Li-Ion Battery State of Health Estimation and Remaining Useful Life Prediction through a Model-Data-Fusion Method

Author(s):  
Zhiqiang Lyu ◽  
Renjing Gao ◽  
Lin Chen
2013 ◽  
Vol 37 (4) ◽  
pp. 313-322 ◽  
Author(s):  
Seong Heum Sim ◽  
Jin Hyuk Gang ◽  
Dawn An ◽  
Sun Il Kim ◽  
Jin Young Kim ◽  
...  

2013 ◽  
Vol 724-725 ◽  
pp. 797-803 ◽  
Author(s):  
Jin Zhang ◽  
An Tong Gao ◽  
Rong Gang Chen ◽  
Yu Sheng Han

The Li-ion battery has high discharge voltage, long cycle life, good safety performance, no memory effect and other advantages. So it has being more and more used and concerned. This paper reviews various aspects of recent research and developments in Li-ion battery prognostics and health monitoring,and summarizes the techniques,algorithms and models used for state-of-charge estimation,voltage estimation,capacity estimation and remaining-useful-life prediction. Especially for state-of-charge estimation, this paper summed up many methods, such as current integration method, open circuit voltage method, Fuzzy logic, Autoregressive moving average model, Electrochemical impedance spectroscopy, Support vector machine and support vector machine based on Extended Kalman filter. And their advantages and disadvantages are summarized.


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