Optimization of LiMn2O4 electrode properties in a gradient- and surrogate-based framework

In this study, the effects of discharge rate and LiMn₂O₄ cathode properties (thickness, porosity, particle size, and solid-state diffusivity and conductivity) on the gravimetric energy and power density of a lithium-ion battery cell are analyzed simultaneously using a cell-level model. Surrogate-based analysis tools are applied to simulation data to construct educed-order models, which are in turn used to perform global sensitivity analysis to compare the relative importance of cathode properties. Based on these results, the cell is then optimized for several distinct physical scenarios using gradient-based methods. The complementary nature of the gradient- and surrogate-based tools is demonstrated by establishing proper bounds and constraints with the surrogate model, and then obtaining accurate optimized solutions with the gradient-based optimizer. These optimal solutions enable the quantification of the tradeoffs between energy and power density, and the effect of optimizing the electrode thickness and porosity. In conjunction with known guidelines, the numerical optimization framework developed herein can be applied directly to cell and pack design.