University of Illinois Urbana-Champaign

A cyber-physical prototyping and testing framework to enable the rapid development of unmanned aircraft

Dantsker, Or Daniel

Content Files
DANTSKER-DISSERTATION-2021.pdf

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https://hdl.handle.net/2142/114098

Description

Title
A cyber-physical prototyping and testing framework to enable the rapid development of unmanned aircraft
Author(s)
Dantsker, Or Daniel
Issue Date
2021-12-03
Director of Research (if dissertation) or Advisor (if thesis)
Caccamo, Marco
Doctoral Committee Chair(s)
Panesi, Marco
Committee Member(s)
  • Bhalerao, Kaustubh
  • Deters, Robert
Department of Study
Aerospace Engineering
Discipline
Aerospace Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Date of Ingest
2022-04-29T21:58:38Z
Keyword(s)
  • UAV
  • Flight Testing
  • Prototype
  • Aircraft Design
  • Unmanned Aircraft
Abstract
"A cyber-physical prototyping and testing framework to enable the rapid development of UAVs is conceived and demonstrated. The framework is an extension of the typical iterative engineering design and development process, specifically applied to the rapid development of electric fixed-wing UAVs. Unlike other development frameworks in the literature, the presented framework allows for iteration throughout the entire development process, from design to construction, using a mixture of simulated and real-life testing as well as cross-aircraft development. For specific aircraft or application requirements, methods and tools can be added, removed, or modified as need to be within the framework. Additionally, the framework still enables traditional aircraft development and system engineering principles. The framework presented includes low- and high-order methods and tools that can be applied to a broad range of fixed-wing UAVs and can either be combined and executed simultaneously or sequentially. As part of this work, 7 novel and enhanced methods and tools were developed that apply to electric fixed-wing UAVs in the areas of: flight testing, measurement, emulation and modeling, and optimization. These methods and tools include: (1) data acquisition, (2) flight testing automation, (3) 3D scanning, (4) moment of inertia measurement, (5) modular emulation, (6) electric aircraft power modeling, and (7) propulsion system optimization. Capturing accurate flight testing data is a fundamental component of UAV development, and doing so requires high-fidelity flight data from a large range of sensors. Two data acquisition systems were developed that showed superior capabilities and performance compared to those developed by comparable research institution and commercial systems. The latter of the data acquisition systems was further enhanced to enable flight control, which was then used to develop and demonstrate a flight-testing automation technique. Compared to other unmanned flight testing efforts in the literature, automating the data collection process, as opposed to the previous manual status quo, has allowed for improved airspace utilization (up to double) and more efficient flight testing through precise maneuvering, minimal trial-and-error, and, more importantly, decreased flight time required (as little as 1/10th). Knowledge of aircraft parameters, including geometric, inertial, and subcomponent properties is vital in the analysis of flight testing results; however, in the case of UAV development, developers, especially researchers, often use existing COTS airframes that have limited parameters available. The 3D scanning methodology enabled accurate geometry data collection, yielding a CAD model used to develop a flight model for the high-fidelity emulation. Along with model generation, the geometry was used to compute the aircraft's aerodynamic characteristics using several computational tools of varying order: the lifting-line theory aerodynamic tools, XFLR5 and AVL, and the computational fluid dynamics (CFD) tool Ansys Fluent; these computed aerodynamic characteristic values were also compared to values estimated from flight testing data. In order to enable practical high-fidelity emulation as well as processing of flight data, a moment of inertia testing rig and methodology was developed that enables very accurate measurement of an object, i.e., within 5%, which is an order of magnitude less error than the existing ""low-effort"" methods from the literature; the accuracy of the developed testing method is comparable to high-effort, complex methods with geometric-based drag or other types of corrections. In order to decrease development time, modeling and emulation became an important component of the developed framework. Instead of prototyping, testing, and analyzing through the many stages of aircraft development in hardware, which is resources and time intensive, a virtual aircraft and its sub-systems were modeled and then implemented into an emulation environment, i.e., creating a ""Virtual Twin"". The uavEE emulation environment integrates a high-fidelity simulator with layers of modeling (e.g. aircraft power model), flight control software (e.g. autopilot software), and interfaces to hardware components (e.g. flight control board and sensors). A high-fidelity, low-order power model for electric, fixed-wing UAVs was developed that incorporates propulsion system power consumption and solar power generation. Both models were evaluated through flight testing and showed very close agreement with experimental flight data. Finally, as the propulsion system consumes a significant portion of onboard energy, a propulsion system optimization tool was developed that determines optimal propeller and motor combination(s) for electric, fixed-wing UAVs, given desired mission requirements and profile. Flight testing validation showed that an optimized propeller-motor combination requires approximately 20% less power than a default manufacturer-recommended combination. Simulations of agricultural survey and infrastructure inspection missions showed potential for greater efficiency gains of 50% to 75%, relative to the default combination, yielding 2-4 fold increases in coverage. Two demonstrations of the development framework are presented. The first demonstration showed how to rapidly develop an unmanned aircraft for agricultural field surveillance based on an existing platform, with general and mission-specific methodology. The second demonstration showed the full development of a computationally-intensive, long-endurance solar-powered unmanned aircraft for visually intensive applications; this framework application required 4 iterations, from conception to flight demonstration of the desired aircraft capabilities. A comparison of the developed solar unmanned aircraft to a similar aircraft developed using a different methodology shows a significantly reduced development timeline and resources requirement. The cyber-physical prototyping and testing framework, tools, and methods developed in this work enable users to rapidly design, develop, and modify UAVs to desired aircraft and mission specifications. The UAV development framework can be applied to clean-sheet designs or utilize existing airframes and other components. The tools and methods developed enable rapid aircraft development, testing, and optimization, to significantly improve their performance, efficiency, and endurance. Finally, the aircraft development demonstrations performed provide a foundation for future UAV development. This is especially true for future long-endurance, solar-powered UAVs, which can build off of the aircraft developed in this work and take advantage of incremental improvements in energy capture and storage capabilities."
Graduation Semester
2021-12
Type of Resource
Thesis
Permalink
http://hdl.handle.net/2142/114098
Copyright and License Information
Copyright 2021 Or D. Dantsker

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