Electrothermal iterative learning control and optimization of electric vehicle operation

• Project/Area Number: 23K03906
• 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: Kyushu University
• Principal Investigator: Nguyen Hoa 九州大学, カーボンニュートラル・エネルギー国際研究所, 准教授 (00801086)
• Project Period (FY): 2023-04-01 – 2026-03-31
• Project Status: Granted (Fiscal Year 2023)
• Budget Amount: ¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000); Fiscal Year 2025: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000); Fiscal Year 2024: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000); Fiscal Year 2023: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
• Keywords: Battery dynamics / Electric vehicle / IILC / Optimization / Ancillary services

Outline of Research at the Start

EVs are being strongly developed worldwide to gradually substitute for gasoline
vehicles as an approach to combat the severe climate changes caused by greenhouse gas emissions. Technologies for EVs unfortunately have not been mature as that for gasoline alternates, hence requiring much more effort to increase their energy efficiency, economy, and charging convenience for users. This project exploits the repetition on the daily driving of a large class of EV users to develop novel iterative learning control methods for the better electricity and thermal control and management of EVs.