Abstract
The quad-rotor UAV (Unmanned aerial vehicle) has a wide application market for its simple structure, easy operation and strong adaptability. During the flight, the endurance of UAV is an important parameter for flight planning, and it is of great significance to master the endurance capability of UAV. The endurance of UAV is mainly decided by the remaining capacity of the battery and the future energy consumption which changes with flight conditions. In this paper, a Flight Condition-Energy Consumption Model is established by analysing a large number of flight data with machine learning method, and the effects of different regression algorithms are compared. The validity of the model is verified by the actual flight. The endurance of the aircraft can be estimated using this model with the given remaining capacity of the battery and the future flight tasks.
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