1358 / 2020-09-29 17:52:02
EKF for Three-Vector Model Predictive Current Control of PMSM
Extended Kalman filter (EKF), model predic- tive current control (MPCC), permanent magnet synchronous machines (PMSM), sensorless algorithm.
终稿
Yongzihao Dai / Huazhong University of Science and Technology
Caiyong Ye / Huazhong University of Science and Technology
Sifeng Zhao / Huazhong University of Science and Technology
Dezuan Yu / Huazhong University of Science and Technology
Renjun Dian / Wuhan University of Science and Technology
Permanent magnet synchronous machines (PMSM) are widely used due to their small size and good running performance. However, PMSM have the disadvantages of

multivariable and strong coupling, which make it difficult to design the regulator parameters. To solve this problem, this paper studies the use of three-vector model predictive current control (TV-MPCC) in PMSM. The traditional TV-MPCC uses speed sensors, which increases the cost and installation difficulty. The extended Kalman filter (EKF) algorithm which is applied for detecting rotor position and speed is proposed in this article. By comparing the traditional TV-MPCC algorithm with sensorless algorithm, the results indicate that there is no significant difference between sensorless algorithm and the traditional MPCC algorithm, sensorless algorithm has an analogous dynamic and steady-state performance.
重要日期
  • 会议日期

    11月02日

    2020

    11月04日

    2020

  • 10月27日 2020

    初稿截稿日期

  • 11月03日 2020

    报告提交截止日期

  • 11月04日 2020

    注册截止日期

  • 11月17日 2020

    终稿截稿日期

主办单位
IEEE IAS Student Chapter of Huazhong University of Science and Technology (HUST)
承办单位
Huazhong University of Science and Technology
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