Flux Linkage-Based Model Predictive Current Control for Nonlinear PMSM Drives

Sebastian Wendel, Petros Karamanakos, Armin Dietz, Ralph Kennel

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

5 Scopus citations

Abstract

In this paper, a flux linkage-based direct model predictive current control approach is presented for small permanent magnet synchronous motor (PMSM) drives. The method aims to minimize the current ripples at steady state by deciding on the optimal switching instant, while exhibiting fast dynamic behavior during transients. To this end, the future trajectory of the stator current is not computed based on the machine inductances or inductance look-up tables, but on the changes of the magnetic flux linkage by utilizing flux linkage maps. As shown, the proposed method can be particularly advantageous for electric drives with a noticeable nonlinearity in terms of saturation and/or cross-coupling effects since it allows for a significantly increased prediction accuracy, which leads to an improved steady-state performance as indicated by the reduced current distortions.

Original languageEnglish
Title of host publicationProceedings - IECON 2020
Subtitle of host publication46th Annual Conference of the IEEE Industrial Electronics Society
PublisherIEEE Computer Society
Pages3051-3056
Number of pages6
ISBN (Electronic)9781728154145
DOIs
StatePublished - 18 Oct 2020
Event46th Annual Conference of the IEEE Industrial Electronics Society, IECON 2020 - Virtual, Singapore, Singapore
Duration: 19 Oct 202021 Oct 2020

Publication series

NameIECON Proceedings (Industrial Electronics Conference)
Volume2020-October

Conference

Conference46th Annual Conference of the IEEE Industrial Electronics Society, IECON 2020
Country/TerritorySingapore
CityVirtual, Singapore
Period19/10/2021/10/20

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