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Energy Demand Prediction in Hybrid Electrical Vehicles for Speed Optimization

Topics: Analytics and Optimization; Analytics for Intelligent Transportation; Automotive Control and Mechatronics; Autonomous Vehicles and Automated Driving; City Mobility and Ecodriving; Information Systems and Technologies; Intelligent Infrastructure and Guidance Systems; Navigation Systems; Systems Modeling and Simulation; Vehicle Information Systems

Authors: Daniel Fink 1 ; Sean Shugar 1 ; Zygimantas Ziaukas 1 ; Christoph Schweers 2 ; Ahmed Trabelsi 2 and Hans-Georg Jacob 1

Affiliations: 1 Leibniz University Hannover, Institute of Mechatronic Systems, An der Universität 1, Garbsen, Germany ; 2 IAV GmbH, Berlin, Germany

Keyword(s): Systems Modeling, Energy Demand Prediction.

Abstract: Targeting a resource-efficient automotive traffic, modern driver assistance systems include speed optimization algorithms to minimize the vehicle’s energy demand, based on predictive route data. Within these algorithms, the required energy for upcoming operation points has to be determined. This paper presents a model-based approach, to predict the energy demand of a parallel hybrid electrical vehicle, which is suitable to be used in speed optimization algorithms. It relies on separate models for the individual power train components, and is identified for a real test vehicle. On route sections of 5 to 7 km the averaged root mean square error for the state of charge prediction results to 0.91% while the required amount of fuel can be predicted with an averaged root mean square error of 0.05 liters.

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Paper citation in several formats:
Fink, D.; Shugar, S.; Ziaukas, Z.; Schweers, C.; Trabelsi, A. and Jacob, H. (2022). Energy Demand Prediction in Hybrid Electrical Vehicles for Speed Optimization. In Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS; ISBN 978-989-758-573-9; ISSN 2184-495X, SciTePress, pages 116-123. DOI: 10.5220/0011075600003191

@conference{vehits22,
author={Daniel Fink. and Sean Shugar. and Zygimantas Ziaukas. and Christoph Schweers. and Ahmed Trabelsi. and Hans{-}Georg Jacob.},
title={Energy Demand Prediction in Hybrid Electrical Vehicles for Speed Optimization},
booktitle={Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS},
year={2022},
pages={116-123},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011075600003191},
isbn={978-989-758-573-9},
issn={2184-495X},
}

TY - CONF

JO - Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS
TI - Energy Demand Prediction in Hybrid Electrical Vehicles for Speed Optimization
SN - 978-989-758-573-9
IS - 2184-495X
AU - Fink, D.
AU - Shugar, S.
AU - Ziaukas, Z.
AU - Schweers, C.
AU - Trabelsi, A.
AU - Jacob, H.
PY - 2022
SP - 116
EP - 123
DO - 10.5220/0011075600003191
PB - SciTePress

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