Enable Model-Based Diagnostics and Prognostics for Lithium-Ion Batteries

Abstract

Physicochemical processes in lithium ion batteries occur in intricate geometries over a wide range of time and length scales. As the size of the battery increases, macroscopic design factors in combination with highly dynamic environmental conditions significantly influence the electrical, thermal, electrochemical, and mechanical responses of a battery system. Computer-aided engineering tools are helping to accelerate the design and validation of large format cells and battery pack systems, which heavily replies on costly and time-consuming experimental tests previously. Validated physics-based models are effective in predicting electrochemical performance, thermal and mechanical response of cells and packs under normal and abuse scenarios and provide valuable insights not possible through experimental testing alone for diagnostics and prognostic purpose. NREL pioneered the Multi-Scale Multi-Domain (MSMD) battery model, overcoming challenges in modeling the highly nonlinear multi-scale response of battery systems. The MSMD model provides flexibility and multi-physics expandability through its modularized architecture. The presentation describes present efforts to develop approaches to make the models better suited for engineering diagnostics and prognostic for large lithium-ion battery units by Enhancing computation speed and stability of the pack-level multi-scale model while still resolving nonlinearities of dynamic battery response across scales from particles to packsBlending field simulation with system simulation in a selective fashion to balance speed and accuracy. Applicable techniques include domain decomposition, physics segregation and reduced-order models (ROM) that can integrate into the system modelDeveloping interactive system interface for enhancement of multi-physics integrityIncorporating spatially distributed model to address 3D non-uniform usage and stress factors.