A method for mutual inductance and load parameter identification of LCL-LCL topology MC-WPT system based on FCN

To address the challenge of real-time and accurate identification of mutual inductance and load parameters in LCL-LCL-type magnetically coupled wireless power transfer (MC-WPT) systems, this paper proposes a parameter identification method based on a Fully Connected Network (FCN). By establishing the electrical model of the LCL-LCL-type MC-WPT system and constructing a high-dimensional simulation dataset, the FCN is utilized to achieve a high-precision nonlinear mapping between the system’s electrical quantities and the mutual inductance/load parameters. This method enables fast prediction and estimation of parameters, featuring advantages such as a simple structure, high computational efficiency, and ease of engineering implementation. Simulation and experimental results demonstrate that the proposed FCN identification model constrains the identification errors of mutual inductance and load parameters within 2.5%, while requiring minimal computational resources and achieving fast identification speed. The research findings can provide effective technical support for the online parameter identification of MC-WPT systems.