Efficient Global Sensitivity Analysis of 3D Multiphysics Model for Li-Ion Batteries

Abstract

Parameter sensitivity analysis of mechanistic battery models has the power to quantify the individual and joint effects of parameters on the performance of lithium-ion cells. This information can be beneficial for industrial cell designs, cell testing, and battery management system (BMS) configurations. The numerical quantification of these parameter sensitivities, however, is challenging in terms of computational costs and is an active field of research. In this paper, based on a 3D multiphysics model, we conduct a global sensitivity analysis for the utilizable cell discharge capacity and the maximum cell temperature at the discharge rate of 1C. The least angle regression version of the polynomial chaos expansion (PCE) concept has been identified as an optimal trade-off between approximation power and computational complexity. As a result, the sensitivities of all parameters in the 3D multiphysics model were studied using a hierarchical design and a stepwise design. We conclude that the cell discharge capacity and the thermal behavior at 1C discharge are most sensitive to the electrode parameters and their pore structure. The results reveal different dependencies and lead to new insights for cell design and operation.