Performance Characteristics Of Engine Research Articles

Selection of propulsion characteristics for systematic assessment of future European RLV-options

AbstractThe propulsion system as the key-element of any space transportation concept is systematically investigated supporting a study on potential future European RLV. Different liquid propellant combinations are compared and evaluated. Subsequently, main stage rocket engines are defined for the two cycle options: open gas-generator and closed staged-combustion. Four different propellant combinations are considered all based on liquid oxygen (LOX) as oxidizer and with the fuel options liquid hydrogen (LH2), liquid methane (LCH4), liquid propane (LC3H8) and kerosene (RP1). These combinations result in eight different generic engines with sub-variants using different nozzle expansion ratios in first and upper stage application. Engine characteristics are similar, as far as conceivable, to be well-suited for the system level comparison of pre-defined RLV-launchers. However, characteristics are not necessarily identical as different engine architectures and propellants might make individual choices necessary. Engine performance characteristics are compared with similar existing engines when available. It is shown that closed-cycle staged combustion engines bring significant performance gains, particularly in sea-level operations. On the other hand, hydrocarbon- and open-cycle gas-generator engines offer a better thrust-to-weight-ratio than hydrogen and staged combustion cycle.

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.

An experimental investigation on performance, emission and combustion characteristics of IC engine using liquid fuel produced through catalytic co-pyrolysis of pressed oil cake and mixed plastics with the addition of nanoparticles

The study focuses on using a combination of diesel and a liquid fuel derived from the co-pyrolysis of pressed neem cake (PNC) and mixed waste plastics (MWP) containing waste polyethylene terephthalate (PET) and low density polyethylene (LDPE) in equal amounts with the help of cupric oxide (CuO) catalyst. The engine analysis was carried out using diesel and five different blends of co-pyrolysis oil with diesel in proportions of 20 % (20 % pyrolysis oil + 80 % diesel = PD20), 40 % (PD40), 50 % (PD50) and 100 % pyrolysis oil (PD100), respectively. Initially, the co-pyrolysis oil was produced using PNC and MWP in a ratio of 1:2 under different operating temperatures between 350 °C and 650 °C. The process temperature was optimized to yield maximum liquid oil, and the characterization study was performed. In addition to that, CeO2 nanoadditives were used to improve the properties of PD20 fuel. Different dosages of nanoadditives were blended with PD20 to prepare PD20@25 (PD20 + 25 ppm CeO2), PD20@50, PD20@75, and PD20@100. The objective of the study is to assess the performance, emission, and combustion characteristics of a diesel engine utilizing co-pyrolysis oil-diesel blend by including the nanoadditives. The analysis was carried out on a single-cylinder water-cooled diesel engine mounted with an eddy current dynamometer. The experiments demonstrated that the combination of PD20 and 50 ppm CeO2 resulted in a 6 % increase in thermal efficiency when compared to other blended fuels and diesel. When compared to all fuels, the PD20@50 produced a higher decrease in CO and HC emissions by roughly 30 and 6.2 %, respectively. The combustion analysis showed that the heat release rate (HRR) and maximum cylinder pressure were also found to have improved by adding nanoparticles.

Improvement in Efficiency of Four Stroke Petrol Engine Blend with Butanol Using Hydrogen Supplementation

Hydrogen is seen as one of energy vector of the next century. Hydrogen, as a renewable energy source provides a potential form sustainable development particular in transportation sector. The hydrogen driven engine reduces both local as well as global emission. Hydrogen gas is in brown color and form of un-separated hydrogen and oxygen generated by the electrolysis process of water by a unique electrode design. Hydrogen gas was used as a supplementary fuel in a petrol engine with few modifications and without need of storage tanks. As hydrogen, Butanol is also used as fuel in engine. Blending of small proportion of petrol and butanol can be used in petrol engine without modification of engine. Using of butanol with petrol improve performance of engine. As hydrogen gas is used as a supplementary and butanol is blend with petrol, it will enhance the combustion characteristics of petrol engine and improve performance. In this project we are going to analyze the performance characteristics of petrol engine with butanol blends using HHO kit. Key Words: Hydrogen, Four stroke petrol engine, Butanol

Experimental investigation of performance, emission, and combustion characteristics of a diesel engine using blends of waste cooking oil-ethanol biodiesel with MWCNT nanoparticles

In this study, blends of 5 % and 10 % ethanol with waste cooking oil biodiesel are mixed with Multi-Walled Carbon Nanotubes (MWCNT) at a concentration of 30 ppm. MWCNTs, known for their high surface area and unique properties, are added to potentially enhance combustion efficiency and reduce emissions. These blends are then tested in a diesel engine to evaluate their performance, emission and combustion characteristics using Design of experiment technique. After conducting various experiments and analyses, the blend of 20 % biodiesel, 10 % ethanol, and 30 ppm MWCNT was identified as the most optimal due to its favorable engine characteristics. Brake Thermal Efficiency (BTE) was increased from 3.1 % to 3.4 % with the addition of MWCNTs, indicating enhanced fuel efficiency. Moreover, average Fuel Consumption is decreased from 2.2 % to 2.5 %, suggesting improved fuel utilization. Using MWCNT 30 ppm in B20 ethanol blends (MWCNT 30 ppm B20+E10) resulted in 35 % reduction in nitrogen oxide (NOx) emissions, 37 % reduction in CO emissions and 39 % reduction in HC emissions. Hence MWCNTs demonstrated effectiveness in mitigating harmful exhaust emissions The optimized values for all parameters fall within acceptable ranges, indicated successful optimization using Response surface methodology. Additionally, statistical analysis reveals that the machine learning- XGBoost model outperformed all other advanced machine learning models across all tested metrics, including MSE, MAE, and R-square.

Development of Free Fatty Acid (FFA) monitoring device for evaluation of oil samples used for biodiesel production

Diversion of oil sources for biodiesel production has been gaining importance to meet the environmental concerns and energy demand. The free fatty acid (FFA) content of the feedstock is a significant factor in biodiesel production. The FFA values determine the complexity of the biodiesel production. Until date, an experimental procedure has been used to determine the FFA concentration of an oil source; this method is dependent on titration, which is a laborious process involving significant volumes of chemicals. Hence, in the present study, an attempt was made to develop a device for the identification of FFA of the oils. Waste cooking oil samples subjected to wide range of cooking conditions like cooking time, temperature, type of food are collected from different food outlets. Subsequently, the composition of oil samples and the variation in their quality were analysed using gas chromatography flame ionization detector (GC – FID). Biodiesel is prepared from the oil samples through transesterification and the impact of FFA and their respective methyl esters in the quality and properties have been investigated. The properties of biodiesel were determined as per ASTM standards. The study was further extended to correlate the properties of biodiesel with the composition of the oil from which it was derived. The analysis evidently proved the dependence of biodiesel properties on the FFA percentage and the composition of the oil. The results have been further substantiated with the performance and emission characteristics of internal combustion engine fuelled with the prepared biodiesel samples.

Optimization of water and 1-pentanol concentrations in biodiesel-diesel blends for enhanced engine performance and environmental sustainability

This study focuses on optimizing the concentrations of water and 1-pentanol in biodiesel-diesel blends derived from Gossypium hirsutum (cottonseed) oil to enhance engine performance and reduce environmental impact. Biodiesel from cottonseed oil (COB) was produced via transesterification, followed by an analysis of its elemental and chemical composition, and physicochemical properties. Using a Box-Behnken design matrix, the volume concentrations of COB (10-30%), water (5-15%), and 1-pentanol (5-20%) in diesel fuel were varied to optimize engine performance and emission characteristics. ANOVA was employed to evaluate the influence of these parameters on key output responses. The results demonstrated that COB possesses favorable elemental and chemical properties, and the optimal concentrations of COB, water, and 1-pentanol were identified as 14.7%, 9.9%, and 11.2%, respectively. ANOVA findings revealed that COB had the maximum influence on brake specific fuel consumption (93.4%), nitrogen oxides (55.3%), carbon monoxide (78.5%), and carbon dioxide (97.1%), while 1-pentanol significantly influenced brake thermal efficiency (38.9%) and hydrocarbon emissions (70%). Confirmation experiments validated these optimizations, showing substantial improvements in both performance and emissions. The study concludes that integrating water and 1-pentanol into COB blends can reduce fossil fuel consumption by approximately 35%, while enhancing energy efficiency and minimizing environmental impact.

Performance and Emission Characteristics of VCR Engine Fueled with TYRE Oil and Cotton Seed Oil Blends

Performance and Emission Characteristics of VCR Engine Fueled with TYRE Oil and Cotton Seed Oil Blends

Assessing performance variability in a dual-fuel diesel engine using diesel and biogas: an experimental study across different compression ratios

The increasing concerns about energy security and environmental sustainability have intensified the search for alternative fuels. This study investigates the performance and emission characteristics of a dual-fuel diesel engine utilizing purified biogas and diesel across various compression ratios. A single-cylinder, direct-injection, water-cooled, variable compression ratio diesel engine was adapted to operate in dual-fuel mode, running experiments at compression ratios of 12, 14, 16, 18, and 20 with a constant injection timing of 23° before top dead center under different load conditions. The study reveals a peak brake thermal efficiency of 33.25% at a compression ratio of 20, demonstrating the potential of biogas as a viable alternative fuel. Notably, while carbon monoxide and hydrocarbon emissions decreased with higher compression ratios, nitrogen oxide emissions increased, highlighting a trade-off in emission characteristics. This work contributes to the understanding of biogas utilization in diesel engines, offering insights into optimizing engine performance and emissions through compression ratio adjustments. The findings can inform future developments in sustainable energy solutions.

Investigating Engine Performance and Emission Characteristics of a CI Engine Fueled with Waste Fried Oil Blend Containing Butanol, Alumina, and Silver Nanoparticles

Investigating Engine Performance and Emission Characteristics of a CI Engine Fueled with Waste Fried Oil Blend Containing Butanol, Alumina, and Silver Nanoparticles

Exploring novel porphyrin photocatalyst for the conversion of frying oil to biodiesel: A step for globular economy

The current protocol addresses the outcomes on the photo-transesterification of frying sunflower oil (FSO) catalysed by porphyrin comprising sulphonic acid functionalized pyridinium ionic liquid (PcSAFPyIL). A novel photocatalyst was synthesized and confirmed by 1H and 13C NMR, Powder XRD, FT-IR, XPS, and fluorescence emission spectrophotometry. The energy band gap (1.85 eV) was determined by cyclic voltammetry, Hammett acidity (H0 = 0.217) by UV–visible spectrophotometer and metal free nature by powder XRD and XPS. The photocatalytic activity of PcSAFPyIL in the visible region was confirmed by reflecting intense Soret band (421 nm) and four Q bands (515, 554, 591 and 647 nm). This may be due to inherent aromatic characters and conjugation with chromophore groups at meso-position of porphyrin ring. The obtained photocatalyst was scrutinized for the photo-transesterification of FSO in a lab-made photoreactor. The ideal reaction parameters were found to be 20 mg photocatalyst quantity with 1:12 (FSO: ROH) under exposure of 2 x 5 W LED at room temperature, to afford 90 % biodiesel in 24 h. Moreover, the formation of biodiesel was confirmed by (1H, 13C) NMR, FT-IR, DEPT-135, and GC–MS. Further, stability, heterogeneous nature and the gram scale reaction PcSAFPyIL was also efficiently accomplished using the optimized photocatalytic conditions. Additionally, the physicochemical properties of the biodiesel fuel B15 (15 % blended with marketed diesel) and pure marketed diesel are consistent. Moreover, the engine performance and emission characteristics of B15 such as brake-specific fuel consumption (BSFC), break thermal efficiency (BTE) found comparable and better than commercial diesel.

K-means clustering optimization of various quantum dots and nanoparticles-added biofuels for engine performance, emission, vibration, and noise characteristics

The utilization of biodiesel as a bio-lubricant, combined with various types of nanoparticles, and quantum dots presents an innovative approach towards enhancing the performance of diesel engines. In this study, biodiesel was blended with different nanoparticles to improve its lubricating properties, and the k-means clustering method was applied to identify the optimal nanoparticle that maximizes the performance of the diesel engine. The experiment involved synthesizing biodiesel-based lubricants infused with nanoparticles of varying compositions, including but not limited to carbon nanotubes, graphene oxide, and metal oxides. The successful implementation of the Entropy-k-means hybrid model facilitated the identification of the optimal bio-lubricant for diesel engines. The experimentation uncertainty came out to be 4 % which lies in an acceptable range. Additionally, a strong Pearson r correlation was observed between Brake Thermal Efficiency (BTE) and Sound, highlighting their interrelationship. Moreover, the prioritization analysis indicated that NOx obtained the highest priority at 0.45, contrasting with the lowest priority attributed to sound at 0.01. Furthermore, the clustering analysis conclusively identified magnetic bio-lubricant as the top-performing option with minimum centroidal distance of 1.2. The optimal outcomes are BTE (30.5 %), Brake Specific Fuel Consumption (191.5 g/kWh), NOx (88 ppm), CO (7.1 g/km), Vibration (68.5 Hz), and Sound (74.5 dB). The application of k-means clustering facilitated the identification of the most effective nanoparticle for enhancing engine performance, thereby contributing to the advancement of sustainable lubrication technologies in the automotive industry.

Investigation of the operating characteristics of diesel engines with chromium oxide (Cr2O3) nanoparticles dispersed in Mesua ferrea biodiesel: an experimental and predictive approach using ANNs and RSM

Abstract This study investigates the effects of using biodiesel from Mesua ferrea (BD20) and chromium oxide (Cr2O3) nanoparticles in diesel engines. The Response Surface Methodology (RSM) model and artificial neural networks (ANNs) were developed to make precise predictions of the operating parameters. The amount of Cr2O3 nanoparticles was set at 80 mg/L, and surfactant and dispersant were applied to the nanoparticles in the same amounts. The study was carried out with different compression ratios and load conditions. The parameters evaluated were engine load, fuel samples and compression ratio as inputs and BTE, BSFC, CP, NHRR, CO, UHC, NO x and smoke opacity as outputs. The addition of the QPAN80 additive at the same dosage of 80 mg/L together with the BD20 fuel blend containing Cr2O3 at a concentration of 80 mg/L resulted in a significant increase in BTE by 16.58 % and a reduction in BSFC by 0.58 %. While the NHRR increased by 85.40 %, the CP increased sharply by 24.47 %. The CO concentration decreased by 31.85 %, the UHC concentration by 22.22 %, the NO x concentration by 6.16 % and the smoke emission by 62.61 %. For each output parameter, the correlation coefficient (R 2), calculated using ANNs and RSM was between 0.96 and 0.98. The observed range of values demonstrates a robust correlation between the experimental data and the predicted outcomes.

Optimizing heat transfer predictions in HCNG engines: A novel model validation and comparative study via quasi-dimensional combustion modeling and artificial neural networks

Heat transfer from the walls of engine has a significant role on engine combustion, performance and emission characteristics. The study objectives to showcase the efficacy of the new model through an analysis by comparison with existing heat transfer models. New model is based on woschni model in which pressure and temperature is replaced by other fluid properties like density, thermal conductivity and dynamic viscosity. A series of experiments were conducted on a compressed natural gas internal combustion engine across varying hydrogen fractions, EGR ratios, engine speeds and different loads under stoichiometric conditions. The study demonstrates the efficacy of the proposed model by constantly achieving high prediction quality across a wide range of engine calibration coefficients by using Quasi-dimensional Combustion Model (QDCM) on MATLAB. Comparative analyses of new model with different heat transfer models were undertaken to validate the heat transfer rates with experimental results across a broad spectrum of operational conditions. It is observed that heat transfer rate is increased by increasing the engine load as 25%, 50%, 75% and 100% as 90.57J/deg, 130.12J/deg, 200.02J/deg, and 260.26J/deg with new model correspondingly. Heat transfer rate reduced by rise in engine speed with 1100 rpm, 1200 rpm, 1500 rpm and 1700 rpm is as 32.91 kW, 32.16 kW, 25.36 kW and 18.03 kW by new heat transfer model respectively. Artificial neural network (ANN) popular backpropagation algorithm is adopted to predict the heat transfer rate of HCNG engine, the five-input and one-output network structure are used. The values of correlation coefficient (R) and mean square error (MSE) were 0.99957 and 0.22667, 0.99998 and 0.010776, 0.99253 and 4.4762, 0.9961 and 1.2329, 0.99994 and 0.025108 for Woschni, New_Model, Chang, Sitkei and experimental respectively. This research work offers that ANN is a wise option for conventional modeling systems. In this way, the heat transfer rate of hydrogen-added CNG engines may be precisely predicted using ANN modeling.

On the Influence of Engine Compression Ratio on Diesel Engine Performance and Emission Fueled with Biodiesel Extracted from Waste Cooking Oil

Despite the extensive research on biodiesels, further investigation is warranted on the impact of compression ratios on emissions and engine performance. This study addresses this gap by evaluating the effects of increasing the engine’s compression ratio on engine performance metrics—brake-specific fuel consumption (BSFC), power, torque, and exhaust gas temperature—and emissions—unburnt hydrocarbons (HCs), carbon dioxide (CO2), carbon monoxide (CO), nitrogen oxides (NOx), and oxygen (O2)—when fueled with a 20% blend of waste cooking oil biodiesel (WCB20) and petroleum diesel (PD) under various operating conditions. The viscosity of the prepared fuels was measured at 25 °C and 40 °C. Experiments were conducted on a single-cylinder diesel engine under wide-open throttle conditions at three different speeds (1400 rpm, 2000 rpm, and 2600 rpm) and two compression ratios (16:1 and 18:1). The results revealed that at a lower compression ratio, both WCB20 and petroleum diesel exhibited reduced BSFC compared to higher compression ratios. However, increasing the compression ratio from 16:1 to 18:1 significantly decreased HC emissions but increased CO2 and NOx emissions. Engine power increased with engine speed for both fuels and compression ratios, with WCB20 initially producing less power than diesel but surpassing it at higher compression ratios. WCB20 demonstrated improved combustion quality with lower unburnt hydrocarbons and carbon monoxide emissions due to its higher oxygen content, promoting complete combustion. This study provides critical insights into optimizing engine performance and emission characteristics by manipulating compression ratios and utilizing biodiesel blends, paving the way for more efficient and environmentally friendly diesel engine operations.

Effect of direct water injection timing and quantity on combustion, performance, and emission characteristics of a homogeneous charge compression ignition engine − A CFD analysis

Direct water injection in an HCCI engine is a promising strategy to extend the operating load limit. The advantage of water injection depends on the percentage of water evaporated inside the cylinder, which further depends on the time available for the evaporation and the interaction of water spray plumes with the in-cylinder air-flow field. Here, CFD investigations are done to find the effect of water injection timing (WIT) and quantity on the load limit and performance and emission characteristics of the HCCI engine. Various WITs are considered for the study, varying from 100° CA before TDC to 20° CA before TDC. The water-to-fuel ratio is varied from 0 to 1 in steps of 0.2. A three-dimensional computational fluid dynamics model is used for the study, and CFD models used are validated from the available experimental data in the literature. The results show that WITs before 650° CA and after 670° CA are inappropriate for the HCCI engine, as heat release rate and MRPR are high in these cases. Also, the evaporation rate of water increases when the water injection is done in the region where the direction of the air-flow field is opposite to the direction of water injection. At the WIT of 60°, the HRR and MRPR are minimal, and the water vapor distribution is good compared to other cases. Also, it is seen that a water-to-fuel ratio of 0.8 gives more scope for extending the upper load limit with a marginal penalty of the IMEP; hence, a WIT of 60° with the water-to-fuel ratio of 0.8 is considered optimum. With the optimum case, it is feasible to increase the ER from 0.74 to 0.95, resulting in an increase of IMEP from 3.23 bar to 4.92 bar, which is 52.3 % more than without a water injection case at the ER of 0.74. Also, it showed minimum NOx emissions in all the water injection cases. Hence, these results address the primary challenges associated with HCCI engines, demonstrating that direct water injection can substantially improve the combustion controllability and operational range of HCCI engines.

Parametric Investigation on the Influence of Turbocharger Performance Decay on the Performance and Emission Characteristics of a Marine Large Two-Stroke Dual Fuel Engine

Parametric Investigation on the Influence of Turbocharger Performance Decay on the Performance and Emission Characteristics of a Marine Large Two-Stroke Dual Fuel Engine

Real-time analytical solution to energy management for hybrid electric vehicles using intelligent driving cycle recognition

For series hybrid electric vehicles, due to the limitation of engine operating characteristics, speed regulation is usually performed using discrete operating points. This leads to the problem of mixed integer programming when solving energy management problem. In this paper, an analytical method with strong real-time performance and small computational load is proposed. First, an intelligent cycle recognition system is designed. It can cluster driving cycles offline based on the probability distribution of the required power and efficiently recognize unknown driving cycles online. Then the analytical expression of power distribution is derived, and the selection scheme of engine operating point is given. Finally, the required power information obtained from the clustering is substituted into the analytical expression. The specific values of the corresponding analytical solutions for each type are computed offline. When facing unknown conditions, this method can match the power distribution scheme quickly once the driving cycle is recognized. The results of the simulation and hardware-in-loop experiments demonstrate that this method can effectively control the SOC trajectory and allocate power more optimally. Compared to the benchmark method, the proposed strategy improves the fuel economy by 5.52 % and 7.49 % in two cases, and the computational efficiency is significantly enhanced.

Investigation of biodiesel blends and hydrogen addition effects on CI engine characteristics through statistical analysis

This study investigates the performance, combustion, and emission characteristics of a single-cylinder compression ignition engine fueled with blends of Soy methyl ester (BS100) and macauba methyl ester (BM100) biodiesels, with hydrogen addition. Biodiesel blends (BSM10 - BSM50), and hydrogen addition (2–5%) were tested at various engine loads and speeds. The optimal blend, BSM20 (80% BS100 + 20% BM100), showed up to 7.8% higher brake thermal efficiency and 6.2% lower brake-specific fuel consumption than diesel. Emissions were significantly reduced: NOx by 12.9%, HC by 22.4%, CO by 27.5%, and smoke opacity by 18.7%. Adding 5% hydrogen to BSM20 further improved performance, reducing fuel consumption by up to 3.1% and increasing thermal efficiency by 2.5%, with substantial reductions in hydrocarbon and carbon monoxide emissions. This investigation highlights the potential of sustainable biodiesel blends and hydrogen as viable alternatives to conventional diesel fuels, offering significant environmental benefits and enhanced engine performance.

Environmental Exhaust Emissions reduction and Performance Improvement Analysis of biodiesel operated Diesel Engine Performance Using Operating Parameters

<p style="margin-top:3px; margin-bottom:3px; text-align:justify; text-indent:31.5pt">The present investigation aims to study the performance and emission characteristics of a CI DI diesel engine using biodiesel blends derived from Jatropha seed feedstock. Four blends, namely B25, B50, B75, and B100, are employed as fuels to run the diesel engine at a rated speed of 1500 rpm, and their performance and emission characteristics are determined under different operating conditions in the first phase. The blend B25 of JME is found to be the optimum blend, and the optimum compression ratio is found to be 18.5.The optimum blend exhibits better performance in terms of brake specific fuel consumption (BSFC) and brake thermal efficiency (BTHE), along with a decline in the emissions of carbon monoxide (CO) and hydrocarbons (HC), except for the emission of nitrogen oxides (NOX) at the optimum compression ratio of 18.5. At maximum load, with a compression ratio of 18.5, the optimum blend results in better BSFC and BTHE, which are 0.255 kg/kW-hr and 31.87%, respectively.</p>