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Diesel Engine Combustion and Emissions Control

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Energy Science and Technology".

Deadline for manuscript submissions: 20 January 2026 | Viewed by 1750

Special Issue Editors


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Guest Editor
Department of Smart Electrics Automobile, Jeonbuk Campus of Korea Polytechnic University, 154 Baekhakje-gil, Gimje-si, Jeollabuk-do, Republic of Korea
Interests: diesel engines; alternative fuels; combustion and emissions; CO2 capture; low-carbon and carbon-free fuels
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Guest Editor
Division of Mechanical Design Engineering, Jeonbuk National University, 567 Baekje-daero, Deokjin-gu, Jeonju-si 54896, Jeollabuk-do, Republic of Korea
Interests: alternative fuels; diesel engine; combustion; emission; particle morphology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As one of the main power output machineries, diesel engines have advantages such as high torque, good fuel economy and excellent durability, and are widely used in automobiles, trucks, ships, agricultural machinery, generators and construction machinery. However, with the increasingly strict environmental requirements and the increasing attention paid to energy efficiency, the combustion efficiency and exhaust emissions of diesel engines have become the main research focus. Therefore, strategies to improve the combustion efficiency and reduce harmful gases and carbon dioxide emissions of diesel engines have become a major research topic. At present, conventional technologies mainly include the development of new alternative fuels (e.g., biofuels, alcohols, ammonia, hydrogen), optimization of injection strategies (e.g., injection timing, injection pressure, multi-stage injection), adoption of advanced exhaust post-treatment technologies (e.g.,  diesel oxidation catalyst, diesel particulate filter, exhaust gas recirculation, selective catalytic reduction), development of new combustion technologies (e.g., homogenous charge compression ignition, reactivity controlled compression ignition and premixed charge compression ignition), optimization of intake system and turbocharging technology, as well as optimization of electronic control systems and vehicle weight.

Therefore, this Special Issue aims to explore advanced combustion and emission reduction technologies for diesel engines. Hereby, we sincerely welcome colleagues all over the world to submit contributions to this Special Issue.

The wide variety of topics for this Special Issue includes, but is not limited to, the following:

  • Diesel engines;
  • Alternative fuels;
  • Combustion and emissions;
  • New combustion technologies;
  • Advanced exhaust post-treatment technologies;
  • CO2 capture;
  • Low-carbon and carbon-free fuels;
  • Powertrain electrification;
  • High-voltage battery;
  • Battery management system;
  • Other advanced technologies.

Dr. Sam Ki Yoon
Dr. Jun Cong Ge
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • diesel engines
  • combustion and emissions
  • alternative fuels
  • new combustion technologies
  • advanced exhaust post-treatment technologies
  • CO2 capture
  • low-carbon and carbon-free fuels
  • powertrain electrification
  • high-voltage battery
  • battery management system

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Published Papers (2 papers)

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Research

21 pages, 4063 KB  
Article
Experimental Study on Biodiesel Injection Characteristics and Spray Development Tendency
by Boban Nikolić, Breda Kegl, Dragan Marinković, Nikola Petrović and Vesna Jovanović
Appl. Sci. 2025, 15(22), 12261; https://doi.org/10.3390/app152212261 - 19 Nov 2025
Viewed by 343
Abstract
The conversion of biodiesel’s chemical energy into mechanical work in diesel engines is strongly influenced by the formation and quality of the fuel–air mixture. The physical and chemical properties of biodiesel, together with the operating characteristics of the fuel injection system, play a [...] Read more.
The conversion of biodiesel’s chemical energy into mechanical work in diesel engines is strongly influenced by the formation and quality of the fuel–air mixture. The physical and chemical properties of biodiesel, together with the operating characteristics of the fuel injection system, play a crucial role in this process. This study presents experimental findings on the injection behavior of a mechanically controlled injection system using three fuel types: pure rapeseed biodiesel, a 50% biodiesel–diesel blend, and conventional diesel fuel. The analysis focused on injection pressure, injection timing, injection duration, and fuel delivery under various operating conditions. In the second part of the experimental investigation, spray visualization was carried out by injecting fuels into a transparent liquid-filled chamber. A dedicated imaging and processing system was applied to capture and analyze spray development. From the recorded sequences, macroscopic spray parameters—including spray penetration length, spray cone angle, and projected spray area—were determined across different injection regimes. This approach allows clear identification of spray development tendencies and supports systematic comparison between fuels, particularly in relation to differences in injection pressure, injection duration, and delivered fuel quantity arising from the mechanically governed injection system. Correlation analysis between spray penetration length and peak injection pressure further highlights pressure-driven contributions to spray evolution. The findings contribute to better understanding of biodiesel spray behavior under realistic mechanically controlled conditions, supporting optimization of fuel injection performance and aiding in the selection or formulation of biodiesel fuels with improved spray characteristics. Full article
(This article belongs to the Special Issue Diesel Engine Combustion and Emissions Control)
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30 pages, 3118 KB  
Article
Prediction of Combustion Parameters and Pollutant Emissions of a Dual-Fuel Engine Based on Recurrent Neural Networks
by Joel Freidy Ebolembang, Fabrice Parfait Nang Nkol, Lionel Merveil Anague Tabejieu, Fernand Toukap Nono and Claude Valery Ngayihi Abbe
Appl. Sci. 2025, 15(18), 9868; https://doi.org/10.3390/app15189868 - 9 Sep 2025
Viewed by 779
Abstract
A critical challenge in engine research lies in minimizing harmful emissions while optimizing the efficiency of internal combustion engines. Dual-fuel engines, operating with methanol and diesel, offer a promising alternative, but their combustion modeling remains complex due to the intricate thermochemical interactions involved. [...] Read more.
A critical challenge in engine research lies in minimizing harmful emissions while optimizing the efficiency of internal combustion engines. Dual-fuel engines, operating with methanol and diesel, offer a promising alternative, but their combustion modeling remains complex due to the intricate thermochemical interactions involved. This study proposes a predictive framework that combines validated CFD simulations with deep learning techniques to estimate key combustion and emission parameters in a methanol–diesel dual-fuel engine. A three-dimensional CFD model was developed to simulate turbulent combustion, methanol injection, and pollutant formation, using the RNG k-ε turbulence model. A temporal dataset consisting of 1370 samples was generated, covering the compression, combustion, and early expansion phases—critical regions influencing both emissions and in-cylinder pressure dynamics. The optimal configuration identified involved a 63° spray injection angle and a 25% methanol proportion. A Gated Recurrent Unit (GRU) neural network, consisting of 256 neurons, a Tanh activation function, and a dropout rate of 0.2, was trained on this dataset. The model accurately predicted in-cylinder pressure, temperature, NOx emissions, and impact-related parameters, achieving a Pearson correlation coefficient of ρ = 0.997. This approach highlights the potential of combining CFD and deep learning for rapid and reliable prediction of engine behavior. It contributes to the development of more efficient, cleaner, and robust design strategies for future dual-fuel combustion systems. Full article
(This article belongs to the Special Issue Diesel Engine Combustion and Emissions Control)
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