Misfire detection based on statistical analysis for an ethanol fueled HCCI engine
many serious problems are known to be due to partial burning and misfire in ethanol fueled hcci engines. new methods for misfire detection play important roles in hcci engine operation and exhaust after treatment system. in this article, statistical analysis technique is introduced for misfire det...
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my.utm.472212019-03-31T08:34:54Z http://eprints.utm.my/id/eprint/47221/ Misfire detection based on statistical analysis for an ethanol fueled HCCI engine Bahri, Bahram Shahbakhti, Mahdi Abdul Aziz, Azhar Muhamad Said, Mohd. Farid TJ Mechanical engineering and machinery many serious problems are known to be due to partial burning and misfire in ethanol fueled hcci engines. new methods for misfire detection play important roles in hcci engine operation and exhaust after treatment system. in this article, statistical analysis technique is introduced for misfire detection which is studied on a reference diesel-converted hcci using ethanol as fuel. an artificial misfire was produced for a 0.3 liter diesel converted hcci engine with port fuel injection system and statistical analysis based on in-cylinder pressure and crankshaft rotational speed was conducted. variations of kurtosis and skewness analysis of in-cylinder pressure and crankshaft rotational speed were compared to max heat release rate. the results indicate that in misfire cycles, some engine parameters such as imep and heat release decrease substantially. skewness of engine rotational speed is a reliable factor for misfire detection in an hcci engine and all misfire cycles have negative skew values. Praise Worthy Prize S.r.l 2012 Article PeerReviewed Bahri, Bahram and Shahbakhti, Mahdi and Abdul Aziz, Azhar and Muhamad Said, Mohd. Farid (2012) Misfire detection based on statistical analysis for an ethanol fueled HCCI engine. International Review of Mechanical Engineering, 6 (6). pp. 1276-1282. ISSN 1970-8734 |
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TJ Mechanical engineering and machinery Bahri, Bahram Shahbakhti, Mahdi Abdul Aziz, Azhar Muhamad Said, Mohd. Farid Misfire detection based on statistical analysis for an ethanol fueled HCCI engine |
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many serious problems are known to be due to partial burning and misfire in ethanol fueled hcci engines. new methods for misfire detection play important roles in hcci engine operation and exhaust after treatment system. in this article, statistical analysis technique is introduced for misfire detection which is studied on a reference diesel-converted hcci using ethanol as fuel. an artificial misfire was produced for a 0.3 liter diesel converted hcci engine with port fuel injection system and statistical analysis based on in-cylinder pressure and crankshaft rotational speed was conducted. variations of kurtosis and skewness analysis of in-cylinder pressure and crankshaft rotational speed were compared to max heat release rate. the results indicate that in misfire cycles, some engine parameters such as imep and heat release decrease substantially. skewness of engine rotational speed is a reliable factor for misfire detection in an hcci engine and all misfire cycles have negative skew values. |
format |
Article |
author |
Bahri, Bahram Shahbakhti, Mahdi Abdul Aziz, Azhar Muhamad Said, Mohd. Farid |
author_facet |
Bahri, Bahram Shahbakhti, Mahdi Abdul Aziz, Azhar Muhamad Said, Mohd. Farid |
author_sort |
Bahri, Bahram |
title |
Misfire detection based on statistical analysis for an ethanol fueled HCCI engine |
title_short |
Misfire detection based on statistical analysis for an ethanol fueled HCCI engine |
title_full |
Misfire detection based on statistical analysis for an ethanol fueled HCCI engine |
title_fullStr |
Misfire detection based on statistical analysis for an ethanol fueled HCCI engine |
title_full_unstemmed |
Misfire detection based on statistical analysis for an ethanol fueled HCCI engine |
title_sort |
misfire detection based on statistical analysis for an ethanol fueled hcci engine |
publisher |
Praise Worthy Prize S.r.l |
publishDate |
2012 |
url |
http://eprints.utm.my/id/eprint/47221/ |
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1643652262658048000 |