0D, quasi-3D, and 3D chemistry solvers with varying degrees of complexity are
developed to predict the thermal runaway propagation in battery cells. The 0D
solver assumes the system as homogeneous and closed. The quasi-3D solver assumes
the system as homogeneous on the selection level and the 3D solver accounts all
spatial inhomogeneities in the temperature and composition. Both the quasi-3D
and 3D solvers are fully integrated into a computational fluid dynamic (CFD)
solver and capable of predicting thermal runaway in multiple battery cells with
cell-specific kinetic reaction model. As the modeling complexity increases with
each solver, respectively, the accuracy and the simulation time increases. With
the large amount of heat and rapid transitions from the onset of thermal
runaway, the CFD solvers usually encounter difficulties in predicting the
solution accurately and in extreme heat release cases the solver may diverge. A
chemical time scale based adaptive time stepping is developed in this work to
address the accuracy, convergence, and stability issues of the CFD solver. The
proposed timescale contains in the definition the reaction rate, reaction
enthalpy, and total enthalpy content of the system. As the thermal runaway
progresses, the CFD solver time step is obtained dynamically from the defined
timescale. The developed solvers and the adaptive time-stepping method were
quite intensively tested and analyzed by using different reaction mechanisms
representing different battery cells and test conditions. The analysis of the
timescales and the adaptive time stepping proved quite efficient for solution
accuracy, simulation time, and solver stability.
