The increase in popularity of unmanned aerial vehicles (UAVs) has been driven by their use in civilian, education, government, and military applications. However, limited on-board energy storage significantly limits flight time and ultimately usability. The propulsion system plays a critical part in the overall energy consumption of the UAV; therefore, it is necessary to determine the most optimal combination of possible propulsion system components for a given mission profile, i.e. propellers, motors, and electronic speed controllers (ESC). Hundreds of options are available for each of the components with generally non-scientific advice for choosing the proper combinations. This paper describes a propulsion system optimization tool that determines the optimal propeller and motor combination(s) for an electric, fixed-wing unmanned aircraft, given desired mission requirements. Specifically, missions are broken down into expected segments with velocity and thrust requirements being computed using a high-fidelity aircraft power model. The optimization tool then estimates the required propeller rotation rate, followed by the power consumption for each segment and propeller-motor combination. It then integrates the segment results into missions for each combination and tabulates the results, sorting by overall efficiency. Among a variety of additional functionality integrated into the tool, the optimizer considers aircraft safety by estimating the maximum thrust each combination can produce, which is crucial in upset recovery scenarios such as stall. Experimental validation testing of the optimization tool was performed through flight testing of an aircraft. Additionally, propulsion system optimization of two simulated missions were performed, demonstrating significant energy saving that can be made; this is especially paramount for long-endurance, solar-powered aircraft.


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    Title :

    Electric Propulsion System Optimization for Long-Endurance and Solar-Powered Unmanned Aircraft


    Contributors:


    Publication date :

    2019-08-01


    Size :

    7123569 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English