Sen, B., Wang, J. orcid.org/0000-0003-4870-3744 and Lazari, P. (2016) A High-Fidelity Computationally Efficient Transient Model of Interior Permanent-Magnet Machine With Stator Turn Fault. IEEE Transactions on Industrial Electronics, 63 (2). pp. 773-783. ISSN 0278-0046
Abstract
An accurate transient model of interior permanent-magnet (IPM) machine with stator turn fault with due account of magnetic saturation is essential to develop robust and sensitive interturn fault detection algorithms and to evaluate drive controller performance and stability under fault conditions. This paper proposes a general method of modeling stator turn fault using flux linkage map of IPM machine under fault extracted from finite-element (FE) analysis. Simulation results from the proposed fault model are compared against FE and experimental results. The results show that the proposed model matches well with experimental data.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works |
Keywords: | Analytical models; condition monitoring; fault currents; permanent-magnet (PM) machines; saturation magnetization |
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) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 05 May 2016 09:41 |
Last Modified: | 05 May 2016 09:41 |
Published Version: | https://dx.doi.org/10.1109/TIE.2015.2491884 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers |
Refereed: | Yes |
Identification Number: | 10.1109/TIE.2015.2491884 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:99304 |