Path tracking fault-tolerant control of intelligent distributed drive electric vehicle based on sliding mode observer

Linfeng Zhao, Ruiteng Wang, Ting Fang, Shengshan Liu, Kaiqi Hu, Jinfang Hu, Dingzhi Zhang
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Abstract

In this paper, an intelligent distributed drive electric vehicle is used as the research object. The research aims to solve the problem of path-tracking control of intelligent vehicles when the single-side in-wheel motor of the front axle fails. A fault-tolerant control method based on sliding mode observer is proposed. Firstly, an overall vehicle dynamics model considering the failure factor is established, and the failure of the in-wheel motor is monitored by the sliding mode observer. Torque coordination compensation control is activated according to the observed failure. The control system mainly consists of two parts: the torque-coordinated lateral stability controller and the prediction fault tolerant deviation compensation controller. The torque-coordinated lateral stability controller controls the torque of the other wheels to balance the front wheel torque, and the prediction tolerant deviation compensation controller uses Model Predictive Control (MPC) to control the front wheel angle and rear wheel torque of the vehicle to reduce the lateral deviation. Finally, under double-lane change conditions, dynamics simulations and hardware-in-loop experiments are performed to validate the effectiveness of the proposed control method.
基于滑模观测器的智能分布式驱动电动汽车路径跟踪容错控制
本文以智能分布式驱动电动汽车为研究对象。研究旨在解决前轴单侧轮内电机故障时智能车辆的路径跟踪控制问题。研究提出了一种基于滑模观测器的容错控制方法。首先,建立考虑故障因素的整车动力学模型,并通过滑模观测器监测轮内电机的故障情况。根据观察到的故障激活扭矩协调补偿控制。控制系统主要由两部分组成:扭矩协调横向稳定性控制器和预测容错偏差补偿控制器。扭矩协调横向稳定性控制器控制其他车轮的扭矩,以平衡前轮扭矩;预测容错偏差补偿控制器使用模型预测控制(MPC)来控制车辆的前轮角度和后轮扭矩,以减少横向偏差。最后,在双车道变化条件下,进行了动力学仿真和硬件在环实验,以验证所提控制方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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