An Improved Current Prediction Model for PMSM Drives Under Single Open-Phase Fault Considering Floating Motor Neutral

Zeliang Zhang, Mohammed Alkahtani, Yihua Hu, Chao Gong, Yuxuan Du, Guangzhao Luo

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

Abstract

The diagnosis and fault-tolerant control of open-phase faults in permanent magnet synchronous motor (PMSM) drive significantly rely on models describing post-fault behaviors of current and voltage. This paper aims to propose an improved current prediction model that can accurately estimate the post-fault current dynamics under the single open-phase fault. Firstly, in each switching state, the post-fault phase voltages are derived by considering the floating neutral voltage incurred by the back electromagnetic force (back-EMF). Furthermore, by incorporating the derived phase voltages as the activation sources in each switching cycle, the post-fault current prediction model is established. Moreover, the changes of inductances under the open-phase fault are taken into account by establishing the model in the independent phase model. Finally, experimental results validate the derived post-fault phase voltages and the post-fault current prediction model.

Original languageEnglish
Title of host publicationIECON 2023 - 49th Annual Conference of the IEEE Industrial Electronics Society
PublisherIEEE Computer Society
ISBN (Electronic)9798350331820
DOIs
StatePublished - 2023
Event49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023 - Singapore, Singapore
Duration: 16 Oct 202319 Oct 2023

Publication series

NameIECON Proceedings (Industrial Electronics Conference)
ISSN (Print)2162-4704
ISSN (Electronic)2577-1647

Conference

Conference49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023
Country/TerritorySingapore
CitySingapore
Period16/10/2319/10/23

Keywords

  • current prediction
  • fault modeling
  • open-phase fault
  • PMSM

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