Evaluation And Optimization Of Electromagnetic Coupling Resonant Wireless Power Transmission System

With the rapid development of wireless power transmission technology in the past decade.The power transmission mode which is not limited by cables has brought great convenience to human life and production.In the four mainstream wireless power transmission technologies,magnetic coupled resonance wireless power transmission technology has many advantages in the medium distance wireless power transmission,it has been focused on by scholars and researchers at home and abroad,and has been widely used.So,a lot of important research results have been obtained.In this paper,based on S-S structure of magnetic coupling resonance wireless power transmission system transmission performance and optimization of intelligent control algorithm are studied and explored.The working principle of magnetic coupling resonance wireless power transmission is analyzed,and several main wireless power transmission strategies are compared and analyzed;The characteristics of S-S structure magnetic coupling resonance wireless power transmission system and P-P structure magnetic coupling resonance wireless power transmission system are compared,Finally,the S-S structure system is taken as the research object of this paper,and the conveying performance of the system is analyzed.This paper analyzes the frequency splitting phenomenon in wireless power transmission,and constructs the impedance matching circuit model to suppress the frequency splitting;An evaluation function and its constraint conditions of the transmission performance of the magnetic coupling resonance wireless power transmission system are proposed,which is related to the transmission efficiency and output power of the system.The intelligent control algorithm to solve the objective function is analyzed in detail,and their advantages and disadvantages are fully explained;Taking the evaluation function as the objective function of the algorithm,four algorithms are used to calculate respectively,and then the operation results of the four algorithms are obtained,Put the best evaluation function value data model into the simulation model made by ANSYS Electronics Desktop Simplorer software,and test the data obtained by the algorithm through the simulation waveform.Finally,the physical experiment is carried out,and the results are consistent with the simulation experiment,which proves that the evaluation function and the adaptive particle swarm optimization algorithm of simulated annealing optimization have certain practical significance and theoretical research value.