Digital Twin Battery Modeling and Simulations: A New Analysis and Design Tool for Rechargeable Batteries

Abstract

The intricate correlation between microstructural properties and performance in lithium rechargeable batteries necessitates advanced methods to elucidate their mechanisms. In this regard, digital twin simulations have been utilized by creating virtual replicas that simulate battery behaviors and performances under various conditions. However, the relationship between microstructural parameters and battery performances is still not fully understood. This focus review aims to revisit the state of digital twin simulations, with a particular focus on its effectiveness for analyzing microstructures and unraveling the hidden parameters. For this purpose, we explore microstructure formation and validation methods as top-down and bottom-up simulation techniques and provide a comprehensive view of multiphysics approaches for understanding the electrochemical, mechanical, and thermal behaviors. Finally, we discuss the potential of artificial intelligence (AI)-driven multiscale modeling strategies and dynamic simulations, offering insights into how digital twin technology can advance battery design and optimization for enhanced performance and safety.