低附着下分布式驱动车辆的路径跟踪与横向稳定性控制方法

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

由于车辆在低附着工况(如积雪、潮湿)下跟踪性与横向稳定性的耦合关系,这使得二者之间的控制难以同时满足跟踪精度及良好的稳定性需求,因此,研究了基于分布式独立驱动电动汽车平台的路径跟踪与横向稳定性联合控制模型。对于路径跟踪问题,采用了横纵向解耦控制;对于横向跟踪控制问题,模型采用基于Frenet坐标系的模型预测控制(model predictive control,MPC)路径跟踪控制方法,并引入了转角补偿策略以提升路径跟踪的准确性;对于纵向车速控制问题,模型利用MPC求解期望加速度,并根据行驶平衡方程和保证路面附着最大利用率的条件下确定电机扭矩输出,实现对纵向车速的控制。对于横向稳定性控制问题,提出了基于稳定性增强系统(stability augmentation system,STA)的横摆力矩控制模型,在获得附加力矩后,以二次规划方法将其合理分配到各个车轮上,从而增强了车辆的横向稳定性。最后,通过CarSim/Simulink联合仿真平台,在双移线道路工况下进行了仿真验证。结果表明:在积雪路面,改进模型相比传统MPC在保证横向误差接近的条件下,最大的质心侧偏角降低了83.1%;在潮湿路面,改进模型相比传统MPC模型最大横向误差降低了52.2%,最大质心侧偏角降低了83.3%;相比于传统滑膜,本文模型在跟踪误差与质心侧偏角占优势的情况下,有效的抑制了震荡现象。通过联合控制,可以加强车辆在低附着路面的稳定性与安全性。

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 simultane-ously.Therefore,a joint control model of path tracking and lateral stability is proposed based on distributed indepen-dent drive electric vehicle platform.The transverse and longitudinal decoupling control is adopted for the path track-ing 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 effective-ly 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 condi-tions.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 er-ror 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.Com-pared 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 stabili-ty and safety of the vehicle on the low adhesion road surface can be enhanced.