An Experimental Study of the Aeroacoustic Properties of a Propeller in Energy Harvesting Configuration

Paolo Candeloro, Edoardo Martellini, R. Nederlof, T. Sinnige, Tiziano Pagliaroli

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The aim of the present manuscript is to investigate the noise footprint of an isolated propeller in different flight configurations for the propulsion of a hybrid-electric aircraft. Experimental tests were performed at the Low-Turbulence Tunnel located at Delft University of Technology with a powered propeller model and flush-mounted microphones in the tunnel floor. The propeller was investigated at different advance ratios in order to study the noise impact in propulsive and energy harvesting configurations. For brevity, this work only reports the results at the conditions of maximum efficiency in both propulsive and energy harvesting regimes, for a fixed blade pitch setting. Comparing these two configurations, a frequency-domain analysis reveals a significant modification in the nature of the noise source. In the propulsive configuration, most of the energy is related to the tonal noise component, as expected for an isolated propeller; however, in energy harvesting configuration, the broadband noise component increases significantly compared to the propulsive mode. A more detailed analysis requires separation of the two noise components and, for this purpose, an innovative decomposition strategy based on proper orthogonal decomposition (POD) has been defined. This novel technique shows promising results; both in the time and in the Fourier domains the two reconstructed components perfectly describe the original signal and no phase delays or other mathematical artifices are introduced. In this sense, it can represent a very powerful tool to identify noise sources and, at the same time, to define a proper control strategy aimed at noise mitigation.

Original languageEnglish
Article number217
Number of pages17
Issue number7
Publication statusPublished - 2022


  • energy harvesting
  • rotor noise
  • proper orthogonal decomposition
  • wavelet transform


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