Abstract
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.
Highlights
The battery of an EV is made of several modules and each module consists of several battery cells arranged in series and in parallels
Because of the many disturbing transient signals present on the voltage and the current measurements made on the battery, we propose an innovative method based on the acoustic emission of electric arcs
An electric arc can be produced when two contacts initially driven by a current are separated
Summary
The battery of an EV is made of several modules and each module consists of several battery cells arranged in series and in parallels This type of arrangement leads to a high number of internal connections. A break at the connection may cause electric arcs that can be maintained because of DC current flowing into the battery. These arcs can cause overheating and even thermal runaway in the battery which can lead to dangerous fires. Because of the many disturbing transient signals present on the voltage and the current measurements made on the battery, we propose an innovative method based on the acoustic emission of electric arcs. We propose a theoretical and experimental study of electric arcs
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