Component matching optimization of high-performance turbofan engine based on experiment test and adaptive performance model to control the average gas temperature

As the turbine inlet total temperature of the turbofan engine continues to increase, it is key to ensuring the long-term reliability of aeroengines that the components matching effectively to achieve the expected average gas temperature. However, over temperature in turbine inlet is a common challenge in advanced engine development. To solve this problem, this paper proposes a new idea of a component matching optimization method to control average gas temperature. This method couples the optimization method with the adaptive performance model, which is built using accurate component characteristics and internal/external bypass mass flow rate within the engine test. Experiment methods of component characteristics measurement in different operating status under the condition of the whole engine are also developed, which capture the entire characteristics maps rather than the mini maps along the operating line. It also establishes calculation method of the core mass flow rate based on the critical characteristics of the high-pressure turbine. Tests have shown that by applying the component matching optimization method, the turbine inlet average gas temperature of a high-performance twin-spool mixed turbofan engine was reduced by 50 K–60 K under the same thrust, ensuring fulfillment of the performance indexes.