Kalman Filter-Based Fusion Estimation Method of Steering Feedback Torque for Steer-by-Wire Systems

Abstract

Universal challenge lies in torque feedback accuracy for steer-by-wire systems, especially on uneven and low-friction road. Therefore, this paper proposes a fusion method based on Kalman filter that combines a dynamics-reconstruction method and disturbance observer-based method. The dynamics- reconstruction method is designed according to the vehicle dynamics and used as the prediction model of the Kalman filter. While the disturbance observer-based method is performed as an observer model of the Kalman filter. The performance of all three methods is comprehensively evaluated in a hardware-in-the-loop system. Experimental results show that the proposed fusion method outperforms dynamics reconstruction method and disturbance observer-based method. Specifically, compared with the dynamics-reconstruction method, the root mean square error is reduced by 36.58% at the maximum on the flat road. Compared with the disturbance observer-based method, the root mean square error is reduced by 39.11% at the maximum on different-friction and uneven road.