A computational study of helicopter vibration and rotor shaft power reduction is conducted using activelycontrolled trailing-edge flaps (ACFs), implemented in both single and dual flap configurations. Simultaneous vibration reduction and performance enhancement is demonstrated under level flight condition at high advance ratios, where dynamic stall effects are significant. Power reduction is achieved using the adaptive Higher Harmonic Control (HHC) algorithm in closed loop, with 2-5/rev flap control harmonics. This approach is compared with an off-line, nonlinear optimizer available in MATLAB, and favorable comparisons are obtained. A parametric study of flap spanwise location is also conducted to determine its optimal location for power reduction. The effectiveness of the ACF approach for power as well as simultaneous vibration and power reduction is also compared with conventional individual blade control (IBC) approach. Rotor power reduction and simultaneous reduction of vibration and power are shown to be larger at higher rotor thrust and advance ratio. Finally, the effect of active flap on dynamic stall is examined to determine the mechanisms of rotor power reduction. The simulation results clearly demonstrate the potential of the ACF system for power reduction as well as simultaneous vibration and power reduction. Nomenclature c Blade chord cc Flap chord CT Rotor thrust coefficient D Matrix defined as TTQT+R fb(.) Blade equations of motion ft(.) Trim equations FHX4,FHY4, FHZ4 4/rev hub shears, nondimensionalized by MbΩR MHX4,MHY4, MHZ4 4/rev hub moments, nondimensionalized by MbΩR J Quadratic-form objective function to be minimized Presented at the American Helicopter Society 62nd Annual Forum, Phoenix, AZ, June 9-11, 2006. 1 Mb Blade mass mc Flap mass per unit length, nondimensionalized by Mb/R MHz1 Yawing moment about rotor hub Nb Number of rotor blades PR Rotor shaft power, nondimensionalized by MbΩR qt Vector of trim variables qti Vector of trim variables at i-th control step Q Weighting matrix for objectives to be minimized R Weighting matrix on control input R Rotor blade radius Rt Trim residuals vector T Sensitivity, transfer matrix between control inputs and objective function uk Control input vector, kth control step uk,opt Optimum value of control input vector xc Spanwise location of center of control surface zk Objective vector, kth control step αR Rotor shaft angle of attack δ f Flap deflection angle ∆Cd,flap Additional drag due to flap deflection δNc,δNs N/rev cosine and sine amplitude of δ βp Blade precone angle γ Lock number μ Helicopter advance ratio ωF , ωL, ωT Blade flap, lead-lag and torsional natural frequencies Ω Rotor angular speed ψ Rotor azimuth angle φR Lateral roll angle θ0,θ1c,θ1s Collective and cyclic pitch components θ0t Tail rotor collective pitch θtw Built-in twist angle σ Rotor solidity Introduction and Background Specifications for noise and vibration levels in rotorcraft are continuously increasing in stringency, thus motivating research related to active noise and vibration reduction. Desirable vibration levels have been identified to be below 0.05g to provide passengers with “jet smooth” ride (Ref. 1). A number of active control techniques have emerged for effective vibration reduction (Refs. 1,2), as illustrated schematically in Fig. 1. These approaches generally fall into one of two categories: (a) active control approaches aimed at reducing vibrations in the rotor before they propagate into the fuselage, and (b) active control approaches
Read full abstract