Vibration Optimization of a passive suspension System via Genetic Algorithm

In this paper, we have formulated mathematical models to optimize the bouncing transmissibility of the sprung mass of the half car system with passengers' seat suspensions considering different road conditions. The corresponding problem has been solved with the help of advanced real coded Genetic Algorithm (GA). The nonlinearity of suspension spring and damper, which are the most important characteristics of the suspension, has been taken into account in order to validate the model to real applications. The nonlinear cubic polynomial has been used to describe the spring characteristic and a quadratic polynomial has been used to describe the damper characteristic. The coefficients of each polynomial represent the design parameters of the suspension system and are to be determined. To find these parameters we have formulated a nonlinear optimization problem in which the bouncing transmissibility of the sprung mass at the center of mass has been minimized with respect to technological constraints and the constraints which satisfy the performance as per ISO 2631 standards. The advanced real coded GA has been used to solve this problem in time domain and the results obtained have been compared to those obtained using the existing design parameters. The objective function and the constraints have been evaluated by simulating the vehicle model over two roads with multiple bumps at uniform velocity.

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