Predictive maintenance is a strategy that identifies potential failures in advance and schedules maintenance by real-time monitoring of equipment status, collecting operating data, and combining data analysis or machine learning models. It is more efficient than regular maintenance, reducing unexpected downtime and lowering maintenance costs. In battery systems, predictive maintenance can be achieved through trend analysis of indicators such as cell temperature, voltage, and internal resistance; prediction of aging rate or failure probability by AI or data-driven models; and triggering early warnings by real-time alarm systems to prevent safety risks such as thermal runaway.
