Harmonic Extraction and Suppression Method of Permanent Magnet Synchronous Motor Based on Adaptive Linear Neural Network

被引：0
|
作者：
Wang S. [1 ]
Kang J. [1 ]
机构：
[1] College of Electronics and Information, Tongji University, Shanghai
来源：
Diangong Jishu Xuebao/Transactions of China Electrotechnical Society | 2019年 / 34卷 / 04期
关键词：
Adaptive linear neural network (ADALINE) algorithm; Current harmonic extraction; Current harmonic suppression algorithm; Permanent magnet synchronous motor;
D O I：
10.19595/j.cnki.1000-6753.tces.181080
中图分类号：
学科分类号：
摘要：
Permanent magnet synchronous motors (PMSM) are usually driven by voltage-source inverters (VSI). The distortion of air-gap magnetic field and the dead time of voltage-source inverters cause the current waveform distortion with a large number of harmonics, especially when the motor runs at low speed. In order to improve the current performance for PMSM and suppress the current harmonics, the neural network harmonic current loop is added in this paper. The ADALINE method is utilized for the decomposition and extraction of the main harmonic currents, and the extracted current harmonics are trained to obtain the compensated voltage. By means of voltage harmonic injection, both detection and suppression of the specified current harmonic waves are achieved. The simulation and experimental results show that the proposed control strategy can effectively suppress the current harmonics, compensate current harmonic distortion and reduce the motor torque ripple. © 2019, Electrical Technology Press Co. Ltd. All right reserved.
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页码：654 / 663
页数：9
相关论文
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