Aerodynamic Modeling and Parameter Estimation from QAR Data of an Airplane Approaching a High-altitude Airport |
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Authors: | WANG Qinga b WU Kaiyuanb c ZHANG Tianjiaoa b KONG Yi’nana b QIAN Weiqia b aState |
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Affiliation: | Key Laboratory of Aerodynamics, China Aerodynamics Research and Development Center, Mianyang 621000, China bComputational Aerodynamics Institute, China Aerodynamics Research and Development Center, Mianyang 621000, China cScientific Research Base of Civil Aviation Flight Technology and Safety, Guanghan 618307, China |
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Abstract: | Aerodynamic modeling and parameter estimation from quick accesses recorder (QAR) data is an important technical way to analyze the effects of highland weather conditions upon aerodynamic characteristics of airplane. It is also an essential content of flight accident analysis. The related techniques are developed in the present paper, including the geometric method for angle of attack and sideslip angle estimation, the extended Kalman filter associated with modified Bryson-Frazier smoother (EKF-MBF) method for aerodynamic coefficient identification, the radial basis function (RBF) neural network method for aerodynamic modeling, and the Delta method for stability/control derivative estimation. As an application example, the QAR data of a civil airplane approaching a high-altitude airport are processed and the aerodynamic coefficient and derivative estimates are obtained. The estimation results are reasonable, which shows that the developed techniques are feasible. The causes for the distribution of aerodynamic derivative estimates are analyzed. Accordingly, several measures to improve estimation accuracy are put forward. |
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Keywords: | civil airplane aerodynamics QAR data aerodynamic modeling aerodynamic parameter estimation flight safety EKF-MBF method neural network |
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