Research of the Optimization Methodology for the Advanced Powertrain Control. Issue 31 (2018)

• Record Type: Journal Article
• Authors: Kako, Junichi; Yoshida, Shozo; Tsunogawa, Hiroki; Shimizu, Rio
• Is Part Of: IFAC-PapersOnLine. Volume 51:Issue 31(2018)
• Page Start: 207
• Page End: 212
• Publication Date: 2018
• Subjects: Optimal control -- Optimization problem -- Power management -- Hybrid vehicles -- Models; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2018.10.038
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: Future vehicle powertrain system will be changed to electrification in order to be cleaner and lower fuel consumption. For the planning of such advanced powertrain system, we have to choose the best system from among many candidates expected by evaluating their potential correctly. It is necessary to make detailed controller for correct system evaluation. But it is very hard and time consuming. In this research, powertrain potential prediction methodology is proposed. With this methodology, it is possible to achieve best input time trace by optimization without any detailed controller.