一种基于自适应线性神经网络算法的永磁同步电机电流谐波提取和抑制方法

Translated title of the contribution: Harmonic Extraction and Suppression Method of Permanent Magnet Synchronous Motor Based on Adaptive Linear Neural Network

Shuo Wang, Jinsong Kang

Research output: Journal PublicationArticlepeer-review

12 Citations (Scopus)

Abstract

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.

Translated title of the contributionHarmonic Extraction and Suppression Method of Permanent Magnet Synchronous Motor Based on Adaptive Linear Neural Network
Original languageChinese (Traditional)
Pages (from-to)654-663
Number of pages10
JournalDiangong Jishu Xuebao/Transactions of China Electrotechnical Society
Volume34
Issue number4
DOIs
Publication statusPublished - 25 Feb 2019
Externally publishedYes

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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