Coordinated control of path tracking and yaw stability for distributed drive electric vehicle based on AMPC and DYC

Author:

Wu Dongmei123,Guan Yuying123,Xia Xin4,Du Changqing123ORCID,Yan Fuwu123,Li Yang5,Hua Min6ORCID,Liu Wei7ORCID

Affiliation:

1. Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan, China

2. Foshan Xianhu Laboratory of the Advanced Energy Science and Technology Guangdong Laboratory, Foshan, China

3. Hubei Research Center for New Energy & Intelligent Connected Vehicle, Wuhan University of Technology, Wuhan, China

4. Department of Civil and Environmental Engineering, University of California, Los Angeles, CA, USA

5. Technical Center of Dongfeng Commercial Vehicle, Wuhan, China

6. School of Engineering, University of Birmingham, Birmingham, UK

7. School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA

Abstract

Maintaining both path-tracking accuracy and yaw stability of distributed drive electric vehicles (DDEVs) under various driving conditions presents a significant challenge in the field of vehicle control. To address this limitation, a coordinated control strategy that integrates adaptive model predictive control (AMPC) path-tracking control and direct yaw moment control (DYC) is proposed for DDEVs. The proposed strategy, inspired by a hierarchical framework, is coordinated by the upper layer of path-tracking control and the lower layer of direct yaw moment control. Based on the linear time-varying model predictive control (LTV MPC) algorithm, the effects of prediction horizon and weight coefficients on the path-tracking accuracy and yaw stability of the vehicle are compared and analyzed first. According to the aforementioned analysis, an AMPC path-tracking controller with variable prediction horizon and weight coefficients is designed considering the change of vehicle speed in the upper layer. The lower layer involves DYC based on the linear quadratic regulator (LQR) technique. Specifically, the intervention rule of DYC is determined by the threshold of the yaw rate error and the phase diagram of the sideslip angle. Extensive simulation experiments are conducted to evaluate the proposed coordinated control strategy under different driving conditions. The results show that, under variable speed and low adhesion conditions, the vehicle yaw stability and path-tracking accuracy have been improved by 21.58% and 14.43%, respectively, compared to AMPC. Similarly, under high speed and low adhesion conditions, the vehicle yaw stability and path-tracking accuracy have been improved by 44.30% and 14.25%, respectively, compared to the coordination of LTV MPC and DYC. The results indicate that the proposed adaptive path-tracking controller is effective across different speeds. Furthermore, the proposed coordinated control strategy successfully enhances the vehicle stability while maintaining good path-tracking accuracy even under extreme conditions.

Funder

Foshan Xianhu Laboratory of the Advanced Energy Science and Technology Guangdong Laboratory

Key R&D Project of Hubei Province, China

Publisher

SAGE Publications

Subject

Mechanical Engineering,Aerospace Engineering

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