DocumentCode :
2655182
Title :
A comparative study of Li-ion battery models and nonlinear dual estimation strategies
Author :
Farag, M.S. ; Ahmed, R. ; Gadsden, S.A. ; Habibi, S.R. ; Tjong, J.
Author_Institution :
McMaster Univ., Hamilton, ON, Canada
fYear :
2012
fDate :
18-20 June 2012
Firstpage :
1
Lastpage :
8
Abstract :
Due to their high energy density, durability, low cost, and inherent safety, lithium-ion (Li-ion) batteries are quickly becoming the most popular energy storage method for electric vehicles. Difficulty arises in properly modeling these types of batteries due to a large number of parameters and different architectures. This paper looks at studying six different Li-ion battery models found in literature, and compares their relative performance based on a benchmark dataset. Kalman-based filtering strategies are also employed to estimate important battery parameters such as capacitance, hysteresis, and state of charge (SOC). In addition, the relatively new smooth variable structure filter (SVSF) is used and compared with these Kalman-based strategies.
Keywords :
Kalman filters; battery powered vehicles; energy storage; lithium; nonlinear estimation; parameter estimation; secondary cells; Kalman-based filtering strategy; Li; SOC; SVSF; battery parameter estimation; benchmark dataset; capacitance; electric vehicle; energy density; energy storage method; hysteresis; li-ion battery model; nonlinear dual estimation strategy; smooth variable structure filter; state of charge; Adaptation models; Batteries; Estimation; Hysteresis; Kalman filters; Mathematical model; System-on-a-chip;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Transportation Electrification Conference and Expo (ITEC), 2012 IEEE
Conference_Location :
Dearborn, MI
Print_ISBN :
978-1-4673-1407-7
Electronic_ISBN :
978-1-4673-1406-0
Type :
conf
DOI :
10.1109/ITEC.2012.6243485
Filename :
6243485
Link To Document :
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