A Simplified Multivector-Based Model Predictive Current Control for PMSM With Enhanced Performance

Zhiwei Xue, Shuangxia Niu, Xianglin Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

3 Citations (Scopus)

Abstract

To address the challenges of poor steady-state performance and large amount calculation of conventional model predictive current control (MPCC), a simplified multivector-based MPCC with enhanced performance is proposed in this article. First, an effective voltage vectors (VVs) selection method based on current error is proposed, which can directly determine the optimal VVs without cost function enumeration. Compared with the standard method, the number of vectors that need to be evaluated is reduced from 7 to 1. Meanwhile, the duty cycle of each VV is calculated based on the current error to realize error-free control. In addition, to alleviate the deleterious effect of dead time on the control performance, an improved MPCC scheme with optimal utilization of dead time is proposed. The key is that the dead time existing in MPCC is regarded as a dead-time VV (DVV), which can be rationally utilized to improve the control performance. Both theoretical analysis and experimental results are given to verify the effectiveness of the proposed MPCC schemes.

Original languageEnglish
Article number10038564
Pages (from-to)4032-4044
Number of pages13
JournalIEEE Transactions on Transportation Electrification
Volume9
Issue number3
DOIs
Publication statusPublished - 1 Sept 2023

Keywords

  • Dead time
  • model predictive control (MPC)
  • multivectors
  • permanent magnet synchronous machine (PMSM)

ASJC Scopus subject areas

  • Automotive Engineering
  • Transportation
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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