Review of Remaining Useful Life for Lithium-Ion Batteries

In recent years, with the swift progression of electric vehicles, new energy storage, intelligent robots and other fields, lithium-ion batteries have been widely used to meet the needs of high energy density, high output voltage and wide operating range of the battery. Typically, lithium-ion batteries operate under complex conditions and are accompanied by physical and chemical changes within them. These factors lead to irreversible physical and chemical changes in lithium-ion batteries, and their potential pitfalls can lead to abnormal system operation and even catastrophic events in electrical systems. Therefore, accurate RUL prediction can effectively indicate the health condition of Li-ion battery, and at the same time can ensure the reliability and safety of the system, which is important for the safe operation of the whole Li-ion battery system, and its remaining life assessment has become a research hotspot in the related fields of electrochemistry, intelligent detection and reliability, and has a good development prospect. Therefore, this paper analyzes the common methods and application status of remaining life prediction of lithium-ion batteries, brings together the prediction methods based on model-based methods, data-driven methods and fusion-based methods, and analyzes the advantages and disadvantages of each method to provide reference for relevant technical personnel.