摘要
永磁同步电机通常采用正弦波进行驱动和控制,由于气隙磁场的畸变和电压型逆变器的死区效应等因素的存在,使永磁同步电机电流波形含有大量的谐波而发生畸变,特别是在电机低速运行时更为严重。为了进一步提高永磁同步电机的电流控制性能,抑制电流谐波,本文在传统矢量控制算法基础上,增加神经网络谐波电流环,通过自适应线性神经网络(ADALINE)算法实现对主要电流谐波的分解和提取,将所提取的电流谐波经过神经网络训练获得补偿电压值进行谐波注入,实现电流谐波的检测和抑制。通过仿真和实验结果证明,本文提出的控制策略可以有效提取并抑制电流谐波,降低电机转矩脉动。
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.
作者
王硕
康劲松
Wang Shuo;Kang Jinsong(College of Electronics and Information Tongji University,ShangHai 201804,China)
出处
《电工技术学报》
EI
CSCD
北大核心
2019年第4期654-663,共10页
Transactions of China Electrotechnical Society
基金
国家重点研发计划(2016YFB0100700)
中央高校基本科研业务费专项资金(1700219142)资助项目
关键词
永磁同步电机
电流谐波提取
电流谐波抑制算法
自适应线性神经网络算法
Permanent magnet synchronous motor
current harmonic extraction
current harmonic suppression algorithm
adaptive linear neural network(ADALINE)algorithm
