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Virtual Sensing Based on Design Engineering Simulation Models

Boekbijdrage - Boekhoofdstuk Conferentiebijdrage

Simulation models are the basis of modern product design engineering. Extending their application to the testingphase opens new opportunities for test data exploitation and allows measuring previously unmeasurable quantitiesand designing reduced test configurations. A common workflow is followed: a validated multiphysics systemmodel provides a prediction of the system states which is corrected by the estimation algorithms using the measurement data. The model can then generate data of the non-measurable quantities (e.g. virtual sensors). Whilethe general concept of virtual sensing is well adopted, the systematic reuse of design engineering simulation models to this purpose offers new opportunities.A wide range of models can be used, including analytical, lumped parameter 1D system models and 3D (FE andMultibody) models. Key is that these models should be easy to evaluate and have a small number of states, whilecapturing the dominant physics. Advanced model order reduction techniques are hence a key to enable the (re)use the complex design engineering models. A wide range of state estimation approaches has been developed such as the various classes of Kalman Filters and the Moving Horizon Estimator. All approaches require a trade-off between accuracy and computational load so that conventional estimators must be tailored to deal with highfidelity nonlinear models of industrial complexity.The approach is illustrated with a number of industrial relevant cases using various model and estimator types.This includes applications for vehicle wheel load estimation using multibody model, the use of FE models for estimating forces and strains in a suspension component, application to an electro-mechanical drivetrain and a steering system. Methodological aspects are evaluated and different estimators are compared.
Boek: ICEDyn2017
Pagina's: 1 - 16
Jaar van publicatie:2017