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

Authors :
Aoyagi, Taiga
Otomo, Yoshitsugu
Igarashi, Hajime
Sasaki, Hidenori
Hidaka, Yuki
Arita, Hideaki
Source :
IEEE Transactions on Magnetics; Sep2022, Vol. 58 Issue 9, p1-4, 4p
Publication Year :
2022

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00189464
Volume :
58
Issue :
9
Database :
Complementary Index
Journal :
IEEE Transactions on Magnetics
Publication Type :
Academic Journal
Accession number :
158869907
Full Text :
https://doi.org/10.1109/TMAG.2022.3167254