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Keywords = real driving emissions test

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24 pages, 2009 KiB  
Article
Artificial Intelligence and Sustainable Practices in Coastal Marinas: A Comparative Study of Monaco and Ibiza
by Florin Ioras and Indrachapa Bandara
Sustainability 2025, 17(16), 7404; https://doi.org/10.3390/su17167404 - 15 Aug 2025
Viewed by 269
Abstract
Artificial intelligence (AI) is playing an increasingly important role in driving sustainable change across coastal and marine environments. Artificial intelligence offers strong support for environmental decision-making by helping to process complex data, anticipate outcomes, and fine-tune day-to-day operations. In busy coastal zones such [...] Read more.
Artificial intelligence (AI) is playing an increasingly important role in driving sustainable change across coastal and marine environments. Artificial intelligence offers strong support for environmental decision-making by helping to process complex data, anticipate outcomes, and fine-tune day-to-day operations. In busy coastal zones such as the Mediterranean where tourism and boating place significant strain on marine ecosystems, AI can be an effective means for marinas to reduce their ecological impact without sacrificing economic viability. This research examines the contribution of artificial intelligence toward the development of environmental sustainability in marina management. It investigates how AI can potentially reconcile economic imperatives with ecological conservation, especially in high-traffic coastal areas. Through a focus on the impact of social and technological context, this study emphasizes the way in which local conditions constrain the design, deployment, and reach of AI systems. The marinas of Ibiza and Monaco are used as a comparative backdrop to depict these dynamics. In Monaco, efforts like the SEA Index® and predictive maintenance for superyachts contributed to a 28% drop in CO2 emissions between 2020 and 2025. In contrast, Ibiza focused on circular economy practices, reaching an 85% landfill diversion rate using solar power, AI-assisted waste systems, and targeted biodiversity conservation initiatives. This research organizes AI tools into three main categories: supervised learning, anomaly detection, and rule-based systems. Their effectiveness is assessed using statistical techniques, including t-test results contextualized with Cohen’s d to convey practical effect sizes. Regression R2 values are interpreted in light of real-world policy relevance, such as thresholds for energy audits or emissions certification. In addition to measuring technical outcomes, this study considers the ethical concerns, the role of local communities, and comparisons to global best practices. The findings highlight how artificial intelligence can meaningfully contribute to environmental conservation while also supporting sustainable economic development in maritime contexts. However, the analysis also reveals ongoing difficulties, particularly in areas such as ethical oversight, regulatory coherence, and the practical replication of successful initiatives across diverse regions. In response, this study outlines several practical steps forward: promoting AI-as-a-Service models to lower adoption barriers, piloting regulatory sandboxes within the EU to test innovative solutions safely, improving access to open-source platforms, and working toward common standards for the stewardship of marine environmental data. Full article
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9 pages, 2222 KiB  
Proceeding Paper
Research and Analysis of the Real-Time Interaction Between Performance and Smoke Emission of a Diesel Vehicle
by Iliyan Damyanov, Rosen Miletiev and Tsvetan Ivanov Valkovski
Eng. Proc. 2025, 100(1), 34; https://doi.org/10.3390/engproc2025100034 - 14 Jul 2025
Viewed by 334
Abstract
In recent decades, environmental requirements for reducing the toxic components emitted from vehicle exhausts have decreased drastically. Technologies for after-treatment of diesel vehicle emissions are being improved continuously in order to meet increasingly stringent regulations. Passenger cars are a significant source of air [...] Read more.
In recent decades, environmental requirements for reducing the toxic components emitted from vehicle exhausts have decreased drastically. Technologies for after-treatment of diesel vehicle emissions are being improved continuously in order to meet increasingly stringent regulations. Passenger cars are a significant source of air pollution, especially in urban areas. The EU has decided to phase out internal combustion engines. Stricter Real Driving Emissions (RDE) testing procedures have also been introduced, aiming to assess the emissions of nitrogen oxides (NOx) and particle number (PN). The present work investigates the interaction between performance and smoke emissions of a diesel vehicle on a pre-established route in an urban environment with an everyday (normal) driving style. The results showed that when the vehicle is technically sound and meets its technical specifications, smoke emissions are within normal limits. Full article
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25 pages, 5231 KiB  
Article
Using AI for Optimizing Packing Design and Reducing Cost in E-Commerce
by Hayder Zghair and Rushi Ganesh Konathala
AI 2025, 6(7), 146; https://doi.org/10.3390/ai6070146 - 4 Jul 2025
Viewed by 1217
Abstract
This research explores how artificial intelligence (AI) can be leveraged to optimize packaging design, reduce operational costs, and enhance sustainability in e-commerce. As packaging waste and shipping inefficiencies grow alongside global online retail demand, traditional methods for determining box size, material use, and [...] Read more.
This research explores how artificial intelligence (AI) can be leveraged to optimize packaging design, reduce operational costs, and enhance sustainability in e-commerce. As packaging waste and shipping inefficiencies grow alongside global online retail demand, traditional methods for determining box size, material use, and logistics planning have become economically and environmentally inadequate. Using a three-phase framework, this study integrates data-driven diagnostics, AI modeling, and real-world validation. In the first phase, a systematic analysis of current packaging inefficiencies was conducted through secondary data, benchmarking, and cost modeling. Findings revealed significant waste caused by over-packaging, suboptimal box-sizing, and poor alignment between product characteristics and logistics strategy. In the second phase, a random forest (RF) machine learning model was developed to predict optimal packaging configurations using key product features: weight, volume, and fragility. This model was supported by AI simulation tools that enabled virtual testing of material performance, space efficiency, and damage risk. Results demonstrated measurable improvements in packaging optimization, cost reduction, and emission mitigation. The third phase validated the AI framework using practical case studies—ranging from a college textbook to a fragile kitchen dish set and a high-volume children’s bicycle. The model successfully recommended right-sized packaging for each product, resulting in reduced material usage, improved shipping density, and enhanced protection. Simulated cost-saving scenarios further confirmed that smart packaging and AI-generated configurations can drive efficiency. The research concludes that AI-based packaging systems offer substantial strategic value, including cost savings, environmental benefits, and alignment with regulatory and consumer expectations—providing scalable, data-driven solutions for e-commerce enterprises such as Amazon and others. Full article
(This article belongs to the Section AI Systems: Theory and Applications)
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20 pages, 3103 KiB  
Article
CO2 Emission and Energy Consumption Estimates in the COPERT Model—Conclusions from Chassis Dynamometer Tests and SANN Artificial Neural Network Models and Their Meaning for Transport Management
by Olga Orynycz, Magdalena Zimakowska-Laskowska and Ewa Kulesza
Energies 2025, 18(13), 3457; https://doi.org/10.3390/en18133457 - 1 Jul 2025
Cited by 1 | Viewed by 382
Abstract
This article aimed to assess the accuracy of the COPERT model in predicting CO2 emissions and energy consumption in real operating conditions, represented by the WLTP homologation tests. Experimental data obtained for a Euro 6 vehicle were compared with the values estimated [...] Read more.
This article aimed to assess the accuracy of the COPERT model in predicting CO2 emissions and energy consumption in real operating conditions, represented by the WLTP homologation tests. Experimental data obtained for a Euro 6 vehicle were compared with the values estimated by the COPERT model, assuming identical speed conditions. MLP and SANN artificial neural networks were also used to create a model describing the complex relationships between emissions, speed, and energy consumption. The results indicate an apparent overestimation of CO2 and energy consumption values by the COPERT model, especially in the low-speed range typical of urban traffic. The minimum energy consumption values were observed at speeds of 50–70 km/h, indicating the existence of an optimal drive system operation zone. The neural models showed high efficiency in predicting the tested parameters—the best results were obtained for the MLP 6-10-1 architecture, whose correlation coefficient exceeded 0.98 in the validation set. The paper highlights the need to calibrate the COPERT model using local experimental data and integrate artificial intelligence methods in modern emission inventories. Full article
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58 pages, 949 KiB  
Review
Excess Pollution from Vehicles—A Review and Outlook on Emission Controls, Testing, Malfunctions, Tampering, and Cheating
by Robin Smit, Alberto Ayala, Gerrit Kadijk and Pascal Buekenhoudt
Sustainability 2025, 17(12), 5362; https://doi.org/10.3390/su17125362 - 10 Jun 2025
Viewed by 1930
Abstract
Although the transition to electric vehicles (EVs) is well underway and expected to continue in global car markets, most vehicles on the world’s roads will be powered by internal combustion engine vehicles (ICEVs) and fossil fuels for the foreseeable future, possibly well past [...] Read more.
Although the transition to electric vehicles (EVs) is well underway and expected to continue in global car markets, most vehicles on the world’s roads will be powered by internal combustion engine vehicles (ICEVs) and fossil fuels for the foreseeable future, possibly well past 2050. Thus, good environmental performance and effective emission control of ICE vehicles will continue to be of paramount importance if the world is to achieve the stated air and climate pollution reduction goals. In this study, we review 228 publications and identify four main issues confronting these objectives: (1) cheating by vehicle manufacturers, (2) tampering by vehicle owners, (3) malfunctioning emission control systems, and (4) inadequate in-service emission programs. With progressively more stringent vehicle emission and fuel quality standards being implemented in all major markets, engine designs and emission control systems have become increasingly complex and sophisticated, creating opportunities for cheating and tampering. This is not a new phenomenon, with the first cases reported in the 1970s and continuing to happen today. Cheating appears not to be restricted to specific manufacturers or vehicle types. Suspicious real-world emissions behavior suggests that the use of defeat devices may be widespread. Defeat devices are primarily a concern with diesel vehicles, where emission control deactivation in real-world driving can lower manufacturing costs, improve fuel economy, reduce engine noise, improve vehicle performance, and extend refill intervals for diesel exhaust fluid, if present. Despite the financial penalties, undesired global attention, damage to brand reputation, a temporary drop in sales and stock value, and forced recalls, cheating may continue. Private vehicle owners resort to tampering to (1) improve performance and fuel efficiency; (2) avoid operating costs, including repairs; (3) increase the resale value of the vehicle (i.e., odometer tampering); or (4) simply to rebel against established norms. Tampering and cheating in the commercial freight sector also mean undercutting law-abiding operators, gaining unfair economic advantage, and posing excess harm to the environment and public health. At the individual vehicle level, the impacts of cheating, tampering, or malfunctioning emission control systems can be substantial. The removal or deactivation of emission control systems increases emissions—for instance, typically 70% (NOx and EGR), a factor of 3 or more (NOx and SCR), and a factor of 25–100 (PM and DPF). Our analysis shows significant uncertainty and (geographic) variability regarding the occurrence of cheating and tampering by vehicle owners. The available evidence suggests that fleet-wide impacts of cheating and tampering on emissions are undeniable, substantial, and cannot be ignored. The presence of a relatively small fraction of high-emitters, due to either cheating, tampering, or malfunctioning, causes excess pollution that must be tackled by environmental authorities around the world, in particular in emerging economies, where millions of used ICE vehicles from the US and EU end up. Modernized in-service emission programs designed to efficiently identify and fix large faults are needed to ensure that the benefits of modern vehicle technologies are not lost. Effective programs should address malfunctions, engine problems, incorrect repairs, a lack of servicing and maintenance, poorly retrofitted fuel and emission control systems, the use of improper or low-quality fuels and tampering. Periodic Test and Repair (PTR) is a common in-service program. We estimate that PTR generally reduces emissions by 11% (8–14%), 11% (7–15%), and 4% (−1–10%) for carbon monoxide (CO), hydrocarbons (HC), and oxides of nitrogen (NOx), respectively. This is based on the grand mean effect and the associated 95% confidence interval. PTR effectiveness could be significantly higher, but we find that it critically depends on various design factors, including (1) comprehensive fleet coverage, (2) a suitable test procedure, (3) compliance and enforcement, (4) proper technician training, (5) quality control and quality assurance, (6) periodic program evaluation, and (7) minimization of waivers and exemptions. Now that both particulate matter (PM, i.e., DPF) and NOx (i.e., SCR) emission controls are common in all modern new diesel vehicles, and commonly the focus of cheating and tampering, robust measurement approaches for assessing in-use emissions performance are urgently needed to modernize PTR programs. To increase (cost) effectiveness, a modern approach could include screening methods, such as remote sensing and plume chasing. We conclude this study with recommendations and suggestions for future improvements and research, listing a range of potential solutions for the issues identified in new and in-service vehicles. Full article
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42 pages, 473 KiB  
Review
Non-Destructive Testing and Evaluation of Hybrid and Advanced Structures: A Comprehensive Review of Methods, Applications, and Emerging Trends
by Farima Abdollahi-Mamoudan, Clemente Ibarra-Castanedo and Xavier P. V. Maldague
Sensors 2025, 25(12), 3635; https://doi.org/10.3390/s25123635 - 10 Jun 2025
Cited by 1 | Viewed by 1755
Abstract
Non-destructive testing (NDT) and non-destructive evaluation (NDE) are essential tools for ensuring the structural integrity, safety, and reliability of critical systems across the aerospace, civil infrastructure, energy, and advanced manufacturing sectors. As engineered materials evolve into increasingly complex architectures such as fiber-reinforced polymers, [...] Read more.
Non-destructive testing (NDT) and non-destructive evaluation (NDE) are essential tools for ensuring the structural integrity, safety, and reliability of critical systems across the aerospace, civil infrastructure, energy, and advanced manufacturing sectors. As engineered materials evolve into increasingly complex architectures such as fiber-reinforced polymers, fiber–metal laminates, sandwich composites, and functionally graded materials, traditional NDT techniques face growing limitations in sensitivity, adaptability, and diagnostic reliability. This comprehensive review presents a multi-dimensional classification of NDT/NDE methods, structured by physical principles, functional objectives, and application domains. Special attention is given to hybrid and multi-material systems, which exhibit anisotropic behavior, interfacial complexity, and heterogeneous defect mechanisms that challenge conventional inspection. Alongside established techniques like ultrasonic testing, radiography, infrared thermography, and acoustic emission, the review explores emerging modalities such as capacitive sensing, electromechanical impedance, and AI-enhanced platforms that are driving the future of intelligent diagnostics. By synthesizing insights from the recent literature, the paper evaluates comparative performance metrics (e.g., sensitivity, resolution, adaptability); highlights integration strategies for embedded monitoring and multimodal sensing systems; and addresses challenges related to environmental sensitivity, data interpretation, and standardization. The transformative role of NDE 4.0 in enabling automated, real-time, and predictive structural assessment is also discussed. This review serves as a valuable reference for researchers and practitioners developing next-generation NDT/NDE solutions for hybrid and high-performance structures. Full article
(This article belongs to the Special Issue Digital Image Processing and Sensing Technologies—Second Edition)
22 pages, 6640 KiB  
Article
Dynamic Closed-Loop Validation of a Hardware-in-the-Loop Testbench for Parallel Hybrid Electric Vehicles
by Marc Timur Düzgün, Christian Heusch, Sascha Krysmon, Christian Dönitz, Sung-Yong Lee, Jakob Andert and Stefan Pischinger
World Electr. Veh. J. 2025, 16(5), 273; https://doi.org/10.3390/wevj16050273 - 14 May 2025
Viewed by 643
Abstract
The complexity and shortening of development cycles in the automotive industry, particularly with the rise in hybrid electric vehicle sales, increases the need for efficient calibration and testing methods. Virtualization using hardware-in-the-loop testbenches has the potential to counteract these trends, specifically for the [...] Read more.
The complexity and shortening of development cycles in the automotive industry, particularly with the rise in hybrid electric vehicle sales, increases the need for efficient calibration and testing methods. Virtualization using hardware-in-the-loop testbenches has the potential to counteract these trends, specifically for the calibration of hybrid operating strategies. This paper presents a dynamic closed-loop validation of a hardware-in-the-loop testbench designed for the virtual calibration of hybrid operating strategies for a plug-in hybrid electric vehicle. Requirements regarding the hardware-in-the-loop testbench accuracy are defined based on the investigated use case. From this, a dedicated hardware-in-the-loop testbench setup is derived, including an electrical setup as well as a plant simulation model. The model is then operated in a closed loop with a series production hybrid control unit. The closed-loop validation results demonstrate that the chassis simulation reproduces driving resistance closely aligning with the reference data. The driver model follows target speed profiles within acceptable limits, achieving an R2 = 0.9993, comparable to the R2 reached by trained human drivers. The transmission model replicates the gear ratios, maintaining rotational speed deviations below 30 min−1. Furthermore, the shift strategy is implemented in a virtual control unit, resulting in a gear selection comparable to reference measurements. The energy flow simulation in the complete powertrain achieves high accuracy. Deviations in the high-voltage battery state of charge remain below 50 Wh in a WLTC charge-sustaining drive cycle and are thus within the acceptable error margin. The net energy change criterion is satisfied with the hardware-in-the-loop testbench, achieving a net energy change of 0.202%, closely matching the reference measurement of 0.159%. Maximum deviations in cumulative high-voltage battery energy are proven to be below 10% in both the charging and discharging directions. Fuel consumption and CO2 emissions are modeled with deviations below 3%, validating the simulation’s representation of vehicle efficiency. Real-time capability is achieved under all investigated operating conditions and test scenarios. The testbench achieves a real-time factor of at least 1.104, ensuring execution within the hard real-time criterion. In conclusion, the closed-loop validation confirms that the developed hardware-in-the-loop testbench satisfies all predefined requirements, accurately simulating the behavior of the reference vehicle. Full article
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13 pages, 16522 KiB  
Article
Advancing Tyre and Road Wear Particle Measurements: Balancing Laboratory Conditions and Real-World Relevance
by Jens Wahlström, Yezhe Lyu, Joacim Lundberg, Joakim Pagels and Rikard Hjelm
Atmosphere 2025, 16(5), 588; https://doi.org/10.3390/atmos16050588 - 14 May 2025
Cited by 1 | Viewed by 605
Abstract
Non-exhaust emissions from the wear of brakes, tyres, and roads have become an increasing concern in recent years, already surpassing exhaust emissions by mass in many countries. However, there is a lack of studies in the scientific literature on test methods that include [...] Read more.
Non-exhaust emissions from the wear of brakes, tyres, and roads have become an increasing concern in recent years, already surpassing exhaust emissions by mass in many countries. However, there is a lack of studies in the scientific literature on test methods that include both real tyre and road materials. This is crucial for accurately replicating the tribological mechanisms and resulting emissions that occur during real-world driving. This study therefore employs a scaled experimental approach to investigate the influence of representative urban load and sliding speed conditions on tyre and road wear particle generation using commercial tyre and road materials. Friction, wear, and emissions were analysed using a pin-on-disc tribometer within a controlled environment, enabling the measurement of both airborne and non-airborne wear particles. The results demonstrate that under moderate test conditions, airborne tyre and road wear particle concentrations remained almost zero, with reasonable coefficients of friction and estimated non-airborne emission factors. However, under harsher contact conditions, the coefficients of friction, airborne tyre and road wear concentrations and estimated emission factors increased significantly, leading to excessive material detachment from both the tyre and road surface. These extreme wear conditions are not representative of real-world tyre–road interactions, emphasising the sensitivity and necessity of using more realistic test conditions in future studies. Full article
(This article belongs to the Section Air Quality)
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10 pages, 4573 KiB  
Article
Experimental Study on the Effect of Environmental Factors on the Real Driving Emission (RDE) Test
by Hao Yu, Yan Su, Lei Cao, Bo Shen, Yulin Zhang and Benyou Wang
Energies 2025, 18(9), 2253; https://doi.org/10.3390/en18092253 - 28 Apr 2025
Viewed by 400
Abstract
The real driving emissions of gasoline and diesel vehicles are significantly influenced by altitude, temperature, and starting conditions. In this study, the real driving emissions (RDEs) of gasoline and diesel vehicles compliant with China V standards were investigated under various conditions. The adaptability [...] Read more.
The real driving emissions of gasoline and diesel vehicles are significantly influenced by altitude, temperature, and starting conditions. In this study, the real driving emissions (RDEs) of gasoline and diesel vehicles compliant with China V standards were investigated under various conditions. The adaptability of RDE testing in China was evaluated by analyzing vehicle emissions at different altitudes, ambient temperatures, and starting conditions. The results show that, with increasing altitude, CO, NOx, and PN emissions generally exhibit a downward trend, particularly for gasoline vehicles, whose conformity factors remain well below the China VI limit. However, for China V diesel vehicles relying solely on EGR technology, NOx emissions significantly exceed China VI standards, indicating that EGR alone is insufficient to meet regulatory requirements. Temperature variations have little effect on the emissions of China V PFI gasoline vehicles, while diesel vehicles continue to exhibit excessive NOx emissions under varying temperatures. Although the cold-start phase generates substantial pollutant emissions, the EMROAD evaluation method excludes this phase, resulting in limited differences between cold- and hot-start emission results. Nevertheless, the inclusion of cold-start emissions should be considered in future RDE assessments. Full article
(This article belongs to the Section I2: Energy and Combustion Science)
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24 pages, 2970 KiB  
Article
Real Energy Efficiency of Road Vehicles
by Óscar S. Serrano-Guevara, José I. Huertas and Michael Giraldo
Energies 2025, 18(8), 1933; https://doi.org/10.3390/en18081933 - 10 Apr 2025
Viewed by 811
Abstract
There is an urgent need for a method of evaluating the real energy performance of vehicles that eliminates the effects of external conditions (topography, altitude, and road conditions) and human factors (driving styles), especially in the case of heavy-duty vehicles. Governmental authorities require [...] Read more.
There is an urgent need for a method of evaluating the real energy performance of vehicles that eliminates the effects of external conditions (topography, altitude, and road conditions) and human factors (driving styles), especially in the case of heavy-duty vehicles. Governmental authorities require results on the energy performance of vehicles to develop strategies that result in reductions in greenhouse gas emissions, while fleet managers require results regarding the energy efficiency of existing vehicle technologies to select the technologies that minimize energy consumption and, therefore, operational costs. Aiming to address this need, we propose a method for evaluating the global energy efficiency of road vehicles by monitoring at 1 Hz the operational variables of a vehicle under normal conditions of use for a long time. The variables monitored are engine RPM and vehicle location, speed, payload, and energy consumption. This method was verified using 49 vehicles, representing 23 vehicle technologies. These vehicles varied in size (light duty and heavy duty), application (cars, buses, and freight), energy sources (gasoline, diesel, and electric), and operational conditions (Chile, Ecuador, Colombia, and México). Testing was conducted across various altitudes (0–3600 masl) and topographies (flat and mountainous regions). The results showed that the energy efficiencies for gasoline-fueled light-duty vehicles ranged from 17 to 30%, those for diesel-fueled heavy-duty vehicles ranged from 25 to 42%, and those for electric heavy-duty vehicles (HDVs) ranged from 70 to 80%. Full article
(This article belongs to the Section B1: Energy and Climate Change)
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20 pages, 6569 KiB  
Article
Changing Fuel Consumption Data in Official Vehicle Documents—Case Study in the Slovak Republic
by Branislav Šarkan, Michal Loman, Jacek Caban, Arkadiusz Malek, Michal Richtář and Mária Stopková
Vehicles 2025, 7(1), 27; https://doi.org/10.3390/vehicles7010027 - 16 Mar 2025
Viewed by 1039
Abstract
This article deals with the technical and official possibilities of changing the official data on vehicle fuel consumption in the Slovak Republic. This case study analyzes various methods of measuring fuel consumption, including the use of a fuel flowmeter, OBD devices and calculation [...] Read more.
This article deals with the technical and official possibilities of changing the official data on vehicle fuel consumption in the Slovak Republic. This case study analyzes various methods of measuring fuel consumption, including the use of a fuel flowmeter, OBD devices and calculation based on emission tests. The tests took place in laboratory conditions using the roller dynamometer on the Kia Ceed mildhybrid vehicle. Based on the Real Drive Emission requirements, five 1.5 h cycles were repeated in urban, suburban and highway conditions. Using multi-criteria analysis, the methods used to measure fuel consumption are evaluated from the point of view of efficiency, accuracy, and economy. This study contains a real view of the performance of these exams in the conditions of the Slovak Republic. The fuel consumption measured by the OBD device compared to the volumetric flowmeters was at a relative difference of −4.94%. The fuel consumption calculated through exhaust gas emissions was +2.83% compared to the volumetric flowmeters. Full article
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29 pages, 13513 KiB  
Article
A Physical-Based Electro-Thermal Model for a Prismatic LFP Lithium-Ion Cell Thermal Analysis
by Alberto Broatch, Pablo Olmeda, Xandra Margot and Luca Agizza
Energies 2025, 18(5), 1281; https://doi.org/10.3390/en18051281 - 5 Mar 2025
Viewed by 1026
Abstract
This article presents an electro-thermal model of a prismatic lithium-ion cell, integrating physics-based models for capacity and resistance estimation. A 100 Ah prismatic cell with LFP-based chemistry was selected for analysis. A comprehensive experimental campaign was conducted to determine electrical parameters and assess [...] Read more.
This article presents an electro-thermal model of a prismatic lithium-ion cell, integrating physics-based models for capacity and resistance estimation. A 100 Ah prismatic cell with LFP-based chemistry was selected for analysis. A comprehensive experimental campaign was conducted to determine electrical parameters and assess their dependencies on temperature and C-rate. Capacity tests were conducted to characterize the cell’s capacity, while an OCV test was used to evaluate its open circuit voltage. Additionally, Hybrid Pulse Power Characterization tests were performed to determine the cell’s internal resistive-capacitive parameters. To describe the temperature dependence of the cell’s capacity, a physics-based Galushkin model is proposed. An Arrhenius model is used to represent the temperature dependence of resistances. The integration of physics-based models significantly reduces the required test matrix for model calibration, as temperature-dependent behavior is effectively predicted. The electrical response is represented using a first-order equivalent circuit model, while thermal behavior is described through a nodal network thermal model. Model validation was conducted under real driving emissions cycles at various temperatures, achieving a root mean square error below 1% in all cases. Furthermore, a comparative study of different cell cooling strategies is presented to identify the most effective approach for temperature control during ultra-fast charging. The results show that side cooling achieves a 36% lower temperature at the end of the charging process compared to base cooling. Full article
(This article belongs to the Section J: Thermal Management)
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19 pages, 5909 KiB  
Article
Driving Sustainability: Analyzing Eco-Driving Efficiency Across Urban and Interurban Roads with Electric and Combustion Vehicles
by Tasneem Miqdady, Juan Benavente, Juan Francisco Coloma and Marta García
World Electr. Veh. J. 2025, 16(3), 143; https://doi.org/10.3390/wevj16030143 - 3 Mar 2025
Cited by 1 | Viewed by 1724
Abstract
Eco-driving is a key strategy for reducing energy consumption and emissions in electric vehicles (EVs) and internal combustion engine (ICE) vehicles. However, research gaps remain regarding its effectiveness across different driving environments, vehicle types, transmission systems, and contexts. This research evaluates eco-driving efficiency [...] Read more.
Eco-driving is a key strategy for reducing energy consumption and emissions in electric vehicles (EVs) and internal combustion engine (ICE) vehicles. However, research gaps remain regarding its effectiveness across different driving environments, vehicle types, transmission systems, and contexts. This research evaluates eco-driving efficiency in urban and interurban settings, comparing small (Caceres) and large (Madrid) cities and assessing EVs ICE with direct, manual, and automatic transmissions. The authors conducted a large-scale driving experiment in Spain, with over 500 test runs across different road types. Results in the large city show that eco-driving reduces energy consumption by 30.4% in EVs on urban roads, benefiting from regenerative braking, compared to 10.75% in manual ICE vehicles. Automatic ICE vehicles also performed well, with 29.55% savings in local streets. In interurban settings, manual ICE vehicles achieved the highest savings (20.31%), while EVs showed more minor improvements (11.79%) due to already optimized efficiency at steady speeds. The small city showed higher savings due to smoother traffic flow, while single-speed transmissions in EVs enhanced efficiency across conditions. These findings provide valuable insights for optimizing eco-driving strategies and vehicle design. Future research should explore AI-driven eco-driving applications and real-time optimization to improve sustainable mobility. Full article
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21 pages, 3286 KiB  
Article
A Concept for On-Road Inter-Laboratory Correlation Exercises with Portable Emission Measurement Systems (PEMS)
by Maria Trikka, Sara Valentini, Giulio Cotogno, Pierluigi Canevari, Anastasios Melas, Michaël Clairotte, Marcos Otura García and Barouch Giechaskiel
Processes 2025, 13(3), 702; https://doi.org/10.3390/pr13030702 - 28 Feb 2025
Cited by 1 | Viewed by 786
Abstract
Portable emission measurement systems (PEMS) are used onboard vehicles to determine the on-road real driving emissions of the vehicles for research or regulatory purposes. The assessment of a PEMS is carried out in a laboratory comparing it with laboratory grade systems (i.e., validation [...] Read more.
Portable emission measurement systems (PEMS) are used onboard vehicles to determine the on-road real driving emissions of the vehicles for research or regulatory purposes. The assessment of a PEMS is carried out in a laboratory comparing it with laboratory grade systems (i.e., validation test). This procedure is described in the European Commission Regulation (EU) 2017/1151 and there are limits that must be respected (permissible tolerances). A few inter-laboratory studies evaluated PEMS in the laboratories of different institutes. However, there are no on-road inter-laboratory studies of PEMS because there is no reference instrument available and the source (i.e., emissions of the vehicle) fluctuates significantly due to the variation of the trip characteristics, driver behavior, and environmental conditions, making meaningful evaluation challenging. Here, we present a concept of how such inter-laboratory studies could take place. The concept is that a ‘reference PEMS’ is evaluated first in the laboratory of one of the participating institutes. Then, the ‘reference PEMS’, with a reference vehicle (optionally) is sent to the other institutes to compare their ‘test PEMS’ with the ‘reference PEMS’ on-road. The difference (absolute or relative) of the two PEMS, corrected for any ‘bias’ of the ‘reference PEMS’, is used for the assessment of the ‘test PEMS’ (i.e., comparison with the permissible tolerances) or any statistical analysis (e.g., z-scores). Ideally, the selected reference PEMS should have negligible ‘bias’ (e.g., due to calibration uncertainties, drift), and for this reason, a thorough investigation at the beginning of the exercise is highly recommended. A statistical analysis can be made to confirm if there is bias. Using the differences (absolute or relative) of PEMS, the source (vehicle emissions) variability is cancelled out. The differences can then be compared with the permissible tolerances of the regulation, but up to 40% higher deviations should still be acceptable. We demonstrate the concept with experiments in our institute. Full article
(This article belongs to the Special Issue Engine Combustion and Emissions)
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22 pages, 3233 KiB  
Article
Emission Characteristics of Hydrogen-Enriched Gasoline Under Dynamic Driving Conditions
by Alfredas Rimkus, Edward Kozłowski, Tadas Vipartas, Saugirdas Pukalskas, Piotr Wiśniowski and Jonas Matijošius
Energies 2025, 18(5), 1190; https://doi.org/10.3390/en18051190 - 28 Feb 2025
Cited by 4 | Viewed by 909
Abstract
This paper investigates the emission characteristics of hydrogen-enriched gasoline (95G5H2) under dynamic driving situations in order to fulfill the growing need for cleaner and more efficient automobile fuels. This study aimed to investigate the impact of hydrogen addition on pollutant-specific emissions, [...] Read more.
This paper investigates the emission characteristics of hydrogen-enriched gasoline (95G5H2) under dynamic driving situations in order to fulfill the growing need for cleaner and more efficient automobile fuels. This study aimed to investigate the impact of hydrogen addition on pollutant-specific emissions, including CO, CO2, HC, and NOx, using a Nissan Qashqai that ran on both pure gasoline (100G) and 95G5H2. Emission statistics were obtained by computer simulations of the Worldwide Harmonized Light Vehicles Test Cycle (WLTC) applied using AVL CRUISE software. The paper presents a method of comparing the characteristics of pollutants emitted by the combustion engine and comparing the pollutants emitted when powered by regular fuel and fuel with hydrogen. The tests were performed in real conditions, and the presented method shows the amount of pollutants emitted when the vehicle is directly in motion, which allows for effective comparison of the amount of pollutants emitted for different fuels. 95G5H2 sharply reduces CO-, CO2-, and HC-specific emissions by 22.19%, 14.55%, and 35.46%, respectively, when compared to 100G. However, NOx-specific emissions increased by 20.17%, suggesting a compromise between higher combustion efficiency and higher burning temperatures. The study shows that 95G5H2 fuel performs better in urban driving cycles, including plenty of acceleration and deceleration, which usually results in incomplete combustion. Although additional refinement is needed to cut NOx-specific emissions, the results demonstrate that hydrogen-enriched fuels have considerable potential to lower vehicle-specific emissions. The significant conclusions of the study on the advantages of hydrogen-enriched fuels, both practically and environmentally, will help in the future development of environmentally friendly transportation solutions. Full article
(This article belongs to the Special Issue Advancements in Hydrogen Application for Internal Combustion Engines)
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