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Kinematic and aerodynamic modeling of flexible wings with wing root adjustment for flapping wing micro aerial
Ziming Liu1,2, Xiaoya Zhang3, Zihao Wang4
1School of Information and Electronics, Beijing Institute of Technology, Beijing, 100081, China.
Abstract:
In the field of insect-like flapping-wing micro aerial vehicle (FWMAV) research, this study focuses on a specific type of FWMAV that is tailless and possesses hovering capabilities. The most common method for generating aerodynamic moment in these vehicles is wing-root adjustment. By varying the twist of the wing root, an uneven or asymmetric aerodynamic distribution is created, which generates control moments. This study develops a kinematic model of flexible wings based on wing-root adjustment for aerodynamic design of insect-like FWMAVs and proposes a new aerodynamic simulation method based on multi-rigid-plane fitting to validate the kinematic model. The complete modeling framework for insect-like FWMAVs is first established, which includes the drive system transmission model, the kinematic model of wing motion under wing-root adjustment, an aerodynamic model based on a quasi-steady method, and a multi-rigid-body dynamics model. Next, the kinematics of the flexible wings are divided into three components: the relaxation phase angle equation, the wing motion equation, and the amplitude calibration equation. Then, multi-rigid plane fitting is carried out for the flexible wings based on the topological structure of the wing vein network. Taking the wing kinematics model as input, aerodynamic simulation is conducted by combining with the blade element theory. Finally, the aerodynamic simulation results are compared with results from single-plane simulations and experimental measurements. The results show that the kinematic model of the flexible wings under wing-root adjustment and the multi-plane aerodynamic simulation method are highly effective in predicting the variation of aerodynamic moment in flexible wings. The estimation error for lift does not exceed 20%, providing valuable guidance for subsequent controller design.
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