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A Review of the State-of-the-Art Emission Control Strategies in Modern Diesel Engines

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Abstract

Accurate prediction and control of diesel engine-out emissions are vital areas of interest for automotive manufacturers and researchers. This article presents an investigative review of performance and emission control improvements in diesel engines over the past few decades. A brief background of environmental organizations like the Environmental Protection Agency has been included because they initiated stringent emission norms. These requirements caused diesel engine development to be a more tedious task and also triggered various technologies employed by engine manufacturers to meet the new norms. This review focuses on various diesel engine modeling methods that have evolved during the last few decades and have contributed to the technological advancement in modern diesel engines. Three types of modeling methods and their applications are discussed in detail along with a few controlling methods using different control theories. A detailed emphasis on recent engine control strategies reviews controlling gridlocks and viable solutions in diesel engines. Significant challenges such as model fitness, accuracy, robustness, and precise predictions that provide extensive scope for researchers working in diesel engine out emission control are addressed. Various advancements in optimized engine model development for further performance enhancement are also reported.

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Abbreviations

0-D:

0 Dimensional

AHRR:

Apparent Heat Release Rate

ANN:

Artificial Neural Network

BSFC :

Brake Specific Fuel Consumption

BTS:

Bureau of Transportation Statistics

CAA :

Clean Air Act

CAD :

Crank Angle Degrees

CI:

Compression-Ignition

CMAC:

Cerebellar Model Articulation Controller

CN:

Cyanide

CO :

Carbon Monoxide

DOF:

Degree of Freedom

DPF:

Diesel Particulate Filter

ECM:

Electronic Control Module

ECU:

Engine Control Unit

EGR:

Exhaust Gas Recirculation

EO:

Engine Out

EOI:

End of Injection

EPA:

Environmental Protection Agency

ETA:

Electric Turbo Assist

FB:

Feedback

FEL:

Feedback Error Learning

FF:

Feedforward

FHWA:

Federal Highway Administration

FMI:

Functional Mockup Interface

GT Suite:

Gamma Technologies Suite

HCCI:

Homogenous Charged Compression Ignition

HCN:

Hydrogen Cyanide

HDE:

Heavy-Duty Engines

HDV:

Heavy-Duty Vehicle

HiL:

Hardware in Loop

HRR:

Heat Release Rate

IC :

Internal Combustion

LL:

Liquid Length

LOL:

Lift-Off Length

LQG :

Linear Quadrature Gaussian

MiL:

Model in Loop

MPC:

Model Predictive Control

N2 :

Nitrogen molecule

N2O:

Nitrous Oxide

NH2 :

Azanide

NH3 :

Ammonia

NOE:

Nonlinear Output Error

NOx :

Nitrogen Oxides

OBD:

On-Board Diagnosis

OICA:

Organisation Internationale des Constructeurs d'Automobiles

OLL:

Optimization layer-by-layer

PCCI:

Premixed Charge Compression Ignition

PI:

Proportional Integral

PID:

Proportional Integral and Derivative Controller

RNN:

Recurrent Neural Network

SCR:

Selective Catalytic Reduction

SiL:

Software in Loop

SOC:

Start of Combustion

SOI:

Start of Injection

TDE:

Turbocharged Diesel Engine

UHC:

Unburnt Hydrocarbon

VGT:

Variable Geometry Turbine

VMT :

Vehicle Miles Traveled

VNT:

Variable Nozzle Turbine

VOCs:

Volatile Organic Compounds

VVA:

Variable Valve Actuation

VVT:

Variable Valve Turbine

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  1. Department of Mechanical and Energy Engineering, Indiana University Purdue University Indianapolis, Indianapolis, IN, 46202, USA

    Vaibhav Ahire, Mahesh Shewale & Ali Razban

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Ahire, V., Shewale, M. & Razban, A. A Review of the State-of-the-Art Emission Control Strategies in Modern Diesel Engines. Arch Computat Methods Eng 28, 4897–4915 (2021). https://doi.org/10.1007/s11831-021-09558-x

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