Model Predictive Control for a Six-Phase PMSM with High Robustness Against Weighting Factor Variation

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Detail(s)

Original languageEnglish
Article number8645694
Pages (from-to)2781-2791
Journal / PublicationIEEE Transactions on Industry Applications
Volume55
Issue number3
Online published20 Feb 2019
Publication statusPublished - May 2019

Abstract

This paper presents a novel model predictive torque control with discrete duty ratio optimization for a six-phase PMSM machine with high robustness against weighting factor variation. First, a two-step lookup table is developed to initially select the optimal voltage vector, which is to regulate the torque and flux in the energy conversion related subspace, as well as suppress the harmonic currents in the x-y subspace. Then, a null vector is inserted along with the selected optimal voltage vector to adjust the duty ratio with a set of value to avoid the complicated derivation. Subsequently, the optimal duty ratio is determined by a cost function to minimize the torque and flux error. So by using the proposed method, the torque ripple is reduced and even applying an improper weighting factor will not deteriorate the machine performance severely. Finally, experimentations are carried out to verify the validity of the proposed method.

Research Area(s)

  • Duty ratio, harmonic currents, lookup table, model predictive control (MPC), permanent magnet machine, PMSM, robustness, six-phase machine, torque ripple