摘要
利用一维发动机仿真软件GT-Power搭建了甲醇/柴油M15(即甲醇燃料所占体积比例为15%)混合燃料缸内直喷模型,选取转矩、比燃油消耗率、NOx排放量和CO排放量为优化目标,以发动机的进排气门正时角度、压缩比及空燃比为优化参数开展多目标优化。为实现多目标优化问题的有效求解,采用灰熵并行分析方法改进第二代非支配遗传算法(non-dominated sorting genetic algorithm-Ⅱ,NSGA-Ⅱ),并利用建立的响应面模型对仿真模型计算结果进行了仿真验证。优化结果显示:转矩提升了6.96%,比燃油消耗率降低了1.19%,NOx和CO排放量分别降低了12.37%和3.77%。
The 1D engine simulation software GT-Power was used to build a direct injection model of methanol/diesel M15(15%volume of methanol fuel)mixed fuel cylinder,and the torque,specific fuel consumption rate,NOx emissions and CO emissions were selected as the optimization targets,and the intake and exhaust valve timing angles,compression ratio and air-fuel ratio of the engine were used as the optimization parameters to carry out multi-objective optimization.In order to solve the multi-objective optimization problem effectively,the second-generation non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ)was improved by using the gray entropy parallel analysis method,and the simulation results were verified by using the established response surface model.The optimization results show that the torque is increased by 6.96%,the specific fuel consumption rate is reduced by 1.19%,and the NOx and CO emissions are reduced by 12.37%and 3.77%,respectively.
作者
赵柯洋
张衡
贺波
庞轶星
程星鑫
苏玉香
李又一
ZHAO Keyang;ZHANG Heng;HE Bo;PANG Yixing;CHENG Xingxin;SU Yuxiang;LI Youyi(School of Marine Engineering Equipment,Zhejiang Ocean University,Zhoushan 316022,China;Sinovat Ocean Technology Co.,Ltd.,Zhoushan 316022,China;Ningbo Institute of Materials Technology and Engineering,Chinese Academy of Sciences,Ningbo 315201,China)
出处
《内燃机工程》
北大核心
2025年第1期17-26,共10页
Chinese Internal Combustion Engine Engineering
基金
舟山市科技计划项目(2022C41009)。
关键词
甲醇/柴油
第二代非支配遗传算法
灰熵并行
性能优化
methanol/diesel
non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ)
grey entropy parallel
performance optimization
作者简介
赵柯洋(1988-),男,博士,讲师,研究方向为船舶动力系统,E-mail:zhaoky@zjou.edu.cn。
