Hybrid Vehicle Control and Optimization with a New Mathematical Method. Issue 31 (2018)

• Record Type: Journal Article
• Authors: Tateiwa, Nariaki; Hata, Nozomi; Tanaka, Akira; Nakayama, Takashi; Yoshida, Akihiro; Wakamatsu, Takashi; Fujisawa, Katsuki
• Is Part Of: IFAC-PapersOnLine. Volume 51:Issue 31(2018)
• Page Start: 201
• Page End: 206
• Publication Date: 2018
• Subjects: Hybrid vehicles -- Graph theory -- Computer simulation -- Optimal control -- Function approximation -- Optimization problem; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2018.10.037
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: For hybrid electric vehicle (HEV) systems, studies using model-based simulators have been actively conducted. The vehicle powertrain simulator makes it easier to evaluate the powertrain system. In this paper, we utilize a Toyota Hybrid System (THS) simulator to obtain a long-term control that optimizes the fuel efficiency when the vehicle speed over a certain period is given. Our proposed method obtains optimal long-term control by solving the shortest path problem with state of charge (SOC) constraints after constructing a graph expressing the transition of the fuel and battery consumption. We also propose a search method for vehicle control using bicubic spline interpolation without the preparation of a controller. We finally remove almost all edges from a graph by 97.2% at most through the utilization of 0-1 integer linear programming, which enables a 3.88x speedup in obtaining the optimal vehicle control.