杜倩颖,倪计民,陈沁青,袁益禧.HILOMOT模型在柴油机超大样本试验中的应用研究[J].内燃机工程,2017,38(4):128-233.
HILOMOT模型在柴油机超大样本试验中的应用研究
Application and Research of HILOMOT in Diesel Engines Extremely Large Sample Test
DOI：
关键词:内燃机  发动机优化  动态试验  数学建模  HILOMOT模型  DMT模型  试验设计
Key Words:IC engine  engine optimization  dynamic test  mathematical modeling  HILOMOT model  dynamic modeling toolbox model  design of experiment(DoE)
基金项目:
作者单位
杜倩颖,倪计民,陈沁青,袁益禧 1.同济大学 汽车学院,上海 201804；2.IAV GmbH公司,德国 柏林 10587 
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摘要:基于某款柴油机动态试验,以经典DMT模型为参照,研究HILOMOT模型超大样本数据拟合能力。研究结果表明：超大样本量时（75006样本点）,针对柴油机排放指标（NOx、CO、THC及碳烟排放）,HILOMOT建模误差平均降低了27.7%（最大降幅为45.6%）,数学建模质量显著优于DMT模型。因此，在样本点数较多的发动机研究领域,HILOMOT模型具备一定的应用优势。
Abstract:Based on the dynamic test of a certain diesel engine, the fitting ability of a HILOMOT model to the extremely large sample data was studied (compared to the classical DMT model). Results show that in dealing with an extremely large sample size (75006 working points) such as diesel emissions targets (NOx, CO, THC and soot emissions), the HILOMOT′s error is reduced by an average of 27.7% (the maximum drop is 45.6% ), and the quality of its mathematical modeling is significantly better than that of the classical DMT model. Therefore, the HILOMOT model has some advantages in the field of engine research and development design with a large number of samples.
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