Diesel Engine Modeling

Characterization of n-butanol diesel blends on a small size variable compression ratio diesel engine: Modeling and experimental investigation

Energy Conversion and Management ◽

10.1016/j.enconman.2017.08.031 ◽

2017 ◽

Vol 150 ◽

pp. 242-258 ◽

Cited By ~ 30

Author(s):

Ashish Nayyar ◽

Dilip Sharma ◽

Shyam Lal Soni ◽

Alok Mathur

Keyword(s):

Experimental Investigation ◽

Diesel Engine ◽

Compression Ratio ◽

Variable Compression Ratio ◽

Engine Modeling ◽

Size Variable ◽

Variable Compression

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Crank Angle - Based Diesel Engine Modeling for Hardware-in-the-Loop Applications with In-Cylinder Pressure Sensors

10.4271/2007-01-1303 ◽

2007 ◽

Cited By ~ 18

Author(s):

Tino Schulze ◽

Markus Wiedemeier ◽

Herbert Schuette

Keyword(s):

Diesel Engine ◽

Pressure Sensors ◽

Hardware In The Loop ◽

Cylinder Pressure ◽

Engine Modeling ◽

Crank Angle

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A New High Pressure Droplet Vaporization Model for Diesel Engine Modeling

10.4271/952431 ◽

1995 ◽

Cited By ~ 24

Author(s):

Eric W. Curtis ◽

A. Uludogan ◽

Rolf D. Reitz

Keyword(s):

High Pressure ◽

Diesel Engine ◽

Droplet Vaporization ◽

Engine Modeling

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Diesel engine modeling based on recurrent neural networks for a hardware-in-the-loop simulation system of diesel generator sets

Neurocomputing ◽

10.1016/j.neucom.2017.12.054 ◽

2018 ◽

Vol 283 ◽

pp. 9-19 ◽

Cited By ~ 5

Author(s):

Mingxin Yu ◽

Xiaoying Tang ◽

Yingzi Lin ◽

Xiangzhou Wang

Keyword(s):

Neural Networks ◽

Diesel Engine ◽

Recurrent Neural Networks ◽

Simulation System ◽

Hardware In The Loop ◽

Diesel Generator ◽

Engine Modeling ◽

Generator Sets

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Mean Value Engine Modeling for a Diesel Engine with GT-Power 1D Detail Model

10.4271/2011-01-1294 ◽

2011 ◽

Cited By ~ 7

Author(s):

Hai Wu ◽

Xinlei Wang ◽

Richard Winsor ◽

Kirby Baumgard

Keyword(s):

Diesel Engine ◽

Mean Value ◽

Engine Modeling

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Heavy Duty Diesel Engine Modeling with Layered Artificial Neural Network Structures

10.4271/2018-01-0870 ◽

2018 ◽

Cited By ~ 3

Author(s):

Anton D. Sediako ◽

Jelena Andric ◽

Jonas Sjoblom ◽

Ethan Faghani

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Diesel Engine ◽

Network Structures ◽

Heavy Duty ◽

Engine Modeling ◽

Heavy Duty Diesel Engine ◽

Artificial Neural ◽

Heavy Duty Diesel

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MEAN VALUE DIESEL ENGINE MODELING, TRANSIENT VALIDATION AND AIR PATH CONTROL

International Journal of Advances on Automotive and Technology ◽

10.15659/ijaat.17.09.550 ◽

2017 ◽

Author(s):

TUĞBA TAPLI ◽

FATİH KENDİR ◽

UĞUR YAVAŞ

Keyword(s):

Diesel Engine ◽

Mean Value ◽

Engine Modeling ◽

Path Control

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Turbocharged Diesel Engine Modeling for Nonlinear Engine Control and State Estimation

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.2798519 ◽

1995 ◽

Vol 117 (1) ◽

pp. 20-30 ◽

Cited By ~ 194

Author(s):

Minghui Kao ◽

John J. Moskwa

Keyword(s):

Diesel Engine ◽

State Estimation ◽

Engine Speed ◽

Fuel Injection ◽

Production Model ◽

Injection Timing ◽

Engine Control ◽

Cylinder Pressure ◽

Engine Modeling ◽

Cylinder Model

Engine models that are used for nonlinear diesel engine control, state estimation, and model-based diagnostics are presented in this paper. By collecting, modifying, and adding to current available engine modeling techniques, two diesel engine models, a mean torque production model and a cylinder-by-cylinder model, are summarized for use in the formulation of control and state observation algorithms. In the cylinder-by-cylinder model, a time-varying crankshaft inertia model is added to a cylinder pressure generator to simulate engine speed variations due to discrete combustion events. Fuel injection timing and duration are control inputs while varying engine speed, cylinder pressure, and indicated torque are outputs from simulation. These diesel engine models can be used as engine simulators and to design diesel engine controllers and observers.

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