文章基本信息

标题：Diesel Engine NOx Emission Modeling Using a New Experiment Design and Reduced Set of Regressors
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作者：Gokhan Alcan ; Mustafa Unel ; Volkan Aran 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2018
卷号：51
期号：15
页码：168-173
DOI：10.1016/j.ifacol.2018.09.114
语种：English
出版社：Elsevier
摘要：AbstractIn this paper, NOx emissions from a diesel engine are modeled with nonlinear autoregressive with exogenous input (NARX) model. Airpath and fuelpath channels are excited by chirp signals where the frequency profile of each channel is generated by increasing the number of sweeps. Past values of the output are employed only in linear prediction with all input regressors, and the most significant input regressors are selected for the nonlinear prediction by orthogonal least square (OLS) algorithm and error reduction ratio. Experimental results show that NOx emissions can be modeled with high validation performance and models obtained using a reduced set of regressors perform better in terms of stability and robustness.
关键词：KeywordsDiesel EngineNOx EmissionOrthogonal Least SquareRegressor SelectionSigmoid NARX