Slip ratio adaptive control for distributed drive electric vehicle based on wheel speed

Aiming at the problems of poor control effect and poor robustness for distributed drive electric vehicles driving on complex and changeable roads, this paper proposes a slip ratio adaptive control method based on wheel speed. Firstly, an optimal slip ratio estimator considering axle load transfer was developed by analyzing the single-wheel dynamics of the vehicle and based on the Burckhardt tire model. Secondly, a cubic polynomial function is used to fit and optimize the optimal slip ratio-peak adhesion coefficient curve, which effectively improves the accuracy of obtaining the optimal slip ratio. Then, a conditional integral sliding mode controller based on wheel speed is designed in order to enhance the transient characteristics of the sliding mode control, to avoid integral saturation, and to improve the control effect of the sliding ratio controller in the low speed start-up phase. Finally, three typical working conditions, namely single road, flat road, and slip road, were established for simulation and experimental validation. The results show that the method in this paper is able to estimate the optimal slip ratio of the road in real time, realize the wheel slip ratio adaptive control, and improve the dynamic performance and lateral stability of distributed drive electric vehicle.

Automated summary

This paper presents a slip ratio adaptive control method based on wheel speed to address the issues of poor control effect and robustness for distributed drive electric vehicles on complex and changeable roads. An optimal slip ratio estimator is developed considering axle load transfer, using the Burckhardt tire model. A cubic polynomial function is used to fit and optimize the optimal slip ratio-peak adhesion coefficient curve. Additionally, a conditional integral sliding mode controller based on wheel speed is designed to improve the control effect of the sliding ratio controller in the low speed start-up phase. Simulation and experimental results demonstrate that the proposed method can estimate the optimal slip ratio in real time, achieve wheel slip ratio adaptive control, and enhance the dynamic performance and lateral stability of distributed drive electric vehicles.