Optimization of Impedance Matching in Wireless Power Transfer Using Genetic Algorithm-Driven Compensation Topologies

Abstract

Wireless Power Transfer (WPT) devices to transmit energy without physical touch in a variety of applications has drawn a lot of attention. In these systems, choosing appropriate compensation topologies and making sure the transmitter and receiver have the right impedance matching are crucial to achieving high transfer efficiency. In order to comprehend their impact on system stability and power transfer efficiency, this study examines the performance of series, parallel, and hybrid compensation topologies. Electromagnetic interactions are modeled and system behavior under various loading and misalignment circumstances is assessed using Finite Element Method (FEM) simulations. To get efficient impedance matching and increased overall efficiency, a Genetic Algorithm (GA) is also used to optimize important parameters, such as operating frequency and compensating capacitances. The findings demonstrate the performance trade-offs between different compensation topologies and offer precise recommendations for choosing the best configurations in real-world WPT systems. The study shows that the design process is much improved by integrating evolutionary optimization with FEM-based analysis, allowing for more dependable, effective, and flexible wireless power transfer systems.