Title :
Li-ion Polymer battery SOC estimation using Bayesian filtering
Author :
Zhao, Qi ; Wenzl, Heinz ; Bohn, Christian
Author_Institution :
Inst. for Electr. Inf. Technol., Clausthal Univ. of Technol., Clausthal-Zellerfeld, Germany
Abstract :
Accurate state-of-charge information is of great importance for battery management system. In this paper, a novel electrical equivalent model for polymer Li-Ion battery is developed and Bayesian filtering methods are employed to estimate the SOC of Lithium-ion Polymer battery accurately.
Keywords :
Bayes methods; battery management systems; filtering theory; lithium; secondary cells; Bayesian filtering methods; Li; battery management system; electrical equivalent model; polymer battery SOC estimation; state-of-charge information; Batteries; Bayesian methods; Integrated circuit modeling; Kalman filters; Mathematical model; System-on-a-chip; Bayesian filtering; Li-ion Polymer battery; SOC estimation; Sigma point Kalman filter; electrical equivalent model;
Conference_Titel :
Control Conference (CCC), 2012 31st Chinese
Conference_Location :
Hefei
Print_ISBN :
978-1-4673-2581-3
