Predicting the heat transfer from burning battery energy storage systems

This paper presents a computational framework for predicting the heat transfer from a burning battery energy storage system (BESS) to adjacent enclosures using computational fluid dynamics (CFD) modeling representative of a large-scale fire test (LSFT) configuration. Simulations were conducted using representative input parameters informed by literature and experimental data. The predicted heat fluxes were in agreement under quiescent conditions with three empirical models. A full factorial sensitivity analysis examined the influence of heat release rate, wind speed and direction, ventilation configuration, radiative fraction, and atmospheric absorption parameters. The results demonstrate that predicted peak heat flux and total heat transfer to neighboring enclosures are sensitive to the flame geometry resulting from the interaction of the heat release rate, enclosure ventilation, and ambient winds. The radiative fraction also impacted the predicted exposure, although atmospheric absorption had less impact in the near field. This work highlights the need to evaluate a range of scenarios when conducting a hazard assessment in BESS installations. CFD models provide a critical role in filling the gap from variability in real-world installations and statistical power of individual full-scale tests. Recommendations are provided for additional measurements in LSFTs to improve model validation and reduce uncertainty in separation distance evaluations.