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.

中文翻译：

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基于前馈-反向传播神经网络的WPT系统阻抗自动匹配方法


在通过耦合磁共振的无线电力传输（WPT）系统中，电力传输效率（PTE）随着传输距离或负载的变化而急剧下降。本文分析了效率下降的原因，并提出了一种基于前馈反向传播（BP）神经网络的自动阻抗匹配方法，以将PTE保持在合理的水平。为了验证和测试所提出方法的性能，实现了WPT自动阻抗匹配仿真系统。此外，基于该方法搭建了原型机并进行了动态匹配实验。仿真结果表明，所提BP方法的算法效率比遗传算法提高了108.5%。实验结果表明，PTE提高了78.33%，并且在10-30 cm的距离内保持良好，与模拟结果一致。