Title :
Estimating the remaining useful life of Li-ion batteries with a Bayesian updating model
Author :
Yizhen Hai ; Jie Tang ; Kwok-Leung Tsui
Author_Institution :
Dept. of Syst. Eng. & Eng. Manage., City Univ. of Hong Kong, Hong Kong, China
Abstract :
In this paper, we studied a prediction method for the remaining useful life of Lithium-ion batteries. First, a battery degradation model is obtained based on exponential degradation signal modeling with data collected from second generation 18650-size lithiumion cells from NASA. Using a Bayesian updating procedure, we then obtain the conditional cumulative distribution function (cdf) of the residual life of the battery at various time intervals. Finally, we discuss this method and draw the conclusion that the model is accurate in terms of prediction.
Keywords :
Bayes methods; exponential distribution; secondary cells; Bayesian updating model; NASA; battery degradation model; battery residual life; cdf; cumulative distribution function; exponential degradation signal modeling; lithium-ion batteries; second generation 18650-size lithium-ion cells; Batteries; Bayes methods; Data models; Degradation; Impedance; NASA; Uncertainty; Battery degradation; Bayesian updating; remaining useful life;
Conference_Titel :
Industrial Engineering and Engineering Management (IEEM), 2012 IEEE International Conference on
Conference_Location :
Hong Kong
DOI :
10.1109/IEEM.2012.6838119
