On the accuracy and Estimation of Battery Behavior

Many multi-scale physics-based models and their reduced-order renditions are used to estimate the lithium concentration and over-potential distributions throughout the battery electrode. The models let us meet time varying power demands while avoiding locally large over-potentials; a condition that leads to increased rate of side-reactions and lithium plating that decrease the battery performance and capacity.
In an effort to evaluate the accuracy of various electrochemical battery models we first use neutron imaging which is an in situ measurement of the lithium concentration along the anode and cathode electrode layers in an operating Lithium Iron Phosphate (LFP) pouch cell battery with typical commercial electrodes. The observations are used to define the limits of the validity of various model simplifications such as the electrode-averaged assumption in single-particle battery models.
We then quantify the fudge factors associated with a lumped heat generation and associated approximation of the radial thermal gradient of a cylindrical cell. Using the surface temperature measurement of the casing, the algorithm employs non-uniform forgetting factors to capture the long term resistance growth due to aging or degradation. The algorithm accounts for the nonlinear dependency of the electric resistance (hence heat generation) on temperature in healthy cells and can be critical for avoiding the onset of thermal run-aways.
This work establishes a simple thermal model than can be parameterized to describe the thermal dynamics for cells of differing chemistry from various suppliers and various manufacturing batches without having to capture the complex geometry and the physical resistance of the interconnected tabbing for a spirally wound cell. Extensions of the cell model to a module or a pack is also supporting an observability analysis which can point to the necessary sensor location for a pack thermal management.
Supported by Ford, US Army (TARDEC), NSF, NIST, A123

Anna G. Stefanopoulou is a professor of Mechanical Engineering and the Director of the Automotive Research Center at the University of Michigan. She was an assistant professor (1998-2000) at the University of California, Santa Barbara and a technical specialist (1996-1997) at Ford Motor Company. She is an ASME and an IEEE Fellow. She has a book, 12 US patents, 4 best paper awards and more than 150 publications on estimation and control of internal combustion engines and electrochemical processes such as fuel cells and batteries.