Study on particulate matter emission amount estimation model for engine control

Real drive emissions (RDE) regulation were introduced from Euro6-d regulation. In order to achieve the regulation value of PM(Particulate Matter) emission in the RDE regulation, it is effective to install GPF(Gasoline Particulate Filter) system. To prevent GPF corruption , GPF system needs “PM emiss...

Full description

Bibliographic Details
Main Authors: Ryutaro KOIWAI, Kazuhiro ORYOJI, Shinya SATO, Akihiro KOMORI
Format: Article
Language:Japanese
Published: The Japan Society of Mechanical Engineers 2022-12-01
Series:Nihon Kikai Gakkai ronbunshu
Subjects:
Online Access:https://www.jstage.jst.go.jp/article/transjsme/88/916/88_22-00227/_pdf/-char/en
_version_ 1797977081171148800
author Ryutaro KOIWAI
Kazuhiro ORYOJI
Shinya SATO
Akihiro KOMORI
author_facet Ryutaro KOIWAI
Kazuhiro ORYOJI
Shinya SATO
Akihiro KOMORI
author_sort Ryutaro KOIWAI
collection DOAJ
description Real drive emissions (RDE) regulation were introduced from Euro6-d regulation. In order to achieve the regulation value of PM(Particulate Matter) emission in the RDE regulation, it is effective to install GPF(Gasoline Particulate Filter) system. To prevent GPF corruption , GPF system needs “PM emission amount estimation model” that estimates PM emission amount from direct injection gasoline engine to estimate PM corrected amount. Some models, for example packet model and map-based model, have been proposed as PM emission amount estimation model. However, these models have problems in terms of calculation load and accuracy for On-board calculation. Purpose of this research is to study On-board PM emission amount estimation model . We proposed a new model method of physical quantities that dominate PM production. Developed model uses probability density function of mixture fraction space so that mixture and fuel adhesion can be treated uniformly as a fuel distribution in cylinder. Also, variance of mixture-derived probability density function and fuel adhesion ratio are functionalized by a second-order polynomial of engine control parameters, and can be applied to multiple operating conditions. The developed model was verified by comparison with measurement data. Under 25 degC of coolant temperature(19 operation points), the estimated error was during 0% and 59% and average estimated error was 19%.
first_indexed 2024-04-11T05:01:15Z
format Article
id doaj.art-ba9241590cb24efabc4b8f346519e7ca
institution Directory Open Access Journal
issn 2187-9761
language Japanese
last_indexed 2024-04-11T05:01:15Z
publishDate 2022-12-01
publisher The Japan Society of Mechanical Engineers
record_format Article
series Nihon Kikai Gakkai ronbunshu
spelling doaj.art-ba9241590cb24efabc4b8f346519e7ca2022-12-26T01:09:00ZjpnThe Japan Society of Mechanical EngineersNihon Kikai Gakkai ronbunshu2187-97612022-12-018891622-0022722-0022710.1299/transjsme.22-00227transjsmeStudy on particulate matter emission amount estimation model for engine controlRyutaro KOIWAI0Kazuhiro ORYOJI1Shinya SATO2Akihiro KOMORI3Research and development group, Hitachi,LtdResearch and development group, Hitachi,LtdHitachi Astemo,LtdHitachi Astemo,LtdReal drive emissions (RDE) regulation were introduced from Euro6-d regulation. In order to achieve the regulation value of PM(Particulate Matter) emission in the RDE regulation, it is effective to install GPF(Gasoline Particulate Filter) system. To prevent GPF corruption , GPF system needs “PM emission amount estimation model” that estimates PM emission amount from direct injection gasoline engine to estimate PM corrected amount. Some models, for example packet model and map-based model, have been proposed as PM emission amount estimation model. However, these models have problems in terms of calculation load and accuracy for On-board calculation. Purpose of this research is to study On-board PM emission amount estimation model . We proposed a new model method of physical quantities that dominate PM production. Developed model uses probability density function of mixture fraction space so that mixture and fuel adhesion can be treated uniformly as a fuel distribution in cylinder. Also, variance of mixture-derived probability density function and fuel adhesion ratio are functionalized by a second-order polynomial of engine control parameters, and can be applied to multiple operating conditions. The developed model was verified by comparison with measurement data. Under 25 degC of coolant temperature(19 operation points), the estimated error was during 0% and 59% and average estimated error was 19%.https://www.jstage.jst.go.jp/article/transjsme/88/916/88_22-00227/_pdf/-char/eninternal combustion enginespark ignition engineengine controlparticulate mattercatalyzer
spellingShingle Ryutaro KOIWAI
Kazuhiro ORYOJI
Shinya SATO
Akihiro KOMORI
Study on particulate matter emission amount estimation model for engine control
Nihon Kikai Gakkai ronbunshu
internal combustion engine
spark ignition engine
engine control
particulate matter
catalyzer
title Study on particulate matter emission amount estimation model for engine control
title_full Study on particulate matter emission amount estimation model for engine control
title_fullStr Study on particulate matter emission amount estimation model for engine control
title_full_unstemmed Study on particulate matter emission amount estimation model for engine control
title_short Study on particulate matter emission amount estimation model for engine control
title_sort study on particulate matter emission amount estimation model for engine control
topic internal combustion engine
spark ignition engine
engine control
particulate matter
catalyzer
url https://www.jstage.jst.go.jp/article/transjsme/88/916/88_22-00227/_pdf/-char/en
work_keys_str_mv AT ryutarokoiwai studyonparticulatematteremissionamountestimationmodelforenginecontrol
AT kazuhirooryoji studyonparticulatematteremissionamountestimationmodelforenginecontrol
AT shinyasato studyonparticulatematteremissionamountestimationmodelforenginecontrol
AT akihirokomori studyonparticulatematteremissionamountestimationmodelforenginecontrol