双燃料发动机温室气体排放预测和影响因素分析  

Prediction and Influencing Factors Analysis of Greenhouse Gas Emission for Dual Fuel Engine

作　　者：陈晖[1] 官维 黄豪中[3] CHEN Hui;GUAN Wei;HUANG Haozhong(School of Automotive Engineering,Liuzhou Vocational&Technical College,Liuzhou 545005,China;Guangxi Yuchai Machinery Co.,Ltd.,Yulin 537005,China;College of Mechanical Engineering,Guangxi University,Nanning 530004,China)

机构地区：[1]柳州职业技术学院汽车工程学院,广西柳州545005 [2]广西玉柴机器股份有限公司,广西玉林537005 [3]广西大学机械工程学院,广西南宁530004

出　　处：《车用发动机》2023年第4期86-92,共7页Vehicle Engine

基　　金：广西自然科学基金项目(2023GXNSFAA026436);广西重点研发计划项目(桂科AB21220055);广西高校中青年教师基础能力提升项目(2021KY1043)。

摘　　要：基于柴油-天然气双燃料发动机测试台架中等转速(1500 r/min)下400,800,1200,1600 N·m 4个扭矩工况的试验数据,以发动机扭矩、喷油正时、喷油压力和天然气替代率为模型输入参数,以温室气体CO_(2)和CH_(4)排放值为模型输出参数,构建了基于粒子群算法优化的BP神经网络的温室气体排放预测模型。模型的预测结果显示:在测试集上CO_(2)和CH_(4)排放预测值的决定系数(R 2)分别为0.99762和0.99809,平均绝对百分比误差(MAPE)分别为0.97%和3.85%,模型具有良好的泛化能力和预测精度。基于构建的排放预测模型,采用平均影响值(MIV)算法分析了发动机在中等转速工况下扭矩、喷油正时、喷油压力和天然气替代率对CO_(2)和CH_(4)排放的影响,结果显示发动机扭矩对CO_(2)和CH_(4)排放的影响占主导地位,贡献率分别达到了71.8%和50.8%;当模型中发动机扭矩设定在小负荷工况,天然气替代率对CO_(2)和CH_(4)排放的影响权重最大。A greenhouse gas emission prediction model of BP neural network optimized by particle swarm algorithm was established with engine torque,injection timing,injection pressure and natural gas substitute rate as the input parameters and CO_(2)and CH_(4)greenhouse gas emissions as the output parameters based on the test data achieved under the conditions of 400,800,1200 and 1600 N·m at 1500 r/min on diesel/natural gas dual fuel engine test bench.The prediction results of the model show that the coefficients of determination(R^(2))of CO_(2)and CH_(4)predictions on the test set are 0.99762 and 0.99809,the mean absolute percentage errors(MAPE)are 0.97%and 3.85%,and the model has good generalization ability and prediction accuracy.With the model,the mean influence value(MIV)algorithm is used to quantitatively analyze the influence of torque,injection timing,injection pressure and natural gas substitute rate on CO_(2)and CH_(4)emissions at 1500 r/min.The results show that engine torque has a dominant effect on CO_(2)and CH_(4)emissions with a contribution of 71.8%and 50.8%respectively.When engine torque is set at low load condition in the model,the natural gas substitute rate occupies the greatest weight in all influences of CO_(2)and CH_(4)emissions.

关 键 词：双燃料发动机 温室气体 排放 预测 神经网络 粒子群算法 

分 类 号：TK421[动力工程及工程热物理—动力机械及工程]