چكيده به لاتين
The suspension optimization can be categorized into some basic steps. First of all, the optimization method should be chosen. In this study, a modified version of genetic algorithm is used for multi-objective optimization problems called multi-objective genetic algorithm with Non-dominated Sorting Genetic Algorithm-II (NSGA-II). In the next step, the dynamic model will be chosen. Since the model has significant effect on design variables, objective functions and constraints, choosing the dynamic model has particular importance. In this study, the Adams software is utilized for the full vehicle dynamic model which is applicable in multi-body dynamic applications. The design variables, objective functions and constraints will be chosen in the next step. The double lane change test and straight line acceleration to the velocity of 100 meters per second are considered as objective functions based on the passenger comfort and handling standards. The spring stiffness and damping coefficient of damper are presented as design variables. For the fact that the spring stiffness coefficient in original car model of L90 has linear behavior, a constant value is used to describe the spring stiffness. Besides, 4 design parameters are described in nonlinear function for introducing the damping coefficient behavior in this model. The main goal of this study is to determine the optimized amount of vehicle suspension parameters for product of national platform. Due to the high similarity between the chassis of this vehicle and L90, the results are obtained based on the L90 vehicle model. In order to account the full vehicle dynamic model in optimization operation the Adams software is utilized in interface with Matlab Simulink software. The results indicated that, although optimization of the full vehicle model need much time, but also this approach is applicable to find the optimized value of spring stiffness and damping coefficient.
