INTELLIGENT POWER MANAGEMENT OF SUPERCONDUCTING INDUCTOR BASED DC–DC CONVERTERS FOR EXTREME FAST EV CHARGING

Abstract

Achieving the 2050 net-zero emission target requires rapid electrification of transportation systems, with battery electric vehicles (BEVs) playing a central role in reducing global carbon emissions. However, long charging durations continue to limit large-scale BEV adoption, creating a strong demand for ultra-fast and highly efficient charging technologies. Although conventional gridconnected AC–DC chargers achieve high conversion efficiency, significant energy losses across generation, transmission, and conversion stages reduce the overall system efficiency. To overcome these limitations, this paper presents an artificial intelligence–based controlled superconducting inductor–assisted DC–DC double-boost converter for ultra-fast electric vehicle charging applications. The proposed converter employs superconducting inductors based on Bi₂₂₂₃ and MgB₂ materials to minimize resistive losses, enhance current-handling capability, and achieve superior power density. An AI-based controller is developed to optimize switching behavior, improve output voltage regulation, and maintain stable operation under dynamic load and input variations. The complete system is designed and simulated in the MATLAB/Simulink environment to evaluate electrical performance, transient response, and conversion efficiency. Simulation results demonstrate that the proposed converter with the MgB₂ superconducting inductor achieves an efficiency exceeding 95% at 15 kW output power, outperforming systems using conventional inductors. Additionally, the AI-based control strategy significantly reduces voltage ripple, improves response speed, and strengthens robustness against parameter variations and disturbances. These results validate the effectiveness of the proposed intelligent superconducting power converter as a promising solution for next-generation ultra-fast electric vehicle charging infrastructure.