Shortening uncrewed aircraft development cycles via automated flight testing

Abstract

Aircraft flight testing is generally a long, laborious task and understanding parameters of an aircraft, such as its drag coefficients, is an important outcome and a key aspect for performance modelling and mission planning. The present project developed an automated flight-testing capability that is suitable for fixed wing Uncrewed Aerial Vehicles (UAVs) and is capable of guiding an iterative UAV design process.

To maximise the quality of the data generated from flight testing and minimise the human effort involved, it is necessary to set up an automated flight test framework. PSI D, a tool developed by the author, enables the performance of fully automated flight tests. Automated unpowered glide slope and slow down manoeuvres are implemented to collect the required data for lift and drag curve generation.

Vast amounts of data are generated in a typical flight testing campaign. Therefore, a process to evaluate the data in a time efficient manner with minimal manual input is required. In order to tackle this, the author developed an open source flight visualisation and report generation software (Automated Flight Log python – AutoFLpy). The tool is capable of providing rapid visualisation of the test flight to evaluate the success of the manoeuvres whilst still at the airfield.

The author also identified several potential pitfalls encountered in flight testing for the purposes of UAV lift and drag determination using wind tunnel data. These errors are taken into account in PSI D whilst extracting coefficients from the flight data.

Furthermore, in order to maximise the effectiveness of the proposed iterative design process, the author outlines a process for developing robust optimal manoeuvre strategies based on real flight data. The strategies maximise the quality of the flight data collected whilst minimising the flight time required. It is found that the strategies vary depending on the atmospheric conditions.

The framework presented here lays the foundation of the rapid flight test based prototyping process, demonstrating the capabilities of automated flight testing and data processing and optimising the flight testing strategies for minimising the error in the coefficients and the flight testing time.

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Identifiers

ORCID for Andras Sobester: orcid.org/0000-0002-8997-4375

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