Feature-based Analysis of the Energy Consumption of Battery Electric Vehicles

Patrick Petersen, Aya Khdar, Eric Sax

Abstract

Battery electric vehicles have become increasingly important for the reduction of greenhouse gas emission. Even though the number of battery electric vehicles is increasing, the general acceptance and widespread introduction to consumers is still related to smaller range, which is in part due to the range anxiety leading to inefficient usage of the complete battery. Thus, an accurate range estimation is a key parameter for increasing the trust in the promised range, but accurate estimation is a nontrivial task. Advanced algorithms estimate the energy consumption based on the travel route and other non-deterministic factors such as driving style, traffic and weather conditions. The possible feature space is huge, therefore, the identification of a few highly energy consumption relevant features is necessary due to time and memory limitations in the vehicle including the improvement of the estimation itself. In this paper we present a data-driven methodology for systematically analyzing and engineering relevant features which influence the energy consumption concurrently, covering not only the driver style but also features based on road topology, traffic and weather conditions. Utilizing a real-world data set different trip segmentation methods and feature selection algorithms are compared to each other in regards to their accuracy and time-efficiency.

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Paper Citation


in Harvard Style

Petersen P., Khdar A. and Sax E. (2021). Feature-based Analysis of the Energy Consumption of Battery Electric Vehicles. In Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS, ISBN 978-989-758-513-5, pages 223-234. DOI: 10.5220/0010482802230234


in Bibtex Style

@conference{vehits21,
author={Patrick Petersen and Aya Khdar and Eric Sax},
title={Feature-based Analysis of the Energy Consumption of Battery Electric Vehicles},
booktitle={Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,},
year={2021},
pages={223-234},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010482802230234},
isbn={978-989-758-513-5},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,
TI - Feature-based Analysis of the Energy Consumption of Battery Electric Vehicles
SN - 978-989-758-513-5
AU - Petersen P.
AU - Khdar A.
AU - Sax E.
PY - 2021
SP - 223
EP - 234
DO - 10.5220/0010482802230234