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Intelligent long-term performance analysis in power electronics systems

This paper proposes a long-term performance indicator for power electronic converters based on their reliability. The converter reliability is represented by the proposed constant lifetime curves, which have been developed using Artificial Neural Network (ANN) under different operating conditions. U...

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Detalles Bibliográficos
Autores principales: Peyghami, Saeed, Dragicevic, Tomislav, Blaabjerg, Frede
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8024307/
https://www.ncbi.nlm.nih.gov/pubmed/33824384
http://dx.doi.org/10.1038/s41598-021-87165-3
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author Peyghami, Saeed
Dragicevic, Tomislav
Blaabjerg, Frede
author_facet Peyghami, Saeed
Dragicevic, Tomislav
Blaabjerg, Frede
author_sort Peyghami, Saeed
collection PubMed
description This paper proposes a long-term performance indicator for power electronic converters based on their reliability. The converter reliability is represented by the proposed constant lifetime curves, which have been developed using Artificial Neural Network (ANN) under different operating conditions. Unlike the state-of-the-art theoretical reliability modeling approaches, which employ detailed electro-thermal characteristics and lifetime models of converter components, the proposed method provides a nonparametric surrogate model of the converter based on limited non-linear data from theoretical reliability analysis. The proposed approach can quickly predict the converter lifetime under given operating conditions without a further need for extended, time-consuming electro-thermal analysis. Moreover, the proposed lifetime curves can present the long-term performance of converters facilitating optimal system-level design for reliability, reliable operation and maintenance planning in power electronic systems. Numerical case studies evaluate the effectiveness of the proposed reliability modeling approach.
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spelling pubmed-80243072021-04-08 Intelligent long-term performance analysis in power electronics systems Peyghami, Saeed Dragicevic, Tomislav Blaabjerg, Frede Sci Rep Article This paper proposes a long-term performance indicator for power electronic converters based on their reliability. The converter reliability is represented by the proposed constant lifetime curves, which have been developed using Artificial Neural Network (ANN) under different operating conditions. Unlike the state-of-the-art theoretical reliability modeling approaches, which employ detailed electro-thermal characteristics and lifetime models of converter components, the proposed method provides a nonparametric surrogate model of the converter based on limited non-linear data from theoretical reliability analysis. The proposed approach can quickly predict the converter lifetime under given operating conditions without a further need for extended, time-consuming electro-thermal analysis. Moreover, the proposed lifetime curves can present the long-term performance of converters facilitating optimal system-level design for reliability, reliable operation and maintenance planning in power electronic systems. Numerical case studies evaluate the effectiveness of the proposed reliability modeling approach. Nature Publishing Group UK 2021-04-06 /pmc/articles/PMC8024307/ /pubmed/33824384 http://dx.doi.org/10.1038/s41598-021-87165-3 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Peyghami, Saeed
Dragicevic, Tomislav
Blaabjerg, Frede
Intelligent long-term performance analysis in power electronics systems
title Intelligent long-term performance analysis in power electronics systems
title_full Intelligent long-term performance analysis in power electronics systems
title_fullStr Intelligent long-term performance analysis in power electronics systems
title_full_unstemmed Intelligent long-term performance analysis in power electronics systems
title_short Intelligent long-term performance analysis in power electronics systems
title_sort intelligent long-term performance analysis in power electronics systems
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8024307/
https://www.ncbi.nlm.nih.gov/pubmed/33824384
http://dx.doi.org/10.1038/s41598-021-87165-3
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