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A Simulation Framework for Battery Safety Modeling

Wednesday, 1 June 2016: 15:55
Indigo 202 A (Hilton San Diego Bayfront)
J. Marcicki, A. Bartlett, X. G. Yang, V. Mejia, M. Zhu, Y. Chen (Ford Motor Company), P. L'Eplattenier, and I. Caldichoury (Livermore Software Technology Corporation)
Increased utilization of Lithium-ion batteries for a variety of applications is driving the need for advanced simulation tools that can predict the combined structural, electrical, electrochemical, and thermal response to abuse conditions.  If such simulation tools are integrated into the product development process, the resultant data has the potential to inform decisions during development and create highly optimized designs.

Academic and national laboratory researchers have pioneered these models1-3, but there is currently no consensus on the required methods for multi-physics coupling or acceptable degree of homogenization.  If coupling is present between the mechanical and electrical or thermal solvers, it is typically one-way and largely manually applied, which requires highly advanced users to implement due to mesh and element compatibility issues.

In order to initiate a much larger investigation into the abuse response of Li-ion cells, modules, and packs, a coupled structural, electrical, and thermal simulation framework has been developed within the commercially available LS-DYNA software.  The finite element model leverages a three-dimensional mesh structure that fully resolves the unit cell components.  Depending on the time scale of the mechanical crush, coupling with the mechanical solver can be one-way for impact loading conditions that occur in the sub-second time scale, or two-way for continuous crush in the tens to hundreds of seconds time scale.  Measurements of the resistance between unit cell layers as a function of applied pressure are reported and used to parameterize the coupling between the structural, electrical, and thermal solvers.  A spatially distributed equivalent circuit model predicts the electrical response with minimal computational complexity.  The thermal model provides information to schedule the electrical model parameters, while simultaneously accepting irreversible and reversible sources of heat generation.  The spatially distributed models of the electrical and thermal dynamics allow for the localization of current density and corresponding temperature response to provide the necessary tool structure for predicting the onset of thermal runaway.

Future work will focus on the structural material models and failure conditions required to quantitatively predict the battery crush response to a variety of loading conditions.  Plans for additional multi-physics functionality within the simulation tool will also be highlighted.

References:

  1. E. Sahraei, R. Hill, and T. Wierzbicki, J. Power Sources, 201, 307 – 321 (2012).

  2. E. Sahraei, M. Kahn, J. Meier, and T. Wierzbicki, RSC Adv., 5, 80369 – 80380 (2015).

  3. C. Zhang, S. Santhanagopalan, M. A. Sprague, and A. A. Pesaran, J. Power Sources, 290, 102 – 113 (2015).