Study and Optimization of Transmission Characteristics of the Magnetically Coupled Resonant Wireless Transmission System

Author:

Wen ChunmingORCID,Chen MinboORCID,Xu Qing

Abstract

The topology and parameter characteristics of the wireless energy transmission system are the main factors affecting the system’s performance. A series–parallel–series–parallel (spsp) topology for magnetically coupled wireless energy transmission is proposed to address the problems of low efficiency and low output power when transmitting electrical energy in the conventional magnetically coupled topology. The spsp topology is compared with the conventional topology based on circuit theory, and the two structures are modeled, characterized, and verified in detail. Simulations and tests are performed for the transmission conditions, an improved Gray Wolf optimization algorithm is proposed, and a physical system is built. Experiments show that the spsp structure is superior near the designed circuit parameters when the network works in a resonant state. The improved Gray Wolf optimization algorithm is then used to find the optimal parameters, and the transmission efficiency reaches 90.53%, which effectively improves the transmission performance of the system. The established physical system utilizes the optimized parameters for coil structure and coil offset experiments, and the average transmission efficiency is 83.75%, with an error of 6.78% calculated by data measurement. The rationality of the proposed structure and the correctness of the simulation parameter design method are verified, and it is hoped that the proposed system and circuit structure in this paper will provide a reference for the design of a magnetically coupled wireless energy transmission system.

Funder

National Natural Science Foundation of China

Guangxi Key Labor-atory of Hybrid Computation and IC Design Analysis

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

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