A family base optimization of a developed nonlinear vehicle suspension model using gray family design algorithm

Abstract

The primary purpose of this paper is to present a novel algorithm for designing a family of variants. This platform base algorithm is utilized for designing suspension system for a family of Renault Logan cars. In this case, a gray penalty function is presented to minimize variations between suspension parameters and generate suspension variants which have most commonality between each other in different cars of the family. This study developed a nonlinear mathematical model in order to simulate the dynamic performance of suspension system. Therefore, a novel suspension model is presented based on combining vehicle vibration model and geometry suspension model which are subjected to a random vibration road profile excitation and gray family design algorithm. Geometry suspension model analyzes the effect of suspension parameters (i.e., hard points, length of arms, camber angle and caster angle) on the stability, ride and handling of the vehicle. Vehicle vibration model investigates the influence of seat location, damping and spring coefficients on the driver seat acceleration, roll angular and pitch angular acceleration, relative displacement and sprung mass acceleration. The results achieved by the simulation of the full vehicle in ADAMS/CAR and experimental test of Renault Logan car, which have been done in one of main Iranian automakers (SAIPA), demonstrate the accuracy of the novel model. Comparing the results of the family base suspension model and results of ADAMS/CAR simulation indicates the beneficial of this algorithm and its usage in designing suspension system.