Lithium-ion battery energy storage systems are confronted with severe safety challenges of thermal runaway. The flammable gases they eject can easily cause secondary explosion and fire when diffused in a sealed cabin. Most existing studies have overlooked the diffusion behavior of the electrolyte vapor

which is dominated by mass and has a complex composition

resulting in significant deviations in explosion risk assessment. We proposed a method that integrates innovative experimental measurement and numerical simulation. Firstly

an electrolyte vapor sensor based on the principle of photoelectric conversion was designed. Subsequently

a distributed sensor array was deployed in the energy storage cabin

and a 280 Ah lithium battery thermal runaway experiment was conducted inside the cabin. By using this array

a three-dimensional concentration field sequence of the evolution of the electrolyte vapor cloud was obtained. Finally

computational fluid dynamics(CFD) multi-component gas simulation was used to simulate the diffusion of gases such as hydrogen and carbon monoxide. By integrating experimental steam data with simulated gas data

the lower explosive limit (LEL) at each point in space was calculated in real time

and an explosion risk cloud map evolving over time was drawn for analysis. The results show that the diffusion characteristics of the electrolyte vapor are significantly different from those of other low-molecular-weight gases. The explosion risk area after mixing first appears in the intense gas production stage and finally concentrates at the top and front of the cabin. This study not only provides a visual observation method for the vapor diffusion characteristics of the electrolyte

but also combines simulation to construct a high-fidelity dynamic risk assessment framework

which can intuitively identify high-risk areas and high-risk periods during the thermal runaway process

providing a crucial theoretical basis and data support for the safe design of energy storage cabins.