Smart Real-time Control for Railway Systems Considering Energy Efficiency and Quality of Transportation

2021 Fiscal Year Final Research Report

• Project/Area Number: 19K04458
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 21040:Control and system engineering-related
• Research Institution: Sophia University
• Principal Investigator: MIYATAKE Masafumi 上智大学, 理工学部, 教授 (30318216)
• Co-Investigator(Kenkyū-buntansha): 荒井 幸代 千葉大学, 大学院工学研究院, 教授 (10372575) ; 近藤 圭一郎 早稲田大学, 理工学術院, 教授 (10425895)
• Project Period (FY): 2019-04-01 – 2022-03-31
• Keywords: 電気鉄道 / 省エネルギー / 輸送サービス / 知的制御 / 強化学習

Outline of Final Research Achievements

Researchers in mechanical and electrical engineering, who have a good understanding of physical phenomena, and researchers in the field of information engineering, who are newly incorporating artificial intelligence into control, have collaborated in this research. As a result, we achieve a high level of energy conservation and passenger service in railway systems by applying artificial intelligence technology with proper consideration of physical phenomena. Specifically, the most significant achievement was developing a new control method using reinforcement learning, its application to the control of power equipment in ground facilities, and the demonstration of its quantitative effectiveness. In addition, we also continued to study the development of more in-depth ground and on-vehicle circuit models, etc., to achieve more precise control and effect evaluation for a more accurate evaluation of energy-saving effects.

Free Research Field

電力変換制御

Academic Significance and Societal Importance of the Research Achievements

カーボンニュートラル社会のモビリティに鉄道の利用拡大は欠かせないが，鉄道自体の省エネルギー化も強力に推し進めなくてはならない。本研究課題では，物理モデルに基づいた電気鉄道の車両や蓄電装置等の知的設計制御手法の開発を行った。この成果により，少ない設備投資金額で，鉄道の輸送サービスの質を保ちながら省エネルギーを実現できるようになる。今後の我が国の鉄道業界の発展や国際展開に寄与することが期待される。