A network-based approach for modeling resonant capacitive wireless power transfer systems

Eli Abramov, Ilya Zeltser, Mor Mordechai Peretz

Research output: Contribution to journalArticlepeer-review

19 Scopus citations


In this paper, a network-based approach to model capacitive wireless power transfer systems is introduced. The modeling methodology provides insights into the electrical cross-coupling relationships between input and output parameters of the capacitive power transfer (CPT) systems, including the effect of distance and alignment of the coupling plates. It is revealed that, regardless of the circuit complexity or matching network order, the model core can be reduced to a basic gyrator relationship with added coefficients when required, thus obtaining a compact, closed-form relationship between the input and output terminals. The model has been validated through rigorous simulations and experiments; all found to be in excellent agreement with the theoretical predictions under changes of the air-gap, and medium capacitance. To this end, an experimental CPT prototype that operates in the MHz range has been designed and implemented while the transmitter and receiver have been realized by four 170 mm × 170 mm copper plates. In addition, to provide better insight into the capacitive interface under different structures and distances and alignments, the capacitive coupler has been methodically examined through Finite Elements Analysis (FEA) tools Maxwell (Ansys). The results of the FEA have been utilized in the simulation platform to enhance the accuracy of the simulations, accounting for the variable capacitance under variations.

Original languageEnglish
Article number8681894
Pages (from-to)19-29
Number of pages11
JournalCPSS Transactions on Power Electronics and Applications
Issue number1
StatePublished - 1 Mar 2019


  • Behavioral modeling
  • Capacitive coupling
  • Capacitive power transfer
  • Gyrator
  • Matching networks
  • Two-port network

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Renewable Energy, Sustainability and the Environment
  • Control and Systems Engineering


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