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Implementation of Neural Network Models for Parameter Estimation of a PEM-Electrolyzer
Citation
Becker, S and Karri, V, Implementation of Neural Network Models for Parameter Estimation of a PEM-Electrolyzer, Journal of Advanced Computational Intelligence, 14, (6) pp. 735-740. ISSN 1343-0130 (2010) [Refereed Article]
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Copyright Statement
Copyright 2010 Fuji Technology Press.
Official URL: http://www.fujipress.jp/JACIII/index.html
DOI: doi:10.20965/jaciii.2010.p0735
Abstract
Predictive models were built using neural networks for hydrogen flow rate, electrolyzer system-efficiency and stack-efficiency respectively. A comprehensive experimental database forms the foundation for the predictive models. It is argued that, due to the high costs associated with the hydrogen measuring equipment; these reliable predictive models can be implemented as virtual sensors. These models can also be used online for monitoring and safety of hydrogen equipment. The quantitative accuracy of the predictive models is appraised using statistical techniques. These mathematicalmodels are found to be reliable predictive tools with an excellent accuracy of ±3% compared with experimental values. The predictive nature of thesemodels did not show any significant bias to either over prediction or under prediction. These predictive models, built on a sound mathematical and quantitative basis, can be seen as a step towards establishing hydrogen performance prediction models as generic virtual sensors for wider safety and monitoring applications.
Item Details
Item Type: | Refereed Article |
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Research Division: | Information and Computing Sciences |
Research Group: | Computer vision and multimedia computation |
Research Field: | Computer vision |
Objective Division: | Information and Communication Services |
Objective Group: | Communication technologies, systems and services |
Objective Field: | Network systems and services |
UTAS Author: | Becker, S (Mr Steffen Becker) |
ID Code: | 66904 |
Year Published: | 2010 |
Deposited By: | Engineering |
Deposited On: | 2011-02-17 |
Last Modified: | 2012-07-03 |
Downloads: | 0 |
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