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Pareto Optimization of Vehicle Suspension Vibration for a Nonlinear Half-car Model Using a Multi-objective Genetic Algorithm

Author Affiliations

  • 1Mechanical Engineering, Guilan University, Rasht, IRAN
  • 2 Mechanical and Aerospace Engineering, Malek Ashtar University of Technology, Shahin Shahr, IRAN

Res. J. Recent Sci., Volume 1, Issue (8), Pages 17-22, August,2 (2012)


In this paper, multi-objective genetic algorithm (MOGA) is used for Pareto optimization of a four degree of freedom vehicle vibration model. Vehicle suspension design must fulfill some conflicting criteria. Among those is ride comfort which is attained by reducing the sprung mass accelerations via suspension spring and damper. Moreover, good handling or road holding capability of a vehicle which is attained by minimize front and rear suspension deflection is a desirable property which requires stiff suspension and therefore is in contrast with a vehicle with ride comfort. Therefore, Multi-objective Genetic Algorithm (MOGA) is used for Pareto approach optimization of passive suspension system. The important conflicting objectives that have been considered in this work are, ride comfort and handling performance. Moreover, this approach returns the optimum answers in Pareto form that designer can, by making trade-offs, select desired answer. Finally, the simulation result shows that optimization of suspension settings will improve ride comfort and road holding capability simultaneously


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