Using Degradation Modes for Large-scale Capacity and Power Fade Diagnostics

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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, charge and discharge currents and state of charge.
Because of the large number of degradation mechanisms, they are often categorized into a smaller number of degradation modes. Three commonly estimated degradation modes are 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.
On this poster, we show the results of an aging study with a commercial 18650 lithium-ion battery with an NCA cathode and a Si-doped graphite anode. We estimate degradations modes during aging with different stress, to reveal the influence of different operation parameters on battery degradation. To estimate the degradation modes, we 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 show that for this cell type and the tested aging stress, loss of lithium inventory is the dominating degradation mode, while loss of active cathode material is smallest compared to the other degradation modes. Moreover, we reveal that the depth-of-discharge has the largest influence on aging for this cell type.
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 the degradation modes can show when different degradation mechanisms dominate battery degradation during different phases of aging.

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