Multi-Criteria Optimization of an Innovative Suspension System for Race Cars

Abstract

The purpose of the present work was to design, optimize, and test an innovative suspension system for race cars. The study was based on a comprehensive approach that involved conceptual design, modeling, simulation and optimization, and development and testing of the experimental model of the proposed suspension system. The optimization process was approached through multi-objective optimal design techniques, based on design of experiments (DOE) investigation strategies and regression models. At the same time, a synthesis method based on the least squares approach was developed and integrated in the optimal design algorithm. The design in the virtual environment was achieved by using the multi-body systems (MBS) software package ADAMS, more precisely ADAMS/View—for modeling and simulation, and ADAMS/Insight—for multi-objective optimization. The physical prototype of proposed suspension system was implemented and tested with the help of BlueStreamline, the Formula Student race car of the Transilvania University of Brașov. The dynamic behavior of the prototype was evaluated by specific experimental tests, similar to those the single seater would have to pass through in the competitions. Both the virtual and experimental results proved the performance of the proposed suspension system, as well as the usefulness of the design algorithm by which the novel suspension was developed.

Kinematics & Compliance Validation of a Vehicle Suspension and Steering Kinematics Optimization Using Neural Networks

“…Steering linkage of a bus is optimized using RSM approach [9]. Multi-criteria optimization of a suspension system is realized utilizing the conventional regression models [10]. DOE approach is used for a solid axle of a heavy commercial vehicle on optimizing steering kinematics which used statistical analysis [11].…”

Optimal Design of Agricultural Mobile Robot Suspension System Based on NSGA-III and TOPSIS

“…The results showed that the improved algorithm outperformed the traditional multi-objective particle swarm algorithm and the genetic algorithm. Totu and Alexandru [21] presented a comprehensive design method based on the least squares approach for the optimal design of an innovative racing car suspension system. This study used Adams/View and Adams/Insight to build a regression model and carry out the optimization design.…”

A Method for Finding the Static Equilibrium of the Non-Steered Wheel Suspension Systems Used in Passenger Cars

“…Frequently, to simplify the theoretical models, the bushings are modeled by spherical (ball) joints, thus neglecting the linear deformations (which are, however, very small compared to the angular ones) [2][3][4][5][6][7]. In the case of the triangular guidance bars, with double articulation to the chassis and/or wheel carrier, as the case may be, the two afferent spherical connections determine, in fact, a revolute joint.…”