Zhu, Z.Q., Liang, D. and Liu, K. (2021) Online parameter estimation for permanent magnet synchronous machines : an overview. IEEE Access, 9. pp. 59059-59084.
Abstract
Online parameter estimation of permanent magnet synchronous machines is critical for improving their control performance and operational reliability. This paper provides an overview of the recent achievements of online parameter estimation of PMSMs with examples. The critical issues in parameter estimation are firstly analysed, especially the rank-deficient issue and inverter nonlinearities. Then, the state-of-the-art online parameter estimation modelling techniques are reviewed and assessed. Finally, some typical applications and examples are outlined, e.g. estimation of mechanical parameters, improvement of sensored and sensorless control performance, thermal condition monitoring, and fault diagnosis, together with future research trends.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 The Authors. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ . |
Keywords: | Condition monitoring; control performance; electrical parameter; fault diagnosis; mechanical parameter; online parameter estimation; permanent magnet synchronous machine; sensorless control |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield) |
Funding Information: | Funder Grant number Engineering and Physical Science Research Council EP/R004900/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 11 May 2021 06:28 |
Last Modified: | 11 May 2021 06:28 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers |
Refereed: | Yes |
Identification Number: | 10.1109/ACCESS.2021.3072959 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:173931 |