This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Characteristics of Rail Pressure Fluctuations under Two-Injection Conditions and the Control Strategy Based on ANN
Technical Paper
2017-01-2212
ISSN: 0148-7191, e-ISSN: 2688-3627
Annotation ability available
Sector:
Language:
English
Abstract
High-pressure common rail (HPCR) fuel injection system is the most widely used fuel system in diesel engines. However, when multiple injection strategy is used, the pressure wave fluctuation is un-avoided due to the opening and closing of the needle valve which will affect the subsequent fuel injection and combustion characteristics. In this paper, several parameters: injection pressure, injection intervals, the main injection pulse widths are investigated on a common rail fuel injection test rig with two injection pulses to explore their effect on the fuel injection rate and fuel quantity. The result showed that the longer injection interval between the pilot and main injections will lead to a rail pressure drop at the beginning of the main injection so that a smaller fuel quantity will be delivered. The main injection pulse width also influences fuel injection rate and the main fuel quantity. The fuel injection rate plays a dominant role on fuel quantity when the main injection pulse width is less than 600 us in the current case. For the rather complicated injection system, a control strategy based on ANN (artificial neural network) with the BP algorithm is adopted to predict intervals, fuel injection pulse width and thus the fuel quantity. First, the injection interval is predicted by the required injection pressure and then the injection pulse width is predicted by injection rate and fuel injection quantity. The model is tested by experiments and the results show that the error is less than 5% between prediction and measurement.
Authors
Topic
Citation
Peng, J., Ma, M., Weizhi, W., Bai, F. et al., "Characteristics of Rail Pressure Fluctuations under Two-Injection Conditions and the Control Strategy Based on ANN," SAE Technical Paper 2017-01-2212, 2017, https://doi.org/10.4271/2017-01-2212.Also In
References
- Carlucci , P. , Ficarella , A. , Chiara , F. , Giuffrida , A. et al. Preliminary Studies on the Effects of Injection Rate Modulation on the Combustion Noise of a Common Rail Diesel Engine SAE Technical Paper 2004-01-1848 2004 10.4271/2004-01-1848
- Fuyuto , T. , Taki , M. , Ueda , R. , Hattori , Y. et al. Noise and Emissions Reduction by Second Injection in Diesel PCCI Combustion with Split Injection SAE Int. J. Engines 7 4 1900 1910 2014 10.4271/2014-01-2676
- Liu , B. , Jia , M. , and Peng , Z. An Investigation of Multiple-Injection Strategy in a Diesel PCCI Combustion Engine SAE Technical Paper 2010-01-1134 2010 10.4271/2010-01-1134
- de Risi , A. , Naccarato , F. , and Laforgia , D. Experimental Analysis of Common Rail Pressure Wave Effect on Engine Emissions SAE Technical Paper 2005-01-0373 2005 10.4271/2005-01-0373
- Baumann , J. , Kiencke , U. , Schlegl , T. , and Oestreicher , W. Practical Feasibility of Measuring Pressure Waves in Common Rail Injection Systems by Magneto-Elastic Sensors SAE Technical Paper 2006-01-0891 2006 10.4271/2006-01-0891
- Tanabe , K. , Kohketsu , S. , and Nakayama , S. Effect of Fuel Injection Rate Control on Reduction of Emissions and Fuel Consumption in a Heavy Duty DI Diesel Engine SAE Technical Paper 2005-01-0907 2005 10.4271/2005-01-0907
- Beierer , P. , Huhtala , K. , Lehto , E. , and Vilenius , M. Study of the Impact of System Characteristics on Pressure Oscillations in a Common Rail Diesel Fuel Injection System SAE Technical Paper 2005-01-0910 2005 10.4271/2005-01-0910
- Pickett , L. , Manin , J. , Payri , R. , Bardi , M. et al. Transient Rate of Injection Effects on Spray Development SAE Technical Paper 2013-24-0001 2013 10.4271/2013-24-0001
- Herfatmanesh M R , Peng Z , Ihracska A et al. 2016 Characteristics of pressure wave in common rail fuel injection system of high-speed direct injection diesel engines Advances in Mechanical Engineering 8 5 1 8 10.1177/1687814016648246
- Badami , M. , Millo , F. , and D'Amato , D. Experimental Investigation on Soot and NOx Formation in a DI Common Rail Diesel Engine with Pilot Injection SAE Technical Paper 2001-01-0657 2001 10.4271/2001-01-0657
- Horibe , N. , Annen , T. , Miyazaki , Y. , and Ishiyama , T. Heat Release Rate and NOx Formation Process in Two-Stage Injection Diesel PCCI Combustion in a Constant-Volume Vessel SAE Technical Paper 2010-01-0608 2010 10.4271/2010-01-0608
- Beierer , P. , Huhtala , K. , and Vilenius , M. Experimental Study of the Hydraulic Circuit of a Commercial Common Rail Diesel Fuel Injection System SAE Technical Paper 2007-01-0487 2007 10.4271/2007-01-0487
- Herfatmanesh , Mohammad Reza , Lu Pin , Attar Mohammadreza Anbari , and Zhao Hua 2013 Experimental Investigation into the Effects of Two-Stage Injection on Fuel Injection Quantity, Combustion and Emissions in a High-Speed Optical Common Rail Diesel Engine Fuel 109 137 47 10.1016/j.fuel.2013.01.013
- Bianchi , G. , Falfari , S. , Parotto , M. , and Osbat , G. Advanced Modeling of Common Rail Injector Dynamics and Comparison with Experiments SAE Technical Paper 2003-01-0006 2003 10.4271/2003-01-0006
- Kalogirou Soteris A. Artificial intelligence for the modeling and control of combustion processes: a review 2003 Progress in Energy and Combustion Science 29 515 566
- Hertz J , Krogh A , Palmer R G 1991 Introduction to the theory of neural computation American Journal of Physics 62 7 668
- Najafi , G. , Ghobadian B. , Tavakoli T. , Buttsworth D.R. , Yusaf T.F. , and Faizollahnejad M. 2009 Performance and Exhaust Emissions of a Gasoline Engine with Ethanol Blended Gasoline Fuels Using Artificial Neural Network Applied Energy 86 5 630 39 10.1016/j.apenergy.2008.09.017
- Canakci , Mustafa , Erdil Ahmet , and Arcaklioǧlu Erol 2006 Performance and Exhaust Emissions of a Biodiesel Engine Applied Energy 83 6 594 605 10.1016/j.apenergy.2005.05.003
- Çelik , Veli , and Arcaklioǧlu Erol 2005 Performance Maps of a Diesel Engine Applied Energy 81 3 247 59 10.1016/j.apenergy.2004.08.003
- Li , H. , Butts , K. , Zaseck , K. , Liao-McPherson , D. et al. Emissions Modeling of a Light-Duty Diesel Engine for Model-Based Control Design Using Multi-Layer Perceptron Neural Networks SAE Technical Paper 2017-01-0601 2017 10.4271/2017-01-0601
- Uzun , Abdullah 2014 Air Mass Flow Estimation of Diesel Engines Using Neural Network Fuel 117 833 38 10.1016/j.fuel.2013.09.078
- Hafner , M. , Schuler , M. , Nelles , O. , Isermann , R. Fast neural networks for diesel engine control design Control Engngineer Pracicet 8 11 1211 21 2000 org/10.1016/S0967-0661(00)00057-5
- Park , S. , Yoon , P. , Sunwoo , M. Feedback error learning neural networks for spark advance control using cylinder pressure Proceedings of the Institution Mechanical Engineers Part D: J Automobile Engineering 2001 215 D5 625 36
- Najafi , G. , Ghobadian B. , Tavakoli T. , Buttsworth D.R. , Yusaf T.F. , and Faizollahnejad M. 2009 Performance and Exhaust Emissions of a Gasoline Engine with Ethanol Blended Gasoline Fuels Using Artificial Neural Network Applied Energy 86 5 630 39 10.1016/j.apenergy.2008.09.017
- Li Jing , Cheng Ji-hang , Shi Jing-yuan , Huang Fei 2012 Brief Introduction of Back Propagation (BP) Neural Network Algorithm and Its Improvement In Advances in Computer Science and Information Engineering Volume 2 553 58