Distributed Drive Electric Vehicles Lateral Stability Strategy

In this paper, an adaptive weight model predictive control strategy (AWMPC) is proposed for the handing stability control of a distributed drive electric vehicle. The upper-level controller adopts MPC controller for obtaining the additional yaw moment and the additional front wheel angle. Then, an optimal controller is used for the torque distribution in the lower layer. The stability coefficient during the vehicle's driving process is determined according to the vehicle's phase plane diagram, and the relative weights of the side slip angle and yaw rate of the center of mass in the model predictive control parameter matrix are adaptively adjusted through the stability coefficient. Finally, simulation results show that compared with the traditional control algorithm, the proposed control algorithm improves the tracking accuracy of the yaw rate by 36.5% and 21.7% under sinusoidal input and double lane change conditions, respectively, and reduces the maximum value of the centroid sideslip angle by 30.6% and 37.5%. This proves that the control strategy proposed in this paper can effectively improve the stability of the vehicle during driving.