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针对汽车主动悬架(Active Suspension System,ASS)传感器卡死、增益变化、恒偏差常见故障,提出一种故障检测与隔离方法(Fault Detection and Isolation,FDI)。建立主动悬架4自由度半车模型和传感器故障时故障悬架模型,在利用故障检测滤波器获得主动悬架输出残差的基础上,设计故障检测指标,计算故障检测指标实时值并于阈值比较,实现传感器故障定量化检测。利用Kalman滤波器组获得主动悬架状态估计信息,选取合适二级决策变量构造故障隔离决策函数,根据决策函数对故障响应敏感情况隔离故障传感器。Matlab/Simulink仿真实验结果与分析表明:故障检测指标实时值大于等于阈值0.5时,可定量化检测出主动悬架传感器故障;同时,相对其他二级决策变量出现明显大幅跳跃性波动的二级决策变量,对应传感器被隔离为故障传感器。该方法能有效实现汽车主动悬架传感器故障检测与隔离,优化悬架设计,提高车辆控制可靠性和使用安全性。
Aiming at the common faults of sensor stuck, gain variation and constant deviation of Active Suspension System (ASS), a fault detection and isolation (FDI) method is proposed. The 4-degree-of-freedom semi-vehicle model of active suspension and the faulty suspension model of sensor failure are established. Based on the fault residuals obtained by fault detection filter, the fault detection index is designed and the real-time fault detection index is calculated. Comparison, to achieve quantitative sensor fault detection. Kalman filter bank is used to obtain the information of active suspension state estimation. The appropriate second-order decision variables are selected to construct the fault isolation decision-making function. According to the decision function, the fault sensor is isolated from the fault response sensitivity. The simulation results and analysis of Matlab / Simulink show that: when the real-time value of the fault detection index is greater than or equal to the threshold value of 0.5, the active suspension sensor can be quantitatively detected; at the same time, the second-order decision-making obviously jumps sharply compared with other second- The corresponding sensor is isolated as a fault sensor. The method can effectively detect and isolate vehicle active suspension sensor faults, optimize suspension design, and improve vehicle control reliability and service safety.