Research on stability control of intelligent electric vehicles by combining multi-parameter control and feedforward feedback control

• Published in: International journal of dynamics and control Vol. 13; no. 8
• Main Author: Gang, Liu
• Format: Journal Article
• Language: English
• Published: Heidelberg Springer Nature B.V 01.08.2025
• Subjects: Control methods; Control stability; Control systems; Control theory; Cornering; Deviation; Dynamic characteristics; Electric vehicles; Feedback control; Feedforward control; Lane changing; Parameters; Predictive control; Roads & highways; Sideslip; Stability; Yaw
• DOI: 10.1007/s40435-025-01792-6
• ISSN: 2195-268X

A feedforward-feedback control method for the stability of intelligent electric vehicles that integrates preview characteristics is proposed. A vehicle preview model is established, and the road curvature is introduced as an influencing factor of vehicle dynamic characteristics through the forward-looking behavior of the vehicle during environmental perception. A stability feedforward control method for tire cornering stiffness compensation is established. At the same time, a model predictive control feedback control law based on multiple control parameters is designed to achieve multi-parameter control of lateral deviation, yaw angle deviation, sideslip angle, and yaw rate. The influence of the prediction time domain parameters on the control strategy is studied, and the prediction time is adaptively adjusted according to the preview information of the vehicle to eliminate the influence of uncertain factors such as feedforward control errors and road disturbances. Verified through the hardware-in-the-loop test platform: Under double lane change and slalom conditions, the sideslip angle, yaw rate, and lateral acceleration of the vehicle under the control strategy proposed in this paper are small, and the tracking accuracy is higher.