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.
Recommended Citation
B. Sim and D. Lho and D. Park and S. Jeong and S. Lee and H. Kim and H. Park and H. Kang and S. Hong and J. Kim, "A Deep Neural Network-Based Estimation of Efficiency Enhancement by an Intermediate Coil in Automotive Wireless Power Transfer System," 2020 IEEE Wireless Power Transfer Conference, WPTC 2020, pp. 231 - 233, article no. 9295620, Institute of Electrical and Electronics Engineers, Nov 2020.
The definitive version is available at https://doi.org/10.1109/WPTC48563.2020.9295620
Department(s)
Electrical and Computer Engineering
Keywords and Phrases
Automotive; Deep neural network; Efficiency; Intermediate coil; Wireless power transfer system
International Standard Book Number (ISBN)
978-172814238-8
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
15 Nov 2020
