Knowledge of the open-circuit voltage (OCV) behaviour of cells and batteries is important for ageing diagnosis as it enables separation of degradation modes such as loss of lithium inventory (LLI) and loss of active material (LAM). While lab tests usually enable reliable extraction of OCV information, the same analysis methods often fail on field data for the following reasons: sampling is sparse, cell type and rated capacity are often unknown, and there is usually no fixed procedure to estimate capacity or open-circuit voltage (OCV). Additionally, highly dynamic load profiles, e.g., urban driving, add fast current transients that bias terminal voltage, especially at low sampling rates.

In this work, we propose an automated pipeline that recovers a full-cell OCV curve from highly dynamic field data. The method detects long rest phases, which are used to model voltage relaxation with an equivalent-circuit representation to estimate true OCV support points. The algorithm then aligns this partial OCV with open-circuit-potential (OCP) literature data of various half-cells through a constrained optimisation over scale and offset. It finally extrapolates the reconstructed OCV between discharge and charge cutoffs to cover the full usable window.

The resulting OCV curve enables capacity estimation over the full voltage range even when terminal limits are not observed in use, e.g., cell cut-off voltages during normal operation. This improves comparability across vehicles and duty cycles and allows direct use of mechanistic models to separate LLI and LAM in order to enable earlier detection of safety-relevant ageing trends in fleets and to reduce reliance on intrusive reference cycles.

Future work will integrate these methods into the open-source Python package PyDPEET (Python Data Processing for Electrical Energy Storage Technology) for advanced battery analysis, add further functions such as internal-resistance estimation, and validate the pipeline against controlled laboratory datasets. The goal is a reproducible, low-overhead procedure that turns routine field logs into physics-consistent ageing metrics.