Coordinated Longitudinal and Lateral Stability Improvement for Electric Vehicles Based on a Real-Time NMPC Strategy

Abstract

Under extreme conditions, such as low friction surfaces, violent steering and urgent acceleration/deceleration, vehicle states change rapidly and are influenced by nonlinear and coupled vehicle dynamics. To improve vehicle stability under extreme conditions, a hierarchical control strategy is proposed for DDEVs. In the upper layer controller, a combined-slip tire model is adopted to improve the model accuracy under extreme conditions. A nonlinear model predictive control based controller is then designed to generate the desired tire slip ratios with the main objectives of tracking the desired yaw rate and suppressing the lateral velocity and tire slip ratios. In the lower layer controller, the disturbance on the driver’s torque requirement, which is disregarded by existing studies, is taken into account. Next, a linear predictive controller is designed to track the desired tire slip ratios by adjusting the motor torques. To improve the computational efficiency of the nonlinear predictive controller, a PMP-based, fast solving algorithm is proposed. The effectiveness of the proposed solving algorithm is checked by comparing the control performance with IPOPT. The proposed control strategy is evaluated by a series of HIL experiments. The HIL results show better performance in overall stability improvement and minimize the disturbance on the driver’s torque requirement.