ANN-Enhanced Dual Phase Shift PWM Control for Efficient Bidirectional Wireless Power Transfer in Electric Vehicle Applications

To support seamless Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) operations, Bidirectional Wireless Power Transfer (BWPT) eliminates manual intervention but faces challenges like power factor control, efficiency, and limited transfer rates. This research proposes a dual-phase shift PWM technique for improved Power Factor Correction (PFC) in BWPT systems. Additionally, an Artificial Neural Network (ANN)-based controller is integrated to enhance dynamic response and optimize switching decisions in real-time. The proposed control strategy is evaluated through simulation and experiments at 85 kHz and 3.7 kW. MATLAB/Simulink is used to model and simulate the BWPT system, enabling detailed performance analysis under various operating conditions. Results show a power transfer efficiency of 94.4% (simulation) and 90.1% (experiment), with improved THD and system robustness. The ANN integration demonstrates strong potential for intelligent, adaptive control in future BWPT systems.