State-of-Health Estimation of Lithium-ion Battery Based on Data-driven

Abstract

With the increase of the output of electric vehicles, it is of great significance to predict the health status of lithium-ion batteries for the safe operation of electric vehicles. In this paper, some common data-driven methods for health state estimation of lithium-ion batteries are reviewed. First of all, this paper introduces the charge and discharge principle of lithium-ion battery. Then four common SOH prediction methods are introduced, and their advantages and disadvantages are summarized and reviewed. In the part of introducing the data-driven research on the health status of lithium-ion battery, it focuses on the application of machine learning and deep neural network. Finally, the research prospect of health state estimation of lithium-ion battery is explained.