Electrode-Level Diagnosis of Lithium-Ion Battery Path-Dependent Degradation Using a Half-Cell Model

With the widespread application of lithium-ion batteries in electric vehicles, degradation diagnosis has attracted increasing attention. In practical operating scenarios, however, path-dependent degradation induced by the alternating effects of calendar aging and cycling aging can significantly influence the diagnosis of battery degradation. Existing methods often identify degradation under these two aging conditions in isolation, making it difficult to quantify their coupled impact. To address this issue, this study applies a physically constrained half-cell OCP reconstruction framework to quantify electrode-level degradation under coupled aging conditions. Specifically, degradation parameters are identified by fitting full-cell pseudo-open-circuit voltage (pOCV) curves with half-cell open-circuit potential (OCP) profiles, and the corresponding degradation modes are further quantified. The results show that the proposed model can reconstruct full-cell pOCV under different aging conditions with an RMSE maintained below 10.5 mV. The loss of active material in the anode is highly sensitive to continuous cycling, whereas the divergence of loss of lithium inventory under alternating aging conditions is relatively weak but shows pronounced differences under distinct single-aging conditions. This method enables electrode-level diagnosis of path-dependent degradation under alternating aging conditions and provides a foundation for reliable degradation diagnosis under complex operating scenarios.