Journal
JOURNAL OF POWER SOURCES
Volume 268, Issue -, Pages 758-764Publisher
ELSEVIER
DOI: 10.1016/j.jpowsour.2014.06.099
Keywords
State of charge; State of health; Lead-acid battery; Symbolic dynamic filtering; k-NN regression
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This short paper presents a recently reported dynamic data-driven method, Symbolic Dynamic Filtering (SDF), for real-time estimation of the state-of-health (SOH) and state-of-charge (SOC) in lead-acid batteries, as an alternative to model-based analysis techniques. In particular, SOC estimation relies on a k-NN regression algorithm while SOH estimation is obtained from the divergence between extracted features. The results show that the proposed data-driven method successfully distinguishes battery voltage responses under different SOC and SOH situations. (C) 2014 Elsevier B.V. All rights reserved.
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