• DocumentCode
    3133059
  • 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
  • Volume
    2
  • fYear
    2011
  • fDate
    20-21 Aug. 2011
  • Firstpage
    390
  • Lastpage
    393
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing, Control and Industrial Engineering (CCIE), 2011 IEEE 2nd International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-9599-3
  • Type

    conf

  • DOI
    10.1109/CCIENG.2011.6008146
  • Filename
    6008146