Development of Modeling Method for the Self Switchable Hydromount by Machine Learning
機械学習を用いた自立切替式液封マウントのモデル化技術開発
- Delivery
- Available on the other site
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- Publication code
- 20214199
- Paper/Info type
- JSAE Transaction
Vol.52 No.2
- Pages
- 475-479(Total 5 p)
- Date of publication
- Mar 2021
- Publisher
- JSAE
- Language
- Japanese
Detailed Information
Category(J) | 技術論文 Translation |
---|---|
Category(E) | TechnicalPaper |
Author(J) | 1) 中津川 英治, 2) 山下 誠二, 3) 堂上 靖史, 4) 伊藤 友文, 5) 森田 英憲, 6) Dirk Hoffmann, 7) Peter Mas |
Author(E) | 1) Eiji Nakatsugawa, 2) Seiji Yamashita, 3) Yasushi Dohnoue, 4) Tomofumi Itoh, 5) Hidenori Morita, 6) Dirk Hoffmann, 7) Peter Mas |
Affiliation(J) | 1) トヨタ自動車, 2) トヨタ自動車, 3) トヨタ自動車, 4) トヨタ自動車, 5) トヨタ自動車, 6) Siemens Industry Software S.A.S. Simcenter Engineering Services Div., 7) Siemens Industry Software S.A.S. Simcenter Engineering Services Div. |
Abstract(J) | 自立切り替え式液封マウントは振幅・周波数に依存する非線形な特性である為,モデルベース開発の時間軸計算に必要な等価力学系への置換えは困難である.そこで,マウントのばね・減衰の要求特性から機械学習によるモデル化手法を構築した.更に,その予測精度を検証し,1D-CAEに組み込んだ際の計算安定性を確認した. Translation |
Abstract(E) | We present a modeling method for self switchable hydromount from the specification of spring and damping by using machine learning. This is because this component has a non-linear characteristic depending on amplitude and frequency, so it is difficult to substitute to the equivalent dynamics system which is generally performed in the time series calculations at the model-based development. We confirmed the model’s prediction accuracy and also inspected the calculation stability when it is incorporated in 1D-CAE. |