Modelling of electric vehicle charging behaviour
Baral, Sushant (2026)
Kandidaatintyö
2026
School of Energy Systems, Sähkötekniikka
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2026052856707
https://urn.fi/URN:NBN:fi-fe2026052856707
Tiivistelmä
The increasing adoption of electric vehicles introduces new challenges for understanding and analysing charging behaviour under varying operating conditions. Ambient temperature has a considerable influence on charging power profiles due to its impact on battery performance and auxiliary energy consumption. Accurate yet transparent modelling approaches are therefore required to analyse temperature-dependent charging behaviour without relying on complex or unmeasured internal battery dynamics.
This thesis presents the development of a system-level charging behaviour simulator for a single electric vehicle connected to a controlled charging point. The simulator models the time evolution of battery state of charge using a discrete-time energy balance formulation, while charging power is prescribed directly from experimentally measured charging, preheating, and standby power profiles. Ambient temperature is treated as a static scenario parameter, with temperature effects incorporated through the selection of temperature-specific datasets rather than through dynamic thermal modelling.
By restricting the model to behaviour that can be directly supported by available measurements, the proposed approach enables comparative and explanatory analysis of charging behaviour under different ambient temperature conditions. The simulator represents the transition from preheating to active charging using measured power profiles and shows how this transition changes with ambient temperature. The results indicate that a system-level model driven by measured charging data is sufficient to analyse temperature-dependent charging behaviour without introducing additional internal battery modelling complexity.
This thesis presents the development of a system-level charging behaviour simulator for a single electric vehicle connected to a controlled charging point. The simulator models the time evolution of battery state of charge using a discrete-time energy balance formulation, while charging power is prescribed directly from experimentally measured charging, preheating, and standby power profiles. Ambient temperature is treated as a static scenario parameter, with temperature effects incorporated through the selection of temperature-specific datasets rather than through dynamic thermal modelling.
By restricting the model to behaviour that can be directly supported by available measurements, the proposed approach enables comparative and explanatory analysis of charging behaviour under different ambient temperature conditions. The simulator represents the transition from preheating to active charging using measured power profiles and shows how this transition changes with ambient temperature. The results indicate that a system-level model driven by measured charging data is sufficient to analyse temperature-dependent charging behaviour without introducing additional internal battery modelling complexity.