Precise Modeling of the Self-Inductance of Circular Coils with Deep Neural Networks

Yue Wu; Yongbin Jiang; Yaohua Li; Chang Wang; Min Wu; Ning Wang; Xiaohua Wang; Yi Tang

doi:10.1109/IECON51785.2023.10311693

Precise Modeling of the Self-Inductance of Circular Coils with Deep Neural Networks

Yue Wu
, Yongbin Jiang
, Yaohua Li
, Chang Wang
, Min Wu
, Ning Wang
, Xiaohua Wang
, Yi Tang

Xi'an Jiaotong University
Nanyang Technological University
Aalborg University

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Abstract

The circular coil is extensively employed in different wireless power transfer (WPT) applications due to its simple structure and satisfactory magnetic coupling capabilities. Different analytical models have been proposed to calculate the inductance of circular coils and some of them have achieved relatively high accuracies for coreless circular coils. However, the influence of ferrite plates is not fully considered in these studies, thus limiting their application potential. Therefore, a new analytical model and practical calculation method of circular coil's inductance are proposed in this paper. First, the parametric structure model for circular coils is derived, and the analytical inductance model is proposed based on Neumann's Formula. Second, the image current method is adopted to calculate the inductances of circular coils when ferrite plates are added to WPT systems. Then, a new Feedforward Neural Netweork (FNN) model is designed and trained to improve the computation accuracy of the proposed analytical inductance model for different circular coils in WPT systems. The proposed model exhibits exceptional precision and stability, which makes it promising in coil designing and optimization for diverse applications.

Original language	English
Title of host publication	Proceedings of 49^th Annual Conference of the IEEE Industrial Electronics Society
Number of pages	7
Publisher	IEEE
Publication date	2023
ISBN (Print)	979-8-3503-3183-7
DOIs	https://doi.org/10.1109/IECON51785.2023.10311693
Publication status	Published - 2023
Event	49th Annual Conference of the IEEE Industrial Electronics Society - Singapore, Singapore Duration: 16 Oct 2023 → 19 Oct 2023 Conference number: 49

Conference

Conference	49th Annual Conference of the IEEE Industrial Electronics Society
Number	49
Country/Territory	Singapore
City	Singapore
Period	16/10/2023 → 19/10/2023

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@inproceedings{491645d704034ff4892f2518153f68ad,

title = "Precise Modeling of the Self-Inductance of Circular Coils with Deep Neural Networks",

abstract = "The circular coil is extensively employed in different wireless power transfer (WPT) applications due to its simple structure and satisfactory magnetic coupling capabilities. Different analytical models have been proposed to calculate the inductance of circular coils and some of them have achieved relatively high accuracies for coreless circular coils. However, the influence of ferrite plates is not fully considered in these studies, thus limiting their application potential. Therefore, a new analytical model and practical calculation method of circular coil's inductance are proposed in this paper. First, the parametric structure model for circular coils is derived, and the analytical inductance model is proposed based on Neumann's Formula. Second, the image current method is adopted to calculate the inductances of circular coils when ferrite plates are added to WPT systems. Then, a new Feedforward Neural Netweork (FNN) model is designed and trained to improve the computation accuracy of the proposed analytical inductance model for different circular coils in WPT systems. The proposed model exhibits exceptional precision and stability, which makes it promising in coil designing and optimization for diverse applications.",

author = "Yue Wu and Yongbin Jiang and Yaohua Li and Chang Wang and Min Wu and Ning Wang and Xiaohua Wang and Yi Tang",

year = "2023",

doi = "10.1109/IECON51785.2023.10311693",

language = "English",

isbn = "979-8-3503-3183-7",

booktitle = "Proceedings of 49th Annual Conference of the IEEE Industrial Electronics Society",

publisher = "IEEE",

address = "United States",

note = "49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023 ; Conference date: 16-10-2023 Through 19-10-2023",

}

Wu, Y, Jiang, Y, Li, Y, Wang, C, Wu, M, Wang, N, Wang, X & Tang, Y 2023, Precise Modeling of the Self-Inductance of Circular Coils with Deep Neural Networks. in Proceedings of 49^th Annual Conference of the IEEE Industrial Electronics Society. IEEE, 49th Annual Conference of the IEEE Industrial Electronics Society, Singapore, Singapore, 16/10/2023. https://doi.org/10.1109/IECON51785.2023.10311693

TY - GEN

T1 - Precise Modeling of the Self-Inductance of Circular Coils with Deep Neural Networks

AU - Wu, Yue

AU - Jiang, Yongbin

AU - Li, Yaohua

AU - Wang, Chang

AU - Wu, Min

AU - Wang, Ning

AU - Wang, Xiaohua

AU - Tang, Yi

N1 - Conference code: 49

PY - 2023

Y1 - 2023

N2 - The circular coil is extensively employed in different wireless power transfer (WPT) applications due to its simple structure and satisfactory magnetic coupling capabilities. Different analytical models have been proposed to calculate the inductance of circular coils and some of them have achieved relatively high accuracies for coreless circular coils. However, the influence of ferrite plates is not fully considered in these studies, thus limiting their application potential. Therefore, a new analytical model and practical calculation method of circular coil's inductance are proposed in this paper. First, the parametric structure model for circular coils is derived, and the analytical inductance model is proposed based on Neumann's Formula. Second, the image current method is adopted to calculate the inductances of circular coils when ferrite plates are added to WPT systems. Then, a new Feedforward Neural Netweork (FNN) model is designed and trained to improve the computation accuracy of the proposed analytical inductance model for different circular coils in WPT systems. The proposed model exhibits exceptional precision and stability, which makes it promising in coil designing and optimization for diverse applications.

AB - The circular coil is extensively employed in different wireless power transfer (WPT) applications due to its simple structure and satisfactory magnetic coupling capabilities. Different analytical models have been proposed to calculate the inductance of circular coils and some of them have achieved relatively high accuracies for coreless circular coils. However, the influence of ferrite plates is not fully considered in these studies, thus limiting their application potential. Therefore, a new analytical model and practical calculation method of circular coil's inductance are proposed in this paper. First, the parametric structure model for circular coils is derived, and the analytical inductance model is proposed based on Neumann's Formula. Second, the image current method is adopted to calculate the inductances of circular coils when ferrite plates are added to WPT systems. Then, a new Feedforward Neural Netweork (FNN) model is designed and trained to improve the computation accuracy of the proposed analytical inductance model for different circular coils in WPT systems. The proposed model exhibits exceptional precision and stability, which makes it promising in coil designing and optimization for diverse applications.

U2 - 10.1109/IECON51785.2023.10311693

DO - 10.1109/IECON51785.2023.10311693

M3 - Article in proceedings

SN - 979-8-3503-3183-7

BT - Proceedings of 49th Annual Conference of the IEEE Industrial Electronics Society

PB - IEEE

T2 - 49th Annual Conference of the IEEE Industrial Electronics Society

Y2 - 16 October 2023 through 19 October 2023

ER -

Precise Modeling of the Self-Inductance of Circular Coils with Deep Neural Networks

Abstract

Conference

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