Optimization of a Lithium-Ion Battery for Maximization of Energy Density with Design of Experiments and Micro-genetic Algorithm

Abstract

Currently, the developments and demands on high-capacity/high-power lithium-ion batteries (LIBs) are increasing owing to the advances in the eco-friendly electric vehicle industry. To improve the power and capacity of LIBs without changing material characteristics such as diffusivity and conductivity, it is effective to optimize design variables such as the electrode thickness, porosity, and active particle size. In this study, optimization to maximize the specific energy density was performed using the LIB electrochemical model and global optimization, which does not require gradient calculation. For many factors that affect the LIB power and capacity performance, major design variables were selected by performing sensitivity analysis using design of experiments. In addition, optimization was performed using the micro-genetic algorithm, which does not include mutation operation. Owing to the optimization, the anode/cathode capacity ratio was improved and the polarization phenomenon decreased, thereby increasing the specific energy density without changing the power performance compared with the initial design.