干式DCT离合器无刷直流作动电机双卡尔曼滤波故障诊断

Fault Diagnosis Based on Dual Kalman Filter of Clutch Brushless DC Actuator Motor for Dry Dual Clutch Transmission

实时有效地对离合器作动电机进行在线故障诊断并进行容错控制,是保证干式双离合器自动变速器(Dry dual clutch transmission,DDCT)安全可靠工作和实现干式DCT快速动力换档的前提条件。论文针对6速干式DCT离合器作动电机,采用双卡尔曼滤波算法对电机相关状态及参数进行了联合仿真估计,并通过台架试验对估计算法进行了试验验证。结果表明:所采用的双卡尔曼状态及参数联合估计算法能对离合器作动电机的状态和参数进行有效估计,估计误差不大于2%,且能进一步实时在线诊断出传感器无法检测的电机潜在故障,为后续干式DCT容错控制研究奠定了基础。

Fault diagnosis and its tolerant control online of the clutch actuator motor quickly and effectively is the precondition to ensure safe and reliable operation of dry dual clutch transmission(DDCT) and to accomplish its power shift.Dual Kalman filter is used to jointly estimate the states and parameters of clutch brushless DC actuator motor of six-speed DDCT.And the feasibility of estimation algorithm is verified by bench test.Results show that the proposed joint estimation algorithm can estimate the states and parameters of the clutch actuator motor effectively with the relative error no more than 2%,and the proposed algorithm can furtherly diagnose the potential fault of the motor in real time which can’t be found through sensor signals.The study lays a foundation for the subsequent fault tolerant control of the DDCT.