Research On Modification Technology Of Aeroengine Model

Aero-engine model is an important tool for the development of advanced aero-power plant.The actual characteristics of engine components are changed and the accuracy of engine model is reduced due to the influence of the installation and manufacturing technology level of each component,component performance degradation and complex and alternating working environment.Aiming at this problem,this paper takes the DGEN380 turbofan engine as the research object,establishes the engine component level model,and carries out the research on the modification method of engine component level model component characteristics based on the engine test data.The main research contents are as follows:(1)According to the design point parameters of DGEN380 engine,the component method was used to establish the component model of DGEN380 turbofan engine,and the steady-state model was established according to the steady-state co-working equation of engine.Based on the N-R method,the improved N-R method is constructed by adding the solution variable constraint mechanism and the adaptive variable step size mechanism.The simulation results show that the improved N-R method has good adaptability to different initial guess conditions and different calculation step sizes,and can guarantee the convergence performance and solution speed of the algorithm.Based on the improved N-R method,the steady-state model is solved,and the results are compared with the experimental data to prove that the steady-state model has certain accuracy but needs further modification.(2)Mechanism analysis and algorithm coding were carried out for the modification and optimization algorithms of three commonly used components:genetic algorithm(GA),differential evolution algorithm(DE)and particle swarm optimization algorithm(PSO),and the modification performance of each algorithm was tested and compared by taking compressor components as an example.The results show that compared with GA algorithm,DE algorithm and PSO algorithm are more adaptable to multi-target and multi-parameter correction,with a success rate of100% and an error of 1%.PSO algorithm has the advantage of simple coding,but theconvergence speed is affected by the value of inertia weight ω.Therefore,an adaptive variable inertia weight method is proposed to improve the performance of particle swarm optimization(PSO).The simulation results show that the improved PSO algorithm not only meets the requirements of solution accuracy,but also improves the convergence performance and solution speed.(3)The modified PSO algorithm was used to modify and update the part characteristic diagram of the DGEN380 engine fan,compressor,high-pressure turbine and low-pressure turbine part model at the design point.For the modification of the design point,the whole part characteristic diagram was adjusted in a small range.The simulation results show that the relative error of the output target parameters of the modified model meets the requirement of 1% accuracy,and the accurate matching of model design points is achieved.(4)Based on the correction result of design point,an off-design point correction method is proposed to carry out local correction of partition according to the location of the point to be corrected.According to the region of the point to be corrected and the location of the reference point,some specific characteristic lines are selected to be adjusted to ensure that the model accuracy of the modified reference point is not affected.Taking the three off-design points of slow speed point,cruise point and take-off thrust point as examples,the off-design point correction of engine component-level model was carried out based on the improved PSO algorithm.The simulation results show that the relative errors of the model’s target parameters are kept at 1%,and the average errors are 0.282%,0.291% and 0.289% respectively,which meet the requirements of accuracy and verify the feasibility of the off-design point correction method.