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This paper presents a general multi-scale multi-physics lithium-ion battery model framework, the Multi-Scale Multi-Dimensional model. The model introduces multiple coupled computational domains to resolve the interplay of lithium-ion battery physics in varied length scales. Model geometry decoupling and domain separation for the physicochemical process interplay are valid where the characteristic time or length scale is segregated. Assuming statistical homogeneity for repeated architectures typical of lithium-ion battery devices is often adequate and effective for modeling submodel geometries and physics in each domain. The modularized hierarchical architecture of the model provides a flexible and expandable framework facilitating modeling of the multiphysics behavior of lithium-ion battery systems. In this paper, the Multi-Scale Multi-Dimensional model is introduced and applied to a model analysis that resolves electrochemical-, electrical-, and thermal-coupled physics in large-format stacked prismatic cell designs.

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SUMMARYProper understanding of heat generation and design of heat dissipation paths are critical for ensuring the safety of lithium ion modules during abuse events such as external shorts. Additionally, the behavior of positive thermal coefficient (PTC) current limiting devices-generally effective at the single-cell level-can be difficult to predict for a multi-cell module. To help guide battery pack design, a coupled thermal/electrical model of a commercial 18 650-size cell and a module with 16 cells in parallel (16P) are developed. Cell electrical response is modeled using an equivalent circuit, including the temperature-dependent behavior of the PTC. Cell thermal response is modeled with a highresolution thermal model from which a simpler 5-node thermal circuit model is extracted. Cell models are integrated into a module-level model considering cell-to-cell electrical and thermal interactions via conduction, convection, and radiation. The module-level model is validated with a 16P external short experiment and applied in a parametric study to assess thermal safety margin.

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