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Coordinated control based path following of distributed drive autonomous electric vehicles with yaw-moment control
Control Engineering Practice ( IF 5.4 ) Pub Date : 2021-01-01 , DOI: 10.1016/j.conengprac.2020.104659
Ju Xie , Xing Xu , Feng Wang , Zhao Tang , Long Chen

Abstract This research seeks to study the path following issue for distributed drive autonomous electric vehicles (DDAEV). In order to improve the tracking accuracy and vehicle stability, coordinated control of tracking deviation compensation and vehicle stability by yaw-moment is proposed. Based on the three degree-of-freedom vehicle model, model predictive control is used to calculate the steering angle of front wheels to control the vehicle along the reference path by autonomous steering. In this process, two sliding surfaces whose control targets are tracking deviation and yaw rate deviation are first set, then two sliding surfaces are combined into one coordinated sliding surface with weight coefficients considering the vehicle stability, and finally the yaw-moment is figured out and distributed with the constant torque requirement of the vehicle. Carsim co-simulation with Simulink and Hardware-in-the-Loop experiment are conducted, which shows that compared to autonomous steering control, coordinated control achieves better path following accuracy and vehicle stability for DDAEV under different driving conditions.

中文翻译:

基于偏航力矩控制的分布式驱动自主电动汽车路径跟随协调控制

摘要 本研究旨在研究分布式驱动自主电动汽车(DDAEV)的路径跟随问题。为了提高跟踪精度和车辆稳定性,提出了基于横摆力矩的跟踪偏差补偿和车辆稳定性协调控制。基于三自由度车辆模型,通过模型预测控制计算前轮转向角,通过自主转向控制车辆沿参考路径行驶。在这个过程中,首先设定控制目标为跟踪偏差和横摆角速度偏差的两个滑动面,然后考虑车辆稳定性,将两个滑动面组合成一个具有权重系数的协调滑动面,最后计算出横摆力矩并根据车辆的恒定扭矩要求进行分配。Carsim 与 Simulink 的联合仿真和硬件在环实验表明,与自主转向控制相比,协调控制在不同驾驶条件下为 DDAEV 实现了更好的路径跟随精度和车辆稳定性。
更新日期:2021-01-01
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