A soft computing algorithmic technique for circuital analysis of a wireless mobile charger

Adedayo Olukayode Ojo, Oluwafemi Oladipupo Alegbeleye, Rashida Omowunmi Olomowewe


Wireless energy transfer is emerging as a promising technology for mobile devices because it enhances rapid charging without requiring conventional cables. In this paper, a wireless mobile charger circuit was designed and simulated, the data obtained thereof was used to train an artificial neural network (ANN) using Levenberg-Marquardt (LM) algorithm. The result obtained was validated against that obtained when trained with regular scaled conjugate algorithm. Analysis of the results showed that the proposed technique remains a viable technique for rapidly analyzing several parts of the wireless mobile charger circuit for design and educational purposes, without always executing computationally intensive and time-consuming simulations.


Artificial neural network; Levenberg-Marquardt algorithm; Wireless charging; Wireless energy transfer; Wireless rechargeable network

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DOI: http://doi.org/10.11591/ijai.v13.i2.pp1443-1449


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IAES International Journal of Artificial Intelligence (IJ-AI)
ISSN/e-ISSN 2089-4872/2252-8938 
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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