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The Study On Control And Optimal Of Suspension Based On ADAMS

Posted on:2006-02-20Degree:MasterType:Thesis
Country:ChinaCandidate:L Q ChenFull Text:PDF
GTID:2132360182956522Subject:Vehicle Engineering
Abstract/Summary:PDF Full Text Request
The paper regards a pickup vehicle as the research object, using ADAMS to suspension optimization design and controlling system study. First, Simulation model of the double wishbone independent suspension is established by using ADAMS software and analysis is carried out. An interface file of ADAMS software and C language is designed. Optimization design based on hereditary algorithm and ADAMS is realized. Comparing with optimizing before, simulation results show that the optimizing after improve performance of suspension. Second, the multi-body dynamic model of a pickup vehicle is established in which suspension, body, steering system and tire are considered, which is then validated by using vehicle field tests. Using optimization toolkit, optimization design can be performed repeatedly until an optimizing result is achieved. Comparing with optimizing before, simulation results show that the optimizing after improve both the ride and handling performance of the vehicle. Third, a PID control system is designed for active suspension system by using control toolkits, simulation can be performed repeatedly until satisfactory control parameters are achieved. Finally, a Stochastic control system is designed for active suspension system by using MATLAB/SIMULINK software ,in addition to which a data exchange interface with ADAMS/view is defined, the proposed control algorithm is integrated with the multi-body dynamic vehicle model and the co-simulations can be performed repeatedly until a satisfactory controller is achieved. Comparing with a conventional passive system, simulation results show that the proposed active suspension considerably improves both the ride and handling performance of the vehicle.
Keywords/Search Tags:Suspension, Hereditary algorithm, Co-Simulation, PID Control, Stochastic Control
PDF Full Text Request
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