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Model based design and optimization of winged UAVs

Authors :
Gu, Haowei
Gu, Haowei
Publication Year :
2019

Abstract

The past few decades have witnessed a dramatically growth of unmanned aerial vehicle (UAV) market. Such an increasing requirement of UAV also caused fierce competition among UAV companies all over the world. For these UAV manufactures and relative researchers, optimization of UAV design is critical to improve performance of UAVs. Compare to all other configurations of UAVs, winged UAV is the most complex and difficult to optimize during the design progress. That is not only because of the involved complex aerodynamic model, but also due to the coupling of aerodynamic model and propulsion system model, which composed by several sub-models, such as battery model, propeller model and motor model. In this thesis, a powerful model based optimization framework is proposed to design highly efficient winged UAVs powered by electric motors. In the proposed approach, the models of aerodynamic configurations and propulsion system are built and cast into an unified optimization problem, where the optimization objective is the design goal (e.g. flight range, endurance). To evaluate the models, the key design variables are parameterized as two groups, which respectively denote the aerodynamic model (e.g. wing span, sweep angle, chord, taper ratio, cruise speed and angle of attack) and the propulsion systems model (e.g. propeller, motor and battery). Moreover, practical constraints are naturally incorporated into the design procedures as constraints of the optimization problem. These constraints may arise from the preliminary UAV shape and layout determined by industrial design, weight constraints, etc. The optimization framework is inherently non-convex and involves both continuous variables (e.g. the aerodynamic configuration parameters) and discrete variables (e.g. propulsion system combinations). To solve this problem, a novel coordinate descent method is proposed. Trial designs show that the proposed method works rather efficiently, converging in a few iterations. And the ret

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1363081368
Document Type :
Electronic Resource