LAUSR

Abstract Braking and steering are common maneuvers performed by drivers during driving. This paper presents a hierarchy control strategy to coordinate the braking and steering performance for in-wheel motor drive electric vehicles (IWMD EVs). A particle swarm optimization-based nonlinear predictive control (PSO-NMPC) scheme is proposed to calculate the required longitudinal force, lateral force and yaw moment of the vehicle in the upper controller. In the lower controller, the PSO algorithm is again utilized to realize the required forces and yaw moment through optimal torque allocation and brake actuator regulation while maintaining vehicle stability and maximizing the regenerative braking recovery. A fault-tolerance mechanism is also incorporated to enhance the robustness of the proposed method. Finally, the effectiveness of the proposed scheme is examined under various braking execution scenarios through the Carmaker-Simulink co-simulation. The results show that the proposed scheme outperforms other state-of-the-art methods in all-round aspects.