Using a broadband multisine excitation signal for the data-driven modeling of the unsteady lift force on a pitching wing

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Understanding unsteady aerodynamic forces on a lifting surface is crucial for many engineering applications. This work demonstrates the use of system identification techniques for the data-driven modelling of the aerodynamic lift force on a pitching wing. This lift force can be considered as a (nonlinear) dynamic function of the angle of attack. The proposed approach consists of multiple steps: 1) excitation by the means of broadband excitation, 2) pre-processing of the measurement, and 3) data-driven modelling techniques. The considered excitation signal is the so-called multisine (also known as periodic pseudo- random noise). However, dynamic stall is known to exhibit important cluster-to-cluster variations and this is no different when utilizing multisines. Therefore, we cluster the data before the actual data-driven Preliminary proceedings modeling and validation. We show that the obtained models can capture the nonlinear aerodynamic forces more accurately than the classical linear and semi-empirical models.
Original languageEnglish
Title of host publicationConference proceedings of 2022 ISMA International Conference on Noise and Vibration Engineering
PublisherKU Leuven
Number of pages10
Publication statusPublished - 12 Sep 2022
Event2022 ISMA International Conference on Noise and Vibration Engineering - KU Leuven, Leuven, Belgium
Duration: 12 Sep 202214 Sep 2022


Conference2022 ISMA International Conference on Noise and Vibration Engineering

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