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Parameters Optimization Design Of Suspension And Steering System Based On ADAMS

Posted on:2018-08-21Degree:MasterType:Thesis
Country:ChinaCandidate:J ZhangFull Text:PDF
GTID:2322330512478089Subject:Vehicle Engineering
Abstract/Summary:PDF Full Text Request
The suspension and steering system are one of the most important parts of vehicle chassis.Due to the kinematic characteristics of them have an directly influence on the handling stability and ride comfort of vehicle,the optimization design of them is a great important task of chassis development.In this paper,the optimization design of hardpoint coordinates was undertaken with an accurate coupled vehicle model developed by Adams/Car.Firstly,the front and rear suspension,steering and type subsystems was developed in ADAMS/Insight.The modal analysis of beam and antiroll bar of rear torsion beam suspension were carried out using Hyperworks,and the corresponding modal neutral file were transferred into the subsystem of ADAMS/Car.The coupled vehicle model was assembled with the subsystem mentioned-above.It is indicated that the model can be applied to subsequent optimization based on result of the comparison of simulation and real vehicle test.Then,the sensitivity analysis of Macpherson suspension and steering system were undertaken to select the design variables.Owing to the optimization of steering is a single optimal problem,the response surface method(RSM)method was used to optimize the steering system in ADAMS/Insight.Finally,due to the optimization of Macpherson suspension is a multi-objective problem,the multi-objective optimization models of the front wheel parameters was formulated using RSM method,where weighted parameters were determined Based on the goal programming method.The Multi Objective Particle Swarm Optimization(MOPSO)algorithm was used to sovel the optimization models.It is indicated that the goal programming method and MOPSO algorithm are effectively way to chassis optimization.
Keywords/Search Tags:Macpherson Suspension, Steering System, Sensitivity Analysis, Particle Swarm Algorithm, Optimization Design
PDF Full Text Request
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