End of Life Detection of Li-ion Primary Cell Battery Based on Closed-Loop Voltage and Ambient Temperature

This paper deals with the detection of Lithium-ion battery end of life based on its voltage and ambient temperature measured every 1 hour. A methodology for classifying the battery status (normal or degradation mode) is presented. The batterys entropy and enthalpy have also been estimated. The classification has been performed using three algorithms: Interquartile, Isolation Forest, and One-Class SVM. The metrics used to compare these methods are F1-score and Average F-measure. The findings showed that enthalpy has promising results in detecting the battery end of life. Copyright (c) 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)