Fault diagnosis of lithium-ion battery energy storage systems based on local outlier factor

Abstract

Lithium-ion batteries may lead to fire and other accidents when working under overcharge， high temperature， and external short circuits. The faults can be prevented from escalating to thermal runaway through early fault diagnosis and fault location of lithium-ion batteries and corresponding measures in time. To this end， based on the operational data of the lithium-ion battery energy storage system， the local outlier factor （LOF） algorithm is used for fault diagnosis and analysis. By calculation of the single-day and multi-day voltage operation data， the specific location of the faulty battery is determined， and the abnormal condition of the battery is analyzed. The research results verify the effectiveness of the LOF algorithm applied to the fault diagnosis of the lithium-ion battery energy storage system.

Keywords

• lithium-ion battery
• energy storage system
• operational data
• lof
• fault diagnosis