DocumentCode :
601864
Title :
Online State of Charge estimation in electrochemical batteries: Application of pattern recognition techniques
Author :
Ying Xiao ; Chenjie Lin ; Fahimi, B.
Author_Institution :
Renewable Energy & Vehicular Technol. Lab., Univ. of Texas as Dallas, Dallas, TX, USA
fYear :
2013
fDate :
17-21 March 2013
Firstpage :
2474
Lastpage :
2478
Abstract :
High precision State-of-Charge (SOC) estimation in electrochemical batteries is an integral part of an effective energy management system. This paper proposes two pattern recognition methods for online estimation of SOC using the impulse response of the battery. By capturing the impulse responses at various levels of SOC, one can use the proposed pattern recognition methods in time domain or in frequency domain to determine the SOC of the battery. These two techniques have been studied in details and their precisions have been compared by simulation and experiment. The results show that the frequency domain method offers higher resolution in SOC estimation and lower computational complexity.
Keywords :
cells (electric); energy management systems; frequency-domain analysis; pattern recognition; time-domain analysis; transient response; battery response; computational complexity; electrochemical batteries; energy management system; frequency domain method; high precision SOC estimation; high precision state-of-charge estimation; impulse response; online SOC estimation; online state of charge estimation; pattern recognition techniques; time domain method;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Applied Power Electronics Conference and Exposition (APEC), 2013 Twenty-Eighth Annual IEEE
Conference_Location :
Long Beach, CA
ISSN :
1048-2334
Print_ISBN :
978-1-4673-4354-1
Electronic_ISBN :
1048-2334
Type :
conf
DOI :
10.1109/APEC.2013.6520643
Filename :
6520643
Link To Document :
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