Xiao, S. and Griffo, A. (2020) Online thermal parameter identification for permanent magnet synchronous machines. IET Power Electronics, 14 (12). pp. 2340-2347. ISSN 1751-8660
Abstract
Temperature monitoring of permanent magnet synchronous machines (PMSMs) is of great importance because high temperatures can significantly shorten the lifetimes of motor components. Accurate temperature predictions can be achieved using reduced-order lumped parameter thermal networks (LPTNs) with accurate thermal parameters. In this study, an online estimation method based on the recursive Kalman filter algorithm is introduced for online identification of the thermal resistances in a three-node LPTN representing motor stator iron, stator winding and permanent magnet. The identification procedure requires a rotor temperature measurement, which is provided by an accurate pulse-width modulation-based estimation method. The proposed methodology is experimentally validated and applied to real-time fault detection of the motor cooling system.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 Institution of Engineering and Technology (IET). This is an author-produced version of a paper subsequently published in IET Electric Power Applications. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | pulse width modulation; fault diagnosis; permanent magnet motors; rotors; Kalman filters; permanent magnets; synchronous motors; power system parameter estimation; iron; temperature measurement; reduced order systems; lumped parameter networks; stators; cooling |
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/P010350/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 24 Aug 2020 08:36 |
Last Modified: | 06 Jan 2021 14:52 |
Status: | Published |
Publisher: | Institution of Engineering and Technology |
Refereed: | Yes |
Identification Number: | 10.1049/iet-epa.2020.0119 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:164680 |