Path Tracking and Handling Stability Coordinated Control of 4WS and DYC for Distributed In-Wheel Motor Drive Electric Vehicle Under Extreme Conditions
Haichuan Zhang, Shu Wang, Xuan Zhao, Zichen Zheng
Abstract
How to improve the path tracking ability and handling stability under critical maneuvers is an important research issue for distributed in-wheel motor drive electric vehicle (IWMDEV). This article proposes a novel coordinated control architecture of active four-wheel steering (4WS) system and direct yaw moment control (DYC) system for IWMDEV. Firstly, a novel shared steering control framework for 4WS system is built, which includes two players, namely, the active front steering (AFS)and active rear steering (ARS). The non-cooperative game theory-based control strategy between AFS and ARS is designed to provide more lateral stability for the path following control. Secondly, a linear time-varying model predictive control (LTV-MPC) is used to determine the direct yaw moment of the vehicle. Then, on the basis of comprehensive consideration of system characteristics and control objective performance requirement, the coordination controller based on K-means Density Peak Clustering and Particle Swarm Optimization (KDPC-PSO) algorithm is put forward to calculate optimal weight coefficient between the ARS system and DYC system. Finally, the Carsim/Simulink co-simulation and Hardware-in-the Loop (HIL) experiment results show that the proposed control system can effectively improve the path tracking ability and handling stability of IWMDEV under extreme conditions.