Abstract: The intelligent chassis corner module system achieves a high degree of integration of by-wire drive/brake, by-wire steering, and active suspension. The corner module eliminates mechanical connections and reduces a large number of mechanical transmission components, supporting independent control of each dynamic unit of the vehicle. This facilitates software-defined and redundant reliability design, making it an ideal carrier for driverless vehicles. However, excessive steering angle control inputs increase the overall control difficulty of the vehicle. Relying solely on traditional steering control methods can easily lead the vehicle into a nonlinear unstable state. To improve the accuracy and stability of vehicle path tracking, a model predictive control(MPC) method based on the instantaneous center of rotation(ICR) is proposed. A corner module vehicle dynamics model and path planning model are established. By converting between Cartesian and polar coordinate systems, a decoupling mapping between vehicle motion and ICR is established. The traditional wheel angle control is transformed into ICR control. Based on model predictive control, coordinated control of lateral and yaw motions is achieved. A wheel angle calculation method with low system conservatism, applicable to the path tracking system of corner module vehicles, is proposed. Combining with closed-loop system feedback, an ICR model predictive control strategy is constructed. The effectiveness and real-time performance of the proposed control strategy are verified through co-simulation and hardware-in-the-loop testing platforms. Simulation results show that the proposed ICR tracking control strategy effectively ensures the accuracy and stability of path tracking, providing significant reference value for the design of steering control systems in corner module vehicles.

Key words: ICR control, path tracking, model predict control, four wheel independent steering, driverless car