Akademik Veri Yönetim Sistemi
Sustainable Aviation, Springer Nature, ss.415-426, 2026
Thermal runaway in lithium-ion batteries remains a critical safety concern across electric vehicles, stationary storage systems, and portable electronics. Computational fluid dynamics has emerged as a powerful tool to investigate the coupled thermal, electrochemical, mechanical, and fluid processes underlying initiation, propagation, and mitigation of these events. This review consolidates recent advances in computational fluid dynamics -based modeling of thermal runaway, spanning single-cell simulations, module- and pack-level propagation studies, and multiphysics coupling strategies. Emphasis is placed on reaction kinetics representation, heat generation modeling, vent gas dynamics, and integration of mechanical deformation effects. The potential of artificial intelligence and deep learning to augment computational fluid dynamics frameworks through data-driven parameter estimation and real-time prediction is also discussed. Cross-sector perspectives highlight application-specific modeling requirements and challenges. Key gaps remain in accurately capturing gas–solid interactions, scaling from cell to pack, and validating high-fidelity simulations under realistic abuse conditions. Insights provided herein aim to guide the development of robust, predictive models to support safer battery system design and management.