Performance seeking control method for minimum pollutant emission mode for turbofan engine

Abstract

The research shows that the impact of aero-engine pollutant emission on the environment cannot be ignored. In addition to fuel type and combustor structure, aero-engine exhaust pollutants are also related to engine operating conditions and control systems. In this context, taking CO and NOx as the main exhaust pollutants of the engine as the research object, a performance optimization control method of the minimum pollutant emission mode of the engine is proposed. Firstly, the CO and NOx emission characteristics of the engine under different operating conditions at sea level are calculated by CFD numerical simulation method, and the engine component-level model applicable to all flight envelope and all conditions is established according to the characteristic data. Secondly, in order to improve computational efficiency, an airborne model with high accuracy and real-time performance is established through the deep neural network. Compared to the component-level model, the average relative error of each performance parameter is less than 0.5 %, and the real-time performance is improved by about 12 times. Finally, the optimization principle of the minimum pollutant emission mode is discussed. The feasible sequential quadratic programming (FSQP) algorithm is selected, and the fuel quantity and throat area of the tail nozzle are taken as control variables. Numerical simulations are performed in the typical mission envelope. Simulation results show that the CO emission index decreases by 5 % and the NOx emission index decreases by more than 6.5 % through performance optimization control of the minimum pollutant emission mode under the premise of ensuring constant engine thrust and meeting other constraints.