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文章基本信息

  • 标题:Design of Optimal Linear Suspension for Quarter Car with Human Model using Genetic Algorithms
  • 本地全文:下载
  • 作者:Saeed Badran ; Ashraf Salah ; Wael Abbas
  • 期刊名称:International Journal of ACM Jordan
  • 印刷版ISSN:2078-7952
  • 电子版ISSN:2078-7960
  • 出版年度:2012
  • 卷号:II
  • 期号:II
  • 出版社:ACM Jordan ISWSA Professional Chapter
  • 摘要:

    This paper presents an optimization of a four-degrees-of-freedom vehicle?s human with seat suspension system using genetic algorithms (GA) to determine vehicle suspension parameters to achieve the best comfort of the human. Maximum allowed vertical acceleration of the human body and the suspension working space were used as constrained limits in this study. The genetic algorithm is applied to solve the optimization problem. The optimization results are compared through step and sinusoidal excitation of the seat suspension system for the optimal and currently used suspension systems. In case of sinusoidal profile excitation, results showed that RMS acceleration of the driver, seat suspension working space and sprung mass are reduced by about 21%, 21.5% and 20.3%, respectively. At step profile excitation, RMS acceleration of the driver, seat suspension working space and sprung mass are reduced by about 24%, 24.98% and 7.15%, respectively. The optimal design parameters of the suspension systems obtained are ks= 10039 N/m and cs= 900 N.s/m in case of sinusoidal input and ks= 10030 N/m and cs= 913 N.s/m in case of step input, respectively.

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