Abstract :
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Shock absorber is widely used on vehicle. The purposes of the shock absorber are to dissipate the energy accumulated by the suspension spring displacement, controlling thus the vertical motion between vehicle body and tires. The shock absorber has great influence on both ride and handling performance of vehicles, and a great many previous researches have been done on modeling and simulation of the shock absorber, the models and parameters presented in those researches are always based on drawings, observations, measurements, experiences, and so on. However, because of the human mistakes and errors in the manufacture, and a lack of information, certain information and precise values do not exist, uncertainty may result. Actually, the uncertainty may have great influence on the shock absorber, so it is necessary to investigate the influence of the uncertainties on the performance of the shock absorber. In this paper, a detailed twin tube shock absorber model was established using Dymola/modelica software. This model contains the piston valve assembly, base valve assembly, rebound chamber, compression chamber, reserve chamber and so on. Then a fuzzy algorithm, which is based on fuzzy set theory, is presented to analyze the response of the shock absorber with uncertain parameters. In this method, uncertain parameters such as the friction between the piston and the chamber, the dimension of the valve disc, the stiffness of the spring, etc., are described mathematically as fuzzy variables and integrated into shock abso- ber analysis. The simulations are carried out to analyze the performance of the shock absorber with uncertain parameters. The results demonstrate the method is effective to model systems with uncertain parameters.
Keywords :
automotive components; fuzzy set theory; mechanical engineering computing; modelling; pistons; shock absorbers; simulation; springs (mechanical); tyres; valves; Dymola/modelica software; base valve assembly; compression chamber; fuzzy uncertain parameters; modeling; piston valve assembly; rebound chamber; reserve chamber; shock absorber; simulation; suspension spring displacement; tires; vehicle; vertical motion; Analytical models; Computational modeling; Measurement uncertainty; Springs; Suspensions; Dymola/Modelica; fuzzy set theory; handling; ride; shock absorber; uncertainty;
