Intelligent long-term performance analysis in power electronics systems

Saeed Peyghami*, Tomislav Dragicevic, Frede Blaabjerg

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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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.

Original languageEnglish
Article number7557
JournalScientific Reports
Volume11
Issue number1
Number of pages12
ISSN2045-2322
DOIs
Publication statusPublished - Dec 2021

Bibliographical note

Funding Information:
This work was supported by the Villum Foundation as a part of the Villum Investigator Program under the Reliable Power Electronic-Based Power System (REPEPS) Project at the Department of Energy Technology, Aalborg University.

Publisher Copyright:
© 2021, The Author(s).

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