An Automatic Impedance Matching Method Based on the Feedforward-Backpropagation Neural Network for a WPT System

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.

[1]  A. Diaz-Mendez,et al.  An adaptive impedance matching approach based on fuzzy control , 2009, 2009 52nd IEEE International Midwest Symposium on Circuits and Systems.

[2]  Chun T. Rim,et al.  Advances in Wireless Power Transfer Systems for Roadway-Powered Electric Vehicles , 2015, IEEE Journal of Emerging and Selected Topics in Power Electronics.

[3]  O. A. Mohammed,et al.  Magnetic Design Considerations of Bidirectional Inductive Wireless Power Transfer System for EV Applications , 2016, IEEE Transactions on Magnetics.

[4]  Mingcong Deng,et al.  Tracking operator-based optimal load control for loosely coupled wireless power transfer systems , 2017, 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[5]  He Yin,et al.  Analysis and Tracking of Optimal Load in Wireless Power Transfer Systems , 2015, IEEE Transactions on Power Electronics.

[6]  S. Fan,et al.  Wireless energy transfer with the presence of metallic planes , 2011 .

[7]  M. Soljačić,et al.  Efficient wireless non-radiative mid-range energy transfer , 2006, physics/0611063.

[8]  Manos M. Tentzeris,et al.  A Real-Time Electrically Controlled Active Matching Circuit Utilizing Genetic Algorithms for Wireless Power Transfer to Biomedical Implants , 2016, IEEE Transactions on Microwave Theory and Techniques.

[9]  Hamid Jabbar,et al.  RF energy harvesting system and circuits for charging of mobile devices , 2010, IEEE Transactions on Consumer Electronics.

[10]  Joshua R. Smith,et al.  A Reconfigurable Resonant Coil for Range Adaptation Wireless Power Transfer , 2016, IEEE Transactions on Microwave Theory and Techniques.

[11]  Takehiro Imura,et al.  Automated Impedance Matching System for Robust Wireless Power Transfer via Magnetic Resonance Coupling , 2013, IEEE Transactions on Industrial Electronics.

[12]  Hao Jiang,et al.  A Low-Frequency Versatile Wireless Power Transfer Technology for Biomedical Implants , 2013, IEEE Transactions on Biomedical Circuits and Systems.

[13]  マチアス ウェクリン,et al.  Apparatus for transmitting electrical energy inductively , 2003 .

[14]  Qiang Zhao,et al.  Optimization of Multiresonant Wireless Power Transfer Network Based on Generalized Coupled Matrix , 2017 .

[15]  Tales Cleber Pimenta,et al.  Self-tuning capacitance for impedance matching in wireless power transfer devices , 2017, 2017 29th International Conference on Microelectronics (ICM).

[16]  Mahamod Ismail,et al.  Opportunities and Challenges for Near-Field Wireless Power Transfer: A Review , 2017 .

[17]  Alanson P. Sample,et al.  Enabling Seamless Wireless Power Delivery in Dynamic Environments , 2013, Proceedings of the IEEE.