TY - GEN
T1 - Estimating the remaining useful life of Li-ion batteries with a Bayesian updating model
AU - Hai, Yizhen
AU - Tang, Jie
AU - Tsui, Kwok-Leung
PY - 2012
Y1 - 2012
N2 - 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. © 2012 IEEE.
AB - 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. © 2012 IEEE.
KW - Battery degradation
KW - Bayesian updating
KW - remaining useful life
UR - http://www.scopus.com/inward/record.url?scp=84903827310&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84903827310&origin=recordpage
U2 - 10.1109/IEEM.2012.6838119
DO - 10.1109/IEEM.2012.6838119
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781467329453
SP - 2113
EP - 2116
BT - IEEE International Conference on Industrial Engineering and Engineering Management
PB - IEEE Computer Society
T2 - 2012 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM 2012)
Y2 - 10 December 2012 through 13 December 2012
ER -
