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Smalling, Kyle M.

Publications and source records attributed to Smalling, Kyle M..

Flight Tests of a Remaining Flying Time Prediction System for Small Electric Aircraft in the Presence of Faults

This paper addresses the problem of building trust in the online prediction of a battery powered aircraft's remaining flying time. A series of flight tests is described that make use of a small electric powered unmanned aerial vehicle (eUAV) to verify the performance of the remaining flying time prediction algorithm. The estimate of remaining flying time is used to activate an alarm when the predicted remaining time is two minutes. This notifies the pilot to transition to the landing phase of the flight. A second alarm is activated when the battery charge falls below a specified limit threshold. This threshold is the point at which the battery energy reserve would no longer safely support two repeated aborted landing attempts. During the test series, the motor system is operated with the same predefined timed airspeed profile for each test. To test the robustness of the prediction, half of the tests were performed with, and half were performed without, a simulated powertrain fault. The pilot remotely engages a resistor bank at a specified time during the test flight to simulate a partial powertrain fault. The flying time prediction system is agnostic of the pilot's activation of the fault and must adapt to the vehicle's state. The time at which the limit threshold on battery charge is reached is then used to measure the accuracy of the remaining flying time predictions. Accuracy requirements for the alarms are considered and the results discussed.

Hogge, Edward F.

Verification of a Remaining Flying Time Prediction System for Small Electric Aircraft

This paper addresses the problem of building trust in online predictions of a battery powered aircraft's remaining available flying time. A set of ground tests is described that make use of a small unmanned aerial vehicle to verify the performance of remaining flying time predictions. The algorithm verification procedure described here uses a fully functional vehicle that is restrained to a platform for repeated run-to-functional-failure 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 in flight. The fully integrated aircraft is repeatedly operated until the charge stored in powertrain batteries falls below a specified lower-limit. The time at which the lower-limit on battery charge is crossed is then used to measure the accuracy of remaining flying time predictions. Accuracy requirements are considered in this paper for an alarm that warns operators when remaining flying time is estimated to fall below a specified threshold.

Hogge, Edward F.

A Short Tutorial on Inertial Navigation System and Global Positioning System Integration

The purpose of this document is to describe a simple method of integrating Inertial Navigation System (INS) information with Global Positioning System (GPS) information for an improved estimate of vehicle attitude and position. A simple two dimensional (2D) case is considered. The attitude estimates are derived from sensor data and used in the estimation of vehicle position and velocity through dead reckoning within the INS. The INS estimates are updated with GPS estimates using a Kalman filter. This tutorial is intended for the novice user with a focus on bringing the reader from raw sensor measurements to an integrated position and attitude estimate. An application is given using a remotely controlled ground vehicle operating in assumed 2D environment. The theory is developed first followed by an illustrative example.

Smalling, Kyle M.