Performance Prediction of Magnetic Core Structures for UAV Wireless Charging Systems

ABSTRACT Magnetic core structure plays an important role in improving the efficiency of wireless power transfer (WPT) systems for unmanned aerial vehicles (UAVs). However, there are still few systematic studies on the effects of ferrite core structural parameters on coil performance. This paper systematically studies the influence mechanism of structural parameters such as ferrite area ratio, thickness, and spacing on coil performance. A prediction model between ferrite size parameters and coupler performance was established using a multilayer perceptron (MLP) neural network algorithm. The determination coefficient R 2 of the established model was as high as 0.98. The experimental results show that the prediction results of the established model are within 10% of the actual test results, underscoring its high accuracy and superior predictive capabilities. This paper provides valuable insights into the design, evaluation, and optimization of magnetic core structures, which is expected to improve UAV‐WPT systems' efficiency.