A cellular automaton model is introduced for simulating electrolyte wetting in porous battery composites. The model offers high flexibility, near real-time runtimes, and strong agreement with experimental data. Validated on individual and multilayer configurations, the model enables fast, accurate wetting prediction for pouch, and cylindrical cell designs in digital production control.

Electrolyte filling is a critical step in lithium-ion battery manufacturing, with direct relevance for wetting dynamics, ion transport pathways, and overall cell performance. Despite its significance, modeling approaches capable of reliably capturing electrolyte infiltration in porous electrode-separator composites (ESCs) vary widely in scope, resolution, and applicability. Based on a literature review on modeling and simulation publications in electrolyte filling, a 2D cellular automaton approach is selected for its combination of computational efficiency, parallelization capability, and modeling flexibility. The resulting model simulates capillary-driven electrolyte wetting using experimentally derived material parameters and is validated against tensiometer-based wetting data. A dynamic time-stepping scheme and saturation-based logic enable accurate predictions at low computational cost. The model reproduces wetting behavior in both single-layer and multilayer ESCs, with strong alignment to experimental data when material interactions are included. Simulations of full pouch and cylindrical cells with varying geometries demonstrate the method's robustness. Across all tested configurations, simulation runtimes remain significantly below physical wetting times, supporting real-time integration. Future work might explore the extension to 3D systems and analysis of design- and process-induced variations in wetting behavior.