基于卡尔曼滤波数据融合的永磁同步电机绕组温度估算研究
首发时间:2023-05-12
摘要:永磁同步电机绕组温度估算对于检测电机安全状况,防止电机过温损坏具有重要意义。本文通过模型参考自适应算法,通过波波夫超稳定理论推导的自适应律对电机定子电阻精确辨识,进而计算绕组温度。通过直流电压注入法,提取出绕组中的直流电压与电流分量计算电机定子电阻值。通过卡尔曼滤波算法对两种方式估算的绕组温度结果进行数据融合,以得到更加精确的温度估算结果。通过仿真验证了绕组温度估算方法的合理性,为后续绕组温度的精确估算奠定了基础。
关键词: 永磁同步电机 模型参考自适应 直流电压注入法 数据融合 绕组温度估算
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Research on Temperature Estimation of Permanent Magnet Synchronous Motor Winding Based on Kalman Filter Data Fusion
Abstract:The estimation of winding temperature of permanent magnet synchronous motor is of great significance for detecting motor safety and preventing motor from overheating damage. In this paper, the stator resistance of the motor is accurately identified by the model reference adaptive algorithm and the adaptive law derived from popov\'s ultra-stable theory, and then the winding temperature is calculated. Through the DC voltage injection method, the DC voltage and current components in the winding are extracted to calculate the stator resistance value of the motor. Kalman filter algorithm is used to fuse the winding temperature results estimated by the two methods, so as to obtain more accurate temperature estimation results. The rationality of the winding temperature estimation method is verified by simulation, which lays the foundation for the accurate estimation of the following winding temperature.
Keywords: Permanent Magnet Synchronous Motor Model Reference Adaptive DC Voltage Injection Data Fusion WindingTemperature Estimation
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