Numerical Investigation and Hybrid Modeling of External–Internal Flow Coupling on Thrust Vector Control Performance

Thrust vector control (TVC) technology significantly enhances the attitude control capability of aircraft. However, conventional multi-axis calibration is inherently cost-prohibitive and time-consuming, whereas static ground-bench calibration completely neglects the significant aerodynamic interference from external freestreams during actual flight. To resolve this operational bottleneck in engineering applications and calibration workflows, this paper proposes an agile, cost-effective hybrid modeling and process optimization methodology that seamlessly integrates low-cost ground experiments with high-fidelity numerical investigations. First, a customized one-axis force sensor test bench was developed to calibrate the baseline thrust vector performance under static ground conditions. Subsequently, computational fluid dynamics (CFD) simulations were conducted across the typical cruise speed range (30–60 m/s) of TVC aircraft to investigate the nonlinear interactions between the external freestream and the vectorized jet. The numerical results reveal that the interaction between the deflected jet exhaust and the external flow field significantly changes the flow structure and pressure distribution around the control surface. The momentum exchange, primarily governed by mass entrainment and cross-shear-layer mixing, broadens the control surface’s impact scope and enhances the injection effect, resulting in nonlinear variations in the control force under different operating conditions. Considering the influence of external flow and deflected jet, a dynamic control force model was established by integrating the ground static baseline model with simulation data. The fitting results demonstrate that this control model limits match error to within 3% across both experimental and numerical datasets, effectively suppressing loop uncertainties across the entire flight envelope while maintaining a minimalist sensing architecture. From a process engineering perspective, this “Hybrid Modeling”-driven approach substitutes expensive multi-degree-of-freedom testing hardware with an integrated simulation-experimental workflow, offering a highly scalable, simplified, and analyzable process method for TVC research and application.