摘要
为了降低生物柴油在低速时NOx排放的同时不引起其他性能的恶化,我们以4JB1型柴油机为对象建立一维仿真模#型,将可变截面涡轮增压器和米勒循环相结合,对体积比为30%的地沟油生物柴油0柴油混合燃料在低转速下的排放进行优化并提出控制策略。结果表明:100%负荷下利用遗传算法对NOx、Soot排放和BSFC分别进行单目标优化后分别降低了28.34%、84.89%和1.15%。通过双目标优化的Pareto解集发现,BSFC和NOx比排放更容易同时实现优化。最后经过多目标优化,在100%和50%负荷时,米勒度分别为M98和M85,VGT阀门开度分别为0.25和0.16时目标函数达到最小,NOx分别比优化前降低了23.17%和8.2%,虽然Soot排放有所上升,但与燃用纯柴油的Soot排放相当。
In order to reduce biodiesel's NOx emission not causing the deterioration of other performance in low speed, 4 JB1 diesel engine was used as research object in this paper, VGT and Miller cycle were combined to discharge the emission of the 0# diesel mixed with the volume ratio of 30% of the gutter oil at low speed. The control strategy is optimized and proposed. the single objective optimization of NOx, Soot emission and BSFC under 100% load is reduced by 28.34%, 84.89% and 1.15% respectively. It is found that BSFC and NOx are easier to achieve simultaneous optimization than emissions by Pareto decomposition of two-objective optimization. At the end of the multi-objective optimization, the Miller degree is M98 and M85 at 100% and 50%, the target function of the VGT valve opening is 0.25 and 0.16 respectively, and the NOx is reduced by 23.17% and 8.2% before the optimization, although the Soot emission increases, but it is equivalent to the Soot discharge from the pure diesel.
引文
[1]Stavinoha L L,Alfaro E S,Dobbs H H,et al.Alternative Fuels:Development of a Biodiesel B20 Purchase Description[J].2000.
[2]Cui Y,Deng K.Thermodynamic model and optimization of a miller cycle applied on a turbocharged diesel engine[J].Journal of Thermal Science&Technology,2014.
[3]楼狄明,郭石磊,谭丕强,等.可变截面涡轮增压器与废气再循环[J].同济大学学报:自然科学版,2015,44(12):1931-1937.
[4]GT-Power User′s Manual and Tutorial.Gala Technologies,March 2003.
[5]郭天文.基于DOE的柴油机喷油规律和EGR耦合优化研究[D].四川:西南交通大学,2016.
[6]刘德辉,石柏军,章雪华.基于GT-Power的柴油机进排气系统多目标优化[J].重庆理工大学学报,2016,30(7):30-37.
[7]蔡俊俊.Miller循环煤层气发动机的仿真优化研究[D].四川:西南交通大学,2017.
[8]王重,刘黎明.拟合优度检验统计量的设定方法[J].统计与决策,2010,(5):154-156.
[9]Gujarati Damodar,费剑平,孙春霞,等.计量经济学基础[M].中国人民大学出版社,2005.
[10]潘峰.粒子群优化算法与多目标优化[M].北京:北京理工大学出版社,2013.