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Predicting the Nitrogen Oxides Emissions of a Diesel Engine using Neural Networks
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 14, 2015 by SAE International in United States
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Nitrogen oxides emissions are an important aspect of engine design and calibration due to increasingly strict legislation. As a consequence, accurate modeling of nitrogen oxides emissions from Diesel engines could play a crucial role during the design and development phases of vehicle powertrain systems. A key step in future engine calibration will be the need to capture the nonlinear behavior of the engine with respect to nitrogen oxides emissions within a rapid-calculating mathematical model. These models will then be used in optimization routines or on-board control features.
In this paper, an artificial neural network structure incorporating a number of engine variables as inputs including torque, speed, oil temperature and variables related to fuel injection is developed as a method of predicting the production of nitrogen oxides based on measured test data. A multi-layer perceptron model is identified and validated using data from dynamometry tests.
The model predicts exhaust nitrogen oxide concentrations under different engine conditions with satisfactory accuracy. The developed neural network model has potential applications in real-time control aimed at reducing nitrogen oxides emission levels.
CitationZhang, Q., Pennycott, A., Burke, R., Akehurst, S. et al., "Predicting the Nitrogen Oxides Emissions of a Diesel Engine using Neural Networks," SAE Technical Paper 2015-01-1626, 2015, https://doi.org/10.4271/2015-01-1626.
- European Commission, “Regulation (EC) No 715/2007 of the European Parliament and of the Council of 20 June 2007 on type approval of motor vehicles with respect to vehicle repair and maintenance information”, 2007.
- European Commission, “Commission proposal to limit the CO2 emissions from cars to help fight climate change, reduce fuel costs and increase European competitiveness”, 2007.
- Heywood, J.B., “Internal Combustion Engine Fundamentals”, McGraw-Hill, 1988.
- Pang, H., Brace, C., and Akehurst, S., “Potential of a Controllable Engine Cooling System to Reduce NOx Emissions in Diesel Engines,” SAE Technical Paper 2004-01-0054, 2004, doi:10.4271/2004-01-0054.
- Burke, R.D., Brace, C.J., Cox, A., Lewis, A., Hawley, J.G. and Pegg, I., “Systems approach to the improvement of engine warm-up behaviour.” Proceedings of the Institution of Mechanical Engineers Part D - Journal of Automotive Engineering, 2011. 225(2):190-205.
- Wijetunge, R., Brace, C., Hawley, J., Vaughan, N. et al., “Dynamic Behaviour of a High Speed Direct Injection Diesel Engine,” SAE Technical Paper 1999-01-0829, 1999, doi:10.4271/1999-01-0829.
- 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.
- Kalogirou, S.A., “Artificial intelligence for the modeling and control of combustion processes: a review.” Progress in Energy and Combustion Science, 2003. 29(6):515-566.
- Deh Kiani, M.K., Ghobadian, B., Tavakoli, T., Nikbakht, A. and Najafi, G., “Artificial neural-network modeling of variablevalve timing in a spark-ignition engine.” Energy, 2010. 35(1):65-69.
- He, Y. and Rutland, C., “Modeling of a Turbocharged DI Diesel Engine Using Artificial Neural Networks,” SAE Technical Paper 2002-01-2772, 2002, doi:10.4271/2002-01-2772.
- Burke, R.D., Baumann, W., Akehurst, S. and Brace, C., “Dynamic modelling of Diesel emissions using the parametric Volterra Series.” Proceedings of the Institution of Mechanical Engineers Part D: Journal of Automotive Engineering, 2014. 228(2):164-179
- Cybenko, G., “Approximation by superpositions of a sigmoidal function.” Mathematics of Control, Signals, and Systems, 1989. 2(4):303-314.
- Burke, R.D, Fath, B., Akehurst, S., Brace, C.J., Baumann, W. and Wascheck, R., “Practical approach to thermodynamic modelling of Diesel engine emissions.” Design of Experiments in Engine Development, 6th Edition. Expert Verlag, Berlin, Germany, 2011.
- Baumann, W., Klug, K., Kohler, B.-U., and Ropke, K., “Modelling of transient Diesel engine emissions.” 5th Conference on the Design of Experiments (DoE) in Engine Development, Berlin, Germany 2009. 29-30.
- Guhmann, C. and Riedel, J.-M., “Comparison of identification methods for nonlinear dynamic systems.” 6th Conference on the Design of Experiments (DoE) in Engine Development, Berlin, Germany, 2011. 41-53.