Affiliation:
1. Nanjing University of Aeronautics and Astronautics
Abstract
<div class="section abstract"><div class="htmlview paragraph">The confidence of the onboard adaptive model in estimating surge margin
significantly affects the operating stability in an aircraft engine’s active
surge margin control process. Unfortunately, the existing onboard adaptive
models lack high confidence, although wide-ranging in estimation, due to the
unknown surge boundaries in component characteristics. Therefore, this paper
first accurately estimates the actual surge margin during the engine operating
near-surge boundary using a pressure correlation measurement technology. Then,
innovatively, the estimated surge margin is used to correct the surge boundary
of the nonlinear onboard model of the engine to obtain the actual surge
boundary, thereby guaranteeing confidence. Finally, a nonlinear onboard adaptive
model based on an improved spherical unscented Kalman filter is employed to
achieve wide-range high-confidence surge margin estimation throughout the
engine’s life cycle. Simulation results demonstrate that the proposed method is
effective and has a high-confidence level in surge margin estimation, ensuring
estimation accuracy of over 95% for both standard and degraded engines, far
surpassing existing techniques. The proposed method provides a technical means
for sensing surge margin in future high-stability engine active control.</div></div>