Nonlinear Stochastic Analysis of Motorcycle Dynamics

dc.contributor.advisorSpanos, Pol D.
dc.contributor.committeeMemberBarrera, Enrique V.
dc.contributor.committeeMemberDick, Andrew J.
dc.contributor.committeeMemberDuenas-Osorio, Leonardo
dc.creatorRobledo Ricardo, Luis
dc.date.accessioned2013-09-16T16:36:39Z
dc.date.accessioned2013-09-16T16:36:43Z
dc.date.available2013-09-16T16:36:39Z
dc.date.available2013-09-16T16:36:43Z
dc.date.created2013-05
dc.date.issued2013-09-16
dc.date.submittedMay 2013
dc.date.updated2013-09-16T16:36:43Z
dc.description.abstractOff-road and racing motorcycles require a particular setup of the suspension to improve the comfort and the safety of the rider. Further, due to ground unevenness, off-road motorcycle suspensions usually experience extreme and erratic excursions in performing their function. In this regard, the adoption of nonlinear devices, such as progressive springs and hydro pneumatic shock absorbers, can help limiting both the acceleration experienced by the sprung mass and the excursions of the suspensions. For dynamic analysis purposes, this option involves the solution of the nonlinear differential equations that govern the motion of the motorcycle, which is excited by the stochastic road ground profile. In this study a 4 degrees-of-freedom (4-DOF) nonlinear motorcycle model is considered. The model involves suspension elements with asymmetric behaviour. Further, it is assumed that the motorcycle is exposed to loading of a stochastic nature as it moves with a specified speed over a road profile defined by a particular power spectrum. It is shown that a meaningful analysis of the motorcycle response can be conducted by using the technique of statistical linearization. The validity of the proposed approach is established by comparison with results from pertinent Monte Carlo studies. In this context the applicability of auto-regressive (AR) filters for efficient implementation of the Monte Carlo simulation is pointed out. The advantages of these methods for the synthesis of excitation signals from a given power spectrum, are shown by comparison with other methods. It is shown that the statistical linearization method allows the analysis of multi-degree-of-freedom (M-DOF) systems that present strong nonlinearities, exceeding other nonlinear analysis methods in both accuracy and applicability. It is expected that the proposed approaches, can be used for a variety of parameter/ride quality studies and as preliminary design tool by the motorcycle industry.
dc.format.mimetypeapplication/pdf
dc.identifier.citationRobledo Ricardo, Luis. "Nonlinear Stochastic Analysis of Motorcycle Dynamics." (2013) Diss., Rice University. <a href="https://hdl.handle.net/1911/72032">https://hdl.handle.net/1911/72032</a>.
dc.identifier.slug123456789/ETD-2013-05-411
dc.identifier.urihttps://hdl.handle.net/1911/72032
dc.language.isoeng
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.
dc.subjectMotorcycle dynamics
dc.subjectNonlinear mechanics
dc.subjectStochastic dynamics
dc.subjectMonte Carlo simulations
dc.subjectAuto-regressive filter
dc.subjectStatistical linearization
dc.subjectMotorcycle modeling
dc.subjectRoad roughness
dc.subjectDynamics and Vibrations
dc.titleNonlinear Stochastic Analysis of Motorcycle Dynamics
dc.typeThesis
dc.type.materialText
thesis.degree.departmentMechanical Engineering and Materials Science
thesis.degree.disciplineEngineering
thesis.degree.grantorRice University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy
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