In the realm of energy storage and safety, a team of researchers from the University of Alberta, including Yukta Pareek, Khadija Omar Said, Satadru Dey, and Ashish Ranjan Kumar, have developed a novel approach to monitor and manage potential hazards associated with the use of large-format lithium-ion batteries (LIBs) in underground mining operations. Their work, published in the journal “Safety Science,” focuses on creating a cyber-physical systems (CPS) framework to track temperature and smoke dynamics following a thermal runaway event in LIBs.
Underground mining operations are increasingly turning to LIBs to power their equipment due to their high energy density, long cycle life, and favorable safety record. Additionally, LIBs offer low noise, heat, and emission footprints, creating a more conducive workplace environment. However, the risk of thermal runaway—a situation where a battery overheats and can potentially catch fire—poses a significant safety concern. In the confined spaces of underground mines, the combustion products, including toxic emissions, can rapidly spread through the ventilation network, endangering miners.
The researchers developed CPS models that integrate the cyber framework of the mine’s supervisory control center with the physical underground mine. These models are trained on high-fidelity computational fluid dynamics (CFD) data sets, allowing them to provide accurate estimates of temperature and smoke concentration evolution in the underground mine tunnels. High-fidelity models, while detailed, are computationally intensive and impractical for large underground mine volumes, complex geometries, and long-duration combustion events. The CPS approach mitigates these computation-related issues.
The practical application of this research is significant for the energy and mining sectors. By implementing these CPS models, mine operators can make informed decisions during emergencies, enhancing the safety of underground mining personnel. This framework can also be adapted for other industries where LIBs are used in confined spaces, ensuring better safety protocols and emergency response strategies. The research underscores the importance of integrating advanced modeling techniques with physical systems to manage risks effectively in energy storage applications.
This article is based on research available at arXiv.