Internal Combustion Engine Research Articles

Theoretical analysis of the piston ring-pack for predicting friction and power loss in an internal combustion engine

The piston ring is considered an essential element in the operation of the internal combustion engine to improve its efficiency and reduce its emissions. It is resistant to high temperature and high-pressure gases in the combustion chamber. A one-dimensional analysis method of lubrication between piston rings and cylinder liner in mixed lubrication conditions is developed in this article by using the GT-Suite simulation software. We applied the finite difference numerical method to solve the Reynolds equation to obtain the variation during an engine cycle of the following parameters; film thickness, frictional force, and power loss. The solution results presented can be used to improve the design of the piston ring pack in internal combustion engines and is available for industry usage.

Molecular dynamics study of the scratching property of the tetrahedral amorphous carbon coating on the piston ring

In order to reduce friction and wear of the piston ring-cylinder liner system of the internal combustion engine, the tetrahedral amorphous carbon (ta-C) coating on the piston ring is considered. The scratching properties of the ta-C coating and diamond ball are studied by molecular dynamics simulation. The atomic configuration, surface morphology, RMS roughness, friction force, coefficient of friction, wear rate, and normal stress of the ta-C coating are analysed under different scratching depths, substrate temperatures, and scratching velocities. The interatomic interactions are described using the second nearest-neighbour modified embedded-atom method potential, as well as Tersoff potential and Lennard-Jones potential. The simulation results show that the ta-C coating exhibits excellent scratching properties. The scratching depth has a significant effect on the scratching property of the ta-C coating, while the substrate temperature and scratching velocity have a relatively small effect.

Internal Combustion Engine Fault Detection Based on Random Convolutional Neural Networks

The internal combustion engine plays a very important role in many fields, and when the internal combustion engine fails, if it is not found in time, it may cause continuous damage to the internal combustion engine, and further affect the life of the entire mechanical system. To solve the above problems, this paper proposes fault detection of internal combustion engines based on a random convolutional neural network. The cylinder burst noise signal of the internal combustion engine is decomposed by a stationary wavelet, and the inclusion matrix is composed of partial decomposition coefficients. Using singular value theory, the singular value containing matrix is extracted as the characteristic of cylinder burst noise signal. The singular value is used as the input of a random convolutional neural network to train and identify faults. The AdaBound optimizer was then applied to adapt the learning rate to changes, thereby accelerating the weight update of the model. At the same time, the neurons in the structure are randomly deactivated by dropout technology to prevent complex collaborative responses to the training data, and the diagnosis results of each network model are integrated by Dempster synthesis rules. The experimental results show that the minimum mean square error of 0.00165 is achieved when there are 15 neurons in the hidden layer, and it gradually increases as the number of neurons increases. Therefore, it is determined that there should be 15 neurons in the hidden layer, and the trainLM algorithm is used. The decision factors for training, validation, cross-validation, and overall data are 0.98947, 0.98597, 0.97738, and 0.9801, respectively, all reaching the control accuracy of 0.95, which indicates that the random convolutional neural network proposed has a high accuracy for internal combustion engine fault detection. For the main bearing Y-directional force, as the gap increases, its fluctuation trend strengthens; the main bearing force changes within a small range at first, then increases sharply when the gap reaches 0.2[Formula: see text]mm, and some main bearings even experience significant impact loads.

The impact of carbon quantum dots derived from spent coffee grounds on the droplet combustion of diesel/n-butanol blend

As global concerns surrounding climate change mount and fossil fuel reserves diminish, the application of additives in internal combustion engines is increasingly prevalent. Butanol and carbonaceous nanomaterials, such as carbon quantum dots (CQD), are being employed as additives to increase engine efficiency and mitigate the emission of pollutants. Nevertheless, understanding the impact of these additives on combustion behavior at the droplet scale through combustion assessments before their use in engines is crucial. In this study, our main objective was to assess the impact of incorporating CQD dispersed in n-butanol as additives to conventional diesel fuel on the combustion characteristics at the droplet scale. CQD were obtained from spent coffee grounds (SCGs) using n-butanol as a solvent. The product obtained was mixed with Colombian commercial diesel (10 % vol. palm oil biodiesel), and its combustion was evaluated using the droplet combustion method. Before the CQD synthesis, SCGs were characterized by thermogravimetric analysis (TGA) and field emission scanning electron microscopy (FESEM). CQD were characterized via Fourier transform infrared (FTIR) spectroscopy, Transmission Electron Microscopy (TEM), UV–vis, and fluorescence spectroscopy. Results indicated that adding n-butanol and CQD to commercial diesel leads to a 5.4 % and 16.5 % increase in droplet ignition delay, respectively. These additives also cause droplet contraction and expansion cycles, resulting in unstable combustion. However, CQD reduces the frequency of microexplosions caused by boiling n-butanol inside the droplet, which mitigates instabilities during droplet combustion. Including CQD can enhance fuel evaporation by increasing the density of nucleation sites for bubble formation and preventing micro-explosions, thereby leading to stable combustion. These attributes can significantly influence the performance of blends in Compression Ignition (CI) Engines.

Fuel Efficiency Optimization in Adaptive Cruise Control: A Comparative Study of Model Predictive Control-Based Approaches

This work investigates the fuel efficiency potential of Adaptive Cruise Control (ACC) systems, focusing on two optimization-based control approaches for internal combustion engine (ICE) vehicles. In particular, this study compares two model predictive control (MPC) designs. In the first approach, a strictly quadratic cost is adopted, and fuel consumption is indirectly minimized by adjusting the weights assigned to state tracking and control effort. In the second approach, a fuel consumption map is explicitly included in the MPC cost function, aiming to directly minimize it. Both approaches are compared to a globally optimal benchmark obtained with dynamic programming. Although these methods have been discussed in the literature, no systematic comparison of their relative performance has been conducted, which is the primary contribution of this article. The results demonstrate that, with proper tuning, the simpler quadratic approach can achieve comparable fuel savings to the approach with explicit fuel consumption minimization, with a maximum variation of 0.5%. These results imply that the first alternative is more suitable for online implementation, due to the more favorable characteristics of the associated optimization problem.

Influence of External Clearance Variation on Vibration Characteristics of Ship Electrically Assisted Turbocharger Rotor Bearing System

Electrically assisted turbocharging (EAT) technology is an important technical means to effectively solve the problems of insufficient intake air and poor transient response of traditional turbocharged engines at low speed or acceleration, and to realize the electrification of marine internal combustion engine power system. In the EAT design stage, the original rotor model of a marine turbocharger was established and verified. Subsequently, the EAT rotor dynamics design and analysis were carried out, and the influence of the unbalanced phase and external clearance on rotor vibration was discussed. The results show that when the external clearance is small, extensive sub-synchronous vibration occurs and bifurcation occurs at high speed. When the external clearance is large, the sub-synchronous vibration component almost disappears but high synchronous vibration occurs at a high speed. At the same time, the shaft is significantly affected by the gravity load at low speeds, and the rotor makes a balanced motion on the critical limit cycle at high speed. In order to minimize the vibration and noise of the same type of EAT, it is recommended to control the outer clearance of the EAT bearing in the range of 0.30–0.36[Formula: see text]mm. The research content provides a reference for the dynamic design and analysis of the EAT, which effectively helps the development of the original engine of the ship electric auxiliary turbocharger and improves the operation stability of the EAT.

Economic implications of a phased‐in EV mandate in Canada

AbstractCanada plans to phase out internal combustion engine vehicle (ICEV) sales in favour of electric vehicles (EVs) by 2035 as part of its climate policy. Herein I examine the economic implications of a phased‐in electric vehicle mandate. I show using partial equilibrium analysis that when both types of cars are available, auto companies will overproduce electric vehicles and earn scarcity rents on internal combustion engine vehicles that partially offset the revenue loss on electric vehicles. I then present a numerical general equilibrium model of the Canadian economy to assess the overall macroeconomic consequences of the policy. The results depend critically on the assumed pace at which electric vehicles achieve cost parity with internal combustion engine vehicles on a quality‐adjusted basis. An electric vehicle mandate will have manageable economic consequences if technology improves so rapidly that the mandate is unnecessary. If the mandate outpaces achievement of cost parity the economic consequences can be severe and would likely cause the auto manufacturing sector to shut down. The cost per tonne of emission reductions are at least 10 times the Canadian carbon tax rate while the mandate is binding. The analysis provides insight into why automakers have been willing hitherto to develop and sell electric vehicles even though they currently lose money on them.

A comparative study of vehicle powertrain efficiency: Data-driven analyzing energy consumption and environmental impact

This study investigates the energy consumption of electric vehicles (EVs) in real-world driving conditions, using in-vehicle sensor data and location tracking. The energy consumption of EVs is compared to that of an internal combustion engine vehicle (ICEV) under similar driving tests. Furthermore, an energy-centric life cycle assessment was conducted to assess the environmental impact of the transition to electrified transportation by reporting the carbon emissions of the EVs and ICEV. Since a large volume of driving data was acquired in the experiment, machine learning (ML) techniques are employed to interpret the obtained data and identify a key feature. ML algorithms can help develop predictive models that estimate energy consumption and explain the major factors that impact such consumption. The findings also offer valuable insights into energy consumption, emission, and the underlying factors that can inform policy discussion related to transport electrification and enhance energy efficiency. This research is significant in comprehending the potential of current EVs and their superiority over traditional vehicles. It is vital to facilitate the shift toward electric transportation, which can be driven by the results.

ICE to EV Conversion in Thailand: Evaluating Feasibility, Benefits, and Challenges

Abstract: The shift to electric vehicles (EVs) is vital for reducing greenhouse gas (GHG) emissions, but Thailand faces challenges in adopting new EVs due to high costs and limited infrastructure. This study investigates the feasibility of converting internal combustion engine (ICE) vehicles to EVs over the next decade, examining the economic, environmental, and social impacts. Findings show that EV conversions can reduce operational costs by 40-50% and lower GHG emissions by up to 70%, even when accounting for electricity-related emissions. In addition, the transition could significantly improve air quality, leading to public health benefits. However, barriers such as high upfront conversion costs, limited access to conversion kits, and the need for skilled labor remain. Addressing these challenges through government incentives, infrastructure development, and workforce training will be essential for scaling up EV conversions, enabling Thailand to accelerate its shift toward sustainable transportation and meet its climate goals.

Numerical Prediction of Inlet Geometry Influence on the In-Duct Acoustics of Small Centrifugal Compressors

Abstract Small centrifugal compressors are employed to boost automotive internal combustion engines or hydrogen fuel cells, amongst other applications. In many scopes, the overall intensity and quality of noise emission is a major concern, so many researchers develop and assess numerical models to predict acoustic spectra. In this work, detached Eddy simulations (DES) of a vaneless centrifugal compressor are conducted to assess the impact of intake geometries on its aeroacoustic performance. Experimental measurements are employed as a means of validation. Flow field analysis and Dynamic Mode Decomposition allow us to analyze the underlying mechanisms of the most relevant acoustic features. This work provides insight into the implications for noise generation of employing tight elbows due to packaging constraints.

Сучасні тенденції розвитку двигунів безпілотних літальних апаратів

The subject of this study is the current state and prospects for the development of the market for unmanned aerial vehicles (UAVs) and power plants. The purpose of this work was to identify trends in the development of UAV engines of various classes. Task: collection, systematization, and analysis of information on the most common engines of reconnaissance and strike UAVs of the operational-tactical level, as well as UAVs of the "barrage ammunition" class. This article provides a brief description of various types of UAV power plants, and their main advantages and disadvantages are given, which are often decisive when choosing the type of power plant for a specific UAV. It was found that a power plant with an internal combustion engine (ICE) is best suited for use in medium- and long-range UAVs.This study demonstrated that four-stroke internal combustion engines are most commonly used in reconnaissance-strike UAVs at both operational and tactical levels. The features of the design and characteristics of four-stroke internal combustion engines, which have become the most widely used UAVs, are described. It was determined that the introduction of turbocharging or increasing the pressure is the main means of forcing four-stroke internal combustion engines, which makes it possible to simultaneously achieve high specific power and high brake efficiency of the engine over a wide range of altitudes during its operation. It is shown that one of the most important tasks for a long-range UAV engine is to reduce the specific brake fuel consumption. Thus, there is a tendency to promote the use of high-powered aviation diesels in long-range UAVs. It was determined that the main requirements for UAV engines of the "barrage ammunition" class are high specific power, low cost and adaptability to mass production. This study shows that gasoline two-stroke internal combustion engines with crank-chamber scavenging are extremely widespread in UAVs of the "barrage ammunition" class. The design features and characteristics of UAV two-stroke internal combustion engines are described. The main means of ensuring high specific power of such two-stroke internal combustion engines are increasing the engine RPM, optimizing gas exchange processes, and reducing the weight of the construction by using new materials. Conclusion. The results show that depending on the UAV type, the set of engine requirements can vary significantly. Modern trends in the development of UAV engines of various classes have been determined. Potentially promising directions for increasing the efficiency of engines and for comprehensive improvement of their indicators and characteristics have been determined.

Assessing the environmental benefits of passenger cars electrification in metropolises: A case study of Singapore

Land-based transportation is a significant contributor to global greenhouse gas (GHG) emissions, with internal combustion engine vehicles being the predominant mode of transport in this sector. As the world population grows and urbanization accelerates, transport demand in metropolitan areas is projected to double by 2050, underscoring the critical need for sustainable transportation strategies, forecasting, and planning within an urban context. One challenge in this endeavor is the insufficient attention given to the distribution of vehicle grades within the overall car population during GHG impact assessment, despite the recognized importance of car grade by researchers and policymakers. In this study, we incorporate both engine type and vehicle grade distribution, derived from data on over 30,000 passenger cars registered with the Land Transport Authority of Singapore between 2018 and 2022, into our life cycle assessment analysis. This approach ensures that our scenario-based studies on prediction and planning are more comprehensive than those that consider only the most popular models. Furthermore, while Singapore benefits from a relatively clean electricity supply, the current limitations in charging infrastructure negatively affect the GHG impact of electric vehicles. The insights from this research will inform the development of transportation policies for metropolises like Singapore, contributing to the advancement of a more sustainable transportation system.

Diagnosis of marine internal combustion engines by means of rapidly variable temperature and composition of exhaust gas as an alternative or support for currently used diagnostic methods

The article points out relevance of parametric diagnostics of ship engines and analyzes the state of research in this field. A method is proposed for diagnosing engine systems on the basis of rapidly variable exhaust temperature while measuring its composition. A method for determining diagnoser tools from the signal within one engine cycle and mathematical and statistical treatment of test results is presented. The products of numerical moddeling in the Diesel-RK software and the products of laboratory research on a Farymann Diesel test engine were analyzed. Affect of the most popular defects on the analyzed parameters was defined. Criteria for matching a diagnoser tool in accordance with the type of damage in a ship engine was presented. A methodology was proposed for adapting the presented method to metering on a ship engine in operation.

Exploration of the Traffic Safety of Battery Electric Vehicles: A Case Study of Tesla Vehicle-Involved Crashes in Pennsylvania, USA

After decades of efforts, the number of battery electric vehicles (BEV) has increased greatly around the world. Meanwhile, their unique technical features also bring many new traffic safety challenges. Using traffic crash data from Pennsylvania from 2018 to 2021, this study aims to identify characteristics and trends of BEV crashes by comparing those crashes involving Tesla vehicles (the premier BEV brand in the auto market of the United States) with crashes involving internal combustion engine vehicles (ICEV). First, Tesla and ICEV crashes are compared for crash severity, collision type, spatial and temporal distributions, and environmental features. Tesla crashes show no significant difference from those of ICEVs in severity, but they have many more rear-end and angle collisions. In addition, Tesla crashes are found to concentrate in peak hours and around noon, occurring mainly in urban areas, at intersections, and on state roads. A logistic regression model is then built to identify the important factors influencing the severity of Tesla crashes. The findings are expected to provide new insights which will help researchers understand better traffic safety issues around BEVs.

Exploring the benefits of hydrogen-water injection technology in internal combustion engines: A rigorous experimental study

Previous hydrogen researchers have demonstrated the great potential of hydrogen as a zero-carbon fuel and its wider operational ability to directly replace the existing fossil-fuelled internal combustion engines (ICE). Hydrogen direct-injection technology can operate at stoichiometric combustion conditions, fully eliminating the intake backfire phenomena, which has the benefit of low airflow requirements and is a suitable solution for naturally aspirated ICE platforms. However, significant challenges must be addressed when operating an H2 ICE at or near stoichiometric. These include rapid pressure rise rate, high in-cylinder gas pressure and temperature and the consequential higher engine-out NOx emissions. This study provides a comprehensive experimental analysis of the effect of water injection on a light-duty H2 engine’s performance, efficiency, burn durations and NOx emission. The engine was modified to operate with hydrogen via a centrally-mounted direct H2 injector and an intake port-mounted water injection system. The study included water vapour measurements, NOx concentrations and other exhaust gases. The practical implications of these findings are significant. The results demonstrated that the NOx emissions were reduced by 79% when the water was injected at a rate of 5 kg/h at 10 bar IMEP and 2000 rpm. This reduction in emissions, coupled with the observed decrease in cylinder pressure and the rate of pressure rise, could substantially improve engine performance and efficiency. At higher load regions, the water injection extended the maximum engine load to 24 bar IMEP and increased the engine torque output by 10%. The maximum Indicated Thermal Efficiency (ITE) increased from 41% at 16.5 bar IMEP to 42.5% at 18 bar IMEP at a lower lambda, with a corresponding reduction in the intake-air-boost pressure requirement. Of particular note, the use of water injection decreased the engine-out NOx emissions under high-load conditions by more than 55%, even at richer AFR compared to pure hydrogen operation.

Numerical study of NOx formation mechanism in ammonia-hydrogen compound fuel marine engines under varying conditions

Ammonia and hydrogen are considered promising fuels for achieving zero carbon emissions in internal combustion engines. However, the mechanism of NOx formation in ammonia–hydrogen combustion remains insufficiently studied owing to the complex interaction between thermal NOx and fuel NOx. This study investigates the effects of varying equivalence ratios, N2/NH3 ratios, and initial temperatures on NOx formation using a decoupling method. Results show that thermal NOx dominates under all conditions, contributing approximately 64%–75% of total NOx. As the equivalence ratio increases from 0.6 to 1.0, the proportion of thermal NOx decreases by 7.2%. Conversely, increasing the N2/NH3 ratio from 0.8 to 1.2 leads to a reduction in both fuel and thermal NOx, while the relative proportion of thermal NOx increases. The trends in thermal NOx proportion exhibit opposite behavior with respect to equivalence ratio and N2/NH3 ratio. When the inlet temperature rises from 400 K to 480 K, thermal NOx emissions increase by 54.2%. Of the factors studied, temperature has the greatest impact on both thermal and fuel NOx formation. These findings offer valuable insights into NOx emission characteristics for researchers working on ammonia-fueled engines.

A Deep Learning Method for the Prediction of Pollutant Emissions from Internal Combustion Engines

A Deep Learning Method for the Prediction of Pollutant Emissions from Internal Combustion Engines

Evaluation of potential electric vehicles load-induced damage on flexible pavements

The adoption of Electric Vehicles (EVs), driven by policies like the Zero Emission Vehicle (ZEV) mandate, is rapidly transforming transportation infrastructure. In 2021, over 1.25-million light-duty EVs were registered in the United States, signaling a shift that extends to heavy vehicle categories. This study evaluates the implications of this transition on road networks, focusing on the increased gross weight of EVs compared to traditional Internal Combustion Engine (ICE) vehicles and its impact on flexible pavement structures. The study investigates the deterioration patterns and potential damage to road infrastructures resulting from integrating EVs into the traffic mix, utilizing both the AASHTO 1993 and Mechanistic-Empirical (ME) pavement evaluation methodologies. The analyses reveal a significant acceleration in road degradation, necessitating urgent consideration of EV-induced stresses by transportation authorities. Recommendations for future research and practical strategies for mitigating these impacts are provided to guide policymakers and engineers in adapting to this evolving vehicular landscape.

Thermo-structural Comparative Analysis of Internal Combustion Engine Piston by Finite Element Methods

Thermo-structural Comparative Analysis of Internal Combustion Engine Piston by Finite Element Methods

Linking sustainability reporting and energy use through global reporting initiative standards and sustainable development goals

AbstractThis paper addresses the critical need for an integrated approach to sustainability reporting by examining the transition from internal combustion engine vehicles to electric vehicles within the automotive industry. By focusing on the top 8 highest-revenue global automakers in 2022, the study utilizes the Global Reporting Initiative (GRI) standards and United Nations Sustainable Development Goals to assess contributions to SDG 7 (affordable and clean energy) and other pertinent indicators. A comprehensive content analysis and logistic regression analysis are employed to explore the correlation between energy use and compliance with GRI standards from 2018 to 2022. The findings reveal significant trends in sustainability reporting, with a noted decrease in quality in the final year analyzed. Specifically, GRI 302-3 (energy intensity) shows a significant negative relationship with energy consumption, indicating higher energy usage correlates with lower compliance. The study reinforces the necessity for more transparent and effective sustainability reporting frameworks to enhance corporate practices and drive progress toward sustainability goals. Graphical abstract