State-Of-Charge Prediction of Batteries and Battery-Supercapacitor Hybrids Using Artificial Neural Networks
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.
T. Weigert et al., "State-Of-Charge Prediction of Batteries and Battery-Supercapacitor Hybrids Using Artificial Neural Networks," Journal of Power Sources, Elsevier, Apr 2011.
The definitive version is available at https://doi.org/10.1016/j.jpowsour.2010.10.075
Natural Sciences and Engineering Research Council of Canada
Ontario Center of Excellence
Keywords and Phrases
Artificial Neural Networks; Battery Lifetime Prediction; Battery- Supercapacitor Hybrid; Pulse Discharge; State-Of-Charge Prediction
International Standard Serial Number (ISSN)
Article - Journal
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