Battery degradation leads to the fade of capacity and power, which are key battery performance parameters. Capacity fade and power fade are highly dependent on the operating strategy since the underlying degradation mechanism are triggered in dependence of e.g. temperature, mechanical stress, current load or electrode stoichiometry.
Because there is a myriad of underlying degradation mechanisms, they are sometimes categorized into the three degradations modes loss of active anode material, loss of active cathode material and loss of lithium inventory. For an aged cell, the degradation modes can be estimated by measuring the open-circuit voltage curve and performing differential voltage analysis.
In this presentation, we show the results of a large aging study, where we correlate estimated degradations modes with aging stress factors, to reveal the dependence of degradation modes on the operating strategy. To estimate the degradation modes, we do not only perform differential voltage analysis, but also use the electrode potential curves to reconstruct the full-cell open-circuit-voltage curve in an optimization algorithm. Comparing these results to the results for a pristine cell allows us to estimate the degradation modes. We can show a correlation of degradations modes to a range of stress factors usually only found in large-scale capacity fade models, because we conduct aging experiments over a large range of temperatures, states-of-charge, depths-of-discharge, and current rates with over 200 cells.
These results could in future be used to gain more insight or build more accurate models for capacity and power fade and the onset of non-linear aging regimes, because we can show when different degradation mechanisms dominate battery degradation during different phases of aging.