An Optimal Reduced-Control-Set Model Predictive Flux Control for 3L-NPC Fed Induction Motor Drive

Ilham Osman, Dan Xiao, Muhammed Fazlur Rahman, Margarita Norambuena, Jose Rodriguez

Research output: Contribution to journalArticlepeer-review

Abstract

This paper proposes an efficient and optimal reduced control set model predictive flux control (RCS-MPFC) for a three-level neutral-point-clamped voltage source inverter (3L-NPC VSI) fed induction motor. The proposed algorithm reduces the computational time in the prediction stage without causing any suboptimality. The optimal voltage vector selected by the proposed method produces the same cost function value as that of the conventional FCS-MPFC which requires enumerating all 27 voltage vectors. Therefore, the proposed algorithm achieves the same performance as the conventional method in the entire range of operation of IM drives while the computational effort is significantly reduced. Experimental results verify the effectiveness of the proposed algorithm and its superior performance compared to the existing RCS-MPFC scheme.

Original languageEnglish
JournalIEEE Transactions on Energy Conversion
DOIs
Publication statusAccepted/In press - 2021

Keywords

  • Cost function
  • cost function
  • flux ripples
  • induction motor drives
  • Inverters
  • model predictive control
  • Prediction algorithms
  • Signal processing algorithms
  • Stators
  • suboptimality
  • three-level inverter
  • Torque
  • Voltage control

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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