A stochastic model-based prognostic for IGBT power module remaining useful life estimation using a physical model-based shape function

The widespread adoption of renewable energy sources (RES) is at the forefront of global efforts, alongside systems electrification, to combat climate change and achieve the ambitious goal of net-zero emissions (NZE). Power electronic modules such as insulated gate bipolar transistors (IGBTs) are the key components in systems electrification and energy conversion systems; their reliability as well as their lifetime prognosis are some of the research's major topics to enable predictive maintenance since they are relatively vulnerable to degradation. This article presents a stochastic Gamma process-based prognostic approach for IGBT power modules, using a physical model as shape function of the Gamma distribution function, to enhance their remaining useful life (RUL) prediction.