State-Of-Charge Prediction of Batteries and Battery-Supercapacitor Hybrids Using Artificial Neural Networks

Abstract

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.

Department(s)

Computer Science

Sponsor(s)

Electrovaya Inc.
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)

0378-7753

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2011 Elsevier, All rights reserved.

Publication Date

01 Apr 2011

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