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Degradation Assessment and Precursor Identification for SiC MOSFETs Under High Temp Cycling.
- Source :
-
IEEE Transactions on Industry Applications . May/Jun2019, Vol. 55 Issue 3, p2858-2867. 10p. - Publication Year :
- 2019
-
Abstract
- Silicon carbide (SiC) power mosfets are promising alternatives to Si devices in high-voltage, high-frequency, and high-temperature applications. The rapid and widespread deployment of SiC devices raises long-term reliability concerns, particularly for mission and safety critical systems due to limited field data and potential uncertainties. Therefore, it is essential to investigate progressive degradations and parameter shifts in SiC devices to develop system integrated degradation monitoring tools for self-monitoring converters, which can recognize failure precursors at the earliest stage and prevent catastrophic failures. This paper presents a comprehensive long-term reliability analysis of commercially available SiC mosfets under high temperature operation and high temperature swing, degradation related key precursors, and possible causes behind them. For this purpose, discrete SiC devices are power cycled and all datasheet parameters are recorded at certain intervals with the aid of the curve tracer. Variation of electrical parameters throughout the tests is presented in order to assess their correlation with the aging/degradation state of the switch. Among them, gate oxide charge trapping related threshold voltage drift and corresponding on state resistance variation has been observed for all samples. For some samples, bond wire heel cracking is found to be the root cause of sudden on state resistance and body diode voltage increases. The discussions regarding aging precursors are supported by failure analysis obtained through the decapsulation of failed devices. Finally, the findings are evaluated in order to define the suitability of electrical parameters as an aging precursor parameter under the light of practical implementation related issues. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00939994
- Volume :
- 55
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Industry Applications
- Publication Type :
- Academic Journal
- Accession number :
- 136101347
- Full Text :
- https://doi.org/10.1109/TIA.2019.2891214