This project is related to state estimation state of health (SoH) of first life battery cells used for electric vehicles application. The rise of electric vehicles (EV) has significantly increased the demand for reliable and long-lasting lithium-ion batteries. Central to maintaining the performance and safety of EV is the accurate estimation of the SoH of these battery cells, which indicates their remaining capacity and overall usability. Accurate SoH estimation is crucial for optimizing battery usage, preventing unexpected failures, and extending battery life. The thesis aims to develop an advanced ageing model for lithium-ion battery cells used in EV, with a specific focus on utilizing voltage and time as input parameters to predict the capacity degradation of the cells. By analyzing how these variables interact and contribute to the ageing process, this research seeks to enhance the precision of SoH predictions. The model is trained and validated using real-world data from first-life battery cells, ensuring its applicability in practical e-mobility scenarios.
| Date of Award | 2024 |
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| Original language | English |
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AGEING MODELS FOR LITHIUM-ION BATTERY CELLS FOR E-MOBILITY APPLICATIONS
Berecibar, M. (Promotor), Kalogiannis, T. (Co-promotor), Rexhepe, A. ((PhD) Student). 2024
Student thesis: Master's Thesis