HUSCAP logo Hokkaido Univ. logo

Hokkaido University Collection of Scholarly and Academic Papers >
Graduate School of Information Science and Technology / Faculty of Information Science and Technology >
Peer-reviewed Journal Articles, etc >

Prediction of Current-Dependent Motor Torque Characteristics Using Deep Learning for Topology Optimization

Files in This Item:
COMPUMAG_aoyagi_fullpaper_final.pdf1.4 MBPDFView/Open
Please use this identifier to cite or link to this item:http://hdl.handle.net/2115/87028

Title: Prediction of Current-Dependent Motor Torque Characteristics Using Deep Learning for Topology Optimization
Authors: Aoyagi, Taiga Browse this author
Otomo, Yoshitsugu Browse this author
Igarashi, Hajime Browse this author →KAKEN DB
Sasaki, Hidenori Browse this author
Hidaka, Yuki Browse this author
Arita, Hideaki Browse this author
Keywords: Convolutional neural networks
CNNs
deep learning
DL
permanent magnet motor
topology optimization
TO
Issue Date: Sep-2022
Journal Title: IEEE Transactions on Magnetics
Volume: 58
Issue: 9
Start Page: 1
End Page: 4
Publisher DOI: 10.1109/TMAG.2022.3167254
Abstract: In this study, we propose a fast topology optimization (TO) method based on a deep neural network (DNN) that predicts the current-dependent motor torque characteristics using its cross-sectional image. The trained DNN is shown to provide the current condition that provides the maximum torque under the assumed motor control method. The proposed method helps perform TO with a reduced number of field computations while maintaining a high search capability.
Rights: © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Type: article (author version)
URI: http://hdl.handle.net/2115/87028
Appears in Collections:情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

Submitter: 五十嵐 一

Export metadata:

OAI-PMH ( junii2 , jpcoar_1.0 )

MathJax is now OFF:


 

 - Hokkaido University