Performance Improvement of Magnet Temperature Estimation using Kernel Method based Non-Linear Parameter Estimator for Variable leakage flux IPMSMs

Atsushi Okada, Ami S. Koshikawa, Kouki Yonaga, Kensuke Sasaki, Takashi Kato, Masayuki Ohzeki

研究成果: Conference contribution

抄録

This paper proposes the novel approach employing the kernel method as regression model to describe the dependency of magnet flux linkage on applied current, which is suitable for magnet temperature estimation. The model estimates flux linkage values with mean relative error of less than 2% compared to values calculated from finite element analysis (FEA). Magnet temperature is estimated by comparing a magnet flux linkage under loaded condition to the values from the regression models built under fixed temperatures. Results of the magnet temperature estimation method is about the same accuracy of the results using look-up table (LUT), hence it suggests the approach is suitable for non-linear motor property modeling.

本文言語English
ホスト出版物のタイトル23rd International Conference on Electrical Machines and Systems, ICEMS 2020
出版社Institute of Electrical and Electronics Engineers Inc.
ページ1957-1960
ページ数4
ISBN(電子版)9784886864192
DOI
出版ステータスPublished - 2020 11 24
イベント23rd International Conference on Electrical Machines and Systems, ICEMS 2020 - Hamamatsu, Japan
継続期間: 2020 11 242020 11 27

出版物シリーズ

名前23rd International Conference on Electrical Machines and Systems, ICEMS 2020

Conference

Conference23rd International Conference on Electrical Machines and Systems, ICEMS 2020
国/地域Japan
CityHamamatsu
Period20/11/2420/11/27

ASJC Scopus subject areas

  • エネルギー工学および電力技術
  • 電子工学および電気工学
  • 機械工学
  • 安全性、リスク、信頼性、品質管理
  • 制御と最適化

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