Comparative study of the artificial neural network with three hyper-parameter optimization methods for the precise LP-EGR estimation using in-cylinder pressure in a turbocharged GDI engine-Reference-Cited by-同舟云学术

Comparative study of the artificial neural network with three hyper-parameter optimization methods for the precise LP-EGR estimation using in-cylinder pressure in a turbocharged GDI engine

Published:2019-02 Issue: Volume:149 Page:1324-1334
ISSN:1359-4311
Container-title:Applied Thermal Engineering
language:en
Short-container-title:Applied Thermal Engineering

Author:

Jo Yuhyeok,Min Kyunghan,Jung Donghyuk,Sunwoo Myoungho^ORCID,Han Manbae

Funder

BK21 plus program

Ministry of Education, Republic of Korea

Industrial Strategy Technology Development Program

International Collaborative Research and Development Program

Ministry of Trade, Industry and Energy

National Research Foundation of Korea

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Energy Engineering and Power Technology

Reference61 articles.

1. M. Wirth, U. Mayerhofer, W. Piock, G. Fraidl, Turbocharging the di gasoline engine, Tech. rep., SAE Technical Paper, 2000.

2. K. Kumano, S. Yamaoka, Analysis of knocking suppression effect of cooled egr in turbo-charged gasoline engine, Tech. rep., SAE Technical Paper, 2014.

3. Gasoline engine exhaust gas recirculation—a review;Wei;Appl. Energy,2012

4. Effects of egr, compression ratio and boost pressure on cyclic variation of pfi gasoline engine at wot operation;Pan;Appl. Therm. Eng.,2014

5. Y. Duchaussoy, A. Lefebvre, R. Bonetto, Dilution interest on turbocharged si engine combustion, Tech. rep., SAE Technical Paper, 2003.

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