Enhancing Wireless Charging Efficiency with Advanced Mechanisms and Analysis Model

This study deals with the task of optimizing wireless charging systems for Electric Vehicles (EV) by focusing on minimizing energy losses and charging effectiveness utilizing inductive power transfer (I). The setup incorporates an sensor network to accurately detect, ensuring precise coil. Moreover, it utilizes Proximal Policy Optimization (PPO), a reinforcement learning framework, to dynamically adjust parameters coil alignment and input based on analytical findings. Furthermore, a Battery Management System (MS) regulates charging profiles, while rectification and power conversion guarantee steady DC output. The control and sensing circuit triggers charging only upon confirming vehicle alignment, with the PPO analysis model enhancing energy transfer efficiency by up to 94% while minimizing power wastage. The system also integrates safety features such as over protection and temperature monitoring. The practical significance of study lies in its ability to offer a more efficient and user-centric EV charging, catering current and future market demands.