Abstract
The cycle life of batteries and battery-supercapacitor hybrid systems was predicted using artificial neural networks. The presented techniques are able to predict the cycle life of a device based on a short (around 4% of the average cycle life) initial segment of the discharge curve. the prediction showed good performance with a correlation coefficient above 0.95. We were able to improve the predication further by considering readily available measurements of the device and usage. ©The Electrochemical Society.
Recommended Citation
T. Weigert et al., "Cycle Life Prediction of Battery-supercapacitor Hybrids using Artificial Neural Networks," ECS Transactions, vol. 28, no. 22, pp. 35 - 42, IOP Publishing, Jan 2010.
The definitive version is available at https://doi.org/10.1149/1.3492329
Department(s)
Computer Science
International Standard Book Number (ISBN)
978-156677848-0;978-160768198-4
International Standard Serial Number (ISSN)
1938-6737; 1938-5862
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 IOP Publishing, All rights reserved.
Publication Date
01 Jan 2010
