Predictive maintenance strategies for telecom backup batteries involve using real-time data, IoT sensors, and machine learning to predict failures before they occur. These strategies monitor voltage, temperature, and discharge cycles to optimize battery health, reduce downtime . In the digital era, lithium-ion batteries (lithium batteries for short) have become a crucial force in energy transition considering the advantages of high energy density, 1 long lifecycles, and easy deployment of intelli-gent technologies. Lithium batteries are widely used, from small-sized. Accurate battery lifetime prediction is important for preventative maintenance, war-ranties, and improved cell design and manufacturing. However, manufacturing variability and usage-dependent degradation make life prediction challenging.
