Development of a Shape Optimization Framework Using AI-Based Shape Generation for Electric Water Pump Design and Its Practical Implementation Challenges
電動ウォーターポンプの形状設計を対象とした形状生成AI活用による最適化プロセスの構築と実務適用課題
- Delivery
- Available on this site
- Format
- Price
- Non-members (tax incl.)：￥1,100 Members (tax incl.)：￥880
- Publication code
- 20266065
- Paper/Info type
- Proceedings (Autumn)
No.105-26
- Pages
- 1-5(Total 5 p)
- Date of publication
- Oct 2026
- Publisher
- JSAE
- Language
- Japanese
- Event
- 2026 JSAE Annual Congress (Autumn)
Detailed Information
| Author(J) | 1) 茨木 優花, 2) 寺部 俊紀, 3) 北村 恭平, 4) 中井 祥平 |
|---|---|
| Author(E) | 1) Yuka Ibaraki, 2) Toshiki Terabe, 3) Kyohei Kitamura, 4) Shohei Nakai |
| Affiliation(J) | 1) アイシン, 2) トヨタ自動車, 3) アイシン, 4) アイシン |
| Affiliation(E) | 1) Aisin, 2) Toyota Motor, 3) Aisin, 4) Aisin |
| Abstract(J) | 電動ウォーターポンプを対象に，DeepSDFによる形状生成とサロゲートモデルを組み合わせた形状最適化手法を検討した．潜在変数と性能の関係を活用することで，新規形状の最適化と性能予測を実現した．本講演では，実務適用において顕在化した課題と今後の展望について報告する． Translation |
| Abstract(E) | A shape optimization method combining DeepSDF-based shape generation and surrogate modeling was investigated for an electric water pump. By leveraging the relationship between latent variables and performance, optimization and performance prediction of newly generated shapes were achieved. This report discusses the challenges identified during practical application, along with approaches to addressing these issues and future perspectives for improving the applicability of the method. |
