内燃机工程2024，Vol.45Issue(6)：1-11,11.DOI:10.13949/j.cnki.nrjgc.2024.06.001
基于高斯过程回归的进气压力对船用柴油/甲醇组合燃烧发动机替代率拓宽研究
Research on Intake Pressures Broadening Methanol Substitution Rate Boundaries for Diesel/Methanol Compound Combustion Marine Engines Based on Gaussian Process Regression
摘要
Abstract
In order to make the marine diesel/methanol compound combustion(DMCC)engine meet increasingly stringent emission regulations and obtain higher economic benefits,the methanol substitution rates under different loads were widened by adjusting the intake pressure of the engine,thus realizing the simultaneous reduction of emissions and fuel consumption rates.Based on the Gaussian process regression model combined with experimental data and simulation models,the impact of intake pressures on the methanol substitution rate boundaries under different loads was analyzed.The MAP graph of the methanol substitution rate boundaries to further analyze the widening proportion was plotted.A prediction model for the engine brake specific fuel consumption(BSFC)and NOx emissions was established.The model was combined with non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)to optimize the BSFC and NOx emissions,and to obtain the optimal Pareto front solution set and select the optimal control parameter combinations.The optimal control parameter combinations were calibrated to the electronic control unit(ECU)for experimental validation.Results show that the maximum substitution rate of methanol is widened by 12.7%on average by adjusting the intake pressure,The BSFC is reduced by 5.6%on average,and the NOx emissions are reduced by 16.4%on average,compared to those under the diesel-only mode.关键词
船舶柴油机/柴油/甲醇组合燃烧/高斯过程回归/非支配排序基因算法-ⅡKey words
marine diesel engine/diesel/methanol compound combustion/Gaussian process regression/nondonminated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ)分类
能源科技引用本文复制引用
范金宇,才正,杨晨曦,李品芳,黄朝霞,黄加亮..基于高斯过程回归的进气压力对船用柴油/甲醇组合燃烧发动机替代率拓宽研究[J].内燃机工程,2024,45(6):1-11,11.基金项目
福建省自然科学基金项目(2022J01812,2021J01849) （2022J01812,2021J01849）
福建省教育厅科技项目(JAT210237)Fujian Province Natural Science Foundation Project(2022J01812,2021J01849) （JAT210237）
Fujian Province Department of Education Science and Technology Project(JAT210237) （JAT210237）
