@inproceedings{a4ad152e739845b4900845ca7a06a6f5,
title = "Design to Minimize Coupling Coefficient between Transmitter Coils based on Deep Learning for Wireless Power Transfer with Multi-Transmitter",
abstract = "The wireless charging pad with multiple transmitter (TX) coils has the advantage of solving the misalignment problem, high efficiency, and low leakage magnetic field. However, since the multi-TX wireless power transfer(WPT) system has coupling coefficients between TX coils, kTX. It changes the resonance point of the TX and causes a problem in that efficiency and power delivered to the receiver are drastically reduced. This paper analyzes the effect of kTX according to the operation of the TX coils and proposes an arrangement method by Deep Learning model that makes kTX to zero. A learning model is constructed using Deep Neural Network, and the model can output the distance where kTX can become zero when the coil specification is input.",
keywords = "coil arrangement, coupling coefficient, deep learning, multiple transmitter, Wireless power transfer",
author = "Sungryul Huh and Semin Choi and Dongryul Park and Haerim Kim and Yujun Shin and Jedok Kim and Jung, \{Gu Ho\} and Hosani, \{Khalifa Al\} and Seungyoung Ahn",
note = "Funding Information: This research was supported by the KAIST-KU Joint Research Center, KAIST, South Korea(N11220031). And this work is supported by Khalifa University under Awards No. kkjrc-2019-trans 2. Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 Wireless Power Week, WPW 2022 ; Conference date: 05-07-2022 Through 08-07-2022",
year = "2022",
doi = "10.1109/WPW54272.2022.9853954",
language = "British English",
series = "2022 Wireless Power Week, WPW 2022 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "443--447",
booktitle = "2022 Wireless Power Week, WPW 2022 - Proceedings",
address = "United States",
}