A novel performance adaptation method for aero-engine matching over a wide operating range

Abstract

High-fidelity performance modelling is crucial for the development of aero-engine digital twin technology. The accuracy of component-level models heavily relies on the precision of characteristic maps, and inaccuracies in these maps can cause significant deviations between predicted and actual engine performance. A novel method of aero-engine performance adaptation based on adaptation factor surfaces is proposed, which aims to provide a performance matching method for aero-engines over a wide operating range. To improve the convergence and stability of the solution, a hybrid algorithm is proposed that fuses model and measured data to calculate the adaptation factor at the operating points. The modification of the characteristic maps is achieved in both directions by means of adaptation factor surfaces. The method is validated by simulating two engines with distinct maps, and the results show that the method significantly improves the model accuracy at the component level under widely varying operating conditions, taking into account the multidimensional aspects of the maps and the differences between the real engine and the model. The proposed approach has the potential to improve the accuracy and efficiency of digital twin technology for aero-engines.