Capacity prediction of lithium-ion battery using UKF based on different C-rate

In this paper, an algorithm is proposed to predict replacement time by estimating the life span of the lithium-ion batteries applied to ESS (Energy storage systems). The batteries do not recover as deterioration progresses due to irreversible reactions. When the capacity of the battery drops to 80% of its initial capacity, it is said that the battery has reached EOL (End-of-life), and the battery needs to be replaced. In the process of estimating the capacity of a battery, it can be predicted by applying an empirical model based UKF (Unscented Kalman filter). However, since the rate at which capacity decreases depends on the load profile of batteries, it is necessary to analyze the characteristics. This paper analyzes the degradation characteristics according to the current rate applied to batteries and performs the resulting capacity prediction.