Electrothermal modeling of silicon carbide (SiC) power devices is frequently performed to estimate the device temperature in operation, typically assuming a constant thermal conductivity and/or heat capacity of the SiC material. Whether and by how much the accuracy of the resulting device temperature prediction under these assumptions is compromised has not been investigated so far. Focusing on high-temperature operating conditions as found under short circuit (SC), this paper presents a comprehensive analysis of thermal material properties determining the temperature distribution inside SiC power MOSFETs. Using a calibrated technology computer-aided design (TCAD) electrothermal model, it is demonstrated that the temperature prediction of SiC power devices under SC operation when neglecting either the top metallization or the temperature dependence of the heat capacity is inaccurate by as high as 25%. The presented analysis enables to optimize compact electrothermal models in terms of accuracy and computational time, which can be used to assess the maximum temperature of SiC power MOSFETs in both discrete packages and multichip power modules exposed to fast thermal transients. A onedimensional thermal network of a SiC power MOSFET is proposed based on the thermal material properties, the size of the active area of the device, and its thickness. Index Terms-Electrothermal (ET) modeling, short circuit (SC), silicon carbide (SiC), TCAD, thermal conductivity.
I. INTRODUCTIONW ITH the ever-increasing requirements for energy saving, the adoption of silicon carbide (SiC) power transistors has been following a growing trend across different power electronic (PE) applications, including electrical vehicles (EVs), EV charging infrastructure, power factor correction, power supply, photovoltaics, uninterruptible power supplies, motor drives, wind, and rail [1]. Increasing the acceptance of the emerging SiC technology in the field of high-frequency, high-temperature, and/or high-power applications needs to be supported by a comprehensive understanding of SiC material properties and their influence on the system performance. Nowadays, multiphysics modeling tools based on the underlying physics of the SiC material are widely employed both in academia and industry to