Lifetime estimation of enameled wires under accelerated thermal aging using curve fitting methods

Khowja, Muhammad Raza, Turabee, Gulrukh, Giangrande, Paolo, Madonna, Vincenzo, Cosma, Georgina, Vakil, Gaurang, Gerada, Chris and Galea, Michael (2021) Lifetime estimation of enameled wires under accelerated thermal aging using curve fitting methods. IEEE Access, 9 . pp. 18993-19003. ISSN 2169-3536

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Estimating the lifetime of enameled wires using the conventional/standard test method requires a significant amount of time that can endure up to thousands of testing hours, which could considerably delay the time-To-market of a new product. This paper presents a new approach that estimates the insulation lifetime of enameled wire, employed in electrical machines, using curve fitting models whose computation is rapid and accurate. Three curve fit models are adopted to predict the insulation resistance of double-coated enameled magnet wire samples, with respect to their aging time. The samples' mean time-To-failure is estimated, and performance of the models is apprised through a comparison against the conventional 'standard method' of lifetime estimation of the enameled wires. The best prediction accuracy is achieved by a logarithmic curve fit approach, which gives an error of 0.95% and 1.62% when its thermal index is compared with the conventional method and manufacturer claim respectively. The proposed approach provides a time-saving of 67% (83 days) when its computation time is compared with respect to the 'standard method' of lifetime estimation.

Item Type: Article
Additional Information: This work was supported by the Clean Sky 2 Joint Undertaking through the European Union's Horizon 2020 Research and Innovation Program under Grant 807081 and Grant 821023.
Keywords: Neural network; curve fitting; insulation lifetime; thermal aging; accelerated aging test; insulation resistance and dissipation factor
Schools/Departments: University of Nottingham Ningbo China > Faculty of Science and Engineering > School of Aerospace
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Depositing User: Yu, Tiffany
Date Deposited: 07 May 2021 09:03
Last Modified: 07 May 2021 09:03

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