Engine Size Research Articles

A scenario-based assessment of the energy efficiency existing ship index (EEXI) and carbon intensity indicator (CII) regulations

International Maritime Organization has entered into force several regulations to lessen the carbon footprint of maritime transport. EEXI is utilized to sustain continuously increased energy efficiency and CII is utilized to measure carbon emissions and rating boundary of ships. In this paper, five different ship types, which are the bulk carrier, gas carrier, tanker, general cargo, and container ship, are examined in seven scenarios. Meeting EEXI and CII requirements is extremely challenging for marine vessels where conventional fuels such as MDO and HFO are utilized and without having an engine power limitation application based on the outcomes of the scenarios. Engine power limitation provides a significant advantage, and the usage of alternative fuels such as LNG and methanol is effective to avoid falling below the threshold of EEXI and CII. The specifications of primary fuel and the usage rate of the alternative fuel are the prominent criteria for dual-fuel engines utilizing LNG to meet the requirements. The EEXI values and CII ratings can be significantly reduced by converting a conventional engine to a methanol engine. The proper selection of the engine size and the speed optimization of the vessel is the key factor for this application.s.

REAL-TIME EMISSIONS OF GASEOUS POLLUTANTS FROM VEHICLES UNDER HETEROGENEOUS TRAFFIC CONDITIONS

Air quality problems in cities are often a cause for worry. The air quality index is increasing daily, leading to an increase in cancer and many respiratory problems. Road transport in an urban area is a significant cause of air pollution. The vehicles must meet Indian emission regulations for which the emissions are measured using legally mandated standard driving cycles that did not accurately reflect real-world driving emissions because of varying traffic conditions, meteorological conditions, driving behaviour, vehicle power, performance, etc. This study focuses on real-time emissions of gaseous pollutants hydrocarbon (HC), carbon dioxide (CO2), carbon monoxide (CO), and nitric oxide (NO) from vehicle exhaust pipes under heterogeneous traffic conditions. The emissions were measured using a Portable Emission Measurement System (PEMS). The PEMS used was an AVL MDS 450 analyser mounted on the vehicle, and on-road emissions were captured. The test sample consists of four passenger vehicles with varying engine sizes, manufacturers, and fuel. The test route comprises city and highway areas, and it was discovered that the emissions were reduced by 40 to 70% on highways compared to the city. In petrol BSIV and BSVI engines, the emission was reduced to 41.73% for CO, 46.90% for HC, and 64% for NO in the city area. Speed and emissions scatter graphs were plotted for the vehicles, and it was found that in the city area, the optimum speed for less emission is between 30-40 km/h, and on highways, the optimum speed is 80-90 km/h. The emissions were also sensitive to the rate and frequency of acceleration and decelerations. This type of study is very limited in India, and more such studies are required for the assessment of air quality in metropolitan areas and successful traffic management strategies, as well as for determining instantaneous projections of pollutant emissions.

Additive engineering for highly efficient and stable perovskite solar cells

Since the groundbreaking report on solid-state perovskite solar cells (PSCs) in 2012, PSC receives great attention due to its high power conversion efficiency (PCE) obtainable at low-cost fabrication. A PCE of 9.7% in 2012 was swiftly improved to 25.7% in 2022 via perovskite composition engineering and grain size control. The excellent photovoltaic performance originates from the defect-tolerant property of organic lead halide perovskite associated with the antibonding nature of the valence band. Nevertheless, the reduction of defect-induced trap density of the state is still required to improve further photovoltaic performance and stability. Among the methods reported to reduce defects, additive engineering is one of the promising strategies for controlling crystallographic defects because it can regulate crystallization kinetics and grain boundaries. In this review, we describe materials and methods for additive engineering applied to lead-based perovskite. In addition, the effects of additive engineering on photovoltaic performance and stability are discussed.

A multivariable output neural network approach for simulation of plug-in hybrid electric vehicle fuel consumption

This study is laser focused on the simulation of fuel consumption and fuel economy label parameters of plug-in hybrid electric vehicles. While fuel economy is a key factor in the design of plug-in hybrid electric vehicles, a fuel economy label can educate customers about the economic advantage of purchasing a particular car. The fuel economy label of a PHEV consists of parameters like driving range, electrical energy consumption, fuel economy for city, highway, and combined use, battery recharge time, and fuel consumption rates. The study used an inverse function model of an artificial neural network to simulate and calculate the parameters of the fuel economy labels of PHEVs. Firstly, the selected parameters of the fuel economy label of plug-in hybrid electric vehicles were used to develop a single output model. The output variable of the single output model was then merged with dummy functions to form input variables for the inverse function model. The output variables simulated were engine size in litres; estimated driving range when the battery is fully charged in km, battery recharged time in hours, city fuel consumption (L/100 ​km), highway fuel consumption (L/100 ​km), combined fuel consumption (L/100 ​km), estimated driving range when the tank is full, carbon dioxide (CO2) emission in grams/km, electric motor power in kW, number of cylinders, and electrical charges consumed in kWh/100 ​km. Different cases of input variables were considered for the inverse function model. The accuracy of the model was 29.1 times greater than that of the conventional inverse artificial neural network model.

A PROPOSAL FOR A HYBRID POWER TRAIN FOR A TRUCK

Aiming at reducing the emission of pollutants from automotive vehicles, international commissions indicate, at each given period, a target of admissible values for these pollutants, to be implemented by the automakers. A case like the future implementation of EuroVII, from 2025, in European regions. In parallel to these conditions, there are many studies with the objective of seeking alternatives for the propulsion of these combustion vehicles, for example, the application of fully electric or hybrid vehicles. This article aims to develop and implement a mathematical model for a proposal for a hybrid engine, in a low-power truck, resulting in a small diesel engine, powering the vehicle's alternator and battery, generating the charging for use in a main electric motor, that is, to develop with a focus on energy conservation and the environment, with a reduction in the size of a combustion engine and its emissions.

Heat Generation Inside Turbocharger Without External Heat Source

Recently, many vehicle manufacturers started to invest in new technology to reduce the emission produced by their engines. Due to the emission regulations that become more stringent and the rising demand for highly efficient vehicles, many new technologies were introduced to achieve the demand. One of the technologies that gain popularity in modern vehicles is applying force induction systems such as turbocharging and supercharging the engine. By using the turbocharger, two major advantages can be achieved which are increasing engine efficiency and engine size reduction. However, turbocharger performance will be affected by the amount of heat that is generated due to friction inside the bearing, air compression process and also the heat transfer from the exhaust gas that has high temperature and pressure. In this paper, the heat generation inside the turbocharger unit without any external heat source was measured and analysed. A turbocharger unit from Garrett Turbocharger where the model is GT2056 was used for this experiment. The operating speed in the study is recorded between 20 000 rpm until 70 000 rpm and the temperature at the turbine inlet and compressor inlet is at room temperature. The parameters that were measured are the temperature difference at the turbine side, bearing housing and also compressor side. From the results obtained, it can be concluded that the bearing housing produces a higher amount of heat compared to the compressor side while the turbine side will experience heat loss.

Definition of a general performance map for single stage radial inflow turbines and analysis of the impact of expander performance on the optimal ORC design in on-board waste heat recovery applications

Small-scale Organic Rankine Cycles (ORCs) represent a promising technology for on-board waste heat recovery (WHR) from internal combustion engines (ICEs) especially in innovative long-haul trucks transport applications. Despite market leader companies have already proved its effectiveness, detailed system design procedures are scarcely available in the open literature and proposed solutions are often more simplified with respect to current industrial state-of-art. The present work describes a methodology to include within the ORC design and optimization procedure an efficiency map of the turbo-expander, retrieved exploiting a reduced-order method developed in-house. The proposed approach allows therefore to design the thermodynamic cycle considering a realistic performance of the expander and to retrieve the best cycle architectures and turbine geometry depending on heat source characteristics and active constraints. First the turbine performance is defined in general terms and investigation of its applicability to different fluids and to expansions characterized by various degrees of non-ideality is provided. Then, the methodology is applied to different WHR applications highlighting for several potential working fluids the impact of adopting turbine performance maps within the cycle optimization procedure rather than assuming constant efficiency values. Results show that the cycle configuration and the main design parameters are strongly affected by the plant size and the working fluid selection, and that the adoption of a turbine performance map is particularly valuable when dealing with small size power plants adopting high density fluids. In particular, the assumption of constant turbine efficiency may lead to the definition of thermodynamic cycles extremely far from the optimal ones (e.g. adoption of supercritical cycles rather than subcritical ones) that in turn can result in an unfeasible design of the turboexpander. Moreover, this assumption may also lead to an incorrect comparison between different candidate working fluids lacking in identify those more suitable for a specific plant size. Both those limits can be solved with the adoption of the expander performance map proposed in this work. Final results show that on board WHR ORC can reach an efficiency of at least 20% in a relatively large range of internal combustion engine size. On the contrary, the choice of the best working fluid is affected by engine size and chosen hot sources: for small available thermal power the use of complex and flammable hydrocarbons (cyclopentane, cyclohexane, toluene) is the most efficient choice while the use of low GWP non-flammable halogenated hydrocarbons (R1233zd and R245fa) becomes promising only for relatively large available thermal power.

Measuring CO2 Emissions in E-Commerce Deliveries: From Empirical Studies to a New Calculation Approach

The rapid development of e-commerce during the COVID-19 pandemic has caused an increase in the demand for urban deliveries. In this study, we conduct an exploratory analysis to identify factors that influence the fuel consumption and related greenhouse gas emissions (GHG) of vans and trucks used for e-commerce delivery. The novelty of this research results from the proposal of a new actionable approach to calculate CO2 emissions from heterogeneous fleets in e-commerce deliveries. Through a literature review, a survey of transport managers, and a case study on e-commerce deliveries, we have found that the heterogeneous fleet structure impacts direct emissions from urban deliveries. We have taken into account the parameters of a heterogeneous fleet structure, such as gross weight, mass, fuel type, engine size, fuel consumption (liters/100 km), and the age of a vehicle. Through numerical experiments, we have identified that the age of a vehicle results in increased fuel consumption of 1.31% year-to-year for vans and 1.01% year-to-year for 18-t trucks. For that reason, we proposed a novel formula to calculate the direct CO2 emissions from heterogeneous fleets in e-commerce deliveries, which takes into consideration the age-related fuel consumption factor and the structure of a fleet.

Lightweight Materials for Automobiles

This paper deals with vehicle lightweighting, as a strategy to help attain sustainability in the automotive industry by facilitating improved fuel economy. We reviewed innovative materials appropriate for the manufacturing of low-carbon vehicles (LCVs), such as advanced high-strength steel (AHSS), aluminum alloys, magnesium alloys, as well as novel composite materials commonly used for lightweight construction applications. Research shows that vehicle curb weight greatly affects fuel consumption. Primary weight reduction refers to body-in-white (BIW), which can subsequently lead to secondary weight reductions in terms of engine and powertrain size. This review takes into account the environmental aspect of the car body material and the possibility of closed-loop recycling, especially for aluminum and magnesium alloys.

Multi-objective optimization and performance analyses of an endoreversible rectangular cycle

Based on the endoreversible rectangular cycle model founded in the previous literature, the rectangular cycle performance characteristics with nonlinear variable specific heats are analyzed by applying finite time thermodynamic theory when the objective functions are efficient power and power density, respectively. The different four-objective, three-objective and two-objective combinations are optimized based on the four objectives of the power density, efficient power, power output and efficiency by using the NSGA-II, then the results of the multi-objective optimizations are compared with those of the single-objective optimizations. The results show that, compared with the maximum power output point, although the heat engine efficiency at the maximum power density working point reduces by 10.97%, the heat engine size reduces by 30.84%; compared with the maximum power output point, although the heat engine power output at the maximum efficient power working point reduces by 0.067%, the heat engine efficiency increases by 0.21%. In the MO optimization results, the smallest deviation index is 0.2371; in the single-objective optimization results, the smallest deviation index is 0.2380; so the optimization result of the MO is better than those of the single-objectives.

Insights of Selective Catalytic Reduction Technology for Nitrogen Oxides Control in Marine Engine Applications

The international shipping industry is facing increasingly stringent limitations on nitrogen oxide (NOx) emissions. New solutions for reducing NOx emitted by marine engines need to be investigated to find the best technology. Selective Catalytic Reduction (SCR) is an advanced active emissions control technology successfully used in automotive diesel engines; it could be applied to marine engines with ad-hoc solutions to integrate it in the exhaust of large engines. In this study, a commercial SCR was tested at the exhaust of a diesel engine in inlet gas conditions typical of a marine engine. The SCR system consisted of a custom monolith (provided by Hug-Engineering AG) that enabled seamless integration for a broad range of engine sizes; the active phases were V2O5 (3 wt%)-WO3 (7 wt%)-TiO2 (75 wt%). The monolith was studied at the laboratory scale for its in-depth chemical/physical characterization and by means of an intermediate-scale engine, reproducing the exhaust gas conditions of a full-scale marine engine. The system’s effectiveness in terms of NOx removal for the selected engine operating conditions was evaluated in a wide range of temperature and NOx emissions values and for different quantities of the reduction agent (AdBlue or ammonia) added to exhaust gases. The investigated technological solution resulted in efficient NOx emission control from a marine engine.

Using a decision tree to compare rural versus highway motorcycle fatalities in Thailand

Thailand ranks first in Asia and ninth in the world in term of road accident. As of 2020, the number of vehicles registered in Thailand was over 41 million, with motorcycles accounting for half of all vehicles. This study aimed to determine the cause of fatalities to reduce motorcycle accidents. The research entailed separating the accidents and fatalities into those occurring on highways (HWs) versus those occurring on rural roadways (RRs) and focused solely on rider at fault accidents to involve any confounding factors related to passengers or others involved. In Thailand, HWs have higher speed limits and allow more vehicle types than some RRs. Thailand’s Department of Public Disaster Prevention and Mitigation recorded 115,154 motorcycle accidents from 2015 to 2020. Decision trees allow for processing large amounts of data to drill down into associations between the individual variables in a large data set; in this study, the tree also separated accidents into whether or not the driver was exceeding the speed limit. The model’s performance for HWs, predicted misclassifications were found to be 28.3% (fatality to nonfatality) and a 44.5% (nonfatality to fatality) while predicted misclassification for RRs were 15.5% (fatality to nonfatality) and 60% (nonfatality to fatality). At all ages, the most fatalities were among male riders on dry straightaways in clear daytime weather; notably, however, on RRs, even when the rider was driving responsibly, fatalities were high at night on roads with no light. Following the presentation of the study findings, suggestions are made for ways the Thai government can improve the motorcycle accident and fatality statistics, including increasing the age limit for a motorcycle license, with engine size limits further divided according to age; proper enforcement of the existing rules will also improve the country’s accident statistics. It will also be highly effective to improve road lighting, particularly on RRs.

Numerical Analysis for Performance and the Combustion Reactants of the Crankcase Explosion Relief Valve

A crankcase explosion relief valve (CERV) is installed to minimize the effects of explosions occurring in the crankcase of marine engines. According to the regulations of the International Association of Classification Societies (IACS), installation of CERV is mandatory and it must be designed and manufactured based on the engine size. As there are various types of engines, the CERV must be developed accordingly. A high cost is required for the explosion test in the development process, so the test is performed for verification purposes in the final development stage. However, if the developed CERV causes an inappropriate result that is different from the expected performance in the explosion test, it needs to return to the development process so conducting the explosion test in the final stage may be unreasonable. In this study, to predict CERV performance, the chamber and CERV were modeled in 2D, and numerical analysis was performed assuming that the DISC of the CERV was opened by causing an explosion inside the chamber. The results of the numerical analysis were verified by comparing the results with the pressure rising during the explosion. In addition, the reasonable results were obtained for temperature, pressure, and combustion products through comparison to the theoretical calculation results. If the numerical analysis method used in this study is applied, it is expected to be able to predict the performance and reactants at the stage before the explosion test when developing the crankcase explosion relief valve.

Past and Future Practical Solutions for Torsional Vibration Damping in Vehicle Industry

In addition to material and production costs, consumption and emission limits, the requirements for performance, efficiency and space utilization must be met when it comes to the design of today's internal combustion engines for the automotive industry. As a result, three new design trends have been emerged (based on J. Pfleghaar and B. Lohmann's paper in 2013): 1. downsizing: reduction of engine size (number of pistons and stroke) for fuel and space-saving and CO2 emission reduction purposes, 2. downspeeding: reduction of engine speed to save fuel, which necessarily entails significantly higher torques being generated and transmitted in the engine, 3. turbo supercharging: increasing the pressure and compression ratio in the engine piston cylinder to cover the increased torque demand, which is accompanied by NOx gas emissions. Due to these new design trends, significant transverse, axial, and torsional oscillations can occur on the engine's crankshaft. To avoid power loss and fatigue due to the torsional oscillations, a torsional vibration damper is advised to be installed on the free end of the crankshaft or integrated into the flywheel. This review paper focuses on the possible reasons for torsional vibrations, the applied methods used to dampen them, and expected future trends.

Heat Transfer of Aggregate in a Drying Drum Based on the Multi-Scale Model and Fluid-Solid Coupling

The simulation of engineering research is difficult, especially the engineering problem of the large differences between the size of the equipment and materials processed. At present, two methods are used to solve this problem, i.e. the equal scale reduction model and the study of only a part of it, which makes it inconsistent with the actual situation. To find a better way to improve this problem, the multi-scale is introduced. In this study, the heat transfer of the particles in a drying drum with engineering size is studied by multi-scale and fluid-solid coupling methods. The general situation of the drying drum is introduced, and the fluid-solid coupling mechanism based on multi-scale is established. A method of establishing a particle micro model is proposed. The feasibility of this method is proved by simulation and experiment, and the accuracy of the proposed model is improved by 15.62% compared with the traditional model.

Modeling distraction tendency of motorized two-wheeler drivers in time pressure situations

Distraction and Time Pressure (TP) are the two major contributors leading to driving performance degradation and crashes. Previous research conducted on distraction and TP mainly focused on car drivers of High-Income Countries and limited studies explored the effects of both conditions on Motorized Two-Wheeler (MTW) drivers of Low-and-Middle-Income Countries. This study evaluates distraction tendency of MTW drivers in TP situations based on psychological, socioeconomic, and demographic factors along with vehicle characteristics. A total of 513 responses were collected through an online survey. The questionnaire focused on MTW drivers’ perception regarding distraction tendency and psychological (subjective norm, motivation for distraction, perceived risk, and attitude and behavior) along with other factors. Initially, Structural Equation Modeling (SEM) was conducted to obtain a relation between distraction tendency and psychological factors. Finally, Ordered Logistic Regression (OLR) models were developed to quantify the influence of various factors and TP situations on distraction tendencies such as talking to pillion rider, conversation and texting on mobile phones while driving. The SEM revealed that motivation for distraction and attitude and behavior was positively related to distraction tendencies under the TP driving situation. Further, the OLR model results showed that the odds of distraction due to mobile phone conversation, texting, and talking to pillion rider reduced by 48%, 33%, and 77%, respectively when the drivers were under TP situation. This study also revealed that MTWs with lower engine sizes, mostly present in Low-and-Middle-Income Countries, had 22% more chances of distraction due to conversation on mobile phones. It was observed that perceived risk had no significant influence on the distraction tendency of the drivers. Therefore, it is important to consider the intervention of psychological factors beyond perceived risk while making policies for reducing distracted driving patterns.

An analysis of the resonance attenuation in a combustion chamber

Resonance in internal combustion engines could represent a limiting factor in spark ignited engines, while constitutes a noise source in compression ignition configurations. The total resonance intensity is a combination between the noise source, for example, type of combustion, and the characteristics of the propagation medium, such as the combustion chamber geometry and the composition of the gases. In this work the in-cylinder resonance attenuation in internal combustion engines during the end of combustion is analyzed and modeled in detail. An approach is proposed to reproduce resonance attenuation evolution over a particular cycle. The method is validated using three different engines with different combustion characteristics. The model is able to predict the effect of the engine size, and it can also be implemented in real time to obtain the optimal window for trapped mass estimation by means of the resonance method.

Power Density Analysis and Multi-Objective Optimization for an Irreversible Dual Cycle

Abstract Considering the various irreversibility conditions caused by heat transfer and working processes in a dual cycle, the power density performance is optimized by applying finite-time thermodynamics theory, and multi-objective optimization is performed by using NSGA-II. The effects of cut-off ratio, maximum cycle temperature ratio, and various losses by heat transfer and working processes on the relationships between the power density and the compression ratio and between the power density and the thermal efficiency are analyzed. The thermal efficiency and engine size obtained under the conditions of maximum power output and power density are discussed. The results show that for a dual cycle, the heat engine has a smaller size and higher thermal efficiency under the condition of maximum power density. The cycle compression ratio and cut-off ratio are selected as decision variables, and the dimensionless power output, thermal efficiency, dimensionless ecological function, and dimensionless power density are selected as objective functions. Multi-objective optimization is performed with different objective combinations. The deviation indexes under the LINMAP, TOPSIS, and Shannon entropy approaches are discussed, and the number of generations when the genetic algorithm reaches convergence are obtained. The results show that the genetic algorithm converges at the 341st generation for the quadru-objective optimization, at the 488th generation for the tri-objective optimization, and at the 399th generation for the bi-objective optimization. When the bi-objective optimization is performed with dimensionless power output and dimensionless ecological function as the objective functions, the deviation index obtained based on the LINMAP approach is 0.1400, which is better than those obtained for other single- and multi-objective optimizations.

An overview of work productivity evaluation of farm tractors in timber skidding operations

Farm tractors have been applied in forest operations to carry out several tasks such as tree/felling/process-ing, forwarding, loading, skidding and cable yarding. Farm tractors can be equipped with special logging equipment that allows for their safe and efficient work in the harvesting of forest stands. This research is aimed to collect and review available literary sources on the productivity of farm tractors during skidding operations. The study results showed that work productivity of farm tractors for timber skidding has been studied by several researchers around the world. According to the results, the reported work productivity of skidding with farm tractors varied from 1.2 m3/PMH0 to 15.8 m3/PMH0 among international studies. Main variables impacting the work productivity of skidding included skidding distance, load volume, number of pieces per turn, tree diameter, tree length, slope of skid trails and engine power. Proper skid trail planning, applying suitable skidding equipment (e.g. winches, sulkies etc.), considering suitable engine size and prop-er safety standards can all help improving the work efficiency of the farm tractors during timber extracting. The information provided in this research can help the forest industry users and researchers gain proper knowledge on the work productivity of farm tractors applied for timber skidding. The study results can be also useful for planning and development purposes within small-scale forest operations.

Cравнительный анализ методов классификации данных при прогнозировании цен trade-in авто ЫХ ПРИ ПРОГНОЗИРОВАНИИ ЦЕН TRADE-IN АВТО

This article implements and analyzes machine-learning algorithms, for predicting carsprices. Predicting prices is one of the most challenging but interesting tasks. There are so many factors involved in the prediction - year of manufacture, condition, mileage, engine size, etc. All these aspects combine to make auto prices volatile and very difficult to predict with a high degree of accuracy. Machine learning techniques can uncover patterns and ideas that we have not seen before, and can be used to predict and classify data accurately and accurately. The choice of the proper data classification algorithm, which would be suitable for a given task, depends on the volume, quality and nature of the data, on the computing resources of the computer, and how you plan to use the result. Each classification algorithm has its own characteristics and is based on certain assumptions. Also requires practical skills. In practice, it is always recommended to compare the quality of at least several different learning algorithms in order to choose the best model for a particular task, since the most experienced data scientists will not be able to tell which algorithm is more efficient. Algorithms can differ in the number of features or samples, the noise level in the dataset, and whether the classes are linearly separable or not. Ultimately, the quality of the classifier, its computational and predictive power, depends on the underlying data intended for training the algorithm. The purpose of this article is to consider the stages of pre-processing training data, and show how machine learning in particular and information technology in general have succeeded in developing tools for modeling, designing, predicting, planning and decision support in the field of auto sales. This study proposes a hybrid approach to forecasting problems, that is, solving forecasting problems using statistical analysis and machine learning methods.