Search Results (74)

Classification of vehicle engines using the chemical composition of the exhaust from these engines can be used to identify the engine’s design and verify compliance with environmental regulations through the vehicle’s emissions. This paper describes a method to identify the type of vehicles using machine learning (ML), where low-cost MQ series sensors measure the gases and particle emissions from a vehicle exhaust system, while simultaneously collecting and measuring the vehicle’s temperature and humidity levels. A custom-designed multi-sensor exhaust sensing module is employed to capture real-time exhaust emissions prior to entering the atmosphere. Exhaust samples are collected from vehicles representing three major engine categories: petrol, diesel, and compressed natural gas (CNG). In addition, fresh air samples are collected as a baseline environmental reference for comparison. All exhaust measurements are collected under controlled and consistent engine operating conditions to ensure comparable emission profiling across vehicle classes. To ensure consistent combustion-based emission profiling, this study focuses on conventional fuel-powered vehicles. MQ-series gas sensors are sensitive to combustion by-products emitted during engine operation, such as carbon monoxide (CO), hydrocarbons (HC), while also exhibiting cross-sensitivity to other gaseous components present in exhaust mixtures. Nevertheless, the proposed system performs pattern-based classification using relative sensor response signatures. Standardization of data is achieved through z-score normalization. The best models developed (based on three separate experimental designs) are trained and validated using six supervised machine learning algorithms such as Logistic Regression, Support Vector Machine (RBF), k-Nearest Neighbors, Random Forest, Gradient Boosting Decision Tree, and XGBoost and are compared against one another. Evaluation of the tested algorithms using various evaluation metrics demonstrated that ensemble models outperformed all other algorithms, achieving the highest accuracy of 99.5%. Furthermore, noise analysis confirms that the proposed solution maintains high classification accuracy (more than 89%) even under substantial sensor perturbations mimicking the real-world deployment. The solution proposed below illustrates how using gas sensors and advanced algorithms can provide accurate exhaust identification and identify engines in real-time. Full article

The transportation sector, a major source of urban air pollution and CO₂ emissions, is the focus of extensive research aimed at developing cleaner and more efficient technologies. In this context, hydrogen–methane blends (HCNG) represent a promising alternative fuel, combining the zero-carbon combustion potential of hydrogen with the availability and cleaner profile of methane. This solution can be implemented in existing internal combustion engines, enabling a technically and economically feasible transition toward more sustainable mobility. This work investigates the use of an HCNG blend in a bus originally powered by natural gas, focusing on pollutant emissions under real driving conditions representative of typical urban operation. Measurements were performed using a Portable Emission Measurement System installed on-board. Two test campaigns were carried out: the first using methane, and the second using an HCNG blend (15% H₂, 85% CH₄ by volume), over identical urban and extra-urban routes with varying drivers and traffic conditions. Results show a reduction in CO₂ emissions with HCNG, along with a more significant decrease in CO, HC, and PN emissions, while NOx exhibited a slight increase due to unchanged engine calibration. The analysis also includes the RPA index, which is related to fuel energy release characteristics, indicating improved vehicle responsiveness and torque delivery with HCNG. Full article

This study numerically investigates the conversion of a Heavy-Duty (HD) Spark-Ignition (SI) Compressed Natural Gas (CNG) engine to operate with hydrogen-rich syngas produced from waste plastic pyrolysis. The engine was modeled with a one-dimensional simulation tool. Fuel-specific properties were included through a tabulated Laminar Flame Speed (LFS) approach, and knock occurrence was predicted with a Tabulated Kinetic of Ignition (TKI) model. Full-load simulations revealed that direct substitution of CNG with syngas leads to abnormal combustion. With adjusted values of Spark Advance (SA) to avoid knock, syngas operation resulted in average reductions of approximately 15% in brake torque and 6% in total efficiency compared to the CNG baseline. Parametric analyses showed that Late Intake Valve Closing (LIVC) provides no benefits, whereas increasing the Compression Ratio (CR) partially recovers performance and efficiency, with knock being a limiting factor. Lastly, a complete engine map of the converted configuration was generated, reporting Brake-Specific Fuel Consumption (BSFC) and emissions. Overall, the study demonstrates that HD SI engines can be operated on hydrogen-rich syngas at the cost of moderate performance penalties. Moreover, it provides a robust modeling framework to support system-level and well-to-wheel assessments of syngas-based powertrains. Full article

Heavy-duty vehicles dominate global freight movement and primarily rely on fossil-derived diesel fuel. However, fluctuations in crude oil prices and evolving emissions regulations have prompted interest in alternative powertrains to enhance fleet energy resiliency. This study paired real-world operational data from a large commercial fleet with high-fidelity vehicle models to evaluate the potential for replacing diesel internal combustion engine (ICE) trucks with alternative powertrain architectures. The baseline vehicle for this analysis is a diesel-powered ICE truck. Alternatives include ICE trucks fueled by bio- and renewable diesel, compressed natural gas (CNG) or hydrogen (H₂), as well as plug-in hybrid (PHEV), fuel cell electric (FCEV), and battery electric vehicles (BEV). While most alternative powertrains resulted in some payload capacity loss, the overall fleetwide impact was negligible due to underutilized payload capacity for the specific fleet considered in this study. For sleeper cab trucks, CNG-powered trucks achieved the highest replacement potential, covering 85% of the fleet. In contrast, H₂ and BEV architectures could replace fewer than 10% and 1% of trucks, respectively. Day cab trucks, with shorter daily routes, showed higher replacement potential: 98% for CNG, 78% for H₂, and 34% for BEVs. However, achieving full fleet replacement would still require significant operational changes such as route reassignment and enroute refueling, along with considerable improvements to onboard energy storage capacity. Additionally, the higher total cost of ownership (TCO) for alternative powertrains remains a key challenge. This study also evaluated lifecycle impacts across various fuel sources, both fossil and bio-derived. Bio-derived synthetic diesel fuels emerged as a practical option for diesel displacement without disrupting operations. Conversely, H₂ and electrified powertrains provide limited lifecycle impacts under the current energy scenario. This analysis highlights the complexity of replacing diesel ICE trucks with admissible alternatives while balancing fleet resiliency, operational demands, and emissions goals. These results reflect a US-based fleet’s duty cycles, payloads, GVWR allowances, and an assumption of depot-only refueling/recharging. Applicability to other fleets and regions may differ based on differing routing practices or technical features such as battery swapping. Full article

Additive manufacturing has been adopted in several industries including the medical field to develop new personalised medical implants including tissue engineering scaffolds. Custom patient-specific scaffolds can be additively manufactured to speed up the wound healing process. The aim of this study was to design, fabricate, and evaluate a range of materials and scaffold architectures for 3D-printed wound dressings intended for soft tissue applications, such as skin repair. Multiple biocompatible polymers, including polylactic acid (PLA), polyvinyl alcohol (PVA), butenediol vinyl alcohol copolymer (BVOH), and polycaprolactone (PCL), were fabricated using a material extrusion additive manufacturing technique. Eight scaffolds, five with circular designs (knee meniscus angled (KMA), knee meniscus stacked (KMS), circle dense centre (CDC), circle dense edge (CDE), and circle no gradient (CNG)), and three square scaffolds (square dense centre (SDC), square dense edge (SDE), and square no gradient (SNG), with varying pore widths and gradient distributions) were designed using an open-source custom toolpath generator to enable precise control over scaffold architecture. An in vitro degradation study in phosphate-buffered saline demonstrated that PLA exhibited the greatest material stability, indicating minimal degradation under the tested conditions. In comparison, PVA showed improved performance relative to BVOH, as it was capable of absorbing a greater volume of exudate fluid and remained structurally intact for a longer duration, requiring up to 60 min to fully dissolve. Tensile testing of PLA scaffolds further revealed that designs with increased porosity towards the centre exhibited superior mechanical performance. The strongest scaffold design exhibited a Young’s modulus of 1060.67 ± 16.22 MPa and withstood a maximum tensile stress of 21.89 ± 0.81 MPa before fracture, while maintaining a porosity of approximately 52.37%. This demonstrates a favourable balance between mechanical strength and porosity that mimics key properties of engineered tissues such as the meniscus. Overall, these findings highlight the potential of 3D-printed, patient-specific scaffolds to enhance the effectiveness and customisation of tissue engineering treatments, such as meniscus repair, offering a promising approach for next-generation regenerative applications. Full article

This study provides a comparison between the impact of two gas fuels, compressed natural gas (CNG) and hydrogen (H₂), on the exhaust emissions of a single-cylinder diesel engine operating in dual-fuel mode. The analysis is conducted with a constant and maximum achieved gas-to-total-fuel ratio (K = 20% and K = max) under varying load conditions, specifically at an engine speed of 2000 min⁻¹ and brake mean effective pressures ranging from 0.2 to 0.43 MPa. The results reveal that H₂ significantly improves the engine’s emissions profile compared to CNG. When H₂ is used as the secondary fuel, reductions in soot, carbon monoxide (CO), carbon dioxide (CO₂), and unburned hydrocarbons (CHs) are more pronounced. However, under certain load conditions, nitrogen oxide (NO_x) emissions are higher with H₂ than with CNG and can even surpass those observed during diesel-only operation. These findings suggest that while H₂ demonstrates superior overall emissions performance, its impact on NO_x emissions under specific conditions requires further optimization to maximize environmental benefits. Full article

Hybrid electric vehicles (HEVs) frequently cycle their internal combustion engines (ICE), potentially cooling the three-way catalyst (TWC). This challenges the use of compressed natural gas (CNG), as methane (CH₄) requires high temperatures for TWC oxidation. This study experimentally investigates the performance, engine-out emissions (CO, NO_x, CH₄, NMHC, CO₂), and catalyst temperatures of a Toyota RAV4 hybrid vehicle on gasoline (G), CNG, and dual fuel (MIX) during the WLTC. Engine-out emissions were measured upstream of the TWC. Results showed similar engine work output (~17.8 kWh/100 km), while CNG significantly reduced fuel mass consumption (−18.7%) and CO₂ emissions (−27.5%) compared to gasoline, driven by both its higher LHV and higher average BTE. CO (−32.3%) and NO_x (−34.0%) emissions were lower with CNG, linked to leaner operation and significantly retarded ignition timing for NO_x control. However, CH₄ emissions drastically increased with CNG. This study reveals a synergy between the same retarded ignition timing strategy used to successfully control engine-out NO_x (−34.0%) and created a positive secondary effect, raising pre-TWC temperatures by 4.5%. Higher thermal condition is essential for the aftertreatment of chemically stable methane, highlighting a direct link between the engine’s NO_x control logic and the potential to mitigate methane slip. Full article

Universities play a critical role in shaping sustainable mobility strategies, especially in urban contexts where the institutional transport system can influence environmental and social outcomes. This study integrates Environmental and Social Life Cycle Assessment (E-LCA and S-LCA) to evaluate the current university transport system from internal combustion engines, diesel, and compressed natural gas (CNG), focusing on the operation and maintenance phases. Also, it compares seven scenarios, including electric, renewable sources, and biodiesel technologies. Environmental impacts were assessed using the ReCiPe 2016 midpoint method, which considers the following impact categories: Global Warming Potential (GWP); Ozone Formation, Human Health (OfHh); Ozone Formation, Terrestrial Ecosystem (OfTe); Terrestrial Acidification (TA); and Fine Particulate Matter Formation (FPmf). The sensitivity analysis explores scenarios to assess the effects of technological transitions and alternative energy sources on the environmental performance. Social impacts are assessed through a Social Performance Index (SPI) and Aggregated Social Performance Index (ASPI), which aggregates indicators such as safety, travel cost, punctuality, accessibility, and inclusive design. Accessibility emerged as the lowest indicator (ranging from 0.61 to 0.67), highlighting opportunities for improvement. Our findings support decision-making processes for integrating sustainable transport strategies into a University Mobility Plan, emphasizing the importance of combining technical performance with social inclusivity. Full article

This study investigates the performance and combustion behavior of a spark ignition engine retrofitted to operate on compressed natural gas (CNG), with a focus on a newly developed stratified charge pre-chamber design. The engine was modified to include an auxiliary intake valve that enables partial enrichment of the pre-chamber mixture without the need for a dedicated fuel injector. This hybrid approach combines the mechanical simplicity of passive systems with the enhanced combustion control of active pre-chambers. Both experimental tests and computational fluid dynamics (CFD) analyses were carried out under partial load conditions (8 Nm) and engine speeds ranging from 900 to 1700 rpm. The results demonstrate improvements in indicated mean effective pressure (IMEP), combustion stability, and flame propagation speed—particularly at lower engine speeds where stratified combustion effects are more pronounced. However, increasing engine speed resulted in reduced volumetric efficiency and elevated exhaust temperatures, indicating potential for further optimization via turbocharging or advanced scavenging techniques. Overall, the findings validate the effectiveness of the proposed design in enhancing thermal efficiency and ignition stability in CNG-fueled engines, especially under urban driving conditions. Full article

Compressed natural gas (CNG) in dual-fuel diesel engines offers environmental benefits but significantly increases unburned methane (CH₄) emissions, especially at low engine loads. This study investigates the effectiveness of different catalytic converters in methane oxidation under transient test conditions (WHTC). Three types of catalysts (Pt-, Rh-, and Pd-based) were evaluated using a combined approach of empirical engine bench tests and mathematical modelling. The results showed that, under actual exhaust gas temperature conditions, the average methane conversion efficiencies were 3.7% for Pt, 17.7% for Rh, and 31.3% for Pd catalysts. Increasing the exhaust gas temperature by 50% improved the conversion efficiencies to 7.3%, 51.8%, and 69.2%, respectively. Despite this enhancement, none of the catalysts reached the 90% efficiency threshold required to increase the CNG content of the fuel beyond 6% without exceeding emission limits. The results highlight the need for high-activity Pd-based catalysts and optimised thermal management strategies to enable the broader adoption of dual-fuel engines, while complying with Euro VI standards. Full article

This study develops and validates a three-dimensional CFD model for a 12 L large-bore active-type pre-chamber spark-ignition (PCSI) engine fueled by natural gas. The model incorporates an advanced Extended Coherent Flamelet Model (ECFM-3Z) with a tuned stretch factor to capture complex turbulence–flame interactions, flame propagation, and pollutant formation under ultra-lean conditions. By systematically varying pre-chamber geometries—specifically the orifice diameter, cone angle, diverging tapered nozzle, and volume—the simulations assess their effects on combustion dynamics, heat release rates, turbulent jet penetration, and emissions (NOx and CO). Model predictions of in-cylinder and pre-chamber pressure profiles, combustion phasing, and emission trends are validated against experimental data. The results demonstrate that optimizing pre-chamber and orifice configurations enhances turbulent mixing, accelerates flame development, and reduces local high-temperature zones, thereby suppressing NOx and CO formation. Although some discrepancies in NOx predictions persist due to limitations in current turbulence–chemistry models, the findings offer valuable insights for the design of high-efficiency, low-emission PCSI engines. Full article

Particle number concentration (PN) in vehicle exhaust and ambient air describes the number of ultrafine particles (UFPs) below 500 nm, which are recognized as a toxic and carcinogenic component of pollution and are regulated in several countries. Metal nuclei, ash, and organic matter contribute significantly to the ultrafine particle size fraction and, thus, to the particle number concentration. Exhaust gas filtration is increasingly being used worldwide to significantly reduce this pollution, both on diesel particulate filter (DPF) and gasoline particulate filter (GPF) engines. In recent years, the EU has also funded research projects dealing with the possibilities of retrofitting gasoline vehicles with GPFs. This paper presents the results and compares the PN emissions of different vehicles. An original equipment manufacturer (OEM) diesel car with a DPF is considered as a benchmark. The PN emissions of this car are compared with a CNG car without filtration and with gasoline cars equipped with GPFs. It can be concluded that the currently used GPFs still have some potential to improve their filtration efficiency and that a modern CNG car would still have remarkable possibilities to reduce PN emissions with an improved quality GPF. Full article

This paper examines the feasibility of converting a Heavy-Duty (HD) Spark Ignition (SI) Compressed Natural Gas (CNG) engine to biogas fuel. A One-Dimensional (1D) simulation tool was used to model a commercially available HD SI CNG engine. The model was validated by comparing experimental and computed in-cylinder pressure, brake power, fuel, and air mass flow rates. The engine was then modified to use biogas with an injection system based on existing designs from the literature. A Spark Advance (SA) sweep was performed to assess the engine’s performance at full load. The chosen equivalence ratio was 0.85, and the engine speed was 1500 rpm. The Maximum Brake Power (MBP) and Maximum Brake Efficiency (MBE) operating points were identified. Partial load analysis was conducted starting from the MBP conditions. Results in terms of brake power, brake efficiency, and NO_x emissions are presented. Conversion to biofuel results in a reduction in power and efficiency of 33% and 4%, respectively, at 1500 rpm and full load conditions. Brake Specific NO_x emissions remained comparable. This numerical study demonstrates the feasibility of biogas conversion for HD SI engines, offering a renewable fuel alternative to reduce greenhouse gas emissions, though with trade-offs in power and efficiency. Full article

One of the solutions contributing to the development of energy independence is the utilization of biogas as an alternative fuel for agricultural tractors. Biogas is recognized as a renewable energy source, and its usage aids in the reduction in greenhouse gas emissions on a global scale. The reuse of this material/waste exemplifies the concept of a circular economy. Several models of agricultural tractors designed explicitly for biogas utilization or adaptable for its use are available in the market. This study aimed to evaluate the energy-ecological parameters of the MP tractor (T6.180 Methane Power) powered by Compressed Natural Gas (CNG) in comparison to its structurally identical counterpart fueled by Diesel (T6.180 Electro Command). Based on the Air–Fuel Ratio (AFR) coefficients for diesel and methane, as well as values of air excess ratios (λ) and the proportions of CO and CO₂ emissions determined for various engine load states, the mass emission of selected exhaust components for the examined tractors was estimated. This research highlights that biogas-powered tractors hold the potential to contribute to the sustainable development of agriculture through the reduction in greenhouse gas emissions, improvement in farm energy autonomy, and optimal resource utilization, closely aligned with the principles of a circular economy. Full article

This study examines the dynamic fluid behavior of a PWM-controlled Solenoid-Operated Gas Admission Valve (SOGAV) for large-bore CNG engines using 3D Computational Fluid Dynamics (CFD) simulations with dynamic mesh techniques. The research focuses on the influence of orifice geometry variations in the multi-hole restrictor and pressure differentials between the inlet and outlet on flow stability, turbulence, and valve performance. Results demonstrate that multi-hole restrictors with different-sized orifices improve flow uniformity and reduce turbulence, thereby mitigating flow resistance. Transient simulations further reveal standing wave formation and pressure wave interference, emphasizing that steady-state models cannot capture critical transient phenomena, such as accelerated and decelerated jet-like flows and flow separation. These findings provide key insights into SOGAV optimization, contributing to enhanced fuel efficiency and engine responsiveness, meeting the performance requirements of modern gas engines. Full article