[关键词]
[摘要]
为满足列车牵引传动系统在牵引电机状态监测、异常诊断与预测等领域对牵引电机定子电流准确估计的需求,提出了一种基于多工况最小二乘支持向量机(LS-SVM)模型的牵引电机电流实时估计方法。该方法结合牵引电机参数和转矩转速试验测量数据,利用牵引电机机理模型计算得到定子电流估计值;然后根据列车运行规律将其分为多个运行工况,基于历史运行数据的相关变量建立各工况下定子电流的LS-SVM估计模型并研究列车不同运行工况对模型精度的影响,基于多工况模型实现牵引电机全工况下电流的实时有效估计。通过实际运行数据验证了所提方法的有效性和可行性。
[Key word]
[Abstract]
In order to meet the requirements of accurate estimation of traction motor stator current for train traction drive system in the fields of traction motor condition monitoring, anomaly diagnosis and prediction, a real-time estimation method of traction motor current is proposed based on multi-condition least squares support vector machine (LS-SVM) model. Combined with traction motor parameters and the test measurement data of torque and speed, the stator current is estimated by using the traction motor mechanism model. Then, according to the train operation law, multiple operating conditions are considered. Based on the relevant variables of historical operation data, the LS-SVM estimation model of stator current under each working condition is established, and the influence of different operating conditions of traction motor on the accuracy of the model is studied, so as to realize the effective real-time estimation of traction motor current under all working conditions based on the multi-condition model. Finally, the effectiveness and feasibility of the proposed method are verified by the actual operation data.
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