Abstract

As the energy density of systems of lithium-ion batteries increases, and as they are employed in larger-scale energy storage systems, greater attention must be paid to the safety of these systems. Failure of a single cell can trigger thermal runaway processes that cascade through the system, endangering first responders and nearby structures. This cascading failure is driven by heat transfer through the system to vulnerable cells and other combustible materials. To understand how to mitigate thermal runaway, the most important heat transfer pathways must be characterized in terms of their magnitude and time scale.Heat must be removed from cells that have gone into thermal runaway without leading vulnerable cells into thermal runaway. The onset of thermal runaway typically occurs around 200oC and depends on the heating time (i.e. cells heated slowly in an oven will begin thermal runaway around 150oC). The objective then becomes avoiding these thermal runaway temperatures for surrounding cells while dissipating any heat released from an initial thermal runaway event.While there are many individual parameters that describe the cells and system, in this work it will be seen that the thermal analysis can be reduced to a collection of non-dimensional parameters. These parameters describe heat conduction within the cell, heat capacity of a cell, total heat released by a cell in thermal runaway, conductive heat transfer to adjacent cells and surroundings, and convective heat transfer to surrounding gases.A simple cell-to-cell propagation scenario is constructed to separately investigate the heat transfer parameter space. In this model scenario, an “initiating” cell is assumed to have just completed thermal runaway and exhausted all its reactants. This heats that cell to a high temperature that depends on the cell chemistry and state of charge. Adjacent to this “initiating” cell is the “target” cell. We use canonical heat transfer problems to identify a set of parameters that determine the temperature of the “target” cell. The attached figure depicts the prominent heat transfer pathways for a notional propagation scenario. The parameters space of interest includes the thermal resistance (left), the heat capacity of the involved materials (center), and heat losses to the ambient surroundings (right). The relative time scales of these heat transfer rates determine the propagation speed and ultimately the point at which cascading thermal runaway is mitigated.The thermal parameter space is interrogated by solving the transient heat transfer problem with a combination of analytical techniques, a quasi-1D finite volume software, and 3D finite element software. The maximum temperature reached by the edge of the target cell is recorded and used as the criteria for the boundary between propagation and mitigation. The scaling relationships developed through this analysis can provide thermal engineers and system designers with a framework for predicting the safety of battery pack designs in the context of cascading thermal runaway. SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525 SAND2023-02583A Figure 1

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