Reconfigurable modelling of physically based systems: Dynamic modelling and optimisation for product design and development applied to the automotive drivetrain system.

Abstract

The work of this thesis is concerned with the aggregation and advancement of modelling practise as used within modern day product development and optimisation environments making use of Model Based Design (¿MBD¿) and similar procedures. A review of model development and use forms the foundation of the work, with the findings being aggregated into two unique approaches for rapid model development and reconfiguration; the Plug-and-Simulate (¿PaS¿) approach and the Paradigm for Large Model Creation (¿PLMC¿); each shown to posses its own advantages. To support the MBD process a model optimisation algorithm that seeks to eliminate parameters that are of little or no significance to a simulation is developed. Eliminations are made on the basis of an energy analysis which determines the activity of a number of energy elements. Low activity elements are said to be of less significance to the global dynamics of a model and thus become targets for elimination. A model configuration tool is presented that brings together the PLMC and parameter elimination algorithm. The tool is shown to be useful for rapid configuration and reconfiguration of models and is capable of automatically running the optimisation algorithms thus producing a simulation model that is parametrically and computationally optimised. The response of the plug-and-simulate drivetrain submodels, assembled to represent a front wheel drive drivetrain, is examined. The resulting model is subjected to a torque step-input and an empirically obtained torque curve that characterises the input to a drivetrain undergoing steady acceleration. The model displays the expected response in both its full parameter and parameter reduced versions with simulation efficiency gains observed in the parameter reduced version.