Intelligent long-term performance analysis in power electronics systems

Abstract 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 cond...

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Autores principales:	Saeed Peyghami, Tomislav Dragicevic, Frede Blaabjerg
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/8593fa95d7ee42f4b0be0b8c18e41e7e
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spelling	oai:doaj.org-article:8593fa95d7ee42f4b0be0b8c18e41e7e2021-12-02T14:17:31ZIntelligent long-term performance analysis in power electronics systems10.1038/s41598-021-87165-32045-2322https://doaj.org/article/8593fa95d7ee42f4b0be0b8c18e41e7e2021-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-87165-3https://doaj.org/toc/2045-2322Abstract 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.Saeed PeyghamiTomislav DragicevicFrede BlaabjergNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-18 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Saeed Peyghami Tomislav Dragicevic Frede Blaabjerg Intelligent long-term performance analysis in power electronics systems
description	Abstract 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.
format	article
author	Saeed Peyghami Tomislav Dragicevic Frede Blaabjerg
author_facet	Saeed Peyghami Tomislav Dragicevic Frede Blaabjerg
author_sort	Saeed Peyghami
title	Intelligent long-term performance analysis in power electronics systems
title_short	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_sort	intelligent long-term performance analysis in power electronics systems
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/8593fa95d7ee42f4b0be0b8c18e41e7e
work_keys_str_mv	AT saeedpeyghami intelligentlongtermperformanceanalysisinpowerelectronicssystems AT tomislavdragicevic intelligentlongtermperformanceanalysisinpowerelectronicssystems AT fredeblaabjerg intelligentlongtermperformanceanalysisinpowerelectronicssystems
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Intelligent long-term performance analysis in power electronics systems

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