Genetic algorithm-based optimum vehicle suspension design using minimum dynamic pavement load as a design criterion

Lu Sun, Ximing Cai, Jun Yang

Research output: Contribution to journalArticle

Abstract

In this paper, the design of a passive vehicle suspension system was handled in the framework of nonlinear optimization. The variance of the dynamic load resulting from the vibrating vehicle operating at a constant speed was used as the performance measure of a suspension system. Using a quarter-car model, the performance measure was derived as an integration of a complex function of several variables. A genetic algorithm is applied to solve the nonlinear optimization problem. It was found from the sensitivity analysis that appropriate mutation rate, crossover rate and population size are 1.0%, 25% and 100, respectively. The optimum design parameters of the suspension systems obtained are ks = 622,180 N / m, kt = 1,705,449 N / m and cs = 26,582 N s / m, respectively.

Original languageEnglish (US)
Pages (from-to)18-27
Number of pages10
JournalJournal of Sound and Vibration
Volume301
Issue number1-2
DOIs
StatePublished - Mar 20 2007

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Mechanics of Materials
  • Acoustics and Ultrasonics
  • Mechanical Engineering

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