Estimating soot emission in diesel engines using gated recurrent unit networks

Alcan, Gökhan and Yılmaz, Emre and Ünel, Mustafa and Aran, Volkan and Yılmaz, Metin and Gürel, Çetin and Köprübaşı, Kerem (2019) Estimating soot emission in diesel engines using gated recurrent unit networks. IFAC-PapersOnLine, 52 (5). pp. 544-549. ISSN 2405-8963

This is the latest version of this item.

[thumbnail of AAC2019_soot_final.pdf] PDF

Download (1MB)


In this paper, a new data-driven modeling of a diesel engine soot emission formation using gated recurrent unit (GRU) networks is proposed. Different from the traditional time series prediction methods such as nonlinear autoregressive with exogenous input (NARX) approach, GRU structure does not require the determination of the pure time delay between the inputs and the output, and the number of regressors does not have to be chosen beforehand. Gates in a GRU network enable to capture such dependencies on the past input values without any prior knowledge. As a design of experiment, 30 different points in engine speed - injected fuel quantity plane are determined and the rest of the input channels, i.e., rail pressure, main start of injection, equivalence ratio, and intake oxygen concentration are excited with chirp signals in the intended regions of operation. Experimental results show that the prediction performances of GRU based soot models are quite satisfactory with 77% training and 57% validation fit accuracies and normalized root mean square error (NRMSE) values are less than 0.038 and 0.069, respectively. GRU soot models surpass the traditional NARX based soot models in both steady-state and transient cycles.
Item Type: Article
Additional Information: WoS Document Type: Proceedings Paper / Conference: 9th IFAC International Symposium on Advances in Automotive Control (AAC) / Location: Orleans, FRANCE / Date: JUN 23-27, 2019
Uncontrolled Keywords: Diesel Engine; Combustion Process; Soot Emission; Experiment Design; Gated Recurrent Unit
Subjects: T Technology > TJ Mechanical engineering and machinery
T Technology > TJ Mechanical engineering and machinery > TJ163.12 Mechatronics
T Technology > TL Motor vehicles. Aeronautics. Astronautics
Divisions: Integrated Manufacturing Technologies Research and Application Center
Faculty of Engineering and Natural Sciences > Academic programs > Mechatronics
Faculty of Engineering and Natural Sciences
Depositing User: Mustafa Ünel
Date Deposited: 05 Nov 2019 00:03
Last Modified: 26 Apr 2022 10:12

Available Versions of this Item

Actions (login required)

View Item
View Item