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20 pages, 3480 KiB

Open AccessArticle

Impact of Vehicle Aging and Mileage on Air Pollution Emissions

by Piotr Pryciński, Jacek Pielecha, Jarosław Korzeb, Roland Jachimowski and Piotr Pielecha

Energies 2025, 18(4), 939; https://doi.org/10.3390/en18040939 - 16 Feb 2025

Viewed by 978

Abstract

The research described in this paper aimed to verify the impact of road vehicle aging on air pollutant emissions. The problem of vehicle aging and the resulting changing air pollutant emissions was identified with the operational mileage of passenger cars. The validity of [...] Read more.

The research described in this paper aimed to verify the impact of road vehicle aging on air pollutant emissions. The problem of vehicle aging and the resulting changing air pollutant emissions was identified with the operational mileage of passenger cars. The validity of such an approach to research on air pollutant emissions changing over time was confirmed by a preliminary review of publications in scientific databases such as Scopus and Web of Science. The research problem presented in this paper was to assess the impact of vehicle aging on essential air pollutant emissions (CO, CO₂, NO_X). The research method included measuring the actual RDE air pollutant emissions using research equipment, i.e., the SEMTECH DS gaseous exhaust gas component analyzer. This study was conducted on vehicles with diesel engines, different operating ages, different mileages, and engines with similar displacement, mostly 1.9–2.0 dm³, and equipped with manual transmissions. The tests were conducted in the Poznań agglomeration. The results of measured air pollutant emissions in the RDE mode allowed for mapping the changes in air pollutant emissions for diesel engine vehicles with similar displacement as a function of operating age (mileage) and also for collecting preliminary data for analyses in the field of modeling road air pollutant emissions within the vehicle aging phenomenon. Full article

(This article belongs to the Special Issue CO₂ Emissions from Vehicles (Volume II))

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27 pages, 4768 KiB

Open AccessArticle

Analysis of Spatial Differences and Influencing Factors of Carbon-Emission Reduction Efficiency of New-Energy Vehicles in China

by Lingyao Wang, Taofeng Wu and Fangrong Ren

Energies 2025, 18(3), 635; https://doi.org/10.3390/en18030635 - 30 Jan 2025

Viewed by 598

Abstract

As new-energy vehicles (NEVs) gradually gain public attention, their carbon-reduction issues have become a focal point in academia. This study evaluates the carbon-reduction efficiency of NEVs in 21 Chinese provinces using an improved three-stage DEA model, analyzes spatial disparities with the Dagum Gini [...] Read more.

As new-energy vehicles (NEVs) gradually gain public attention, their carbon-reduction issues have become a focal point in academia. This study evaluates the carbon-reduction efficiency of NEVs in 21 Chinese provinces using an improved three-stage DEA model, analyzes spatial disparities with the Dagum Gini coefficient, and decomposes carbon-emission factors using the LMDI method. Results show that the overall carbon-reduction efficiency is low, with an average value of only 0.266. Significant differences exist in production- and consumption-stage efficiencies across regions. Shanxi Province performed the best, with efficiency scores of 1 in both stages, while the carbon-reduction stage showed the lowest efficiency, ranging between 0.2 and 0.3 in most regions. The central region exhibited the highest carbon-reduction efficiency, followed by the western and eastern regions, primarily influenced by intra-regional disparities. Energy intensity significantly suppresses carbon emissions, followed by energy structure, while economic development and population size positively contribute to carbon emissions. This study provides theoretical support for regional governments to formulate policies related to the NEV industry and offers practical guidance for its further development. Full article

(This article belongs to the Special Issue CO₂ Emissions from Vehicles (Volume II))

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11 pages, 3374 KiB

Open AccessArticle

Analysis of the Impact of Turn Signal Usage at Roundabouts on CO Emissions and Traffic Flows

by Monika Ziemska-Osuch and Dawid Osuch

Energies 2024, 17(23), 6145; https://doi.org/10.3390/en17236145 - 6 Dec 2024

Viewed by 776

Abstract

In contemporary times, one of the challenges in road traffic is the failure of drivers to adhere to traffic regulations. While the use of turn signals may seem trivial, the studies presented in this article demonstrate the significant impact that this practice can [...] Read more.

In contemporary times, one of the challenges in road traffic is the failure of drivers to adhere to traffic regulations. While the use of turn signals may seem trivial, the studies presented in this article demonstrate the significant impact that this practice can have on road traffic, both in terms of urban network capacity and fuel consumption, which consequently affects the emission of exhaust gases into the natural environment. A common example of the failure to use turn signals is when drivers navigate roundabouts. The example presented here analyzes an existing road network configuration consisting of two roundabouts and an intersection between them. The method of microsimulation was employed using the PTV Vissim 25 software. This study examined a scenario where the percentage of drivers adhering to the use of turn signals increased by 10% in each successive simulation version. The results clearly indicate that the capacity of the network, as well as the emissions of road pollutants, depend not only on traffic volume but also, most importantly, on traffic flow efficiency. Full article

(This article belongs to the Special Issue CO₂ Emissions from Vehicles (Volume II))

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35 pages, 7080 KiB

Open AccessArticle

The Possibility of Using Hydrogen as a Green Alternative to Traditional Marine Fuels on an Offshore Vessel Serving Wind Farms

by Monika Bortnowska and Arkadiusz Zmuda

Energies 2024, 17(23), 5915; https://doi.org/10.3390/en17235915 - 25 Nov 2024

Cited by 2 | Viewed by 1002

Abstract

Achieving the required decarbonisation targets by the shipping industry requires a transition to technologies with zero or near-zero greenhouse gas (GHG) emissions. One promising shipping fuel with zero emission of exhaust gases (including CO₂) is green hydrogen. This type of fuel, [...] Read more.

Achieving the required decarbonisation targets by the shipping industry requires a transition to technologies with zero or near-zero greenhouse gas (GHG) emissions. One promising shipping fuel with zero emission of exhaust gases (including CO₂) is green hydrogen. This type of fuel, recognised as a 100% clean solution, is being investigated for feasible use on a service offshore vessel (SOV) working for offshore wind farms. This study aims to examine whether hydrogen may be used on an SOV in terms of the technical and economic challenges associated with the design process and other factors. In the analyses, a reference has been made to the current International Maritime Organization (IMO) guidelines and regulations. In this study, it was assumed that hydrogen would be directly combusted in a reciprocating internal combustion engine. This engine type was reviewed. In further research, hydrogen fuel cell propulsion systems will also be considered. The hydrogen demand was calculated for the assumed data of the SOV, and then the volume and number of high-pressure tanks were estimated. The analyses revealed that the SOV cannot undertake 14-day missions using hydrogen fuel stored in cylinders on board. These cylinders occupy 66% of the ship’s current volume, and their weight, including the modular system, accounts for 62% of its deadweight. The costs are over 100% higher compared to MDO and LNG fuels and 30% higher than methanol. The actual autonomy of the SOV with hydrogen fuel is 3 days. Full article

(This article belongs to the Special Issue CO₂ Emissions from Vehicles (Volume II))

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19 pages, 927 KiB

Open AccessArticle

The Correlation of the Smart City Concept with the Costs of Toxic Exhaust Gas Emissions Based on the Analysis of a Selected Population of Motor Vehicles in Urban Traffic

by Wojciech Lewicki, Milena Bera and Monika Śpiewak-Szyjka

Energies 2024, 17(21), 5375; https://doi.org/10.3390/en17215375 - 29 Oct 2024

Cited by 2 | Viewed by 1164

Abstract

The intensive development of road transport has resulted in a significant increase in air pollution. This phenomenon is particularly noticeable in urban areas. This creates the need for analyses and forecasts of the scale and extent of future emissions of harmful substances into [...] Read more.

The intensive development of road transport has resulted in a significant increase in air pollution. This phenomenon is particularly noticeable in urban areas. This creates the need for analyses and forecasts of the scale and extent of future emissions of harmful substances into the environment. The aim of this study was to estimate the costs of the emission of toxic components of exhaust gases generated by all users of conventionally propelled vehicles travelling on a section of urban road in the next 25 years. The traffic study was carried out on an urban traffic route, playing a key role for road transport in the dimension of a given urban agglomeration. The traffic forecast for the analysed road section was based on the results of our own measurements carried out in April 2023 and external data from the General Directorate for Roads and Motorways. The results of the observations concerned six categories of vehicles for the morning and afternoon rush hours. Based on the data obtained, the generic structure of the vehicle population on the analysed section and the average daily traffic were determined. Using the methodology contained in the Blue Book of Road Infrastructure, parameters were calculated in the form of annual indicators of traffic growth on the analysed section, travel speed, and annual air pollution costs for selected vehicle categories, remembering at the same time that the Blue Book-based methodology does not distinguish between unit costs in relation to the type of emissions. The results of the study confirmed that there was an increase in the cost of toxic emissions for each vehicle category over the projected 25-year period. The largest increases were seen for trucks with trailers and passenger cars. In total, for all vehicle categories, emission costs nearly doubled from 2024 to 2046, from EUR 3,745,229 to EUR 7,443,384, due to the doubling of the number of vehicles resulting from the traffic forecast. The analyses presented here provide an answer to the question of what pollution costs may be faced by cities in which road transport will continue to be based on conventional types of propulsion. In addition, the research presented can be used to develop urban mobility transformation plans for the coming years, within the scope of the widely promoted smart city concept and the idea of electromobility, by pointing out to local authorities the direct economic benefits of these changes. Full article

(This article belongs to the Special Issue CO₂ Emissions from Vehicles (Volume II))

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22 pages, 3695 KiB

Open AccessArticle

Utilizing Artificial Neural Network Ensembles for Ship Design Optimization to Reduce Added Wave Resistance and CO₂ Emissions

by Tomasz Cepowski

Energies 2024, 17(21), 5326; https://doi.org/10.3390/en17215326 - 25 Oct 2024

Cited by 1 | Viewed by 827

Abstract

Increased maritime cargo transportation has necessitated stricter management of emissions from ships. The primary source of this pollution is fuel combustion, which is influenced by factors such as a ship’s added wave resistance. Accurate estimation of this resistance during ship design is crucial [...] Read more.

Increased maritime cargo transportation has necessitated stricter management of emissions from ships. The primary source of this pollution is fuel combustion, which is influenced by factors such as a ship’s added wave resistance. Accurate estimation of this resistance during ship design is crucial for minimizing exhaust emissions. The challenge is that, at the preliminary parametric design stage, only limited geometric data about the ship is available, and the existing methods for estimating added wave resistance cannot be applied. This article presents the application of artificial neural network (ANN) ensembles for estimating added wave resistance based on dimensionless design parameters available at the preliminary design stage, such as the length-to-breadth ratio (L/B), breadth-to-draught ratio (B/T), length-to-draught ratio (L/T), block coefficient (CB), and the Froude number (Fn). Four different ANN ensembles are developed to predict this resistance using both complete sets of design characteristics (i.e., L/B, B/T, CB, and Fn) and incomplete sets, such as L/B, CB, and Fn; B/T, CB, and Fn; and L/T, CB, and Fn. This approach allows for the consideration of CO₂ emissions at the parametric design stage when only limited ship dimensions are known. An example in this article demonstrates that minor modifications to typical container ship designs can significantly reduce added wave resistance, resulting in a daily reduction of up to 2.55 tons of CO₂ emissions. This reduction is equivalent to the emissions produced by 778 cars per day, highlighting the environmental benefits of optimizing ship design. Full article

(This article belongs to the Special Issue CO₂ Emissions from Vehicles (Volume II))

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18 pages, 7864 KiB

Open AccessArticle

Towards Simpler Approaches for Assessing Fuel Efficiency and CO₂ Emissions of Vehicle Engines in Real Traffic Conditions Using On-Board Diagnostic Data

by Fredy Rosero, Carlos Xavier Rosero and Carlos Segovia

Energies 2024, 17(19), 4814; https://doi.org/10.3390/en17194814 - 26 Sep 2024

Cited by 1 | Viewed by 1703

Abstract

Discrepancies between laboratory vehicle performance and real-world traffic conditions have been reported in numerous studies. In response, emission and fuel regulatory frameworks started incorporating real-world traffic evaluations and vehicle monitoring using portable emissions measurement systems (PEMS) and on-board diagnostic (OBD) data. However, in [...] Read more.

Discrepancies between laboratory vehicle performance and real-world traffic conditions have been reported in numerous studies. In response, emission and fuel regulatory frameworks started incorporating real-world traffic evaluations and vehicle monitoring using portable emissions measurement systems (PEMS) and on-board diagnostic (OBD) data. However, in regions with technical and economic constraints, such as Latin America, the use of PEMS is often limited, highlighting the need for low-cost methodologies to assess vehicle performance. OBD interfaces provide extensive vehicle and engine operational data in this context, offering a valuable alternative for analyzing vehicle performance in real-world conditions. This study proposes a straightforward methodology for assessing vehicle fuel efficiency and carbon dioxide (CO₂) emissions under real-world traffic conditions using OBD data. An experimental campaign was conducted with three gasoline-powered passenger vehicles representative of the Ecuadorian fleet, operating as urban taxis in Ibarra, Ecuador. This methodology employs an OBD interface paired with a mobile phone data logging application to capture vehicle kinematics, engine parameters, and fuel consumption. These data were used to develop engine maps and assess vehicle performance using the vehicle-specific power (VSP) approach based on the energy required for vehicle propulsion. Additionally, VSP analysis combined with OBD data facilitated the development of an energy-emission model to characterize fuel consumption and CO₂ emissions for the tested vehicles. The results demonstrate that OBD systems effectively monitor vehicle performance in real-world conditions, offering crucial insights for improving urban transportation sustainability. Consequently, OBD data serve as a critical resource for research supporting decarbonization efforts in Latin America. Full article

(This article belongs to the Special Issue CO₂ Emissions from Vehicles (Volume II))

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20 pages, 6222 KiB

Open AccessEditor’s ChoiceArticle

Analysis of Non-Road Mobile Machinery Homologation Standards in Relation to Actual Exhaust Emissions

by Natalia Szymlet, Michalina Kamińska, Andrzej Ziółkowski and Jakub Sobczak

Energies 2024, 17(15), 3624; https://doi.org/10.3390/en17153624 - 24 Jul 2024

Cited by 3 | Viewed by 1119

Abstract

This article presents issues related to the current approval procedures in the group of off-road vehicles. Our research aimed to demonstrate significant differences between actual railway vehicle operation and stationary homologation tests regarding exhaust emissions. The research cycle consisted of analyzing emissions of [...] Read more.

This article presents issues related to the current approval procedures in the group of off-road vehicles. Our research aimed to demonstrate significant differences between actual railway vehicle operation and stationary homologation tests regarding exhaust emissions. The research cycle consisted of analyzing emissions of toxic compounds from exhaust systems under real operating conditions, supplemented by a temporal share analysis based on the denormalized NRTC test upon which the tested object was homologated. Based on the conducted analyses, a significant difference was found between the actual operation of the tested railway vehicle and the stationary homologation test. By interpreting emission intensities within the parameter ranges of the propulsion unit’s operation, key areas with a significant impact on the vehicle’s overall emissions were identified. Based on the obtained results, a critical opinion is expressed regarding current homologation standards for the off-road vehicle group and the necessity for further empirical research in the area of actual operation of the tested vehicle group. Full article

(This article belongs to the Special Issue CO₂ Emissions from Vehicles (Volume II))

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30 pages, 6492 KiB

Open AccessArticle

Reducing CO₂ Emissions through the Strategic Optimization of a Bulk Carrier Fleet for Loading and Transporting Polymetallic Nodules from the Clarion-Clipperton Zone

by Tomasz Cepowski and Paweł Kacprzak

Energies 2024, 17(14), 3383; https://doi.org/10.3390/en17143383 - 10 Jul 2024

Cited by 2 | Viewed by 1040

Abstract

As global maritime cargo transportation intensifies, managing CO₂ emissions from ships becomes increasingly crucial. This article explores optimizing bulk carrier fleets for transporting polymetallic nodules (PMNs) from the Clarion-Clipperton Zone (CCZ) to reduce CO₂ emissions. Our analysis shows that larger bulk [...] Read more.

As global maritime cargo transportation intensifies, managing CO₂ emissions from ships becomes increasingly crucial. This article explores optimizing bulk carrier fleets for transporting polymetallic nodules (PMNs) from the Clarion-Clipperton Zone (CCZ) to reduce CO₂ emissions. Our analysis shows that larger bulk carriers, despite greater drifting forces from environmental conditions, emit less CO₂ over the entire transport mission, including loading and transit. Deploying large ships in global maritime trade could significantly reduce CO₂ emissions. This study also introduces a novel artificial neural network (ANN) model to estimate drifting forces during loading operations and proposes a new method for estimating CO₂ emissions, considering environmental conditions and ship seakeeping properties. These findings highlight the importance of fleet size optimization and effective operational planning in achieving environmental sustainability in maritime transport. Full article

(This article belongs to the Special Issue CO₂ Emissions from Vehicles (Volume II))

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15 pages, 31003 KiB

Open AccessArticle

Visualisation Testing of the Vertex Angle of the Spray Formed by Injected Diesel–Ethanol Fuel Blends

by Artur Krzemiński and Adam Ustrzycki

Energies 2024, 17(12), 3012; https://doi.org/10.3390/en17123012 - 18 Jun 2024

Cited by 2 | Viewed by 1326

Abstract

The internal combustion engine continues to be the main source of power in various modes of transport and industrial machines. This is due to its numerous advantages, such as easy adaptability, high efficiency, reliability and low fuel consumption. Despite these beneficial qualities of [...] Read more.

The internal combustion engine continues to be the main source of power in various modes of transport and industrial machines. This is due to its numerous advantages, such as easy adaptability, high efficiency, reliability and low fuel consumption. Despite these beneficial qualities of internal combustion engines, growing concerns are related to their negative environmental impacts. As a result, environmental protection has become a major factor determining advancements in the automotive industry in recent years, with the search for alternative fuels being one of the priorities in research and development activities. Among these, fuels of plant origin, mainly alcohols, are attracting a lot of attention due to their high oxygen content (around 35%). These fuels differ from diesel oil, for instance, in kinematic viscosity and density, which can affect the formation of the fuel spray and, consequently, the proper functioning of the compression–ignition engine, as well as the performance and purity of the exhaust gases emitted into the environment. The process of spray formation in direct injection compression–ignition engines is extremely complicated and requires detailed analysis of the fast-changing variables. This explains the need for using complicated research equipment enabling visualisation tests and making it possible to gain a more accurate understanding of the processes that take place. The present article aims to present the methodology for alternative fuel visualisation tests. To achieve this purpose, sprays formed by diesel–ethanol blends were recorded. A visualisation chamber and a high-speed camera were used for this purpose. The acquired video provided the material for the analysis of the changes in the vertex angle of the spray formed by the fuel blends. The test was carried out under reproducible conditions in line with the test methodology. The shape of the fuel spray is impacted by an increase in the proportional content of ethanol in the diesel and dodecanol blend. Based on the present findings, it is possible to note that the values of the vertex angle in the spray produced by the diesel–ethanol blend with the addition of dodecanol are most similar to those produced by diesel oil at an injection pressure of 100 MPa. The proposed methodology enables an analysis of the injection process based on the spray macrostructure parameters, and it can be applied in the testing of alternative fuels. Full article

(This article belongs to the Special Issue CO₂ Emissions from Vehicles (Volume II))

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11 pages, 3062 KiB

Open AccessArticle

The Oxidation Performance of a Carbon Soot Catalyst Based on the Pt-Pd Synergy Effect

by Diming Lou, Guofu Song, Kaiwen Xu, Yunhua Zhang and Kan Zhu

Energies 2024, 17(7), 1737; https://doi.org/10.3390/en17071737 - 4 Apr 2024

Cited by 2 | Viewed by 1172

Abstract

Pt-Pd-based noble metal catalysts are widely used in engine exhaust aftertreatment because of their better carbon soot oxidation performance. At present, the synergistic effect of Pt and Pd in CDPFs, which is the most widely used and common doping method, in catalyzing the [...] Read more.

Pt-Pd-based noble metal catalysts are widely used in engine exhaust aftertreatment because of their better carbon soot oxidation performance. At present, the synergistic effect of Pt and Pd in CDPFs, which is the most widely used and common doping method, in catalyzing the combustion of carbon smoke has not been reported, and it is not possible to give an optimal doping ratio of Pt and Pd. This paper investigates the carbon soot oxidation performance of different Pt/Pd ratios (Pt/Pd = 1:0, 10:1, 5:1, 1:1) based on physicochemical characterization and particle combustion kinetics calculations, aiming to reveal the Pt-Pd synergistic effect and its carbon soot oxidation law. The results show that Pt-based catalysts doped with Pd can improve the catalyst dispersion, significantly increase the specific surface area, and reduce the activation energy and reaction temperature of carbon soot reactions, but excessive doping of Pd leads to the enhancement of the catalyst agglomeration effect, a decrease in the specific surface area, and an increase in the activation energy and reaction temperature of the carbon soot reaction. The specific surface area and pore capacity of the catalyst are the largest, and the activation energy of particle oxidation and the pre-exponential factor are the smallest (203.44 kJ∙mol⁻¹ and 6.31 × 10⁷, respectively), which are 19.29 kJ∙mol⁻¹ and 4.95 × 10⁸ lower than those of pure carbon soot; meanwhile, the starting and final combustion temperatures of carbon soot (T₁₀ and T₉₀) are the lowest at 585.8 °C and 679.4 °C, respectively, which are 22.1 °C and 20.9 °C lower than those of pure carbon soot. Full article

(This article belongs to the Special Issue CO₂ Emissions from Vehicles (Volume II))

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20 pages, 2544 KiB

Open AccessArticle

The Effectiveness of HEVs Phase-Out by 2035 in Favor of BEVs with Respect to the Production of CO₂ Emissions: The Italian Case

by Francesca Maria Grimaldi and Pietro Capaldi

Energies 2024, 17(4), 961; https://doi.org/10.3390/en17040961 - 19 Feb 2024

Cited by 3 | Viewed by 2120

Abstract

The EU has planned the phase-out of new vehicles based on internal combustion engines in favor of high-efficiency battery electric vehicles (BEV) by 2035 (Fit for 55 package). However, many doubts remain about the effectiveness of this choice for each country of the [...] Read more.

The EU has planned the phase-out of new vehicles based on internal combustion engines in favor of high-efficiency battery electric vehicles (BEV) by 2035 (Fit for 55 package). However, many doubts remain about the effectiveness of this choice for each country of the Union in terms of CO₂ emissions reduction, as each State is characterized by a different carbon intensity related to the production of electricity needed to manufacture and recharge vehicles. This study seeks to explore the Italian case. To this aim, carbon intensities related to electricity production were calculated considering both the Italian electricity mix production in 2022 and those envisaged in 2035, considering two energy scenarios based on different introductions of renewable energy sources (RES). Afterward, the values obtained were adopted for determining the CO₂ emissions related to the whole production process of battery systems in Italy (emissions from mining and refining, scrap materials, and final assembly included) by comparing some of the most up-to-date Life-Cycle Assessment (LCA) analyses related to the manufacturing cycle of the batteries. Finally, the results were adopted to calculate the starting carbon debit for A, B, C, and M car segments for Mild Hybrid, Full Hybrid, and Full Electric powertrains. At the same time, statistical road fuel/electricity consumption data were collected and overall CO₂ emissions were calculated for the same vehicles adopting a dynamic approach and plotted for a defined distance, so as to determine break-even points with respect to the cumulative (i.e., from battery and road) carbon emissions. The results showed that advantages related to electric vehicles are significant only if a low carbon intensity related to electricity production is reached by means of a very high introduction of RES, thus keeping the door open for innovative hybrid powertrain technologies, if fed with low carbon fuels. Full article

(This article belongs to the Special Issue CO₂ Emissions from Vehicles (Volume II))

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17 pages, 22879 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

The Influence of the Type and Condition of Road Surfaces on the Exhaust Emissions and Fuel Consumption in the Transport of Timber

by Andrzej Ziółkowski, Paweł Fuć, Piotr Lijewski, Maciej Bednarek, Aleks Jagielski, Władysław Kusiak and Joanna Igielska-Kalwat

Energies 2023, 16(21), 7257; https://doi.org/10.3390/en16217257 - 25 Oct 2023

Cited by 5 | Viewed by 2286

Abstract

Owing to society’s growing ecological awareness, researchers and car manufacturers have increasingly been focusing on the adverse impact of transport on the environment. Many scientific publications have been published addressing the influence of a variety of factors on the exhaust emissions generated by [...] Read more.

Owing to society’s growing ecological awareness, researchers and car manufacturers have increasingly been focusing on the adverse impact of transport on the environment. Many scientific publications have been published addressing the influence of a variety of factors on the exhaust emissions generated by vehicles and machinery. In this paper, the authors present an analysis of the exhaust emissions of components such as CO, THC, and NO_x in relation to the type and condition of the road surface. The analysis was performed on a heavy-duty truck designed for carriage of timber. The investigations were carried out with the use of the PEMS equipment (portable emission measurement system) on bitumen-paved roads and unpaved forest access roads. The portable measurement system allowed for an accurate determination of the influence of the road conditions on the operating parameters of the vehicle powertrain and its exhaust emissions. Additionally, the authors present the influence of the type of road surface on the vehicle fuel consumption calculated based on the carbon balance method. Full article

(This article belongs to the Special Issue CO₂ Emissions from Vehicles (Volume II))

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21 pages, 3322 KiB

Open AccessFeature PaperArticle

Application of Machine Learning to Classify the Technical Condition of Marine Engine Injectors Based on Experimental Vibration Displacement Parameters

by Jan Monieta and Lech Kasyk

Energies 2023, 16(19), 6898; https://doi.org/10.3390/en16196898 - 29 Sep 2023

Cited by 2 | Viewed by 1473

Abstract

The article presents the possibility of using machine learning (ML) in artificial intelligence to classify the technical state of marine engine injectors. The technical condition of the internal combustion engine and injection apparatus significantly determines the composition of the outlet gases. For this [...] Read more.

The article presents the possibility of using machine learning (ML) in artificial intelligence to classify the technical state of marine engine injectors. The technical condition of the internal combustion engine and injection apparatus significantly determines the composition of the outlet gases. For this purpose, an analytical package using modern technology assigns experimental test scores to appropriate classes. The graded changes in the value of diagnostic parameters were measured on the injection subsystem bench outside the engine. The influence of the operating conditions of the fuel injection subsystem and injector condition features on the injector needle vibration displacement waveforms was subjected to a neural network (NN) ML process and then tested. Diagnostic parameters analyzed in the amplitude, frequency, and time–frequency domains were subjected after a learning process to recognize simulated various regulatory and technical states of suitability and unfitness with single and complex damage of new and worn injector nozzles. Classification results were satisfactory in testing single damage and multiple changes in technical state characteristics for unfitness states with random wear injectors. Testing quality reached above 90% using selected NNs of Statistica 13.3 and MATLAB R2022a environments. Full article

(This article belongs to the Special Issue CO₂ Emissions from Vehicles (Volume II))

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Review

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31 pages, 3374 KiB

Open AccessReview

Vehicle Emission Models and Traffic Simulators: A Review

by Maksymilian Mądziel

Energies 2023, 16(9), 3941; https://doi.org/10.3390/en16093941 - 7 May 2023

Cited by 47 | Viewed by 10004

Abstract

Accurate estimations and assessments of vehicle emissions can support decision-making processes. Current emission estimation tools involve several calculation methods that provide estimates of the exhaust components that result from driving on urban arterial roads. This is an important consideration, as the emissions generated [...] Read more.

Accurate estimations and assessments of vehicle emissions can support decision-making processes. Current emission estimation tools involve several calculation methods that provide estimates of the exhaust components that result from driving on urban arterial roads. This is an important consideration, as the emissions generated have a direct impact on the health of pedestrians near the roads. In recent years, there has been an increase in the use of emission models, especially in combination with traffic simulator models. This is because it is very difficult to obtain an actual measurement of road emissions for all vehicles travelling along the analysed road section. This paper concerns a review of selected traffic simulations and the estimation of exhaust gas components models. The models presented have been aggregated into a group with respect to their scale of accuracy as micro, meso, and macro. This paper also presents an overview of selected works that combine both traffic and emission models. The presented literature review also emphasises the proper calibration process of simulation models as the most important factor in obtaining accurate estimates. This work also contains information and recommendations on modelling that may be helpful in selecting appropriate emission estimation tools to support decision-making processes for, e.g., road managers. Full article

(This article belongs to the Special Issue CO₂ Emissions from Vehicles (Volume II))

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Other

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14 pages, 1270 KiB

Open AccessBrief Report

On-Board Fuel Consumption Meter Field Testing Results

by Peter Tapak, Michal Kocur and Juraj Matej

Energies 2023, 16(19), 6861; https://doi.org/10.3390/en16196861 - 28 Sep 2023

Cited by 2 | Viewed by 2836

Abstract

This paper aims to investigate and compare the fuel consumption data obtained from on-board fuel consumption meters (OBFCMs) from approximately 1000 vehicles through field testing. Furthermore, this research aims not only to compare the OBFCM readings but also to juxtapose them against the [...] Read more.

This paper aims to investigate and compare the fuel consumption data obtained from on-board fuel consumption meters (OBFCMs) from approximately 1000 vehicles through field testing. Furthermore, this research aims not only to compare the OBFCM readings but also to juxtapose them against the fuel consumption specifications provided by the respective vehicle manufacturers. To collect data, a cost-effective on-board diagnostics (OBD) reader and a user-friendly mobile app were employed, providing an accessible and efficient method for fuel consumption analysis. Field testing involved a diverse range of vehicles, covering various makes, models, and years of production. The OBCFM readings were recorded over a 9-month period, probably capturing a wide range of driving conditions and patterns. In order to ensure the reliability of the OBCFM readings, the fuel consumption measurements obtained from the manufacturers specifications were utilized as a reference benchmark. Preliminary data analysis indicates that there are noticeable variations in the fuel consumption data obtained from the OBCFM and the manufacturer specifications. These differences can be attributed to various factors. The novelty of the presented data lies in using a new feature implemented in EU cars since 2019. The study capitalizes on this feature, allowing for the collection of data from a broad spectrum of vehicles throughout the country under genuine driving conditions. Full article

(This article belongs to the Special Issue CO₂ Emissions from Vehicles (Volume II))

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