Title
Hybrid powertrain control with dynamic traffic prediction based on real-world V2X information
Date Issued
25 May 2021
Access level
metadata only access
Resource Type
conference paper
Author(s)
Deng J.
Adelberger D.
Universidad de Linz
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
Abstract
A priori information about the future traffic conditions along the planned route can be essential for optimal hybrid powertrain energy management. However, due to the limited sensor range of a single vehicle, it cannot be acquired locally. In recent time, V2X (decentralized wireless vehicle to everything) has been receiving much attention as a way to obtain and share information from different distributed sources. V2X data can provide updated information on traffic at different locations. Still, this information will be obsolete when the corresponding positions are reached due to changing traffic, and an optimal strategy based on outdated information may not bring the full benefit. Against this background, we propose a method based on a velocity prediction approach which utilizes V2X data currently available in the market in combination with historical data, to obtain a prediction of the expected traffic conditions at in the close future. Actual measurements on a city highway in Linz, Austria, are used to estimate the potential of the approach. Even for rather mild changes in traffic conditions, a reduction of up to 4% in terms fuel consumption over this track was found, confirming the potential benefit of this method.
Start page
1644
End page
1649
Volume
2021-May
Language
English
OCDE Knowledge area
Ingeniería mecánica
Scopus EID
2-s2.0-85111939635
Source
Proceedings of the American Control Conference
Resource of which it is part
Proceedings of the American Control Conference
ISSN of the container
07431619
ISBN of the container
978-166544197-1
Conference
2021 American Control Conference, ACC 2021
Sponsor(s)
VII. ACKNOWLEDGEMENTS This work has been supported by the COMET-K2 Center of the Linz Center of Mechatronics (LCM) funded by the Austrian federal government and the federal state of Upper Austria.
Sources of information: Directorio de Producción Científica Scopus