Research on Three-Dimensional Localization of Pressure Relief Sound Source of Energy Storage Battery Pack Based on BP Neural Networks

Thermal runaway events in energy storage power stations exhibit distinct acoustic characteristic signals. Three-dimensional localization of the sound source is of significant importance for achieving precise firefighting interventions. This study proposes an internal fault localization method for power stations based on the acoustic signals from pressure relief valves of energy storage battery packs. By deploying four microphones to capture the acoustic signals from the battery pack pressure relief valves, the spatial location of the faulty pack can be calculated using a three-dimensional localization model trained on a Back Propagation (BP) neural network. The localization accuracy of this model is better than 0.5 m, with the majority of measurement points achieving an accuracy of less than 0.3 m, meeting the requirements for battery pack-level localization. A key advantage of this method is its low sensitivity to time delay measurement errors caused by reverberation and reflections in enclosed spaces. Reliable and stable localization of pressure relief sound sources can be achieved through multiple training sessions within the battery cabin, which facilitates practical deployment.