Aero gas turbine flight performance estimation using engine gas path measurements - Li, Yiguang (American Institute of Aeronautics and Astronautics (AIAA), 2015)
Mature gas turbine performance simulation technology has been developed in the past decades and, therefore, gas turbine performance at different ambient and operating conditions can be well predicted if good thermodynamic performance software and necessary engine performance information are available. However, the performance of gas turbine engines of the same fleet may be slightly different from engine to engine due to manufacturing and assembly tolerance and may change over time due to engine degradation. Therefore, it is necessary to monitor and track important performance parameters of gas turbine engines, particularly those that cannot be directly measured, to ensure safe operation of the engines. For that reason, a novel gas turbine performance estimation method using engine gas path measurements has been developed to predict and track engine performance parameters at different ambient, flight, degraded, and part-load operating conditions. The method is based on the influence coefficient matrix of thermodynamic performance parameters of gas turbine engines and the Newton Contrary to the conventional gas turbine off-design performance predictions where component characteristic maps are essential, it has the advantage that no component characteristic maps are required for the predictions and, therefore, it is relatively simple thermodynamically, fast in calculation, and desirable in engineering applications. It is able to make important invisible performance parameters visible to gas turbine users, which is a useful complement to current engine condition monitoring techniques. The developed method was applied to the performance prediction of a model gas turbine engine similar to EJ200 low-bypass turbofan engine running at different altitudes, Mach numbers, and part load, with and without degradation, by using simulated gas path measurements to test the effectiveness of the method. The results show that the method is able to predict the engine performance with good accuracy without the consideration of measurement noise and with slightly lower accuracy when measurement noise is included. It takes about 30 s for a typical prediction point, which is suitable for offline performance tracking and condition monitoring. Theoretically, the method can be applied to the performance estimation of any types of gas turbine engines.–Raphson mathematical algorithm.