Verification of Prognostic Algorithms to Predict Remaining Flying Time for Electric Unmanned Vehicles

Edward F. Hogge, Brian M. Bole, Sixto L. Vazquez, Chetan S. Kulkarni, Thomas H. Strom, Boyd L. Hill, Kyle M. Smalling, and Cuong C. Quach
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Full Paper
ijphm_18_021.pdf1.1 MBMay 24, 2018 - 7:48am

This paper addresses the problem of building trust in the online prediction of a battery powered UAV’s remaining available flying time. A series of ground tests is described that make use of an electric unmanned aerial vehicle (eUAV) to verify the performance of remaining flying time predictions. The algorithm verification procedure described is implemented on a fully functional vehicle that is restrained to a platform for repeated run-to-functional-failure (charge depletion) experiments. The vehicle under test is commanded to follow a predefined propeller RPM profile in order to create battery demand profiles similar to those expected during flight. The eUAV is repeatedly operated until the charge stored in powertrain batteries falls below a specified limit threshold. The time at which the limit threshold on battery charge is crossed is then used to measure the accuracy of the remaining flying time prediction. In our earlier work battery aging was not included. In this work we take into account aging of the batteries where the parameters were updated to make predictions. Accuracy requirements are considered for an alarm that warns operators when remaining flying time is estimated to fall below the specified limit threshold.

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Submission Keywords: 
verification and validation
Aircraft Avionics
battery degradation
fault detection
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Verification and validation
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