Multi-objective evolutionary optimization design of vehicle magnetorheological fluid damper

Abstract

Structure design and parameters selection are crucial steps in developing magnetorheological fluid (MRF) damper for vehicle semi-active suspension system. Most traditional methods for deciding structure parameters by experiential expressions are unilateral and imprecise. In this paper, a multiobjective evolutionary optimization approach will be used to solve the optimization design problem. Based on Bingham fluid models, a structure design for MRF damper with shearing valve mode is completed for vehicle suspension. To reduce the dynamic response time and to enlarge the range the controllable damping force are taken as the optimization objectives. Three crucial parameters, including gap width, effective axial pole length and coil turns number are taken as optimization variables, a hybrid evolutionary algorithm combining particle swarm optimization (PSO) and crossover is employed to search for the Pareto solutions, According to the optimized results, a new type MRF damper design is accomplished for a pickup truck suspension system. The proposed method and analysis present a beneficial reference for MRF damper design.