Engine Performance Parameters Research Articles

Experimental investigation of nano-enhanced Azolla biodiesel blends for improved diesel engine performance and emission mitigation

Abstract This study investigates the performance and emission characteristics of a diesel engine fueled with Azolla microphylla biodiesel blends and the effects of aluminium oxide (Al2O3) and copper oxide (CuO) nanoparticles as fuel additives. Azolla microphylla, an aquatic fern, was used to produce biodiesel through a transesterification process. Diesel fuel was blended with Azolla biodiesel in ratios of 10:90 (B10), 20:80 (B20), and 30:70 (B30). Engine performance parameters, including brake thermal efficiency (BTE), brake-specific fuel consumption (BSFC), and emissions of carbon monoxide (CO), hydrocarbons (HC), nitrogen oxides (NOx), and smoke, were evaluated. The results showed that the B30 blend exhibited the highest BTE under maximum load conditions. To address the high viscosity and poor combustion performance of higher biodiesel blends, Al2O3 and CuO nanoparticles were added to the B30 blend at concentrations of 50 ppm and 100 ppm. The B30 blend with 100 ppm Al2O3 nanoparticles demonstrated the highest BTE and the lowest emissions of HC, CO, CO2, and smoke compared to the other test blends. The improved combustion and reduced emissions were attributed to the enhanced heat transfer and catalytic properties of the Al2O3 nanoparticles. These findings suggest that Azolla biodiesel, especially when combined with Al2O3 nanoparticles, can be a viable and sustainable alternative to conventional diesel fuel.

Neural Network Prediction of Locomotive Engine Parameters Based on the Dung Beetle Optimization Algorithm and Multi-Objective Optimization of Engine Operating Parameters

Neural Network Prediction of Locomotive Engine Parameters Based on the Dung Beetle Optimization Algorithm and Multi-Objective Optimization of Engine Operating Parameters

Optimisation of performance and emission parameters of a CI engine fuelled with kapok oil methyl ester–turpentine oil blends and diethyl ether additive

The article aims to investigate the characteristics of compression ignition (CI) engines fuelled with blends of kapok oil methyl ester (KME) and turpentine oil (TO) with the inclusion of diethyl ether (DEE) as a fuel additive and the RSM has been used to analyse the engine characteristics. The design matrix is created for 50% to 100% loading and 30% to 70% blending in TO with kapok methyl ester. The experiment was conducted on a water-cooled 5.2 kW CI engine and 30%, 50%, and 70% of KME and TO blend. According to the test results, 50–50 KME and TO have a brake thermal efficiency of 29.13%. Another design matrix was designed for a load range of 50% to 100% and DEE of 0% to 20% in a 50 KT blend. The 50 KT blend with 20% DEE has the highest brake thermal efficiency (30.30%) and the lowest brake-specific energy consumption. The emissions of carbon monoxide, hydrocarbons, and smoke decrease to 8.25 g/kWh, 0.13 g/kWh, and 57%, respectively. The combustion process leads to the highest peak pressure and net heat release rate, which are 72 bar and 74.93 kJ/OCA, respectively. The outcome is 50–50% turpentine and kapok oil methyl ester blends, with 20% DEE have improved the performance and reduced the emissions.

EXAMINING THE ECO-FRIENDLY ASPECTS OF ETHANOL–METHANOL BLENDED GASOLINE ON ENGINE PERFORMANCE AND EMISSIONS

The increasing global demand for energy, environmental concerns, and the limited availability of energy resources have heightened interest in alternative fuels for internal combustion engines. In this context, internal combustion engines like gasoline engines play a significant role in the search for environmentally friendly and sustainable energy sources. Alcohols are among the most used alternative fuels in spark-ignition engines. This study examines the feasibility of using ethanol and methanol alcohols as fuels simultaneously in a gasoline engine. The research investigates the effects of blending 10% ethanol and 10% methanol alternative fuels with gasoline and using the resulting blended fuel as the engine's fuel source on motor performance and exhaust emissions. The study was conducted under throttle wide-open conditions at different engine speeds. The results revealed a maximum decrease of 1.3% in effective power. Significant reductions in hydrocarbon and nitrogen oxide emissions were observed at all engine speeds, with maximum reductions of 18% and 19%, respectively. Furthermore, a decrease in carbon monoxide emissions is evident across the entire spectrum of engine speeds, underscoring the potential of ethanol-methanol blended gasoline to contribute to a reduced carbon footprint in the transportation sector. As a result of the study, in the case of using ethanol and methanol in engines, both the higher oxygen content of alcohols and their high evaporation energy due to their cooling effect cause an improvement in the emission values emitted from the engine without significant deterioration in engine performance parameters.

Theoretical Analysis of Performance Characteristics of Non- road Spark Ignition Engines

Non-road spark ignition (SI) engines play a critical role in Nigeria, particularly in agriculture, construction, and small-scale power generation. Despite their extensive use, there is limited research on how Nigeria's unique environmental and operational conditions such as high ambient temperatures, poor fuel quality, and irregular maintenance practices affect the performance of these engines. This study presents a theoretical analysis of the performance characteristics of non-road SI engines under Nigerian conditions, focusing on fuel efficiency, power output, thermal efficiency, and emissions. The effect of engine speed, engine load and equivalence ratio on the performance characteristics of non-road spark ignition engines were studied in this research. Three operating parameters (engine load, engine speed, and equivalence ratio) and eight engine performance parameters which are Brake Specific Fuel Consumption (BSFC), Brake Power (BP), Thermal Efficiency (TE), Brake Mean Effective Pressure, Exhaust Gas Temperature (EGT), carbon monoxide emission, hydrocarbon emission, and nitrogen oxide were considered in this work. Theoretical analysis was performed using a two-zone SI engine model, the resulting equations were solved with the aid of a computer program developed by the authors and implemented in MATLAB software. The effect of the operating parameters on the performance parameters was simulated using the computer code developed which was implemented in MATLAB. The results show that the engine speed of 3000 rpm gave the optimum values of 250 g/kWh, 33 kW, 1070 kPa, 28% and 720 oC for BSFC, BP, BMEP, TE, and EGT respectively. Also, all performance parameters increased with an increase in engine load. The equivalence ratio of 0.9 gave the optimum values for all the parameters considered in this work. It can be concluded that for optimum performance of non-road SI engines, it should be operated at equivalence ratio of 0.9, engine speed of 3000 rpm and low engine loads.

Formation of a set of parameters for assessing the technical condition of autonomous power plants

Abstract. Problem. The object of study is the problem of creating a relatively simple diagnostic model of a diesel engine for an autonomous power plant in terms of the number of required input parameters. Goal.The aim of the study is to develop a diesel engine diagnostic system for an autonomous power plant. Methodology. To achieve this goal, the following tasks were solved: - to develop a method for synthesising a diagnostic graph model of a diesel engine for an autonomous power plant; - to propose a method for selecting the initial parameters of the diagnostic graph model of a diesel engine.The subject of the study is the relationship between the selected set of input parameters of the diagnostic model of a diesel engine and the adequacy of the response of the resulting model to real emergency situations. Results. As a result of the study, a methodology for synthesising a diagnostic graph model of a diesel engine of an autonomous power plant has been developed. The resulting model allows monitoring the performance of a diesel engine and adjusting the relevant parameters to achieve the required operating state or localise an emergency. Originality. The proposed method of synthesis of a diagnostic graph model of a diesel engine of an autonomous power plant, based on the use of the graph theory method, allows obtaining results that correspond to the actual state of operation of a diesel engine of a power plant with relative simplicity of use. This is achieved by using specially selected groups of diesel power control parameters as diagnostic parameters of the graph model. These indicators are available for measurement without significant dismantling and installation work, the use of complex measuring instruments, but can be measured during routine maintenance and operation. A methodology for selecting the output parameters of a diagnostic graph model of a diesel engine is proposed, which includes the process of forming the minimum required sample of parameters of diesel engine operation. Practical value. The following parameters have been selected as parameters for assessing the technical condition of power plant diesel engines and functionally related systems and circuits: power plant capacity; diesel crankshaft rotation frequency; fuel consumption; and a group of thermal parameters. This minimum required set of system state parameters makes it possible to link the diagnostic scheme for the studied technical condition of power plant diesel engines with their operational performance

SIMULATION OF TRACTOR ENGINE OPERATION IN GAS-DIESEL MODE

In modern conditions of fuel use in agriculture, it is necessary to diversify sources and use alternatives to the traditional use of petroleum products. However, there is a pressing issue that is actively being studied regarding the change in power when using a dual-fuel engine power supply system, since there is data on a slight decrease in this indicator, it was also established that the main parameters are preserved, the duty cycle and a significant increase in engine life. The purpose of the study is to simulate the main parameters of the engine in gas-diesel mode. A mathematical model of the duty cycle of the PowerTech 6068HF250 gas-diesel engine of the John Deere 7930 tractor has been created, which makes it possible to establish the operational and technological parameters of its operation. To determine the operating and technological parameters of the tractor engine in gas-diesel mode, for example, determining the LPG gas consumption and the ignition dose of liquid fuel and setting other control points, the thermal calculation of the engine according to the Grynivetsky -Mazing method using the Mathcad environment is informative and relevant. The obtained data were purposefully processed in the Microsoft Excel environment. This method allows to significantly improve the analysis of the operation of diesel engines in gas-diesel mode. When using the mathematical model of the operation of the PowerTech 6068HF250 diesel engine in the Mathcad 14 environment, it was found that the nominal power in the diesel cycle was 3.13% less than the declared engine power by the manufacturer. The obtained data allow us to state the conformity of the model we built. During the next simulation of the engine operation in the gas-diesel cycle, an increase in engine power was detected. An increase in engine power when using a mixture of fuels was also noted. This makes it possible to reduce the dose of consumed gas (LPG) fuel to such an amount that the power was equal to the nominal, which can be observed in the diagrams.

Possibilities of Improving the Emission Characteristics of Passenger Cars by Controlling the Concentration Levels of Combustion-Generated BTEX Components

Replacing the alkyl lead derivatives with aromatic hydrocarbons and additives in modern reformulated fuels to improve internal combustion engine performance, lower fuel consumption, increase power, and improve emission characteristics have resulted in the emission of large quantities of BTEX (benzene, toluene, ethylbenzene, and xylene) compounds into the atmospheric compartment. In this research, how the different working regimes of an experimental engine affect the BTEX compound concentration levels was observed to evaluate the quantities emitted during the movement of a passenger car in urban driving conditions. The target compounds were analyzed in exhaust gas samples using the Photovac Voyager-mobile GC (Waltham, MA, USA). This experimental research demonstrates that optimizing engine operational parameters significantly reduces the concentration levels of BTEX compounds in exhaust gas mixtures by adjusting specific working regimes, contributing to better emission characteristics and promoting sustainable transportation solutions. The most significant effect of the independent increase in air quantity in the feed mixture is realized through the decrease in concentration levels of toluene in the exhaust gas mixture of approximately 81%. A significant reduction in concentration levels is achieved with m,p-xylene (79%) and o-xylene (79%) as well, whilst the lowest effect has been noted with benzene (73%) and ethylbenzene (71%).

Machine learning application to forecasting performance and thermodynamics parameters of small turbojet engine

Machine learning application to forecasting performance and thermodynamics parameters of small turbojet engine

Methods and equipment for analysis and diagnosis of marine engines during navigation

ABSTRACT Expert diagnostic systems are required for the development of intelligent marine engines and other ship systems. Measurement and analysis of marine engine parameters are fundamental in ensuring the efficient operation of these key propulsion systems. This paper introduces a novel measurement device and method capable of real-time monitoring of cylinder pressure and emissions in marine engines. The experimental procedure involved measuring critical engine parameters and emissions, such as NOx, CO2, and particulate matter, under various operating conditions. The device provided accurate real-time data acquisition, enabling detailed analysis of combustion processes and emission profiles under various operating conditions. Furthermore, a numerical model was developed, like digital twins, which utilized the measured data to simulate engine performance, predict potential failures, and optimize operational parameters to enhance efficiency and reduce environmental impact. The two most important parameters: the indicated cylinder pressure and NOx emissions were simulated and validated. Measured NOx was measured 889 ppm at 90% and simulated results was 985 ppm, which is 10% difference. Specific fuel consumption has less than 1% difference between measured and simulated data. Novelty of this work is the methodology used in the testing and calibration processes. Current actual parameters of engine operation are monitored, based on which a comparative analysis is made in real time. Previous diagnostic control systems did not provide diagnostics, comparative analysis and optimization in real time. The integration with digital twin allowed potential wear and tear predictions, fuel consumption optimization, and emission reduction strategies, showcasing the potential of this technology to improve marine engine diagnostics and maintenance. The device and its virtual counterpart worked well together to provide a complete understanding of the engine’s response. This facilitates proactive maintenance strategies and contributes to eco-efficiency in the maritime sector.

Effect of engine parameters on the mixture distribution, performance and emission characteristics of a gasoline direct injection engine with baffles – A numerical analysis

Baffles inside the combustion chamber of internal combustion (IC) engines improve in-cylinder mixture distribution, performance, and emission characteristics. However, the effect of engine operating parameters on these aspects of the engine with baffles (EWB) remains underexplored. In this study, using computational fluid dynamics (CFD), the effects of fuel injection pressure (FIP), engine speed and load in a spray-guided, gasoline direct injection engine (GDI) are analysed and compared with the conventional engine. For the analysis, injection pressures of 30, 50, 80, and 120 bar; engine speeds of 1000, 2000, and 3000 rev/min.; and overall equivalence ratios of 0.7, 0.9, and 1.2 are considered, keeping the fuel injection timing constant. Results show that, EWB outperforms the conventional engine under various conditions considered. Also, it is found that the performance of EWB at an FIP of 30 bar is comparable to that of the base engine at an FIP of 80 bar. Additionally, the EWB exhibits better thermal efficiency across all the engine speeds and load conditions. Moreover, the HC and CO emissions of the EWB are found to be lower in most engine operating conditions. However, NOx emissions are marginally higher than those of the base engine.

The operating parameter optimization of spark duration effect on the performance and emission characteristics of direct-injection propane by genetic algorithm

It is challenging to optimize of the effect of spark discharge duration on low carbon direct injection combustion of propane from a specific aspect of the internal combustion engine. The strategy in this paper combines a genetic algorithm (GA) with an artificial neural network (ANN) to enhance efficiency of a large bore diesel engine modified with spark plug and fueled with propane direct injection under various spark timing durations and identify its engine performance parameters and corresponding conditions for operational control purpose. In-cylinder performance experiments were used to create 756 datasets for training, testing, and validating the ANN with 16 neurons on each hidden layer, respectively. The selected performance parameters were the heat release rate, turbulent kinetic energy, indicated mean effective pressure, and indicated thermal efficiency. The NOx and CO emissions are improved by 7.14 % and 0.74 %, respectively, by the optimized ANN model. In addition, compared to an experimental result, the model improves the indicated thermal efficiency, heat release rate, and indicated mean effective pressure by 1.35 %, 0.37 %, and 0.04 %, respectively. The combined of ANN-GA is effective in identifying the optimal operating parameters for in-cylinder performance and emission.

To Enhance the Performance of CI Engine with Using of Additives Based Hybrid Bio Fuel—A Review

AbstractThe growing demand of sustainable and environment friendly energy sources has spurred research and development efforts towards the integration of biofuels in various applications, particularly in internal combustion engines. Microemulsion technique is a new and innovative alternative to traditional fossil fuel that has gained a significant attention in recent years. This type of bio fuel is made by blending of small amount of biofuel and large amount of conventional diesel fuel. This review paper explores the potential of enhancing the performance of Compression ignition (CI) engines by incorporating additives into hybrid biofuels. The study focuses on the synergistic effects of combining traditional fossil fuels with bio‐derived components, such as ethanol, biodiesel, and other bio‐based additives. This review paper aim is to explore the performance of a 4‐stroke, single‐cylinder, direct injection Compression Ignition (CI) engine at different loads using different fuels blends like CNWEDB, BFNP150, PPNP150, and ME Diesel/Colza oil. The review outlines recent advancements in biofuel technology, including novel production methods and feedstock options, aiming to overcome limitations associated with conventional biofuels. The article aims to investigate the potential of vegetable oil in formulating MHBF, analyzing its performance and emissions in CI engines. The engine performance parameters viz., brake thermal efficiency brake specific fuel consumption have been reviewed and found that these values are comparable to the biodiesel blends with pure petrodiesel. At 60%, 80%, and full load condition the BTE of microemulsion diesel/colza oil is increasing while at 40%, 80%, and full load the BSFC is decreasing. Emissions reported by the various researchers, however, have a positive attribute with respect to NOx, CO, and UHC. At full load CO is decreasing and at all load conditions the value of UHC is decreasing. The paper concludes with a discussion on future research directions, emphasizing the need for continued innovation to address emerging issues and optimize the performance of CI engines for a sustainable and energy‐efficient future.

Evaluating Ammonia-Diesel Blends in Engine Operations: Performance and Stability Impacts

Abstract This study investigated the effects of incorporating ammonia into diesel engine operations, focusing on its impact on performance and stability. Ammonia was introduced into the engine via the intake air. By varying ammonia ratios at different engine speeds and under full load conditions, it was found that ammonia integration could be achieved without stability issues up to an energy fraction of 54%. However, exceeding this threshold resulted in misfire occurrences during engine operation. Notably, lower energy ammonia fractions below 40% led to increased power output, while higher fractions caused power reduction. Additionally, consistent reductions in brake-specific energy consumption were observed with ammonia supplementation. Variations in in-cylinder pressure were directly correlated with power output changes. Peak pressure initially increased with ammonia but decreased beyond 40% energy sharing, with its location consistently retarded. Moreover, ammonia induction led to longer ignition delays and altered combustion phasing across all engine speeds, indicating its significant influence on engine operating parameters.

Clarifying the impact of engine operating parameters of heavy-duty diesel vehicles on NOx and CO2 emissions using multimodal fusion methods

The issue of air pollution from transportation sources remains a major concern, particularly the emissions from heavy-duty diesel vehicles, which pose serious threats to ecosystems and human health. China VI emission standards mandate On-Board Diagnostics (OBD) systems in heavy-duty diesel vehicles for real-time data transmission, yet the current data quality, especially concerning crucial parameters like NOx output, remains inadequate for effective regulation. To address this, a novel approach integrating Multimodal Feature Fusion with Particle Swarm Optimization (OBD-PSOMFF) is proposed. This network employs Long Short-Term Memory (LSTM) networks to extract features from OBD indicators, capturing temporal dependencies. PSO optimizes feature weights, enhancing prediction accuracy. Testing on 23 heavy-duty vehicles demonstrates significant improvements in predicting NOx and CO2 mass emission rates, with mean squared errors reduced by 65.205 % and 70.936 % respectively compared to basic LSTM models. This innovative multimodal fusion method offers a robust framework for emission prediction, crucial for effective vehicle emission regulation and environmental preservation.

Empirical study on butanol-ethanol-gasoline blends using Artocarpus heterophyllus peel resource for eco-friendly gasoline engine application

Since using current engine fuels contributes to climate change and global warming, there is intense competition to provide an ecologically friendly and less harmful substitute fuel. It proved to be rather feasible to mix engine-designed fuel with alcohol fuel. In this work, the peel of Artocarpus heterophyllus is used to produce the bioethanol. In three ratios—10 % butanol-ethanol + 90 % petrol (BEG10), 20 % butanol-ethanol + 80 % petrol (BEG20), and 30 % butanol-ethanol + 70 % petrol (BEG30)-butanol-ethanol and petrol were mixed in the present work. Using a four-stroke, spark ignition (SI) engine one-cylinder, the effect of the butanol-ethanol-gasoline combination on operational properties was examined and studied. Three test fuels (BEG10, BEG20, and BEG30) were studied in the engine speed range of 2500 rpm to 4500 rpm. The best practical responses found were brake thermal efficiency (43.21 %) and brake-specific fuel consumption (0.23 kg/kWh). The findings showed that more significant concentrations of ethanol-butanol improve the performance characteristics. In the end, engine emission parameters such as hydrocarbon (40 %), carbon monoxide (25 %), and nitrogen oxide (5.88 %) were reduced by the butanol-ethanol combination with petrol. Artificial neural network (ANN) models of multiple regression are used to forecast the engine performance parameters. An ANN model is trained using a database produced from the experimental findings. It shows that the suggested artificial neural network model can provide a precise correlation between input variables and output replies. The input parameters like Speed, Load, and Blend were predicted using the identified model. The R2 (0.9638, 0.9735) value of BTE and BSFC obtained indicated that the neural network approach model generated was more accurate for the prediction process. ANN application is thus a superior forecasting tool for SI engine performance characteristics.

Multi-objective Optimization of Diesel Engine Operating Parameters Under Highway Drive Conditions

Abstract Experimental and optimization work is carried out to study the effects of fuel injection pressure, boost pressure, pilot injection timing, pilot injection quantity and main injection timing as input parameters. A four-cylinder, automotive model direct injection diesel engine, incorporated with a variable-geometry turbocharger, was chosen for the experiment. Engine test runs are conducted at a driving condition of 80.3 Nm torque and an engine speed of 1750 rpm, respectively, corresponding to highway driving conditions, using 10 % of exhaust gases recirculated. The Response Surface Methodology is employed to design experiments and analyze the experimental data to optimize engine parameters, considering the mentioned parameters as input parameters. A multi-objective response approach is adopted to optimize engine-operating parameters to obtain desired performance and engine-out emissions. Confirmatory tests are conducted at design conditions to validate the results predicted by the model. It is observed that for the chosen engine configuration, the optimum performance and emission characteristics could be obtained with 120 kPa boost pressure, 61.1 MPa fuel injection pressure, and 11.5 % of total fuel amount as pilot injection and remaining as main injection quantity at 332° and 359° crank angle, respectively. Overall. fairly better engine performance was observed with the use of selected ranges. It is noted that with the procedures adopted, improved engine performance and a significant reduction in harmful emissions are obtained without using major add-ons. The investigation revealed excellent potential for a diesel engine to be an effective prime mover.

Experimental investigations on the performance and emission characteristics of hydrogen enriched Bio-CNG in a common rail direct injection dual fuel diesel engine

The current energy and environmental problems demand the replacement of fossil fuels with renewable fuels. Research shows that hydrogen-enriched CNG fuels enhance the thermal efficiency of diesel engines while reducing gaseous emissions. This experimental work investigates the performance and emissions parameters of a diesel engine in dual fuel mode with hydrogen-enriched Bio-CNG (HBCNG). It is performed on a single-cylinder, four-stroke common rail direct injection (CRDI) diesel engine at 1500 rpm and 3.5 kW. The outcomes of this experiment are compared to a neat diesel operation. It is observed that at low load with 30% gaseous fuel substitution (GFS), brake thermal efficiency decreases by 13.70% and 15.53% for hydrogen and BCNG-enriched diesel, respectively. Similarly, at medium load, with the gaseous mixture of 40% H2 and 60% BCNG co-combusted with 60% diesel, the BTE improves by 15.83%. At high load, 40% gaseous fuel mixture (40% H2 + 60% BCNG) combustion with diesel results in 21.25% enhanced BTE. Moreover, at the same load condition and GFS, emissions of HC increase by 41.59%, CO decreases by 30%, CO2 decreases by 55.36%, and NOx decreases by 25.94%.

Effect of Piston Geometry on Performance Characteristics of VCR Engine with and without EGR when Fueled with Blends of Methyl Ester

The growing population and exhaustion of fossil fuels necessitate our search for new sources of energy. The study for this research encompasses an amalgamation of interest in alternative fuels, advanced engine technology such as variable compression ratio VCR, engine component modification, and a methodical approach to testing for assessing the effects on key performance of the engine. A 3.5 kW compression ignition (CI) engine was fueled with blends of behada, chicken fat, and turmeric oil methyl ester. Engine operating parameters, such as the compression ratio (CR), rate of exhaust gas recirculation (EGR), and piston top geometry, are optimized to maximize engine performance. CI engine was modified by changing the piston head (square and tangential groove top) for methyl ester diesel blend operations. In the study, diesel fuel is designated as B00 and methyl ester as B20. The influence of compression ratio (CR16 and CR18) with exhaust gas re-circulation (EGR 0% and EGR 10%) was evaluated. The key performance indicators: brake thermal efficiency (BTE), brake-specific energy consumption (BSEC), brake-specific fuel consumption (BSFC), air-to-fuel ratio (AFR), and exhaust gas temperature (EGT) are investigated. Results indicate that an increase in BTE accompanies an increase in load, suggesting enhanced thermal efficiency with increased power output. The consequence of VCR is also investigated, and it is determined that a higher CR results in a higher BTE due to an increase in compression pressure and temperature, thereby enhancing combustion. Due to the re-combustion of unburned hydrocarbons with the addition of EGR at a 10% rate, BTE increases further. Utilizing a piston geometry with tangential grooves and methyl ester blends also contributes to increased BTE. BSEC increases with increasing load, with an important rise observed when operating at maximum capacity. However,at CR 18, BSEC decreases as a result of enhanced combustion efficiency. EGR has different effects on BSEC depending on the geometry of the piston and the kind of fuel used. Enhanced air-fuel blending and re-combustion of unburned hydrocarbons reduce the BSEC of the engine. The tangential groove top piston operates with 10% EGR. Similar to BSEC, BSFC decreases with increasing CR and improves with the use of a piston with a tangential groove and 10% EGR operation. AFR decreases as the consumption of fuel increases to meet the power demand, and higher CR values result in a lower AFR. EGT rises with load, and CR18 has a lower EGT than CR16 as a result of a higher compressing temperature and pressure. 10% EGR operation reduces EGT by decreasing the concentration of oxygen in the combustible area.

Influence of the air–fuel-ratio and fuel on the reactivity of diesel soot

This work deals with the influence of the variation of the air–fuel-ratio on the emissions as well as on the soot reactivity of a commercial vehicle diesel engine. The emissions and the associated soot reactivity are compared between conventional fossil diesel fuel and the regeneratively produced paraffinic diesel fuel HVO (hydrotreated vegetable oils). All investigations were carried out on a single-cylinder engine and the gaseous and particulate emissions were recorded. Additionally, the collected engine out soot samples were analyzed by thermogravimetric balance (thermogravimetric analysis = TGA) to determine the reactivity of the soot. Regardless of the set engine operating point, it was shown that the particulate mass is significantly reduced when operating with HVO compared to fossil diesel fuel. Other gaseous emissions are also minimally lower compared to fossil diesel. In contrast, however, the HVO fuel has an increased number of particles due to smaller particles. The variation of the engine operating parameters showed the same tendencies with regard to soot reactivity, regardless of the fuel used. However, the parameter variations were more or less pronounced depending on the respective fuel. It is particularly noticeable that the reactivity of soot, which is produced when using HVO, is reduced at every operating point despite the lower particulate mass compared to fossil diesel fuel.