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Casi Bench Test Presentation Transcript

  • 1. Morphing Wing Control in Bench Test Andrei Vladimir Popov PhD student, Laboratory of Research in Active Controls, Avionics and AeroServoElasticity LARCASE, 1100 Notre-Dame West Street, Montreal, Quebec, H3C 1K3, Canada Lucian Grigorie Postdoctoral fellow , Laboratory of Research in Active Controls, Avionics and AeroServoElasticity LARCASE, 1100 Notre-Dame West Street, Montreal, Quebec, H3C 1K3, Canada Ruxandra Mihaela Botez Professor, Laboratory of Research in Active Controls, Avionics and AeroServoElasticity LARCASE, 1100 Notre-Dame West Street, Montreal, Quebec, H3C 1K3, Canada, Ruxandra@gpa.etsmtl.ca, CASI Member
  • 2. SUMMARY
    • Project context
    • Theoretical considerations
    • Experimental setup description
    • Data processing and validation
    • Future work
  • 3. Project context
    • CRIAQ Project 7.1
      • Laminar Flow Improvement on an Aeroelastic Research Wing
      • Objectives:
      • To develop a system for active control of wing airfoil geometry during flight. In-flight modifications of aircraft wing airfoils will make it possible to maintain laminar flow over the wing as flight regime changes.
    • Partners:
  • 4. Theoretical considerations
    • Reference airfoil WTEA – laminar optimized for M=0.7
    • Wind tunnel tests – max air velocity M=0.3
    • Aerodynamic simulations:
      • Fluent and XFoil (pannels + e N method)
    • Alpha angles : between -1 ° and 2 °
    • Morphing airfoil:
      • Upper surface only
      • Flexible skin
      • Two points of control
    • Objective:
      • Delaying the transition
      • To the trailing edge
  • 5. Theoretical considerations (2)
    • 35 aerodynamical cases studied
    • For each case obtained an optimized airfoil
    • Each optimized airfoil obtained through B-Spline approximation in 4 points:
      • 2 fixed points – flexible skin fitting points
      • 2 mobile points – flexible skin actuator control points (Y1 & Y2)
    C135 C134 C133 C132 C131 C130 C129 3.3654 0.300 C128 C127 C126 C125 C124 C123 C122 3.1044 0.275 C121 C120 C119 C118 C117 C116 C115 2.8384 0.250 C114 C113 C112 C111 C110 C109 C108 2.5679 0.225 C107 C106 C105 C10 4 C103 C102 C101 2.2932 0.200 2.00 1.50 1.00 0.50 0.00 -0.50 -1.00 Angle of attack (degrees) Re (mil.) Mach
  • 6. Experimental setup
    • Wing model:
      • 0.5 m x 0.9 m
      • Lower part – aluminium block
      • Upper part :
        • aluminium structure
        • composite materials flexible skin (carbon-kevlar)
        • Shape memory actuators (Ni-Ti)
  • 7. Experimental setup (2)
    • SMA’s control working modes :
      • Heating for SMA increasing length
      • Cooling for SMA decreasing length
      • Desired parameters – dY 1 & dY 2
      • Input signal – position of actuators
      • from LVDT (dL = 3 ·dY )
      • Output signal – control voltage to power supplies – control current for SMA’s
  • 8. Data processing and validation dY 1 dY 2
  • 9. Future work
    • Closed loop control system of
    • aerodynamic pressure distributions
    • Simulations using Matlab-Simulink/XFoil
    M=0.3  °
  • 10. Wind tunnel tests
    • Real time data acquisition using Kulite pressure sensors and NI-DAQ USB M = 0.2,  = 0 ° (ref/optim)
  • 11. Conclusions
    • SMA does respond only to heating or cooling, i.e. pass current or no current (8 A/12 V DC or 0 A/0 V)
    • Excellent control of SMA using PID + switch control due to simplicity and technological limitations of SMA’s
    • Very responsive in heating (~10 sec)
    • Slow response in cooling (~30 to 60 sec)
    • Precision of setting point ~0.02 mm due to LVDT accuracy
    • The control can be improved by a fuzzy controller that will provide the exact current required to keep the SMA heated as needed instead of cycling ON-OFF