Nonlinear Vibration Response Modeling and Performance Prediction of Air Suspension Using Machine Learning
機械学習によるエアサスペンションの非線形振動応答のモデル化と性能予測
- Delivery
- Available on this site
- Format
- Price
- Non-members (tax incl.)：￥1,100 Members (tax incl.)：￥880
- Publication code
- 20266333
- Paper/Info type
- Proceedings (Autumn)
No.162-26
- Pages
- 1-2(Total 2 p)
- Date of publication
- Oct 2026
- Publisher
- JSAE
- Language
- Japanese
- Event
- 2026 JSAE Annual Congress (Autumn)
Detailed Information
| Author(J) | 1) 渥美 良宏, 2) 佐藤 恭一 |
|---|---|
| Author(E) | 1) Yoshihiro Atsumi, 2) Yasukazu Sato |
| Affiliation(J) | 1) 横浜国立大学, 2) 横浜国立大学 |
| Affiliation(E) | 1) Yokohama National University, 2) Yokohama National University |
| Abstract(J) | 機械学習を用いてエアサスペンションの非線形特性を表現する振動応答モデルを構築し，乗り心地性能を高精度に予測する手法を提案する．設計値および実験データに基づき非線形特性を静特性と動特性に分離してモデル化した．台上試験による検証に向けて予測精度をシミュレーションで評価し，本手法の有効性を確認した． Translation |
| Abstract(E) | A vibration response model incorporating the nonlinear characteristics of an air suspension is constructed using machine learning, and a method for accurately predicting ride comfort performance is proposed. The nonlinear characteristics are separated into static and dynamic components based on design specifications and experimental data. These components are then modeled. The prediction accuracy of the proposed method is evaluated through simulations in preparation for bench testing, and its effectiveness is demonstrated. |
