Application and Research of HILOMOT in Diesel Engines Extremely Large Sample Test

杜倩颖

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Application and Research of HILOMOT in Diesel Engines Extremely Large Sample Test

更新时间：2026-04-16

- Application and Research of HILOMOT in Diesel Engines Extremely Large Sample Test
- Vol. 38, Issue 4, Pages: 128-233(2017)
- 作者机构：
  
  1. 同济大学汽车学院,上海,201804
  2. IAV GmbH公司,柏林,德国,10587
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2017
- 稿件说明：
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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.

杜倩颖. Application and Research of HILOMOT in Diesel Engines Extremely Large Sample Test[J]. 2017, 38(4): 128-233.
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. DOI：

杜倩颖. Application and Research of HILOMOT in Diesel Engines Extremely Large Sample Test[J]. 2017, 38(4): 128-233. DOI：

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

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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