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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


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
Issue number1
Early online date29 Sept 2023
Publication statusPublished - Mar 2024


  • Finite control set model predictive control (FCS-MPC)
  • low complexity
  • multi-vector control
  • permanent magnet synchronous motor (PMSM)
  • pre-selection


Dive into the research topics of 'An Efficient Multi-Vector-Based Model Predictive Current Control for PMSM Drive'. Together they form a unique fingerprint.

Cite this