Case Temperature Waveform Similarity-based Online Aging Monitoring for SiC MOSFETs of Accelerated Power Cycling Tests for DC-SSPCs

Online condition monitoring of SiC MOSFETs is essential for improving the reliability of Solid-State Power Controllers (DC-SSPC). Traditional monitoring methods based on electrical parameters require the design of highly precise monitoring circuits and complex control systems, to prevent disruptions...

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Bibliographic Details
Published in:IEEE journal of emerging and selected topics in power electronics 2025, p.1-1
Main Authors: Yu, Bin, Shi, Xingjian, Zhou, Ze, Xiang, Enyao, Gao, Hongyi, Luo, Haoze, Li, Wuhua
Format: Article
Language:English
Subjects:
Aging
case temperature
Circuits
Condition monitoring
cosine similarity
Monitoring
MOSFET
Power electronics
Reliability
SiC MOSFET
Silicon carbide
solid-state power controller
Temperature measurement
Temperature sensors
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Summary:Online condition monitoring of SiC MOSFETs is essential for improving the reliability of Solid-State Power Controllers (DC-SSPC). Traditional monitoring methods based on electrical parameters require the design of highly precise monitoring circuits and complex control systems, to prevent disruptions to the system's normal operation. This paper introduces a non-electrical, easily measured parameter-the case temperature-as a means of monitoring the aging status of SiC MOSFETs online, using an electrically insulated temperature sensor. Two aging characteristic parameters, mea cosk and std cosk, are proposed based on the improved cosine similarity of the case temperature waveform. These parameters enable effective tracking of overall aging trends of SiC MOSFETs and allow for the detection of severe aging in the bonding wire and the solder layer, without dependence on electrical parameters. This approach enhances the practicality of non-invasive and online monitoring. The effectiveness of the proposed method is validated through experiment results. Ultimately, this conditions monitoring technique supports fault diagnosis and predictive maintenance for DC-SSPCs.
ISSN:2168-6777
2168-6785
DOI:10.1109/JESTPE.2024.3513357