Advanced control algorithm for FADEC systems in the next generation of turbofan engines to minimize emission levels

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dc.contributor.authorAghasharifian Esfahan, Majid
dc.contributor.authorNamazi, Mohammadmehdi
dc.contributor.authorNikolaidis, Theoklis
dc.contributor.authorJafari, Soheil
dc.date.accessioned2022-05-25T09:37:30Z
dc.date.available2022-05-25T09:37:30Z
dc.date.issued2022-05-23
dc.description.abstractNew propulsion systems in aircrafts must meet strict regulations and emission limitations. The Flightpath 2050 goals set by the Advisory Council for Aviation Research and Innovation in Europe (ACARE) include reductions of 75%, 90%, and 65% in CO2, NOx, and noise, respectively. These goals are not fully satisfied by marginal improvements in gas turbine technology or aircraft design. A novel control design procedure for the next generation of turbofan engines is proposed in this paper to improve Full Authority Digital Engine Control (FADEC) systems and reduce the emission levels to meet the Flightpath 2050 regulations. Hence, an Adaptive Network–based Fuzzy Inference System (ANFIS), nonlinear autoregressive network with exogenous inputs (NARX) techniques, and the block-structure Hammerstein–Wiener approach are used to develop a model for a turbofan engine. The Min–Max control structure is chosen as the most widely used practical control algorithm for gas turbine aero engines. The objective function is considered to minimize the emission level for the engine in a pre-defined maneuver while keeping the engine performance in different aspects. The Genetic Algorithm (GA) is applied to find the optimized control structure. The results confirm the effectiveness of the proposed approach in emission reduction for the next generation of turbofan engines.en_UK
dc.identifier.citationAghasharifian Esfahani M, Namazi M, Nikolaidis T, Jafari S. (2022) Advanced control algorithm for FADEC systems in the next generation of turbofan engines to minimize emission levels, Mathematics, Volume 10 Issue 10, May 2022, Article number 1780en_UK
dc.identifier.issn2227-7390
dc.identifier.urihttps://doi.org/10.3390/math10101780
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/17959
dc.language.isoenen_UK
dc.publisherMDPIen_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectemission reductionen_UK
dc.subjectgas turbine aero enginesen_UK
dc.subjectartificial neural networksen_UK
dc.subjectadaptive network-based fuzzy inference systemen_UK
dc.titleAdvanced control algorithm for FADEC systems in the next generation of turbofan engines to minimize emission levelsen_UK
dc.typeArticleen_UK

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