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

Edward F Hogge¹, Brian M Bole², Sixto L Vazquez³

¹Northrop Grumman Technology Services, NASA Langley Research Center, Hampton, Virginia 23681.

International Journal of Prognostics and Health Management

|April 19, 2021

Summary

This study validates flying time predictions for battery-powered unmanned aerial vehicles (UAVs) by accounting for battery aging. Ground tests confirm algorithm accuracy for reliable remaining flight time estimation.

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Area of Science:

Aerospace Engineering
Electrical Engineering
Robotics

Background:

Accurate prediction of remaining flying time is crucial for battery-powered unmanned aerial vehicles (UAVs).
Previous models did not account for battery aging, impacting prediction accuracy over time.
Establishing trust in online predictions requires rigorous verification.

Purpose of the Study:

To verify the performance of an algorithm predicting remaining flying time for electric UAVs (eUAVs).
To incorporate battery aging into prediction models for enhanced accuracy.
To define accuracy requirements for an early warning system for low battery levels.

Main Methods:

Conducted ground tests using a functional eUAV restrained on a platform.
Performed repeated charge depletion experiments following a predefined propeller RPM profile.
Measured prediction accuracy by comparing estimated time to actual battery charge depletion.

Main Results:

The implemented algorithm demonstrated verifiable performance in predicting remaining flying time.
Incorporating battery aging parameters improved the accuracy of flight time predictions.
Established a baseline for accuracy requirements for a critical low-battery warning.

Conclusions:

The developed method provides a trustworthy approach to online prediction of UAVs' remaining flying time.
Accounting for battery aging is essential for robust and reliable flight time estimations.
The findings support the development of safety-critical systems for autonomous aerial operations.