Towards an Accurate Aerodynamic Performance Analysis Methodology of Cross-Flow Fans

Rania M. Himeur, Sofiane Khelladi, Mohamed Abdessamed Ait Chikh, Hamid Reza Vanaei, Idir Belaidi and Farid Bakir
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Rania M. Himeur: LEMI, Faculty of Technology, University M’Hamed Bougara of Boumerdes, Boumerdes 35000, Algeria
Sofiane Khelladi: Arts et Metiers Institute of Technology, CNAM, LIFSE, HESAM University, 75013 Paris, France
Mohamed Abdessamed Ait Chikh: LEMI, Faculty of Technology, University M’Hamed Bougara of Boumerdes, Boumerdes 35000, Algeria
Hamid Reza Vanaei: Arts et Metiers Institute of Technology, CNAM, LIFSE, HESAM University, 75013 Paris, France
Idir Belaidi: LEMI, Faculty of Technology, University M’Hamed Bougara of Boumerdes, Boumerdes 35000, Algeria
Farid Bakir: Arts et Metiers Institute of Technology, CNAM, LIFSE, HESAM University, 75013 Paris, France

Energies, 2022, vol. 15, issue 14, 1-28

Abstract: Cross-flow fans (CFFs) have become increasingly popular in recent years. This is due to their use in several domains such as air conditioning and aircraft propulsion. They also show their utility in the ventilation system of hybrid electric cars. Their high efficiency and performance significantly rely on the design parameters. Up to now, there is no general approach that predicts the CFFs’ performance. This work describes a new methodology that helps deduce the performance of CFFs in turbomachinery, using both analytical modeling and experimental data. Two different loss models are detailed and compared to determine the performance–pressure curves of this type of fan. The efficiency evaluation is achieved by realizing a multidisciplinary study, computational fluid dynamics (CFD) simulations, and an optimization algorithm combined to explore the internal flow field and obtain additional information about the eccentric vortex, to finally obtain the ultimate formulation of the Eck/Laing CFF efficiency, which is validated by the experimental results with good agreement. This approach can be an efficient tool to speed up the cross-flow fans’ design cycle and to predict their global performance.

Keywords: cross-flow fan; performance prediction; turbomachinery; fluid machinery; aerodynamics; internal flow; computational fluid dynamics (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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