• DocumentCode
    2628238
  • Title

    Study on the Optimization Design of Hydro-pneumatic Spring Based on Genetic Algorithm

  • Author

    Zhanfang, Li ; Junling, Tong

  • Author_Institution
    Coll. of Appl. Sci. & Technol., China Univ. of Min. & Technol., Xuzhou, China
  • Volume
    3
  • fYear
    2011
  • fDate
    6-7 Jan. 2011
  • Firstpage
    568
  • Lastpage
    571
  • Abstract
    Genetic algorithm (GA) was used to solve the multi-objective non-linear optimization design of a hydro-pneumatic spring. To develop the genetic algorithm of the optimization of hydro-pneumatic spring, a weighted sum was used to normalize the four objectives of ride comfort, suspension stroke, road holding and road friendliness with fixed weight, linear fitness scaling was used to enhance the global search ability of GA, and adaptive penalty method was used to handle the constraint conditions besides the range of design variables. Optimization design examples of 2 and 5 design variables were practiced, analysis based on testing and simulating shows that the comprehensive performance of the hydro-pneumatic suspension increases by 50.66% and 118.18% respectively comparing with the non-optimized one, which confirms the validity of this method.
  • Keywords
    design engineering; genetic algorithms; pneumatic systems; springs (mechanical); suspensions (mechanical components); GA global search ability; adaptive penalty method; genetic algorithm; hydropneumatic spring; hydropneumatic suspension; linear fitness scaling; multiobjective nonlinear optimization design; ride comfort; road friendliness; road holding; suspension stroke; Gallium; Mathematical model; Optimization; Pistons; Springs; Suspensions; Vibrations; Genetic algorithm; Hydro-pneumatic spring; Multi-objective; Non-linear; Optimization design;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Measuring Technology and Mechatronics Automation (ICMTMA), 2011 Third International Conference on
  • Conference_Location
    Shangshai
  • Print_ISBN
    978-1-4244-9010-3
  • Type

    conf

  • DOI
    10.1109/ICMTMA.2011.712
  • Filename
    5721549