A physics-based control-oriented combustion model is developed to accurately predict in-cylinder pressure and temperature of a diesel engine. The model is under the assumption that the combustion chamber consists of three zones: a liquid fuel zone, a reaction zone, and an unmixed zone. These zones are formulated to account for three key events in diesel combustion: fuel evaporation, chemical reaction, and fuel-air mixing, respectively. The liquid fuel zone is assumed to be of spherical shape. The evaporation of fuel is governed by Fick’s first law of diffusion. The reaction zone is modeled as a reactive system consisting of six species and two reaction steps. The burn rate is calculated based on species concentrations and reaction zone temperature. The unmixed zone contains only air and inert gas. The results of simulations are compared to the test data from a GM 6.7 L 8-cylinder Duramax diesel engine. The multi-zone model is shown to be capable of predicting in-cylinder pressure accurately with more degree of freedoms, compared to the singlezone reaction-based model.
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ASME 2017 Dynamic Systems and Control Conference
October 11–13, 2017
Tysons, Virginia, USA
Conference Sponsors:
- Dynamic Systems and Control Division
ISBN:
978-0-7918-5829-5
PROCEEDINGS PAPER
A Multi-Zone Reaction-Based Diesel Combustion Model for Model-Based Control Available to Purchase
Yifan Men,
Yifan Men
Michigan State University, East Lansing, MI
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Guoming G. Zhu
Guoming G. Zhu
Michigan State University, East Lansing, MI
Search for other works by this author on:
Yifan Men
Michigan State University, East Lansing, MI
Guoming G. Zhu
Michigan State University, East Lansing, MI
Paper No:
DSCC2017-5074, V003T27A003; 8 pages
Published Online:
November 14, 2017
Citation
Men, Y, & Zhu, GG. "A Multi-Zone Reaction-Based Diesel Combustion Model for Model-Based Control." Proceedings of the ASME 2017 Dynamic Systems and Control Conference. Volume 3: Vibration in Mechanical Systems; Modeling and Validation; Dynamic Systems and Control Education; Vibrations and Control of Systems; Modeling and Estimation for Vehicle Safety and Integrity; Modeling and Control of IC Engines and Aftertreatment Systems; Unmanned Aerial Vehicles (UAVs) and Their Applications; Dynamics and Control of Renewable Energy Systems; Energy Harvesting; Control of Smart Buildings and Microgrids; Energy Systems. Tysons, Virginia, USA. October 11–13, 2017. V003T27A003. ASME. https://doi.org/10.1115/DSCC2017-5074
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