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Neural network modelling of automotive dampers for variable temperature operation and suspension system tuning

This thesis focuses on modelling of passive hydraulic automotive dampers for use in computationally-fast vehicle-dynamic simulation. An extended version of the Duym and Reybrouck 1998 physical model is examined to enable work with high frequency input displacements. This computationally-expensive model is verified with real damper data under both isothermal and variable temperature regular, and random (Pave) input displacement conditions. Initially the extension includes just additional input kinematics to account for inertial effects, with an imposed temperature profile. Subsequently a heat generation model is developed to include appropriate energy losses. When the heat generation model is coupled to the damper model, naturally-generated transient-temperature operation of the damper can be accounted for.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:496859
Date January 2009
CreatorsAlghafir, Mohammed Najib
PublisherUniversity of Sussex
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation

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