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

被引：0
|
作者：
Sim, Boogyo [1 ]
Lho, Daehwan [2 ]
Park, Dongryul [3 ]
Jeong, Seungtaek [2 ]
Lee, Seongsoo [2 ]
Kim, Hongseok [4 ]
Park, Hyunwook [2 ]
Kang, Hyungmin [2 ]
Hong, Seokwoo [2 ]
Kim, Joungho [2 ]
Shik, Cho Chun [3 ]
机构：
[1] Korea Adv Inst Sci & Technol KAIST, Sch Elect Engn, Daejeon, South Korea
[2] Korea Adv Inst Sci & Technol, Sch Elect Engn, Daejeon, South Korea
[3] Korea Adv Inst Sci & Technol, Grad Sch Green Transportat, Daejeon, South Korea
[4] Missouri Univ Sci & Technol MST, Rolla, MO USA
来源：
2020 IEEE WIRELESS POWER TRANSFER CONFERENCE (WPTC) | 2020年
关键词：
Automotive; Deep neural network; Efficiency; Intermediate coil; Wireless power transfer system;
D O I：
10.1109/wptc48563.2020.9295620
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
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.
引用
收藏
页码：231 / 233
页数：3
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