An improved thermal single particle model and parameter estimation for high-capacity battery cell

Abstract

Single particle model (SPM) is an electrochemical model which can be used with energy balance to calculate the state of charge, terminal voltage, and temperature of the battery. The conventional SPM neglects the lithium-ion dynamics in the electrolyte, and the energy balance usually does not consider the heat transfer delay from the battery center to the surface. These lead to model errors when SPM is used for high-capacity battery cells. In this study, we propose several strategies to improve the model accuracy for high-capacity battery cells. First, the actual discharge capacity is considered by modifying the desired Li-ion flux at the electrode surface. Second, a part of the equivalent circuit model is integrated with SPM to consider the resistance in the electrolyte computationally efficiently. Third, the delay in the heat transfer from the center to the surface is represented using a second-order system dynamic. In electric vehicles, battery cells are stacked as a pack; we account for the additional heat generated by stacking pressure-induced swelling repression. Finally, parameter estimation is conducted to determine the best parameter values of the model using the experimental data. The reference values are set using a dimensionless scale-up approach. When the parameters are estimated and the model is tested with the validation data, the error percentages in the calculated terminal voltage and temperature are smaller than 2.0410% and 3.5032%, respectively, even with the cell variances.