Journal of Power Electronics

The Korean Institute of Power Electronics (전력전자학회)
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Novel modulation method for torque ripple suppression of brushless DC motors based on SIMO DC-DC converter

  • Sun, Shikai (School of Microelectronics, Xidian University) ;
  • Guo, Hui (School of Microelectronics, Xidian University) ;
  • Zhang, Yimeng (School of Microelectronics, Xidian University) ;
  • Jia, Yupeng (School of Microelectronics, Xidian University) ;
  • Lv, Hongliang (School of Microelectronics, Xidian University) ;
  • Song, Qingwen (School of Microelectronics, Xidian University) ;
  • Tang, Xiaoyan (School of Microelectronics, Xidian University) ;
  • Zhang, Yuming (School of Microelectronics, Xidian University)
  • Received : 2019.11.30
  • Accepted : 2020.02.28
  • Published : 2020.05.20
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Abstract

In this paper, a novel modulation method is proposed for the torque ripple suppression of a brushless DC motor (BLDCM) during both the commutation period and the speed regulation period. The main sources of torque ripple are the imbalance current during commutation and the PWM during speed regulation. A single-inductor multiple-output (SIMO) Buck DC-DC converter is adopted to generate input voltage for the inverter driver of a BLDCM. During the commutation period, the input voltage of an inverter can be adjusted to four times the back electromotive force (EMF), which suppresses the torque ripple caused by imbalance commutation current. Meanwhile, by changing the output voltage of a SIMO DC-DC, the speed of a BLDCM can be regulated without PWM on the inverter switches, which also suppresses the torque ripple. A control algorithm is applied on a Field Programmable Gate Array (FPGA), and the proposed BLDCM drive prototype is fabricated and tested. Measurement results show that with the proposed speed regulation strategy, the torque ripple is suppressed from 33.3% to 20.1%, and that with the proposed suppression strategy in commutation, the torque ripple is suppressed further to 5.3%.

Keywords

Acknowledgement

This work is supported by the National Science and Technology Major Project of China (Grant No. 2017-V-0014-0066).

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