Dynamic numerical calculation of multi-physics fields in IGBT chip layer based on ETM-PINN

Abstract

The electric-thermal-mechanical (ETM) multi-physics coupling fields commonly exists in power electronic devices such as insulate-gate bipolar transistor (IGBT), which dominates the evolution of key state variables inside the components. Among them, the junction e and electric potential of the chip layer, as the dependent variables of various lifetime physical models, directly affect its remaining service life and health status. Aiming at the problem that the key physical variables inside the IGBT are difficult to monitor and predict, this paper first integrates and establishes the ETM coupling partial differential equations (PDEs) inside the IGBT, then accordingly proposes an accurate numerical calculation method for coupled physical fields based on ETM-physics-informed neural networks (ETM-PINN).Through relevant simulation verification, it can not only realize the numerical calculation of the chip layer junction temperature and electric potential field without data, but also perform multi-physics predictive calculation with reduced accuracy in the absence of the key coefficients in PDEs. In the presence of additional physical field data, it can also perform data-model fusion calculations to further improve the solution accuracy.