Skip to main navigation Skip to search Skip to main content

Emission and Performance Optimization of Marine Four-Stroke Dual-Fuel Engine Based on Response Surface Methodology

  • Huaiyu Wang
  • , Huibing Gan*
  • , Guanjie Wang
  • , Guoqiang Zhong
  • *Corresponding author for this work
  • Dalian Maritime University

Research output: Contribution to journalArticlepeer-review

Abstract

As the emissions regulations have become more stringent, reducing NOX emissions is of great importance to the shipping industry. Due to the price and emissions advantages of natural gas, the diesel-natural gas engines have become an attractive solution for engine manufacturers. Firstly, in this paper, the NOX emissions prediction model of a large marine four-stroke dual-fuel engine is built by using AVL-BOOST. In addition, the model is further calibrated to calculate the performance and emissions of the engine. Then, the influences of boost pressure, compression ratio, and the timing of intake valve closing on engine performance and emissions are analyzed. Finally, the response surface methodology is used to optimize the emissions and performance to obtain the optimal setting parameters of the engine. The results indicate that the response surface method is a highly desirable optimization method, which can save a lot of repeated research. Compared with the results from manufactured data, the power is increased by 0.55% and the BSFC, the NOX emissions, and the peak combustion pressure are decreased by 0.60%, 13.21%, and 1.51%, respectively, at low load.

Original languageEnglish
Article number5268314
JournalMathematical Problems in Engineering
Volume2020
DOIs
Publication statusPublished - 2020
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 14 - Life Below Water
    SDG 14 Life Below Water

Fingerprint

Dive into the research topics of 'Emission and Performance Optimization of Marine Four-Stroke Dual-Fuel Engine Based on Response Surface Methodology'. Together they form a unique fingerprint.

Cite this