Multi-objective particle swarm optimization applied to the design of Wireless Power Transfer systems

N. Hasan, Tuba Yilmaz, R. Zane, Zeljko Pantic
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引用次数: 18

Abstract

This paper proposes a stochastic method - particle swarm optimization (PSO) and Pareto front technique, to conduct a multivariable optimization and design an inductively coupled power transfer system. Previously, design methods have been proposed which require designer experience; they are not only computationally challenging, but also frequently result in suboptimum solutions. The algorithm proposed in this paper models all losses and inductance matrix analytically. We study four common compensation structures, and select a series-parallel topology to design a 200 W experimental prototype optimized with respect to transfer efficiency and VA rating. Experiments and numerical simulations are employed to verify the optimization algorithm.
多目标粒子群算法在无线电力传输系统设计中的应用
本文提出了一种随机方法——粒子群优化(PSO)和帕累托前沿技术,进行多变量优化设计电感耦合输电系统。以前,提出的设计方法需要设计师的经验;它们不仅在计算上具有挑战性,而且经常导致次优解决方案。本文提出的算法对所有损耗和电感矩阵进行了解析建模。我们研究了四种常见的补偿结构,并选择串并联拓扑设计了一个200 W的实验样机,对传输效率和VA额定值进行了优化。通过实验和数值模拟对优化算法进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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