Development of a Cross-Flow Fan Powered Quad-Rotor Unmanned Aerial Vehicle

Abstract

The research presented is dedicated to the advancement of construction techniques in order to implement new designs of a vehicle suited for cross-flow fan propulsion. This is accomplished by designing a quad-rotor cross-flow fan that incorporates lessons learned from previous generation models as well introducing novel new construction concepts tailored to cross-flow fan propulsion vehicles. The current vehicle design was built using both custom and standard sections. Commercially available drivetrain and control components are used. The new design focused on three key areas of improvement: airframe simplification, gross takeoff weight reduction and structural rigidity improvement. At all phases the construction and emphasis on using readily available technologies or minor modifications to these was maintained. Novel techniques in construction are presented that allow these technologies to be leveraged. Finally, a new vehicle was built and tested and shown to be able to take-off vertically and be fully controllable in pitch, yaw, and roll.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2015
Accession Number
ADA632493

Entities

People

  • Erc D. Smitley

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Energy and Power Technologies
  • Space

DTIC Thesaurus Topics

  • Aircraft Equipment
  • Aircraft Industry
  • Aircrafts
  • Airframes
  • Computational Fluid Dynamics
  • Construction
  • Control Systems
  • Cross Flow
  • Geometry
  • Mechanical Properties
  • Propulsion Systems
  • Rotary Wing Aircraft
  • Short Takeoff Aircraft
  • Structural Components
  • Tilt Rotor Aircraft
  • Unmanned Aerial Vehicles
  • Vertical Takeoff Aircraft

Readers

  • Aerial Unmanned Vehicle Swarm Micro Periodontal Dentistry.
  • Electrical Engineering
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Neural Networks
  • Autonomy