The maximum energy that lithium-ion batteries can store decreases as they are used because of various irreversible degradation mechanisms. Many models of degradation have been proposed in the literature, sometimes with a small experimental data set for validation. However, a thorough comparison betweendifferent model predictions is lacking, making it difficult to select modelling approaches which can explain the degradation trends actually observed from data. Here various degradation models from literature are implemented within a single article model framework and their behaviour compared. It is shown that many different models can be ?fitted to a small experimental data set. The interactions between different models are simulated, showing how some of the models accelerate degradation in other models, altering the overall degradation trend. The effects of operating conditions on the various degradation models is simulated. Thisidentifies which models are enhanced by which operating conditions and might therefore explain specific degradation trends observed in data. Finally, it is shown how a combination of different models is needed to capture different degradation trends observed in a large experimental data set. Vice versa, only a large data set enables to properly select the models which best explain the observed degradation.
Experimental data of lithium-ion batteries under galvanostatic discharge tests at different rates and temperatures of operation
