In the framework of this project, dedicated electrical, thermal, electrochemical and mechanical battery models will be developed. Combinations of these dedicated models will be used to address a diverse set of phenomena occurring on an electrode/electrolyte level and on a cell level. Key issues observable over a short time scale, such as electrical and thermal responses, and over a long time scale such as ageing phenomena and cycle life deterioration in the battery will be examined and modelled. Furthermore, the statistical variation of the battery parameters over many cells of the same cell type will be examined. This will be of high importance for battery management systems which handle multiple cells on a module level.
Besides the innovative approaches for the development of the electrical, thermal, electrochemical and mechanical fatigue, the main achievement of the BATTLE project lies in the development of the interdisciplinary battery modelling unit that can be used for different purposes. Such an interdisciplinary model is unique and has not been accomplished before. Furthermore, this model will be able to address the heating phenomena in the battery cells and packs, which is one of the critical considerations in the development of a battery system in a vehicle. Also unique is the fact that the numerical electrochemical models will incorporate the influence of the heat present from electrochemical and mass transfer reactions, and will predict the heat generated by the reactions themselves in one and the same model.
Aimed key advancements and breakthroughs through the resulting interdisciplinary battery model are:
- An accurate prediction of the battery dynamics under all environmental conditions, such as temperature, state of charge, life cycle, etc.
- Increase of the actual available battery capacity by 20% through this interdisciplinary model approach.
- Forecasting the residual battery lifetime by using advanced state-of-health estimation techniques.
- Fundamental understanding of factors leading to ageing phenomena in the battery, such as current, depth of discharge, temperature, fast charging, temperature distribution and calendar life. Up to our knowledge such a complete analysis has never been carried out on Li-ion batteries.
? Understanding the heat distribution in a battery module or a battery pack by using advanced 2D and 3D simulation thermal models. Solutions based on these new insights should allow increasing the battery lifetime by up to 20-30%.
- Determine the statistical spread of the battery parameters over multiple cells, which will enhance the confidence of the models for battery management systems. Such an approach has never been accomplished.
- Development of system identification techniques to model nonlinear battery behaviours. This approach will be unique to battery modelling and should accelerate the model development and its accuracy.
- Development and optimisation of new adequate test procedures. These new test procedures for Li-ion batteries should accelerate the development of dedicated battery models by 50% and decrease the test time by 40%.
- Development of accurate estimation techniques for SoC and SoH based on novel optimal state estimation methods.
- Predicting improved compositions and geometries for batteries through the advanced numerical electrochemical models, aiming to reduce the development costs for new batteries by 25%.
- Validation of battery models based on test benches.