Hybrid Vehicle Control and Optimization with a New Mathematical Method

Nariaki Tateiwa, Nozomi Hata, Akira Tanaka, Takashi Nakayama, Akihiro Yoshida, Takashi Wakamatsu, Katsuki Fujisawa

Research output: Contribution to journalConference articlepeer-review

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.

Original languageEnglish
Pages (from-to)201-206
Number of pages6
JournalIFAC-PapersOnLine
Volume51
Issue number31
DOIs
Publication statusPublished - 2018
Event5th IFAC Conference on Engine and Powertrain Control, Simulation and Modeling, E-COSM 2018 - Changchun, China
Duration: Sep 20 2018Sep 22 2018

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

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