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Processes
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Clean Combustion and Emission in Vehicle Power System, 2nd Edition
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Clean Combustion and Emission in Vehicle Power System, 2nd Edition

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Sustainable Processes".

Deadline for manuscript submissions: 28 February 2025 | Viewed by 6698

Special Issue Editor

Prof. Dr. Jiaqiang E

grade E-Mail Website
Guest Editor
College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, China
Interests: combustion & micro-combustion; biodiesel combustion; micro-thermophotovoltaic power generators; after-treatment system of automotive systems; battery thermal management system
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Air pollutants from vehicle power systems are not only harmful to the environment but also have detrimental effects on human health, and there is a global trend towards enforcing more stringent regulations on these exhaust gas constituents. As a result, many clean combustion and emission technologies, such as chemical looping combustion, mild combustion, porous media combustion, and plasma-assisted combustion, have been developed in the past 30 years. Through the application of these technologies, nitrogen oxide (NOx), carbon dioxide (CO2), and particulate matter (PM) emission from combustion can be mitigated effectively. Nowadays, clean combustion technologies are attracting more and more attention from researchers all over the world. To promote communication between researchers, we invite investigators to contribute original research articles, as well as review articles, that will stimulate the continuing efforts to understand the mechanisms, production, and controls related to clean combustion and emission technology in vehicle power systems.

The 1st edition link: https://www.mdpi.com/journal/processes/special_issues/combustion_emission

Prof. Dr. Jiaqiang E
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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. Processes is an international peer-reviewed open access monthly 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

  • reaction kinetics
  • clean combustion and emission
  • after-treatment system
  • diagnostic techniques
  • laminar and turbulent flames
  • heat and mass transfer
  • novel combustion concepts, technologies, and systems
  • clean combustion instability

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Published Papers (7 papers)

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Research

20 pages, 7575 KiB  
Article
Structural Performance Analysis and Optimization of Small Diesel Engine Exhaust Muffler
by Fang Li, Wenhua Yuan, Yi Ma and Jun Fu
Processes 2024, 12(10), 2186; https://doi.org/10.3390/pr12102186 - 8 Oct 2024
Viewed by 650
Abstract
In recent years, the optimization of diesel engine exhaust mufflers has predominantly targeted acoustic performance, while the impact on engine power performance has often been overlooked. Therefore, this paper proposes a parallel perforated tube expansion muffler and conducts a numerical analysis of its [...] Read more.
In recent years, the optimization of diesel engine exhaust mufflers has predominantly targeted acoustic performance, while the impact on engine power performance has often been overlooked. Therefore, this paper proposes a parallel perforated tube expansion muffler and conducts a numerical analysis of its acoustic and aerodynamic performance using the finite element method. Then, a Kriging model is established based on the Design of Experiments to reveal the impact of different parameter couplings on muffler performance. With transmission loss (TL) and pressure loss (PL) as the optimization objectives, a multi-objective optimization study is carried out using the competitive multi-objective particle swarm optimization (CMOPSO). The optimization results indicate that this method can simplify the optimization model and improve optimization efficiency. After CMOPSO calculation, the average TL of the muffler increased from 27.3 dB to 31.6 dB, and the PL decreased from 1087 Pa to 953 Pa, which reduced the exhaust noise and improved the fuel economy of the engine, thus enhancing the overall performance of the muffler. This work provides a reference and guidance for the optimal design of mufflers for small agricultural diesel engines. Full article
(This article belongs to the Special Issue Clean Combustion and Emission in Vehicle Power System, 2nd Edition)
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18 pages, 4478 KiB  
Article
Experimental Study on the Spray Characteristics of Diesel and Hydrotreated Vegetable Oil (HVO) Fuels under Different Injection Pressures
by Chang Zhai, Kuichun Li, Pengbo Dong, Yu Jin, Hongliang Luo, Beini Zhou and Yang Liu
Processes 2024, 12(8), 1697; https://doi.org/10.3390/pr12081697 - 14 Aug 2024
Viewed by 976
Abstract
This investigation employed the diffused back-illumination (DBI) technique to analyze the spray characteristics of hydrotreated vegetable oil (HVO) fuel at three injection pressures and compared them with conventional diesel fuel. The results showed that as the injection pressure increased, the peak injection rates [...] Read more.
This investigation employed the diffused back-illumination (DBI) technique to analyze the spray characteristics of hydrotreated vegetable oil (HVO) fuel at three injection pressures and compared them with conventional diesel fuel. The results showed that as the injection pressure increased, the peak injection rates of both the HVO and diesel increased. At injection pressures above 120 MPa, the injection rates of both fuels were nearly identical, though differences were observed at lower pressures. Increasing the injection pressure reduced the injection delay. The HVO fuel exhibited a shorter spray tip penetration, lower equivalence ratio, larger spray angle, and spray volume, but its spray angle stability was lower than that of diesel. The ambient gas entrainment rate primarily occurred in two stages, significantly influenced by the spray breakup development stage. For diesel sprays, the injection pressure mainly affected the equivalence ratio near the nozzle with minimal downstream impact. Dent’s model provided better predictions of the penetration distance for diesel, while Hiroyasu’s model was more accurate in predicting the penetration distance of the HVO at 120 MPa and 180 MPa. Inagaki’s model performed better in predicting the spray angle for diesel, whereas Hiroyasu’s model was more accurate for the HVO spray angle predictions. Through this research, a better understanding of the spray characteristics of green fuels will be achieved, providing a reference for the design and optimization of new generation engines. Full article
(This article belongs to the Special Issue Clean Combustion and Emission in Vehicle Power System, 2nd Edition)
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23 pages, 12365 KiB  
Article
Optimization Analysis of Various Parameters Based on Response Surface Methodology for Enhancing NOx Catalytic Reduction Performance of Urea Selective Catalytic Reduction on Cu-ZSM-13 Catalyst
by Weiqi Li, Jie Wu, Dongwei Yao, Feng Wu, Lei Wang, Hua Lou, Haibin He and Jingyi Hu
Processes 2024, 12(7), 1519; https://doi.org/10.3390/pr12071519 - 19 Jul 2024
Viewed by 596
Abstract
While selective catalytic reduction (SCR) has long been indispensable for nitrogen oxide (NOx) removal, optimizing its performance remains a significant challenge. This study investigates the combined effects of structural and intake parameters on SCR performance, an aspect often overlooked in previous [...] Read more.
While selective catalytic reduction (SCR) has long been indispensable for nitrogen oxide (NOx) removal, optimizing its performance remains a significant challenge. This study investigates the combined effects of structural and intake parameters on SCR performance, an aspect often overlooked in previous research. This paper innovatively developed a three-dimensional SCR channel model and employed response surface methodology to conduct an in-depth analysis of multiple key factors. This multidimensional, multi-method approach enables a more comprehensive understanding of SCR system mechanics. Through target optimization, we achieved a simultaneous improvement in three critical indicators: the NOx conversion rate, pressure drop, and ammonia slip. It is worth noting that the NOx conversion rate has been optimized from 17.07% to 98.25%, the pressure drop has been increased from 3454.62 Pa to 2558.74 Pa, and the NH3 slip has been transformed from 122.26 ppm to 17.49 ppm. These results not only advance the theoretical understanding of SCR technology but also provide valuable design insights for practical applications. Our findings pave the way for the development of more efficient and environmentally friendly SCR systems, potentially revolutionizing NOx control in various industries. Full article
(This article belongs to the Special Issue Clean Combustion and Emission in Vehicle Power System, 2nd Edition)
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21 pages, 22371 KiB  
Article
Study on the Evolution of Physicochemical Properties of Carbon Black at Different Regeneration Stages of Diesel Particulate Filters Regenerated by Non-Thermal Plasma
by Yong Luo, Yunxi Shi, Kaiqi Zhuang, Ruirui Ji, Xulong Chen, Yankang Huang, Zhe Wang, Yixi Cai and Xiaohua Li
Processes 2024, 12(6), 1113; https://doi.org/10.3390/pr12061113 - 28 May 2024
Cited by 8 | Viewed by 894
Abstract
As a new type of aftertreatment technology, non-thermal plasma (NTP) can effectively decompose the particulate matter (PM) deposited in diesel particulate filters (DPFs). In this paper, a regeneration test of a DPF loaded with carbon black was carried out using an NTP injection [...] Read more.
As a new type of aftertreatment technology, non-thermal plasma (NTP) can effectively decompose the particulate matter (PM) deposited in diesel particulate filters (DPFs). In this paper, a regeneration test of a DPF loaded with carbon black was carried out using an NTP injection system, and the changes of oxidative activity, elemental content, and occurrence state, microstructure and graphitization degree of carbon black were analyzed to reveal the evolution of the physicochemical properties of carbon black at different regeneration stages of the DPF regenerated by NTP. As the regeneration stage of the DPF advanced, Ti, Tmax, and Te of the carbon black at the bottom of the DPF decreased, which were higher than those at the regeneration interface. After the NTP reaction, the proportion of C element decreased to less than 80%, while the proportion of O element increased to more than 20%; C-O was converted to C=O and the relative content of C=O increased. The average microcrystalline length and average spacing decreased, while the average microcrystalline curvature increased. The ID1/IG (relative peak intensities) of carbon black samples decreased from 3.31 to 3.10, and the R3 (relative peak intensities, R3 = ID3/(IG + ID2 + ID3)) increased from 0.41 to 0.58. The content of carbon clusters had a great influence on the disorder of the microcrystalline structure, so the graphitization degree of carbon black decreased and the oxidation activity increased. Full article
(This article belongs to the Special Issue Clean Combustion and Emission in Vehicle Power System, 2nd Edition)
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17 pages, 5298 KiB  
Article
Constructing a Skeletal Iso-Propanol–Butanol–Ethanol (IBE)–Diesel Mechanism Using the Decoupling Method
by Yi Ma, Shaomin Zhao, Junhong Zhao, Jun Fu and Wenhua Yuan
Processes 2024, 12(5), 995; https://doi.org/10.3390/pr12050995 - 14 May 2024
Viewed by 862
Abstract
In recent years, biofuels have gained considerable prominence in response to growing concerns about resource scarcity and environmental pollution. Previous investigations have revealed that the appropriate blending of iso-propanol–butanol–ethanol (IBE) into diesel significantly improves both the c combustion efficiency and emission performance of [...] Read more.
In recent years, biofuels have gained considerable prominence in response to growing concerns about resource scarcity and environmental pollution. Previous investigations have revealed that the appropriate blending of iso-propanol–butanol–ethanol (IBE) into diesel significantly improves both the c combustion efficiency and emission performance of internal combustion engines (ICEs). However, the combustion mechanism of IBE–diesel for the numerical studies of engines has not reached maturity. In this study, a skeletal IBE–diesel multi-component mechanism, comprising 157 species and 603 reactions, was constructed using the decoupling method. It was formulated by amalgamating the reduced fuel-related sub-mechanisms derived from diesel surrogates (n-dodecane, iso-cetane, iso-octane, toluene, and decalin) and n-butanol, along with the detailed core sub-mechanisms of C1, C2, C3, CO, and H2. The constructed mechanism is capable of better matching the physical and chemical properties of actual diesel fuel. Extensive validation, including ignition delay, laminar flame speed, a premixed flame species profile, and engine experimental data, confirms the reliability of the mechanism in engine numerical studies. Subsequent investigations reveal that as the IBE blend ratio and EGR rate increase, the ignition delay exhibits an increase, while the combustion duration experiences a decrease. Blending IBE into diesel, along with a specific EGR rate, proves effective in simultaneously reducing NOx and soot emissions. Full article
(This article belongs to the Special Issue Clean Combustion and Emission in Vehicle Power System, 2nd Edition)
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14 pages, 2981 KiB  
Article
Using a One-Dimensional Convolutional Neural Network with Taguchi Parametric Optimization for a Permanent-Magnet Synchronous Motor Fault-Diagnosis System
by Meng-Hui Wang, Fu-Chieh Chan and Shiue-Der Lu
Processes 2024, 12(5), 860; https://doi.org/10.3390/pr12050860 - 25 Apr 2024
Viewed by 870
Abstract
Hyperparameter tuning requires trial and error, which is time consuming. This study employed a one-dimensional convolutional neural network (1D CNN) and Design of Experiments (DOE) using the Taguchi method for optimal parameter selection, in order to improve the accuracy of a fault-diagnosis system [...] Read more.
Hyperparameter tuning requires trial and error, which is time consuming. This study employed a one-dimensional convolutional neural network (1D CNN) and Design of Experiments (DOE) using the Taguchi method for optimal parameter selection, in order to improve the accuracy of a fault-diagnosis system for a permanent-magnet synchronous motor (PMSM). An orthogonal array was used for the DOE. One control factor with two levels and six control factors with three levels were proposed as the parameter architecture of the 1D CNN. The identification accuracy and loss function were set to evaluate the fault-diagnosis system in the optimization design. Analysis of variance (ANOVA) was conducted to design multi-objective optimization and resolve conflicts. Motor fault signals measured by a vibration spectrum analyzer were used for fault diagnosis. The results show that the identification accuracy of the proposed optimization method reached 99.91%, which is higher than the identification accuracy of 96.75% of the original design parameters before optimization. With the proposed method, the parameters can be optimized with a good DOE and the minimum number of experiments. Besides reducing time and the use of resources, the proposed method can speed up the construction of a motor fault-diagnosis system with excellent recognition. Full article
(This article belongs to the Special Issue Clean Combustion and Emission in Vehicle Power System, 2nd Edition)
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15 pages, 1858 KiB  
Article
Diesel Adulteration Detection with a Machine Learning-Enhanced Laser Sensor Approach
by Bachar Mourched, Tariq AlZoubi and Sabahudin Vrtagic
Processes 2024, 12(4), 798; https://doi.org/10.3390/pr12040798 - 16 Apr 2024
Viewed by 1171
Abstract
This paper introduces a novel and cost-effective method for detecting adulterated diesel, specifically targeting contamination with kerosene, by leveraging machine learning and the refractive index values of mixed diesel samples. It proposes a laser-based sensor, employing COMSOL simulations for synthetic data generation to [...] Read more.
This paper introduces a novel and cost-effective method for detecting adulterated diesel, specifically targeting contamination with kerosene, by leveraging machine learning and the refractive index values of mixed diesel samples. It proposes a laser-based sensor, employing COMSOL simulations for synthetic data generation to facilitate machine learning training. This innovative approach not only streamlines the detection process by eliminating the need for expensive equipment and specialized personnel but also enables on-site testing without extensive sample preparation. The sensor’s design, utilizing light refraction and reflection principles, allows for the accurate measurement of diesel adulteration levels. Validation results showcase the machine learning models’ high precision in predicting adulteration percentages, as evidenced by an R-squared value of 0.999 and a mean absolute error of 0.074. This research signifies a leap in sensor technology, offering a practical solution for rapid diesel adulteration detection, especially in developing countries, by minimizing reliance on advanced laboratory analyses. The sensor’s design aligns with the requirements for low-cost IoT technology, presenting a versatile tool for various applications. Full article
(This article belongs to the Special Issue Clean Combustion and Emission in Vehicle Power System, 2nd Edition)
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