AFS/DYC Control of In-Wheel Motor Drive Electric Vehicle With Adaptive Tire Cornering Stiffness

A linear tire model with constant conering stiffness does not guarantee the model accuracy, while a traditional nonlinear tire model has to face complicated parameter adjustment problems. In order to improve the adaptive capability of path tracking controller for a in-wheel motor drive electric vehicle (IDEV), the cornering stiffness is regarded as a time-varying parameter when tire sideslip angle increases. For the upper controller, the lateral tire force is estimated online based on square root cubature Kalman filter (SRCKF) to solve the cornering stiffness uncertainty. Then a prediction model of MPC with cornering stiffness modified is proposed to reduce the effect of model mismatch. For the lower controller, an active front steering control (AFS) and direct yaw moment control (DYC) based on integrated MPC is designed to track path and improve handling stability. The proposed control strategy is verified under extreme conditions through CarSim/Simulink simulation. It is shown that the strategy effectively improves the accuracy of path tracking and the stability of vehicle compared with the conventional MPC controller.