Title :
QPSO algorithm in aeroengine performance optimization of application
Author :
E-er-dun, Bao ; Xiao-ping, Wang ; Jian-ping, Xue ; Qin, Liu ; Fa-wei, Wang
Author_Institution :
Eng. Coll., Air Force Eng. Univ., Xian, China
Abstract :
A novel and practical method which is Quantum-behaved Particle Swam Optimization (QPSO) algorithm is applied in one type of turbo fan engine performance optimization. In this paper, by comparison with PSO algorithm, QPSO algorithm have obvious advantages. The simulation is carried out under different altitudes and velocities. The result shows that thrust can be increased by 7% ~ 9% under maximum thrust mode and improved by 0.3% ~ 3.7% than that is optimized by Particle Swam Optimization (PSO) algorithm. Meanwhile, fuel consumption can be decreased by 2% ~ 3% under the minimum fuel consumption mode. The influence of initial values on PSO algorithm is reduced and the problem of being easily trapped in local optimal values is solved as well. Apparently, the algorithm is of great application value.
Keywords :
jet engines; particle swarm optimisation; QPSO algorithm; aeroengine performance optimization; fuel consumption mode; quantum-behaved particle swam optimization algorithm; turbo fan engine performance; Engines; Fuels; Genetic algorithms; Optimization; Particle swarm optimization; Propulsion; Sun; Particle Swam Optimization algorithm; Performance optimization; Quantum-behaved Particle Swam Optimization algorithm; Turbo fan engine;
Conference_Titel :
Computing, Control and Industrial Engineering (CCIE), 2011 IEEE 2nd International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-9599-3
DOI :
10.1109/CCIENG.2011.6008146