Integrated chassis control algorithm design for path tracking based on four-wheel steering and direct yaw-moment control

This article focuses on an integrated chassis control algorithm design for path tracking utilizing four-wheel steering and direct yaw-moment control. The designed integrated chassis control algorithm mainly consists of three parts: (1) taking the parametric uncertainties, external disturbances, measurement noise and unmodeled dynamics into consideration, a robust controller is designed for path tracking utilizing mu synthesis approach; (2) the control allocation algorithm is proposed to distribute the output torque requirements to each in-wheel motor based on the weighted least square; and (3) considering that vehicle lateral velocity is a critical state variable for path-tracking control, while it is not easy to measure with low-cost sensors, a state observer is designed for lateral velocity estimation using unscented Kalman filter. To verify the performance of the designed integrated chassis control algorithm, three simulation maneuvers including the single-lane change, curve and the double-lane change are carried out in MATLAB/Simulink with a high-fidelity, full-vehicle model built in CarSim. The proposed integrated chassis control algorithm is compared with other three control algorithms, that is, active front steering, four-wheel steering and active front steering + direct yaw-moment control, and simulation results indicate that the integrated chassis control algorithm has superior path-tracking performance and handling stability. The robust performance of the integrated chassis control algorithm is also verified under the variation of vehicle velocity and different road conditions.