Dynamic Programming Resolution and Database Knowledge for Online Predictive Energy Management of Hybrid Vehicles

Rustem Abdrakhmanov, Lounis Adouane

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 DP, 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.

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Paper Citation


in Harvard Style

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, pages 132-143. DOI: 10.5220/0006437301320143


in Bibtex Style

@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},
}


in EndNote Style

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
AU - Abdrakhmanov R.
AU - Adouane L.
PY - 2017
SP - 132
EP - 143
DO - 10.5220/0006437301320143