Class-8 Heavy Truck Duty Cycle Project Final Report - Center for ...

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Lesson Learned: Adding external sensors and systems to a test vehicle can introduce unexpected results. Again, ample shake down testing through all phases of vehicle operation is required to identify problems in advance of the FOT. 7.2.1.5 DAS wiring Vibration and its effects on electrical connectors are well known. In order to protect against longterm connection problems, a decision was made to “hard wire” as much of the DAS and sensor system as possible and to eliminate as many connectors as possible. While this approach accomplished the goal of eliminating failures due to vibration damage to connections, it made removing the DAS units from the test vehicles very difficult due to the fact that there were no connectors to allow the various sensors and power wires to be removed quickly. Lesson Learned: For future FOTs using this or a similar DAS, mil-spec electrical connections should be utilized and tested. This will allow for easy removal of the DAS from a given test vehicle for calibration, maintenance, or repair. 7.2.1.5 System design documentation During the Pilot Test, various DAS and sensor systems were tested to determine the equipment and equipment configurations best suited for the FOT data collection effort. Dana led this effort and gained the expertise necessary to move to the next phase of the program. However, when Dana entered bankruptcy negotiations at the end of the Pilot Test effort, much of this expertise was lost due to personnel changes at Dana. ORNL subsequently had to regain this experience and knowledge during Phase II of the program. To prevent this from happening again in the program, ORNL began to document its efforts in a Systems Design and Operations Document (Appendix D). This document is a detailed, step-by-step instruction manual that calls out the specific equipment used, describes the configuration of this equipment, shows detailed schematics of the systems, and explains the nature of the signals collected and their use. Lesson Learned: A Systems Design and Operations Document should be developed and deployed for research projects utilizing complex DASs to interface with vehicles systems. This is done to prevent the loss of expertise in the event of personnel changes or entity changes. 7.2.2 Non-Corrected, Negative Lessons Learned 7.2.2.1 Vehicle availability Because of the nature of long-haul operations, all test vehicles were not always available to ORNL for data down-load on Saturdays and Sundays during the FOT. This situation increased the number of visits required to Schrader to collect the FOT data, prevented in some cases the early detection of issues with the DAS equipment, and in some cases caused the DAS data buffers to fill and overflow (data loss). Lesson Learned: Even in an operation which allows all of its vehicles to return home each weekend, circumstances do not always allow for their return. Circumstances that contribute to vehicle unavailability include: extended trips, vehicle breakdown, equipment warranty work, and driver schedule. Sufficient planning and budgeting allowances must be factored in to account for this inefficiency. 104
7.2.2.2 Driver communication Again, because of the nature of long-haul operation, communications with the drivers of the test vehicles was difficult and indirect. This made getting information from the drivers about equipment issues (i.e. weather station damage), and information to the drivers about ORNL’s needs (e.g. increasing the number of weigh tickets so that ORNL could have data to correlate with the data provided by the on-board Air-Weigh system), more problematic and introduced more uncertainty into the process. Lesson Learned: An effective communication method/protocol is needed with all personnel within all organizations that are partners in research projects of this nature. 7.2.2.3 Travel While the distance from ORNL to Schrader was approximately 45 miles, allowing weekly access to most of the test vehicles, it required a substantial amount of driving for each data collection event. Now that wireless technology has further improved and has been further adopted by DAS manufacturers, it is recommended that the use of wireless data collection be explored and considered for subsequent data collection efforts. Lesson Learned: Collecting data remotely adds time and cost considerations that are hard to quantify in the planning stages of a project. Lesson Learned: Effective wireless data collection could greatly reduce manpower requirements for FOT data collection efforts. 7.2.2.4 Tractor-trailer marriage Almost all tractor-trailers involved in long-haul trucking operations in the US are not “married.” This means that a tractor could pull a different trailer on every run. It is conceivable that a tractor might not pull the same trailer twice, or, if it does, the occurrence will be relatively infrequent. For the HTDC project, marriage was desirable so that the DAS could see the Air-Weigh weigh sensor on the instrumented trailers and gather fuel usage data linked to a specific trailer’s tires. It was hoped that Schrader could establish an operational protocol that could “force fit” instrumented tractors to pull instrumented trailers in order to increase the percentage of marriage between the test tractors and the test trailers. However, the data analysis section of this report (Chapter 6) shows that the percentage of marriage was no higher that it would have been if the tractors and trailers were selected at random (the normal process). Lesson Learned: When working with real-world fleets, the operational needs of partner fleets tend to take precedence over research, when day-to-day decisions in operations are made. It is difficult or perhaps impossible to change the percentage of tractor-trailer marriage. 7.2.2.5 “Calibration” of fuel readings During the FOT a decision was made to use fuel tickets to corroborate the readings obtained from the truck databus regarding fuel consumption. This would allow for reasonably accurate estimates of fuel consumption to be made using the fuel consumption data from the vehicle data bus. However, as explained in the data analysis section of this report (Chapter 6), there were several problems with the fuel ticket information that severely restricted their usefulness in the assessment and calibration of the information obtained from the databus. Some fuel tickets were missing, and it was impossible to 105
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Class-8 Heavy Truck Duty Cycle Proj
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Vehicle Systems Program ORNL/TM-200
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2.7 LAUNCH OF THE FOT (OCTOBER 23,
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40 Connection and Support Structure
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LIST OF TABLES Table Page 1 Pilot T
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ACKNOWLEDGEMENTS The Oak Ridge Nati
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Sixty channels of data were collect
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xviii
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The data analyses performed in Phas
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Fig. 2. HHDDT Transient Mode In add
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vehicle; 3) a transit bus; 4) a nei
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payload and accessory load would al
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Data # Performance Measure Benefit
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Data # Performance Measure Benefit
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Fig. 10. NGK NOx/O2 Sensors Fig. 11
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1.3.4 De-instrumentation: Following
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Fig. 16. Pilot Test North-South Rou
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GPS information collected with the
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2.1 REVIEW OF PERFORMANCE MEASURE R
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2.3.2 Performance Measures Fig. 18.
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Signal Sensor 53 Road Grade Calcula
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2.3.6 Tractor and Trailer Details F
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determined that the particular CANo
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Cable runs to and from sensors were
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2.8 CONDUCTION OF FOT The FOT laste
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3. INTERNET DATA ACCESS TOOL The HT
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Fig. 30. Search Results The file se
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When the button “Extract Data”
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Data Fig. 33. Segment Merging In ad
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Fig. 36 shows the synthetic cycle g
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Fig. 39. A Synthetic Duty Cycle wit
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tractors) as well as the maximum to
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vehicle was carrying a heavy load o
Page 74 and 75: Vehicle Speed [mph] Vehicle Speed [
Page 76 and 77: 5.2 REAL-WORLD DUTY CYCLES Informat
Page 78 and 79: Vehicle Speed [mph] 70 60 50 40 30
Page 80 and 81: Given the size and complexity of th
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Page 84 and 85: 6.1.1 Spatial Information Using the
Page 86 and 87: For those cases in which an instrum
Page 88 and 89: Fig. 56. DCGenT Prototype Search Cr
Page 90 and 91: at constant speed. Parameters m, b,
Page 92 and 93: weight. Notice that, as expected, m
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Page 98 and 99: q q ( − ) ( feb'− feb) 100 '
Page 100 and 101: Table 15. General Statistics: Total
Page 102 and 103: 70% 60% 50% 40% 30% 20% 10% 0% Idli
Page 104 and 105: Fig. 68. All Trips with Dual Tires
Page 106 and 107: The almost 700,000 miles logged dur
Page 108 and 109: Frequency 300 250 200 150 100 50 0
Page 110 and 111: Speed [mph] 80 70 60 50 40 30 20 10
Page 112 and 113: vehicle is hauling light or heavy l
Page 114 and 115: Frequency 350 300 250 200 150 100 5
Page 116 and 117: A summary of the statistics describ
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Page 120 and 121: 6.3.2.4 Summary of Fuel Efficiency
Page 122 and 123: Lesson Learned: A technology progre
Page 126 and 127: know if the vehicle was “filled u
Page 129 and 130: 8. SUMMARY OF RESULTS AND CONCLUSIO
Page 131 and 132: 9. FUTURE DIRECTIONS The Heavy Truc
Page 133: Appendix A PILOT TEST LETTER REPORT
Page 136 and 137: 1.0 BACKGROUND 2.0 PROJECT OVERVIEW
Page 138 and 139: ACKNOWLEDGEMENTS The authors wish t
Page 140 and 141: evaluate the data collection system
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Page 144 and 145: March and provided to the ORNL Prog
Page 146 and 147: Between January, 2005 and May, 2005
Page 148 and 149: Figure 4: NGK Sensor Figure 5: Omeg
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Page 152 and 153: Figures 28 through 31 show the ball
Page 154 and 155: Figure 22: Airweigh System Figure 2
Page 156 and 157: DVD. Figures 35 and 36 show some of
Page 158 and 159: 3.3.7.1 Pre-Analysis Efforts: As th
Page 160 and 161: Task 1: Identification of Fleet(s)
Page 162 and 163: Data # Performance Measure Performa
Page 164 and 165: Sensor or eDaq Performance Performa
Page 166 and 167: 45 46 47 48 49 50 51 52 53 Measure
Page 168 and 169: Data # 62 63 64 65-67 68-69 70-71 7
Page 170 and 171: Data # Performance Measure 87 Headi
Page 172 and 173: Appendix A-B Final Pilot Test Plan
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• DAS/sensor suite/cabling operab
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9 10 11 12 13 14 15 Lateral Velocit
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34 Rain Intensity 35 36 37 38 39 40
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59 60 61 62 63 64 65-67 68-69 70-71
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85 Longitude 86 Velocity 87 Heading
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3.2 Sensors The PMs listed in Table
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vehicles will be dedicated to the p
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DATE TEST ENGINEER: DRIVER: DEPARTI
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Jim Ridge, Dana Product Engineer, w
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Table 5.1 October Route and Schedul
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Table 5.2 December Route and Schedu
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Appendix A-C Field Test Signals 64
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9 Performance Measure Performance M
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Performance Measure 25 Rain Duratio
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Letter Report SUMMARY OF RELEVANT H
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Sensor or Performance Data Sensor o
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GAWR 44 lb AirWeigh 5800 Road Surfa
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Appendix B SCHRADER MEMORANDUM OF U
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MOU-UTB-2007001 Schrader Trucking C
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MOU-UTB-2007001 Schrader Trucking C
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Appendix C FIELD OPERATIONAL TEST P
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Collection, Analysis, and Archiving
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4.0 APPROACH Phases 2 and 3 of the
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Signal Sensor 60 Tractor-Trailer Ma
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Schrader Trucking will provide six
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Sensitive Information] [Partner Sen
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4.6 Sensor and DAS Integration to T
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5.5 Vehicle Deployment Methodology
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Start address: 2360 Cherahala Blvd
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Figure 6.2: Schrader Shop, Far Left
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Figure 6.7: eDAQ Lite with two Vehi
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6.5 Safety Information For Student
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Appendix D SYSTEM DESIGN AND OPERAT
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TABLE OF CONTENTS Collection, Analy
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9.1.2. Shutdown Procedure 9.1.3. SI
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Signal Sensor 26 Cruise Control Acc
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Figure 4.1: Air-Weigh System Compon
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4.5. EDAQ The eDAQ Lite is connecte
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the equipment inside from overheati
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5.4. Weather Station Connections Fi
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Figure 5.5.3: VBOX Cable Table 5.5.
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Figure 6.3: Weather Station Locatio
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6.6 Power Supply Use a second cable
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can also be changed from this windo
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on and the yellow light should begi
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Figure 7.1.3-1: Weather Station and
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Speed unit: m/s Sampling frequency:
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iii) Click on Browse to find and op
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c) Power Controller (Power) - no co
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1) Select the Transducer and Messag
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Figure 7.2.4-2: Adding Transducer C
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Figure 7.2.4-3: Editing DIO Vehicle
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A. Changing Units - Converting tran
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C. Coordinates - Assign correct sig
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switch) Table 7.2.5: Contents of Ti
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Trigger Delay Setup: Check Enable d
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Figure 7.2.5-6: Time Base Shifter S
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Units: Full Scale Estimate - Min: 0
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Figure 7.2.6-2: Burst History Data
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Press Ctrl+3 (or click Run in the T
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8.2. Procedures for Heavy Truck Dut
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d) Turn on the ignition. e) Turn on
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4) Change the IP address field to t
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5) Check to see that the computer c
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e) When all SIC files have been sav
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4) To verify the time setting, go t
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e) Alter the id, mask, value, etc.
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Longitudinal CAN 0x87FF 0x0304 Long
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ULSB 0x98EAFFFBC1FE00 MaxVehSpLm CA
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Figure 9.1.6-2: Performing a ColdSt
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Table 9.2.2-1: Descriptions and Uni
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Channel ID Sensor Format Integer? P
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Channel ID eDAQ Invalid Data Value
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Channel ID Resolution Accuracy Note
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9.3. Appendix C: Additional DAS Not
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e replicated and saved as five iden
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2) Type in “cmd” 3) Type “ipc
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Producing multiple setup files 1) G
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9.4. Appendix D: Checklists and For
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D-96
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9.5. Appendix E: References and Web
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E-3
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E-5
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E-7
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E-9
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E-11
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E-13
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E-15
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E-21
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E-23
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E-25
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E-27
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E-29
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E-33
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