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dc.contributor.authorCallejo, Alfonso
dc.contributor.authorGarcia de Jalon, Javier
dc.date.accessioned2015-02-13T15:52:08Z
dc.date.available2015-02-13T15:52:08Z
dc.date.issued2015-02
dc.identifier.citationCallejo Alfonso, de Jalón Javier García. Vehicle Suspension Identification Via Algorithmic Computation of State and Design Sensitivities J. Mech. Des. 137(2), 021403 (2015) (9 pages); Paper No: MD-14-1399en_US
dc.identifier.issn1050-0472
dc.identifier.otherWOS:000348069800004
dc.identifier.urihttp://dx.doi.org/10.1115/1.4029027
dc.identifier.urihttp://hdl.handle.net/10057/11064
dc.descriptionClick on the DOI link to access the article (may not be free).en_US
dc.description.abstractIt is common in mechanical simulation to not know the value of key system parameters. When the simulation is very sensitive to those design parameters and practical or budget limitations prevent the user from measuring the real values, parameter identification methods become essential. Kalman filter methods and optimization methods are the most widespread approaches for the identification of unknown parameters in multibody systems. A novel gradient-based optimization method, based on sensitivity analyses for the computation of machine-precision gradients, is presented in this paper. The direct differentiation approach, together with the algorithmic differentiation of derivative terms, is employed to compute state and design sensitivities. This results in an automated, general-purpose and robust method for the identification of parameters. The method is applied to the identification of a real-life vehicle suspension system (namely of five stiffness coefficients) where both smooth and noisy reference responses are considered. The identified values are very close to the reference ones, and everything is carried out with limited user intervention and no manual computation of derivatives.en_US
dc.description.sponsorshipMinistry of Science and Innovation of Spain under OPTIVIRTEST (TRA2009-14513-C02-01) and DOPTCARR (TRA2012-38826-C02-01) Research Projects, and of the Education Department of the Government of Navarra.en_US
dc.language.isoen_USen_US
dc.publisherAmerican Society of Mechanical Engineersen_US
dc.relation.ispartofseriesJournal of Mechanical Design;v.137:no.2
dc.subjectParameter-estimationen_US
dc.subjectMultibody systemsen_US
dc.subjectDynamic-systemsen_US
dc.subjectOptimizationen_US
dc.titleVehicle suspension identification via algorithmic computation of state and design sensitivitiesen_US
dc.typeArticleen_US
dc.rights.holder© 2015 ASME


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