Estimation Technique of Differential Pressure–Flow Characteristics of Shock Absorber Valves Based on Machine Learning
機械学習を用いたショックアブソーバ用ピストンバルブの差圧-流量特性の予測手法
- Delivery
- Available on this site
- Format
- Price
- Non-members (tax incl.)：￥1,100 Members (tax incl.)：￥880
- Publication code
- 20266334
- Paper/Info type
- Proceedings (Autumn)
No.162-26
- Pages
- 1-4(Total 4 p)
- Date of publication
- Oct 2026
- Publisher
- JSAE
- Language
- Japanese
- Event
- 2026 JSAE Annual Congress (Autumn)
Detailed Information
| Author(J) | 1) 加藤 大人, 2) 呂 鵬, 3) 柱山 健二, 4) 原田 脩史 |
|---|---|
| Author(E) | 1) Haruhito Kato, 2) Peng Lyu, 3) Kenji Hashirayama, 4) Naofumi Harada |
| Affiliation(J) | 1) Astemo, 2) Astemo, 3) Astemo, 4) Astemo |
| Affiliation(E) | 1) Astemo, 2) Astemo, 3) Astemo, 4) Astemo |
| Abstract(J) | ショックアブソーバの初期設計では，搭載するピストンバルブの差圧-流量特性の推定が必要である．この特性はバルブ形状に依存するため，一般的な物理計算に基づく推定では，精度と計算時間の両立が難しい．この問題に対し，本研究では，機械学習を用いる方法を開発し，短時間で精度よく推定できることを確認した． Translation |
| Abstract(E) | In the early design phase of shock absorbers, it is necessary to obtain the differential pressure–flow characteristics of the valves. The characteristics are generally estimated using computer simulations. It is difficult to increase both estimation accuracy and computational efficiency since the characteristics depend on valve geometry. In this paper, we develop the machine-learning-based estimation technique that is able to address the practical problem. |
