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Authors: Kurt Kruppok 1 ; Tobias Walter 1 ; Reiner Kriesten 1 and Eric Sax 2

Affiliations: 1 University of Applied Sciences, Germany ; 2 Karlsruhe Institute of Technology (KIT), Germany

ISBN: 978-989-758-293-6

Keyword(s): Electric Vehicle, Driver Behaviour Prediction, Energy Demand Estimation, Driver Properties.

Abstract: Due to the battery's limited storage capacity, it is important to reduce energy consumption of electric vehicles. Depending on the average speed, an aggressive driving behaviour can result in an up to 40% higher energy consumption compared to an economic one. In this work, we propose a methodology, which calculates driver parameters based on measured real drive speed and acceleration profiles as well as signposted speed limits. The presented approach compares the energy consumption and driver parameters between our past estimation and the real drive speed profile in order to continuously improve the energy demand estimation for the remaining distance. Thus, this paper provides a procedure to increase the accuracy of energy demand estimation for battery electric vehicles which helps to reduce the range anxiety. In future work, it will be used within a navigation assistance system that supports the driver in reaching his destination with a low battery charge.

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Paper citation in several formats:
Kruppok, K.; Walter, T.; Kriesten, R. and Sax, E. (2018). Improving Range Prediction of Battery Electric Vehicles by Periodical Calculation of Driver Parameters based on Real Driving Data.In Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS, ISBN 978-989-758-293-6, pages 349-356. DOI: 10.5220/0006696103490356

@conference{vehits18,
author={Kurt Kruppok. and Tobias Walter. and Reiner Kriesten. and Eric Sax.},
title={Improving Range Prediction of Battery Electric Vehicles by Periodical Calculation of Driver Parameters based on Real Driving Data},
booktitle={Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,},
year={2018},
pages={349-356},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006696103490356},
isbn={978-989-758-293-6},
}

TY - CONF

JO - Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,
TI - Improving Range Prediction of Battery Electric Vehicles by Periodical Calculation of Driver Parameters based on Real Driving Data
SN - 978-989-758-293-6
AU - Kruppok, K.
AU - Walter, T.
AU - Kriesten, R.
AU - Sax, E.
PY - 2018
SP - 349
EP - 356
DO - 10.5220/0006696103490356

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