基于IMOGWO算法的无线电能传输系统参数优化  

Parameter Optimization of Wireless Power Transfer System Based on IMOGWO Algorithm

作　　者：黄文聪[1] 张凤顺 胡滢 余文锦 常雨芳[1] HUANG Wencong;ZHANG Fengshun;HU Ying;YU Wenjin;CHANG Yufang(Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System,Hubei University of Technology,Wuhan 430068,China)

机构地区：[1]湖北工业大学太阳能高效利用及储能运行控制湖北省重点实验室,湖北武汉430068

出　　处：《控制工程》2025年第4期628-636,645,共10页Control Engineering of China

基　　金：国家自然科学基金资助项目(61903129);湖北工业大学博士启动基金资助项目(BSQD2020012)。

摘　　要：针对当前无线电能传输系统多目标优化的效率不高,难以同时兼顾传输效率和功率密度等问题,提出了一种改进的多目标灰狼优化(improved multi-objective grey wolf optimization,IMOGWO)算法对系统参数进行优化。首先,推导了磁耦合机构参数的解析表达式,并以线圈半径、线圈匝数、线圈间距、工作频率和负载阻值为设计变量,以系统的传输效率和功率密度为优化目标,建立了磁耦合机构多目标优化的数学模型。然后,提出了3种改进策略对多目标灰狼优化(multi-objective greywolf optimization,MOGWO)算法进行改进,并对模型求解。仿真结果表明,与非支配排序遗传算法Ⅱ(non-dominated sorting genetic algorithm Ⅱ,NSGA-Ⅱ)和MOGWO算法相比,IMOGWO算法在进行优化时所得的解集更优,性能评价指标值也更优。结合实际应用需求对目标函数赋予不同权重,在最优解集中选择一组参数用于设计参考,在COMSOL Multiphysics平台和MATLAB/Simulink平台上进行联合仿真,仿真结果验证了IMOGWO算法的有效性。To solve the problems that the efficiency of multi-objective optimization of the wireless power transfer system is not high and it is difficult to study both transfer efficiency and power density,an improved multi-objective grey wolf optimization(IMOGWO)algorithm is proposed to optimize the system parameters.Firstly,the analytical expressions of the parameters of the magnetic coupling mechanism are deduced.On this basis,the multi-objective optimization mathematical model of the magnetic coupling mechanism is established with the coil radius,the number of coil turns,the turn spacing,the frequency and the load resistance as the design variables and the transfer efficiency and power density of the system as the optimization objectives.Then,three improvement strategies are used to improve the multi-objective grey wolf optimization(MOGWO)algorithm,and the improved algorithm is used to process the multi-objective optimization mathematical model.The simulation results show that,compared with the non-dominated sorting genetic algorithm II(NSGA-II)and MOGWO algorithm,the IMOGWO algorithm obtains better solution sets and performance evaluation index values during optimization.According to the actual application requirements,different weights are given to the objective function,a set of parameters is selected in the optimal solution sets for design reference,and the co-simulation is carried out on the COMSOL Multiphysics platform and MATLAB/Simulink platform.The simulation results verify the effectiveness of the IMOGWO algorithm.

关 键 词：无线电能传输 多目标优化 IMOGWO算法 联合仿真 

分 类 号：TM724[电气工程—电力系统及自动化] TP18[自动化与计算机技术—控制理论与控制工程]