Development, Implementation, and Pilot Evaluation of a Model-Driven Envelope Protection System to Mitigate the Hazard of In-Flight Ice Contamination on a Twin-Engine Commuter Aircraft

Fatal loss-of-control accidents have been directly related to in-flight airframe icing. The prototype system presented in this report directly addresses the need for real-time onboard envelope protection in icing conditions. The combination of prior information and real-time aerodynamic parameter estimations are shown to provide sufficient information for determining safe limits of the flight envelope during inflight icing encounters. The Icing Contamination Envelope Protection (ICEPro) system was designed and implemented to identify degradations in airplane performance and flying qualities resulting from ice contamination and provide safe flight-envelope cues to the pilot. The utility of the ICEPro system for mitigating a potentially hazardous icing condition was evaluated by 29 pilots using the NASA Ice Contamination Effects Flight Training Device. Results showed that real time assessment cues were effective in reducing the number of potentially hazardous upset events and in lessening exposure to loss of control following an incipient upset condition. Pilot workload with the added ICEPro displays was not measurably affected, but pilot opinion surveys showed that real time cueing greatly improved their awareness of a hazardous aircraft state. The performance of ICEPro system was further evaluated by various levels of sensor noise and atmospheric turbulence.

[1]  Qing Wang,et al.  Calibration of a Radome-Differential GPS System on a Twin Otter Research Aircraft for Turbulence Measurements , 2002 .

[2]  R. E. Maine,et al.  Important factors in the maximum likelihood analysis of flight test maneuvers , 1979 .

[3]  Eugene A. Morelli,et al.  Real-Time Parameter Estimation in the Frequency Domain , 1999 .

[4]  G. W. Foster,et al.  The identification of aircraft stability and control parameters in turbulence , 1982 .

[5]  Eugene A. Morelli,et al.  Aircraft system identification : theory and practice , 2006 .

[6]  W. E. Silver,et al.  Economics and Information Theory , 1967 .

[7]  Qing Wang,et al.  Aerodynamic Effects on Wind Turbulence Measurements with Research Aircraft , 2002 .

[8]  Alex Sim,et al.  NASA/FAA Tailplane Icing Program: Flight Test Report , 2000 .

[9]  Maliha S. Nash,et al.  Handbook of Parametric and Nonparametric Statistical Procedures , 2001, Technometrics.

[10]  Rolf Isermann,et al.  Identification of Dynamic Systems , 2011 .

[11]  Eugene A. Morelli,et al.  System IDentification Programs for AirCraft (SIDPAC) , 2002 .

[12]  Petros G. Voulgaris,et al.  Smart icing systems for aircraft icing safety , 2002 .

[13]  R. Maine,et al.  Formulation and implementation of a practical algorithm for parameter estimation with process and measurement noise , 1980 .

[14]  Thomas P. Ratvasky,et al.  Simulation Model Development for Icing Effects Flight Training , 2002 .

[15]  Thomas P. Ratvasky,et al.  Iced Aircraft Flight Data for Flight Simulator Validation , 2002 .

[16]  Thomas P. Ratvasky,et al.  Envelope Protection for In-Flight Ice Contamination , 2009 .

[17]  K. W. Iliff,et al.  Effects of time-shifted data on flight determined stability and control derivatives , 1975 .

[18]  R. Dobosy,et al.  A sensitive fast-response probe to measure turbulence and heat flux from any airplane , 1992 .

[19]  Wayne M Olson,et al.  Aircraft Performance Flight Testing , 2000 .

[20]  G. E. Cooper,et al.  Human error in aviation operations , 1974 .

[21]  Donald H. Lenschow,et al.  Vanes for sensing incidence angles of the air from an aircraft , 1971 .

[22]  G. M. Sakamoto Aerodynamic characteristics of a vane flow angularity sensor system capable of measuring flight path accelerations for the Mach number range from 0.40 to 2.54 , 1976 .

[23]  Eugene A. Morelli,et al.  Practical Aspects of the Equation-Error Method for Aircraft Parameter Estimation , 2006 .