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A Structure and Calibration Method for Data-Driven Modeling of NOX and Soot Emissions from a Diesel Engine
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 16, 2012 by SAE International in United States
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The development and implementation of a new structure for data-driven models for NOX and soot emissions is described. The model structure is a linear regression model, where physically relevant input signals are used as regressors, and all the regression parameters are defined as grid-maps in the engine speed/injected fuel domain.
The method of using grid-maps in the engine speed/injected fuel domain for all the regression parameters enables the models to be valid for changes in physical parameters that affect the emissions, without having to include these parameters as input signals to the models. This is possible for parameters that are dependent only on the engine speed and the amount of injected fuel. This means that models can handle changes for different parameters in the complete working range of the engine, without having to include all signals that actually effect the emissions into the models.
The approach possibly also enables for the model to handle the main differences between steady-state engine operation and transient engine operation, thus possibly being able to use steady-state engine measurement data to calibrate the model, but still achieve acceptable performance for transient engine operation. This, however, is not evaluated in this study.
The model structure has been used to create models for NOX and soot emissions. These models have been calibrated using measured steady-data from a 5 cylinder Volvo passenger car diesel engine with a displacement volume of 2.4 liters, equipped with a turbocharger, an exhaust gas recirculation system, and a common rail injection system. The models estimate NOX mass flow with a root mean square error of 0.0021 g/s and soot mass flow with a root mean square error of 0.59 mg/s for the steady-state engine data used in this study.
The models are capable of reacting to different calibratable engine parameters, and they are also fast to execute. This makes them suitable for development of engine management system optimization. The models could also be implemented directly into an engine management system.
For comparison, three other fast models of different types for NOX and soot emissions have been implemented and evaluated.
CitationGrahn, M., Johansson, K., Vartia, C., and McKelvey, T., "A Structure and Calibration Method for Data-Driven Modeling of NOX and Soot Emissions from a Diesel Engine," SAE Technical Paper 2012-01-0355, 2012, https://doi.org/10.4271/2012-01-0355.
- Shrivastava, R., Hessel, R., and Reitz, R., “CFD Optimization of DI Diesel Engine Performance and Emissions Using Variable Intake Valve Actuation with Boost Pressure, EGR and Multiple Injections,” SAE Technical Paper 2002-01-0959, 2002, doi:10.4271/2002-01-0959.
- Brahma, I. and Rutland, C., “Optimization of Diesel Engine Operating Parameters Using Neural Networks,” SAE Technical Paper 2003-01-3228, 2003, doi:10.4271/2003-01-3228.
- Atkinson, C., Allain, M., and Zhang, H., “Using Model-Based Rapid Transient Calibration to Reduce Fuel Consumption and Emissions in Diesel Engines,” SAE Technical Paper 2008-01-1365, 2008, doi:10.4271/2008-01-1365.
- Brahma, I., Sharp, M., and Frazier, T., “Empirical Modeling of Transient Emissions and Transient Response for Transient Optimization,” SAE Int. J. Engines 2(1):1433-1443, 2009, doi:10.4271/2009-01-1508.
- Arsie, I., Pianese, C., and Sorrentino, M., “Control parameters optimization in automotive diesel engines via two zone modeling”, Advances in Automotive Control 5(1), 2007, doi:10.3182/20070820-3-US-2918.00058
- Heywood, J.B., “Internal Combustion Engine Fundamentals”, McGraw-Hill, Singapore, ISBN 0-07-100499-8, 1988
- Wenzel, S.P., “Modellierung der Ruβ- und NOX-Emissionen des Dieselmotors”, Ph.D. thesis, Otto-von-Guericke-Universität, Magdeburg, 2006
- Berger, B., Rauscher, F., and Lohmann, B., “Analysing Gaussian Processes for Stationary Black-Box Combustion Engine Modelling”, Proceedings of the 18th IFAC World Congress 18(1), 2011, doi:10.3182/20110828-6-IT-1002.01160
- Grahn, M., Olsson, J., and McKelvey, T., “A Diesel Engine Model For Dynamic Drive Cycle Simulations”, Proceedings of the 18th IFAC World Congress 18(1), 2011, doi: 10.3182/20110828-6-IT-1002.03541
- Mrosek, M., Sequenz, H., and Isermann, R., “Control Oriented NOX and Soot Models for Diesel Engines”, Advances in Automotive Control, 2010, doi: 10.3182/20100712-3-DE-2013.00074
- Wilhelmsson, C., Tunestål, P., Widd, B., and Johansson, R., “A Physical Two-Zone NOX Model Intended for Embedded Implementation” SAE Technical Paper 2009-01-1509, 2009, doi:10.4271/2009-01-1509.
- Sequenz, H., and Isermann, R., “Emission Model Structures for an Implementation on Engine Control Units”, Proceedings of the 18th IFAC World Congress 18(1), 2011, doi: 10.3182/20110828-6-IT-1002.03131
- Maiboom, A., Tauzia, X., and Hétet, J-F., “Experimental study of various effects of exhaust gas recirculation (EGR) on combustion and emissions of an automotive direct injection diesel engine”, Energy 33(1):22-34, 2008