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Statements

Subject Item
n2:RIV%2F68407700%3A21220%2F14%3A00227476%21RIV15-MSM-21220___
rdf:type
n13:Vysledek skos:Concept
rdfs:seeAlso
http://waset.org/Publications/XML?abstract=14423&t=bibtex
dcterms:description
*Particle swarm optimization (PSO) algorithm has attracted significant consideration among a lot of modern heuristic optimization techniques. Nowadays, PSO is widely applied in various scientific and engineering fields. This paper concerns the investigation of design the passive suspension system parameters of heavy vehicles using the non-linear PSO algorithm, for the first time. A mathematical model and the equations of motion of a passive quarter vehicle suspension are derived and simulated using Matlab/Simulink software. The proposed PSO algorithm aims to minimize the dynamic tyre load generated by vehicle–pavement interaction as the objective function with constraint the natural frequency of the unsprung mass. It is applied to solve the nonlinear optimization problem to find the tyre stiffness, suspension stiffness and the damping coefficient of the passive damper by identifying the optimal problem solution through cooperation and competition among the individuals of a swarm. Suspension performance criteria are evaluated in the time and frequency domains in order to quantify the obtained parameters under bump and random road disturbance. Compared with the passive suspension system optimized using the Genetic Algorithm (GA), the proposed PSO algorithm improves the suspension performance effectively and gives a superior performance. *Particle swarm optimization (PSO) algorithm has attracted significant consideration among a lot of modern heuristic optimization techniques. Nowadays, PSO is widely applied in various scientific and engineering fields. This paper concerns the investigation of design the passive suspension system parameters of heavy vehicles using the non-linear PSO algorithm, for the first time. A mathematical model and the equations of motion of a passive quarter vehicle suspension are derived and simulated using Matlab/Simulink software. The proposed PSO algorithm aims to minimize the dynamic tyre load generated by vehicle–pavement interaction as the objective function with constraint the natural frequency of the unsprung mass. It is applied to solve the nonlinear optimization problem to find the tyre stiffness, suspension stiffness and the damping coefficient of the passive damper by identifying the optimal problem solution through cooperation and competition among the individuals of a swarm. Suspension performance criteria are evaluated in the time and frequency domains in order to quantify the obtained parameters under bump and random road disturbance. Compared with the passive suspension system optimized using the Genetic Algorithm (GA), the proposed PSO algorithm improves the suspension performance effectively and gives a superior performance.
dcterms:title
*Enhancement of Suspension System Performance Performance of Heavy Vehicles through the Optimized Parameters Using Particle Swarm Technique (ICCV Paris) *Enhancement of Suspension System Performance Performance of Heavy Vehicles through the Optimized Parameters Using Particle Swarm Technique (ICCV Paris)
skos:prefLabel
*Enhancement of Suspension System Performance Performance of Heavy Vehicles through the Optimized Parameters Using Particle Swarm Technique (ICCV Paris) *Enhancement of Suspension System Performance Performance of Heavy Vehicles through the Optimized Parameters Using Particle Swarm Technique (ICCV Paris)
skos:notation
RIV/68407700:21220/14:00227476!RIV15-MSM-21220___
n3:aktivita
n9:P
n3:aktivity
P(LO1311)
n3:dodaniDat
n15:2015
n3:domaciTvurceVysledku
El Sawaf, Ahmed n11:4484061 Metered, Hassan Ahmed Mohamed n11:3361195
n3:druhVysledku
n6:D
n3:duvernostUdaju
n17:C
n3:entitaPredkladatele
n10:predkladatel
n3:idSjednocenehoVysledku
14683
n3:idVysledku
RIV/68407700:21220/14:00227476
n3:jazykVysledku
n19:eng
n3:klicovaSlova
Suspension system; heavy vehicles, parameters design; parameters optimization; particle swarm technique
n3:klicoveSlovo
n5:Suspension%20system n5:parameters%20design n5:heavy%20vehicles n5:parameters%20optimization n5:particle%20swarm%20technique
n3:kontrolniKodProRIV
[9BA9821685D0]
n3:mistoKonaniAkce
Brussels
n3:mistoVydani
Toronto
n3:nazevZdroje
ICAMME 2014 - Transactions on Mechanical and Mechatronics Engineering Vol:2, No:10, 2014
n3:obor
n16:JT
n3:pocetDomacichTvurcuVysledku
4
n3:pocetTvurcuVysledku
4
n3:projekt
n20:LO1311
n3:rokUplatneniVysledku
n15:2014
n3:tvurceVysledku
Vampola, Tomáš Metered, Hassan Ahmed Mohamed El Sawaf, Ahmed Šika, Zbyněk
n3:typAkce
n21:WRD
n3:zahajeniAkce
2014-10-05+02:00
s:issn
1307-6892
s:numberOfPages
7
n14:hasPublisher
World Academy of Science, Engineering and Technology
n18:organizacniJednotka
21220