Review of artificial neural networks for gasoline, diesel and homogeneous charge compression ignition engine

被引：49

作者：

Veza, Ibham ^{[1
]}

Afzal, Asif ^{[2
,3
]}

Mujtaba, M. A. ^{[4
]}

Hoang, Anh Tuan ^{[5
]}

Balasubramanian, Dhinesh ^{[6
,7
,8
]}

Sekar, Manigandan ^{[9
]}

Fattah, I. M. R. ^{[10
]}

Soudagar, M. E. M. ^{[11
]}

EL-Seesy, Ahmed, I ^{[12
,13
]}

Djamari, D. W. ^{[14
]}

Hananto, A. L. ^{[15
]}

Putra, N. R. ^{[16
]}

Tamaldin, Noreffendy ^{[1
]}

机构：

[1] Univ Teknikal Malaysia Melaka, Fac Mech Engn, Durian Tunggal 76100, Melaka, Malaysia

[2] PA Coll Engn, Dept Mech Engn, Mangaluru 574153, India

[3] Visvesvaraya Technol Univ, Belagavi, India

[4] Univ Engn & Technol, Dept Mech Engn, New Campus Lahore, Lahore, Pakistan

[5] HUTECH Univ, Inst Engn, Ho Chi Minh City, Vietnam

[6] Mepco Schlenk Engn Coll, Dept Mech Engn, Sivakasi, India

[7] Khon Kaen Univ, Fac Engn, Mech Engn, Khon Kaen, Thailand

[8] Khon Kaen Univ, Ctr Alternat Energy Res & Dev, Khon Kaen, Thailand

[9] Sathyabama Inst Sci & Technol, Dept Aeronaut Engn, Chennai, Tamil Nadu, India

[10] Univ Technol Sydney, Fac Engn & IT, Ctr Green Technol, Sydney, NSW 2007, Australia

[11] Glocal Univ, Sch Technol, Dept Mech Engn, Delhi Yamunotri Marg SH-57, Mirzapur Pole 247121, Uttar Pradesh, India

[12] Banha Univ, Benha Fac Engn, Mech Engn Dept, Banha 13512, Egypt

[13] Jiangsu Univ, Inst Energy Res, 301 Xuefu Rd, Zhenjiang 212013, Jiangsu, Peoples R China

[14] Sampoerna Univ, Mech Engn Study Program, Jakarta, Indonesia

[15] Univ Buana Perjuangan Karawang Teluk Jambe, Fac Engn & Comp Sci, Karawang 41361, Indonesia

[16] UTM, Ibnu Sina Inst Sci & Ind Res, Ctr Lipid Engn & Appl Res CLEAR, Johor Baharu 81310, Malaysia

来源：

ALEXANDRIA ENGINEERING JOURNAL | 2022年 / 61卷 / 11期

关键词：

Artificial neural network; SURFACE METHODOLOGY RSM; ANN BASED PREDICTION; EXHAUST EMISSIONS; HCCI ENGINE; OPERATING PARAMETERS; PERFORMANCE; COMBUSTION; BIODIESEL; OPTIMIZATION; MODEL;

D O I：

10.1016/j.aej.2022.01.0721110-0168

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

In automotive applications, artificial neural network (ANN) is now considered as a favorable prediction tool. Since it does not need an understanding of the system or its underlying physics, an ANN model can be beneficial especially when the system is too complicated, and it is too costly to model it using a simulation program. Therefore, using ANN to model an internal combustion engine has been a growing research area in the last decade. Despite its promising capabilities, the use of ANN for engine applications needs deeper examination and further improvement.

引用

页码：8363 / 8391

页数：29

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