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When two electrode open-circuit potentials form a full-cell OCV (open-circuitvoltage) model, cell-level SOH parameters related to LLI (loss of lithiuminventory) and LAM (loss of active materials) naturally appear. Such modelshave been used to interpret experimental OCV measurements and infer these SOHparameters associated with capacity fade. In this work, we first propose aminimal and intuitive parametrization of the OCV model that involvespristine-condition-agnostic and cutoff-voltage-independent parameters such asthe N/P ratio and Li/P ratio. We then study the modal identifiability ofcapacity fade by mathematically deriving the gradients of electrode slippageand cell OCV with respect to these SOH parameters, where the electrodedifferential voltage fractions, which characterize each electrode's relativecontribution to the OCV slope, play a key role in passing the influence of afixed cutoff voltage to the parameter sensitivity. The sensitivity gradients ofthe total capacity also reveal four characteristic regimes regarding how muchlithium inventory and active materials are limiting the apparent capacity. Weshow the usefulness of these sensitivity gradients with two applicationsregarding degradation mode identifiability from OCV measurements at differentSOC windows and relations between incremental capacity fade and the underlyingLLI and LAM rates.

Identifiability Study of Lithium-Ion Battery Capacity Fade Using  Degradation Mode Sensitivity for a Minimally and Intuitively Parametrized  Electrode-Specific Cell OCV Model