Parameter Sensitivity Analysis and Optimization of Nickel-Iron Batteries Using a Physics-Based Model

Abstract

Large-scale energy storage has rapidly advanced with the increasing demand for clean energy sources. One type of storage is the nickel-iron (Ni-Fe) battery which is regaining attention due to its cost-effectiveness, durability, and inherent safety. However, its full capability is limited by its low energy and power density due to low active iron utilization and Coulombic efficiency due to hydrogen formation at the anode. While most research on improving Ni-Fe batteries focused on experimental studies, multiphysics modeling is a practical tool to analyze the phenomena in the battery system instead. This study built a simple one-dimensional (1D) isothermal multiphysics model of a Ni-Fe battery with nanostructured electrodes using COMSOL Multiphysics®. Sensitivity analysis was conducted based on the first discharge plateau only (1-step case) and on the overall discharge (2-step case) to investigate the susceptibility of energy density to battery design parameters. These parameters were ranked according to their sensitivity and subjected to a constrained optimization by linear approximation (COBYLA) algorithm to optimize the energy and power density. In the 1-step case, the simultaneous optimization resulted in a ~ 25 % increase in energy density and a ~ 23 % increase in power density, which correspond to the maximized anode thickness and minimized cathode porosity. Results in the 2-step case showed a ~ 23 % increase in energy density and an ~ 18 % increase in power density, which are attributed to the minimization of cathode thickness, porosity, and active particle size.