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Compared with the forced oscillation test in a conventional wind tunnel test, the wind tunnel virtual flight test can achieve partially constrained dynamic motion of the model in the wind tunnel by manipulating the control surface deflection. In this paper, a new four-degree-of-freedom (4-DOF) wind tunnel virtual flight test device is established. Compared with the 3-DOF wind tunnel virtual flight test with rotation around the center of mass, the model adds vertical motion, enabling it to simulate free flight more realistically. In this paper, the nonlinear flight dynamics model of 4-DOF wind tunnel virtual flight test is established, the differences in dynamics characteristics between it and free flight are analyzed, and the identification model of aerodynamic derivatives based on 4-DOF wind tunnel virtual flight test is derived. To ensure the safety of the test, the longitudinal altitude control law as well as the sideslip and roll angle control laws in the lateral direction are designed. Finally, a set of aerodynamic parameter identification methods based on a 4-DOF wind tunnel virtual flight test is formed. The output error method is used to identify the aerodynamic derivatives of the test model, and the accuracy of the identification results is higher than that of the 3-DOF wind tunnel virtual flight test.

The wind tunnel virtual flight test realizes the dynamic semi-free flight of the model in the wind tunnel through the deflections of the control surface and uses the test data to identify the aerodynamic derivatives. The difference in dynamics between the wind tunnel virtual flight and the free flight leads to discrepancies between the identification and theoretical results. To solve the problems, a step-by-step identification and correction method for aerodynamic derivatives is established based on the difference between the equations of motion of wind tunnel virtual flight and free flight to identify and correct the lift, drag derivatives, pitch moment derivatives, and velocity derivatives, respectively. To establish an aerodynamic parameter identification model, the flight dynamics equation is expressed as a decoupled form of the free flight force and the influence of the test support frame force on the model’s motions through linearization. To ensure the identification accuracy of each aerodynamic derivative, an excitation signal design method based on amplitude–frequency characteristic analysis is proposed. The longitudinal aerodynamic parameter identification results of a blended-wing-body aircraft show that identification results with higher accuracy can be obtained by adopting the proposed identification and correction method.

In the early stages of aircraft design, a scaled model of the aircraft is installed in a wind tunnel for dynamic semi-free flight to approximate real flight, and the test data are then used to identify the aerodynamic parameters. However, the absence of the translational motion of the test model makes its flight dynamics different from those in free flight, and the effect of this difference on parameter identification needs to be investigated. To solve this problem, a 3-DOF wind tunnel virtual flight test device is built to fix the test model on a rotating mechanism, and the model is free to rotate in three axes through the deflection of the control surfaces. The flight dynamics equations for the wind tunnel virtual flight test are established and expressed as a decoupled form of the free flight force and the influence of the test support frame force on the model’s motions through linearization. The differences between wind tunnel virtual flight and free flight are analysed to develop a model for the identification of aerodynamic parameters. The selection of the lateral-directional excitation signal and the design method of its parameters are established based on the requirements for the identifiability of the aerodynamic derivatives, and a step-by-step method for the identification of aerodynamic force and moment derivatives is established. The aerodynamic parameter identification results of a blended wing body aircraft show that the identification method proposed in this paper can obtain results with high accuracy, and the response of the modified motion model is consistent with that of the free flight motion model.