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A Deep Neural Network-based Estimation of Efficiency Enhancement by an Intermediate Coil in Automotive Wireless Power Transfer System

Authors :
Joungho Kim
HyunWook Park
Seongsoo Lee
Daehwan Lho
Boogyo Sim
Hyungmin Kang
Seungtaek Jeong
Dongryul Park
Seokwoo Hong
Hongseok Kim
Source :
2020 IEEE Wireless Power Transfer Conference (WPTC).
Publication Year :
2020
Publisher :
IEEE, 2020.

Abstract

In this paper, we proposed a deep neural network (DNN)-based estimation of efficiency enhancement by an intermediate (Int) coil in automotive wireless power transfer (WPT) system. The Int coil can enhance the efficiency in the WPT system with the proper resonant frequency of the Int coil. The previous study has explained the resonant frequency of the Int coil should be higher than the operating frequency. According to the resonant frequency of the Int coil, we can achieve the amount of efficiency enhancement. Therefore, the design of the Int coil is essential for optimize the efficiency enhancement of the automotive WPT system. However, it is impossible to achieve the optimize results of efficiency enhancement by simulations. The proposed DNN-based estimation method can predict the amount of the efficiency enhancement in real cases consisted of ferrites and shielding structures.

Details

Database :
OpenAIRE
Journal :
2020 IEEE Wireless Power Transfer Conference (WPTC)
Accession number :
edsair.doi...........a9deb836878f49d487cad22514a9a232