There is a great need for non-invasive methods to unravel the underlying causes of battery ageing. This work investigates cycling and calendar ageing effects on high-energy cylindrical cells (NCA/Gr-Si), using non-invasive techniques, such as an accelerated entropy measurement and a differential voltage analysis (DVA). The information about observed changes is then used as an input to an electrochemical model to examine if the battery’s output voltage can be simulated with the same degree of accuracy for both pristine and aged cells.
Firstly, DVA is used to identify the main degradation modes of the aged cells. These are then translated to several parameters, to reflect in the single particle model equations. The parameters affected by ageing include: diffusion time constant, internal resistance, stoichiometry, active material volume fraction and kinetic rate constant. Focus is placed on the diffusion time constant, which increases as the battery ages, resulting in a doubling of time needed to reach thermodynamic equilibrium following full (dis)charge. Given that the diffusion time constant in the model is defined by both diffusion coefficient and a particle radius, it is impossible to differentiate which one (or both) is affected by ageing. Initially, the model is simulated on a training data set in PyBaMM, optimising values of selected parameters. Subsequently, a new data set is introduced to the model, taking optimised parameters from the previous simulation. The results show that the output voltage is computed with a very similar accuracy for both pristine and aged cells.
The degradation detection methods based on voltage response to the applied current are limited in their analysis depth. However, complimentary information can be obtained from a voltage response to the applied temperature changes. In this work, these thermodynamic changes are tracked by the means of accelerated entropy measurement. The study reveals a strong correlation between entropy ageing and the diffusive time constant behaviour. The comparison is presented in Fig. 1, where a significant increase in the diffusion time constant for the cycled group of cells is accompanied by a decrease in entropy. Pristine cell is marked A, calendar aged – B, and cycle aged – C. In both diffusion time constant (Fig. 1a) and entropy (Fig. 1b) profiles, the horizontal shift is attributed to the loss of active material (LAM). It is believed that LAM does not influence the microscopic properties of the material, therefore entropy of configuration should be preserved. A possible explanation to this phenomenon is a particle size change due to cycling. Such change would also be reflected in the diffusion time constant variation, which fits well to the simulated model, but cannot be identified by the DVA.