电动汽车永磁同步电动机(PMSM)驱动系统受其功率密度、控制方式以及运行环境的影响,易出现永磁体局部退磁或均匀退磁故障,为了实现电动汽车PMSM驱动系统的安全可靠运行,PMSM退磁故障诊断与故障模式识别已成为亟需解决的关键技术问题之一.首先提出采用代数辨识法实现永磁体磁链的在线辨识,将辨识结果作为退磁故障定性诊断的依据;在此基础上,采用基于希尔伯特黄变换的定子电流瞬时频率分析方法,实现车用工况下局部退磁故障非平稳特征信号的有效提取.最后,通过系统仿真研究和实验研究证实建议的永磁体退磁故障诊断及故障模式识别的一体化解决方案能够在测量噪声和车用工况约束下,通过永磁体磁链的在线准确辨识及局部退磁非平稳微弱故障特征信号的有效提取,实现永磁体退磁故障的在线准确诊断及故障模式的有效识别.%The local demagnetization fault and uniform demagnetization fault of permanent magnets easily appears in permanent magnet synchronous motor (PMSM) drive system of electric vehicle (EV) due to the influences of PMSM power density, control method and operation environment.In order to realize safe and reliable operation of PMSM drive system, the demagnetization fault diagnosis and fault mode recognition of PMSM has been one of the key technique problems which urgently need to be solved.Therefore, an algebraic identification method is first proposed in this paper to implement online identification of permanent magnet flux, then the identification results is used as the criterion of qualitative diagnosis of demagnetization fault, and then, the instantaneous frequency analysis method of stator current based on Hilbert-Hang transform (HHT) is adopted to realize the effective extraction of non-stationary characteristic signals of local demagnetization fault under the vehicle operating conditions.At last, the simulation and experimental research results are showed to confirm that the proposed integrated solutions of demagnetization fault diagnosis and fault mode recognition of permanent magnets are able to realize the signal of online accurate diagnosis of demagnetization fault and reliable recognition of fault mode by realizing the online accurate identification of permanent magnet flux and the effective extraction of non-stationary weak characteristic signals of local demagnetization fault under the constraints of measurement noise and vehicle operating conditions.Finally, recognition of demagnetization fault online diagnosis and fault mode can be achieved effectively.
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