TY - JOUR
T1 - Hybrid Vehicle Control and Optimization with a New Mathematical Method
AU - Tateiwa, Nariaki
AU - Hata, Nozomi
AU - Tanaka, Akira
AU - Nakayama, Takashi
AU - Yoshida, Akihiro
AU - Wakamatsu, Takashi
AU - Fujisawa, Katsuki
N1 - Funding Information:
Our research was mainly supported by Toyota Motor Corporation, the Japan Science and Technology Agency (JST), Core Research of Evolutionary Science and Technology (CREST), and JSPS KAKENHI, Grant No. JP 16H01707.
Publisher Copyright:
© 2018
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
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U2 - 10.1016/j.ifacol.2018.10.037
DO - 10.1016/j.ifacol.2018.10.037
M3 - Conference article
AN - SCOPUS:85056162561
SN - 2405-8963
VL - 51
SP - 201
EP - 206
JO - IFAC-PapersOnLine
JF - IFAC-PapersOnLine
IS - 31
T2 - 5th IFAC Conference on Engine and Powertrain Control, Simulation and Modeling, E-COSM 2018
Y2 - 20 September 2018 through 22 September 2018
ER -