DocumentCode :
1769307
Title :
An approach for state of charge estimation of Li-ion battery based on Thevenin equivalent circuit model
Author :
Bing Chen ; Haodong Ma ; Hongzheng Fang ; Huanzhen Fan ; Kai Luo ; Bin Fan
Author_Institution :
Coll. of Electron. Eng., Naval Univ. of Eng., Wuhan, China
fYear :
2014
fDate :
24-27 Aug. 2014
Firstpage :
647
Lastpage :
652
Abstract :
Recently, Lithium-ion battery has been used in electric vehicles, portable electronic devices, even aerospace and other fields, since its many advantages compare to the other conventional batteries. At the same time, the estimation of state of charge (SOC), cycle life and other performance for lithium-ion batteries become research focus in the related fields, in order to ensure that the operation of lithium-ion battery-powered devices and systems were safe, reliable and economic. Efficient and accurate state of charge estimation for the Lithium-ion batteries can help to optimize the charging/discharging and operation strategy, prevent the occurrence due to losing power unexpectedly from happening, and decrease the cost of the consequent accidents. Open circuit voltage is often used to estimate SOC of the battery, unfortunately, it is not easy to measure usually, and the hysteresis effect is a big challenge. In this paper, we built a Thevenin equivalent circuit model and identified the relationship of SOC compare to battery terminal voltage and charging/discharging current, and then estimated the SOC with relevance vector machine. The experimental results proved the feasibility of the methodology, which can provide potential application for SOC prediction.1.
Keywords :
power engineering computing; secondary cells; support vector machines; SOC; Thevenin equivalent circuit model; battery terminal voltage; charging/discharging current; cycle life; lithium-ion battery; relevance vector machine; state of charge estimation; Batteries; Equivalent circuits; Estimation; Integrated circuit modeling; Mathematical model; System-on-chip; Voltage measurement; Li-ion battery; SOC estimation; Thevenin equivalent circuit model; model identification; relevance vector machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Prognostics and System Health Management Conference (PHM-2014 Hunan), 2014
Conference_Location :
Zhangiiaijie
Print_ISBN :
978-1-4799-7957-8
Type :
conf
DOI :
10.1109/PHM.2014.6988253
Filename :
6988253
Link To Document :
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