Fast data based identification of thermal vehicle models for integrated powertrain control

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.