基于变参数模型的智能车辆转向执行器故障诊断  

Steering Actuator Fault Diagnosis of Intelligent Vehicle Based on Variable Parameter Model

作　　者：王宏伟 李磊 刘晨宇 汪洵 WANG Hong-wei;LI Lei;LIU Chen-yu;WANG Xun(School of Control Engineering,Northeastern University at Qinhuangdao,Qinhuangdao 066004,China)

机构地区：[1]东北大学秦皇岛分校控制工程学院,河北秦皇岛066004

出　　处：《东北大学学报（自然科学版）》2024年第7期913-920,共8页Journal of Northeastern University(Natural Science)

基　　金：国家自然科学基金资助项目(61903072);中央高校基本科研业务费专项资金资助项目(N2223029).

摘　　要：为解决传统车辆研究将纵向车速设为定值的问题,设计一种基于观测器的鲁棒增益调度故障诊断算法.首先,以纵向车速为调度变量,同时考虑执行器故障、模型不确定性以及外部干扰,在传统车辆模型基础上建立四轮转向线性变参数(linear parameter varying,LPV)数学模型.然后,对执行器故障进行状态重构,设计具有可变权重因子的鲁棒增益调度观测器,实现对车辆状态信息及执行器故障信号的双重估计.最后,选取双移线和蛇形工况,通过MATLAB/Simulink和Carsim联合仿真,结果表明,所设计的执行器故障诊断算法能有效处理车辆纵向车速的时变特性,在复杂工况下能及时快速地跟踪车辆的状态及故障信息,突破了原有传统车辆故障诊断算法的局限性.In order to solve the problem that the longitudinal vehicle speed is set as a constant value in traditional vehicle research,a robust gain scheduling fault diagnosis algorithm is designed based on an observer.Firstly,by taking the longitudinal vehicle speed as the scheduling variable,while considering actuator fault,model uncertainty and external interference,a mathematical model using linear parameter varying(LPV)is established on the basis of the traditional vehicle model.Then,the state of the actuator fault is reconstructed,and a robust gain scheduling observer with variable weight factor is designed to achieve dual estimation of vehicle state information and actuator fault signals.Finally,joint simulations using MATLAB/Simulink and Carsim are carried out under double lane change and snake maneuvers.The results show that the designed actuator fault diagnosis algorithm can effectively deal with the time-varying characteristics of vehicle longitudinal speed,and track the vehicle state and fault information timely and accurately under complex working conditions,which breaks through the limitations of traditional vehicle fault diagnosis algorithms.

关 键 词：智能车辆 线性变参数 执行器故障 故障诊断 增益调度 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]