Gray optimized adaptive model predictive control for enhanced efficiency and misalignment tolerance in wireless EV charging systems

Wireless power transfer (WPT) systems have gained a lot of attention in electric vehicle (EV) charging due to their potential for efficient, contactless energy transfer, offering enhanced convenience and safety compared to traditional plug-in methods. A phase-shifted full bridge inverter and continuous control set model predictive control are the foundations of a suggested primary side control technique for the WPT system. The optimal control variable is then found by converting the controller's gray wolf optimization issue into a problem of minimizing the cost function's value in order to get the best response from the system. According to the findings of the simulation, the control system operates at a frequency of 10 kHz to achieve real-time voltage adjustment, and about 8.6 kW of power is transmitted. Compared with the conventional technique, the power transferred is improved when misalignment is addressed by interference factors. The system, validated through hardware implementation and testing, demonstrated stable output power and voltage regulation with an average efficiency of 95.2%, demonstrating its reliability for real-world EV charging applications. The proposed method enhances double LCC compensated WPT systems' performance, making them suitable for compact, lightweight receiver applications, and enables real-time regulation of system output voltage.