Shape Optimization of Rotor in Interior Permanent Magnet Motor Based on Topology OptimizationMethod Using Normalized Gaussian Network
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- Sato Takahiro
- Graduate School of Information Science and Technology, Hokkaido University
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- Igarashi Hajime
- Graduate School of Information Science and Technology, Hokkaido University
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- Takahashi Shinya
- Meidensha Corporation
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- Uchiyama Syo
- Meidensha Corporation
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- Matsuo Keisuke
- Meidensha Corporation
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- Matsuhashi Daiki
- Meidensha Corporation
Bibliographic Information
- Other Title
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- トポロジー最適化による埋込磁石同期モータの回転子形状最適化
- トポロジー サイテキ カ ニ ヨル ウメコミ ジシャク ドウキ モータ ノ カイテンシ ケイジョウ サイテキ カ
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Abstract
This paper presents a new topology optimization method based on normalized Gaussian network (NGnet). In this method, the machine region is subdivided into small elements whose material states are determined from the output of NGnet so that the objective function is extremized under the given constraints. The present method is applied to shape optimization of the rotor in an interior permanent magnet motor. The rotor shape is optimized to minimize the torque ripple while keeping the average torque. It is shown that the optimization halves the torque ripple while the average torque remains unchanged. This result was validated through a comparison between the computed and measured torques.
Journal
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- IEEJ Transactions on Industry Applications
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IEEJ Transactions on Industry Applications 135 (3), 291-298, 2015
The Institute of Electrical Engineers of Japan
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Details 詳細情報について
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- CRID
- 1390282679635074432
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- NII Article ID
- 130004876902
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- NII Book ID
- AN10012320
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- ISSN
- 13488163
- 09136339
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- NDL BIB ID
- 026245758
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed