Abstract:  A path tracking control strategy with integrated vehicle stability was proposed to improve the path tracking precision and vehicle stability of distributed drive electric vehicles under dangerous driving conditions such as high speed and low adhesion conditions. The hierarchical structure path tracking control strategy with vehicle stability, including the path tracking control layer, the stability controller decision layer and the drive wheel torque distribution layer. To solve the problem of the lower accuracy of LQR path tracking controller under high-speed and large curvature conditions, a closed loop PID correction driver model was used to compensate the front wheel angle of the vehicles. In addition, the stability controller was designed to track the ideal reference model of the vehicles. The controller developed the model predictive control algorithm to generate additional yaw moment. Meanwhile, the controller realized the optimal distribution of the wheel drive torques with the objective of minimizing tire load rate. Based on the independently designed distributed drive electric test vehicle, the double lane change tests were carried out on high-speed high adhesion road surfaces and high-speed low adhesion road surfaces respectively. The results show that, when driving on dry concrete pavement at 90 km/h speed, the lateral root mean square errors of the path tracking precision with integrated dynamics stability reduce by 29.7%, compared to the LQR path tracking controller using only closed-loop PID correction for path tracking. When driving on wet asphalt pavement at 70 km/h speed, the lateral root mean square errors reduce by 10.3%. Therefore, the proposed path tracking control strategy with integrated vehicle stability of distributed drive electric vehicles may improve path tracking accuracy, ensuring yaw stability under extreme conditions effectively. 

Key words: automotive engineering, distributed drive electric vehicle, path tracking, stability control

摘要： 提出了一种融合车辆稳定性的路径跟踪控制策略，以提高分布式驱动电动汽车在高速、低附着等危险行驶工况下的路径跟踪精度和车辆稳定性，该控制策略包括路径跟踪控制层、稳定性控制器决策层、驱动轮转矩分配层。针对LQR路径跟踪控制器在高速大曲率工况下跟踪精度不足的问题，采用闭环PID矫正驾驶员模型补偿车辆前轮转角，并设计稳定性控制器用以跟踪车辆理想参考模型，基于模型预测控制算法决策出附加横摆力矩，同时以轮胎负荷率最小为目标优化车轮驱动转矩分配。利用自主开发的分布式驱动电动试验车分别在高速高附着和高速低附着双移线工况进行试验。结果表明：相对于只运用闭环PID矫正的LQR路径跟踪控制器进行路径跟踪，车辆在干燥的混凝土路面以90 km/h速度行驶时，融合车辆稳定性的路径跟踪精度的横向均方根误差降低了29.7%；车辆在潮湿沥青路面以70 km/h速度行驶时，均方根误差降低了10.3%。所提控制策略能够提高车辆的路径跟踪精度，满足车辆在危险行驶工况下的横摆稳定性。

关键词: 汽车工程, 分布式驱动电动汽车, 路径跟踪, 稳定性控制