Optimization of a Single Lithium-Ion Battery Cell with a Gradient-Based Algorithm

This paper presents a numerical framework for automating the design of lithium-ion cells to maximize cell energy density while meeting specific power density requirements. The various processes in a battery cell are simulated using a physics-based electrochemistry model. The design is automatically performed by coupling the battery model with a gradient-based optimization algorithm. We demonstrate the potential for gradient-based optimization by applying this framework to optimize the design of a lithium-ion cell with spinel manganese dioxide cathode and meso-carbon micro beads (MCMB) anode for a range of power requirements. Results indicate that variations in the electrode thickness and porosity at optimal cell designs can be quantified via active mass ratios and it is found that the active mass ratios for optimal cell designs are independent of discharge rate.