NTRD-02 Final Project Report The Effects of Low Rolling Resistance ...

NTRD-02 Final Project Report
The Effects of Low Rolling Resistance Tires
on the NOx Emissions and Fuel Economy of
Drayage Trucks
by
Tim Diller and Ron Matthews
Engines Research Program, The University of Texas
Cynthia Palacios and Timothy H. DeFries
Eastern Research Group, Inc.
and
Brent Shoffner, Hector DeLaFuente, and Mark Kasper
Southwest Research Institute
submitted by
Ron Matthews
Professor of Mechanical Engineering
Head, Engines Research Program
The University of Texas MC C2200
1 University Station
Austin, TX 78712-0292
The preparation of this report is based on work funded
by the State of Texas
through a grant from the Texas Environmental Research Consortium,
with funding provided by the Texas Commission on Environmental Quality.
July 2, 2007

Table of Contents
Executive Summary........................................................................................................................ 1
1 INTRODUCTION .................................................................................................................... 3
2 PROJECT OBJECTIVES ......................................................................................................... 4
3 DATA LOGGING .................................................................................................................... 4
3.1 Truck Selection ............................................................................................................... 4
3.2 Data Logging Instrumentation ........................................................................................ 5
3.3 Data Logging Results...................................................................................................... 7
4 DEVELOPMENT OF THE TEXAS DRAYAGE TRUCK TEST CYCLE ............................ 7
4.1 Preparation of Raw Data for Cycle Building.................................................................. 8
4.2 Cycle Development......................................................................................................... 9
4.2.A General Methodology ............................................................................................. 9
4.2.B Specific Details of Non-Idle Cycle Generation ...................................................... 9
4.2.C Idle Periods in the Cycle....................................................................................... 12
4.3 Evaluation of the Candidate Cycle ............................................................................... 13
5 J1321 TRACK TESTS AND RESULTS................................................................................ 15
5.1 Program Setup............................................................................................................... 15
5.2 Test Phase ..................................................................................................................... 19
5.2.A Texas Drayage Truck Driving Cycle .................................................................... 19
5.2.B Test Method .......................................................................................................... 19
5.3 Track Test Results......................................................................................................... 20
6 DISCUSSION AND CONCLUSIONS .................................................................................. 25
Acknowledgements....................................................................................................................... 27
References..................................................................................................................................... 27
Appendix A - Drayage Operator Inventory .................................................................................. 28
Appendix B - J1321 Tire Information .......................................................................................... 31
Appendix C - Detailed J1321 Fuel Consumption and NOx Results............................................. 33
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List of Figures
Figure 1. Trucks A & B operating at the Port of Houston............................................................. 5
Figure 2. Trucks C and D operating for Double G Transportation in the DFW area. ................... 5
Figure 3. Accelerator pedal and engine driveshaft sensors............................................................ 6
Figure 4. Hall-effect sensor for driveshaft revolution counting. .................................................... 6
Figure 5. 5-second smoothing of the speed signal (the speed history from the data is the grey
line; the smoothed speed history is in black).......................................................................... 8
Figure 6. Speed history of the first non-idle portion of the cycle................................................ 11
Figure 7. Speed h tory of the second non-idle portion of the cycle............................................. 12
Figure 8. The Texas Drayage Truck Test Cycle.......................................................................... 14
Figure 9. Truck rig used for track testing. ................................................................................... 16
Figure 10. (a)Semtech-D PEMS unit (b)mass airflow sensor.................................................. 16
Figure 11. Mounting of the removable weigh fuel tank. ............................................................. 17
Figure 12. Wide-single wheels and tires installed on the test truck drive axles. ......................... 18
Figure 13. (a) 10-bolt pattern wheel (b) “spider hub” as used on chassis trailers. ...................... 19
Figure 14. Fuel consumption T/C ratios from the track tests (Segments 1 and 4 are comparisons
between nominally identical vehicles).................................................................................. 22
Figure 15. NOX emission T/C ratios from the track tests (Segments 1 and 4 are comparisons
between nominally identical vehicles).................................................................................. 23
List of Tables
Table 1. Comparison of Data Set and Test Cycle Characteristics. .............................................. 13
Table 2. Specifications of the Control and Test Rigs. ................................................................. 15
Table 3. Axle Loads for Test Rigs............................................................................................... 17
Table 4. Test Segments for SAE J1321 Testing. ......................................................................... 20
ii

EXECUTIVE SUMMARY
Trucks operating dray duty, i.e. transporting “cargo containers” in inter-modal operation in and
around port and rail terminals, are responsible for a large proportion of the emissions of the
oxides of nitrogen (NOx), which are problematic for the air quality of such Texas metropolitan
areas as Houston and Dallas/Ft. Worth. The University of Texas at Austin lead a program, with
the Eastern Research Group and the Southwest Research Institute as subcontractors, to develop a
standardized test cycle, called the Texas Drayage Truck Cycle, which would adequately
represent the operation of heavy-duty diesel trucks in dray operations at the Port of Houston and
the freight train terminals in Dallas-Ft. Worth, and to use this cycle to quantify the effects of use
of wide-single tires on fuel economy and NOX emissions.
Data logged from the operations of two trucks operating in the Port of Houston and one in the
Dallas-Ft. Worth area revealed that dray trucks spend about 45% of their engine-on time at idle,
and the rest of the time in relatively short but high intensity (with many accelerations) trips (

owner/operator, as motivated by the fuel savings our research team measured for use of widesingle
tires. Unfortunately, the majority of chassis trailers in use are owned by the steam lines,
which have no incentive to retrofit with expensive wide-single tires and corresponding wheels
and hubs. Thus, an alternative arrangement, with possible state funding, would have to be made
for full conversion of dray trucking operations.
2

1 INTRODUCTION
Through Project NTRD-02, the Houston Advanced Research Center (HARC) funded research
under TCEQ’s New Technology Research and Development (NTRD) program to evaluate the
emission reduction potential of a specific fuel-saving technology selected from the U.S.
Environmental Protection Agency (EPA) SmartWay Transport Partnership. The SmartWay
program is aimed at reducing emissions and improving fuel economy in the transportation sector.
Of specific interest for this grant was the application of SmartWay technologies to drayage
trucks operating in the two major non-attainment areas within Texas. Drayage operations in the
Port of Houston and at a freight locomotive terminal in the Dallas-Fort Worth are believed to be
significant sources of emissions of the oxides of nitrogen (NOx).
Drayage operations include inter-modal haulage between shipping and rail operators and their
warehouses and customers. A large proportion of the cargo is in shipping (often called “cargo”)
containers, and much of the remainder is in box vans. Most of the trips are less than 30 miles in
length and include long periods of stop-and-creep, idling, and short bursts on the highways. As
such, the range of loading on the trucks is broad and, up to the present, there has not been a
standard characterization for operations in the major air-quality non-attainment areas in Texas.
The first part of this project was to characterize the operation of drayage trucks in Texas at the
Port of Houston and the freight rail terminals of the Dallas-Ft. Worth metroplex. Specifically,
we logged data from drayage truck operations in and around the Port of Houston and the Dallas-
Ft. Worth freight rail terminals and used this logged data to develop a standardized Texas
Drayage Truck Cycle.
The second part of the project was to use the new standardized test cycle to characterize a
particular technology for reductions in fuel consumption and NOx emissions: the Michelin X-
One tire, which is designed to reduce a vehicle’s rolling resistance and inertial mass, resulting in
improved fuel economy and reduced tailpipe emissions. With sponsorship from TCEQ/HARC,
the University of Texas (UT) undertook a study to determine whether the new tires result in
reduced NOx emissions when used on drayage trucks. During the final task of this project,
drayage trucks were driven on a test track with the new low rolling resistance tires and with
standard tires to quantify the effects on tailpipe emissions and fuel economy.
At the time of this study, the Michelin X-One wide-single tires were unique in the market due to
their combination of light-weight and low rolling resistance compared to conventional dual tires.
Michelin X-One wide-single tires have already been the subject of Phase I and Phase 2 testing by
the EPA for Class 8 line-haul trucks (Bachman et al., 2005; Bachman et al., 2006). Michelin has
shown that these tires provide a fuel economy benefit for a variety of heavy-duty truck
applications and that these wide-single tires do not damage the roadway, unlike earlier attempts
(in the 1980s) at introducing such tires. Michelin has also shown that these tires provide
improved emergency maneuvering capabilities. In fact, the improved fuel economy from use of
these tires should offset the cost of the tires and corresponding wheels within a reasonable payback
period. By itself, this should result in the widespread use of these tires by commercial
heavy-duty fleets.
3

2 PROJECT OBJECTIVES
This project had three major objectives, each of which is briefly discussed below.
The first objective was the development of a Texas Drayage Truck Test Cycle that represents
drayage operations in the Houston-Galveston-Brazoria (HGB) and Dallas-Fort Worth (DFW)
areas. This objective required two tasks. The first task was data logging on drayage trucks in
these two regions, as discussed in Section 3. The second task was to use the logged data to
develop a driving cycle that represents drayage operations in the HGB and DFW areas, as
discussed in Section 4.
The second objective was to use this cycle to quantify the fuel economy and emissions benefits
of use of wide-single tires via SAE J1321 track testing. The track tests, including the results
from these tests, are discussed in Section 5.
The third objective was to develop an inventory of drayage truck operators in the Houston-
Galveston-Brazoria and Dallas-Fort Worth areas. This inventory is provided in Appendix A.
3 DATA LOGGING
Collecting data for the project consisted of three phases: identifying the trucks, building and
installing the data logging equipment, and recording the data on trucks in service.
3.1 Truck Selection
Drayage firms operating in the Port of Houston in Dallas-Ft. Worth typically provide dispatching
and logistical service to truck owner-operators who work for them under contract. As such, the
drayage firms do not typically own their own fleets. Therefore, in order to install equipment on
the trucks, approval was needed both from the owner-operator and from the ownership of the
drayage operation. For those trucks operating from the Barbour’s Cut Container Terminal, it was
critical to minimize downtime since the port operates from 7:00 to 4:00 only.
Drivers at two firms operating in the Port of Houston and two drivers at a drayage firm operating
in Dallas agreed to allow us to install data loggers on their trucks
Figure 1 shows Trucks A and B operating at the Port of Houston. Truck A is a 2003 model
Freightliner sleeper-cab 4X6 tractor with a Detroit Diesel Series 60 engine and automatic
transmission. Truck B is a 1994 Kenworth sleeper cab 4X6 tractor with a Cummins N14 engine
and manual transmission (5-speed with low and high range) and operates in and around the Port
of Houston.
4

Figure 1. Trucks A & B operating at the Port of Houston.
Trucks C and D (shown in Figure 2) operated in and around the Dallas-Ft. Worth metroplex
providing inter-modal container and van transport between rail terminals and warehouses. Truck
C is a 1994 model year International sleeper cab-type 4X6 tractor with a manual transmission
and a Detroit Diesel Series 60 engine. Truck D was a 1993 model year International cab-over
type 4X6 tractor with a manual transmission and a Detroit Diesel Series 60 engine.
Figure 2. Trucks C and D operating for Double G Transportation
in the DFW area.
3.2 Data Logging Instrumentation
Each of the trucks was fitted with a data logger designed to record the accelerator pedal position
and the rotational speeds of the engine and drive shaft every second. A photo of the accelerator
pedal position sensor for Truck B is shown in Figure 3(a).
5

(a) (b)
Figure 3. Accelerator pedal and engine driveshaft sensors.
Engine speed was measured by fixing a retro-reflective tape to the harmonic balancer and
mounting an infrared photo emitter-detector close by to view it. In this way, the photo emitterdetector
returned a square wave signal to the data logger, which counted the rising edges. The
installation of the engine speed detector is illustrated in Figure 3(b).
Driveshaft revolutions were measured with a Hall-effect sensor mounted above the driveshaft, as
illustrated in Figure 4. A steel socket-head cap screw was filed so that it would lie flat and was
held to the driveshaft under the Hall-effect sensor with a hose clamp. In this configuration, as the
driveshaft rotated, the head of the screw passed under the Hall-effect sensor, inducing it to send
one square wave signal per revolution of the driveshaft to the data logger, which counted the
number of pulses each second. Because the final drive ratio of the differential gear was constant,
this served as a measurement of vehicle speed.
Figure 4. Hall-effect sensor for driveshaft revolution counting.
6

After having the data loggers installed, the trucks were operated for at least a week to record
their movements in and around the study areas. The number of driveshaft revolutions per mile
was determined by plotting the most recent trip on a map and matching it to the data-logging file.
The trip distance was divided by the total number of driveshaft revolutions to determine the final
drive ratio. Thus, the number of driveshaft revolutions per second could be turned into vehicle
speed for use in the cycle development.
3.3 Data Logging Results
For several of the trucks, we experienced scheduling and technical difficulties, and in order to
get a whole week's worth of data, the equipment had to remain in place for several weeks. In the
end, Truck A returned six days of useful information; however, the NOx sensor did not function
properly, and no useful data from the NOx signal was retained. For Truck A, the other three
channels worked well, and the number of driveshaft revolutions per mile was 1887. During the
operation of Truck B, the optical sensor recording engine RPM ceased to function, but the
driveshaft signal remained good, and a total of nine useful days was obtained. The revolutions
per mile for Truck B was 3602. For Truck C, unfortunately, the driver was ill for part of the
period, and after three days of driving, he accidentally unplugged the power from the data logger
while cleaning his cab. Thus, only three days of data was available for Truck C. Its number of
driveshaft revolutions per mile was 2031. The Hall-effect sensor was knocked loose from Truck
D shortly after installation, and there was not enough data to show a single complete trip. There
was not enough time for a re-installation, so no useful data was obtained from Truck D.
4 DEVELOPMENT OF THE TEXAS DRAYAGE TRUCK TEST CYCLE
In order to develop a usable drive cycle, we broke the entire drayage truck operation data set into
individual micro-trips (a period of driving that begins and ends with an idle). We chose the
subset of micro-trips that best matched the speed and acceleration characteristics of the entire set
of micro-trips. Speed and acceleration were chosen for matching purposes because they largely
influence the emissions behavior of a given vehicle. In spite of their known effects on emissions,
vehicle weight and road grade were not included in developing these cycles, because those
parameters do not influence the cycle and can be accounted for in the track tests.
Because the cycle developed in this study was to be used to test vehicle emissions and fuel
economy during test-track driving, a short cycle was desirable. However, SAE standards
required consumption of at least six gallons of fuel in the truck being tested, so the cycle was
developed to contain just over 30 miles of driving.
The data revealed that the trucks were at idle about 45% of the time they were turned on;
however, this full idle period is not represented in the driving cycle but is accounted for via
“weighting”. Finally, we considered all of the data to be driving under warmed-up, running
operating conditions, and did not build different “phases” for cold starts and hot starts.
Section 4.1 describes the preparation of the raw data for cycle building. It includes a discussion
of the quality checks and edits that were made to the hundreds of thousands of second-by-second
7

observations in the datasets. Section 4.2 describes the general methodology and the specific
details of building the cycle, and post-processing of the selected cycle. A comparison of
statistics for the cycle and the dataset on which it was built is presented in Subsection 4.3. A
complete record of the cycle development is available in Palacios and DeFries (2007).
4.1 Preparation of Raw Data for Cycle Building
Data logging operations provided second-by-second driving data for three drayage trucks. The
data was processed by smoothing and removing errors and electronic artifacts.
For the purpose of cycle-building, vehicle speeds were smoothed using a weighted average speed
over nine seconds:
Speedn,9s Smooth=(1*Speedn-4 + 2*Speedn-3 + 3*Speedn-2 + 4*Speedn-1 + 5*Speedn +
4*Speedn+1 + 3*Speedn+2 + 2*Speedn+3 + 1*Speedn+4)/25
where Speedn is the speed for the current second, and the other speeds are for the 4 seconds
before and after the current second. New acceleration values were then calculated from the
smoothed speeds. Figure 5 shows a sample of the smoothed speed trace for a single micro-trip
superimposed over the raw speed trace from which it was derived. The smoothed speed and
acceleration values were used for building the driving cycle.
Figure 5. 5-second smoothing of the speed signal (the speed
history from the data is the grey line; the smoothed speed
history is in black).
The cycle was created by concatenating the micro-trips the with speed and acceleration
characteristics that best matched the speed and acceleration of driving in the entire dataset. A
8

micro-trip was defined as a contiguous speed trace of vehicle driving and is made up of an idle
followed by all non-idle driving until the next idle begins. A single vehicle trip, defined as the
period from engine-on to engine-off, typically comprised numerous micro-trips. Therefore, the
driving was divided into trips and sub-divided into micro-trips before the cycle was built.
Each trip was assigned a unique trip number, and each micro-trip was assigned a unique microtrip
number. The smoothing of the raw data using a five second average, as described above,
eliminated any idle periods that were less than five seconds long, since the zero speeds just
before and just after non-zero speeds were averaged to became non-zero speeds during
smoothing. As a result, some micro-trips based on the smoothed data are longer than they would
have been if they had been based on the raw data.
The second-by-second observations for all of the micro-trips in the edited dataset were placed
into bins according to speed and acceleration. Only those longer than 20 seconds were used to
eliminate repetitive non-representative operation of the vehicle.
4.2 Cycle Development
To develop the drayage cycle we used pieces of real driving, the micro-trips from the drayage
truck activity database, which when connected together would exhibit emissions behavior similar
to a drayage truck driving on the road. The cycle was built around parameters of vehicle
operation and usage that were known to be important to exhaust emissions. By using the
approach of matching vehicle operation between measured driving behavior and the candidate
cycle, the emissions behavior of vehicles over the cycle would be similar to the emissions
behavior of drayage trucks on the road. Vehicle speed and acceleration were chosen as the
variables most important to exhaust emissions. These variables together provided a measure of
the load on the engine, which is an important variable associated with exhaust emissions. The
cycle was developed only for warmed up operation of drayage trucks. That is, we assumed that
all data in the datasets represent warmed-up driving and did not build special cycles for cold
starts and warm starts.
4.2.A General Methodology
The cycle was created by combining micro-trips taken from the recorded operation of Trucks A-
C. The two critical variables (speed and acceleration) were used for selection of micro-trips for
the cycle. To identify specific segments of vehicle driving for inclusion in the cycle, the entire
activity dataset was converted to a set of micro-trips as described in the previous section. A
strategy based on a minimizing the difference between a cycle vector C representing the driving
in the candidate cycle and a target vector T representing the driving in the activity database was
used to select micro-trips from the database for inclusion in the cycle. Enough micro-trips were
used to build-up a candidate cycle so that the difference between the two vectors was minimized
to an acceptable level; the two vectors were substantially the same, and the duration of the cycle
met the length criterion for SAE J1321 testing. For full details on the building process and the
multi-dimensional vectors space used to build the cycle, see Palacios and DeFries (2007).
4.2.B Specific Details of Non-Idle Cycle Generation
After the dataset containing all of the second-by-second driving activity for the three drayage
trucks was edited and prepared, the micro-trip information was used to find those micro-trips
9

which, when concatenated, best described the drayage truck driving activity. We matched the
non-idle portions of the cycle to the non-idle driving in the activity dataset in the process of
selecting micro-trips to build the cycle. Each micro-trip was converted into a vector and the
entire set of micro-trips into the target vector T. We then found the micro-trip with the smallest
sum of the squared differences between the cumulative normalized elements of the micro-trip
with the corresponding elements of the target. This corresponded to finding the micro-trip such
that the T-C vector was the smallest. This became the first micro-trip in the cycle. Then microtrips
were chosen from those remaining micro-trips and added to the first, minimizing the T-C
vector length at each iteration. This process was repeated until 25 micro-trips were added to the
cycle. As each micro-trip was added, the square of the length of the vector dropped to a
minimum at micro-trip 10. As additional micro-trips beyond the 10 th were added, they did not
substantially improve the match of the cycle to the target vector, but rather were necessary to
meet the 30-mile goal.
Therefore, it was decided to create a composite cycle with two separate non-idle sub-cycles. The
first non-idle portion of the composite cycle would be the first 10 micro-trips that were chosen.
Then the process was repeated, excluding the first 10 that had already been chosen, to obtain the
second non-idle portion of the composite cycle. The square of the length of the second T-C
vector reached a minimum at 13 micro-trips, so these 13 micro-trips were selected to make up
the second sub-cycle of the composite cycle.
In this composite cycle, either half of the cycle represents the target vector almost as well as the
composite. Therefore, if equipment or other problems invalidated emissions concentration
results from one sub-cycle, results from the other sub-cycle could still be used, and a whole test
run would not be lost. Also, since the two sub-cycles represent the same target vector, the
measured emissions concentrations should be similar for each.
10

Figure 6. Speed history of the first non-idle portion of the
cycle.
Speed versus time plots of the micro-trips that make up the first and second non-idle sub-cycles
are shown in Figure 6 and Figure 7. The small circles on the plot indicate the beginning of each
micro-trip. These candidate cycle plots were used to examine the overall appearance of the cycle
and to show the duration of the cycle.
11

Figure 7. Speed history of the second non-idle portion of the
cycle.
4.2.C Idle Periods in the Cycle
According to the drayage truck activity database, the trucks were at idle for approximately 45%
of the time that they were turned on. Since it was not desirable to require the test truck driver to
sit at idle for that length of time, a ten-minute idle period was added to the beginning of the
composite cycle before the first non-idle sub-cycle, and another ten-minute idle period was
placed between the two non-idle sub-cycles. The emissions concentrations for the ten-minute
idle periods must be multiplied by a scale factor to increase their weight to 45% of all driving in
the composite. The final cycle consists of four components:
Phase 1: 10-minute idle period,
Phase 2: the first non-idle sub-cycle, 2000 seconds of driving,
Phase 3: 10-minute idle period, and
Phase 4: the second non-idle sub-cycle, 2600 seconds of driving.
To combine Phases 1 and 2, emissions results from Phase 1 must be multiplied by 2.7, so that
they comprise 45% of the total time for Phases 1 and 2 (600 seconds*2.7=1620 seconds, or 45%
of 1620+2000 seconds). The scaled result for Phase 1 may then be added to Phase 2, for a
combined idle/non-idle result. Similarly, Phases 3 and 4 may be combined by multiplying
results from Phase 3 by 3.6 and then adding Phase 4. All parts of the cycle may be combined by
adding Phases 1 and 3, multiplying the result by 3.2, and then adding Phases 2 and 4.
12

4.3 Evaluation of the Candidate Cycle
After synthesizing the composite cycle, several evaluations were made, including comparisons of
the cycle to the target dataset. Analysis of speed v. acceleration distributions for the composite
cycle and the raw data showed a good match; a few outlying points in the raw data were not
included in the micro-trips used in the cycle, and thus the representation is good from that
standpoint. The speed histogram of the composite cycle matches the speed histogram from the
raw data, showing that the time-at-speed for the cycle is representative of the raw data. Full
details can be seen in the detailed report on the cycle development (Palacios and DeFries, 2007).
A number of statistics were calculated so that the characteristics of the cycle could be compared
to the characteristics of the target dataset (see Table 1). Because the micro-trips in the cycle
were selected for their non-idle speed and acceleration characteristics, other statistics that are
calculated and compared do not necessarily reflect as close a match between the test cycle and
the raw data.
Table 1 shows that the average second-by-second speeds of the selected cycle and target
database are similar, although the cycle speeds are slightly lower than those in the target dataset.
The difference results from high-speed trips in the target dataset, which were few in number but
very long. Also, the micro-trips selected for the cycle have a longer average length (duration in
seconds and distance traveled) compared to the average for the target vector. This is due to the
exclusion of all-idle micro-trips and micro-trips of less than 20 seconds for cycle building.
Finally, Table 1 shows that the square of the length of T-C was very low, both for the two subcycles
separately and for the two when combined. This indicates a good fit of the driving
conditions (speed and acceleration) in the selected cycle, compared to the target database.
Table 1. Comparison of Data Set and Test Cycle Characteristics.
Total Time
(s)
Average sxs
Speed
(mph)
Total
Distance
(miles)
13
Average
Micro-Trip
Time
(s)
Average
Micro-Trip
Distance
(miles)
Micro-
Trips
(count)
Target 242,724 26.2 1767.2 139.2 1.0 1744 -
Final
Square
of L.
of T-C
Sub-Cycle 1 2,594 24.5 13.6 259.4 1.4 10 0.21
Sub-Cycle 2 3,186 24.8 18.0 289.6 1.6 11 0.20
Sub-Cycles
1&2 5,780 24.7 31.6 275.2 1.5 21 0.19
The final version of the Texas Drayage Truck Test Cycle is illustrated in Figure 8.

Figure 8. The Texas Drayage Truck Test Cycle.
14

5 J1321 TRACK TESTS AND RESULTS
The new Texas Drayage Truck Test Cycle was used to evaluate low-mass low-rolling resistance
tires on representative trucks in the SAE J1321 “Joint TMC/SAE Fuel Consumption Test
Procedure Type II”. The test program was designed to evaluate both the fuel economy and the
NOx impact of using the wide-single tires on drayage trucks while hauling chassis with
corresponding containers. The test trucks were model year 2006 Freightliner Class 8 trucks with
Detroit Diesel engines. In addition to gravimetric fuel tanks for measuring fuel economy, a
Portable Emissions Monitoring System (PEMS) was installed in each truck to measure NOx.
The PEMS units were Sensors, Inc. SEMTECH-D instruments.
The J1321 recommended practice provides a standard test procedure for comparing the inservice
fuel consumption of a vehicle operating under two conditions: a test and a baseline. An
unchanging control vehicle is run in tandem with a test vehicle to provide an unchanging
reference. The result of a test using this procedure is the percentage difference in fuel
consumption or NOx emissions of the test vehicle in two different test configurations.
The program setup is discussed in Section 5.1, the testing is discussed in Section 5.2, and the
results from the track tests are presented in Section 5.3. A complete record of the track testing is
available in Shoffner et al. (2007).
5.1 Program Setup
Two truck and chassis/container combinations (each one designated a truck and trailer “rig”)
were used for testing. The trucks were chosen to be as close to each other as possible in
construction, age, and usage history. Note the similar VIN numbers and engine serial numbers in
the specifications and data for the trucks, chassis trailers, and containers shown in Table 2. A
photograph of one of the truck and trailer rigs is provided in Figure 9.
Table 2. Specifications of the Control and Test Rigs.
Name “Control” “Test”
Truck Ser. No. 509338 509340
Truck VIN 1FUJA6CK87DX33832 1FUJA6CK17DX33834
Truck manufacturer Freightliner Freightliner
Engine manufacturer Detroit Diesel Detroit Diesel
Engine
Series 60/14.0 L Series 60/14.0 L
model/displacement
Engine emissions family 6DDXH14.0ELY 6DDXH14.0ELY
Engine Ser. No. 06R0902859 06R0904064
PEMS No. SEMTEC-D-G04-SD03 SEMTEC-DS E06-SDS01
Chassis (trailer) No. FLXZ402881 FLXZ401251
Container No. 5877886 5069635
15

Figure 9. Truck rig used for track testing.
Figure 10 shows (a) an installed PEMS unit and (b) the associated mass air-flow sensor. The
PEMS unit was mounted in the sleeper cab, and the mass air-flow sensor was mounted in-line
with the exhaust stream, directly downstream of the muffler.
Figure 10. (a)Semtech-D PEMS unit (b)mass airflow sensor.
Each container was ballasted with eight concrete blocks for a total load in each container of
approximately 43,000 lb. The truck and trailer rig weights by axle are provided in Table 3.
These weights were measured with the fuel tanks ¾-full, the PEMS installed, no driver or
passenger, and without the auxiliary fuel tank that was used for the fuel consumption
measurements. Note that the weight savings of the wide-single tires, hubs, and wheels compared
to the as-received test tires, hubs, and wheels was approximately 1,236 lb.
16

Table 3. Axle Loads for Test Rigs.
During the setup the wheels of the tractors and trailers were aligned, and a removable weigh tank
with quick-disconnect hose couplings was mounted on each truck. The fuel supply and return
lines were modified with quick-disconnect couplings to facilitate switching from the truck tanks
to the weigh tank. A photograph of an auxiliary tank is shown in Figure 11.
Figure 11. Mounting of the removable weigh fuel tank.
For the baseline configuration of the test truck, the steer axle was fitted with 11R22.5
BFGoodrich ST234’s, and the drive axles were fitted with11R22.5 BFGoodrich DR675’s. These
tires represented a typical new-purchased tire designed for optimal performance in high scrub
environments and with moderate to high rolling resistance. In the baseline configuration, the
trailer tires were left as received on the container chassis (see Appendix B for details), which
included a mix of re-treaded and original tread tube-type tires. This was appropriate since the
chassis are typically owned by the steam-ship or rail lines, and tire choices are out of the control
of the truck owner/operator.
For the test condition of the test truck, Michelin provided a set of 445/50R22.5 X-One XDA tires
for the drive axles and 445/50R22.5 X-One XTA tires for the trailer axles. The X-One XDA and
XTA tires are optimized for low-rolling resistance and, when mounted to an aluminum rim, are
about 100 lb lighter per axle-end than the conventional dual arrangement. The steer tires from
the baseline configuration were used in the test condition. The X-One XDA wide-singles are
shown installed on the drive axles in Figure 12.
17

Figure 12. Wide-single wheels and tires installed on the test
truck drive axles.
The control truck was run throughout the program with the tires as received on both the tractor
and chassis trailer. Between Segments 2 and 3, the control truck trailer had a flat tire. Two tires
with similar tread depth from the baseline configuration of the test trailer were used during
Segment 3 while the flat was repaired, and for Segment 4, the tires were all returned to their
original positions. Details of the tire fitments are provided in Appendix B.
The chassis trailers used by the shipping industry use a “spider hub” design on the axles. Figure
13 compares photographs of the 10-bolt wheels used on modern trucks and trailers with the 5bolt
wheels used on older trucks and on chassis trailers. The wide-single trailer tires mounted on
wheels with a 10-bolt pattern would not fit on these spider hubs. No adapters for the 10-bolt
pattern wheels to the hubs were available, so we modified the test trailer axles before fitting the
wide-single tires in the test configuration. The 10-bolt hubs were installed with new bearings
and seals, and the axles were charged with Service Pro 80W-90 gear oil.
For Segment 4, the final repetition of the baseline configuration, the spider-hubs were installed in
their original locations on the test trailer with new seals and a fresh charge of axle gear oil.
18

Figure 13. (a) 10-bolt pattern wheel (b) “spider hub” as used on
chassis trailers.
5.2 Test Phase
5.2.A Texas Drayage Truck Driving Cycle
Track testing of the tires was done on an 8.5-mile oval track at the Continental-General Proving
Grounds (CCPG) in Uvalde, TX. The Texas Drayage Truck Driving Cycle was adapted for use
at the CGPG. Signs were placed at locations where the vehicle started, stopped, or made a
significant change in acceleration rate. The drivers used the GPS speed from the PEMS rather
than the speedometer to drive the route to ensure the truck speed profile was as close as possible
in all laps regardless of potential differences in rolling radius of the drive tires. In-cab observers
aided the drivers with time-keeping and speed matching.
The track surface was asphalt and generally flat with a few rolling hills. The total distance of the
cycle (31.69 miles, or approximately 3.75 times around the track) was designated one lap
according to SAE J1321. The approximate average speed for a lap was 20.75 mph.
5.2.B Test Method
Prior to each day of operation, tire inflation pressures were checked and adjusted to a pressure of
100 psi. The truck fuel tanks were filled, and a separate removable weigh-tank was filled and
installed on each truck. The trucks were driven around the 8.5-mile oval track three times at a
constant speed of 65 mph as a warm-up each day before testing.
According to SAE J1321, one test lap consisted of simultaneous operation of the test truck and
the control truck. After completion of a test lap, the weigh tanks were removed and weighed,
and the mass of fuel consumed by the test truck (T) was compared to the mass of fuel consumed
in the control truck (C). These were combined in a T/C ratio according to SAE J1321 procedure.
Prior to each test lap, the engine was stopped, and the fuel supply and return lines were switched
from the truck tank to the weigh-tank. The trucks started each lap with a five to ten minute
separation. The engine was restarted and the truck was idled for 10 minutes to start the Texas
Drayage Truck Driving Cycle. After the driving cycle was completed, the truck was decelerated
19

to a stop. The engine was allowed to idle for approximately 60 seconds and then stopped to
switch fuel lines from the weigh tank to the truck tank. The weigh-tanks were removed and
weighed to determine the fuel consumed.
To maintain consistent operation during a driving cycle sequence, the trucks were operated with
the headlights on and the air conditioning and the blower fan controls in the same position. An
observer in each truck recorded driving times at key mile markers. The total time for each lap
had to match the appropriate target times within +/-0.5% for that lap to be considered
operationally valid.
According to SAE J1321, one test segment consisted of three valid test laps where the spread in
T/C ratios of the three laps did not exceed 2.00%. The T/C ratios for the three laps were then
averaged to obtain a T/C ratio for the segment. The control truck and trailer rig remained in the
same configuration throughout testing, and the test tires were added or removed from the test
truck rig by segment.
Four segments were tested, as outlined in Table 4. The order of the segments was designed to
ensure repetition of each configuration with a minimum number of setup changes.
Table 4. Test Segments for SAE J1321 Testing.
Segment
Number
1
(baseline)
2
(test)
3
(baseline)
4
(test)
Test Trailer
As-received trailer spider hubs,
rims, and tires
10-bolt hubs, wide-single rims,
and wide-single tires
10-bolt hubs, wide-single rims,
and wide-single tires
Original trailer spider hubs,
rims, and tires
20
Test tractor drive tires
BF Goodrich tires supplied by
Michelin North America
Wide-single tires on the drive
locations
Wide-single tires on the drive
locations
BF Goodrich tires supplied by
Michelin North America
5.3 Track Test Results
Fuel consumption was measured by weighing the weigh-tanks after each completed run and
subtracting the initial value. In order to account for the fuel consumed during the idle period, the
data log was examined, and the values commanded by the engine controller were noted. An
appropriate calibration factor was formed by forming a ratio of the total fuel consumed according
to the engine control bus to the total fuel consumed as measured by the weigh tanks. This
correction factor was then applied to the idle-period data recorded by the engine control bus, and
the appropriate weighting factors were applied according to the test cycle specifications. In this
way, the fuel consumption for each segment was determined, and a T/C ratio could be formed.
By comparing the T/C ratio for each test segment, the fuel economy improvement (percent fuel
saved in the test versus the baseline configurations) was calculated.

NOx in grams per mile was recorded from the PEMS data for the SAE J1321 laps. The NOx
emissions for the idle periods were summed and multiplied by the appropriate weighting factors
as specified by the test cycle. An average NOx mass emissions rate (grams per mile) was
calculated for each segment using the weighted values. Similar to the J1321 fuel savings
calculation, a NOx_T/C ratio was calculated for a simultaneous lap by dividing the NOx in
grams per mile for the test truck by the NOx in grams per mile for the control truck. The NOx
reduction was determined via the following equation:
The detailed results for NOx emissions (in grams per mile) and fuel consumed in each lap are
provided in Appendix C. The laps chosen to calculate the SAE J1321 average T/C ratio for a
segment are also identified in Appendix C.
Figures 14 and 15 present the ratios of fuel consumption and NOx emissions, respectively, from
the valid laps. Note that Segments 1 and 4 are comparisons of nominally identical vehicles
(truck and trailer combination).
21

Figure 14. Fuel consumption T/C ratios from the track tests
(Segments 1 and 4 are comparisons between nominally identical
vehicles).
22

Figure 15. NO X emission T/C ratios from the track tests
(Segments 1 and 4 are comparisons between nominally identical
vehicles).
A summary of the results from the J1321 track tests is provided in Table 5, which shows that the
low rolling-resistance wide-single tires provide a reduction in fuel consumption of 8.7% and a
reduction in NOx emissions of 3.75%. These improvements are statistically significant.
23

Table 5. Summary of Track Test Results.
SAE NOx
Segment Segment J1321 Ratio
Number Description T/C
Ratio
Segment 1 Baseline 1 1.0354 1.0463
Segment 2 Test 1 0.9415 0.9844
Segment 3 Test 2 0.9391 0.9666
Segment 4 Baseline 2 1.0245 0.9821
SAE J1321 Evaluation 1
SAE J1321 Evaluation 2
Average of two J1321
Evaluations
Fuel NOx
Saved Reduction
9.07% 5.92%
8.34% 1.58%
8.71%
3.75%
It is interesting to note that calculating the values without weighting the idle periods results in a
higher reduction in fuel consumption of 9.3% and a reduction in NOx emissions of 7.4%, as
shown Table 6.
Table 6. Summary of Track Test Results Without Weighting the
Idle Periods.
24

6 DISCUSSION AND CONCLUSIONS
Based on in-service measurements of trucks operating in dray service in the Port of Houston and
in the rail terminals of Dallas-Ft. Worth, we developed a new Texas Drayage Truck Test Cycle,
which allows drayage truck operation to be simulated on a chassis dynamometer or on a test
track under controlled conditions. The Texas Drayage Truck Test Cycle is 31.6 miles in length,
has an average speed of 24.7 mph, consists of 21 micro-trips (where a micro-trip begins with a
stationary idle followed by an acceleration transient and ends with a deceleration back to a
stationary idle), and 45% of the total test time is stationary idle.
We used this new test cycle to evaluate the use of wide-single (also called super wide and singlewide)
tires for use on the non-steered axles of heavy-duty trucks. These are single tires designed
to replace the two tires conventionally fitted to each non-steered axle end. One design, recently
introduced to the Market by Michelin North America, optimizes each wide-single tire for lower
rolling-resistance and lighter weight than the pair of tires it replaces in a conventional setup.
These tires, branded Michelin X-One TM , have already been the subject of Phase I and Phase 2
testing by the EPA.
Our research team examined the NOx emissions reduction and fuel economy benefits that are
realized through the use of these tires on drayage trucks, including trailers hauling shipping
containers. As a result of this study the final EPA Technology Verification will include the use
of wide-single heavy truck tires for an additional category of Class 8 trucks: those used in
drayage operations.
We found that fitting wide-single tires with low rolling resistance to trucks and trailers in
drayage operation reduced the emissions of NOx by 3.8% and reduced the consumption of fuel
by 8.7%. As such, low-rolling resistance, lightweight wide-single tires represent a viable retrofit
solution for the reduction of NOx emissions in those fleets. By not weighting the idle periods
according to the test cycle specification, higher reductions of 7.4% for NOx emissions and 9.3%
for fuel consumption were seen, and this leads to questions about the effects of idling trucks. A
rule regarding idling at the ports could possibly have an impact similar to an equipment retrofit.
In a 2005 study carried out by the US EPA, the effects of wide-single tires and aerodynamic
devices on NOx emissions and fuel consumption were measured for heavy-duty trucks operating
on three types of highway cycles. Both the wide-single tires and the aerodynamic devices were
found to reduce fuel consumption and NOx emissions. The reductions in fuel consumption were
found to correlate well with reductions in NOx emissions, which tended to be disproportionately
higher than the improvements in fuel economy. In the highway cycles, the tires were found to be
responsible for reductions in fuel consumption of about 7% for a 55 mph highway cycle, 13% for
a 65 mph highway cycle, and 10% for a suburban stop-and-go cycle. NOx reductions were
found to be about 30% for the highway cycles and about 10% for the suburban stop-and-go
cycle. Due to various factors, the confidence interval for the reductions in the EPA study was
somewhat high but still statistically significant (Bachman et al., 2005).
The suburban stop-and-go cycle offers the most similar comparison to the Texas Drayage Truck
Test Cycle, and we find that the reductions seen in the Texas Drayage Truck Test Cycle are of a
similar magnitude. This is what we expected: because the effect of speed on tire rolling
resistance is weak (LaClair and Truemner, 2005), so we would expect to see a small reduction in
25

the effect of the tires at higher speeds, but a majority of the production of NOx happens during
accelerations when the engine is running at high loads. In the stop-and-go cycles there are many
accelerations, where the load on the engine is determined primarily by the inertia of the vehicle.
Reduction in mass and rotational inertia of the tires affect this directly, but the effect is limited
because, relative to the overall inertia of the vehicle, the reduction is small. In a highway cycle,
the load on the engine is primarily due to aerodynamic drag and tire rolling resistance, and the
reduction in rolling resistance covers a much greater portion of the engine load profile. Thus, we
conclude that because the highway cycles tested by the EPA are more steady-state in nature than
the Texas Drayage Truck Test Cycle or the suburban stop-and-go cycle, the effect of the lighter,
lower rolling resistance tires would be greater on highway-type cycles. Nevertheless, the
reductions in fuel consumption and NOx emissions in the Texas Drayage Truck Test Cycle are
significant and warrant follow-up action.
The test configuration in this study was not a strictly “clean” comparison of the effect of the tires
alone, but was a real-world comparison. The tires that were found on the chassis trailer were
tube-type and of bias-ply construction, and several of them had recapped treads. These three
changes alone would account for some reduction in rolling resistance. In addition, it is evident
from the difference in fuel consumption between the repetitions of the baseline configuration that
the change of bearing lubricant had some effect on the rolling resistance and thus the emissions
and fuel consumption. However, budgetary limitations restricted us from a complete analysis of
the independent effect of all of the factors. Instead, we chose to examine a case that might
reasonably be expected to occur in the field. Thus, our baseline configuration had the trailer in
the “as-found” condition and the tractor with new but non-optimal tires, and the test condition
demonstrated the effect of new tires and the accompanying good maintenance on the hubs. This
suggests that future studies should examine the effects of maintenance and retrofits on just the
chassis trailers: tires, hubs, lubricants, regular pressure monitoring, etc.
It should be noted, however, that implementation may not be straightforward. In our study, we
tested the truck and trailer (chassis plus cargo container) as a unit, whereas, in real operation, the
tractor is owned and operated by an independent driver working under contract with a drayage
company. In general, the owner/operator is responsible for maintaining and upgrading his/her
own equipment. An owner/operator will be motivated by the fuel savings (which he/she will
realize as a reduction in operating costs) to make the upgrade.
The container chassis, however, are generally owned by the steamship lines, which have no
motivation to install more expensive equipment for the sake of fuel savings since that is not their
cost. It will be the job of the State of Texas to either delegate to TCEQ the work of upgrading
for the steamship lines their chassis pools (buying and installing the tires, wheels, and hubs) or to
establish a state-owned chassis pool with upgraded hubs, rims, and tires. A per-unit calculation
of conversion cost should include the costs of four new tires, four new rims, four new hubs, and
the disposal of eight old tires, rims, and hubs per container chassis.
That is, if the State of Texas is to enjoy the NOx emissions benefits of use of these wide-single
tires for drayage operations, it will require a new policy.
26

Acknowledgements
The preparation of this report is based on work funded by the State of Texas through a grant
from the Texas Environmental Research Consortium with funding provided by the Texas
Commission on Environmental Quality.
The Michelin Americas Research and Development Corporation and the Truck Tire Marketing
Group at Michelin North America provided material support in the form of tire sizing and
selection and two complete sets of tires for the test trucks.
The U.S. Environmental Protection Agency (EPA) provided the aluminum wide-single wheels at
no cost for testing. The wheels had been formerly used for the EPA SmartWay Transport
Partnership Program conducted from October 2005 to April 2006.
References
Bachman, L.J.., A. Erb, and C.L. Bynum (2005), “Effect of Single Wide Tires and Trailer
Aerodynamics on Fuel Economy and NOx Emissions of Class 8 Line-Haul Tractor-Trailers”,
U.S. Environmental Protection Agency, SAE Paper 2005-01-3551.
Bachman, L.J.., A. Erb, C.L. Bynum, B. Shoffner, H. DeLa Fuent, and C. Ensfield (2006), “Fuel
Economy Improvements and NOx Reduction by Reduction of Parasitic Losses: Effect of
Engine Design”, SAE Paper 2006-01-3474.
LaClair, T. J., and R. Truemner (2005), “Modeling of Fuel Consumption for Heavy-Duty Trucks
and the Impact of Tire Rolling Resistance”, SAE Paper 2005-01-3550.
Palacios, C., and T.H. DeFries (2007), “Driving Schedule for Drayage Trucks”, Final Report
from Eastern Research Group to UT, ERG Report No. 3616.00.001.001, April 30.
SAE J1321 (1986), “Joint TMC/SAE Fuel Consumption Test Procedures – Type II”, SAE
International
Shoffner, B., H. DeLaFuente, and M. Kasper (2007), “SAE J1321 Evaluations of Drayage
Trucks”, Final Report from Southwest Research Institute to UT, SwRI Report No. 08.13084,
June 20.
27

Appendix A - Drayage Operator Inventory
Company Contact Phone No./FAX No. URL or e-mail
Port of Houston
270 Cheetah Transportation Van 713-671-0229/713-671-0752
Adams Warehouse & Delivery Al Adams 713-699-3515/713-694-7510 www.adamsdist.com
AllTrans Port Trucking Donna Rains 713-673-7180/713-674-3684
www.alltransportservices.com
Bay Water Trucking Delmas W. Heinke 713-678-4141/713-678-4087 baywatertrans@aol.com
BDS Port Services Fred Dole 281-842-7040/281-842-1328 www.bds-solutions.com
Best Delivery Systems Frieda Lolley (sales) 713-741-8530/713-749-5906
www.best-transportation.com
Bethel Enterprises of Texas Rhonda Bertling ----/713-673-5219
Bridge Terminal Transport Don Smith 800-279-3305/----- www.bttinc.com
Bryan Logistics Ted Gaze 281-291-7771/281-291-7776
Canal Cartage Rick Maddox 713-762-1779/------ www.canalcartage.com
Caribou International Brian J. Mensi 281-528-0720/832-201-9743
www.caribouinternational.com
Carolina National Transportation Julio Magaña 713-554-0563/713-554-0567
juliojr@carolinanational.biz
Century Transportation John 713-224-2121/713-224-1177
Champion Cartage John Champman, Jr. -----/713-676-1335 www.ChampionCartage.com
28
jp.chapman@championcartage.com
Clark Freight Lines John Patteson 281-487-3160/------ www.clarkfreight.com
Commercial Cartage James Adair 713-643-1010/713-643-8762
Container and Trailer Marrying Co Cynthia Keel 713-674-7290/------- www.contramar.com
Double G Transportation Jim Gillis 713-514-8181/713-514-8102
www.globalgrouplogistics.com
Empire Truck Lines Stacey Lowe 713-672-7403/ 713-672-1203 www.emtl.com
Excargo Service Marcia Faschingbauer 713-921-7700/713-921-0099 www.excargo.com
Frontier Logistics John Vossler 800-610-6808/------- www.frontierlogistics.com
Global Group Logistics Jim Gillis 713-514-8077/713-514-8102
www.globalgrouplogistics.com
Gulf Winds 713-747-4909/----- www.gwii.com
Houston Central Industries Sean Harmon 713-225-2081/713-225-4451 www.houcent.com
Houston Transfer & Storage Jim Walt 281-291-7666/281-291-7744 www.teamlogisco.com
Intermodal Cartage Jim Gillis 713-675-4600/713-675-0435 www.imcg.com

J&G Transport Gerardo Escamilla 713-450-4829/713-450-4910 www.jngtransport.com
Land Transportation LLC Ken Palm 281-902-5500 www.slg.com
LOGISCO Dan Verburg 281-291-9494 www.teamlogisco.com
Marko Transportation Doyle Martin 713-729-9500
NOCS Transport , Ltd. Cathy Nagin 504-944-4400
O. B. Transport, Inc. Nanette Garcia 713-672-2382
Overland Express Co. Cecil Simmons 713-672-6161 www.overlandexp.com
Overland Distribution Mark Taylor 713-672-2464 www.overlandexp.com
Palletized Jaime 713-672-7403
Patriot Logistics, Inc. Edwis L. Selph Jr. 713-590-4041 www.patriot-logistics.com
Pinch Transportation Brooks Elliott 713-674-4766 www.pinchtransport.com
Pioneer Freight Bill Burnash 713-860-0343 www.pioneerfrt.com
Port Dispatch service Connie 713-675-6835
Powers Transportation (Schneider) Gary Harbin 713-675-9100 http://www.ptran.com/
Richway Cartage & Richway Transportation Services, Inc.
Don Taylor 713-673-1110 www.richwaycartage.com
Roadmaster Trucking Inc., Carlos Musetti 713-672-0100
Roll-Ex Freight Ways, Inc. Carla McLeod 281-456-8899 rolxfrtwys.com
S & S Traffic Management Corp Barbara O. Wirth 281-902-5500 www.slg.com
SilverTrans, Inc. Earl Silver/Willie Baker 713-455-4411 www.silvertrans.com
Southwest Freight, Inc Michael Johnson 713-633-8889 www.Southwestfreight.com
St. George Warehouse John M. Kanai 713-674-3030 www.stgwarehouse.com
Trans Gulf Transportation Inc Ted Trascher 281-470-0500 www.transgulftrans.com
VersaCold Joe Peraza 281-867-2613 www.versacold.com
W W. Rowland Trucking Co. Gary Conner 713-675-1200 www.wwrowland.com
Walton Barge Terminal Mike Thebeau 713-453-6311
Wm. Morris Enterprises Bill Morris 281-487-4148
World Trade CES Jeff Joaquim 713-672-7295 www.wtcfs.com/contact/contact.htm
Dallas/Ft. Worth Area
Company Name City Contact Phone Fax
Asset Based Intermodal Garland Randall Waldon 972-487-9900 972-487-9901
C & K Trucking, LLC Dallas Matt Schriener 817-652-1490 817-652-6068
Comtrak Logistics Dallas Garland Davis 214-330-6856 214-330-8272
Empire Truck Lines Irving NA 972-870-9455 972-870-9456
Genesis Intermodal Delivery, Inc Dallas Richard Wallace 214-540-5380 214-540-5381
29

Geo-Lesco Inc Garland NA 972-205-0560 972-205-0737
Double G Transportation Dallas Chad Jackson 214-206-7095
Intermodal Bridge Transport, Inc Grand Prarie NA 972-522-2233 972-522-1205
Knight Transportation Inc Texarkana Randell McKnight 870-773-0511 870-773-0661
LAS Trucking Plano Lucky Osa 214-718-0260 214-474-1389
Midwest Intermodal Services Inc Haslet Corey Pate 817-439-0635 817-439-8304
Morgan Southern - DAL Seagoville John Hammett 972-287-6060 972-287-6078
Patriot Logistics, Inc. Irving Art Padilla 972-438-4050 972-438-5022
Richard Daniels Transportation Dallas KC Stephenson 214-341-6759 214-341-2160
Spring Valley Cartage Garland Aaron Wolfe 972-272-2565 972-494-6497
TCI Trucking & Warehousing, Inc. Dallas Mitch Fussell 214-428-0560 214-421-7901
30

Appendix B - J1321 Tire Information
31

Segment
No. Lap
2.7 Times
Ten
Minute
Idle one
(lbs)
3.6 Times
Ten
Minute
Idle two
(lbs)
Appendix C - Detailed J1321 Fuel Consumption and NOx Results
The
remainder
of the test
(lbs)
Total Fuel
Consumed
(lbs)
2.7 Times
Ten
Minute
Idle one
(grams)
3.6 Times
Ten
Minute
Idle two
(grams)
The
remainder
of the test Total NOx
(grams) (grams)
2.7 Times
Ten
Minute
Idle one
(lbs)
3.6 Times
Ten
Minute
Idle two
(lbs)
The
remainder
of the test
(lbs)
Total Fuel
Consumed
(lbs)
2.7 Times
Ten
Minute
Idle one
(grams)
3.6 Times
Ten
Minute
Idle two
(grams)
The
remainder
of the test Total NOx
(grams) (grams)
1 2* 2.71 3.36 57.83 63.9 62.07 56.77 375.38 494.22 2.39 2.99 59.79 65.2 53.97 45.13 410.18 509.28
1 3* 2.57 3.49 58.04 64.1 60.28 57.16 374.46 491.90 2.33 3.18 61.23 66.7 48.28 50.05 418.13 516.46
1 4* 2.87 3.45 57.58 63.9 63.31 57.67 402.43 523.41 2.38 3.09 61.35 66.8 52.64 53.70 447.47 553.81
2 1* 2.65 3.29 60.36 66.3 51.54 48.27 366.16 465.97 2.30 2.88 56.45 61.6 44.90 43.02 350.76 438.68
2 2* 2.76 3.28 56.46 62.5 56.49 42.85 338.98 438.32 2.18 2.91 54.02 59.1 42.99 43.81 340.48 427.28
2 3
2 4* 2.52 3.27 57.51 63.3 51.00 47.40 342.49 440.89 2.35 2.95 54.83 60.1 48.29 50.12 358.52 456.93
3 1* 2.75 3.27 58.08 64.1 53.09 47.27 336.50 436.86 2.22 2.93 54.59 59.7 42.13 41.17 327.09 410.39
3 2* 2.31 3.27 59.32 64.9 42.38 40.84 357.82 441.04 2.33 2.96 55.71 61.0 41.47 42.88 357.04 441.39
3 3
3 4* 2.77 3.23 55.50 61.5 56.35 44.08 351.60 452.03 2.08 2.71 53.28 58.1 41.44 43.79 348.67 433.90
4 1 63.00 53.27 363.76 480.03 42.95 49.51 379.83 472.29
4 2 50.82 56.04 336.97 443.83 53.71 44.88 347.44 446.03
4 3* 2.69 3.32 55.99 62.0 45.31 45.50 322.56 413.37 2.27 2.93 58.36 63.6 41.30 43.16 317.09 401.55
4 4* 2.69 3.32 57.99 64.0 59.03 43.02 310.63 412.68 2.36 3.02 59.89 65.3 41.48 40.29 321.12 402.89
4 5* 2.69 3.32 57.99 64.0 57.10 39.94 324.39 421.43 2.40 3.01 60.28 65.7 43.39 41.16 326.04 410.59
* Laps used for SAE J1321 calculation
Truck 338
Truck 340
Fuel Consumed NOX Fuel Consumed NOX
33