Specific Fuel Consumption Research Articles

Performance prediction and multi-objective optimization for the Atkinson cycle engine using eXtreme Gradient Boosting

In this study, substantial efforts have been done to enhance both the economy and nitrogen dioxide (NOx) emission characteristics of an Atkinson cycle engine (ACE). The integrated simulation model was meticulously formulated and calibrated utilizing GT-Power software based on test data, and four machine learning (ML) models were developed to predict the performance of the ACE. On this basic, the improved multi-objective hybrid particle swarm optimization (IMHPSO) algorithm was proposed to conduct comprehensive optimization of ACE performance. The results highlight the superior prediction performance and generalization ability of the eXtreme Gradient Boosting (XGBoost) model, attaining an average coefficient of determination (R2) of 0.9978 and 0.9966 on the train and test sets, respectively. The IMHPSO algorithm exhibited efficient convergence, uniform distribution and rich diversity across five benchmark test problems, effectively mitigating issues related to local optima and premature convergence. The Optimal Brake Specific Fuel Consumption (BSFC) solution is chosen as the preferred optimized scheme and realizes significant reductions of 8.5 % for BSFC and 96.1 % for NOx emissions, which experiences a remarkable increase of over 1300 times in computational efficiency compared to the GT-Power model. These findings provide theoretical basis, data support and novel insights for multi-objective optimization of ACE performance.

A highly efficient and cost-effective liquid biofuel for agricultural diesel engines from ternary blending of distilled Yang-Na (Dipterocarpus alatus) oil, waste cooking oil biodiesel, and petroleum diesel oil

This study reports a highly efficient and cost-effective liquid biofuel for agricultural diesel engines by a ternary blending of waste cooking oil (WCO) biodiesel, distilled Yang-Na oil, and petroleum diesel oil. Biodiesel oil from WCO synthesized by NaOH-catalyzed pilot plant-scale solar reactor exhibited fuel properties that met ASTM-D6751 and EN-14214 standards. Crude Yang-Na was distilled at 280 oC to obtain distilled Yang-Na oil with major components of α-Gujernene (63.07 wt.%), α-Caryophyllene (19.08 wt.%), γ-Gujernene (5.16 wt.%), and γ-Elemene (5.23 wt.%), along with 7.46 wt.% of other hydrocarbon compounds. The ternary blendings of waste cooking oil (WCO) biodiesel, distilled Yang-Na oil, and petroleum diesel oil were formulated (50:30:20 and 50:25:25) and their physicochemical properties were evaluated and compared with a commercial B10 petroleum diesel oil. The formulated liquid biofuels met standards and closely resembled petroleum diesel with a viscosity of 3.86 cSt, density value of 876 kg m-3, and heating values of 9991 kcal/kg. The performance testing of the blended fuels in a small agricultural diesel engine showed the efficiency levels matched with a commercial B10 petroleum diesel oil and outperformed individual biodiesel and distilled Yang-Na oil. Variances in Brake Power and Brake Specific Fuel Consumption were <1% with low emissions of CO2, CO, HC, and NOx, while Engine Torque and biofuel consumption during cultivation showed differences of 3.42% and 2.54%, respectively. Accordingly, the obtained blended fuel is a promising option for community resource utilization, offering an alternative energy source for future communities.

A COMMERCIAL TURBOFAN ENGINE MODELING AND EXERGY ANALYSIS

Turbofan engines are one of the most common types of engines used in modern commercial and military aircraft due to their efficiency and performance characteristics. In this study, a thermodynamic model is generated using GasTurb 14 software for a commercial two-spool, unmixed flow, and booster turbofan engine (CFM56-5A3) used in Boeing A320-212. Besides, an exergy analysis of the modeled turbofan engine is performed. Exergy performance criteria such as exergy efficiency, exergy development potential, exergy destruction ratio, productivity lack ratio, and fuel depletion ratio are evaluated for the engine components. In addition, how bypass ratio (BPR) affects net thrust and specific fuel consumption (SFC) for the modeled turbofan engine is investigated. As a result, the net thrust and SFC values of the modeled engine and the actual engine are overlapped with 14.0% and 7.2% deviation, respectively. The maximum exergy efficiency occurs at the high-pressure turbine as 0.992. When the bypass ratio is minimum, the maximum net thrust and SFC occur as 62.24 kN and 24.08 g kN-1 s-1, respectively. High pressure turbine has the minimum exergy development potential of 1528.5 kW.

Engine performance and emission characteristics of microwave-produced biodiesel blends

The main objective of this research is to investigate, experimentally, the effects of biodiesel blends on the performance and emissions of a Diesel engine. Measurements were carried out on a single-cylinder, four-stroke, and air-cooled compression-ignition engine, under half and full load conditions. Engine speed was varied from 1000-3000 rpm. Biodiesel was produced by transesterification process of sunflower oil with ethanol, using microwave-assisted heating reactor. Three biodiesel-diesel mixtures: containing 5%, 10%, and 20% by volume of biodiesel, respectively, have been tested and compared to pure diesel fuel. The effects of these biodiesel blends on the engine operating characteristics such as brake specific fuel consumption, brake power, brake thermal efficiency, brake mean effective pressure, and on carbon CO, CO2, and NOx emissions, have been investigated. It was noticed that, at full load, the specific fuel consumptions of biodiesel blends were higher compared to the pure diesel fuel, but no change was observed under ? load. An improvement in the brake thermal efficiency, under ? load, was obtained, but at full load, for medium and high speed, the thermal efficiencies of all biodiesel blends showed a decrease compared to pure diesel fuel. Concerning pollutants emissions, a decrease in CO emissions of all biodiesel blends was noticed. The best result in CO emissions was achieved by the mixture containing 10% by volume of biodiesel with an average reduction value close to 40%. In addition, a significant reduction in NOx emissions was observed for the three biodiesel blends.

Unjuk Kerja Mesin Diesel Berbahan Bakar Campuran Biodiesel Jatropha- Jelantah 1:9

In the context of a rapidly growing industry and increasing energy needs, the dwindling sources of fossil fuels prompt the necessity for alternative fuels. This study focuses on the performance of diesel engines running on a blended biodiesel made from jatropha oil and waste cooking oil in a 1:9 ratio. The aim of this study is to investigate the effects of biodiesel fuel made from jatropha oil and waste cooking oil on diesel engine performance and fuel physical properties. The tests include an evaluation of the fuels physical properties, injection characteristics, engine speed, generated power, and specific fuel consumption (SFC). Results indicate that although this blended biodiesel has higher density and viscosity compared to diesel, it offers promising calorific value and spray angle. Moreover, engines using this fuel showed relatively stable engine speeds and power outputs, along with efficient SFC at higher loads. The jatropha-waste cooking oil biodiesel blend shows potential as a sustainable and environmentally-friendly alternative fuel

Comparison of Engine Performance and Emissions for W20 and P20 Methyl Ester Blends as Fuel

Demand for energy in transportation, industrial and other energy sectors has led to the huge consumption of fossil fuels. This has directly affected on climatic issues, global warming as well as financial status of a country. In order to reduce these problems biofuels have been used in the engines. The present work reports the performance and emission studies conducted on an engine for W20 (waste cooking oil methyl ester 20% + diesel 80%) blend and P20 (pongamia methyl ester 20% + diesel 80%) blends on volume basis tested on a single cylinder 4-stroke water cooled compression ignition direct injection engine. At 2.2kW engine loading Brake Thermal Efficiency (BTE) for W20 and P20 blends are 2.11% and 5.92% lesser than that of diesel fuel. Brake Specific Fuel Consumption (BSFC) for W20 and P20 blends are 2.386% and 0.198% higher than that of diesel respectively. Exhaust Gas Temperature (EGT) for W20 and P20 blends are 6.89% and 3.44% greater than that of diesel respectively. Carbon Monoxide (CO) emissions for W20 and P20 blends are 0.046%, 0.04% lower, Carbon Dioxide (CO2) emissions for W20 and P20 blends are 0.33% and 0.18% higher than that of diesel respectively. Hydro Carbon (HC) emissions for W20 blend is 56% higher and P20 blend is 12% lower when compared with diesel. Oxides of Nitrogen (NOx) for W20 and P20 blends are 18.87% and 1.72% larger than that of diesel. Therefore, P20 blend fuel is good when compared to W20 blend fuel.

Experimental Investigation of the Effects of Gasoline-Methyl Ethyl Ketone Fuel Blends on Engine Performance and Exhaust Emissions

Gasoline engines have been widely used because of operating with stoichiometric ratio and lower exhaust emissions compared to compression ignition engines. However, thermal efficiency is less than diesel engines due to lower compression ratio. In the present study, the influences of methyl ethyl addition were researched on engine performance, CO, CO2 and HC emissions in a single cylinder spark ignition engine. For this purpose, the test engine was run at wide-open throttle, engine speeds of 2400, 2800, 3200, 3600, 4000 rpm and the variations of engine torque, effective power, specific fuel consumption (SFC), thermal efficiency, CO, CO2 and HC emissions were investigated. It has been observed that engine power and torque increase and SFC decreases as methyl ethyl ketone is added to gasoline. It was observed that the thermal efficiency at 2800 rpm increased by 6.47%, 13.81% and 19.51%, respectively, with MEK20, MEK30 and MEK40 test fuels compared to gasoline. As the methyl ethyl ketone ratio in the blended fuels increased, HC and CO emissions reduced compared to gasoline. As a result, it was seen that methyl ethyl ketone additive can be utilized easily in a spark ignition engine without making any modification.

Parametric Characterization of a Tractor Engine by Specific Fuel Consumption

The paper highlights that equipping agricultural mobile machines with sensors and electronic controls enables the remote acquisition of real-time information regarding the technical condition of engine systems while operation. (Research purpose) The objective of this research is to formulate a methodology for determining the multi-parameter characteristics of specific effective fuel consumption. This is illustrated through an examination of the Deutz BF 6M 2012 C engine, installed in the of the Terrion ATM 4200 tractor. (Materials and methods) The electronic control system was examined through data analysis. Utilizing Logic Analyzer 8, a connected logic analyzer, facilitated the extraction of a multi-parameter characteristic related to the specific fuel consumption of the engine. This data was obtained from the CAN bus while the machine was in operation. A statistical data processing method was developed using the Statistica 10 program. Regression equations were formulated to illustrate the correlation between fuel consumption, crankshaft speed and engine torque. The statistical significance of the relationship between fuel consumption across the entire range of operating modes and the selected parameters was corroborated by the values of the coefficient of determination and Fisher’s criterion. (Results and discussion) The data from the multi-parameter characteristic, illustrating the correlation between fuel consumption, engine speed, and torque, aligns with the information provided by the manufacturing plant. This alignment further validates the accuracy of the derived regression equations. (Conclusions) The suggested sequence of steps for obtain a multi-parameter characteristic can be applied to other engine performance indicators. Monitoring operational performance to analyze information on the technical condition of machine components and assemblies is necessary for diagnostics and ensuring timely maintenance and repair.

Numerical investigation for performance and emission characteristics of a diesel engine fueled with soybean methyl ester biodiesel - Diesel blend

The usage of conventional fossil fuels is reducing day by day due to the overwhelming use of business and personal automobiles for transportation, delivery, and ambulance. Factories also require conventional fuels to run their machines, which serve the primary purpose of production and factory operation. As a result, conventional fuels have a wide range of applications in our daily lives. However, there are certain downsides to utilizing traditional fuels, such as increased pollution, which adds to an increase in the temperature of the globe, causing global warming. Alternative fuels not only minimize pollution but also do not impair vehicle performance. There are other forms of alternative fuels available, including biodiesel, electricity, and solar energy, which have already gained popularity. This paper focuses on SME (Soybean Methyl Ester) as an alternative biofuel and provides a full review of the fuel by running it through an engine virtual simulation. The biofuel is combined with 20% and 80% diesel mixtures. The virtual simulation revealed that the brake thermal efficiency (BTE) and Brake Specific Fuel Consumption (BSFC) of diesel and SMEB20 is nearly identical. SMEB20 emit more NOx and CO2 than diesel under all load whereas emit less particulate matter (PM) and smoke emission than diesel under all engine load.

Performance Simulation of Thermodynamic Design for a New Turboshaft Engine

For a search and rescue (SAR) helicopter, the requirements of long-range and twin-engine are becoming increasingly important. In this paper, the overall performance of a new turboshaft engine for SAR helicopters is simulated. Firstly, the main performance parameters of competitor engines are collected and compared, and the thermodynamic cycle parameters of the new engine are proposed subsequently. Then, an engine model is created in Turbomatch and the overall performance of this model at the design point is calculated. Finally, the off-design performances at different conditions of output power, ambient temperature, altitudes and flight Mach numbers (Ma) are investigated. A strategy of variable stator vane (VSV) for the anti-surge control of the axial compressor is also introduced. The results of the performance simulation indicate that this engine is quite competitive with lower specific fuel consumption (SFC) and higher specific power (SP) compared to the current SAR helicopter engines.

Artificial Neural Network-Based Modeling of Performance Spark Ignition Engine Fuelled with Bioethanol and Gasoline

Machine learning technology can distinguish the relationship between engine characteristics and performances. Therefore, the goal of the present work is to predict the performance parameters of a single-cylinder 4-stroke gasoline engine at different ignition timings using a blended mixture of gasoline and bioethanol by an artificial neural network (ANN). Experimental data for training and testing in the proposed ANN was obtained at a dynamic speed and full load condition. An ANN model was developed based on standard Back-Propagation algorithm for the spark ignition engine. Multi-layer perception network (MLP) was used for non-linear mapping between the input and output parameters. An optimizer in the family of quasi-Newton methods (lbfgs) and the rectified linear unit function were used to assess the percentage error between the desired and the predicted values. The network input parameters are engine speed, fuel, and ignition timing. Furthermore, torque, power, specific fuel consumption (SFC), thermal efficiency (ηth), and energy consumption (EC) are taken as output parameters. The results show that ANN is the proper method for predicting SIE performance because it has accurate prediction results that are very similar to experimental results. Moreover, from the observation results, the ANN model can predict the engine performance quite well with correlation coefficient (R)=0.962139 and MSE=0.003967 for data testing.

Correlation between Physical Properties and Specific Fuel Consumption in Jatropha -Used Cooking Oil Biodiesel Mixtures

This study was motivated by the need to understand the influence of using waste jatropha biodiesel on the physical properties of fuel and the performance of diesel engines. The primary aim was to determine the relationship between the fuel's physical properties, spray angle, and specific fuel consumption (SFC) at various load levels. The methodology employed included measurements of density, viscosity, flash point, calorific value, spray angle, and SFC for different blends of waste jatropha biodiesel and diesel (B5, B10, B15, B20). The research results demonstrate an increase in density, kinematic viscosity, and flash point, along with a decrease in calorific value, as the biodiesel content increases. The density of the biodiesel mixture ranges from 823 kg/m³ at B5 to 836.50 kg/m³ at B20. The kinematic viscosity increases from 3.9 cSt at B5 to 5.2 cSt at B20, and the flash point rises from 112.9°C at B5 to 128.7°C for B20. Meanwhile, the calorific value decreases from 10308.2670 cal/g at B5 to 10133.8280 cal/g for B20. A strong correlation exists between density and kinematic viscosity with the spray angle, exhibiting R2 values of 0.9141 and 0.8287, respectively. The correlation between the fuel's physical properties and the specific fuel consumption (SFC) is also substantial, marked by high R2 values above 0.93. These findings provide a solid foundation for the development of more optimal biodiesel formulations.

Economic analysis and TOPSIS approach to optimize the CI engine characteristics using span 80 mixed carbon nanotubes emulsified Sapindus trifoliatus (soapnut) biodiesel by artificial neural network prediction model

The rise in fuel use within the vehicle sector leads to a corresponding escalation in energy demand. To achieve optimal operating conditions, it is necessary to reduce energy usage. For that, the primary objective of this study is to utilize an artificial neural network (ANN) and the optimization approach as a technique for order performance by similarity to the ideal solution (TOPSIS) to forecast the optimal features of a compression ignition (CI) engine. The experiment was performed with a four-stroke mono-cylinder compression ignition (CI) engine under different load situations. The study considers six operational parameters, including brake thermal efficiency (BTE), specific fuel consumption (SFC), as well as emission characteristics including carbon monoxide (CO), hydrocarbon (HC), Nitrogen oxides (NOx), and smoke. From the ANN results, the correlation coefficients for BTE, SFC NOx, smoke, HC, and CO were 0.9712, 0.9862, 0.964, 0.941, 0.998, and 0.978, respectively. The SNBD25 + 30 mg/L SP80 + 30 mg/L CNT blend exhibited the maximum closeness coefficient under various load conditions. The maximum closeness coefficient obtained from the TOPSIS optimisation approach under full load conditions is 0.982386. From the result of the ANN prediction technique, for TOPSIS optimised blend SNBD25 + 30 mg/L SP80 + 30 mg/L CNT a 13.84% increase in BTE, 11.21% decrease in SFC, 16.67% decrease in CO, 13.87% decrease in NOx, 19.23% decrease in HC, and 32.53% decrease in smoke. Based on the outcomes obtained from the ANN and TOPSIS methodologies, it can be concluded that the SNBD25 + 30 mg/L SP80 + 30 mg/L CNT blend exhibits superior performance in terms of reduced NOx emissions and enhanced efficiency, surpassing the other blends under consideration. The incorporation of carbon nanotubes (CNTs) into a system leads to an increase in the carbon-to‑oxygen ratio, resulting in a reduction in the generation of nitrogen oxides (NOx). The cost of a mixture consisting of SNBD25 + 30 mg/L SP80 + 30 mg/L blend is 20% lower than the cost of diesel on a per-litre basis.

SCO2 power cycle/reverse osmosis distillation system for water-electricity cogeneration in nuclear powered ships and submarines

As global concerns about climate change and environmental impacts continue to grow, there is a strong demand for cleaner, greener, and more efficient propulsion solutions in the maritime industry. By leveraging nuclear energy, which offers low carbon emissions and high efficiency, naval vessels can significantly reduce their environmental footprints and contribute to global efforts to combat climate change. Additionally, the ability to produce electricity and freshwater simultaneously addresses the critical need for self-sufficiency during long missions, particularly in remote or resource-constrained areas where access to freshwater may be limited. This study explores a novel approach to address water and energy supply challenges in naval applications through a nuclear-driven supercritical carbon dioxide (sCO2) power cycle–Reverse Osmosis (RO) cogeneration system. The aim is to assess the feasibility and benefits of this system for meeting water and electricity demands in maritime operations and enhancing the sustainability, efficiency, and self-sufficiency of naval vessels with nuclear energy and advanced technologies. A parametric study has been performed to understand the effects of important parameters such as the maximum and minimum cycle temperature and pressure, seawater inlet conditions, pressure vessel design, and membrane properties on the system performance. Moreover, an optimization study has been performed to determine the best possible combination of these parameters to achieve the highest system efficiency. For the determined optimal set of parameter values, it is possible to have an sCO2 power cycle with a cycle efficiency of 40.5 %, an electrical power output of 121.6 MW and an RO system with an efficiency of 29.4 %, a recovery ratio of 29.3 %, a specific fuel consumption (SEC) of 2.29 kW·h/m3, and a freshwater production rate of 1531.6 m3/d by utilizing 145.9 kW electrical power. The positive outcomes of this study indicate that the system has the potential to be a viable and effective solution for addressing water and energy supply challenges in naval operations.

Artificial Neural Network based prediction of Specific Fuel Consumption in various Compression Ratio CI Engine Fueled with Various Plastic Composition Pyrolysis oil and Diesel

This study looks at the usage of Artificial Neural Network Modeling for predicting Specific Fuel Consumption for compression ignition engines running on Diesel, Low-Density Polyethylene Pyrolysis Oil (LDPE PO), High-Density Polyethylene Pyrolysis Oil (HDPE PO), and Polypropylene Pyrolysis Oil (PP PO). Using preliminary practical findings, The Model of ANN was built to estimate SFC by adjusting the parameters of the engine. SFC is anticipated by adjusting the parameters and utilizing the orthogonal array. The experiment is then carried out using an orthogonal array. The outcomes of experimental work are used to create an ANN model. In the case of a non-linear mapping between input &amp; output, the classic back-propagation method and a multi-layer perception network are utilized. The values of Mean Square Error (MSE), Root Mean Square Error (RMSE), and Regression Coefficient (R2) for LM10TP architecture are 1.5143×10–06, 0.0012 &amp; 1 in training &amp; the validation values 1.2185×10–06, 0.0011 and 0.9999 respectively. It was discovered that neural networks are useful tools for prediction since they performed well in specific fuel consumption prediction in both training and validation.

Performance and emission characteristics of a diesel engine fuelled by biodiesel from black soldier fly larvae: Effects of synthesizing catalysts with citric acid

Biodiesel has several environmental benefits, such as biodegradability, renewability and lower soot emissions. However, biodiesel has undesirable properties such as higher viscosity and density and low calorific value compared to petroleum diesel, resulting in high Brake Specific Fuel Consumption (BSFC), reduced Brake Power (BP) and increased NOX emissions creating an environmental concerns in biodiesel development. This study investigated the effects of synthesizing transesterification catalysts (CaO and NaOH) with Citric Acid (CA) on the quality of biodiesel and biodiesel blends produced from Black Soldier Fly Larvae (BSFL) (Hermetia Illucens). The quality of biodiesel and blends was determined based on fuel properties, engine performance and emission composition characteristics. The tests were performed on a single-cylinder, four-stroke, Compression Ignition (CI) diesel engine at five loads at a constant speed of 1500 rpm. The results showed that synthesizing the catalysts with CA significantly affected the fatty acid profile of the biodiesel compared to physical fuel properties. B100 (pure BSFL biodiesel) exhibited higher BSFC by 10.57–13.97 % and lower BP by 4.21–7.83 % than diesel fuel. However, the Brake Thermal Efficiency (BTE) of biodiesel was higher than that of diesel fuel by 0.82–4.34 % at maximum load. Synthesizing catalysts with CA improved the viscosity of biodiesel by 0.93–2.81 % and effectively reduced NOX, HC and Smoke opacity by 2.23–3.16 %, 4.95–5.83 % and 20.51–41.15 %, respectively.

Efficacy of performance and mitigate pollution of CI engine: Delonix regia biodiesel with n‐butanol and exhaust gas recirculation

AbstractThe primary aim of this research study was to examine the effectiveness and environmental consequences of using Delonix regia biodiesel (DRB) in combination with butanol (BUT), exhaust gas recirculation (EGR), and diesel fuel (D) on a direct injection compression ignition engine operating at a constant speed. This study involved the formulation of five distinct biodiesel blends, namely DRB10% + D90%, DRB20% + D80%, DRB10% + BUT10% + D80%, DRB10% + BUT20% + D70%, and DRB20% + D80% + EGR10%. The inclusion of n‐butanol in a biodiesel blend serves to tackle the problem of inadequate combustion in fuel blends by alleviating the oxygen deficiency that occurs during the combustion process. The findings of the study revealed that the combination of DRB at 10%, BUT at 20%, and D at 70% produced in a significant reduction in specific fuel consumption (SFC) by 11.19% and brake thermal efficiency by 2.62%. Additionally, this combination led to a decrease in exhaust emissions of CO and Smoke, with the exception of HC and NOx, when compared to the use of diesel fuel. The control of HC and NOx emissions can be achieved through the implementation of an exhaust gas recirculation system. The results of this investigation suggest that Delonix regia biodiesel, in combination with a 20% concentration of n‐butanol, has potential as a viable alternative fuel choice that may be utilized without necessitating any engine modifications.

Performance Analysis and Optimization of Regenerative Gas Turbine Power Plant using RSM

In the present study, a thermodynamic analysis of thermal performance is carried out in a regenerative GT power plant. The optimization procedure of design parameters is realized by the response surface methodology (RSM). The thermodynamic simulations were carried out using the EES code for numerous variables such as compression ratio (2≤rp≤12), inlet temperature (273≤T1≤313K), turbine inlet temperature (1200≤T3≤1600K), and regenerator effectiveness (45≤ε≤85%). Analysis of variance (ANOVA) was carried out to identify the process parameters that influence thermal efficiency (ηth) and specific fuel consumption (SFC). Then, a second-order regression model was developed to correlate the process parameters with ηth and SFC. Consequently, numerical and graphical optimizations were performed to achieve multi-objective optimization for the desired criteria. According to the desirability function approach, it can be seen that the optimum objective functions are ηth=50.61% and SFC=0.117 kg/kWh, corresponding to process parameters T1=273.26K, T3=1597.64K, rp=6.95 and ε=84.89%. Lastly, verification simulations were conducted to validate the importance of the generated statistical models.

An experimental study on optimum temperature of B20 POBD for higher efficiency and lower emissions of a DI diesel engine in lean and ultra‐lean combustion conditions

AbstractThe impact of inlet fuel temperature on the performance and emission characteristics of a 406 cc, single‐cylinder, air‐cooled, 4‐stroke, direct injection (DI) diesel engine was investigated to determine the suitable temperature of fuel for the best conditions of the engine in lean and ultra‐lean mixture combustion mode. B20 palm oil biodiesel‐diesel blend fuel (B20 POBD), as common renewable fuel and favorite biodiesel blend ratio used in the research, was provided and injected in the engine at varying temperatures in the range of 10–40°C and the engine parameters including the output power, specific fuel consumption (SFC), thermal efficiency, flue gas heat recovery efficiency and CO and NOx pollutant emissions were measured at different air–fuel ratios corresponded to lean and ultra‐lean mixtures. The results showed that there is an optimum temperature for fuel (about 20°C) in which maximum thermal efficiency and minimum SFC and CO emission are obtained. The minimum SFC and CO emission were 0.45 Kg/kWh and 610 ppm at the optimum temperature and output power of 1.5 kW, respectively. The effect of fuel temperature on SFC and CO increases as the output power decreases and for all fuel temperatures, the output power is inversely related to the air–fuel ratio. In addition, the elevated output power reduces the CO emission in all inlet fuel temperatures. Furthermore, an ultra‐lean mixture (very high A/F ratio) can dramatically decrease the thermal efficiency of diesel engines at all fuel temperatures, such that at the inlet fuel temperature of 17°C, increase in A/F ratio from 51 to 108 decreases the thermal efficiency from 16.8% to 0.12%. Finally, low engine output power leads to low levels of NOx emission, such that decrease in output power from 1.5 to 0.5 kW reduces the NOx emission from 522 to 204 ppm, respectively.

Performance and Emission Comparison of Different Test Fuels in a Compression Ignition Engine with Syngas and Pyrolytic Oil Derived from Safflower

ABSTRACT This work aimed to compare the performance and emissions of different test fuels in a compression ignition engine. The fuels included diesel, SFEEE20, and SFME20, with and without a diesel reforming and partial oxidation system. Syngas and pyrolytic oil produced from Safflower were used in single and dual fuel modes. The results showed that brake thermal efficiency (BTE) increased in dual fuel mode compared to single fuel mode. Diesel with SFS exhibited the highest efficiency of 32.20%, followed by SFEEE20 with SFS at 31.91% and SFME20 with SFS at 31.08%. The specific fuel consumption (SFC) decreased in dual fuel, and at maximum load condition, SFME20 with SFS demonstrated the lowest SFC of 0.3193 kg/kW-hr in dual fuel mode. SFEEE20 with and without SFS displayed SFC values of 0.28051 kg/kW-hr and 0.3005 kg/kW-hr, respectively. At maximum load condition, SFME20 with SFS exhibited an EGT of 187°C, while PME and diesel with SFS showed EGT values of 183°C and 184°C, respectively. CO and HC emissions decreased in dual fuel mode compared to single fuel mode. The work concluded that SFEEE20 with SFS showed promising results with high BTE and low emissions, making it a potential fuel blend for compression ignition engines.