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Adaptation application to engine modelling
KTH, School of Industrial Engineering and Management (ITM), Energy Technology. Cranfield University, United Kingdom .
2007 (English)In: Proceedings of the ASME Power Conference 2007, ASME Press, 2007, 39-48 p.Conference paper (Refereed)
Abstract [en]

The optimisation of engine performance by predictive means can help save cost and reduce environmental pollution. This can be achieved by developing a performance model which depicts the operating conditions of a given engine. Such models can also be used for diagnostic and prognostic purposes. Creating such models requires a method that can cope with the lack of component parameters and some important measurement data. This kind of method is said to be adaptive since it predicts unknown component parameters that match available target measurement data. In this paper an industrial aeroderivative gas turbine has been modelled at design and off-design points using an adaptation approach. At design point, a sensitivity analysis has been used to evaluate the relationships between the available target performance parameters and the unknown component parameters. This ensured the proper selection of parameters for the adaptation process which led to a minimisation of the adaptation error and a comprehensive prediction of the unknown component and available target parameters. At offdesign point, the adaptation process predicted component map scaling factors necessary to match available off-design point performance data.

Place, publisher, year, edition, pages
ASME Press, 2007. 39-48 p.
Keyword [en]
Adaptation, Engine, Model and performance
National Category
Energy Engineering
URN: urn:nbn:se:kth:diva-155549DOI: 10.1115/POWER2007-22139ISI: 000250717400004ScopusID: 2-s2.0-37249075346ISBN: 0791842738ISBN: 978-079184273-7OAI: diva2:762380
2007 ASME Power Conference, 17 July 2007 through 19 July 2007, San Antonio, TX, United States

QC 20141111

Available from: 2014-11-11 Created: 2014-11-07 Last updated: 2014-11-11Bibliographically approved

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