Reducing emissions by optimising the fuel injector match with the combustion chamber geometry for a marine medium-speed diesel engine

Nao Hu, Peilin Zhou, Jianguo Yang

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

The effects of seven matching parameters of a fuel injector and combustion chamber geometries on nitrogen oxide (NOx), soot and specific fuel oil consumption (SFOC) were investigated by means of a parametric study. The study was carried out on four different engine loads, i.e. L25 (25%), L50 (50%), L75 (75%) and L100 (100%) loads. The injection-related parameters were found to have more prominent influences as opposed to the combustion chamber geometries. Then, a multi-objective genetic algorithm (MOGA) method was proposed in order to identify a set of optimal designs for the L100 load. The emissions and performance of these optimal designs were also examined and compared on the other three engine loads. Finally, an optimal design which meets the IMO (International Maritime Organization) Tier II NOx emissions regulations (research shows it is impossible to meet Tier III NOx emissions regulations solely on the basis of the optimisation of the combustion progress) and which has the best fuel economy was singled out.
LanguageEnglish
Pages1-16
Number of pages16
JournalTransportation Research. Part D, Transport and Environment
Volume53
Early online date6 Apr 2017
DOIs
Publication statusPublished - 30 Jun 2017

Fingerprint

Nitrogen oxides
diesel engine
Combustion chambers
nitrogen oxides
chamber
Diesel engines
combustion
mathematics
geometry
Geometry
engine
Engines
regulation
Fuel oils
soot
Fuel economy
Soot
genetic algorithm
Genetic algorithms
organization

Keywords

  • injector
  • combustion chamber
  • diesel engine
  • emission
  • fuel consumption

Cite this

@article{e468d665485143fbbf6e4ec95011eb2a,
title = "Reducing emissions by optimising the fuel injector match with the combustion chamber geometry for a marine medium-speed diesel engine",
abstract = "The effects of seven matching parameters of a fuel injector and combustion chamber geometries on nitrogen oxide (NOx), soot and specific fuel oil consumption (SFOC) were investigated by means of a parametric study. The study was carried out on four different engine loads, i.e. L25 (25{\%}), L50 (50{\%}), L75 (75{\%}) and L100 (100{\%}) loads. The injection-related parameters were found to have more prominent influences as opposed to the combustion chamber geometries. Then, a multi-objective genetic algorithm (MOGA) method was proposed in order to identify a set of optimal designs for the L100 load. The emissions and performance of these optimal designs were also examined and compared on the other three engine loads. Finally, an optimal design which meets the IMO (International Maritime Organization) Tier II NOx emissions regulations (research shows it is impossible to meet Tier III NOx emissions regulations solely on the basis of the optimisation of the combustion progress) and which has the best fuel economy was singled out.",
keywords = "injector, combustion chamber, diesel engine, emission, fuel consumption",
author = "Nao Hu and Peilin Zhou and Jianguo Yang",
year = "2017",
month = "6",
day = "30",
doi = "10.1016/j.trd.2017.03.024",
language = "English",
volume = "53",
pages = "1--16",
journal = "Transportation Research. Part D, Transport and Environment",
issn = "1361-9209",

}

TY - JOUR

T1 - Reducing emissions by optimising the fuel injector match with the combustion chamber geometry for a marine medium-speed diesel engine

AU - Hu, Nao

AU - Zhou, Peilin

AU - Yang, Jianguo

PY - 2017/6/30

Y1 - 2017/6/30

N2 - The effects of seven matching parameters of a fuel injector and combustion chamber geometries on nitrogen oxide (NOx), soot and specific fuel oil consumption (SFOC) were investigated by means of a parametric study. The study was carried out on four different engine loads, i.e. L25 (25%), L50 (50%), L75 (75%) and L100 (100%) loads. The injection-related parameters were found to have more prominent influences as opposed to the combustion chamber geometries. Then, a multi-objective genetic algorithm (MOGA) method was proposed in order to identify a set of optimal designs for the L100 load. The emissions and performance of these optimal designs were also examined and compared on the other three engine loads. Finally, an optimal design which meets the IMO (International Maritime Organization) Tier II NOx emissions regulations (research shows it is impossible to meet Tier III NOx emissions regulations solely on the basis of the optimisation of the combustion progress) and which has the best fuel economy was singled out.

AB - The effects of seven matching parameters of a fuel injector and combustion chamber geometries on nitrogen oxide (NOx), soot and specific fuel oil consumption (SFOC) were investigated by means of a parametric study. The study was carried out on four different engine loads, i.e. L25 (25%), L50 (50%), L75 (75%) and L100 (100%) loads. The injection-related parameters were found to have more prominent influences as opposed to the combustion chamber geometries. Then, a multi-objective genetic algorithm (MOGA) method was proposed in order to identify a set of optimal designs for the L100 load. The emissions and performance of these optimal designs were also examined and compared on the other three engine loads. Finally, an optimal design which meets the IMO (International Maritime Organization) Tier II NOx emissions regulations (research shows it is impossible to meet Tier III NOx emissions regulations solely on the basis of the optimisation of the combustion progress) and which has the best fuel economy was singled out.

KW - injector

KW - combustion chamber

KW - diesel engine

KW - emission

KW - fuel consumption

UR - http://www.sciencedirect.com/science/journal/13619209

U2 - 10.1016/j.trd.2017.03.024

DO - 10.1016/j.trd.2017.03.024

M3 - Article

VL - 53

SP - 1

EP - 16

JO - Transportation Research. Part D, Transport and Environment

T2 - Transportation Research. Part D, Transport and Environment

JF - Transportation Research. Part D, Transport and Environment

SN - 1361-9209

ER -