scholarly journals Parameter Identifiability and Parameter Estimation of a Diesel Engine Combustion Model

2014 ◽  
Vol 02 (05) ◽  
pp. 131-137 ◽  
Author(s):  
Lilianne Denis-Vidal ◽  
Zohra Cherfi ◽  
Vincent Talon ◽  
El Hassane Brahmi
Keyword(s):  
Parameter Estimation ◽  
Diesel Engine ◽  
Combustion Model ◽  
Parameter Identifiability ◽  
Engine Combustion

Adaptive Combustion Control System Design of Diesel Engine via ASPR Based Adaptive Output Feedback with a PFC

2016 ◽  
Vol 28 (5) ◽  
pp. 664-673 ◽  
Author(s):  
Ikuro Mizumoto ◽  
◽  
Seiya Fujii ◽  
Jyunpei Tsunematsu
Keyword(s):  
Adaptive Control ◽  
Control System ◽  
Diesel Engine ◽  
Output Feedback ◽  
Combustion Model ◽  
Control System Design ◽  
Combustion Control ◽  
Adaptive Control System ◽  
Controlled System ◽  
Engine Combustion

[abstFig src='/00280005/07.jpg' width='300' text='Adaptive engine combustion control system' ] This paper deals with a combustion control system design problem of diesel engine. For a combustion model of diesel engine, which has been provided for on-board control, an adaptive control system based on an adaptive output feedback control with a simple adaptive feedforward input will be proposed based on the “almost strictly positive real-ness” (ASPR-ness) of the controlled system. A simple parallel feedforward compensator (PFC) design scheme, which renders the resulting augmented controlled system ASPR, will also be proposed based on basic combustion model properties to design stable adaptive control system for the diesel engine combustion control. The effectiveness of our proposal is confirmed through numerical simulation.

Common Rail Multi-Jet Diesel Engine Combustion Model Development for Control Purposes

2007 ◽  
Author(s):  
Fabrizio Ponti ◽  
Enrico Corti ◽  
Gabriele Serra ◽  
Matteo De Cesare
Keyword(s):  
Diesel Engine ◽  
Model Development ◽  
Common Rail ◽  
Combustion Model ◽  
Engine Combustion

Effects of water introduction on diesel engine combustion and emissions

1977 ◽  
Vol 16 (1) ◽  
pp. 321-336 ◽  
Author(s):  
G. Greeves ◽  
I.M. Khan ◽  
G. Onion
Keyword(s):  
Diesel Engine ◽  
Engine Combustion

scholarly journals A Multicomponent Blend as a Diesel Fuel Surrogate for Compression Ignition Engine Applications

2015 ◽  
Vol 137 (11) ◽  
Author(s):  
Yuanjiang Pei ◽  
Marco Mehl ◽  
Wei Liu ◽  
Tianfeng Lu ◽  
William J. Pitz ◽  
...  
Keyword(s):  
Diesel Engine ◽  
Diesel Fuel ◽  
Flow Reactor ◽  
Expert Knowledge ◽  
Combustion Model ◽  
Compression Ignition ◽  
Compression Ignition Engine ◽  
Combined Mechanism ◽  
Fuel Surrogate ◽  
Skeletal Mechanism

A mixture of n-dodecane and m-xylene is investigated as a diesel fuel surrogate for compression ignition (CI) engine applications. Compared to neat n-dodecane, this binary mixture is more representative of diesel fuel because it contains an alkyl-benzene which represents an important chemical class present in diesel fuels. A detailed multicomponent mechanism for n-dodecane and m-xylene was developed by combining a previously developed n-dodecane mechanism with a recently developed mechanism for xylenes. The xylene mechanism is shown to reproduce experimental ignition data from a rapid compression machine (RCM) and shock tube (ST), speciation data from the jet stirred reactor and flame speed data. This combined mechanism was validated by comparing predictions from the model with experimental data for ignition in STs and for reactivity in a flow reactor. The combined mechanism, consisting of 2885 species and 11,754 reactions, was reduced to a skeletal mechanism consisting 163 species and 887 reactions for 3D diesel engine simulations. The mechanism reduction was performed using directed relation graph (DRG) with expert knowledge (DRG-X) and DRG-aided sensitivity analysis (DRGASA) at a fixed fuel composition of 77% of n-dodecane and 23% m-xylene by volume. The sample space for the reduction covered pressure of 1–80 bar, equivalence ratio of 0.5–2.0, and initial temperature of 700–1600 K for ignition. The skeletal mechanism was compared with the detailed mechanism for ignition and flow reactor predictions. Finally, the skeletal mechanism was validated against a spray flame dataset under diesel engine conditions documented on the engine combustion network (ECN) website. These multidimensional simulations were performed using a representative interactive flame (RIF) turbulent combustion model. Encouraging results were obtained compared to the experiments with regard to the predictions of ignition delay and lift-off length at different ambient temperatures.

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