Department of Mechanics, Ferdowsi University of Mashhad, Mashhad, Iran
Engineering Faculty, Ferdowsi University of Mashhad, Mashhad, Iran
In this research, the effect of shape parameters such as number of magnet wire turns, spools, thickness of the gap, and pole length in a Magneto-rheological (MR) fluid damper is analytically investigated and the optimization of these parameters is done with response surface method (RSM) which is combined Neuro-Fuzzy method and Particle Swarm Optimization (PSO) algorithm. Since the electro-magnetic and mechanical components of a Magneto-rheological (MR) fluid damper have a direct effect on the electrical power consumption, time delay and damped force, which are considered as objective functions. Because of the nonlinear behavior of the components, a robust approach is needed to predict their behaviors; therefore, Neuro-Fuzzy is utilizeded to generate a high accurate surface and PSO finds the optimum solution base on the surface. The sensitive analysis is also performed to examine the variation of the objective functions with various input parameters. In this process, the best parameters are obtained by overtaking the appropriate value of the objective functions. The results demonstrate that the optimum MR damper has provided the best configurations so that damps a maximum force in a minimum time and lowest power consumption. On the other hand, the amplitude of vibrations is significantly decreased in the presence of the optimized MR damper.