Heat transfer coefficient estimation of an internal combustion engine using particle filters

被引:9
|
作者
Hamilton, Fabiana C. [1 ]
Colaco, Marcelo J. [1 ]
Carvalho, Rogerio N. [1 ,2 ]
Leiroz, Albino J. K. [1 ]
机构
[1] Univ Fed Rio de Janeiro, Dept Mech Engn, Rio De Janeiro, Brazil
[2] CENPES, PETROBRAS Res & Dev Ctr, Rio De Janeiro, Brazil
关键词
internal combustion engines; particle filters; inverse problem; Bayesian inference; SPARK-IGNITION ENGINE; DIESEL-ENGINE; THERMAL-ANALYSIS; BAYESIAN-INFERENCE; TRANSFER MODEL; SIMULATION; OPTIMIZATION;
D O I
10.1080/17415977.2013.797411
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The continuous growth of the worldwide vehicle fleet is leading to many private initiatives and governmental policies for the achievement of lower pollutant and greenhouse gas emissions through energetic efficiency improvement. The in-cylinder heat transfer has been generally recognised as a major factor influencing internal combustion engines efficiency and exhaust emissions. Therefore, the analysis of in-cylinder heat transfer is of importance for fuel economy, as well as for environmental preservation. In the present paper, the use of particle filters applied on the time-dependent heat transfer coefficient estimation of a combustion process in a spark-ignition internal combustion engine is presented. The combustion process was modelled as a transient zero-dimensional process based on the First Law of Thermodynamics for a perfect gas, and the fuel burned fraction was modelled through a Wiebe's function model. Results with different measurement frequencies and errors are available, using a sample importance resampling filter, showing a very good estimate, even for initial guesses far away from the real value of the unknown function.
引用
收藏
页码:483 / 506
页数:24
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