摘要
针对LCC-S型无线充电系统各个参数间相互影响且参数设计难以兼顾输出功率与传输效率等问题,提出了一种基于改进遗传粒子群算法(IPSO-GA)进行参数优化的方法。首先,分析了LCC-S补偿网络的工作原理,构建电路等效模型并评估了负载电阻、互感和谐振电感对系统输出特性的影响。其次,在传输特性分析基础上建立了系统多目标参数优化数学模型,提出三点改进策略对传统粒子群算法(PSO)进行改进,并设计了IPSO-GA算法参数优化方法的算法流程来实现传输性能的提升。最后,搭建仿真与实验平台进行验证。结果表明:该无线充电系统在满足输出功率的同时传输效率最高可达88.2%,能够有效地优化了系统的补偿参数进而提升无线电能传输系统的传输效率,并降低系统输出电压波动,为解决此类问题提供了新的思路。
To address the challenges of interdependent parameters and the difficulty in balancing output power with transmission efficiency in LCC-S type wireless charging systems,this paper proposes a parameter optimization method based on an Improved Genetic Particle Swarm Optimization algorithm(IPSO-GA).Firstly,the working principle of the LCC-S compensation network is analyzed.A circuit equivalent model is constructed,and the impacts of load resistance,mutual inductance,and resonant inductance on the system′s output characteristics are evaluated.Secondly,based on the transmission characteristic analysis,a multi-objective parameter optimization mathematical model for the system is established.Three improvement strategies are proposed to enhance the traditional Particle Swarm Optimization(PSO)algorithm,and the algorithmic workflow of the IPSO-GA parameter optimization method is designed to improve transmission performance.Finally,simulation and experimental platforms are established for verification.The wireless charging system can meet the output power while transmitting an efficiency of up to 88.2%.It effectively optimizes the system′s compensation parameters,thereby enhancing the transmission efficiency of the wireless power transfer system and reducing output voltage fluctuations.This approach provides a new solution for solving such problems.
作者
冯家璇
郭家虎
Feng Jiaxuan;Guo Jiahu(School of Electrical and Information Engineering,Anhui University of Science and Technology,Huainan,Anhui 232000,China)
出处
《黑龙江工业学院学报(综合版)》
2025年第11期105-111,共7页
Journal of Heilongjiang University of Technology(Comprehensive Edition)
