Research On Modeling Correction For Turboshaft Engine

The accuracy of model is a key technical index. Improving the accuracy of aero-engine model has always been the emphasis which is difficulty in the modeling area. Model correcting method for turboshaft engine is studied in this thesis.Firstly, a nonlinear Component-Level Performance model of the turboshaft engine was built up. Using genetic algorithm and PSO-Immune algorithm independently, the characteristic correction coefficients of every component, the air-entraining correction coefficients and pressure recovery correction coefficients were optimized based on the steady state model. It was found that both genetic algorithm and PSO-Immune algorithm had good effect on correcting the model of turboshaft engine. However, the latter could further reduce the error of the model and it was easier to be coded for engineering operation.Secondly, use PSO-Immune algorithm to carry out specific modeling correction work. On correcting design point, a set of new correction coefficients which stand for the mass scale of the turbine export cooling air flow who take part in doing manual work was added to the original optimized parameters. On correcting off-design points, through simulation analizing the location of the opearating line on the component characteristic map, correcting strategy for component characteristic was proposed.Finally, the method of correcting the component characteristic map was proposed: for compressor characteristic map, correction was carried out by relative conversion rotational speed from the high to the low; for power turbine characteristic map, correction was carried out to change the slope of the “Climbing” area by pressure ratio from the high to the low after translating all of the characteristic line by the characteristic correction coefficients obtained on correcting design point. The correction results of several steady state points showed that the method of correcting the component characteristic map was practicable.