• DocumentCode
    2070788
  • Title

    Additional fuel system optimization for CNG vehicle base on MDO method

  • Author

    Fang, Lu ; Deng-feng, Wang

  • Author_Institution
    State Key Lab. of Automotive Simulation & Control, Jilin Univ., Changchun, China
  • fYear
    2011
  • fDate
    16-18 Dec. 2011
  • Firstpage
    770
  • Lastpage
    774
  • Abstract
    Usually CNG vehicle is modified based on conventional vehicle in structure, the additional fuel system is very heavy due to its gas and structure, which increases the danger of potential gas leakage and explosion. Therefore the safety and reliability of the CNG vehicle should be highly emphasized. In this paper, we analyze the characteristic fuel structure of CNG vehicle and emphatically study on rear impact and NVH performance. A finite element model of CNG vehicle for rear impact and NVH analysis was created. Using OPTIMUS software with multidisciplinary feasible algorithm which integrated with Pam-Crash and MD Nastran software for collaborative optimization, we made the additional fuel system lighter and fit all requirements. From sensitivity analysis of initial design space we found sensitive ingredient of structure, and built response surface model for these sensitive parts as design parameters base on RBF function. We apply an adaptive evolutionary algorithm with discrete variables to find global optimal solution on response surface. Calculated results show that the response surfaces have high accuracy, and the optimization calculation converges very fast. Finally the mass of additional fuel system is significantly reduced, and the model and MDO method is proved to be effective and correct.
  • Keywords
    design engineering; evolutionary computation; explosions; finite element analysis; fuel systems; leak detection; natural gas technology; reliability; response surface methodology; road safety; road vehicles; sensitivity analysis; CNG vehicle reliability; CNG vehicle safety; MD Nastran software; MDO method; NVH performance analysis; OPTIMUS software; Pam-Crash; RBF function; adaptive evolutionary algorithm; additional fuel system optimization; collaborative optimization; finite element model; gas explosion; global optimal solution; multidisciplinary feasible algorithm; potential gas leakage; response surface model; sensitivity analysis; Finite element methods; Fuels; Optimization; Response surface methodology; Safety; Software; Vehicles; CNG vehicle; MDO; NVH; crash safety; lightweight;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Transportation, Mechanical, and Electrical Engineering (TMEE), 2011 International Conference on
  • Conference_Location
    Changchun
  • Print_ISBN
    978-1-4577-1700-0
  • Type

    conf

  • DOI
    10.1109/TMEE.2011.6199316
  • Filename
    6199316