臺灣博碩士論文加值系統

This thesis investigates a strategy that seeks to improve the stability of the tractor semi-trailer by controlling the rear wheels of the tractor unit to track a desired articulation angle. A linear quadratic regulator controller with tracking capability was designed in Simulink to track the desired articulation angle using tractor rear wheel steering. The performance of the controller was tested by interfacing Simulink with TruckSim, thereby allowing the use of TruckSim’s accurate vehicle model. From the simulations, it was found that by tracking the desired articulation angle, the roll and yaw stability of the tractor semi-trailer improved except in cases where sharp inputs are given in low road-tire friction coefficient conditions, e.g. J-turn. It was also found that it is crucial for the driver/system to consider the rear wheel kinematics of the tractor unit when deciding on the steering input of the front wheels. To verify the simulation results, scaled vehicle testing, using the principle of dynamic similarity was attempted; however, due to the speed limitations of the designed scaled articulated vehicle, the pi-groups could not be matched successfully, therefore, the simulation results could not be verified using scaled vehicle testing.

This thesis investigates a strategy that seeks to improve the stability of the tractor semi-trailer by controlling the rear wheels of the tractor unit to track a desired articulation angle. A linear quadratic regulator controller with tracking capability was designed in Simulink to track the desired articulation angle using tractor rear wheel steering. The performance of the controller was tested by interfacing Simulink with TruckSim, thereby allowing the use of TruckSim’s accurate vehicle model. From the simulations, it was found that by tracking the desired articulation angle, the roll and yaw stability of the tractor semi-trailer improved except in cases where sharp inputs are given in low road-tire friction coefficient conditions, e.g. J-turn. It was also found that it is crucial for the driver/system to consider the rear wheel kinematics of the tractor unit when deciding on the steering input of the front wheels. To verify the simulation results, scaled vehicle testing, using the principle of dynamic similarity was attempted; however, due to the speed limitations of the designed scaled articulated vehicle, the pi-groups could not be matched successfully, therefore, the simulation results could not be verified using scaled vehicle testing.

Chapter 1: Introduction 1
1.1 Background and Motivation for Research into the Tractor Semi-Trailer 1
1.2 Purpose of the Thesis 2
1.3 Thesis Objectives 3
1.4 Methodology 3
1.5 Literature Review 4
Chapter 2: The Articulated Vehicle Model 6
2.1 The Complex Articulated Vehicle Model 7
2.2 Linearizing the Complex Articulated Vehicle Model 8
2.3 TruckSim 12
2.3.1 The Articulated Vehicle 13
2.3.2 Tire Model 14
2.3.3 Driver Model 16
2.4 Validation of the Simple Articulated Vehicle Model with TruckSim Data 17
2.4.1 Validation Procedure 17
2.4.2 Estimating the Cornering Stiffness of Each Tire for the Simple Model 18
2.4.3 Results of the Model Validation 21
Chapter 3: Controller Design 28
3.1 Control Strategy 28
3.2 Controller Selection 32
3.3 Controller Design 33
3.3.1 Controllability 33
3.3.2 Modification of the Simple Model 33
3.3.3 The LQR Controller 34
3.3.4 Selection of the [Q] and [R] matrices 42
Chapter 4: Verifying the Controller Design Using Simulation 45
4.1 Open Loop Steer Input 46
4.1.1 Step Input 46
4.1.2 J-turn (Fishhook) 50
4.1.3 Summary of the Results for Open Loop Steer Input 55
4.2 Double Lane Change 57
4.2.2 Trailer Sway 58
4.2.3 Rollover 60
4.2.4 Jackknife 62
4.2.5 Summary of the Results for the Double Lane Change Manoeuvre 63
4.3 Real Road Simulation 68
Chapter 5: Scaled Vehicle Testing 72
5.1 Method to Ensure Dynamic Similarity 72
5.1.1 Obtaining the Pi-Groups 73
5.1.2 Simulation Evidence to Support the Principle of Dynamic Similarity 76
5.2 Building the Scaled Articulated Vehicle 81
5.2.1 Material Used 81
5.2.2 Driving and Steering Motors 81
5.2.3 Sensor Used to Measure the State Vector 82
5.2.4 Implementing the Controller 84
5.2.5 The Completed Scaled Articulated Vehicle 89
5.3 Experimental Validation 91
5.3.1 Adjusting the Pi-Groups 91
5.3.2 Issues with the Designed Scaled Articulated Vehicle 96
5.3.3 Results of the Scaled Articulated Vehicle Test 97
5.4 Suggested Improvements for Future Scaled Articulated Vehicle Testing 99
Chapter 6: Conclusion 101
REFERENCES 102
APPENDIX A 104
APPENDIX B 107

[1] Department of Infrastructure and Regional Development, “Heavy truck safety: crash analysis and trends,” Australia, Jul.2016.
[2] National Highway Traffic Safety Administration, “An Analysis of Fatal Large Truck Crashes,” United States of America, Jun.2003.
[3] American Automobile Association Foundation for Traffic Safety, “Leveraging Large-Truck Technology and Engineering to Realize Safety Gains: Air Disc Brakes,” Sep.2017.
[4] American Automobile Association Foundation for Traffic Safety, “Leveraging Large-Truck Technology and Engineering to Realize Safety Gains: Video-Based Onboard Safety Monitoring Systems,” Sep.2017.
[5] American Automobile Association Foundation for Traffic Safety, “Leveraging Large-Truck Technology and Engineering to Realize Safety Gains: Automatic Emergency Braking Systems,” Sep.2017.
[6] American Automobile Association Foundation for Traffic Safety, “Leveraging Large-Truck Technology and Engineering to Realize Safety Gains: Lane Departure Warning Systems,” Sep.2017.
[7] Federal Motor Carrier Safety Administration, “Large Truck and Bus Crash Facts 2015.” [Online]. Available: https://www.fmcsa.dot.gov/safety/data-and-statistics/large-truck-and-bus-crash-facts-2015#A5. [Accessed: 18-Dec-2017].
[8] N.L.Azad, A.Khajepour, and J.McPhee, “Analysis of jackknifing in articulated steer vehicles,” in 2005 IEEE Vehicle Power and Propulsion Conference, 2005, pp. 86–90.
[9] Z.Tianjun and Z.Changfu, “Modelling and Active Safe Control of Heavy Tractor Semi-Trailer,” in 2009 Second International Conference on Intelligent Computation Technology and Automation, 2009, vol. 2, pp. 112–115.
[10] L.K.Chen and Y.A.Shieh, “Jackknife Prevention for Articulated Vehicles Using Model Reference Adaptive Control,” National Taiwan University of Science and Technology, 2011.
[11] R.McCann and A.Le, “Electric motor based steering for jackknife avoidance in large trucks,” in 2005 IEEE Vehicle Power and Propulsion Conference, 2005, vol. 2005, pp. 103–109.
[12] T.Kaneko, I.Kageyama, and H.Tsunashima, “Braking Stability of Articulated Vehicles on Highway,” Veh. Syst. Dyn., vol. 37, pp. 1–11, 2002.
[13] R. C.Lin, D.Cebon, and D. J.Cole, “Active roll control of articulated vehicles,” Veh. Syst. Dyn., vol. 26, no. 1, pp. 17–43, 1996.
[14] S.Manesis, N.T.Koussoulas, and G.N.Davrazos, “On the Suppression of Off-tracking in Multi-articulated Vehicles through a Movable Junction Technique,” J. Intell. Robot. Syst., vol. 37, no. 4, pp. 399–414, 2003.
[15] N.Koussoulas, S.Manesis, and G.Davrazos, “A hybrid system approach to off-tracking suppression in multi-articulated vehicles,” in 2007 European Control Conference (ECC), 2007, pp. 652–658.
[16] M.Sampei, T.Tamura, T.Kobayashi, and N.Shibui, “Arbitrary path tracking control of articulated vehicles using nonlinear control theory,” IEEE Trans. Control Syst. Technol., vol. 3, no. 1, pp. 125–131, 1995.
[17] P.Bolzern and A.Locatelli, “A comparative study of different solutions to the path-tracking problem for an articulated vehicle,” in Proceedings of the International Conference on Control Applications, 2002, vol. 1, pp. 427–434 vol.1.
[18] C.Chen and M.Tomizuka, “Modeling And Control Of Articulated Vehicles.,” Berkeley, United States of America, Nov.1997.
[19] Q.Wang, K.Okumura, M.Oya, and T.Kobayashi, “Adaptive steering controller to improve handling stability of combined vehicles,” in Second International Conference on Innovative Computing, Information and Control, ICICIC 2007, 2008.
[20] J.B.Burl, Linear Optimal Control: H2 and H∞ Methods. Addison Wesley Longman, 1999.
[21] S.Brennan, “Modeling And Control Issues Associated With Scaled Vehicles,” University of Illinois, Urbana-Champaign, United States of America, 1999.
[22] S.Brennan, “On size and control: the use of dimensional analysis in controller design,” University of Illinois, Urbana-Champaign, United States of America, 2002.