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. Sanc hez, Assessment and Standards Division L. Bachman, Transportation and Regional Programs Division C. Jackson and J. Davis, Complian ce and Innovative Strategies Division

TO: Docket EPA-HQ-OAR-2010

Background

EPA has conducted several coas tdown 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 Cl ass 4 pickup and deliver y 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 a nd 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 Deve lopment – 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 we re tested. EPA, through the contractors URS Corporation 1 (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 J2263 3 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 to2 coastdown testing, the testing crew would monitor the forecast closely for low winds and no precipitation before departing for Rout e 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 set up which we fabricated for two of our test vehicles is shown in Figure 1. This boom ex tended 2-3 meters in front of the heavy-duty vehicle where we fixed an ultrasonic anem ometer that measured wind speed and wind direction. Table 1 lists the Class 6 and Cla ss 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 [m 2 ] Weight [lb] August 5, 2009 Freightliner FL 60 N/A Full 9.2 (assumed) 20640 August 6, 2009 Freightliner FL 60 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 th e 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 pe rformed two to four consecutive runs in the same direction befo re 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 pa irs). 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 Technologie s analysis software package outputs 5hz “.csv” file which is subsequently qu ality 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 fo r 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 indicat ors to determine if th e data gathered is4 valid. Another feature of this tool is to a llow 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 th e 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 la st graph displays the uncorrected yaw angle

versus vehicle speed. This graph would rev eal whether the anemometer reading was affected by any strong crosswind and/or pa ssing 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 progra m 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 inlin e 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 of5 the East and West runs together. By averagin g the runs in the same direction first, this practice insures that there is no bias due to mo re runs in one direction. The averages in each direction are averaged together to can cel 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 wi nd 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 th e 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 vehi cle speed in miles per hour, corrected relative wind speed in miles per hour and corrected yaw angl e 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 labe led 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

j i k i N N 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 i j 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 repr esents each data point in a test6 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” N 1,j = the number of data points within the i-th test going in the direction of “1” N

2,j = the number of data points within the i-th test going in the direction of “2” N 1 = the number of tests going in the direction of “1” N

2 = 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 te st 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 methodol ogy 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 we re 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 th e measured wind speed to estimate actual wind speed.

Equation 1 

# ∑ ∑ ⎥ ⎥ ⎦ ⎤ ⎢ ⎢ ⎣ ⎡ ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛

=
dir i i dir meas r i dir

dir i i dir meas r i r V V

n V V

, , , ,

, , , , , 1
2 1

We observed an offset to the anemomet er’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 i dir meas dir i i meas i Y
n Y Y 25

1 , ,

, , 1
2 17 In general, the J2263 analysis method and equations were used as a foundation for this analysis:

Equation 3 ds dh Mg Y a Y a Y a Y a a DV V C V B A dt dV M

r m m m e ± + + + + + + + = − ) ( 4 4 3 3 2 2 1 0 2 2

We used a mixed model (through SAS® soft ware) 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 erro r 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 vers ions of Equation 3 we modeled to determine means and significances of each of the variables. As an initial simplification,

a 1 , a 3 , and a 4 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 a 0 =1 so that the drag coefficient could be characterized by the D term. Since our elevation change was negligible in the stre tch 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 Y a DV V C V B A dt dV M

r m m m e + + + + = − , rewritten as

2 2 2 2 Y EV DV V C V B A dt dV M

r r m m m e + + + + = − , where D E a =

2 MM1

Equation 6 2 2

r m m m e DV V C V B A dt dV M + + + = − MM2

Equation 7 2 2 2 Y EV DV V B A dt dV M

r r m m e + + + = − MM3

Equation 8 2

r m m e DV V B A dt dV M + + = − MM4

Equation 9 2 2 2 Y EV DV A dt dV M

r r m e + + = − MM5

Equation 10 2

r m e DV A dt dV M + = − MM6

Based on statistical significance of the va rious 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 B m , C m , and E were not consistently significant from zero. As examples, models MM4 and MM6 are described below. In MM4, the results consistently show that B m is not significant from zero. Table 2 summarizes these results. The inclusion of B m 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 A**  **m [lb]**  **% Std**

**err Sig**  **from zero?**  **B m**  **[lb/mph] % Std** 

**err Sig**  **from zero?**  **D [lb/mph**  **2 ]**  **% Std**

**err Sig**  **from zero?** 

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

**6-Aug-09 FL60_N/A_full 137.7 5.24% Y es 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 B m shows confident and stable estimates of A m and D
, with lower relative standard errors. This indicates that the road load curve is best described by just A m and D

.

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

**Date Truck configuration**  **(tractor_trailer_payload) A**  **m [N]**  **A m**  **[lb] % Std error**  **D [N/(m/s) 2**  **] D [lb/mph**  **2 ]**  **% 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 re peatable 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 coefficien ts. 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 V Ac Mg dt dV M D e ρ μ + = − Therefore,

Equation 12 Mg A

m = μ and A D c D ρ 2 = Equation 13

Equations 11 and 12 assume that the rolling resistance coefficient μ is wholly contained in the A m coefficient and the drag coefficient C d is wholly contained in the D coefficient. The equations also imply that any values of B m and C m 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 C d , 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 pr ovision 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 

## ( ) trailer trailer drive drive steer steer M M M 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 th e 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 we10 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 co astdown results do, however, show a larger increase in coefficient due to complete payload removal compa red to the lab results.

0 1 2 3 4 5 6 7 8 9FL60_N/A_fullFL60_N/A_fullInt'l_flatbed_fullInt'l_flatbed_fullInt'l_flatbed_fullInt'l_flatbed_halfInt'l_flatbed_emptyInt'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 th e International truck to be 99 ft 2 (9.2 m 2 ) 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 E quation 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 m 2 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 coe fficient as an input to the compliance model.11 0.0 0.2 0.4 0.6 0.8 1.0 1.2FL60_N/A_fullFL60_N/A_fullInt'l_flatbed_fullInt'l_flatbed_fullInt'l_flatbed_fullInt'l_flatbed_halfInt'l_flatbed_emptyInt'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 Calcul ated 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 a nd 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 pr ogram, 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 ra nge does not cover the specified high and especially minimum ve hicle coastdown speeds, then th e 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 an12 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 possi ble, the run should be a continuous run to avoid introducing another source of po ssible error into the procedure.

2) Automotive Testing and Development Services Coastdown Testing in California
Beginning in February 2010, EPA, through contractors URS Corporation 1 and ATDS 7 (Automotive Testing and Development Se rvices, Inc. based in California), conducted extensive coastdown tes ting using SAE test methods J1263 8 and J2263 1 with a total of 24 configura tions, including Class 7/8 combina tion 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 9 214 The vehicles tested included six pickup trucks and one va n. The van and three of the six pickup trucks were ballast ed 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 te sted 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 tr actor and trailer combinati ons 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 differen t 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 Coas tdown Configurations and Results

One Class 7 and seven Class 8 tractors have been procured to produce a total of thirteen tractor-trailer coastdown configura tions, 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 fairin gs. 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 combinati ons 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 be en 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 m 2 ) 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, EP A 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 D erived from TRC and NVFEL Coastdown Testing

Truck configuration Test Location Frontal Area [m 2 ] 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 combine d 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/mph 2 ] 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 J1263 8 and J2263 1 on three SmartWay-certified Class 8 tractor-trailers during the period October 2008 through September 2010. The16 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 a llow calculation of road load (RL) as a function of speed:

2 2 0 V F F RL × + =

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. Ho wever, 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 bein g 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 standa rd deviation) 7.3% 8.28%17 Another SmartWay vehicle, designated as Truck 598, has undergone coastdown testing near Corpus Christi r ecently per SAE J2263. Initial tes ting 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 conducte d on this truck since October 2008, when SwRI first started performi ng coastdown testing/analysis. The road load curve generated in October 2008, comprised of only knitted data, is deviant from those obtained in subsequent te sts. As seen, Figure 9 shows that the July 2010 coastdown results generated by MM6, the only test c onducted 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 (lb f** **) 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 th at 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 protocol 10 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 Te sting 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

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