Energy Demand Prediction in Hybrid Electrical Vehicles for Speed Optimization

Daniel Fink, Sean Shugar, Zygimantas Ziaukas, Christoph Schweers, Ahmed Trabelsi, Hans-Georg Jacob

2022

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.

Paper Citation

in Harvard Style

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 - Volume 1: VEHITS, ISBN 978-989-758-573-9, pages 116-123. DOI: 10.5220/0011075600003191

in Bibtex Style

@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 - Volume 1: VEHITS,},
year={2022},
pages={116-123},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011075600003191},
isbn={978-989-758-573-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,
TI - Energy Demand Prediction in Hybrid Electrical Vehicles for Speed Optimization
SN - 978-989-758-573-9
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