(607c) Digital-Twin Battery Modeling and Simulations for Next-Generation Batteries | AIChE

(607c) Digital-Twin Battery Modeling and Simulations for Next-Generation Batteries

Authors 

Lee, Y. - Presenter, Yonsei University
Digital-twin-driven 3D modeling becomes as a pivotal tool in unraveling the intricacies of composite electrodes for next-generations batteries. Once we construct 3D structures with commendable precision, they become invaluable assets for scrutinizing structural, electrochemical, and mechanical dynamics under diverse conditions, from mechanical roll pressing to electrochemical testing. However, the initial challenge lies in crafting 3D structures with utmost accuracy, whether by reconstructing actual electrodes or creating virtual counterparts with limited data. Moreover, the choice of the optimal method is contingent upon the available time and computational resources.

In this endeavor, we embark on an exploration of how digital-twin 3D modeling reshapes the landscape of all-solid-state battery research. We delve into its applications, from visualizing the microcosm of composite electrodes to quantifying specific contact areas between electrode constituents and calculating effective electronic or ionic conductivity. Furthermore, we navigate the realm of simulations, unveiling their prowess in depicting voltage profiles, overpotentials, and lithium ion concentrations during cycling. Additionally, we unveil the successful simulation of mechanical behaviors within single electrode particles throughout the charging and discharging phases, marking a significant stride in our understanding.

Beyond the confines of electrochemistry, our inquiry extends to the mechanical realm, where we elucidate the structural deformation of composite electrodes through a comparative analysis employing finite element, finite volume, and discrete element methodologies. This comprehensive investigation not only sheds light on the multifaceted nature of all-solid-state batteries but also underscores the versatility and potency of digital-twin-driven 3D modeling in driving innovation within the realm of energy storage.