Multiscale simulation and AI techniques for optimizing electrolyte injection processes

Lithium-ion batteries (LIBs) are essential for portable electronics and electric vehicles. As battery sizes increase and performance demands rise, electrolyte injection and wetting processes have become more complex. Current optimization methods face difficulties due to poor integration of multiscale factors and challenges in real-time adjustments, with many existing approaches relying on single-scale analyses that overlook microscopic-macroscopic interactions. This perspective proposes a multiscale, fully coupled optimization framework integrating material innovations, structural design improvements, and advanced simulations. The framework examines modifications to electrode and separator materials, along with coatings and additives, while emphasizing microscopic structural modeling, macroscopic fluid dynamics, and electro-thermal coupling. These elements are critical for understanding how manufacturing parameters affect wetting efficiency and battery performance. This approach aims to enhance real-time adjustment capabilities and improve multiscale interaction understanding, leading to more efficient electrolyte wetting and high-performance, cost-effective LIBs.