Volume 41 Issue 6
Dec.  2023
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Article Contents
YANG Wei, TAN Liang, DU Yafeng, SUN Xue, ZHANG Yujie. Path Tracking and Lateral Stability Control for Distributed Drive Vehicles with Low Adhesion[J]. Journal of Transport Information and Safety, 2023, 41(6): 61-70. doi: 10.3963/j.jssn.1674-4861.2023.06.007
Citation: YANG Wei, TAN Liang, DU Yafeng, SUN Xue, ZHANG Yujie. Path Tracking and Lateral Stability Control for Distributed Drive Vehicles with Low Adhesion[J]. Journal of Transport Information and Safety, 2023, 41(6): 61-70. doi: 10.3963/j.jssn.1674-4861.2023.06.007

Path Tracking and Lateral Stability Control for Distributed Drive Vehicles with Low Adhesion

doi: 10.3963/j.jssn.1674-4861.2023.06.007
  • Received Date: 2023-05-09
    Available Online: 2024-04-03
  • Due to the coupling relationship between tracking and lateral stability of vehicles under low adhesion conditions (such as snow and moisture), it is difficult to control both tracking accuracy and good stability simultaneously. Therefore, a joint control model of path tracking and lateral stability is proposed based on distributed independent drive electric vehicle platform. The transverse and longitudinal decoupling control is adopted for the path tracking problem. Besides, the model predictive control (MPC) method based on Frenet coordinate system is adopted for the horizontal tracking control problem, and angle compensation strategy is introduced to improve the accuracy of path tracking. For the longitudinal speed control problem, the model uses MPC to solve the expected acceleration, and determines the motor torque output according to the driving balance equation and the maximum utilization rate of road adhesion, so as to achieve the longitudinal speed control. For lateral stability control, a yaw torque control model based on stability augmentation system (STA) is proposed. After additional torque is obtained, it is effectively distributed to each wheel by quadratic programming method, thus enhancing the lateral stability of the vehicle. Moreover, the CarSim/Simulink co-simulation platform is used to simulate and verify the double-shift road conditions. The results show that under the condition of snow-covered pavement, the maximum lateral deflection angle of the improved model is reduced by 83.1% compared with the traditional MPC under the condition that the lateral error is close. Under wet road conditions, the maximum lateral error and the maximum lateral deflection angle of the improved model are reduced by 52.2% and 83.3%, respectively, compared with the traditional MPC model. Compared with the traditional synovial model, this model can effectively suppress the oscillation phenomenon when the tracking error and the side deflection angle of the center of mass are dominant. Through the joint control, the stability and safety of the vehicle on the low adhesion road surface can be enhanced.


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