Fuel consumption optimization for a power-split HEV via gain-scheduled model predictive control

Hitoshi Iyama; Toru Namerikawa

doi:10.1109/SICE.2014.6935205

Fuel consumption optimization for a power-split HEV via gain-scheduled model predictive control

Hitoshi Iyama, Toru Namerikawa

Department of System Design Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

In this paper, we propose a fuel consumption optimization technique for a power-split hybrid electric vehicle (HEV) via gain-scheduled model predictive control. The control algorithms for the hybrid powertrain choose the power split between the internal combustion engine and electric motor of the HEV in order to minimize the fuel consumption. The operating conditions of the HEV change during driving in real time by road conditions and driver demand. Therefore, it is necessary to have optimal control in real time and to consider the time-varying motor condition. We model an HEV and propose a gain-scheduled model predictive control for a power-split HEV. Using the proposed technique, the optimal fuel consumption for a power-split HEV is achieved. Finally, the proposed approach is validated by numerical simulations.

Original language	English
Title of host publication	Proceedings of the SICE Annual Conference
Publisher	Society of Instrument and Control Engineers (SICE)
Pages	468-473
Number of pages	6
ISBN (Electronic)	9784907764463
DOIs	https://doi.org/10.1109/SICE.2014.6935205
Publication status	Published - 2014 Oct 23
Event	2014 53rd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2014 - Sapporo, Japan Duration: 2014 Sept 9 → 2014 Sept 12

Publication series

Name	Proceedings of the SICE Annual Conference

Other

Other	2014 53rd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2014
Country/Territory	Japan
City	Sapporo
Period	14/9/9 → 14/9/12

Keywords

Gain-Scheduled Model Predictive Control
Hybrid Electric Vehicle
Optimal Control

ASJC Scopus subject areas

Control and Systems Engineering
Computer Science Applications
Electrical and Electronic Engineering

Access to Document

10.1109/SICE.2014.6935205

Cite this

Fuel consumption optimization for a power-split HEV via gain-scheduled model predictive control. / Iyama, Hitoshi; Namerikawa, Toru.
Proceedings of the SICE Annual Conference. Society of Instrument and Control Engineers (SICE), 2014. p. 468-473 6935205 (Proceedings of the SICE Annual Conference).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Iyama, H & Namerikawa, T 2014, Fuel consumption optimization for a power-split HEV via gain-scheduled model predictive control. in Proceedings of the SICE Annual Conference., 6935205, Proceedings of the SICE Annual Conference, Society of Instrument and Control Engineers (SICE), pp. 468-473, 2014 53rd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2014, Sapporo, Japan, 14/9/9. https://doi.org/10.1109/SICE.2014.6935205

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abstract = "In this paper, we propose a fuel consumption optimization technique for a power-split hybrid electric vehicle (HEV) via gain-scheduled model predictive control. The control algorithms for the hybrid powertrain choose the power split between the internal combustion engine and electric motor of the HEV in order to minimize the fuel consumption. The operating conditions of the HEV change during driving in real time by road conditions and driver demand. Therefore, it is necessary to have optimal control in real time and to consider the time-varying motor condition. We model an HEV and propose a gain-scheduled model predictive control for a power-split HEV. Using the proposed technique, the optimal fuel consumption for a power-split HEV is achieved. Finally, the proposed approach is validated by numerical simulations.",

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N2 - In this paper, we propose a fuel consumption optimization technique for a power-split hybrid electric vehicle (HEV) via gain-scheduled model predictive control. The control algorithms for the hybrid powertrain choose the power split between the internal combustion engine and electric motor of the HEV in order to minimize the fuel consumption. The operating conditions of the HEV change during driving in real time by road conditions and driver demand. Therefore, it is necessary to have optimal control in real time and to consider the time-varying motor condition. We model an HEV and propose a gain-scheduled model predictive control for a power-split HEV. Using the proposed technique, the optimal fuel consumption for a power-split HEV is achieved. Finally, the proposed approach is validated by numerical simulations.

AB - In this paper, we propose a fuel consumption optimization technique for a power-split hybrid electric vehicle (HEV) via gain-scheduled model predictive control. The control algorithms for the hybrid powertrain choose the power split between the internal combustion engine and electric motor of the HEV in order to minimize the fuel consumption. The operating conditions of the HEV change during driving in real time by road conditions and driver demand. Therefore, it is necessary to have optimal control in real time and to consider the time-varying motor condition. We model an HEV and propose a gain-scheduled model predictive control for a power-split HEV. Using the proposed technique, the optimal fuel consumption for a power-split HEV is achieved. Finally, the proposed approach is validated by numerical simulations.

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Fuel consumption optimization for a power-split HEV via gain-scheduled model predictive control

Abstract

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Keywords

ASJC Scopus subject areas

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