2026 Scarpa SiC Power Module Condition Monitoring

Silicon carbide (SiC) power modules are increasingly deployed in automotive traction inverters, where reliable condition monitoring is essential to prevent in-service failures and reduce maintenance costs. Despite extensive qualification procedures standardized under AQG 324, no consolidated approach exists for in-field health state estimation of SiC devices. Existing methods range from physics-of-failure lifetime models, which lack real-time applicability, to purely data-driven architectures that require large labeled datasets and offer limited generalization, to physics-informed machine learning frameworks that, while promising, remain computationally demanding for embedded deployment. This work addresses condition monitoring of SiC MOSFET power modules assembled with sintered packaging technology, which prevents solder degradation and thereby produces aging behavior qualitatively distinct from previously studied devices. In solder-based modules, the forward voltage drop VDS follows smooth quasi-exponential trajectories driven by progressive solder delamination. With sintered packaging this mechanism is suppressed, and VDS instead exhibits multi-regime degradation profiles; modules are additionally subject to wirebond liftoff events that introduce abrupt, non-monotonic perturbations directly onto VDS, posing new challenges for condition monitoring and the transferability of cumulative-damage features for health state estimation of SiC power modules.