Journal
JOURNAL OF POWER SOURCES
Volume 196, Issue 8, Pages 4061-4066Publisher
ELSEVIER
DOI: 10.1016/j.jpowsour.2010.10.075
Keywords
State-of-charge prediction; Battery lifetime prediction; Battery-supercapacitor hybrid; Pulse discharge; Artificial neural networks
Funding
- Ontario Center of Excellence
- Electrovaya Inc.
- NSERC Canada
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The state-of-charge (SOC) of batteries and battery-supercapacitor hybrid systems is predicted using artificial neural networks (ANNs). Our technique is able to predict the SOC of energy storage devices based on a short initial segment (less than 4% of the average lifetime) of the discharge curve. The prediction shows good performance with a correlation coefficient above 0.95. We are able to improve the prediction further by considering readily available measurements of the device and usage. The prediction is further shown to be resilient to changes in operating conditions or physical structure of the devices. (C) 2010 Elsevier B.V. All rights reserved.
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