Multiobjective Optimization of the Performance and Emissions of a Large Low-Speed Dual-Fuel Marine Engine Based on MNLR-MOPSO

With increasingly strict emission regulations and growing environmental concerns, it is urgent to improve engine performance and reduce emissions. In this paper, multivariate nonlinear regression (MNLR) combined with multiobjective particle swarm optimization (MOPSO) was implemented to optimize the...

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Autores principales:	Yujin Cong, Huibing Gan, Huaiyu Wang, Guotong Hu, Yi Liu
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	dual-fuel engine performance and emission optimization multiobjective particle swarm optimization multivariate nonlinear regression Naval architecture. Shipbuilding. Marine engineering VM1-989 Oceanography GC1-1581
Acceso en línea:	https://doaj.org/article/cc2c2d71720246ee8347a32ea96b9393
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id	oai:doaj.org-article:cc2c2d71720246ee8347a32ea96b9393
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spelling	oai:doaj.org-article:cc2c2d71720246ee8347a32ea96b93932021-11-25T18:03:53ZMultiobjective Optimization of the Performance and Emissions of a Large Low-Speed Dual-Fuel Marine Engine Based on MNLR-MOPSO10.3390/jmse91111702077-1312https://doaj.org/article/cc2c2d71720246ee8347a32ea96b93932021-10-01T00:00:00Zhttps://www.mdpi.com/2077-1312/9/11/1170https://doaj.org/toc/2077-1312With increasingly strict emission regulations and growing environmental concerns, it is urgent to improve engine performance and reduce emissions. In this paper, multivariate nonlinear regression (MNLR) combined with multiobjective particle swarm optimization (MOPSO) was implemented to optimize the performance and emissions of a large low-speed two-stroke dual-fuel marine engine. First, a simulation model of a dual-fuel engine was established using AVL-BOOST software. Next, a single-factor scanning value method was applied to control a range of variables, including intake pressure, intake temperature, and natural gas mass fraction. Then, a nonlinear regression model was established using the statistical multivariate nonlinear regression equation. Finally, the multiobjective optimization algorithm implementing MOPSO was used to solve the trade-off between performance and emissions. It was found that when the intake pressure was 3.607 bar, the intake temperature was 297.15 K and the natural gas mass fraction was 0.962. The engine power increased by 0.34%, the brake specific fuel consumption (BSFC) reduced by 0.21%, and the NOx emissions reduced by 39.56%. The results show that the combination of multiple nonlinear regression and intelligent optimization algorithm is an effective method to optimize engine parameter settings.Yujin CongHuibing GanHuaiyu WangGuotong HuYi LiuMDPI AGarticledual-fuel engineperformance and emission optimizationmultiobjective particle swarm optimizationmultivariate nonlinear regressionNaval architecture. Shipbuilding. Marine engineeringVM1-989OceanographyGC1-1581ENJournal of Marine Science and Engineering, Vol 9, Iss 1170, p 1170 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	dual-fuel engine performance and emission optimization multiobjective particle swarm optimization multivariate nonlinear regression Naval architecture. Shipbuilding. Marine engineering VM1-989 Oceanography GC1-1581
spellingShingle	dual-fuel engine performance and emission optimization multiobjective particle swarm optimization multivariate nonlinear regression Naval architecture. Shipbuilding. Marine engineering VM1-989 Oceanography GC1-1581 Yujin Cong Huibing Gan Huaiyu Wang Guotong Hu Yi Liu Multiobjective Optimization of the Performance and Emissions of a Large Low-Speed Dual-Fuel Marine Engine Based on MNLR-MOPSO
description	With increasingly strict emission regulations and growing environmental concerns, it is urgent to improve engine performance and reduce emissions. In this paper, multivariate nonlinear regression (MNLR) combined with multiobjective particle swarm optimization (MOPSO) was implemented to optimize the performance and emissions of a large low-speed two-stroke dual-fuel marine engine. First, a simulation model of a dual-fuel engine was established using AVL-BOOST software. Next, a single-factor scanning value method was applied to control a range of variables, including intake pressure, intake temperature, and natural gas mass fraction. Then, a nonlinear regression model was established using the statistical multivariate nonlinear regression equation. Finally, the multiobjective optimization algorithm implementing MOPSO was used to solve the trade-off between performance and emissions. It was found that when the intake pressure was 3.607 bar, the intake temperature was 297.15 K and the natural gas mass fraction was 0.962. The engine power increased by 0.34%, the brake specific fuel consumption (BSFC) reduced by 0.21%, and the NOx emissions reduced by 39.56%. The results show that the combination of multiple nonlinear regression and intelligent optimization algorithm is an effective method to optimize engine parameter settings.
format	article
author	Yujin Cong Huibing Gan Huaiyu Wang Guotong Hu Yi Liu
author_facet	Yujin Cong Huibing Gan Huaiyu Wang Guotong Hu Yi Liu
author_sort	Yujin Cong
title	Multiobjective Optimization of the Performance and Emissions of a Large Low-Speed Dual-Fuel Marine Engine Based on MNLR-MOPSO
title_short	Multiobjective Optimization of the Performance and Emissions of a Large Low-Speed Dual-Fuel Marine Engine Based on MNLR-MOPSO
title_full	Multiobjective Optimization of the Performance and Emissions of a Large Low-Speed Dual-Fuel Marine Engine Based on MNLR-MOPSO
title_fullStr	Multiobjective Optimization of the Performance and Emissions of a Large Low-Speed Dual-Fuel Marine Engine Based on MNLR-MOPSO
title_full_unstemmed	Multiobjective Optimization of the Performance and Emissions of a Large Low-Speed Dual-Fuel Marine Engine Based on MNLR-MOPSO
title_sort	multiobjective optimization of the performance and emissions of a large low-speed dual-fuel marine engine based on mnlr-mopso
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/cc2c2d71720246ee8347a32ea96b9393
work_keys_str_mv	AT yujincong multiobjectiveoptimizationoftheperformanceandemissionsofalargelowspeeddualfuelmarineenginebasedonmnlrmopso AT huibinggan multiobjectiveoptimizationoftheperformanceandemissionsofalargelowspeeddualfuelmarineenginebasedonmnlrmopso AT huaiyuwang multiobjectiveoptimizationoftheperformanceandemissionsofalargelowspeeddualfuelmarineenginebasedonmnlrmopso AT guotonghu multiobjectiveoptimizationoftheperformanceandemissionsofalargelowspeeddualfuelmarineenginebasedonmnlrmopso AT yiliu multiobjectiveoptimizationoftheperformanceandemissionsofalargelowspeeddualfuelmarineenginebasedonmnlrmopso
_version_	1718411707402944512

Multiobjective Optimization of the Performance and Emissions of a Large Low-Speed Dual-Fuel Marine Engine Based on MNLR-MOPSO

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