Engine Map Research Articles

Strategic optimization of dual-fuel diesel/gas engines by numerical approach for environmental and economic benefits

The study introduces a framework for optimizing eco-friendly dual-fuel engines, combining CFD and ANN, to reduce carbon emissions and improve sustainable transportation.We achieved optimal performance with a 52–65 % NG substitution ratio. SOI timing had a big effect on NOx emissions; later injection decreased NOx formation because it made the mixture more homogeneous. We developed a radial basis function neural network model to predict engine performance and emissions with 99 % accuracy. The study examines the effect of fuel droplet spraying on cylinder walls on engine performance and emissions, utilizing response surface methodology to create engine maps. Numerical experiments revealed that a lowered natural gas replacement ratio of less than 50 % resulted in decreased flame propagation and the attainment of a burn mixture mode. The decrease in flame propagation speed during CA10 led to a fivefold increase in CO emissions. As the NG substitution ratio exceeded 50 %, the air/fuel ratio neared equilibrium, resulting in a reduction in NOx emissions and in-cylinder combustion temperature. Nevertheless, the highest RoHR level decreased by 25 %. The downward trend proceeded until the natural gas substitution ratio reached to 90 %. The TOPSIS method was utilized to identify optimal operating conditions for DFDI engines, offering valuable insights for efficiency and emissions reduction.

Experimental Investigation of a Free-Form Honed Cylinder Liner for Heavy-Duty Engines

For future internal combustion engines, driven by regenerative fuels, efficiency is more important than ever. One approach to reduce the losses inside the piston cylinder unit (PCU) is to improve the alignment of the liner and the piston. Therefore, a cylinder liner with a free form was developed at the Institute of Technical Combustion (ITV) of the Leibniz University Hannover which compensates radial and linear deformations along the stroke. The layout is based on a FEM simulation. The liner was manufactured by the Institute of Production Engineering and Machine Tools (IFW) of Leibniz University of Hannover with a novel turn-milling process. The liner was investigated on the heavy-duty Floating-Liner engine of ITV with a displacement of 1991 ccm and a bore diameter of 130 mm. The experimental results show improvement in the friction losses over the whole engine map in the range of 9% and up to 17.3% compared to a serial liner. Sealing efficiency could be improved up to 28.8%, depending on the operational point. Overall, the investigation aims for lower fuel consumption which would in result fewer emissions.

Exploring the passive the pre-chamber ignition concept for spark-ignition engines fueled with natural gas under EGR-diluted conditions

The pre-chamber ignition system has demonstrated to be a suitable technology for increasing burning rates while reducing the cycle-to-cycle variability in spark-ignition engines. This concept offers an improvement in thermal efficiency through an increase in ignition energy and flame surface, allowing it to overcome knocking combustion issues at high engine load/speeds. This fact makes this ignition concept well compatible with the use of dilution strategies to control emissions or to further improve efficiency. However, despite promoting faster combustion, knocking combustion is still a major limitation at low rotational speeds and high engine loads (low-end torque). In this investigation, the performance of the passive pre-chamber concept is evaluated in a single-cylinder turbocharged spark-ignition engine fueled with compressed natural gas in EGR-diluted conditions. Several experiments and numerical simulations are combined to analyze the basis of the pre-chamber operation, while seeking to improve the global performance of the engine. To this end, a new pre-chamber geometry is proposed that is able to achieve better features in the ejected jets, to enhance the performance of the concept in the whole engine map.

Automatic smooth map generation of internal combustion engines via local-global model based calibration technique

The addition of new sensors and actuators to the engine, to reduce fuel consumption and emissions besides improving the engine operation, complicates the control commands stored in the engine control unit (ECU). Substitution of mechanical actuators with electronic ones increases the engine’s degrees of freedom and the number of control parameters, which results in the increased engine calibration time and cost. The aim of this paper is to take advantage of optimization techniques to achieve optimal values of control parameters in a fast and automated way. In this regard, it requires replacing the real engine with the virtual model and implementing the model-based calibration by coupling the virtual engine model with optimization algorithms. In this study, deep neural network (DNN) modeling and genetic algorithm (GA, NSGA-II) optimization are used for model-based calibration. The effect of all input control parameters, including ignition angle, continuously variable valve timing, etc., on all output control parameters including, brake-specific fuel consumption, emissions level, knock limit, combustion stability, etc., are investigated simultaneously by a valid global model, which is a remarkable achievement in the model-based calibration. Dynamic lag of some actuators delays the execution of control commands sent from ECU. To avoid abrupt variations in the actuators values, smoothness of the engine maps is considered in the calibration process. To reduce fuel consumption, decrease emission levels and attain smooth maps, the calibration of control parameters is performed by local-multi-objective optimization and global-single-objective optimization. Local-global model-based calibration presented in this study reduces 3.7% of the brake-specific fuel consumption and 7%–10% of emissions level at breakpoints of the engine map compared to manual calibration. In addition, the calibration time and costs while producing better engine performance can be reduced by automating the calibration process. Finally, calibrated maps are stored as a lookup table (LUT) in ECU. Generating an optimal lookup table involves the pre-calculation of several points that cover the calculation domain and allow the interpolation for other points. Selecting the optimal points for exact calculation is of great importance in the size and accuracy of LUT. In this study, an optimization tool is also presented to generate accurate and efficient LUT.

Developing Fuel Efficiency and CO2 Emission Maps of a Vehicle Engine Based on the On-Board Diagnostic (OBD) Approach

A vehicle interacts with the road, other vehicles, and traffic control devices in real traffic conditions. The level of traffic influences driving patterns and, consequently, this can affect the vehicle´s fuel efficiency and emissions. This study aims to develop engine maps of fuel consumption and CO2 emissions for a light vehicle operating under real traffic conditions. A representative passenger vehicle of the Ecuadorian vehicle fleet, powered by gasoline, was selected for the experimental campaign that was developed on a test route designed according to real driving emission (RDE) regulation. An on-board diagnostic (OBD) device was used for recording in real-time engine and vehicle operating parameters. Moreover, CO2 emissions were estimated using the fuel rate registered from the OBD system of the vehicle This study proposed a novel methodology for developing two-dimensional contour engine maps based on OBD data. The result showed that the vehicle engine operated in real traffic conditions with a brake thermal efficiency (BTE) of 27%, a brake-specific fuel consumption (BSFC) of 275 g/kWh, and a carbon dioxide (CO2) energy-emission factor of 716 g/kWh. In terms of distance, the CO2 emission factor for the tested vehicle was approximately 190 g/km. Overall, this study demonstrates that the OBD approach is a potential method to be used to assess the fuel consumption and emissions of a vehicle operating under real-world traffic conditions, especially in Latin American countries, where portable emission measurement systems (PEMS) are not readily available.

Measurement of engine performance and maps-based emission prediction of agricultural tractors under actual operating conditions

This paper develops a comprehensive data collection system (CDCS) based on radio frequency identification (RFID) technology, on-board diagnostic system (OBD), and portable emission measurement system (PEMS) to study the performance of tractors in the real world. The actual operating modes, fuel consumption and emission levels of the tractor engine were studied and the braking thermal efficiency (BTE) under actual operating conditions was reported for the first time, with a maximum value close to 45%. The engine maps were developed and used to predict tractor emissions and fuel consumption, and the results showed that it can accurately predict tractor fuel consumption and carbon dioxide (CO2) emissions, with mean absolute percentage error (MAPE) and coefficient of determination (R2) values reaching over 90%. This article provides a reliable testing and prediction method for the actual performance of tractor engines, and suggests that real performance indicators should be given better attention.

Split injection strategy control map development through prediction-based calibration approach to improve the biodiesel-fuelled diesel engine characteristics.

Karanja oil blended with diesel acts as a good alternative for a CI engine due to its low emission and high oxygen content as compared to pure diesel which leads to the non-toxic and biodegradable nature of the fuel. The objective of this project is to enhance the performance and emission characteristics of a diesel engine that runs on biofuel by accurately calibrating its fuel injector control parameters. To achieve this goal, the project focuses on creating optimal split injector control maps using a novel global model-based calibration approach that considers the entire range of engine speed-load conditions. To develop the model, the experimentation was conducted using the I-optimal design of the experiment technique. To establish a relationship between the calibration parameters and engine performance parameters based on experimental data, the study employed response surface methodology (RSM). With the support of a developed model and multi-objective optimization approach under equivalent importance to performance and emissions, the optimum injector control points are derived. For the developed engine map for 20% KBD (Karanja bio-diesel)-blended fuel, the BTE (brake thermal efficiency) reaches up to 30% and lower BSFC (brake specific fuel consumption) of 0.37 kg/kW-hr. After optimization, the split injector control map showed significant improvements over the un-optimized map. At 19 Nm and 3000 rpm, the optimized map resulted in a 31.36% increase in BTE and a 29.31% decrease in BSFC. Moreover, the optimization successfully balanced the trade-off between reducing nitrogen oxide (NOx) emissions and smoke emissions. However, the optimized fuel map for 20% KBD-blended fuel shows slightly lower performance compared to diesel fuel. While the optimization process led to a decrease in smoke emissions about 22.3%, it also resulted in elevated NOx emissions about 9.83% when compared to diesel fuel. Furthermore, emissions of CO and HC are reduced by 12.8% and 19.2%, respectively, in an optimized control map of 20% KBD-blended fuel compared to un-optimized map.

Real Driving Cycle Simulation of a Hybrid Bus by Means of a Co-Simulation Tool for the Prediction of Performance and Emissions

This work is focused on the simulation of a complete hybrid bus vehicle model performing a real-world driving cycle. The simulation framework consists of a coupled co-simulation environment, where all the vehicle sub-system models are linked to achieve a real time exchange of input and output signals. In the vehicle model also the electric devices of the powertrain and accumulation system are included. This co-simulation platform is applied to investigate the hybridization of a 12-m city bus, performing a typical urban driving mission. A comparison between the conventional powertrain is performed against the hybridized version, to highlight the advantages and challenges. In particular, the novelty of this modeling approach is that the IC engine simulation does not rely on pre-processed look-up tables, but exploits a high-fidelity one-dimensional thermo-fluid dynamic model. However, it was necessary to develop a fast simulation methodology to exploit this predictive tool, achieving a low computational cost. The 1D engine model is first validated against the experimental engine map data available, showing a good model predictivity. Then the 1D engine model and the other models of the powertrain are coupled to the vehicle model, in order to follow the prescribed velocity profile of the driving cycle. The complete model is applied under different conditions, to evaluate the impact on performance and emissions and assess the simulation predictivity.

Numerical and experimental evaluation of the passive pre-chamber concept for future CNG SI engines

The third decade of the 21st century is set to be one of the most relevant in terms of the transition of methods and forms of using different energy sources, with short and medium-term developments on the road to decarbonization. One of the most widely accepted measures on this path is the reduction of CO2 emissions from internal combustion engines, which is why different concepts are being studied in order to optimize combustion. Furthermore, this research focuses on developing a suitable Spark-Ignition (SI) engine configuration integrating the passive pre-chamber ignition concept (TJI), together with a high compression ratio and the use of the Miller cycle, in order to exploit the benefits of using Compressed Natural Gas (CNG) as fuel. Thus, the novelty of this investigation is the detailed evaluation of the aforementioned SI engine architecture by state-of-the-art CFD simulations and a broad experimental campaign, to understand the advantages of the combined technologies against a conventional SI engine operating with gasoline. The pre-chamber technology is able to overcome the issues associated with the lower laminar flame speeds of CNG, and the reduction of turbulence caused by prematurely closing the intake valve with the Miller cycle. The experimental results showed that the new engine definition achieved higher levels of indicated efficiency compared to the baseline engine (around a 3% increase at high load/speed conditions). Moreover, the addition of EGR allows to further improve the engine performance, extending the load limit in the low-end torque region of the engine map. Finally, a full dynamic 1D model of a current passenger car vehicle was developed to perform transient driving cycle simulations, showing a reduction of 15% in fuel consumption and 25% in CO2 emissions for the new engine definition compared to the baseline engine.

Optimasi konsumsi bahan bakar pada mesin bensin menggunakan artificial neural network

The engine control unit (ECU) is the primary component of the current injection technique used in spark ignition (SI) engines. The combustion system, which includes injection timing and ignition timing, is controlled by the engine map recorded in the ECU. To maximize an engine's performance, ECU remapping can be used. Remapping is currently not efficient because the data is typically employed in a trial-and-error fashion. To solve these issues, artificial neural network (ANN) techniques are being developed. In this study, engine remapping for fuel economy optimization is predicted using an artificial neural network (ANN). The purpose of this study is to use ANN to compare motorbike performance between before and after engine remapping (Artificial Neural Network). A set of dynamometers is used in this study approach to assess the performance of the 4 stroke, 160 CC spark plug ignition engine in terms of fuel consumption, power, and torque. A current (standard) engine map that contains a number of data from the electronic control unit (ECU) is used to start the optimization process. Pertalite and Pertamax, which are purchased from the closest gas station, are the fuels used in this study. In addition, optimization utilizing ANN is carried out with the goal of 10% increases in torque and power while maintaining a consistent fuel consumption. Following re-implementation into the ECU, the outcomes of the ANN training will be tested again on the dynamometer. The study's finding is that by using the training function, it is possible to improve machine performance using the regression value of R = 0.98993 and the ANN prediction outcomes. Comparing the optimized engine performance to the factory default engine performance, torque increased 10.9% and power rose 9.5%.

Numerical Modeling and Simulation of a Spark-Ignition Engine Fueled with Ammonia-Hydrogen Blends

Carbon-free fuels, in particular ammonia and hydrogen, could play a significant role in the decarbonization of the mobility sector. In this work, the authors assessed the operation of a light-duty spark-ignition engine fueled with an ammonia–hydrogen blend (85% ammonia and 15% hydrogen by volume) using a 1D predictive model. Three-dimensional computations have been used in order to verify the reliability of the 1D model. The addition of hydrogen to the air–fuel mixture allows the operating capacity of the engine to be extended with respect to neat ammonia fueling. The engine can be properly regulated between 1500 rpm and 3000 rpm. Its operating range reduces as engine speed increases, and it cannot run at 6000 rpm. This is due to different engine operating constraints being exceeded. The maximum engine torque is about 240 Nm and is reached at 1500 rpm. The engine efficiency ranges between 42% and 19%, and the specific fuel consumption varies from about 350 g/kWh to about 750 g/kWh. The results provide both performances and operating ranges of the engine allowing us to define optimized engine maps obtained by means of a constrained optimization.

Mapping Cropland Extent in Pakistan Using Machine Learning Algorithms on Google Earth Engine Cloud Computing Framework

An actual cropland extent product with a high spatial resolution with a precision of up to 60 m is believed to be particularly significant in tackling numerous water security concerns and world food challenges. To advance the development of niche, advanced cropland goods such as crop variety techniques, crop intensities, crop water production, and crop irrigation, it is necessary to examine how cropland products typically span narrow or expansive farmlands. Some of the existing challenges are processing by constructing precision-high resolution cropland-wide items of training and testing data on diverse geographical locations and safe frontiers, computing capacity, and managing vast volumes of geographical data. This analysis includes eight separate Sentinel-2 multi-spectral instruments data from 2018 to 2019 (Short-wave Infrared Imagery (SWIR 2), SWIR 1, Cirrus, the near infrared, red, green, blue, and aerosols) have been used. Pixel-based classification algorithms have been employed, and their precision is measured and scrutinized in this study. The computations and analyses have been conducted on the cloud-based Google Earth Engine computing network. Training and testing data were obtained from the Google Earth Engine map console at a high spatial 10 m resolution for this analysis. The basis of research information for testing the computer algorithms consists of 855 training samples, culminating in a manufacturing field of 200 individual validation samples measuring product accuracy. The Pakistan cropland extent map produced in this study using four state-of-the-art machine learning (ML) approaches, Random Forest, SVM, Naïve Bayes & CART shows an overall validation accuracy of 82%, 89% manufacturer accuracy, and 77% customer accuracy. Among these four machine learning algorithms, the CART algorithm overperformed the other three, with an impressive classification accuracy of 93%. Pakistan’s average cropland areas were calculated to be 370,200 m2, and the cropland’s scale of goods indicated that sub-national croplands could be measured. The research offers a conceptual change in the development of cropland maps utilizing a remote sensing multi-date.

Emissions from a Euro 6 engine using polyoxymethylene dimethyl ethers: Chemical effects vs mapping strategy

New fuel technologies, such as electrofuels, are an attractive alternative to meet the energy demand and emission regulations, with sustainable electricity being the primary source of energy. Recently, there is increasing interest in using polyoxymethylene dimethyl ether (OME) as a diesel substitute. This study investigated the effect of a diesel fuel blend with 20% of OME (OME20) with 3–5 oxymethylene groups, on the performance, combustion characteristics, regulated emissions, particle number (PN), and particle size distribution in a compression ignition Euro 6 engine following the Worldwide harmonized Light vehicle Test Cycle (WLTC). Regulated emissions were measured downstream of the aftertreatment system, while PN emissions were measured upstream of the particulate filter. The results showed that OME20 increased the peaks of pressure and heat released rate, causing an increase in the combustion speed compared to diesel. OME20 reduced CO and THC accumulated emissions by 52% and 17%, respectively, and the PN exhibited a dramatic reduction close to 61%. Such reductions were influenced by both the fuel formulation and the engine settings induced by the fuel. With OME20, the engine requires higher fueling to maintain the same power output. Therefore, the accelerator pedal position was higher compared to diesel, leading a decrease in exhaust gas recirculation (EGR) rate to increase the air mass flow. Consequently, PN, CO and THC emissions were reduced, and conversely, accumulated NOx emissions increased up to 42%. OME20 decreased the peak number concentrations of accumulation-mode particles at all driving cycle phases and caused a slight shift of the particles toward smaller size compared to diesel fuel. From the results, it can be concluded that PN and regulated emissions, despite being strongly affected by the fuel properties, are very sensitive to the EGR rate and the equivalence ratio, which are established in the engine mapping.

Проект краткого курса «Избранные вопросы инженерии»

It is proposed to supplement the existing university courses "Introduction to Engineering" with a brief overview of the author's project-based learning course "Selected engineering issues". As an example, a five-day course plan is given. The course is intended for a general understanding of the specifics, structure and problems of engineering activities, and, according to the plan, should improve the mastering of the material of the Introduction to Engineering courses. The course has the format of a collective educational and project process, which is implemented in the cognitive infrastruc- ture of the situation center on the resources available to the organizers. Such a center can be set up outside the class- room using participants' smartphones. The cognitive environment is ensured by the presence of a support team consist- ing of a coordinator, a methodologist, a tablet keeper and a game technician. The functions of the support team can be performed by one specially trained teacher capable of reflexive perception of the learning situation. A constructor of course options is proposed, which includes various types of implementation processes. A variant of a metaphorical cog- nitive engineering map as a set of pictures and comments to them is proposed. The need for separate consideration of the setting tasks stages, working on bugs and opportunities for students to quickly access network resources and team- work technologies is noted. The author's "4C" approach (collective, cognitive, configurative, convergent) is used in combination with a cross-technology system that provides multidisciplinarity. The concept of mutual adjustment of students' cognitive profiles and teaching formats of academic subjects (visual, audio, kinesthetic, tactile) is also used. The use of the listed author's tools ensures the originality of the proposed solutions.

Detailed prediction of HRR and NOx emissions in CI engines via a novel thermodynamic model with constant equivalence ratio zones

This paper presents a novel, quasi dimensional-model for the simulation of the combustion process in compression-ignition engines. The model discretizes with a multiple number of zones the in-cylinder air-fuel mass on fixed values of local equivalence ratio, with the charge stratification determined from a 2D reconstruction via a one-dimensional control-volume-based spray approach. Reacting multi-zones are further split into three conceptual sub-zones: liquid, unburnt vapor and burnt vapor, in which chemical reactions proceed according to a tabulated kinetics of ignition (TKI) model. This approach provides a simple methodological framework for the combustion of direct injection of virtually every kind of liquid fuel and relies on a detailed phenomenological chemical/physical link of jet’s reacting phenomena. To account for engine geometry, a spray-wall interaction sub-model has been added to the axial spray. The model has been validated against experimental data and detailed CFD simulation results. First, the direct injection model (as a free jet) has been assessed with respect to ECN sprays A, C, and D experiments. For both the long injection and split injection cases, all the combustion phases are well predicted: premixed peak, mixing-controlled combustion, burn-out are seamlessly described and in good agreement with experimental and detailed CFD data. The wall interaction sub-model was validated with a suitable experiment where a reacting jet impinges on a mock-up wall inside a combustion vessel. Finally, the model has been validated against real heavy-duty engine experimental observations of 151 points of a complete engine map. The tuning of the model consists in two parameters, that are engine-specific, hence constant for the whole map. With these assumptions, the AHRR traces are well described in all simulated conditions. Mean predicted BSFC is only slightly underestimated (−2.3%), as it is the NOx production (−1.6%).

Energy efficiency improvements and CO2 emission reduction by CNG use in medium- and heavy-duty spark-ignition engines

This research studies the mechanism of improving energy efficiency and reducing CO2 emissions from medium- and heavy-duty spark-ignition engines by replacing gasoline fuels with natural gas. Detailed experimental analyses are conducted on a multi-cylinder research engine using 91RON, 98RON gasoline, and natural gas fuels. Under 7 key operating conditions, energy efficiency breakdown is performed for each fuel to quantify the individual impact of the fuel's carbon content, pumping work, knock tendency, and fuel enrichment. Complete engine mapping is thereafter carried out with all three fuels, and CO2 emissions are compared over the emission certification test cycle. As demonstrated by the test results, the lower carbon content of natural gas is the major contributor to CO2 emission reduction. At idle and part load conditions, engine operation on natural gas shows reduced pumping loss, improved idle stability, and thus increased fuel efficiency. At high load conditions, the greater resistance to knock allows natural gas to operate at optimal combustion phasing. At the peak power condition, the earlier combustion phasing helps to lower exhaust temperatures, thereby avoiding fuel enrichment. With proper calibration, natural gas outperforms its gasoline counterparts to produce 4% better peak power performance and emits 22.5% lower CO2 emissions.

Multi-Objective Optimization of Organic Rankine Cycle (ORC) for Tractor Waste Heat Recovery Based on Particle Swarm Optimization

Diesel engines are widely used in agricultural tractors. During field operations, the tractors operate at low speed and high load for a long time, the fuel efficiency is only about 15% to 35%, and the exhaust waste heat accounts for 38% to 45% of the energy released from the fuel. The use of tractor exhaust waste heat can effectively reduce fuel consumption and pollutant emissions, of which the organic Rankine cycle (ORC)-based waste heat recovery conversion efficiency is the highest. First, the diesel engine map is achieved through the test rig, a plate-fin evaporator is trial-produced based on the tractor size, and the thermodynamic and economic performance model of the ORC are established. Then, taking the thermal efficiency of ORC and the specific investment cost (SIC) as the objective function, the particle swarm optimization (PSO) algorithm and the technique for order of preference by similarity to ideal solution (TOPSIS) decision method were used to obtain the optimal operating parameter set under all working conditions. Finally, the results showed that the ORC thermal efficiency could reach a maximum of 12.76% and the corresponding SIC value was 8539.66 $/kW; the ORC net output power could be up to 8.31 kW compared with the system without ORC; and the maximum brake specific fuel consumption (BSFC) could be reduced by 8.3%. The improvement in the thermodynamic performance will lead to a sacrifice in economic performance, and at high speeds, the economic benefits and thermal efficiency reach a balance and show a better thermal economic performance. Recovering exhaust heat energy through ORC can reduce tractor fuel consumption and pollution emissions, which is one of the effective technical means to achieve “carbon neutrality” in agricultural production. At the same time, through the PSO algorithm, the optimal combination of ORC operating parameters is obtained, which ensures that the exhaust heat energy can be effectively recovered during the tractor field operation, and provides a basis for the adjustment of real-time work strategies for future research.

Effect of balance valve on exhaust pulse energy of a heavy-duty diesel engine equipped an asymmetric twin-scroll turbine

The exhaust pulse energy of engine is capable of driving the asymmetric twin-scroll turbine to run complicatedly in a wider flow range, which significantly causes more difficulty of an asymmetric twin-scroll turbine to match a diesel engine. In the present study, It was initially analyzed that an engine exhaust pulse energy of an asymmetric twin-scroll turbine with a balance valve. First, a pulsating flow model of asymmetric twin-scroll turbine was built to decouple the operation states of the small and large scroll turbines. Second, the experiments of asymmetric twin-scroll turbine were performed on a turbine test rig and an engine performance stand to determine the operation rules of turbine flow parameter, turbine efficiency, blade speed ratio, as well as turbine available energy. Asthe balance valve opens, the flow parameter of twin-scroll would perform more broadly around the swallow capacity curves of equal admission. Moreover, the fully-opened balance valve would make the exhaust pulse strength at the small and large scroll inlets sharply degrade by about 25% and 21%, the cycle turbine efficiency enhance by nearly 3%, the turbine available energy and BSFC degrade by about 8.15% and 2.9% at 800 rpm full load engine condition; At 1100 rpm full load engine condition, the exhaust pulse strength at the small and large scroll inlets only degraded by about 7.2% and 5.8%, the cycle turbine efficiency enhanced by about 4%, the turbine available energy and BSFC improved by about 3.7% and 2.1%. Lastly, this study delved into the distributions of the balance valve opening rate and the pulse strength at the small and large scroll inlets at full engine map.

Numerical analysis of the passive pre-chamber ignition concept for light duty applications

The use of advanced ignition concepts and enhanced combustion strategies is being widely studied for modern engine applications. In this framework, the passive pre-chamber ignition system is gaining popularity for its mechanical simplicity. However, in order to implement this ignition system in passenger car vehicles, the concept must be able to operate in the whole engine map. Numerous experimental investigations in the literature have found that the concept operates suitably at high load/speed conditions but has several problems operating at low engine load/speeds. However, not many investigation conducted to date have focused on comparing and understanding the underlying physics of this ignition strategy in different engine load/speed conditions. Therefore, in this investigation, a numerical study is carried out using a state of the art 3D-CFD model, to analyze the performance of the passive pre-chamber ignition system in three relevant operating conditions of the engine map. A novel methodology is developed to analyze the fundamentals of the passive pre-chamber concept in terms of internal flow field characteristics, combustion and energy conversion. The model is validated with experiments performed previously by the authors. In particular, the low load/speed operating point, representative of idle conditions, was deeply analyzed to asses the issues reported in the literature. Results have shown that the inherent deterioration of the flow field properties inside the pre-chamber as the engine load/speed decreases, compromises the operation at low load/speed conditions. The energy conversion in the pre-chamber is also worsened when operating at lower load/speeds, hindering the generation of suitable jets for igniting the main chamber charge. Moreover, the position of the pre-chamber in the cylinder head has a significant impact on the energy distribution in the main chamber. The results also revealed that a higher amount of non-reacting/cold flow is ejected from the pre-chamber as the spark is pushed from MBT conditions towards the top dead center (TDC), and the gap between the triggering of the spark and the onset of main chamber combustion increases. The findings of this article have allowed to close the knowledge gap between the physical characteristics of the passive pre-chamber concept and the experimental trends found in other researches on this topic.

Nucleation-accumulation mode trade-off in non-volatile particle emissions from a small non-road small diesel engine.

Small (< 8kW) non-road engines are a significant source of pollutants such as particle number (PN) emissions. Many small non-road engines do not have diesel particulate filters (DPFs). They are so designed that air-fuel ratio (AFR) can be adjusted to control visible diesel smoke and particulate matter (PM) resulting from larger accumulation mode particles. However, the effect of AFR variation on smaller nucleation mode nanoparticle emissions is not well understood. Several studies on larger engines have reported a trade-off between smaller and larger particles. In this study, AFR was independently varied over the entire engine map of a naturally aspirated (NA) non-road small diesel engine using forced induction (FI) of externally compressed air. AFR's ranged from 57 to 239 compared to the design range of 23-92 for the engine, including unusually high AFR's at full-load operation, not previously reported for conventional combustion. As expected, larger accumulation mode particles were lowered (up to 15 times) for FI operation. However, the smaller nucleation mode nanoparticles increased up to 15 times. Accumulation mode particles stopped decreasing above an AFR threshold while nucleation particles continuously increased. In-cylinder combustion analysis showed a slightly smaller ignition delay and higher burn rate for FI cases relative to NA operation. Much higher peak cylinder pressures were accompanied by much lower combustion and exhaust gas temperatures (EGT), due to higher in-cylinder mass during FI operation. Peak nucleation mode emissions were shown to be negatively correlated to EGT for all the data, collapsing on a single curve. This is consistent with some other studies reporting increased nucleation mode emissions (and higher accumulation mode particles) with decreased load, lower speed, lower EGR, advanced combustion phasing, and higher injection pressure, all of which reduce EGT. The nucleation-accumulation trade-off has been explained by the 'adsorption hypothesis' by some investigators. In the current work, an alternative/supplemental argument has been made for the possibility that lower cylinder temperatures during the late-burning phase (correlated to lower EGT) phase hampers oxidation of nucleation mode particles and increases nucleation mode emissions.