DocumentCode :
2633036
Title :
Battery hysteresis modeling for state of charge estimation based on Extended Kalman Filter
Author :
Qiu, Shiqi ; Chen, Zhihang ; Masrur, M. Abul ; Murphey, Yi Lu
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Michigan-Dearborn, Dearborn, MI, USA
fYear :
2011
fDate :
21-23 June 2011
Firstpage :
184
Lastpage :
189
Abstract :
This paper presents our research in battery SOC estimation for intelligent battery management. We developed a SOC estimation algorithm based on Extended Kalman Filter to model battery hysteresis effects. The proposed method has been evaluated using data acquired from two different batteries, a lithium-ion battery U1-12XP and a NiMH battery with 1.2V and 3.4 Ah. Our experiments show that our method, which models battery hysteresis based on separated charge and discharge OCV curves gave the top performances in estimating SOC in both batteries when compared with other advanced methods.
Keywords :
Kalman filters; battery management systems; secondary cells; state estimation; U1-12XP; battery SOC estimation; battery hysteresis modeling; extended Kalman filter; intelligent battery management; lithium-ion battery; state of charge estimation; voltage 1.2 V; Batteries; Battery charge measurement; Discharges; Estimation; Hysteresis; System-on-a-chip; Voltage measurement; Kalman filtering; battery SOC; intelligent battery management;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics and Applications (ICIEA), 2011 6th IEEE Conference on
Conference_Location :
Beijing
ISSN :
pending
Print_ISBN :
978-1-4244-8754-7
Electronic_ISBN :
pending
Type :
conf
DOI :
10.1109/ICIEA.2011.5975576
Filename :
5975576
Link To Document :
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