AI-Based Multi-Objective Design Optimization Environment for EV Wireless Power Transfer

被引：0
|
作者：
Almazmomi, Rakan [1 ]
Arkadan, A. A. [1 ]
机构：
[1] Colorado Sch Mines, Dept Elect Engn, Golden, CO 80401 USA
来源：
2024 INTERNATIONAL APPLIED COMPUTATIONAL ELECTROMAGNETICS SOCIETY SYMPOSIUM, ACES 2024 | 2024年
关键词：
Artificial Neural Networks; Finite Element; Particle Swarm Optimization; State Space; Wireless Power Transfer;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
This study introduces a characterization and design optimization environment suitable for Electric Vehicle Wireless Power Transfer charging systems. It utilizes a Particle Swarm Optimization (PSO) search algorithm and Artificial Neural Networks (ANN), in conjunction with 3D EM Finite Element and State Space models to determine the optimal design parameters of wireless power transfer charging pads. The multi-objective optimization problem investigated considers system efficiency, output power, total material cost, and electromagnetic leakage.
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页数：2
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