基于径向基神经网络的多负载无线电能传输系统自适应阻抗匹配方法

doi:10.19595/j.cnki.1000-6753.tces.L90268

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Abstract With the development of wireless power transfer (WPT) technology, more and more attention has been paid to supplying electricity to multiple loads simultaneously. In a multi-load WPT system, the cross coupling between the receiving coils will detune the system, resulting in a decrease of transmission efficiency at the resonant frequency. This paper firstly analyzes the influence of cross coupling on transmission efficiency, and proposes a "T" type impedance matching network based on RBF neural network. The proposed method adjusts the capacitance in the matching network in real time according to different loads, realizing the adaptive matching of system and load. Finally, an experimental setup was built for the proposed method, and the results show that when the cross coupling is the greatest, the system transmission efficiency increased from 34% to 78%.

Key words： Radial basis function (RBF) cross coupling impedance matching wireless power transfer

Received: 07 July 2020

PACS:	TM72
	TM15

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	Articles by authors
	Wu Yuebao
	Zhao Jinbin
	Zhang Shaoteng
	Zhang Junwei
	Wang Xueliang

Cite this article:

Wu Yuebao,Zhao Jinbin,Zhang Shaoteng等. An Adaptive Impedance Matching Method Based on Radial Basis Function Neural Network in Multi-Load Wireless Power Transfer Systems[J]. Transactions of China Electrotechnical Society, 2021, 36(19): 3969-3977.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.L90268 OR https://dgjsxb.ces-transaction.com/EN/Y2021/V36/I19/3969

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