Intrinsic Design of Experiments for Modeling of Internal Combustion Engines

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Sjöblom, Jonas,1968Chalmers tekniska högskola,Chalmers University of Technology (author)

Intrinsic Design of Experiments for Modeling of Internal Combustion Engines

Article/chapterEnglish2018

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2018-04-03
400 Commonwealth Drive, Warrendale, PA, United States :SAE International,2018

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LIBRIS-ID:oai:research.chalmers.se:3b7b41c0-228d-4cc6-8ff1-439ca9a1c746
https://doi.org/10.4271/2018-01-1156DOI
https://research.chalmers.se/publication/502865URI

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Language:English
Summary in:English

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Subject category:ref swepub-contenttype

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In engine research and development there are often different engine parameters that produce similar effects on the end-point results. When calibrating modern engines, a huge number of parameters needs to be set, which also includes compensation parameters for model imperfections. In this context, simpler, more robust, and physically based models should be beneficial both for calibration work load and powertrain performance. In this study, we present an experimental methodology that uses intermediate ("intrinsic") variables instead of engine parameters. By using simple thermodynamic models, the engine parameters EGR, IVC, and P Boost could be translated into oxygen concentration, temperature and gas density at the start of injection. The reason for this transformation of data is to "move" the Design of Experiment (DoE) closer to the situation of interest (i.e. the combustion) and to be able to construct simpler and more physically based models. In this example, the system was a diesel engine. However, the method can be applied to any experimental system that shares the non-intrinsic nature (e.g. the internal combustion engine), which makes this methodology general. The approach was demonstrated for a heavy-duty diesel engine and five design variables were investigated. Regression models were made using either the engine variables or the intrinsic variables and the resulting regression coefficients were compared and contrasted. By using exactly the same experiments but described in a different way (using the intrinsic variables), the optimization task becomes facilitated. Furthermore, by using physical properties instead of engine settings, these models should be more general and more robust during powertrain optimization.

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Andric, Jelena,1979Chalmers tekniska högskola,Chalmers University of Technology(Swepub:cth)jelenaa (author)
Faghani, EthanVolvo Group (author)
Chalmers tekniska högskolaVolvo Group (creator_code:org_t)

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In:SAE Technical Papers400 Commonwealth Drive, Warrendale, PA, United States : SAE International2018-April0148-71912688-3627

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ENGINEERING AND TECHNOLOGY: ENGINEERING AND ...; and Mechanical Engin ...; and Other Mechanical ...

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