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Masters Thesis: Vehicle Dynamics Control Using Control Allocation Vehicle Dynamics Control Using Control Allocation Karan Chatrath Master of Science Thesis Department Of Cognitive Robotics (CoR) Vehicle Dynamics Control Using Control Allocation Master of Science Thesis For the degree of Master of Science in Vehicle Engineering at Delft University of Technology Karan Chatrath July 12, 2019 Faculty of Mechanical, Maritime and Materials Engineering (3mE) · Delft University of Technology Copyright c Department Of Cognitive Robotics (CoR) All rights reserved. Delft University of Technology Department of Department Of Cognitive Robotics (CoR) The undersigned hereby certify that they have read and recommend to the Faculty of Mechanical, Maritime and Materials Engineering (3mE) for acceptance a thesis entitled Vehicle Dynamics Control Using Control Allocation by Karan Chatrath in partial fulfillment of the requirements for the degree of Master of Science Vehicle Engineering Dated: July 12, 2019 Supervisor(s): Dr. Barys Shyrokau Yanggu Zheng Reader(s): Dr.ir.Tamas Keviczky Dr. Bilge Atasoy Abstract Advancement of the state of the art of automotive technologies is a continuous process. It is essential for automotive engineers to combine the knowledge of vehicle dynamics and control theory to develop useful applications that meet requirements of improved safety, comfort and performance. A road vehicle is equipped with several actuators that can assist a user during a dynamic driving task and ensure overall system reliability. Using all available actuators effectively to make a vehicle move in the desired manner is necessary. Typically, the available actuators outnumber the states of motion to be controlled. Such mechanical systems are referred to as over-actuated. An effective way to control an over-actuated system is through the use of control allocation (CA).CA ensures coordination between, and the optimal use, of all available actuators. This strategy also considers the limits of the actuators. Despite its features, a lot ofCA methods have a drawback that actuator dynamics are neglected. This drawback has been addressed with a method called model predictive control allocation (MPCA). The behaviour of mechanical actuators is usually approximated by simplified models. Un-modelled system dynamics are always a source of uncertainty. Also, the aging of actuators introduces the element of uncertainty. The ability of MPCA to handle uncertainties is investigated and a solution is proposed to overcome this shortcoming. The proposed solution is the combination of an online adaptive parameter estimator with the MPCA strategy. This way, the CA solver is constantly updated with the parameters of each actuator. This technique is used to design vehicle stability controllers and their performance on simulation is reported. The results indicate that the proposed control allocation technique is effective for vehicle stability control in various scenarios. However, scope for betterment has been recognised and relevant recommendations are made, to conclude this work. Master of Science Thesis Karan Chatrath ii Karan Chatrath Master of Science Thesis Table of Contents Acknowledgements xiii 1 Introduction1 1-1 Introduction to Electronic Stability Control..................... 2 1-2 Over-actuated Mechanical Systems......................... 3 1-3 Control Allocation.................................. 4 1-4 Problem Definition................................. 5 1-5 Summary Of Work Done.............................. 5 1-6 Contributions.................................... 7 1-7 Layout of This Master Thesis............................ 7 2 Vehicle Dynamics Modelling9 2-1 IPG CarMaker Multi Body Vehicle Model..................... 9 2-2 Planar Vehicle Model................................ 10 2-2-1 Vehicle Body................................ 10 2-2-2 Wheel and Tire Related Quantities..................... 13 2-3 Tire Modelling.................................... 14 2-3-1 Linear Tire Model And Friction Circle................... 14 2-3-2 Dugoff Tire Model............................. 15 2-4 The Linear Bicycle Model.............................. 15 2-5 Actuator Dynamics................................. 16 2-5-1 Brake Actuator Dynamics.......................... 16 2-5-2 Steering Actuator Dynamics........................ 18 2-6 Dynamic Driving Manoeuvre............................ 19 2-7 Validation Of The Planar Model.......................... 20 2-8 Summary....................................... 22 Master of Science Thesis Karan Chatrath iv Table of Contents 3 Control Allocation Theory 23 3-1 Control Allocation Problem Formulation...................... 23 3-2 Control Allocation Methods - A Brief Literature Review.............. 24 3-3 Weighted Least Squares Control Allocation.................... 26 3-4 Dealing With Actuator Dynamics.......................... 27 3-5 Model Predictive Control Allocation........................ 28 3-6 A Simple Example.................................. 31 3-7 MPCA With Adaptive Parameter Estimation (APE)................ 34 3-7-1 Online adaptive parameter estimation................... 35 3-7-2 Combining APE with MPCA........................ 36 3-8 Summary....................................... 38 4 Electronic Stability Control Using Control Allocation 39 4-1 Sine With Dwell Test With No Control....................... 39 4-2 General Layout Of The Stability Control System.................. 40 4-3 Reference Generator................................. 41 4-4 High-Level Controller................................ 43 4-5 Control Effectiveness Matrix Derivation...................... 44 4-5-1 Case 1: 4 Actuators - Differential Braking................. 45 4-5-2 Case 2: 5 Actuators - Differential Braking And Active Front Steering.. 45 4-6 Summary Of All Simulation Scenarios....................... 46 4-6-1 Configuration 1: With Four Actuators................... 46 4-6-2 Configuration 2: With Five Actuators................... 46 4-6-3 Additional Scenarios............................. 47 4-7 Details Of Simulation Scenarios and Results.................... 47 4-7-1 Tuning Parameters............................. 48 4-7-2 Simulation Scenario Case E......................... 51 4-7-3 Simulation Scenario - Case J........................ 53 4-8 Additional Vehicle Dynamics Factors........................ 54 4-8-1 Tire Limits As Control Allocation Constraints............... 55 4-8-2 Variation of Cornering Stiffness....................... 56 4-9 Simulations Scenarios: Cases K and M....................... 58 4-9-1 Simulations With Hydraulic Brake Model................. 60 4-10 Summary....................................... 63 5 Conclusions And Recommendations 65 5-1 Highlights And Conclusions............................. 65 5-2 Recommendations And Scope For Future Work.................. 66 A Planar vehicle model and Dugoff model validation 69 Karan Chatrath Master of Science Thesis Table of Contents v B ESC with Control Allocation - Results 73 B-1 Case A Results.................................... 73 B-2 Case B Results.................................... 75 B-3 Case C Results.................................... 77 B-4 Case D Results.................................... 79 B-5 Case E Results.................................... 80 B-6 Case F Results.................................... 81 B-7 Case G Results.................................... 83 B-8 Case H Results.................................... 85 B-9 Case I Results.................................... 87 B-10 Case J Results.................................... 88 B-11 Case K Results.................................... 91 B-12 Case L Results.................................... 93 B-13 Case M Results................................... 95 Bibliography 97 Glossary 101 List of Acronyms................................... 101 Master of Science Thesis Karan Chatrath vi Table of Contents Karan Chatrath Master of Science Thesis List of Figures 1-1 Working Of ESC Using Differential Braking.................... 2 1-2 Control allocation general strategy......................... 4 2-1 Planar vehicle motion indicating coordinate frames................ 10 2-2 Hydraulic brake model schematic for a single wheel................ 17 2-3 Pfeffer Steering Model............................... 19 2-4 Sine With Dwell Test Steering Input........................ 20 2-5 Validation with Steering wheel angle amplitude of 120 degrees.......... 21 2-6 Dugoff Tire Model Validation - Steering Wheel Angle 120 degrees........ 21 3-1 Weighted Least squares CA block diagram..................... 27 3-2 Control allocation with actuator dynamics considered............... 28 3-3 Simple example - WLS - CA - No actuator Dynamics............... 32 3-4 Simple example - WLS - CA - With actuator Dynamics.............. 33 3-5 Simple example - MPCA.............................. 33 3-6 Simple example - MPCA with actuator uncertainties............... 34 3-7 Simple example - APE with MPCA......................... 37 3-8 Simple example - APE with MPCA - Parameter Convergence........... 37 4-1 Vehicle Response With No Control......................... 40 4-2 General Block Diagram for ESC Using Control Allocation............. 41 4-3 Reference signals for yaw rate control for the sine with dwell test......... 42 4-4 MPCA BLOCK Diagram - General......................... 49 4-5 APE+MPCA BLOCK Diagram - General...................... 50 4-6 Sine With Dwell - Case E - Vehicle Response................... 52 4-7 Sine With Dwell - Case E - Actuator Response................... 52 Master of Science Thesis Karan Chatrath viii List of Figures 4-8 Sine With Dwell - Case
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