An Efficient Multi-Vector-Based Model Predictive Current Control for PMSM Drive

Jun Sun, Yong Yang, Rong Chen, Xinan Zhang, Chee Shen Lim, Jose Rodriguez

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

To address the problems of high current harmonics, large torque ripples, and heavy computational burden in the finite control set model predictive control (FCS-MPC), this paper proposes an efficient multi-vector model predictive current control (MPCC) scheme for permanent magnet synchronous motor (PMSM) drive. Firstly, a simple pre-selection method based on the trace of the stator current increment is proposed to obtain the candidate optimal voltage vectors. This pre-selection method avoids the heavy computational burden of evaluating all voltage vectors and is easy to implement. Then, to further reduce the torque ripples and current harmonics, the dwelling time of each voltage vector is achieved in inverse proportion to its cost function. Compared to the standard means, the proposed scheme is able to obtain great performance while greatly decreasing the computational burden and complexity. And its effectiveness is experimentally validated through comparative assessments.

Original languageEnglish
Pages (from-to)79-89
Number of pages11
JournalCPSS Transactions on Power Electronics and Applications
Volume9
Issue number1
DOIs
Publication statusPublished - Mar 2024

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