Journal of Power Electronics

The Korean Institute of Power Electronics (전력전자학회)
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Multi-amplitude voltage vector MPTC for dual three-phase PMSMs with low torque ripple

  • Shuang Wang (School of Mechatronic Engineering and Automation, Shanghai University) ;
  • Qianru Zhang (School of Mechatronic Engineering and Automation, Shanghai University) ;
  • Deliang Wu (School of Mechatronic Engineering and Automation, Shanghai University) ;
  • Jianfei Zhao (School of Mechatronic Engineering and Automation, Shanghai University)
  • Received : 2023.03.22
  • Accepted : 2023.08.01
  • Published : 2024.01.20
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Abstract

In model predictive torque control (MPTC), voltage vectors with a fixed amplitude have poor performance in torque tracking. In this paper, a multi-amplitude MPTC (MA-MPTC) method for dual three-phase permanent magnet synchronous motor (PMSM) is proposed, which can effectively reduce torque ripple by combining virtual voltage vectors (VVVs) and actual voltage vectors (AVVs). First, the deadbeat (DB) technique is used to simplify voltage vector selection and to avoid the enumeration of all the possible voltage vectors. After calculating the reference voltage vector (RVV) using this method, four vectors with different amplitudes can be selected as candidate voltage vectors (CVVs) according to the angle of the RVV. Then a new cost function is used to calculate the four candidate vectors, and the vector that minimizes the cost function is the optimal vector. Therefore, the MA-MPTC strategy has the advantages of both the MPTC method and the DB method, which can effectively reduce the torque ripple with a low computational cost. In addition, VVVs are used to reduce the influence of harmonic currents while suppressing torque ripple. Finally, the stability and dynamic response are investigated on the test bench. When compared with a contrast method, the torque ripple is reduced by nearly half and the advantage of fast response is maintained. The experimental results confirm the effectiveness of the proposed method.

Keywords

Acknowledgement

Natural Science Foundation of Shanghai, 19ZR1418600, Shuang Wang.

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