无人车的线控转向系统故障诊断

Fault Diagnosis for SBW Systems of Unmanned Vehicles

针对无人车线控转向系统的安全性及可靠性问题,分析了它的结构组成、工作原理以及故障类型,并且利用线控转向系统离散动力学模型和车辆二自由度模型,借助横摆角速度、侧向加速度和转向执行电机电流信号,设计了基于卡尔曼滤波方法的对转向管柱转角传感器进行实时故障诊断的算法,针对电机的突变故障,通过对电机参数的实时估计来进行故障诊断。实车试验验证表明,所设计的故障诊断算法能够准确、及时诊断出无人车线控转向系统所出现的故障。

In order to ensure the safety and reliability of SBW systems for unmanned vehicles,the structures,working principles and malfunctions of SBW were analyzed.Using discrete dynamics model and 2-DOF vehicle model,with yaw rate signals,lateral acceleration signals and the current signals of steering motor,a real-time fault diagnose algorithm was designed based on Kalman filter method for steering tube column corner sensor,and through real-time estimation of motor parameters on abrupt faults to diagnose real-time faults of the motor.Real vehicle test results show the fault diagnose algorithm proposed herein may timely and accurately diagnose the failures of SBW systems.