电源学报

基于PSO算法的无人平台无线电能传输系统参数优化

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魏曙光中国电源学会会员 , 许非凡 , 李嘉麒 , 袁东

电源学报 | 无线电能传输 2026,24(5): 275-285

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电源学报 |无线电能传输 2026 , 24 (5) : 275 -285

基于PSO算法的无人平台无线电能传输系统参数优化

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许非凡（1999—　），男，博士研究生。研究方向：无线电能传输。E-mail：extraordinaryxu@163.com。

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许非凡（1999—　），男，博士研究生。研究方向：无线电能传输。E-mail：extraordinaryxu@163.com。

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李嘉麒（1991—　），男，博士，讲师。研究方向：永磁电机，无线电能传输。E-mail：lijiaqi8643@163.com。

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魏曙光中国电源学会会员, 许非凡, 李嘉麒, 袁东

作者信息

中国人民解放军陆军兵种大学，北京　100072

通讯作者:

袁东（1981—　），男，通信作者，博士，副教授。研究方向：能量管理。E-mail：yuandong198106@163.com。

作者简介:

魏曙光（1975—　），男，中国电源学会会员，博士，教授。研究方向：无线电能传输，陆战平台综合电力系统。E-mail：weishuguang1975@163.com。

许非凡（1999—　），男，博士研究生。研究方向：无线电能传输。E-mail：extraordinaryxu@163.com。

李嘉麒（1991—　），男，博士，讲师。研究方向：永磁电机，无线电能传输。E-mail：lijiaqi8643@163.com。

Parameter Optimization of Wireless Power Transfer System Based on PSO Algorithm for Unmanned Platforms

Shuguang WEI Member, CPSS, Feifan XU, Jiaqi LI, Dong YUAN

Affiliations

Army Arms University of PLA, Beijing 100072, China

出版时间: 2026-05-30 doi: 10.13234/j.issn.2095-2805.2026.5.275

文章导航

摘要

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无人平台具有体积小、成本低、无需载员操作等优势，广泛应用于各类军事任务中。目前，无人平台主要以电能作为能源，其对可靠电能传输方式的需求不断增大，在人员无法参与、充电接口不适配、充电流程效率低等场合，有线充电或更换电池存在弊端，无法满足无人平台对电能传输的需求。针对无人平台无线电能传输需求设计系统结构，并基于该结构提出了一种基于粒子群优化PSO（particle swarm optimization）算法的参数优化方法。通过对无人平台无线电能传输系统补偿电路、耦合线圈、储能器件结构及特性进行分析，提出系统参数优化数学模型的优化目标及功率、效率、电流3个方面的约束条件，设计基于PSO算法的无人平台无线电能传输系统参数优化方法的算法流程。通过算法仿真与样机实验相结合的方法进行验证，结果表明，提出的基于PSO算法的无人平台无线电能传输系统参数优化方法能够降低系统输出电压和功率、效率随负载电阻和耦合系数变化的波动幅度，提高无人平台无线电能传输系统的鲁棒性和环境适应性。

关键词

无线电能传输 / LCC/S补偿电路 / 参数优化方法 / 粒子群优化算法

Abstract

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The unmanned platforms have the advantages of small size, low cost and no man-carrying operation, and are widely used in various military missions. At present, the unmanned platforms mainly use electric energy as power source, and their demand for reliable power transmission methods is increasing. In the cases where personnel cannot participate, the charging interfaces are not suitable, and the charging process is low in efficiency, wired charging or battery replacement has drawbacks, which cannot meet the demand for electric power transmission of the unmanned platforms. The system structure is designed to meet the requirements of unmanned platforms wireless power transfer, and based on this structure, a parameter optimization method based on particle swarm optimization (PSO) algorithm is proposed. By analyzing the structure and characteristics of the compensation circuit, coupling coil and energy storage device of the unmanned platform wireless power transfer system, the optimization objectives of the mathematical model of the system parameter optimization and the constraints of power, efficiency and current are proposed, and the algorithm flow of the parameter optimization method of the unmanned platform wireless power transfer system based on PSO algorithm is designed. The results show that the proposed optimization method based on PSO algorithm can reduce the fluctuation amplitude of the output voltage, power and efficiency with the load resistance and coupling coefficient change, and improve the robustness and environmental adaptability of the unmanned platform wireless power transfer system.

Key words

Wireless power transfer / LCC/S compensation topology / parameter optimization method / particle swarm optimization (PSO) algorithm

引用本文

魏曙光中国电源学会会员, 许非凡, 李嘉麒, 袁东. 基于PSO算法的无人平台无线电能传输系统参数优化. 电源学报, 2026 , 24 (5) : 275 -285 . DOI: 10.13234/j.issn.2095-2805.2026.5.275

Shuguang WEI, Feifan XU, Jiaqi LI, Dong YUAN. Parameter Optimization of Wireless Power Transfer System Based on PSO Algorithm for Unmanned Platforms[J]. Journal of Power Supply, 2026 , 24 (5) : 275 -285 . DOI: 10.13234/j.issn.2095-2805.2026.5.275

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2026年第24卷第5期

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doi: 10.13234/j.issn.2095-2805.2026.5.275

接收时间：2024-03-11
首发时间：2026-10-29
出版时间：2026-05-30

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收稿日期：2024-03-11
修回日期：2024-04-17
录用日期：2024-05-02

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中国人民解放军陆军兵种大学，北京　100072

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袁东（1981—　），男，通信作者，博士，副教授。研究方向：能量管理。E-mail：yuandong198106@163.com。

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2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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