Empirical battery degradation modelling

Abstract

Renewable energy sources, although they are quickly increasing their share in the energy mix, face a major barrier to more widespread adoption. Energy storage solutions overcome this hurdle, and lithium-ion batteries are at the forefront of this. The need for lithium-ion battery degradation studies arises due to the ever increasing use of these batteries in a wide variety of applications.

There exist a large number of empirical and semi-empirical battery degradation models in literature, however their usage with irregular, real world profiles has not been explored. Moreover, understanding where different models can be used and comparing these models is also an area that has not been looked at.

A real world power profile was created in MATLAB based on the WLTP drive cycle. Simultaneously, each model considered was verified against the experimental data for that same model to make sure model predicted degradation values matched the experimental observations. In three models, the verification procedure revealed errors and inaccuracies that were corrected. Implementing an irregular
power profile posed two challenges, first, the stress factors of time and throughput required linearized versions of the model equations to be properly accounted for. Second, the identification of cycles in the irregular power profile is usually done using the rainflow counting algorithm, however, an alternative method is proposed in this study.

The real world power profile was applied to each calendar and cyclic ageing model and it was noted that although the power profile was equalized for each cell based on the model in question, the results were widely differing. In some cases, it was possible to explain the differences but in some cases the differences were not easily explained. Apart from the comparison, each model was individually analyzed to understand how degradation phenomena and stress factors affect the accuracy and use case of a model.

Finally, a toolbox was built in MATLAB to summarize the findings of this study, to help users understand where each model studied is likely to be accurate and useful. It was concluded that empirical and semi-empirical models are highly dependent on the testing conditions of the experimental data they
are built on, and there are extremely limited scenarios in which these models are applicable outside these conditions. Moreover, accelerated testing conditions which are often used in the experimental phase usually cover different degradation phenomena than those which occur under regular use cases.
With respect to the application of irregular (real-world) power profiles to these models, this study details a unique method used to obtain accurate predictions.