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

被引:1
作者
Yu, Bin [1 ,2 ,3 ,4 ]
Shi, Xingjian [5 ]
Zhou, Ze [6 ]
Xiang, Enyao [5 ]
Gao, Hongyi [5 ]
Luo, Haoze [5 ]
Li, Wuhua [5 ]
机构
[1] Nanjing Univ Informat Sci & Technol, Coll Automat, Nanjing 210044, Peoples R China
[2] Southeast Univ, Jiangsu Key Lab Smart Grid Technol & Equipment, Nanjing 210096, Peoples R China
[3] Zhejiang Univ, Coll Elect Engn, Hangzhou 310058, Peoples R China
[4] Yongjiang Lab, Ningbo 315202, Peoples R China
[5] Zhejiang Univ, Coll Elect Engn, Hangzhou 310027, Peoples R China
[6] Hebei Univ Technol, State Key Lab Reliabil & Intelligence Elect Equipm, Tianjin 300130, Peoples R China
基金
中国博士后科学基金;
关键词
Aging; Silicon carbide; MOSFET; Temperature measurement; Monitoring; Temperature sensors; Circuits; Reliability; Power electronics; Condition monitoring; Case temperature; condition monitoring; cosine similarity; SiC MOSFET; solid-state power controller (SSPC); DEGRADATION; RESISTANCE; FATIGUE;
D O I
10.1109/JESTPE.2024.3513357
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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 article introduces a nonelectrical, 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, meacosk and stdcosk, 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 noninvasive 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.
引用
收藏
页码:380 / 393
页数:14
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