An Automatic Impedance Matching Method Based on the Feedforward-Backpropagation Neural Network for a WPT System
Yang Li, Weihao Dong, Qingxin Yang, Jingtai Zhao, Liu Liu, Shaojie Feng
Tiangong University
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摘要与影响
In a wireless power transfer (WPT) system via coupled magnetic resonances, the power transfer efficiency (PTE) drastically decreases with the transfer distance or the load changing. In this paper, the causes of efficiency degradation are analyzed, and an automatic impedance matching method based on the feedforward-backpropagation (BP) neural network is proposed to maintain the PTE at a reasonable level. To validate and test the performance of the proposed method, a WPT automatic impedance matching simulation system is implemented. Moreover, a prototype based on the proposed method is built and dynamic matching experiments were performed. The simulation results show that the algorithm efficiency of the proposed BP method is 108.5% higher than that of the genetic algorithm. The experimental results show that the PTE is improved up to 78.33% and this is closely maintained within a distance of 10-30 cm, which is consistent with the simulation result.
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工程Wireless Power Transfer Systems
Advanced DC-DC Converters · Induction Heating and Inverter Technology
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