The novel aircraft has higher requirements for prediction accuracy of aerodynamic characteristics. Therefore, this paper studies an aerodynamic characteristics correction framework for multiple flight test data to achieve correction of ground aerodynamic model and prior uncertainty model. Firstly, to improve the accuracy of model identification, the traditional multivariate orthogonal function method is improved based on the characteristics of experimental data. Statistical selection criteria for multi-test data model items are constructed, and the customized parameter estimation algorithm is designed based on the total least square method. Then, for the purpose of uncertainty quantification, the total deviation of the aerodynamic correction model is estimated, and the prior uncertainty model is corrected. Finally, the proposed correction framework is used to process 10 test data of a certain aircraft. The results show that compared with the original ground aerodynamic characteristics prediction method, the revised method can yield more accurate prediction of aerodynamic coefficients, and fewer out-of-band measurement points and higher accuracy in estimation of aerodynamic error bands.
LI Jinsheng
,
ZHUANG Ling
,
SONG Jiahong
,
LU Baogang
,
SU Wei
,
WU Qiao
. Aircraft aerodynamic characteristic correction framework for engineering data[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022
, 43(5)
: 125157
-125157
.
DOI: 10.7527/S1000-6893.2021.25157
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