Title
Fast data based identification of thermal vehicle models for integrated powertrain control
Date Issued
25 May 2021
Access level
metadata only access
Resource Type
conference paper
Author(s)
Meier F.
Adelberger D.
Johannes Kepler University,
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
Abstract
In vehicles without additional heat sources but the combustion engine, fast cabin heating tends to delay engine heating. This negatively effects consumption so that a trade-off is necessary between windscreen heating, cabin temperature and fuel consumption. This is even more the case for hybrid electric vehicles (HEVs), as they may have to use the thermal mode even if an electrical operation would be preferable, for instance in city traffic conditions. A fixed strategy may not be optimal, as the actual heating behavior will depend on several environmental factors, like wind, presence of snow on the roof or sun radiation. In order to optimize the heating strategy in real time, computationally efficient - whilst still accurate - models of the different thermal systems are required. This paper presents a fast data based approach to model the heat flows based on first principles, but using only easily accessible data from real drives. The chosen model structure enables the possibility of online identification in case of parameter changes during a drive.
Start page
1836
End page
1841
Volume
2021-May
Language
English
OCDE Knowledge area
Termodinámica
Scopus EID
2-s2.0-85111902000
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
9781665441971
Conference
2021 American Control Conference, ACC 2021
Sources of information: Directorio de Producción Científica Scopus