This paper focuses on the multiparametric design analysis of the EV traction inverter system to perform trade-off studies between two competing objectives: reliability and efficiency. A seamless performance evaluation process was developed between PLECS, a simulation platform for power electronic systems and the optimization computation of genetic algorithm based on NSGA-II in Python to achieve a reliable repetition of varied operating modes of the inverter to seek optimized parameters and non-dominant solutions. A realistic, high-fidelity, and multi-domain EV model based on the known physical parameters of Nissan Leaf was developed in PLECS along with a dynamic driving profile.
