Active Thermal Management of IGBT Modules in Electric Vehicle Inverters Under CLTC Driving Cycles Using Multi-Parameter Fuzzy Control

To address junction-temperature fluctuations and thermal-fatigue degradation of IGBT modules in EV traction inverters under CLTC conditions, this study develops a hierarchical active thermal-management framework. A temperature-dependent loss model coupled with a fourth-order Foster thermal network is first established and evaluated against experimentally derived temperature references. The prediction errors are mainly within ±5 °C over approximately 30–145 °C, with a small number of larger deviations during rapid thermal transients. Speed-based feedforward scheduling, single-variable fuzzy feedback, and dual-variable fuzzy control coordinating switching frequency and cooling intensity are then evaluated in simulation. Rainflow counting and the Miner rule show cumulative-damage reductions of 57.09%, 66.70%, and 81.90%, respectively, while the dual-variable strategy increases the model-based equivalent lifetime from 5.32 to 31.99 years. The results demonstrate the benefit of coordinated heat-generation and heat-dissipation control for inverter thermal reliability.