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The cold start hydrocarbon emission from the increasing population of two wheelers in countries like India is one of the research issues to be addressed. This work describes the prediction of cold start hydrocarbon emissions from air cooled spark ignition engines through fuzzy logic technique. Hydrocarbon emissions were experimentally measured from test engines of different cubic capacity, at different lubricating oil temperature and at different idling speeds with and without secondary air supply in exhaust. The experimental data were used as input for modeling average hydrocarbon emissions for 180 seconds counted from cold start and warm start of gasoline bike engines. In fuzzy logic simulation, member functions were assigned for input variables (cubic capacity and idling rpm) and output variables (average hydrocarbon emission for first 180 seconds at cold start and warm start). The knowledge based rules were adopted from the analyzed experimental data and separate simulations were carried out for predicting hydrocarbon emissions from engines equipped with and without secondary air supply. The simulation yielded the average hydrocarbon emissions of air cooled gasoline engine for a set of given input data with accuracy over 90%.
PAPER REVISED: 2013-03-25
PAPER ACCEPTED: 2013-07-18
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THERMAL SCIENCE YEAR 2014, VOLUME 18, ISSUE Issue 1, PAGES [179 - 191]
  1. Heywood, J. B., Internal Combustion Engine Fundamentals, McGraw- Hill Publications, New York, USA, 1998
  2. Weilenmann, M., Favez, J. Y., Alvarez, R., Cold-start emissions of modern passenger cars at different low ambient temperatures and their evolution over vehicle legislation categories, Atmospheric Environment, 43 (2009), pp.2419-2429
  3. Favez. J. Y., Weilenmann. M., Stilli. J., Cold start extra emissions as a function of engine stop time: Evolution, over the last 10 years, Atmospheric Environment, 43 (2009). pp. 996-1007
  4. Park, J. H., et al., A fast and quantitative assay for developing zeolite type hydrocarbon trap catalyst, Microporous and Mesoporous Materials, 101 (2007), pp.264-270
  5. Yeon. T. H., et al., Adsorption and desorption characteristics of hydrocarbons in multi-layered, hydrocarbon traps, Microporous and Mesoporous Materials, 119, (2009), pp.349-355
  6. Miao, Y., et al., Study of SCR cold-start by energy method, Chemical Engineering Journal, 155 (2009), pp. 260-265
  7. Twigg, M. V., Roles of catalytic oxidation in control of vehicle exhaust emissions, Catalysis Today, 117 (2006), pp.407-418
  8. Twigg, M. V., Progress and future challenges in controlling automotive exhaust gas emissions, Applied Catalysis B, Environmental, 70 (2007), pp.2-15
  9. Farid, M. M., et al., A review on phase change energy storage: materials and applications, Energy Conversion and Management, 45 (2004), pp.1597-1615
  10. Gumus, M., Reducing cold-start emission from internal combustion engines by means of thermal energy storage system, Applied Thermal Engineering, 29 (2009), pp.652-660
  11. Lou, H.H., Huang, Y.L., Fuzzy-logic-based process modeling using limited experimental data, Engineering Applications of Artificial Intelligence, 13 (2000), pp.121-135
  12. Castellano, G., et al., Knowledge discovery by a neuro-fuzzy modeling framework, Fuzzy Sets and Systems, 149 (2005), pp.187-207
  13. Tasdemir, S., et al., Artificial neural network and fuzzy expert system comparison for prediction of performance and emission parameters on a gasoline engine, Expert Systems with Applications, 38 (2011), pp.13912-13923
  14. Ikonen, E., Najim, K., Kortela, U., Neuro-fuzzy modelling of power plant flue-gas emissions, Engineering Applications of Artificial Intelligence, 13 (2000), pp.705-717
  15. Zhou, Q.,et al., Modeling of the carbon dioxide capture process system using machine intelligence approaches, Engineering Applications of Artificial Intelligence, 24 (2011), pp.673-685
  16. Lughofer, E., et al., Identifying static and dynamic prediction models for NOx emissions with evolving fuzzy systems, Applied Soft Computing, 11 (2011), pp.2487-2500
  17. Keynejad, F., Manzie, C., Cold start modeling of spark ignition engines, Control Engineering Practice, 19 (2011), pp.912-925
  18. Ntziachristos, L., Samaras, Z., An empirical method for predicting exhaust emissions of regulated pollutants from future vehicle technologies, Atmospheric Environment, 35 (2001), pp.1985-1999

© 2023 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence