Detection of electric arcs in large batteries

This paper addresses the precocious detection of electric arcs in an electric vehicle battery generated by a connector fault. The detection principle is based on the acoustic emission of the arc. First, the identification of the electric arc acoustic signature as well as disturbances in the environment of detection has been realized. Subsequently, we have been focused on the propagation of acoustic waves emitted by the arc in the confined environment of the battery. We proposed a detection method based on correlation whose performance was evaluated. Finally, a localization system based on signal time-difference-of-arrival estimation and triangulation is described and assessed. A demonstrator has been developed and validates the detection performance.