Rotas, R.; Iliadis, P.; Nikolopoulos, N.; Rakopoulos, D.; Tomboulides, A. Dynamic Battery Modeling for Electric Vehicle Applications. Preprints2024, 2024040647. https://doi.org/10.20944/preprints202404.0647.v1
APA Style
Rotas, R., Iliadis, P., Nikolopoulos, N., Rakopoulos, D., & Tomboulides, A. (2024). Dynamic Battery Modeling for Electric Vehicle Applications. Preprints. https://doi.org/10.20944/preprints202404.0647.v1
Chicago/Turabian Style
Rotas, R., Dimitrios Rakopoulos and Ananias Tomboulides. 2024 "Dynamic Battery Modeling for Electric Vehicle Applications" Preprints. https://doi.org/10.20944/preprints202404.0647.v1
Abstract
The development of accurate dynamic battery pack models for electric vehicles (EVs) is critical for the ongoing electrification of the global automotive vehicle fleet, since these serve as a key element in the energy performance of an EV powertrain system. The Equivalent Circuit Model (ECM) technique at the cell level is commonly employed for this purpose, combining accuracy and efficiency in the representation of battery operation within the broader powertrain system. In this study, a second-order ECM model of a battery cell is being developed using Modelica, an equation-based modeling language. Parameter lookup tables at multiple levels of state of charge (SoC), extracted from Li-ion battery cells with 4 different commonly used cathode materials, have been utilized. This approach allows for a representation of the battery systems that are used in a wide range of commercial EV applications. To verify the model, an integrated EV model is developed and simulation results of the FTP75 driving cycle have been compared against an equivalent application in MATLAB Simulink. The findings demonstrate a close match between the results obtained from both software across different system points. Specifically, the maximum deviation of SoC is limited to 0.08% and the maximum value of relative voltage deviation is 1.4%. The verified model enables the exploration of multiple possible architecture configurations of EV powertrains with Modelica.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
