Optimal Coordinated Control of ARS and DYC for Four-Wheel Steer and In-Wheel Motor Driven Electric Vehicle With Unknown Tire Model

Abstract

To improve the handling and maneuverability of four-wheel steer (4WS) and in-wheel motor driven electric vehicle (EV) in which the mechanical properties of tires are unknown, an optimal coordinated control combining active rear wheel steering (ARS) and direct yaw moment control (DYC) in the form of active drive torque distribution is proposed. By designing a new type of particle filter (PF), the online identification of unknown tire model is realized and its uncertainties and road surface disturbances are both considered. The constraints of vehicle motions tracking ideal values are derived according to the estimated tire lateral forces with Lyapunov stability theory. And then based on the thought of backstepping and optimization, the drive torque distribution method and the rear wheel steer strategy are obtained aiming at minimizing tire load and control inputs, which also take the effective working range of in-wheel motor into account. Finally, the validity and practicability of overall controller are verified through the simulation of Carsim and Matlab/Simulink. The proposed control strategy lays a theoretical foundation for the integration and optimization of 4WS EVs driven by in-wheel motors.