Multi-objective Robust Optimization of Automobile Suspension Parameters Considering Random Factors

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Journal of Vibration and Shock ›› 2009, Vol. 28 ›› Issue (11) : 146-149.

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Multi-objective Robust Optimization of Automobile Suspension Parameters Considering Random Factors

WANG Tao;Tao Wei

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Abstract

For robustly improving automobile ride comfort and decreasing tire dynamic load to road, the four-degree-of-freedom suspension model was established for study. Monte carlo and self-adaptive MOGA were applied to solving the multi-objective robust optimization of suspension parameters, which taking the statistic mean and standard deviation of root-mean-square value of vertical acceleration of body, front and rear tire dynamic load as objective functions. The results show that the spring stiffness decreases, the coefficient of damper increases and the performance gets better. Compared with the traditional multi-objective optimization method, the method can improve the reliability of the design.

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Suspension system / Monte carlo / MOGA / Robust optimization

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WANG Tao;Tao Wei. Multi-objective Robust Optimization of Automobile Suspension Parameters Considering Random Factors[J]. Journal of Vibration and Shock, 2009, 28(11): 146-149