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Analysis and modeling of exhaust gas temperature in an ethanol fuelled HCCI engine

Abstract

Low exhaust temperature in homogeneous charge compression ignition (HCCI) significantly limits efficiency of an exhaust aftertreatment system to mitigate high HC and CO emissions in HCCI engines. This article aims to understand the effect of varying input parameters on HCCI exhaust gas temperature (Texh) for an ethanol fuelled engine. A single cylinder engine is used to collect experimental data at 100 different HCCI conditions. The results indicate that variation in combustion parameters such as start of combustion (SOC), burn duration (BD) and maximum in-cylinder pressure (Pmax) are not effectively correlated with variations of Texh, but the indicated mean effective pressure (IMEP) and constant-volume adiabatic flame temperature (Tad) are strongly related to Texh. These experimental findings were then used to design an artificial neural network (ANN) model to predict Texh. The model was validated with the experimental data, indicating an average error less than 4.5°C between predicted and measured Texh.

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Correspondence to Bahram Bahri.

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Recommended by Associate Editor Kyoung Dong Min

Bahram Bahri received his B.S. and M.S. degree in Mechanical engineering from Shiraz University, Shiraz, Iran, in 2001 and 2006, respectively. He is currently a PhD student of Mechanical engineering (automotive) in Universiti Teknologi Malaysia (UTM). He worked for 2 years in the automotive industry (Saipa Automotive Company) from 2006 to 2008. His research interests include internal combustion engines specially LTC, alternative fuel and thermodynamics.

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Bahri, B., Aziz, A.A., Shahbakhti, M. et al. Analysis and modeling of exhaust gas temperature in an ethanol fuelled HCCI engine. J Mech Sci Technol 27, 3531–3539 (2013). https://doi.org/10.1007/s12206-013-0879-z

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  • DOI: https://doi.org/10.1007/s12206-013-0879-z

Keywords

  • HCCI
  • Ethanol combustion
  • Exhaust gas temperature
  • Artificial neural network