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Initial Comparison of analytical methods for noise prediction of future electric aircraft powertrains

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Increasing requirements regarding greenhouse gas emissions produced in the aviation sector require new technologies for aircraft propulsion systems. A suitable technology for a more sustainable and low emission aircraft is the electrification of the powertrain. The noise emission by electric machines becomes an important contribution to the overall aircraft noise, especially since future aircraft will need high-power density electric machines that pose additional challenges regarding design and manufacturing. Electric machines with power densities of 10 kW/kg and higher are currently not available for detailed measurements, to get a first impression of the dominating noise sources of electric motors, models for predicting the noise emission are necessary. Compared to numerical methods, analytical models offer a fast estimation of the noise generated by electric motors. In this paper, analytical models for noise prediction generated by electric motors suitable for aircraft propulsion systems are presented. The most advanced model includes the calculation of the excitation forces acting on the stator due to the magnetic flux density that is coupled with a sound radiation analysis of the outer surface of the motor. By varying the basic parameters for each model under investigation, the noise radiation of a permanent magnet synchronous electric motor is assessed.

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Document Type: Research Article

Affiliations: Institute of Electrified Aero Engines, German Aerospace Center (DLR)

Publication date: 04 October 2024

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  • The Noise-Con conference proceedings are sponsored by INCE/USA and the Inter-Noise proceedings by I-INCE. NOVEM (Noise and Vibration Emerging Methods) conference proceedings are included. All NoiseCon Proceedings one year or older are free to download. InterNoise proceedings from outside the USA older than 10 years are free to download. Others are free to INCE/USA members and member societies of I-INCE.

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