基于Pearson相关性分析的双V型永磁同步电机失磁故障动态识别方法

doi:10.19595/j.cnki.1000-6753.tces.231722

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摘要

针对电驱动系统用高功率密度永磁驱动电机存在的不可逆退磁问题,以一款8极48槽的双V型永磁同步电机为例对退磁故障的动态识别方法进行了研究。在考虑电机闭合磁路对永磁体退磁故障影响的基础上,通过分析高退磁率电机模型退磁前后的空载和负载参数变化,采用Pearson相关性分析的方法提取了表征退磁故障的特征参量,给出了一种退磁故障的动态识别方法,并分析了转速和电流对特征参量的影响,完成了对退磁故障动态识别方法的修正。通过仿真和实验测试的方法对退磁故障动态识别方法的准确性进行了验证,结果表明,仿真结果的误差为0.68%,实验测试的预测结果最大误差为1.765%,误差均在可接受范围内。

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	黄康杰
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关键词 ：驱动电机, 双V型永磁同步电机, 退磁故障, Pearson相关性

Abstract：

With the gradual development of permanent magnet drive motors in the direction of high speed, high torque, and high power density, the risk of irreversible demagnetization of permanent magnets has increased dramatically. In addition, rotor poles combined with multiple permanent magnets are widely used, and spatial specificity exists in pole demagnetization of space-distributed permanent magnets due to the different arrangement positions. Therefore, real-time detection of special demagnetization faults for permanent magnet drive motors is crucial. Numerous scholars have proposed online diagnostic methods. However, these methods either have the cost increase caused by the stator coil modification, or the assumed demagnetization model of the permanent magnet is far from the actual. Hence, the online diagnostic methods for the demagnetization fault have yet to be verified by experiments. In this paper, taking a permanent magnet motor with an 8-pole 48-slot double V-type as an example, the influence of the closed magnetic circuit of the motor on the demagnetization fault of permanent magnets is considered.
Firstly, Assuming that the motor has good heat dissipation and ignores the axial temperature difference effect on the demagnetization of permanent magnets, the permanent magnet demagnetization caused by the armature reverse magnetic field is analyzed. Meanwhile, this paper establishes a high demagnetization rate motor model under different armature currents, considering the difference between the closed magnetic circuit inside the motor and the magnetic circuit outside the motor. Then, the motor's no-load and load parameters are analyzed. The Person correlation coefficient method extracts the characteristic parameters of permanent magnet motor demagnetization faults. The dynamic identification method of the demagnetization fault is established, and the armature current is introduced to correct this dynamic identification method. Finally, the simulation error of the dynamic identification method is calculated by establishing a new motor model with a high demagnetization rate, and the experimental error is calculated through two working condition experiments.
The following conclusions can be drawn. (1) Considering the influence of the closed magnetic circuit in the motor on the permanent magnet demagnetization makes the demagnetization model closer to the actual demagnetization condition of the permanent magnet. (2) The no-load parameters of the motor can be used as the characteristic parameters of the no-load demagnetization fault. The loss rate of torque and cross-axis inductance under load conditions is not affected by the current angle, which can be used as the characteristic parameters of the load demagnetization fault. (3) The simulation error of the dynamic identification method is 0.68%, and the experimental error is 1.765%.

Key words： Drive motor double V-shaped PMSM demagnetization fault Pearson correlation

收稿日期: 2023-10-16

PACS:

TM351

基金资助:

国家自然科学基金资助项目（52177064）

通讯作者: 熊斌男,1979年生,研究员,研究方向为电机与电器、冷却技术、电气设备健康状况评估等。E-mail: xiongbin@mail.iee.ac.cn

作者简介: 黄康杰男,1997年生,硕士研究生,研究方向为电机与电器。E-mail: 13593573965@163.com

引用本文:

黄康杰, 熊斌, 崔刚, 李振国, 鲍炳炎. 基于Pearson相关性分析的双V型永磁同步电机失磁故障动态识别方法[J]. 电工技术学报, 2024, 39(22): 7111-7125. Huang Kangjie, Xiong Bin, Cui Gang, Li Zhenguo, Bao Bingyan. Dynamic Identification Method of Demagnetization Fault of Double V-Shaped PMSM Based on Pearson Correlation Analysis. Transactions of China Electrotechnical Society, 2024, 39(22): 7111-7125.

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