Experimental Validation Of Rotor Broadband Noise Models For Aam In Urban Environment

Abstract

New technologies are paving the way for Advanced Air Mobility (AAM) like Urban Air Mobility (UAM) and Unmanned Aerial Vehicles (UAV). Numerous of such systems are being developed and a common architecture is electrically driven multi-rotors for thrust generation. Besides thrust, rotors also generate noise, causing annoyance for people in and around the AAM. Predicting this noise is therefore important for policy makers and developers of AAM. This paper describes the experimental validation of a recently developed noise prediction tool for AAM in urban environments, yielding a Virtual Reality environment. The focus is on rotor broadband noise, as its contribution to human perception is currently not well understood. First an overview of the considered semi-empirical broadband noise models is presented. Then a first validation step is described for an isolated single drone rotor in a wind tunnel test setup. Secondly, validation of a full multi-rotor drone flyover field test is described. Spectrograms show in general an underprediction for all noise components. Low-frequency range predictions show the improvement potential by including turbulence ingestion. The need for further research to improve the middle frequency range prediction is discussed.