Lithium-ion batteries life prediction method basedon degenerative characters and improved particle filter

Abstract

Recently, in order to make sure that the operation of Lithium-ion battery-powered devices and systems are safe, reliable and economic, it is very important to predict life and other performances for Lithium-ion batteries. Efficient and accurate state of life prediction for Lithium-ion batteries can be used to optimize the charging/discharging and operation strategy. Thus it could prevent operation failure due to unexpected power loss, and decrease the cost of consequent accidents. Among current prognostic methods, particle filter (PF) method is often used to estimate the life of batteries. However, in traditional PF methods, the original degenerative characters are much affected by outside interference. This means that it might not be suitable to apply these characters directly in prediction, because the accuracy of the prediction result is excessively depended on the prediction model. In this paper, we propose a prediction method based on degenerative characters and improved particle filter to estimate the cycle life of Lithium-ion batteries. The experimental results proved the feasibility of the proposed prediction method, which can provide potential application for remain useful life prediction.