Risk analysis of fire and explosion in battery energy storage systems under high-speed impact

Fire and explosion accidents in battery energy storage systems (BESSs) triggered by high-speed impact scenarios can lead to severe consequences. To enhance the uncertainty representation of extreme environment with limited data and high uncertainty, this paper proposes a risk analysis method based on the integration of interval type 2 fuzzy set (IT2FS) theory and enhanced expert weighting scheme. This method takes into account the experts’ professional background, experience, and the judgment reliability, and refines the weight calculation method to reduce the subjectivity and uncertainty of event probability estimation. Based on the constructed BN, sensitivity analysis is applied to identify the key risk nodes that influence fire and explosion accidents, and corresponding risk mitigation strategies are discussed. Furthermore, the combined effects of expert expertise and opinion consistency on the probability aggregation are examined through a parametric sensitivity analysis of the weighting parameter. The results reveal the way in which expert dominance and group consensus influence the risk propagation under extreme impact conditions. The obtained results confirm the applicability of the developed method for risk evaluation in extreme mechanical environments.