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Physics-Informed Condition Monitoring of SiC Power Modules

Mattia Scarpa, Evgeny Kusmenko

2025encondition monitoringSiC power modulesmachine learningautomotivehealth estimation

Abstract

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Silicon carbide (SiC) power modules are increasingly utilized in automotive traction inverters, necessitating reliable condition monitoring to avert in-service failures and mitigate maintenance costs. This study addresses the lack of a consolidated approach for in-field health state estimation of SiC devices despite existing qualification procedures and diverse methodologies. We examine condition monitoring of SiC MOSFET power modules using sintered packaging technology, which changes the aging behavior compared to solder-based modules. In solder-based units, the forward voltage drop, VDS, demonstrates quasi-exponential trajectories influenced by solder delamination, whereas in sintered packaging, VDS displays multi-regime degradation profiles, introducing unique challenges. The modules encounter wirebond liftoff events causing abrupt, non-monotonic changes to VDS, which complicates condition monitoring. This characterizes previously unconsidered dynamics in the health monitoring of SiC power modules deployed in automotive applications and paves the way for improved predictive maintenance strategies.

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Cite This Work

@article{3bac9552-b75b-4a53-acfd-77a2cce48676,
  title={Physics-Informed Condition Monitoring of SiC Power Modules},
  author={Mattia Scarpa and Evgeny Kusmenko},
  year={2025},
  language={en}
}
TY  - JOUR
TI  - Physics-Informed Condition Monitoring of SiC Power Modules
AU  - Mattia Scarpa
AU  - Evgeny Kusmenko
PY  - 2025
LA  - en
ER  -

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