Despite the huge expansion of electric vehicle sales in the market, customers are discouraged by the possible catastrophic consequences brought by the safety issues of lithium-ion batteries, such as internal...

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Metallic Lithium deposited on graphite particles is the major phenomenon responsible for the degradation of cell capacity, triggering of internal short circuit (ISC), and exacerbating thermal runaway (TR) in lithium‐ion batteries (LIBs). However, currently, no available physics‐based model can provide an accurate quantitative description of lithium‐plating behavior. Herein, this work establishes a mechanism model to characterize the Li deposition‐stripping process, especially the formation of dead Li and the reversibility of deposited Li. By the combination of the battery model and 3D particle model with the Li deposition‐stripping model, this work enables the quantitative prediction of Li deposition during charging–discharging cycles at various charging rates. Based on the revealed understanding of the Li deposition‐stripping process, a smart charging strategy with the optimization of the minimized Li‐deposition and expedited charging time is proposed. Furthermore, this work also quantifies the influence of anode heterogeneity on Li plating. The results highlight the promise of physics‐based mechanistic modeling for the quantification of the Li disposition‐stripping process and provide fundamental guidance on battery design and charging protocols for next‐generation long cycle life Li‐ion cells.

Lithium-ion batteries (LIBs) have played an increasingly dominant role in the current mobile society. Due to the risky safety testing procedure, ultra-rigorous demands of the testing facility, and complicated multiphysics nature of the safety issues, lack of high-fidelity models to describe the safety behaviors of lithium-ion batteries upon abusive loading has significantly deferred the further application of LIBs. Herein, firstly, mechanical behaviors of the battery component materials are characterized by both in-situ and post-mortem experiments. Then, we reveal the formation process of various internal short circuit (ISC) modes inside batteries upon different abusive loadings with the aid of ex-situ observation using the X-ray Computed Tomography scanning technique and post-mortem characterization of the battery samples. To quantify the stress-driven ISC mode and failure behavior of the component material, numerical models for all component materials are established and applied in a cell model which can reveal the deformation-material failure-material contact-different ISC mode formation process. To further quantify the relationship between electrothermal response and mechanical response of battery, we develop a 2D detailed model with fully coupling of electrochemo-thermal-mechanics governing laws consisting of a 2D mechanical model, 2D ISC model, 2D heat model and Thermal Runaway model. The multiphysics model demonstrates a promising generalization in various SOC and loading situations. Results highlight the power of computational modeling to understand the underlying mechanism of safety issues in energy storage systems in a broader context.