Multi-objective optimization for 10-kW rated power dynamic wireless charging systems of electric vehicles

被引:2
|
作者
Zhou, Ze [1 ]
Liu, Zhitao [1 ]
Su, Hongye [1 ]
Zhang, Liyan [2 ]
机构
[1] Zhejiang Univ, Inst Cyber Syst & Control, State Key Lab Ind Control Technol, Hangzhou 310027, Peoples R China
[2] Wuhan Univ Technol, Sch Automat, Wuhan 430070, Peoples R China
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
dynamic wireless charging; electric vehicles; multi-objective optimization; constrained adaptive particle swarm optimization; PARTICLE SWARM; IPT SYSTEMS; COUPLER; DESIGN;
D O I
10.1007/s11432-020-3255-5
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we propose a method to optimize the output power, efficiency, and cost of the dynamic wireless charging (DWC) system of electric vehicles by using the transmitting coil spacing as the decision variable. In a set of transmitting equipment, we adopt a structure with two transmitting networks in parallel and derive loss models. The expressions of the output power and efficiency of the DWC system are obtained by data fitting. In addition, combined with the proposed cost function, we construct a multi-objective optimization problem on output power, efficiency, and cost. Due to the complexity of the objective function, it is difficult to solve the problem by the analytic method, and thus we propose a constrained adaptive particle swarm optimization (CAPSO) algorithm with high accuracy to solve the problem. Finally, the simulation results verify the feasibility of the proposed model. The advantages of the proposed CAPSO algorithm and the optimization results under different weight combinations are presented.
引用
收藏
页数:18
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