<p>Tire forces are prone to saturation, leading to vehicles being in a nonlinear state with longitudinal and lateral coupling under extreme road conditions. Furthermore, coupling interaction between vehicle trajectory tracking precision and yaw stability compromises adaptability under complex working conditions. This paper proposes a control strategy of multi-objective coordinated trajectory tracking based on in-wheel motor-driven vehicles. First, a model of multi-objective coordinated control is established. A method of centroid slip angle–yaw rate phase plane stability region division based on a multi-constraint approach is proposed. Then, an upper layer adaptive weight model predictive controller (MPC) is built. Model-free adaptive control is introduced to mitigate MPC distortion. The lower layer achieves drive anti-slip by adjusting wheel torque through a sliding mode variable structure algorithm. Finally, results of dSPACE verification demonstrate that, compared with conventional MPC active steering controllers, the multi-objective coordinated controller achieves a 51% reduction in maximum lateral displacement deviation and a 53% reduction in maximum yaw angle deviation across four road conditions, optimizing both trajectory tracking accuracy and yaw stability in complex conditions.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Research on multi-objective coordinated trajectory tracking control for in-wheel motor-driven vehicles

  • Xiang Fu,
  • Yipeng Yin,
  • Yuxin Wang,
  • Shuiyan Yang,
  • Jiaqi Wan,
  • Xilong Zhang,
  • Zitai Xiao,
  • Qianfeng Ruan,
  • Tianqi Yang

摘要

Tire forces are prone to saturation, leading to vehicles being in a nonlinear state with longitudinal and lateral coupling under extreme road conditions. Furthermore, coupling interaction between vehicle trajectory tracking precision and yaw stability compromises adaptability under complex working conditions. This paper proposes a control strategy of multi-objective coordinated trajectory tracking based on in-wheel motor-driven vehicles. First, a model of multi-objective coordinated control is established. A method of centroid slip angle–yaw rate phase plane stability region division based on a multi-constraint approach is proposed. Then, an upper layer adaptive weight model predictive controller (MPC) is built. Model-free adaptive control is introduced to mitigate MPC distortion. The lower layer achieves drive anti-slip by adjusting wheel torque through a sliding mode variable structure algorithm. Finally, results of dSPACE verification demonstrate that, compared with conventional MPC active steering controllers, the multi-objective coordinated controller achieves a 51% reduction in maximum lateral displacement deviation and a 53% reduction in maximum yaw angle deviation across four road conditions, optimizing both trajectory tracking accuracy and yaw stability in complex conditions.