Seamless Shifting of 2-speed Transmission for EV by Machine Learning
機械学習によるEV用2段速変速トランスミッションのシームレス変速
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- Publication code
- 20214588
- Paper/Info type
- JSAE Transaction
Vol.52 No.4
- Pages
- 857-862(Total 6 p)
- Date of publication
- Jul 2021
- Publisher
- JSAE
- Language
- Japanese
Detailed Information
| Category(J) | 研究論文 Translation |
|---|---|
| Category(E) | ResearchPaper |
| Author(J) | 1) 小川 和樹, 2) 相原 建人 |
| Author(E) | 1) Kazuki Ogawa, 2) Tatsuhito Aihara |
| Affiliation(J) | 1) 法政大学大学院, 2) 法政大学 |
| Abstract(J) | 機械学習は人間が行う高度な知的処理を代替できるため，様々な応用先が探索されている．本研究では機械学習をEV用２段速トランスミッションの変速制御に適用することを目的とした．シミュレーション上で学習モデルを作成し繰り返し学習をした結果，シームレス変速を実現する制御ルールを自動で獲得できた． Translation |
| Abstract(E) | This research aims to apply the deep reinforcement learning to the shift control of the EV two-speed transmission， develops a model for learning the shift control, and performs iterative learning to realize a seamless shift control. First， theoretical formulae are constructed to clarify the input-output relationship of the transmission. Next, it is confirmed that seamless shift control is possible based on the theoretical formula constructed. After that, a deep reinforcement learning models aiming at seamless shift control are developed, and the usefulness is verified by comparing the shift result after learning and the shift result based on the theoretical formulae. |
