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Authors: Rustem Abdrakhmanov and Lounis Adouane

Affiliation: Institut Pascal/IMobS3 and UCA/SIGMA, France

Keyword(s): Hybrid Electric Vehicle, Energy Management Strategy, Dynamic Programming, Online Sub-optimal Optimization, SOC Prediction, Multi-dimensional Database Knowledge.

Related Ontology Subjects/Areas/Topics: Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Intelligent Transportation Technologies and Systems ; Robotics and Automation ; Software Agents for Intelligent Control Systems

Abstract: This paper presents a sub-optimal strategy, based on Dynamic Programming (DP) approach, for online energy (electric battery and fuel) optimization of a Hybrid Electric Vehicle (HEV). An optimal offline optimization is first proposed in this work, permitting to have simultaneous speed profile optimization and optimal power split strategy of a series-parallel hybrid bus. The aim of this optimization is mainly to reduce the fuel and electrical energy consumption of the studied HEV while maintaining smooth bus navigation to ensure the passengers’ comfort. It is assumed in this first proposal that current road profile (slope, geometry, etc.) and the overall bus trip (time at the stations) are known in advance. Afterward, the basis of the offline optimal strategy has been adapted in order to deal online with the current road profile and driver velocity demand. The proposed sub-optimal online strategy uses mainly an appropriate speed profile and power-split database, obtained offline with D P, in order to cope with the current bus situations, and this is carried out by using a multi-dimensional interpolation method. The present work is conducted on a dedicated high-fidelity model of the hybrid bus that was developed on MATLAB/TruckMaker software. (More)

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Paper citation in several formats:
Abdrakhmanov, R. and Adouane, L. (2017). Dynamic Programming Resolution and Database Knowledge for Online Predictive Energy Management of Hybrid Vehicles. In Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-989-758-263-9; ISSN 2184-2809, SciTePress, pages 132-143. DOI: 10.5220/0006437301320143

@conference{icinco17,
author={Rustem Abdrakhmanov. and Lounis Adouane.},
title={Dynamic Programming Resolution and Database Knowledge for Online Predictive Energy Management of Hybrid Vehicles},
booktitle={Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2017},
pages={132-143},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006437301320143},
isbn={978-989-758-263-9},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - Dynamic Programming Resolution and Database Knowledge for Online Predictive Energy Management of Hybrid Vehicles
SN - 978-989-758-263-9
IS - 2184-2809
AU - Abdrakhmanov, R.
AU - Adouane, L.
PY - 2017
SP - 132
EP - 143
DO - 10.5220/0006437301320143
PB - SciTePress