted the resulting value from all of the measured wind direction values to get 

our correct wind direction. 

Equation 2 ∑ ∑ ⎥

⎥

⎦

⎤

⎢

⎢

⎣

⎡ = − dir i=

meas dir i

i dir

i meas i Y

n

Y Y

25

1

, ,

,

,

1

2

1
7 

In general, the J2263 analysis method and equations were used as a foundation for 

this analysis: 

Equation 3 ds

dh A B V C V DV a a Y a Y a Y a Y Mg dtdV − Me = m + m + m + r ( + + + + ) ± 4

4

3

3

2

0 1 2

2 2

We used a mixed model (through SAS® software) to describe our 5-hz data with 

the above equation. A mixed model allows us to accurately predict the mean coefficients 

for each vehicle, while accounting for the scatter within each run and also the run-to-run 

variability when determining the standard error of the coefficient estimates. This takes 

into account that measurements are not independent within each run, but each run is 

independent from all other runs. 

The equations below represent the versions of Equation 3 we modeled to 

determine means and significances of each of the variables. As an initial simplification, 

a1, a3, and a4 were eliminated in all iterations since we determined that yaw angle did not 

vary enough during testing to warrant such a complex polynomial characterization. We 

also set a0=1 so that the drag coefficient could be characterized by the D term. Since our 

elevation change was negligible in the stretch of road on which we conducted coastdown 

testing, the grade term was also eliminated for all runs. The following mixed models 

were run: 

Equation 4 

Equation 5 

(1 )

2

2

2 2 A B V C V DV a Y

dt

dV − Me = m + m + m + r + , rewritten as 

2 2 2 2 A B V C V DV EV Y

dt

dV − Me = m + m + m + r + r , where D a = E

2

MM1 

Equation 6 2 2

e Am BmV CmV DVr dt

dV − M = + + + MM2 

Equation 7 2 2 2 A B V DV EV Y

dt

dV − Me = m + m + r + r MM3 

Equation 8 2

e Am BmV DVr dt

dV − M = + + MM4 

Equation 9 2 2 2 A DV EV Y

dt

dV − Me = m + r + r MM5 

Equation 10 2

e Am DVr dt

dV − M = + MM6 

Based on statistical significance of the various effects, one of the mixed models 

was chosen as the model to appropriately determine the road load coefficients. For heavy 

duty trucks, this was usually MM6. 
8 

Mixed Model Results 

In each mixed model (MM1-MM6), we found that the Bm, Cm, and E were not 

consistently significant from zero. As examples, models MM4 and MM6 are described 

below. In MM4, the results consistently show that Bm is not significant from zero. Table 

2 summarizes these results. The inclusion of Bm often causes the estimates and 

uncertainties of the other terms to vary. 

Table 2 – Mixed Model MM4 Shows No Significant Road Load Linear with Vehicle Speed 

Date Truck configuration 

tractor-/trailer-payload

Am

[lb] 

% Std 

err 

Sig 

from 

zero? 

Bm

[lb/mph] 

% Std 

err 

Sig 

from 

zero? 

D 

[lb/mph2

] 

% Std 

err 

Sig 

from 

zero? 

5-Aug-09 FL60_N/A_full 153.8 7.75% Yes 0.165 497.0% No 0.143 9.64% Yes 

6-Aug-09 FL60_N/A_full 137.7 5.24% Yes 1.105 41.4% Yes 0.127 5.86% Yes 

1-Sep-09 Int’l_flatbed_full 490.5 10.94% Yes -2.070 -177.7% No 0.233 25.87% Yes 

2-Sep-09 Int’l_flatbed_full 483.3 7.69% Yes -2.065 -122.7% No 0.237 17.99% Yes 

3-Sep-09 Int’l_flatbed_full 551.5 7.76% Yes -6.123 -47.4% No 0.291 16.55% Yes 

18-Sep-09 Int’l_flatbed_half 372.2 9.72% Yes -1.979 -127.8% No 0.244 17.38% Yes 

23-Sep-09 Int’l_flatbed_empty 226.3 9.38% Yes 1.153 119.9% No 0.174 12.27% Yes 

24-Sep-09 Int’l_box_full 521.5 6.51% Yes -3.480 -63.15% No 0.248 14.11% Yes 

25-Sep-09 Int’l_box_full 495.7 8.47% Yes -1.149 -238.0% No 0.208 21.04% Yes 

In MM6, the elimination of Bm shows confident and stable estimates of Am and D, 

with lower relative standard errors. This indicates that the road load curve is best 

described by just Am and D. 

Table 3 – Mixed Model MM6 Shows the Most Confident Estimates of A and D. 

Date Truck configuration 

(tractor_trailer_payload) Am [N] Am [lb] % Std error D [N/(m/s)2

] D [lb/mph2] % Std error

5-Aug-09 FL60_N/A_full 693.9 156.0 3.81% 3.24 0.145 2.05% 

6-Aug-09 FL60_N/A_full 676.8 152.2 2.63% 3.23 0.145 1.13% 

1-Sep-09 Int’l_flatbed_full 2060.3 463.2 4.85% 4.45 0.200 6.08% 

2-Sep-09 Int’l_flatbed_full 2030.6 456.5 3.71% 4.51 0.203 4.59% 

3-Sep-09 Int’l_flatbed_full 2093.6 470.7 3.89% 4.25 0.191 5.55% 

18-Sep-09 Int’l_flatbed_half 1539.8 346.2 3.92% 4.71 0.212 4.09% 

23-Sep-09 Int’l_flatbed_empty 1076.2 242.0 4.53% 4.27 0.192 2.39% 

24-Sep-09 Int’l_box_full 2119.1 476.4 3.87% 4.32 0.194 4.06% 

25-Sep-09 Int’l_box_full 2136.5 480.3 4.12% 4.23 0.190 4.88% 
9 

Compared to the MM4, MM6 produces more confident mean coefficient values. 

Also, for the same configurations, the MM6 shows better day-to-day variability, 

confirming that the coastdown procedure is repeatable from one day to the next. Often, 

the MM6 model is used to simplify the road load versus speed curve through rolling 

resistance and aerodynamic drag coefficients. The EPA MOVES heavy-duty inventory 

model and the CRC E-55/59 chassis dynamometer emissions test program are two 

examples of this. In general, the equation implemented during a coastdown is: 

Equation 11 2

2

1 Mg Ac V

dt

dV − Me = μ + ρ D

Therefore, 

Equation 12 Mg

Am μ = and 

A

D

cD 2ρ = Equation 13 

Equations 11 and 12 assume that the rolling resistance coefficient μ is wholly 

contained in the Am coefficient and the drag coefficient Cd is wholly contained in the D

coefficient. The equations also imply that any values of Bm and Cm that would be used in 

the other mixed models are mechanical drag forces, other than rolling resistance, that are 

dependent on vehicle speed. To check the reasonability of our results and feasibility of 

using our coefficients to accurately determine μ and Cd, we can compare our results to 

realistic values of rolling resistance and drag coefficients. 

Rolling Resistance Coefficient 

For the International truck, we recorded the tire model and obtained different 

laboratory results of tire rolling resistance coefficients. These values were determined 

through the SAE J1269 standard. This standard does not contain a provision that allows a 

laboratory result be corrected against a reference laboratory result. As a result, each 

laboratory has its own bias for any given tire. When we weighed the truck, we recorded 

the weight measured over each axle: steer, drive, and trailer. Since we had no more than 

one tire model on any one axle, we can weight-average the laboratory rolling resistance 

coefficients to estimate the truck’s overall rolling resistance coefficient. 

Equation 14 ( ) steerM steer driveMdrive trailerMtrailer M μ = μ + μ + μ

1

Figure 4 compares our coastdown rolling resistance results with those from three 

different tire labs. We are not naming the tire models or the laboratories to protect 

confidential business information. The dimensionless rolling resistance coefficient is 

multiplied by 1000 for convenience (resulting “unit” is often referred to as kg/metric ton). 

There are only three different labs, with four unique weightings (flatbed full, 

flatbed half, flatbed empty, and box full) for each lab. Lab results were only available for 

the tires used on the International truck. Our coastdown results show reliable day-to-day 

repeatability for the same truck configuration (Sep 1-3, Sep 24-25). Also, when we 
10 

reduced the weight on the flatbed trailer, we found that our coastdown data produced a 

higher theoretical tire rolling resistance. This is most likely due to the fact that reducing 

weight from full payload increases the relative weight over the drive axle. Since the tires 

on the drive axle have a higher rolling resistance coefficient (inverse relation with grip 

for a given tire material and surface), the overall rolling resistance coefficient increased. 

This is confirmed by the lab tests, which showed higher rolling resistance coefficients for 

the drive and steer axles tire models. Our coastdown results do, however, show a larger 

increase in coefficient due to complete payload removal compared to the lab results. 

0

1

2

3

4

5

6

7

8

9

FL60_N/A_fullFL60_N/A_full

Int'l_flatbed_fullInt'l_flatbed_fullInt'l_flatbed_full

Int'l_flatbed_half

Int'l_flatbed_empty

Int'l_box_fullInt'l_box_full

5-Aug-09 6-Aug-09 1-Sep-09 2-Sep-09 3-Sep-09 18-Sep-09 23-Sep-09 24-Sep-09 25-Sep-09

Rolling resistance coefficient [kg/metric ton]

Coastdown RR

Lab A

Lab B

Lab C

3 Lab avg

Figure 4 – Coastdown-determined and Independent Lab Rolling Resistance Coefficients 

Match Reasonably Well 

Aerodynamic Drag Coefficient 

We estimated frontal area of the International truck to be 99 ft2

 (9.2 m2) by 

measuring the various dimensions of the tractor cab and other equipment such as exterior 

mirrors and tires. We used this value as a placeholder estimate for the FL60 vehicle also. 

Using these frontal area estimates and Equation 13, Figure 5 shows our coastdownestimated drag coefficients for each date and truck configuration. 

Unlike rolling resistance, we do not expect our drag coefficient to change with 

payload removal because the physical configuration of the tractor-trailer is not 

significantly altered, which is reflected in Figure 5. Also, while we are using a frontal 

area of 9.2 m2

 specific to the International tractor, a uniform frontal area, such as an 

average box trailer frontal area or typical tractor frontal area, may be used for all trucks 

of a certain class when determining drag coefficient as an input to the compliance model. 
11 

0.0

0.2

0.4

0.6

0.8

1.0

1.2

FL60_N/A_fullFL60_N/A_full

Int'l_flatbed_fullInt'l_flatbed_fullInt'l_flatbed_full

Int'l_flatbed_half

Int'l_flatbed_empty

Int'l_box_fullInt'l_box_full

5-Aug-09 6-Aug-09 1-Sep-09 2-Sep-09 3-Sep-09 18-Sep-09 23-Sep-09 24-Sep-09 25-Sep-09

Figure 5 – Drag Coefficient Calculated from D from Mixed Model 

Knitting Analysis 

SAE J2263 does allow knitting of a run if the coastdown track or road is not long 

enough for the vehicle to reach the required minimum speed. For a given run in one 

direction, knitting is achieved by gathering coastdown data from the high vehicle speed 

required in SAE J2263 (125 km/h or 77.7 mi/h) to an intermediate speed and gathering 

the data from the intermediate speed to the minimum speed required in SAE J2263 (15 

km/h or 9.3 mi/h). The data from the high and low speed runs should be combined at the 

intermediate speed point to obtain a resulting file that does not have a speed gap or bump, 

enabling the final knitted data to resemble that of a continuous run, as shown in Figure 6. 

When using the SAE coastdown software program, it is very important to have 

both high and low speed data ranges for all the pair runs since incomplete data will 

generate erroneous results. If the data range does not cover the specified high and 

especially minimum vehicle coastdown speeds, then the A, B, and C coefficients 

generated by the SAE software program will produce inaccurate results which is evident 

with a speed vs. aerodynamic force chart generated with the A, B, and C coefficients. 

Figure 7 shows vehicle speed versus aerodynamic force obtained from wellknitted, coastdown speed data for a Class 8 truck In contrast, Figure 8 shows results 

generated from partial speed range data (from 60 mph to 30 mph). Figure 7 shows an 
12 

expected decrease in force as the speed decreases, while Figure 8 shows an unrealistic 

and erroneous increase in force at lower speeds. 

Figure 6 – Example of Data Knitted from Two Separate Speed Ranges (X-axis: coastdown time in 

seconds, Y-axis: vehicle speed) 

0

200

400

600

800

1000

1200

1400

0 10 20 30 40 50 60 70 80 90

Vehicle Speed (mph)

Force (lbf)

Figure 7 – Speed vs. Aerodynamic Force Chart Generated from a Complete Speed Data Set (77 mph 

to 9 mph). 
13 

0

500

1000

1500

2000

2500

3000

0 10 20 30 40 50 60 70 80 90

Vehicle Speed (mph)

Force (lbf)

Figure 8 – Speed vs. Aerodynamic Force Chart Generated from an Incomplete Speed Data Set (60 

mph to 30 mph) 

While knitting is allowed for data encompassing complete vehicle speed range, it 

is not the preferred method. Whenever possible, the run should be a continuous run to 

avoid introducing another source of possible error into the procedure. 

2) Automotive Testing and Development Services Coastdown Testing in California 

Beginning in February 2010, EPA, through contractors URS Corporation1 and 

ATDS7

 (Automotive Testing and Development Services, Inc. based in California), 

conducted extensive coastdown testing using SAE test methods J12638

 and J22631 with a 

total of 24 configurations, including Class 7/8 combination tractors as well as Class 2b 

pickup trucks and van. Table 4 shows the test matrix. 

Table 4 – Coastdown Testing Configurations Matrix 

Configuration Class 8 Class 7 Pickup Truck Van 

Box 5 

Flatbed 5 1 

Tanker 1 

Twin 1 

Weight 1 6 1 

Weight 2 3 1 

TOTAL 12 1 9 2 
14 

The vehicles tested included six pickup trucks and one van. The van and three of 

the six pickup trucks were ballasted at two different weights for testing. One Class 7 day 

cab was tested with a flatbed trailer, while seven Class 8 tractors were combined with 

various types of trailers and tested either as procured tractor configuration or tested after 

retrofitting the tractor with various aerodynamic fairings by the truck dealer. In all, a 

total of twelve Class 8 tractor and trailer combinations were coastdown tested. 

Class 2b Pickup Trucks and Van Coastdown Weights and Results 

A total of seven vehicles have been procured in this category. Four of the Class 

2b vehicles were tested using two different weights. The data are currently being 

gathered and/or analyzed. Thus far we have found the existing coastdown protocols used 

by light-duty manufacturers appropriate for vehicles in this category or weight class. 

Class 7/8 Tractor and Trailer Coastdown Configurations and Results 

One Class 7 and seven Class 8 tractors have been procured to produce a total of 

thirteen tractor-trailer coastdown configurations, shown in Table 5. These tractors 

included mostly late models, day and sleeper cabs of varying roof heights that are 

equipped with and without aerodynamic fairings. For our Class 7/8 coastdown study, 

each tractor is combined with one or more trailer types, including several mismatches 

between tractor roof height and trailer type. While we have obtained some preliminary 

results, this work is in progress. Our analysis using MM6 on a number ‘regulatory class’ 

tractor and trailer combinations produced the aerodynamic drag coefficients listed in 

Table 6. 

Table 5 – Class 7/8 Tractor and Trailer Configurations for Coastdown Testing 

Truck 

Class 

Cab 

Type Roof Height Aero Treatment Trailer Type 

 Box Flatbed Tanker Twin 

Aero High 

Non-aero 

Aero √ 

Class 7 Day 

Low 

Non-aero 

Aero √ High Non-aero √ √ 

Aero Day 

Low 

Non-aero √ √ 

Aero √ √ √ High Non-aero √ 

Aero √ Mid Non-aero 

Aero √* 

Class 8 

Sleeper 

Low 

Non-aero √ 

* This tractor has not been procured to date. 
15 

Table 6 – Aerodynamic Drag Coefficients Derived from ATDS Coastdown Testing 

Truck 

Class Cab Type Roof Height Aero Treatment 

Cd (Frontal Area 

Default in m2

) 

High Aero n/a Class 7 Day 

Low/Mid Aero 0.83 (6) 

High Aero/Non-aero 0.59/0.60 (9.8) Day Low/Mid Non-aero 0.73 (6) 

High Aero 0.54 (9.8) 

Mid Aero tbd 

Class 8 

Sleeper 

Low Non-aero tbd 

Using the same methodology and MM6, EPA also generated aerodynamic drag 

coefficients for the two Class 8 trucks tested at TRC and NVFEL. These results are listed 

in Table 7. 

Table 7 – Aerodynamic Drag Coefficients Derived from TRC and NVFEL Coastdown Testing 

Truck configuration Test Location Frontal Area 

[m2

] Cd 

Class 8 conventional sleeper International 9200i #1 TRC 9.8 0.71 

Class 8 conventional sleeper International 9200i #2 NVFEL 9.8 0.70 

In addition, we observed that a mismatch between tractor and trailer roof height, 

especially for a low roof tractor, affects the coastdown D term, which characterizes the 

truck aerodynamics. As seen in Table 8, a low roof tractor combined with a box trailer 

produced a D term that is significantly higher than that from the same low roof tractor 

combined with a flatbed. The effect seems less pronounced when a high roof tractor is 

combined with a flatbed, although this is still not an optimum pairing. We expect the 

impact of crosswinds in the real world would exacerbate all the inefficiencies due to 

tractor and trailer mismatches. 

Table 8 – Tractor/Trailer Mismatches Affect Coastdown Aerodynamic Terms 

Class 8 Truck configuration D [lb/mph2

] Mismatch? 

Class 8 day – low roof – non-aero – flatbed 0.115 No 

Class 8 day – low roof – non-aero–box 0.196 Yes 

Class 8 day – high roof – non-aero–flatbed 0.165 Yes 

Class 8 day – high roof – non-aero – box 0.154 No 

Class 8 day – high roof – aero – box 0.151 No 

Class 8 sleeper – high roof – aero – flatbed 0.139 Yes 

Class 8 sleeper – high roof – aero – box 0.140 No 

Class 8 sleeper – high roof – aero – twin 0.141 No 

3) Southwest Research Institute Coastdown Testing in Texas 

EPA, through its contractor Southwest Research Institute (SwRI)9, conducted 

coastdown tests using SAE test methods J12638

 and J22631 on three SmartWay-certified 

Class 8 tractor-trailers during the period October 2008 through September 2010. The 
16 

tests were conducted on three trucks identified as trucks 555, 598, and 029. Most of the 

earlier J2263 tests were not considered valid due to crosswinds that exceeded the limits 

specified by the test method. In summer 2010, these trucks are being scheduled to be retested per J2263 near Corpus Christi, Texas. 

The J1263 test provides coefficients that allow calculation of road load (RL) as a 

function of speed: 

2 RL = F0 + F2×V

where F0 and F2 are the coefficients derived from the coastdown test and V is the vehicle 

speed. 

The J1263 test requires a minimum of 10 coastdown runs, conducted in 

alternating directions. Coastdown runs in which the wind speed and temperature exceed 

the specified limits are excluded, and a successful test requires a minimum of 5 pairs 

valid coastdown runs. The F0 and F2 coefficients are calculated for each coastdown, and 

the valid coefficients are averaged for the final test coefficients, which are entered into 

the dynamometer control system. 

During tests conducted at Fowlerton, Texas in January and February 2009, 

Southwest Research Institute conducted 12 coastdown runs and obtained 6 valid 

coastdown tests, i.e., 6 paired runs. They conducted one test each for trucks 029 and 598 

and a replicate set of tests for truck 555. However, the coastdown road in Fowlerton was 

not long enough to coast these Class 8 trucks from the specified maximum to minimum 

speeds in one continuous setting. Therefore, SwRI knitted data for those runs. 

Additional tests without requiring knitting, were conducted at an alternate test road near 

Corpus Christi, Texas during June 2009 and November 2009. In summer 2010, 

coastdown tests per SAE J2263 are again being conducted for these trucks near Corpus 

Christi, Texas. 

Results of coastdown coefficients of valid runs using knitted data for truck 555 

show considerable run-to run variability for a given day’s test. However, the variability 

of the final test results, which are averages of the individual runs, is much less, with a 

coefficient of variability (COV) of 7.3% for F0 and 8.3% for F2 (Table 9) as compared to 

COV values of 15-27% for the individual coastdown runs. 

Table 9 – Corrected Average Values of Coastdown Coefficients for Truck 555, as Determined by 

SAE J1263 Test Method from Both Knitted and Whole Run Data 

TEST DATE F0 F2 

10/8/2008 368.13 0.18 

10/10/2008 415.01 0.16 

6/5/2009 422.1 0.19 

Mean 401.75 0.17 

Standard deviation 29.3 0.01 

COV (mean divided by standard deviation) 7.3% 8.28% 
17 

Another SmartWay vehicle, designated as Truck 598, has undergone coastdown 

testing near Corpus Christi recently per SAE J2263. Initial testing of this truck in 2008 in 

Fowlerton, Texas required knitting. In June and November 2009, SwRI repeated testing 

of this truck without knitting near Corpus Christi. Figure 9 compares the road load 

curves derived from a total of four separate coastdown tests conducted on this truck since 

October 2008, when SwRI first started performing coastdown testing/analysis. The road 

load curve generated in October 2008, comprised of only knitted data, is deviant from 

those obtained in subsequent tests. As seen, Figure 9 shows that the July 2010 coastdown 

results generated by MM6, the only test conducted per SAE J2263, coincides very well 

with both results obtained in 2009, which also did not include knitting. 

0

200

400

600

800

1000

1200

0 10 20 30 40 50 60 70

mph

Road Load Force (lbf)

Truck 598 J1263 10/9/08 (Used Knitting)

Truck 598 J1263 6/3/09

Truck 598 J1263 11/18/09

Truck 598 J2263 07/30/10

Figure 9 – Comparison of Truck 598 Coastdown Results Gathered in 2008, 2009 and 2010 

 Coastdown testing is ongoing at ATDS, TRC, and SwRI. Our analysis of raw 

data gathered to date for a number of heavy-duty trucks indicates that coastdown testing 

as per SAE J2263 with slight modifications is feasible for heavy-duty trucks. The 

coefficients derived follow a reasonable, expected trend, which are useful for extracting a 

truck’s aerodynamic drag coefficient and for chassis dynamometer testing using the 

chassis dynamometer test protocol10 to qualify SmartWay certified tractor-trailers. 
18 

References 

1

 URS Corporation, http://www.urscorp.com 

2

 Transportation Research Center Inc., http://www.trcpg.com 

3

 SAE Recommended Practice J2263 “Road Load Measurement Using Onboard Anemometry and 

Coastdown Techniques” December 2008. 4

 Transportation Research Center Inc., “SAE J2263 Road Load Measurement Using Onboard Anemometry 

and Coastdown Techniques,” Final Report Prepared for EG&G Technical Services, Inc. Project Number 

20090915, January 12, 2010. 

5

 Transportation Research Center Inc., “Coastdown Testing of a Heavy Truck,” Final Report Prepared for 

EG&G Technical Services, Inc. Project Number 20090915, February 4, 2010. 

6

 SAS, http://www.sas.com/technologies/analytics/statistics/index.html 

7

 Automotive Testing and Development Services, Inc., http://www.automotivetesting.com 

8

 SAE Recommended Practice 1263, “Road Load Measurement and Dynamometer Simulation Using 

Coastdown Techniques” January 2009. 9

 Southwest Research Institute, http://www.swri.org 

10 U.S. Environmental Protection Agency, SmartWay Fuel Efficiency Test Protocol for Medium and Heavy 

Duty Vehicles – Working Draft, EPA420-P-07-003, November 2007, 

http://www.epa.gov/smartway/transport/documents/tech/420p07003.pdf.