154 / 2019-06-17 15:38:26
An Optimized Commutation Method for Sensorless Brushless DC Motor Based on Back Electromotive Force Using Backpropogation Neural Network
Sensorless brushless DC motor,commutation,Back-EMF,BP Neural Network
全文待审
Yuxiang Liu / South China University of Technology
Zhaohui Wu / South China University of Technology
Bin Li / South China University of Technology
Fang Yuan / Institute of Semiconductors, Chinese Academy of Sciences
Zhaolin Yao / Institute of Semiconductors, Chinese Academy of Sciences
Xu Zhang / Institute of Semiconductors, Chinese Academy of Sciences
In this paper, an optimized commutation method based on BP neural network is proposed to solve the problem of slow response, large overshoot and power dissipation caused by algorithm deviation in conventional commutation strategy based on back electromotive force method. Performance of different commutation methods is compared by simulation. Experiment results show that the proposed method can realize a good commutation performance, with a 0.8% power deviation and a 15.906 mean square error compared with ideal condition, which improves 275 times than conventical strategy. The proposed method has better compensation ability for fixed errors such as signal transmission delay, signal filtering delay and motor armature effect at the same time.
重要日期
  • 会议日期

    10月09日

    2019

    10月10日

    2019

  • 07月20日 2019

    初稿截稿日期

  • 10月10日 2019

    注册截止日期

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Xi’an Jiaotong University
历届会议
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