A Battery Pack Risk Assessment Tool

When many Lithium-ion battery cells are integrated into a large pack, the possible outcomes resulting from individual cell faults are complex and difficult to predict. Consequently, there is great interest in developing design tools to aid in the optimization of pack performance as well as to understand and mitigate the effects of individual cell failures from propagating to other cells or even the host platform. During this program, we will determine the feasibility of developing a software-based Battery Pack Risk Assessment Tool to accomplish these goals. Our previously developed Lithium-ion battery pack predictive algorithms include three-dimensional, coupled electro-chemical, electrical, and thermal physical models which encompass a multitude of failure mechanisms and provide broad state-of-health awareness. During Phase I we will adapt these algorithms and develop a user interface to allow the designer to assess the overall impact on battery pack and host platform for a cell-level fault. During Phase II we will work with our commercialization partners to conduct laboratory testing, validate the models, and extend the tools to allow analysis of multiple configurations.