Battery Ageing Modelling and Health Monitoring
On the component level, the research of the Christian-Doppler-Laboratory (CDL) is primarily concerned with batteries and fuel cells. The main research question regarding battery ageing is how to predict battery degradation and end-of-life for Li-ion cells. It is thereby crucial to gain insights which phenomena lead to accelerated ageing. It is essential to understand how the operating conditions and particularly the driver behaviour affect the capacity fade of the battery so that an energy management system can take preventive care and operate the battery in an optimal way. For that purpose, ageing prediction models were investigated and validated by means of measurement data from a large-scale battery ageing experiment.
In addition to predicting degradation, estimating the current state of health (Soll) during real driving conditions (without being able to per form specially designed measurements) and at different temperatures is also a key challenge. In this context, the amount (duration, excitation and number of cells) of measurement data required for a meaningful ageing model was investigated an the one hand. On the other hand, the combination with the SoH observer was also studied, with the aim of increasing the robust ness of the Soll estimation and also enabling an online update of the ageing prediction model.
Online tracking of the cell capacity and internal resistance
- Estimation of EOL
- High impact on the majority of algorithms in a battery management system (BMS)
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- February 2017 - January 2024