Extraction and Reduction of Torque Ripples for Permanent Magnet Motors Controlled by FCS-MPCC Method

Yunshu Liu, Chao Gong, Shuangxia Niu, Xing Zhao, Jose Rodriguez

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper introduces a novel approach for torque ripple extraction and reduction in the context of finite control set model predictive control (FCS-MPCC) for permanent magnet motors (PMMs). Firstly, adopting a torque evaluation-based method to diminish torque ripples in PMMs under FCS-MPCC control, the proposed method distinguishes itself from traditional approaches by assessing torque ripple magnitudes through the formulation of new constraint conditions, obviating the need for weighting factors. Secondly, torque ripple magnitudes are extracted by deducting load torque and friction from electromagnetic torque. The load torque is observed via a sliding mode observer (SMO), with the stability of this SMO rigorously examined using a Lyapunov function. Finally, simulation is conducted on a three-phase PMM to validate the proposed method.

Original languageEnglish
Title of host publication2024 IEEE 10th International Power Electronics and Motion Control Conference, IPEMC 2024 ECCE Asia
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2134-2139
Number of pages6
ISBN (Electronic)9798350351330
DOIs
StatePublished - 2024
Event10th IEEE International Power Electronics and Motion Control Conference, IPEMC 2024 ECCE Asia - Chengdu, China
Duration: 17 May 202420 May 2024

Publication series

Name2024 IEEE 10th International Power Electronics and Motion Control Conference, IPEMC 2024 ECCE Asia

Conference

Conference10th IEEE International Power Electronics and Motion Control Conference, IPEMC 2024 ECCE Asia
Country/TerritoryChina
CityChengdu
Period17/05/2420/05/24

Keywords

  • extraction
  • model predictive control
  • Permanent magnet motor
  • reduction
  • torque ripple

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