摘要
为使柴油/甲醇组合燃烧(diesel/methanol compound combustion,DMCC)船用发动机满足日益严苛的排放法规,同时获得更高的经济效益,通过调节发动机进气压力,拓宽不同负荷下甲醇替代率,进而实现排放和燃油消耗率的同步下降。利用高斯过程回归模型,结合试验数据和仿真模型,分析了在不同负荷下进气压力对甲醇替代率边界的影响。并绘制了甲醇替代率边界MAP图,进一步分析了拓宽比例。随后建立了发动机有效燃油消耗率和NO_(x)排放的预测模型。将所建模型与非支配排序基因算法-Ⅱ(nondominated sorting genetic algorithm-Ⅱ,NSGA-Ⅱ)相结合,对有效燃油消耗率(brake specific fuel consumption,BSFC)和NO_(x)排放进行优化,获得最优Pareto前沿解集并选取最佳控制参数组合。最后将最优控制参数组合标定至电子控制单元(electronic control unit,ECU)中进行试验验证。结果表明:调节进气压力可使甲醇最大替代率平均拓宽12.7%。相较纯柴油模式,优化后BSFC平均下降5.6%,NO_(x)排放平均下降16.4%。
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 NO_(x) emissions was established.The model was combined with non-dominated sorting genetic algorithmⅡ(NSGA-Ⅱ)to optimize the BSFC and NO_(x) 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 NO_(x) emissions are reduced by 16.4%on average,compared to those under the diesel-only mode.
作者
范金宇
才正
杨晨曦
李品芳
黄朝霞
黄加亮
FAN Jinyu;CAI Zheng;YANG Chenxi;LI Pinfang;HUANG Zhaoxia;HUANG Jialiang(Marine Engineering College,Jimei University,Xiamen 361021,China;Fujian Provincial Key Laboratory of Shipbuilding and Marine Engineering,Xiamen 361021,China;College of Science,Jimei University,Xiamen 361021,China)
出处
《内燃机工程》
CAS
CSCD
北大核心
2024年第6期1-11,共11页
Chinese Internal Combustion Engine Engineering
基金
福建省自然科学基金项目(2022J01812,2021J01849)
福建省教育厅科技项目(JAT210237)。
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-Ⅱ
marine diesel engine
diesel/methanol compound combustion
Gaussian process regression
nondonminated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ)