TY - JOUR
T1 - Optimizing Fast Charging and Wetting in Lithium-Ion Batteries with Optimal Microstructure Patterns Identified by Genetic Algorithm
T2 - Article No. 120506
AU - Usseglio-Viretta, Francois
AU - Weddle, Peter
AU - Tremolet de Villers, Bertrand
AU - Dunlap, Nathan
AU - Kern, Dana
AU - Smith, Kandler
AU - Finegan, Donal
PY - 2023
Y1 - 2023
N2 - To sustain the high-rate current required for fast charging electric vehicle batteries, electrodes must exhibit sufficiently high effective ionic diffusion. Additionally, to reduce battery manufacturing costs, wetting time must decrease. Both of these issues can be addressed by structuring the electrodes with mesoscale pore channels. However, their optimal spatial distribution, or patterns, is unknown. Herein, a genetic algorithm has been developed to identify these optimal patterns using a CPU-cheap proxy distance-based model to evaluate the impact of the added pore networks. Both coin-cell and pouch cell form factors have been considered for the wetting analysis, with their respective electrolyte infiltration mode. Regular hexagonal and mud-crack-like patterns, respectively, for fast charging and fast wetting were found to be optimal and have been compared with pre-determined, easier to manufacture, patterns. The model predicts that using cylindrical channels arranged in a regular hexagonal pattern is ~6.25 times more efficient for fast charging as compared to grooved lines with both structuring strategies being restricted to a 5% electrode total volume loss. The model also shows that only a very limited electrode volume loss (1%-2%) is required to dramatically improve the wetting (5-20 times) compared to an unstructured electrode.
AB - To sustain the high-rate current required for fast charging electric vehicle batteries, electrodes must exhibit sufficiently high effective ionic diffusion. Additionally, to reduce battery manufacturing costs, wetting time must decrease. Both of these issues can be addressed by structuring the electrodes with mesoscale pore channels. However, their optimal spatial distribution, or patterns, is unknown. Herein, a genetic algorithm has been developed to identify these optimal patterns using a CPU-cheap proxy distance-based model to evaluate the impact of the added pore networks. Both coin-cell and pouch cell form factors have been considered for the wetting analysis, with their respective electrolyte infiltration mode. Regular hexagonal and mud-crack-like patterns, respectively, for fast charging and fast wetting were found to be optimal and have been compared with pre-determined, easier to manufacture, patterns. The model predicts that using cylindrical channels arranged in a regular hexagonal pattern is ~6.25 times more efficient for fast charging as compared to grooved lines with both structuring strategies being restricted to a 5% electrode total volume loss. The model also shows that only a very limited electrode volume loss (1%-2%) is required to dramatically improve the wetting (5-20 times) compared to an unstructured electrode.
KW - electrolyte wetting
KW - fast charging
KW - genetic algorithm
KW - lithium-ion battery
KW - secondary pore network
KW - topology optimization
U2 - 10.1149/1945-7111/ad0a7a
DO - 10.1149/1945-7111/ad0a7a
M3 - Article
SN - 0013-4651
VL - 170
JO - Journal of the Electrochemical Society
JF - Journal of the Electrochemical Society
IS - 12
ER -