The solid-electrolyte interface (SEI) on the highly reductive negative electrode surface of lithium-ion batteries is a key component affecting the electrical performance and stability; however, the formation of SEI involves complex processes in multiscale and multiphysical fields with extremely complex components. In the "black box" environment of a battery shell, the existing technology cannot characterize SEI, and in situ technology is difficult to obtain highly precise results. Using mathematical methods to model SEI is expected to decouple the complex physical fields and accurately describe the mechanisms and processes of SEI formation and evolution, which is a research hotspot in the field of battery. In this study, first, we describe the main methods and progress of SEI modeling from the atomic scale to mesoscale, including first-principles classical molecular dynamics, reactive molecular dynamics, classical molecular dynamics, Monte Carlo simulations, and macroscopic models. We also summarize some modeling applications in guiding electrode material synthesis and electrolyte modification, focusing on the difficulties and shortcomings of multiscale modeling. Next, we propose a force field algorithm platform based on the electrochemical potential field characteristics of SEI, expanding the modeling to tens of thousands or even hundreds of millions of atoms using the kinetic Monte Carlo simulations and machine learning assistance. Then, calculations are performed step by step, combining experimental verification and expert evaluation to promote convergence. Finally, we obtain an SEI model with quantum mechanical accuracy and electrochemical potential field, which is expected to realize SEI modeling at various lengths and timescales.

Keywords： lithium-ion batteries ; multiscale modeling ; molecular dynamics simulation ; reaction force field ; solid electrolyte interface