Angle Prediction for Field Orientation Based on Back Propagation Neural Network of Wireless Power Transfer System

被引：1

作者：

Xu, Jianxin ^{[1
]}

Tan, Pingan ^{[1
]}

Shen, Hang ^{[1
]}

Zhang, Hao ^{[1
]}

Pang, Lisheng ^{[2
]}

Deng, Yimeng ^{[1
]}

机构：

[1] Xiangtan Univ, Sch Automat & Elect Informat, Xiangtan 411105, Peoples R China

[2] Zhongshan Done Lighting Technol Co Ltd, Zhongshan 528400, Peoples R China

来源：

2020 IEEE 9TH INTERNATIONAL POWER ELECTRONICS AND MOTION CONTROL CONFERENCE (IPEMC2020-ECCE ASIA) | 2020年

关键词：

wireless power transfer(WPT); BP neural network; Location prediction;

D O I：

10.1109/IPEMC-ECCEAsia48364.2020.9367945

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In an omnidirectional wireless power transfer (WPT) system, the technology of field orientation is seen as a new method to raise transfer efficiency and the angle change of receiving coil is the major constraint of field orientation in the system. At present, it is no method to accurately predict the angle of receiving coil. This paper proposes an angle prediction method based on back propagation neural network to address the problem of low prediction accuracy. This method can accurately predict the angle and has a better generalization ability. The proposed method is verified by simulation, and experimental results.

引用

页码：1947 / 1951

页数：5

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