Dynamic modeling and optimization: the natural extension to classical DoE
Dynamic modeling and optimization: the natural extension to classical DoE
- New search for: Knaak, Mirko
- New search for: Schoop, Ulrike
- New search for: Barzantny, Berthold
- New search for: Knaak, Mirko
- New search for: Schoop, Ulrike
- New search for: Barzantny, Berthold
This paper introduces dynamic model-based calibration. The model-based engine calibration process, based on DoE has been proven in the last years to be an effective method to significantly reduce the measurement time for engine calibration. Currently it mainly focuses on steady-state calibration, but a large part of engine calibration is based on time-dependent or dynamic effects. The extension to dynamic model-based calibration is the next logical development step to further reduce the measuring effort. The scope of this paper is a new complete framework for dynamic model-based calibration developed by IAV that includes Extended Parametric Volterra Series (EPV) as a powerful model family for data-driven models; a methodology and tool chain for model fitting and model structure identification; and Dynamic Programming as an effective optimization method. The new process has been successfully applied to start and warm-up calibration, catalyst modeling, or prediction of static values (rapid measurement). Several results are shown in the end of this paper.
Document information
Dynamic modeling and optimization: the natural extension to classical DoE
2007
12 Seiten, 8 Bilder, 10 Quellen
Conference paper
English
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