Battery hysteresis modeling for state of charge estimation based on Extended Kalman Filter

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 lithi...

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Bibliographic Details
Published in2011 6th IEEE Conference on Industrial Electronics and Applications pp. 184 - 189
Main Authors Shiqi Qiu, Zhihang Chen, Masrur, M. Abul, Murphey, Yi Lu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2011
Subjects
Batteries
Battery charge measurement
battery SOC
Discharges
Estimation
Hysteresis
intelligent battery management
Kalman filtering
System-on-a-chip
Voltage measurement
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Summary: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.
ISBN:9781424487547
1424487544
ISSN:2156-2318
DOI:10.1109/ICIEA.2011.5975576