...
首页> 外文期刊>Fuel >Multi-objective optimization of the performance-emission trade-off characteristics of a CRDI coupled CNG diesel dual-fuel operation: A GEP meta-model assisted MOGA endeavour
【24h】

Multi-objective optimization of the performance-emission trade-off characteristics of a CRDI coupled CNG diesel dual-fuel operation: A GEP meta-model assisted MOGA endeavour

机译:CRDI耦合CNG柴油双燃料运行的性能-排放权衡特性的多目标优化:GEP元模型辅助的MOGA努力

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

A meta-model based multi-objective optimization endeavor was undertaken in the present work to investigate the potential of the off-line model based calibration technique to extend the actual CRDI-CNG dual-fuel experimental investigations in determining the possibility of unearthing viable potential trade-off domains hitherto unexplored by the constraints of resources, cost and time warranted by an experimental investigation. For the ensuing optimization study, CNG energy share, fuel injection pressure and load have been used as the decision variables while PM, NHC and BSFC were chosen as the output variables to be optimized. In absence of a closed form correlation between the participating variables under study, the explicit characterization capability of the Gene Expression Programming technique was harnessed. The appropriate GEP based meta-models were adopted from a previous study correlating the identical system output responses for the same set of decision variables of interest in the present study. Genetic algorithm was chosen as the optimization routine in the present study in view of its promising potential of extremely fast convergent speed, diversity of optimal solutions and simplicity of operation. Experimental validation of the obtained solutions pertaining to the desired objectives were carried out by actual experimentation. The present optimization endeavor was able to better the best vantage in category of the desired objective of minimum fuel consumption and exhaust emissions, obtained not only as compared to baseline diesel operation comprehensively but also was superior than the actual CRDI-CNG strategy during actual dual-fuel operation corresponding to actual experimentation.
机译:在本工作中,进行了基于元模型的多目标优化工作,以研究基于离线模型的校准技术的潜力,以扩展实际的CRDI-CNG双燃料实验研究,以确定发掘可行的潜在贸易的可能性迄今为止,尚未通过实验研究保证的资源,成本和时间的限制无法探索这些领域。在随后的优化研究中,压缩天然气的能量份额,燃油喷射压力和负荷已用作决策变量,而PM,NHC和BSFC被选作要优化的输出变量。在所研究的参与变量之间没有封闭形式的相关性的情况下,利用了基因表达编程技术的显式表征功能。从先前的研究中采用了适当的基于GEP的元模型,该模型将本研究中相同的目标决策变量集的相同系统输出响应相关联。由于遗传算法具有极快的收敛速度,最优解的多样性和操作简单的潜力,因此在本研究中选择遗传算法作为优化例程。通过实际实验对获得的与所需目标有关的解决方案进行实验验证。当前的优化工作能够更好地实现最低燃料消耗和废气排放的预期目标类别中的最佳优势,这不仅与全面的基准柴油运行相比,而且在实际的双柴油机运行中也优于实际的CRDI-CNG策略。燃料操作与实际实验相对应。

著录项

相似文献

  • 外文文献
  • 中文文献
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号