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基于燃料特性的汽油机颗粒物排放预测关系式
引用本文:吴涛阳,姚安仁,王辉,李壮壮,姚春德,闫俊杰.基于燃料特性的汽油机颗粒物排放预测关系式[J].环境科学学报,2020,40(1):102-110.
作者姓名:吴涛阳  姚安仁  王辉  李壮壮  姚春德  闫俊杰
作者单位:天津大学内燃机燃烧学国家重点实验室,天津300072,天津大学内燃机燃烧学国家重点实验室,天津300072,天津大学内燃机燃烧学国家重点实验室,天津300072,天津大学内燃机燃烧学国家重点实验室,天津300072,天津大学内燃机燃烧学国家重点实验室,天津300072,丰田汽车研发中心(中国)有限公司北京分公司,北京100020
基金项目:国家自然科学基金重点项目(No.51336005)
摘    要:汽油机的颗粒物排放与所用燃料的性能密切相关.为评价燃料特性对汽油机颗粒物排放的影响,建立了一个简化PN指数(SPNI)关系式并进行了统计学检验.该指数包含T70(70%蒸馏温度)、重芳烃(碳数≥9)含量、终馏点温度和烯烃含量4个关键的燃料参数.在试验和分析过程中配制了代表不同地区市场油的20种模型燃料,并对其燃料参数进行了相关性分析和多元线性回归.发动机试验结果表明,各种典型运行模式下的发动机实际颗粒物数量(PN)排放均与SPNI呈现高度的相关性.与已有的详细PM指数相比,该模型计算更为简便,可操作性强.该简化PN指数可用于工程上评价不同汽油燃料的颗粒物排放潜势.

关 键 词:汽油机  颗粒物排放  评价  燃料特性  简化PN指数
收稿时间:2019/6/16 0:00:00
修稿时间:2019/7/10 0:00:00

Predicting formula of particulate matter emission from gasoline engines based on fuel properties
WU Taoyang,YAO Anren,WANG Hui,LI Zhuangzhuang,YAO Chunde and YAN Junjie.Predicting formula of particulate matter emission from gasoline engines based on fuel properties[J].Acta Scientiae Circumstantiae,2020,40(1):102-110.
Authors:WU Taoyang  YAO Anren  WANG Hui  LI Zhuangzhuang  YAO Chunde and YAN Junjie
Institution:State Key Laboratory of Engines, Tianjin University, Tianjin 300072,State Key Laboratory of Engines, Tianjin University, Tianjin 300072,State Key Laboratory of Engines, Tianjin University, Tianjin 300072,State Key Laboratory of Engines, Tianjin University, Tianjin 300072,State Key Laboratory of Engines, Tianjin University, Tianjin 300072 and Toyota Motor Engineering & Manufacturing(China) Co. Beijing Branch, Beijing 100020
Abstract:Particulate matter emissions (PM) from gasoline engines are closely related to the fuel used. In order to evaluate the impact of fuel properties on PM emission tendencies from gasoline engines, a simplified PN index (SPNI) formula was developed. The index covers four key fuel parameters of fuel, namely T70 (70% distillation temperature), heavy aromatics content, final boiling point temperature and olefins content. Twenty typical fuels representing market gasoline from different regions were formulated during the process of testing and analysis. Meanwhile, the correlation analysis and multivariate linear regression were performed on the parameters of these fuels. The results of the engine tests show that the actual PN emissions from the engine are highly correlated with the test fuel''s SPNI in various typical operating modes. Compared with the existing detailed PM index (PMI), the SPNI is simpler to calculate and more operable. The SPNI can be used to evaluate the particulate matter emission potentials of different gasoline fuels in engineering.
Keywords:gasoline engines  particulate matter emission  evaluation  fuel properties  simplified PN index
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