Dynamic Thermal Network Parameter Updating Strategy for IGBT Full-Bridge Modules in Digital Twin Applications

To meet the conflicting demands of real-time simulation and high fidelity for thermal modeling of IGBT modules in digital twin applications, this paper presents a dynamic thermal network parameter updating strategy. A hybrid thermal model is constructed by combining a high-fidelity finite-element-method reference model with a 3-D compact network. Initial thermal resistance and capacitance parameters are obtained via offline calibration and validated against the transient thermal impedance curve. A dynamic identification method based on recursive least squares with precomputed sensitivity matrices is then proposed. It dynamically updates each independent thermal branch using only real-time chip junction temperature measurements. The Vincotech full-bridge IGBT module is used for simulation validation. The proposed method achieves steady-state identification errors of 3.2% for the IGBT chip thermal resistance and 4.5% for the freewheeling diode chip thermal resistance, outperforming particle swarm optimization and dual Kalman filter in both convergence speed and steady-state accuracy. Thus, it satisfies the requirements of real-time tracking and dynamic evolution for thermal models in digital twin systems.