A Critical Review of Online Battery Remaining Useful Lifetime Prediction Methods

Lithium-ion batteries play an important role in our daily lives. The prediction of the remaining service life lithium-ion has become issue. This article reviews methods for predicting from three aspects: machine learning, adaptive filtering, and random processes. purpose this study is to review, classify compare different proposed literature predict batteries. first summarizes classifies various that have been recent years. On basis, by selecting specific criteria evaluate accuracy models, find most suitable method. Finally, summarize development methods. According research article, average learning 32.02% higher than other two methods, cycle 9.87% shorter