摘要
基于新欧洲行驶工况(NEDC)进行某款柴油机快速标定试验,以经典多项式模型为参照研究HILOMOT模型较大样本数据的拟合能力.结果表明:较大样本时(NEDC试验共有1009个样本点),针对柴油机经济性指标(燃油消耗率)及排放指标(NO_x、soot、CO及THC排放),HILOMOT建模误差平均降低了51.9%,(最大降幅为73.0%,),数学建模质量显著优于经典多项式模型.HILOMOT模型在样本点数较多的发动机研究领域具备一定的应用优势.
Based on NEDC calibration diesel engine tests, a scientific research was done in order to find the fitting ability of the HILOMOT model to large sample compared with the polynomial model. The research result shows that for the large sample size (full factorial design, 1 009 working points), HILOMOT's RMSE reduces the fuel con- sumption and exhaust emissions of NOx, soot, CO and THC by an average of 51.9% (the maximum drop is 73.0% ). HILOMOT has a much better data fitting ability than the polynomial model, and is more suitable to large samples and complicated modeling cases in engine calibration.
作者
杜倩颖
倪计民
陈沁青
袁益禧
Du Qianying;Ni Jimin;Chen Qinqing;Yuan Yixi(School of Automotive Studies, Tongji University, Shanghai 201804, China;IAVAutomotive Engineering Company Limitied, Berlin 10587, Germany)
出处
《内燃机学报》
EI
CAS
CSCD
北大核心
2018年第4期347-352,共6页
Transactions of Csice
关键词
柴油机
标定
HILOMOT模型
NEDC
diesel engine
calibration
hierarchical local model tree model
new European driving cycle