A Literature Review on Remaining Useful Life Prediction of Lithium-Ion Batteries

Lithium-ion batteries have evolved into a critical part of the power supply system, and predicting their remaining usable life is critical to ensuring their reliability. Intricate operational characteristics of lithium-ion batteries with the changes with their model parameter as they age, improving the accurateness in the online remaining usable life forecast is hard yet important for the reliable power supply application. We've analyzed research papers in different aspects like: dataset utilized for evaluations, different techniques utilized for Machine Learning, Analysis of SOH prediction, classification of RUL prediction, filtering based methods as well as different data-driven algorithms. The paper also summarizes, each of for accuracy, error, and cost. Moreover, the current challenges faced in the RUL prediction will be rendered, which will stand a milestone for the future investigators.