Coupled simulation of aero-engine mainstream and Secondary Air System (SAS) can enhance the accuracy of performance prediction. However, conventional methods either oversimplify SAS modelling or suffer from high computational costs due to tightly integrated architectures, making it challenging to achieve a balance between accuracy and efficiency. To address this issue, a novel coupled simulation strategy is proposed based on similarity-derived SAS characteristic maps. Firstly, an improved one-dimensional network model of the SAS is established, and experimental validation is conducted to verify the effectiveness of the model. Then, similarity theory is extended to SASs, and similarity parameters corresponding to bleed flow rate, boundary conditions, and shaft speed are derived using Buckingham π theorem. Based on these parameters, generalized characteristic maps for SAS branches are constructed, enabling integration with the engine performance model. The proposed method is evaluated using test data from a dual-spool turbofan engine. The results demonstrate that the coupling strategy based on SAS characteristic maps significantly improves computational efficiency while maintaining high prediction accuracy across the entire operating envelope. A scalable and physically consistent framework for transient coupled simulations is established, offering strong potential for real-time applications and digital twin implementation.
Jian et al. (Wed,) studied this question.