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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 language | English |
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Article number | 7557 |
Journal | Scientific Reports |
Volume | 11 |
Issue number | 1 |
Number of pages | 18 |
ISSN | 2045-2322 |
DOIs | |
Publication status | Published - 6 Apr 2021 |
Keywords
- Reliability
- AI applications
- Artificial Intelligence (AI)
- Power Electronics
- Power Systems
- Design for Reliability
- Operations & Maintenance planning
- Power sharing control
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Dive into the research topics of 'Intelligent long-term performance analysis in power electronics systems'. Together they form a unique fingerprint.Projects
- 1 Finished
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REPEPS: REliable Power Electronic based Power System
Blaabjerg, F., Iannuzzo, F., Davari, P., Wang, H., Wang, X. & Yang, Y.
01/08/2017 → 01/12/2023
Project: Research