Development of an ANN based system identification tool to estimate the performance-emission characteristics of a CRDI assisted CNG dual fuel diesel engine

Journal of Natural Gas Science and Engineering

Volumn 21, Issue , 2014, Pages 147-158

  Roy, Sumit ^a   Banerjee, Rahul ^a   Das, Ajoy Kumar ^a   Bose, Probir Kumar ^a  

^a NATIONAL INSTITUTE OF TECHNOLOGY   (India)

Author keywords

Artificial neural network; CNG; CRDI; Dual fuel; Engine performance; Exhaust emissions

Indexed keywords

DIESEL ENGINES; ELECTRON EMISSION; FUELS; MEAN SQUARE ERROR; NEURAL NETWORKS;

CRDI; DUAL-FUELS; EMISSION CHARACTERISTICS; ENGINE PERFORMANCE; EXHAUST EMISSION; MEAN ABSOLUTE PERCENTAGE ERROR; PERFORMANCE AND EMISSIONS; ROOT MEAN SQUARE ERRORS; CNG;

DUAL FUEL ENGINES; NEURAL NETWORKS;

EID: 84906482966     PISSN: 18755100     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jngse.2014.08.002     Document Type: Article

References (62)

1. Arcaklioǧlu E. Çelikten İ. A diesel engine's performance and exhaust emissions. Appl. Energy 2005, 80:11-22.
2. Badami M., Nuccio P., Trucco G. Influence of injection pressure on the performance of a DI diesel engine with a common rail fuel injection system. SAE Int. 1999, 1999-01-0193. 10.4271/1999-01-0193.
3. Balusamy T., Marappan R. Effect of injection time and injection pressure on CI engine fuelled with Methyl Ester of Thevetia Peruviana Seed oil. Int. J. Green Energy 2010, 7:397-409.
4. Bose P.K., Banerjee R. An experimental investigation on the role of hydrogen in the emission reduction and performance trade-off studies in an existing diesel engine operating in dual fuel mode under exhaust Gas recirculation. J.Energy Resour. Technol. 2012, 134. 012601.
5. x emissions and injection timing of a low heat rejection diesel engine. Int. J. Therm. Sci. 2008, 47:1096-1106.
6. Canakci M., Erdil A., Arcaklioǧlu E. Performance and exhaust emissions of a biodiesel engine. Appl. Energy 2006, 83:594-605.
7. Carlucci A.P., de Risi A., Laforgia D., Naccarato F. Experimental investigation and combustion analysis of a direct injection dual-fuel diesel-natural gas engine. Energy 2008, 33:256-263.
8. Cascetta F., Rotondo G., Musto M. Measuring of compressed natural gas in automotive application: a comparative analysis of mass versus volumetric metering methods. Flow. Meas. Instrum. 2008, 19:338-341.
9. Cay Y. Prediction of a gasoline engine performance with artificial neural network. Fuel 2013, 111:324-331.
10. Çay Y., Çiçek A., Kara F., Saǧiroǧlu S. Prediction of engine performance for an alternative fuel using artificial neural network. Appl. Therm. Eng. 2012, 37:217-225.
11. Çelik V., Arcaklioǧlu E. Performance maps of a diesel engine. Appl. Energy 2005, 81:247-259.
12. Cortés O., Urquiza G., Hernández J.A. Optimization of operating conditions for compressor performance by means of neural network inverse. Appl. Energy 2009, 86:2487-2493.
13. de Lucas A., Durán A., Carmona M., Lapuerta M. Modeling diesel particulate emissions with neural networks. Fuel 2001, 80:539-548.
14. Delagrammatikas G.J., Assanis D.N. Development of a neural network model of an advanced, turbocharged diesel engine for use in vehicle-level optimization studies. Proc. Inst. Mech. Eng. Part D J. Automob. Eng. 2004, 218:521-533.
15. Desantes J.M., Benajes J., Molina S., González C.A. The modification of the fuel injection rate in heavy-duty diesel engines: part 2: effects on combustion. Appl. Therm. Eng. 2004, 24:2715-2726.
16. Devan P.K., Mahalakshmi N.V. Performance, emission and combustion characteristics of poon oil and its diesel blends in a DI diesel engine. Fuel 2009, 88:861-867.
17. Dyntar D., Onder C., Guzzella L. Modeling and control of CNG engines. SAE Int. 2002, 2002-01-1295. 10.4271/2002-01-1295.
18. Fritz S.G., Egbuonu R.I. Emissions from heavy-duty trucks converted to CNG. J.Eng. Gas Turbines Power 1992, 114:561-567.
19. Ghobadian B., Rahimi H., Nikbakht A.M., Najafi G., Yusaf T.F. Diesel engine performance and exhaust emission analysis using waste cooking biodiesel fuel with an artificial neural network. Renew. Energy 2009, 34:976-982.
20. Gölcü M., Sekmen Y., Erduranli P., Sahir Salman M. Artificial neural-network based modeling of variable valve-timing in a spark-ignition engine. Appl. Energy 2005, 81:187-197.
21. Isermann R., Sinsel S., Schaffnit J. Modeling and real-time simulation of diesel engines for control design. SAE Int. 1998, 980796. 10.4271/980796.
22. Johnson T.V. Diesel emission control in review. SAE Int. J. Fuels Lubr. 2008, 1:68-81.
23. Johnson T.V. Review of diesel emissions and control. SAE Int. J. Fuels Lubr. 2010, 3:16-29.
24. Johnson T.V. Diesel emissions in review. SAE Int. J. Engines 2011, 4:143-157.
25. Kalam M.A., Masjuki H.H. An experimental investigation of high performance natural gas engine with direct injection. Energy 2011, 36:3563-3571.
26. Kalogirou S.A. Artificial intelligence for the modeling and control of combustion processes: a review. Prog. Energy Combust. Sci. 2003, 29:515-566.
27. Kannan G.R., Anand R. Experimental investigation on diesel engine with diestrol-water micro emulsions. Energy 2011, 36:1680-1687.
28. Kara Togun N., Baysec S. Prediction of torque and specific fuel consumption of a gasoline engine by using artificial neural networks. Appl. Energy 2010, 87:349-355.
29. x emission. Fuel 2004, 83:885-895.
30. Kusaka J., Okamoto T., Daisho Y., Kihara R., Saito T. Combustion and exhaust gas emission characteristics of a diesel engine dual- fueled with natural gas. JSAE Rev. 2000, 21:489-496.
31. Kvenvolden K.A. Natural gas hydrate occurrence and issues. Ann. N. Y. Acad. Sci. 1994, 715:232-246.
32. Liu J., Yang F., Wang H., Ouyang M., Hao S. Effects of pilot fuel quantity on the emissions characteristics of a CNG/diesel dual fuel engine with optimized pilot injection timing. Appl. Energy 2013, 110:201-206.
33. Maiboom A., Tauzia X., 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 2008, 33:22-34.
34. Maji S., Pal A., Arora B.B. Use of CNG and Diesel in CI Engines in Dual Fuel Mode 2008, The Automotive Research Association of India.
35. Mani M., Nagarajan G. Influence of injection timing on performance, emission and combustion characteristics of a DI diesel engine running on waste plastic oil. Energy 2009, 34:1617-1623.
36. McGeehan J.A., Yeh S., Couch M., Hinz A., Otterholm B., Walker A., et al. On the road to 2010 emissions: field test results and analysis with DPF-SCR system and ultra low Sulfur diesel fuel. SAE Int. 2005, 2005-01-3716. 10.4271/2005-01-3716.
37. Millo F., Ferraro C.V., Bernardi M.G., Barbero S., Pasero P. Experimental and computational analysis of different EGR systems for a common rail passenger car diesel engine. SAE Int. J. Engines 2009, 2:527-538.
38. Minato A., Tanaka T., Nishimura T. Investigation of premixed lean diesel combustion with ultra high pressure injection. SAE Int. 2005, 2005-01-0914. 10.4271/2005-01-0914.
39. Mohamed Ismail H., Ng H.K., Queck C.W., Gan S. Artificial neural networks modelling of engine-out responses for a light-duty diesel engine fuelled with biodiesel blends. Appl. Energy 2012, 92:769-777.
40. Nagata K., Tanaka Y., Yano K. Technologies of DENSO common rail for diesel engine and consumer values 2004, Convergence Transportation Electronics Association.
41. Najafi G., Ghobadian B., Tavakoli T., Buttsworth D.R., Yusaf T.F., Faizollahnejad M. Performance and exhaust emissions of a gasoline engine with ethanol blended gasoline fuels using artificial neural network. Appl. Energy 2009, 86:630-639.
42. Oǧuz H., Saritas I., Baydan H.E. Prediction of diesel engine performance using biofuels with artificial neural network. Expert Syst. Appl. 2010, 37:6579-6586.
43. Papadimitriou I., Warner M., Silvestri J., Lennblad J., Tabar S. Neural network based fast-running engine models for control-oriented applications. SAE Int. 2005, 2005-01-0072. 10.4271/2005-01-0072.
44. Parlak A., Islamoglu Y., Yasar H., Egrisogut A. Application of artificial neural network to predict specific fuel consumption and exhaust temperature for a diesel engine. Appl. Therm. Eng. 2006, 26:824-828.
45. Paul A., Bose P.K., Panua R.S., Banerjee R. An experimental investigation of performance-emission trade off of a CI engine fueled by diesel-compressed natural gas (CNG) combination and diesel-ethanol blends with CNG enrichment. Energy 2013, 55:787-802.
46. Payri F., Benajes J., Arrègle J., Riesco J.M. Processus de combustion et émissions de polluants d'un moteur diesel de poids lourd fonctionnant avec une phase de combustion en prémélange augmentée par retard à l'injection. Oil Gas Sci. Technol. Rev. IFP 2006, 61:247-258.
47. Pickett L.M., Siebers D.L. Non-sooting, low flame temperature mixing-controlled DI diesel combustion. SAE Int. 2004, 2004-01-1399. 10.4271/2004-01-1399.
48. Pierpont D.A., Reitz R.D. Effects of injection pressure and nozzle geometry on D.I. Diesel emissions and performance. SAE Int. 1995, 950604. 10.4271/950604.
49. Rakopoulos C.D., Dimaratos A.M., Giakoumis E.G., Rakopoulos D.C. Investigating the emissions during acceleration of a turbocharged diesel engine operating with bio-diesel or n-butanol diesel fuel blends. Energy 2010, 35:5173-5184.
50. x-BSFC trade-off characteristics of a CRDI assisted diesel engine -an EPA perspective. J.Nat. Gas Sci. Eng. 2014, 20:221-240.
51. Roy S., Banerjee R., Bose P.K. Performance and exhaust emissions prediction of a CRDI assisted single cylinder diesel engine coupled with EGR using artificial neural network. Appl. Energy 2014, 119:330-340.
52. Sayin C., Ertunc H.M., Hosoz M., Kilicaslan I., Canakci M. Performance and exhaust emissions of a gasoline engine using artificial neural network. Appl. Therm. Eng. 2007, 27:46-54.
53. Schubiger R., Bertola A., Boulouchos K. Influence of EGR on combustion and exhaust emissions of heavy duty DI-diesel engines equipped with common-rail injection systems. SAE Int. 2001, 2001-01-3497. 10.4271/2001-01-3497.
54. Shayler P.J., Goodman M., Ma T. The exploitation of neural networks in automotive engine management systems. Eng. Appl. Artif. Intell. 2000, 13:147-157.
55. Shimazaki N., Tsurushima T., Nishimura T. Dual mode combustion concept with premixed diesel combustion by direct injection near top dead center. SAE Int. 2003, 2003-01-0742. 10.4271/2003-01-0742.
56. Shivakumar Srinivasa, Pai P., Shrinivasa Rao B.R. Artificial neural network based prediction of performance and emission characteristics of a variable compression ratio CI engine using WCO as a biodiesel at different injection timings. Appl. Energy 2011, 88:2344-2354.
57. Sözen A. Arcaklioǧlu E. Solar potential in Turkey. Appl. Energy 2005, 80:35-45.
58. Suh H.K. Investigations of multiple injection strategies for the improvement of combustion and exhaust emissions characteristics in a low compression ratio (CR) engine. Appl. Energy 2011, 88:5013-5019.
59. Thurnheer T., Edenhauser D., Soltic P., Schreiber D., Kirchen P., Sankowski A. Experimental investigation on different injection strategies in a heavy-duty diesel engine: emissions and loss analysis. Energy Convers. Manag. 2011, 52:457-467.
60. Yang F., Minggao O. Experimental research on EGR in a diesel engine equipped with common rail injection system. SAE Int. 2003, 2003-01-0351. 10.4271/2003-01-0351.
61. Yusaf T.F., Buttsworth D.R., Saleh K.H., Yousif B.F. CNG-diesel engine performance and exhaust emission analysis with the aid of artificial neural network. Appl. Energy 2010, 87:1661-1669.
62. Zhao H. Advanced direct injection combustion engine technologies and development. Diesel Engines 2010, vol. 2. Woodhead Publishing Limited, Cambridge, UK.