Trajectory tracking algorithm in a hierarchical strategy for electric vehicle driven by four independent in-wheel motors

Abstract

ABSTRACT Trajectory tracking is a key technology for precisely controlling autonomous vehicles. The characteristics of an independent drive electric vehicle (IDEV) are used as the basis for designing a trajectory tracking algorithm using a hierarchical strategy. While the upper controller tracks the desired trajectory based on model predictive control (MPC), the middle controller adjusts the speed using the fuzzy theory to optimize the parameters of the proportional integral (PI) controller and generates an additional yaw control moment based on sliding mode control (SMC). Finally, the lower controller distributes the torque to each wheel according to stability and adhesion conditions. A co-simulation platform is established to verify the performance of the proposed algorithm under typical scenarios. Results indicate that the proposed algorithm can provide good dynamic driving ability at high speeds and on low-adhesion roads. The accuracy of trajectory tracking using the proposed algorithm is better than that of the traditional preview–follower driver model and the performance of the proposed torque distribution algorithm is superior to that of the traditional even torque distribution algorithm.