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This article describes stochastic 3D structure models for electrodes of lithium-ion batteries, which can be used for model-based optimization of the electrode morphology. First, a single particle model is presented which can be used to parametrically describe individual particles from 3D tomographic image data. By fitting parametrical distributions it is therefore also possible to simulate (statistically similar) particles. Hereafter, different approaches for the arrangement of individual particles in the observation window are presented, so that system-based properties of different electrode types can be approximately matched (e. g. the connectivity of the particle system as well as the structure of the pore space). Finally, algorithms for the automatic recognition of particle cracks in tomographic image data are presented which can be used to integrate ageing effects into the models.

Analysis, Modeling and Simulation of Tomographic Image Data for the 3D Microstructure of Electrode Material in Lithium-Ion Batteries