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Automotive Engineering ›› 2023, Vol. 45 ›› Issue (6): 1010-1021.doi: 10.19562/j.chinasae.qcgc.2023.06.011

Special Issue: 底盘&动力学&整车性能专题2023年

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Vehicle Trajectory Tracking Control Based on Road Adhesion Coefficient Estimation

Yunfei Zha1(),Lü Xiaolong1,Huiqin Chen2,Yingchun Yi1,Yanyan Wang1   

  1. 1.Fujian University of Technology,Fujian Key Laboratory of Automotive Electronics and Electric Drive,Fuzhou 350118
    2.College of Mechanical Engineering,Hangzhou Dianzi University,Hangzhou 310018
  • Received:2023-03-04 Revised:2023-04-03 Online:2023-06-25 Published:2023-06-16
  • Contact: Yunfei Zha E-mail:zhayf@fjut.edu.cn

Abstract:

For the trajectory tracking control problem of vehicles under high speed steering and different road adhesion coefficients, a variable sideslip angle constrained MPC control strategy is proposed based on model predictive control theory considering road adhesion coefficients. According to the magic formula tire model, the tire cornering property as well as the influence of different adhesion coefficients on the tire slip angle-lateral force linear region is analysed. Then the function relationship between tire slip angle constraint and different road adhesion coefficients is established. The genetic algorithm (GA) is used to optimize the BP neural network model to design the road adhesion coefficient estimator, and the estimation results are transmitted to the MPC controller as variables related to the tire slip constraint. Finally, the system control quantity constraint, the control increment constraint, and the variable sideslip angle constraint considering the road adhesion coefficient are established in the MPC controller. The trajectory tracking problem under different road adhesion conditions is transformed into the optimal value solution problem under various constraints to realize trajectory tracking and vehicle stability control. The simulation and experimental results show that the MPC control method considering the change of road adhesion coefficient has higher trajectory tracking accuracy and better vehicle stability than the traditional MPC control method under various working conditions, with high estimation accuracy of the GA-BP neural network road coefficient estimation method.

Key words: trajectory tracking, road adhesion coefficient, model predictive control, slip angle constraint