High-Efficient Multivector Model Predictive Control with Common-Mode Voltage Suppression

Xiaomei Tang, Xin Yuan, Shuangxia Niu, K. T. Chau

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

Multivector model predictive control (MPC) has gained many attractions in motor drive applications due to its accurate and stable control performance. However, two key challenges have limited the control development. First of all, the switching frequency is not fixed and remains at a high level under the full range of operating conditions. More seriously, the zero vectors applied to adjust the output amplitude will generate high common-mode voltage (CMV), resulting in axis current, electromagnetic interference, and a host of other adverse effects. To address the two main concerns, this article proposes a control strategy that can efficiently respond to different operating conditions for permanent magnet synchronous motors (PMSMs). First, the reference voltage is constructed by the deadbeat principle, and the motor operating condition is distinguished according to the amplitude of the reference voltage. Second, to inherit satisfactory performance in steady-state while exhibiting fast current tracking response simultaneously, two voltage generation approaches that avoid the use of zero vectors are designed. Finally, comparative experimental results are presented, and the effectiveness of the proposed strategy is verified.

Original languageEnglish
Pages (from-to)2674-2685
Number of pages12
JournalIEEE Journal of Emerging and Selected Topics in Power Electronics
Volume12
Issue number3
DOIs
Publication statusPublished - 1 Jun 2024

Keywords

  • Common-mode voltage (CMV)
  • model predictive control (MPC)
  • multivector
  • switching frequency

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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