An Adaptive Impedance Matching Method Based on Radial Basis Function Neural Network in Multi-Load Wireless Power Transfer Systems
Wu Yuebao1, Zhao Jinbin1, Zhang Shaoteng1, Zhang Junwei1, Wang Xueliang2
1. College of Electrical Engineering Shanghai University of Electric Power Shanghai 200082 China; 2. Shanghai Guangwei Meixian Power Source and Electric Appliance Co. Ltd Shanghai 201100 China
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%.
吴月宝, 赵晋斌, 张少腾, 张俊伟, 汪学良. 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[J]. 电工技术学报, 2021, 36(19): 3969-3977.
Wu Yuebao, Zhao Jinbin, Zhang Shaoteng, Zhang Junwei, Wang Xueliang. An Adaptive Impedance Matching Method Based on Radial Basis Function Neural Network in Multi-Load Wireless Power Transfer Systems. Transactions of China Electrotechnical Society, 2021, 36(19): 3969-3977.
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2021, Vol. 36 
