Robust gain-scheduled output feedback yaw stability control for in-wheel-motor-driven electric vehicles with external yaw-moment |
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| Institution: | 1. School of Mechanical Engineering, Southeast University, Nanjing 211189, China;2. State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, China;3. Department of Mechanical and Aerospace Engineering, The Ohio State University, Columbus 43210, USA;1. State Key Laboratory of Automotive Simulation and Control, Jilin University, PR China;2. Department of Control Science and Engineering, Jilin University, PR China |
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| Abstract: | This paper presents a robust gain-scheduled output feedback yaw stability H∞ controller design to improve vehicle yaw stability and handling performance for in-wheel-motor-driven electric vehicles. The main control objective is to track the desired yaw references by managing the external yaw moment. Since vehicle lateral states are difficult to obtain, the state feedback controller normally requires vehicle full-state feedback is a critical challenge for vehicle lateral dynamics control. To deal with the challenge, the robust gain-scheduled output feedback controller design only uses measurements from standard sensors in modern cars as feedback signals. Meanwhile, parameter uncertainties in vehicle lateral dynamics such as tire cornering stiffness and vehicle inertial parameters are considered and handled via the norm-bounded uncertainty, and linear parameter-varying polytope vehicle model with finite vertices is established through reducing conservative. The resulting robust gain-scheduled output feedback yaw stability controller is finally designed, and solved in term of a set of linear matrix inequalities. Simulations for single lane and double lane change maneuvers are implemented to verify the effectiveness of developed approach with a high-fidelity, CarSim®, full-vehicle model. It is confirmed from the results that the proposed controller can effectively preserve vehicle yaw stability and lateral handling performance. |
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