Improved Model Predictive Current Control for SPMSM Drives Using Current Update Mechanism

Xin Yuan, Shuo Zhang, Chengning Zhang, Alessandro Galassini, Giampaolo Buticchi, Michele Degano, Shuo Zhang

Research output: Journal PublicationArticlepeer-review

17 Citations (Scopus)

Abstract

Finite-set model predictive current control (FS-MPCC) has been employed for machine drives owing to the good dynamic performance. Sensitivity to parameter variation is one of the main barriers to its widespread application. To overcome this barrier, this article proposes an improved FS-MPCC for surfaced permanent magnet synchronous machines (SPMSMs). The contribution of this article is developing a novel current update mechanism, where the variation of resistance, rotor flux linkage, and inductance is considered, in which a modified coordinate system that contains a stationary and rotary axis frame is introduced. In this case, the predicted parameter can be obtained more accurately based on this mechanism, which can suppress the disturbances caused by model parameter mismatch. In addition, SPMSM parameter mismatch effect on FS-MPCC performance is analyzed in this article, which testifies that resistance mismatch influence on current prediction error can be neglected in practical system. The proposed FS-MPCC is validated and compared with different state-of-the-art methods. Improvement of the proposed control strategy is validated by means of experimental results on a 2-kW test rig.

Original languageEnglish
Article number9007627
Pages (from-to)1938-1948
Number of pages11
JournalIEEE Transactions on Industrial Electronics
Volume68
Issue number3
DOIs
Publication statusPublished - Mar 2021

Keywords

  • Finite-set model predictive current control (FS-MPCC)
  • model parameter mismatch
  • surfaced permanent magnet synchronous machines (SPMSMs)

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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