Fueled Compression Ignition Engine Research Articles

Effects of temperature and composition inhomogeneity on the ignition characteristics of NH3/H2 co-firing fuels under HCCI operating conditions

The application of ammonia (NH3) in combustion devices, such as internal combustion engines (ICEs), is expected to largely reduce the greenhouse gas (CO2) emission. NH3/H2 cofiring fuels in homogeneous charge compression ignition (HCCI) engines may provide a potential way to deal with zero carbon requirements. However, in HCCI engines, the ignition process needs to be moderated since the ignition is only controlled by the chemical kinetics of the fuel. Therefore, this study investigates the effects of temperature and composition stratification strategies on the auto-ignition characteristics of NH3/H2/air mixtures under HCCI engine operating conditions with direct numerical simulation (DNS). 12 cases with different stratification strategies have been set under turbulent conditions. The chemical kinetics of NH3/H2/air was verified with the laminar flame speeds and ignition delay times. Results show that the temperature stratification can reduce the peak value of heat release rate (HRR), advance the ignition time and extend the combustion duration. In this case, the chemical reaction front is dominated by the deflagration or flame propagation mode. However, in contrast, composition stratification shows very limited effect on the overall combustion process, which is similar to homogeneous ignition and denoted as the spontaneous ignition mode. When increasing the hydrogen content in the fuel, the ignition time is obviously advanced and the peak of HRR is slightly increased. Higher NO emission is also observed which is mainly due to the increase of O, H, and OH intermediates to enhance the fuel NO production. Temperature stratification degree can improve the ignition process under both negatively correlated or unrelated T-Φ fields. However, the improvement is more evident for unrelated T-Φ condition when increasing the stratification degree.

Effects of hydrogen and EGR on energy efficiency improvement with ultra low emissions in a common rail direct injection compression ignition engine fueled with dimethyl ether (DME) under HCCI mode

This study deals with enhancing the energy efficiency with ultra-low emissions and extending the operating range (maximum load limit) of dimethyl ether (DME) fueled homogeneous charge compression ignition (HCCI) engine using hydrogen and exhaust gas recirculation (EGR). In the neat DME mode, the possible maximum load limit with controlled auto-ignition (CAI) was found as 24% (BMEP of 1.67 bar). Beyond 24% load, the knocking was observed with an advanced combustion phase, and shortened combustion duration resulted in uncontrolled auto-ignition (UAI) combustion. The addition of EGR extended the maximum load limit to 52% (BMEP of 3.62 bar) (60% EGR). Near-zero levels of NOx, zero smoke, and marginal CO and HC emissions reduction were observed with the optimized EGR rate (35%). The hydrogen fuel addition along with DME at an optimized EGR rate resulted in combustion phase retardation with the elimination of the low-temperature reaction (LTR) region. The energy efficiency (EE) and indicated thermal efficiency (ITE) increased along with zero smoke emission, ultra-low NOx, CO, and HC, and lower CO2 emissions till 12% of hydrogen energy share (HES). Thus, the combined strategy of EGR and hydrogen could effectively extend the operating range with ultra-low emissions levels.

Synthesis of spirulina microalgae biodiesel, and experimental research of its effects on compression ignition engine responses with iron II-III oxide (Fe3O4) nanoparticle supplementation

The raw material from which biodiesel is produced, the pioneer of alternative fuels in compression ignition engines, has increased importance in recent years. Third-generation biodiesels, which do not harm the food chain and environment, have become popular in recent years. In this study, fuel mixtures were obtained by mixing biodiesel produced from spirulina microalgae, the third-generation biodiesel type, with diesel and iron II-III oxide (Fe3O4) at different concentrations. Microalgae biodiesel (MAB) was mixed with diesel at two different percentages (10% and 20%), and three diverse quantities of Fe3O4 (25, 50, and 75 ppm) were added to 20MAB80D. Since the effects of the fuel mixture containing 20% MAB on the engine response are more optimistic, nanoparticles were added to the fuel containing 20% MAB. These fuel blends were evaluated under various engine loads (from 25% to 100%) at a constant engine speed (1500 rpm), and a compression ratio (15.5:1). Brake thermal efficiency (BTHE) and brake mean effective pressure (BMEP) improved with the addition of both MAB and Fe3O4. Compared to diesel (D100), the highest increases were achieved with 20MAB80D75IO fuel, with an average of 28.64% and 13.18%, respectively. With the 20MAB80D, these increases averaged 12.85% and 3.85%, respectively. On the other hand, brake-specific fuel consumption (BSFC) response increased with MAB and decreased with Fe3O4. With 20MAB80D75IO fuel, it showed an average decrease of 19.02% compared to BSFC diesel. With the 20MAB80D, there was an average increase of 11.31%. MAB and Fe3O4 contributed to reducing carbon monoxide (CO) and hydrocarbon (HC) emissions, which are products of incomplete combustion. With 20MAB80D75IO fuel, an average of 24.21% and 57.36% reductions were achieved, respectively, compared to D100. With the 20MAB80D, there was an average of 20.14% and 22.62% reductions, respectively. Conversely, NOx produced by 20MAB80D75IO was 11.63% higher than D100, while NOx produced by 20MAB80D was 3.83% higher. In conclusion, the experimental data obtained using Fe3O4 nanoparticles added to improve engine responses by improving the properties of MAB produced as third-generation biofuels revealed that MAB would be an excellent alternative fuel and Fe3O4 was a suitable additive.

A Synergic Application of High-Oxygenated E-Fuels and New Bowl Designs for Low Soot Emissions: An Optical Analysis

Synthetic fuels significantly reduce pollutant emissions and the carbon footprint of ICE applications. Among these fuels, oxymethylene dimethyl ethers (OMEX) are an excellent candidate to entirely or partially replace conventional fuels in compression ignition (CI) engines due to their attractive properties. The very low soot particle formation tendency allows the decoupling of the soot-NOX trade-off in CI engines. In addition, innovative piston geometries have the potential to reduce soot formation inside the cylinder in the late combustion stage. This work aims to analyze the potential of combining OMEX with an innovative piston geometry to reduce soot formation inside the cylinder. In this way, several blends of OMEX-Diesel were tested using a radial-lips bowl geometry and a conventional reentrant bowl. Tests were conducted in an optically accessible engine under simulated EGR conditions, reducing the in-cylinder oxygen content. For this purpose, 2-colour pyrometry and high-speed excited state hydroxyl chemiluminescence techniques were applied to trace the in-cylinder soot formation and oxidation processes. The results confirm that increasing OMEX in Diesel improves the in-cylinder soot reduction under low oxygen conditions for both piston geometries. Moreover, using radial lips bowl geometry significantly improves the soot reduction, from 17% using neat Diesel to 70% less at the highest OMEX quantity studied in this paper.

Impact of titanium dioxide (TiO2) nanoparticles addition in Eichhornia Crassipes biodiesel used to fuel compression ignition engine at variable injection pressure

Power production through combustion of fuels plays a vital role in the progress of a nation. In liquid fuels, biodiesel has emerged as a potential replacement of fossil fuel. In this regard, the improvement of fuel properties or adjustment of the operating parameters can improve the efficiency and lower the emission for a biodiesel run diesel engine. In this regard, the current study focuses on the use of novel nano blended biodiesel, prepared by blending titanium dioxide nano particles along Eichhornia Crassipes biodiesel. Three different biodiesel blends are prepared having composition of titanium dioxide by 50 ppm, 100 ppm and 150 ppm which is tested in a four stroke, single cylinder, naturally aspirated water cooled diesel engine of 3.5 kW rated power for different loading conditions for performance, emission, and combustion evaluation. Further, at the same engine conditions, the biodiesel blend having 150 ppm of titanium dioxide is tested at fuel injection pressure of 220 bar. The findings suggests that the brake thermal efficiency improves and emissions lowers with the addition of nano particles at high fuel injection pressure. The maximum improvement of brake thermal efficiency of 1.01% in comparison to diesel mode has been found for nano blended biodiesel composition of 150 ppm of titanium dioxide at fuel injection pressure of 220 bar under full loading condition. For the same fuel injection pressure of 220 bar and same nano blended biodiesel composition, the hydrocarbon and carbon monoxide emission were found to minimum at 60% load.

Investigation on novel natural gas fueled homogeneous charge compression ignition engine based combined power and cooling system

A significant part of energy of fuel supplied is lost in internal combustion engines in the form of atmospheric discharge of engine exhaust gases which are considered as a big source of engine inefficiency and formation of pollutant emissions. To address this issue, a bottoming cycle combining the transcritical CO2 (T-CO2) refrigeration cycle and the supercritical CO2 (sCO2) power cycle is employed, aiming to produce cooling for food preservation by utilizing the exhaust heat of homogeneous charge compression ignition (HCCI) engine powering the refrigerated truck. The operative variables and their effect on thermal and exergetic efficiency of HCCI engine and the combined system are investigated. At the base case operative conditions, the thermal and exergy efficiencies of natural gas fueled HCCI engine are improved significantly from 48.69% to 61.28% and from 41.14% to 42.79%, respectively, after employing the sCO2 powered T-CO2 refrigeration cycle. Promotion of equivalence ratio from 0.3 to 0.9 enhances the thermal and exergy efficiencies of HCCI engine from 47.44% to 49.54% and from 40.14% to 42.12%, respectively. Increasing of engine speed from 1400 r.p.m to 2200 r.p.m provides marginal improvement in HCCI engine efficiencies but the efficiencies of combined cycle are significantly improved from 57.67% to 65.18% and from 40.64% to 45.06%, respectively. Finally, exergy analysis applied to determine the sources of non-idealities within the system revealed that out 361 kW (100%) fuel exergy supplied to the system, HCCI engine destroys 93.31 kW (25.85%), catalytic convertor destroys15.49 kW (4.29%), and the in-cylinder heat transfer losses and system exhaust losses are found as 35.72 kW (9.91%) and 16.61 kW (4.61%), respectively.

Efficacy of machine learning algorithms in estimating emissions in a dual fuel compression ignition engine operating on hydrogen and diesel

Emission created by combustion of fossil fuels are a major concern of the world for the past few decades. The stringent emission norms have impacted the automobile manufacturers to work on exhaust emissions and its impact. This research focused on using machine learning regression models to evaluate the efficacy of experimental results for a dual fuel compression ignition (CI) engine operating on hydrogen and diesel. In the present study, engine emissions were estimated using 29 regression algorithms. A total of 5 input data namely, concentration of hydrogen, engine load, diesel intake, speed and equivalence ratio were considered in the study to estimate various emissions like oxides of nitrogen (NOx), carbon dioxide (CO2), hydrocarbon (HC) and smoke. Correlation coefficient, mean absolute error, root mean squared error, relative absolute error and root relative squared error were adopted as the performance metrics in the present study. Amongst the algorithms considered, pace regression, radial basis function regressor, multilayer perceptron regressor and alternating model tree produced the highest correlation coefficient of 0.9985, 0.8958, 0.9950 and 0.9256 in estimating the engine emissions like CO2, smoke, NOx and HC respectively. Additionally, an attempt was made to establish an individual algorithm that can estimate all the emissions was identified as multilayer perceptron regressor with correlation coefficient values of 0.9977 (CO2), 0.9950 (NOx), 0.8501(smoke) and 0.8731(HC) respectively.

Evaluating the Operating Parameters of a Compression Ignition Engine Fueled With Waste Cooking Oil—Diesel Blends Using Artificial Neural Network and Ensemble Methods

Abstract Fossil fuels being the primary source of energy for industrial and power sectors are being consumed at an alarming rate. There is a dire need to search for alternative fuels and optimize the performance parameters of internal combustion (IC) engines. Traditional methods of testing and optimizing the performances of IC engine are complex, time-consuming, and expensive. This has led the researchers to shift their focus to faster and computationally feasible techniques like soft computing (SC) and machine learning (ML) algorithms, which predict the optimum performance with a substantial accuracy. This study focuses on the implementation of artificial neural network (ANN) and ensembling methods (random forest regression and extreme gradient boosting algorithm) modeling of a compression ignition (CI) diesel engine run on waste cooking oil (WCO). A single-cylinder, four-stroke, variable compression ratio diesel engine's performance, combustion, and emission parameters have been predicted using ANN and ML approaches. These models have been developed to predict the brake power, brake thermal efficiency, brake-specific fuel consumption, ignition delay, combustion duration, carbon monoxide, carbon dioxide, and oxides of nitrogen. All the models have been trained by tuning and optimizing a different number of hyper-parameters and training algorithms (Levenberg–Marquardt (LM), scaled conjugate gradient, and Broyden–Fletcher–Goldfarb–Shanno). Further the most optimum parameters have been selected using hyper-parameter optimization. The mathematical models are assessed for their generalization capability by subjecting them to a set of new testing data.

Characterization of soot emissions formed in a compression ignition engine cofired by ammonia and diesel

The impact of ammonia (NH3) co-firing with diesel on the greenhouse gases (GHG) and soot emissions of compression ignition (CI) engines is a current concern in large-scale agriculture, marine transportation and shipping applications for which NH3 is proposed as a near-term decarbonization solution. In this study, the effect of NH3 port injection on the GHG emissions and the characteristics of the soot formed in a NH3-diesel dual fuel CI engine is investigated. Soot is sampled from the engine exhaust operating in dual-fuel mode at 20% and 40% NH3 energy fraction and in diesel-only mode at a fixed engine speed, load, and diesel injection strategy. Detailed analysis of soot is done to investigate: the exhaust soot yield using gravimetric analysis, soot growth and inception through the average primary particles size and number concentration using analysis of Transmission Electron Microscopy (TEM) imaging, the soot nanostructure using Raman spectroscopy, and the chemical composition using X-ray Photoelectron Spectroscopy (XPS). The engine GHG emissions measurements shows that carbon dioxide (CO2) is reduced while N2O emissions increases with NH3 addition. The engine soot emissions yield is significantly reduced with the average primary particles size and number concentration decreasing as the NH3 energy fraction increases. The soot nanostructure is impacted by NH3 addition as it becomes more graphitic with high ratio of sp2 to sp3 carbon bonding. The XPS chemical composition analysis also shows an increase in the nitrogen bonding with carbon in the aromatic rings on the particles surface. The results suggest that the chemical interaction of NH3 with diesel results in soot with more graphitic nanostructure as nitrogen reaction with carbon at active defect sites leads to an increase in the nitrogen content on the soot surface with NH3 addition. This indicates an increased potential of NH3 co-firing with diesel to form nitrogenated PAHs (N-PAH) on the soot surface which would require further studies to identify the risks posed on the environment and human health.

Predication of performance and emissions characteristics adual fuel engine energized with liquid and gaseous materials by Artificial neural network

The current study investigates the use of Artificial Neural Network (ANN) modelling for prediction of performance and emission characteristics biogas fuelled compression ignition engine under dual fuel mode. The biogas flow rate was varied from 1.2 to 3.2 kg/h while diesel fuel was injected as ignition source. The ANN model was developed to predict Brake Power (BP), Brake Specific Energy Consumption (BSEC), Brake Thermal Efficiency (BTE), Brake Specific Fuel Consumption (BSFC), Carbon Monoxide (CO), Carbon dioxide (CO2), and Hydrocarbons (HC) based on experimentation performed by varying load and biogas flow rates. In this study, ANN based models have been developed in the MATLAB2012a environment using the Neural Network toolbox, Back propagation algorithm, Levenberg- Marquardt Back propagation (TRAINLM), was used for the ANN structure for prediction of performance and emissions characteristics. There was a high correlation between the predicted values by the ANN model and the measured values resulted from experimental tests. The correlation coefficient was 0.99956 in the analysis of whole network when biogas and diesel were used, which implies that the model succeeded in prediction of the generator performance. It is found that the ANN modelling are good tools for prediction of performance and emission characteristics of biogas operated dual fuel diesel engine with varying engine operating loads and flow rates.

Optimization of combustion characteristics of novel hydrodynamic cavitation based waste cooking oil biodiesel fueled CI engine

The increment in the usage of automobiles is resulting in increased greenhouse gases (GHG) emissions continuously and there is a substantial need to reduce them effectively. The present research work investigates the emission behavior of waste cooking oil biodiesel doped with CuO nanoparticles during testing in Compression Ignition (CI) engines. This investigation is based on the effective emission reduction analysis emitted by diesel fuel during experimentation on CI engines. It suggests a cost effective modification of biodiesel as a fuel prepared from waste cooking oil (WCO) by a novel hydrodynamic cavitation technique which includes the hydrodynamic cavitation reaction mixture composed of 1.28 L of methanol and 10 g KOH and 5 L of preheated WCO at 45 °C in the cavitation reactor for 40 min. These reactants are synthesized utilizing the principle of cavitation and the final manufactured esterified oil is authenticated with ASTM Standard property measurement for suitability check. In the research work, two different investigations are carried out. In the first one, WCO biodiesel-diesel blends of 0, 30, and 100% (B0, B30, B100) ratio are prepared and the emission characteristics have investigated at 1500 rpm constant speed with varying load and indicated mean effective pressure (IMEP). In the second investigation, the emission suitable blend B30 is doped with CuO nanoparticles, keeping other parameters as per the previous setup, the emission characteristics investigated for the second one. For precise results, more experimental trials are needed to achieve this decrease in the emission of harmful gases. Using an amalgamation of L9 Taguchi and response surface methodology (RSM) the maximum emission control with a minimum number of experimental trials is achieved. The first investigation includes the predefined predictors as A (blend), B (load), and C (IMEP), where blends (0 ≤ A ≤ 100%), load (0 ≤ B ≤ 12 kg), IMEP (3.5 ≤ C ≤ 7.5 bar) are controllable features. Optimization process resulted into a minimum emission of CO, CO2, and NOx by appertaining the condemnatory merger of inputs such as blend B0 (Diesel), load 12 kg, and IMEP 3.48 bar in the first investigation, which has resulted into 0.08 ppm CO, 0.6 ppm CO2 and 30 ppm NOx emission. Taguchi analysis-based second experimental investigation includes the predefined predictors as A (CuO), B (load), and C (IMEP), including nanoparticles CuO in blend B30, and the prognosticated results of optimization are 0.03 ppm CO, 0.3 ppm CO2 and 21 ppm NOx emission. In current investigation, the percentage reduction is found to be 92.3%, 94.82%, and 96% compared to the emission of diesel in CO, CO2 and NOx gases, respectively. The coefficient of determination is almost equal to 1, which reveals the chosen optimization technique is very accurate in prediction. The investigation has provided suitable minimum emission characteristics in a cost-effective way.

Autoignition of sustainable fuels under dual operation with H2-carriers in a constant volume combustion chamber

The expected increase in the use of environmentally friendly liquid fuels in medium and heavy-duty compression ignition engines (for both off-road and transport applications), together with the well-documented benefits of hydrogen-carriers to decrease energy dependence and to achieve a neutral-carbon economy (internal combustion engines highly contributing to the global CO2 emissions), have motivated this work. The autoignition characteristics of different alternative diesel-type fuels (hydrotreated vegetable oil, advanced biodiesel and blends of conventional diesel fuel with polyoxymethylene dimethyl ether and 1-butanol) under dual-fuel operation with H2, NH3, and CH4 were studied in a constant volume combustion chamber at 535 and 600 °C. The high reactivity fuel was replaced by the gaseous fuel up to 40 % by energy. The main ignition delay time was significantly affected not only by the type of low reactivity fuel, with ammonia considerably retarding autoignition, but also by the nature of the liquid fuel, biodiesel being the less sensitive to the presence of the H2-carrier fuel. Results also proved that the higher the reactivity of the diesel-type fuel (quantified through the cetane number), the lower the influence of the gaseous fuel on the autoignition time.

Promising Bioalcohols for Low-Emission Vehicles

In recent decades, many kinds of research have been conducted on alternative fuels for compression ignition (CI) engines. Low/zero-carbon fuels, such as bioalcohols and hydrogen, are the most promising alternative fuels and are extensively studied because of their availability, ease of manufacturing, and environmental benefits. Using these promising fuels in CI engines is environmentally and economically beneficial. The most common alcohols are methanol, ethanol, isopropanol, propanol, butanol, n-butanol, tert-butanol, iso-butanol, and pentanol. The primary objective of this review paper is to examine the impact of bioalcohols and their blends with conventional diesel fuel in CI engines since these fuels possess characteristic properties that impact overall engine performance and exhaust emissions. This research also indicated that alcohols and blended fuels could be used as fuels in compression ignition engines. Chemical and physical properties of alcohols were examined, such as lubricity, viscosity, calorific value, and cetane number, and their combustion characteristics in compression ignition engines provide a comprehensive review of their potential biofuels as alternative fuels.

Investigating the Effect of Compression Ratio on Operating Characteristics of Compression Ignition Engine Fueled with Diesel—Ricebran Biodiesel—n-Butanol Additive Blends

Investigating the Effect of Compression Ratio on Operating Characteristics of Compression Ignition Engine Fueled with Diesel—Ricebran Biodiesel—n-Butanol Additive Blends

Artificial neural network based prediction of engine-out responses from a biodiesel fuelled compression ignition engine

Numerical simulations, based on relatively complex physical models developed for CFD, can accurately predict engine-out responses, but they require huge memory space and/or computation time. In terms of resources and computer time, artificial intelligence methodologies are more cost-effective. In this work, we used an ANN to predict the performance and exhaust emissions of a single-cylinder Diesel engine running on fossil diesel, biodiesel, and their blends under various speed and load regimes. To perform the modeling, we employed multilayer perceptrons and a back-propagation gradient algorithm with momentum to train the network weights. The modification of the network weights was done using the second-order method of Levenberg-Marquardt, and the technique of early termination was utilized to avoid overtraining the model. The study involved using 70% of the complete experimental data to train the neural network, allocating 15% for network validation, and reserving the remaining 15% to evaluate the trained network effectiveness. The ANN model that was created demonstrated remarkable accuracy in predicting both engine performance and emissions. This is evident from the strong correlation coefficients observed, which ranged from 0.987 to 0.999, as well as the low mean squared errors ranging from 7.44?10-4 to 2.49?10-3.

Effects of Injection Timing and Antioxidant on NOx Reduction of CI Engine Fueled with Algae Biodiesel Blend Using Machine Learning Techniques

Fossil fuels are depended upon often in the transport sector. The use of diesel engines in all areas produce pollutants, such as NOx and CO, which cause serious environmental pollution and hazards, such as global climate change and breathing difficulties. Conventional fuel usage should be reduced, and there should be a shift toward alternative fuels. For compression ignition (CI) engines, microalgae biodiesel has been promoted as a clean, sustainable fuel. This is because it possesses desired traits, such as a quick rate of development, high productivity, and the capacity to turn CO2 into fuel. When algal biodiesel is used, pollutants, such as CO, UBHC, and smoke, are typically reduced, whereas NOx emissions are typically increased. The adoption of an exhaust gas recirculation technology and the advancement or delay of injection timing can effectively reduce NOx formation. Incorporating antioxidant chemicals such as butylated hydroxyl anisole (BHA) into fuel also minimizes NOx formation. In this study, the use of microalgae biodiesel as a substitute fuel for CI engines was investigated by altering the injection timing and adding each antioxidant in two doses. According to ASTM standard test procedures for biodiesel, the fuel qualities of various blends of algal biodiesel with antioxidants were tested and compared with the diesel fuel. The experiments were conducted using CI engines, and parameters were examined, such UBHC, CO, NOx, and smoke opacity. In comparison to diesel fuel, B20 + 30% BHA (21 bTDC) blends produced 49% lower oxides of nitrogen. The smoke, HC, and CO emissions of fuel blend B20 + 30% BHA (25 bTDC) were reduced by 33.33%, 32.37%, and 11.21%, respectively, compared with those of diesel fuel. The fuel blend B20 + 30% BHA (25 bTDC) showed the highest brake thermal efficiency of 14.52% at peak load condition. A multi-output regression deep long short-term memory (MDLSTM) model was designed to predict the performance and emissions of CI engines operating with varied fuel mixtures. The average RMSE and R2 values for the proposed MDLSTM were 0.38 and 0.9579, respectively.

Experimental assessment on the performance, emission and combustion characteristics of a safflower oil fueled CI engine with hydrogen gas enrichment

Inducting hydrogen with biodiesel in a compression ignition (CI) engine contributes to improvising the performance characteristics of the engine and minimize long-term issues. Combustion of hydrogen along with intake air impacts positively in air quality by preventing the formation of toxic emissions like hydrocarbons (HC) and carbon monoxide (CO). The benefits of hydrogen such as good diffusion rate, lesser ignition energy and fast flame propagation rate promotes a more homogenously mixed air fuel ratio. This experimental work focuses on enhancement of the performance and combustion characteristics of a direct injection compression ignition (DICI) engine by enriching the biodiesel with various levels of hydrogen gas supplement at the intake manifold. The brake thermal efficiency of the engine with safflower oil biodiesel is 31.15 % which is far inferior to that of diesel with 34 %. As an effort to improve the performance characteristics of the CI engine, hydrogen gas is inducted at 4 %, 8 % and 12 % energy share. HC, CO and smoke emission decreases by 15.09 %, 34.6 % and 18 % respectively compared to neat biodiesel at full load of 5.2 kW. An opposite trend is observed in NOx emissions which are raised from 1650 ppm to 1852 ppm. A 12.2 % increase in NOx emissions are realized due to homogenous flammable mixture that combusts closer to Top dead center (TDC). The hydrogen enrichment with safflower oil biodiesel influences the combustion characteristics in a positive vein except for the NOx emissions, which could be minimized through the use of retrofit devices like selective catalytic reducer, diesel oxidation catalyst etc.

Notable improvement of fuel properties of waste tire pyrolysis oil by blending a novel pumpkin seed oil–biodiesel

A comprehensive fuel property using neat diesel, neat tire (100% tire oil after distillation of crude tire oil from pyrolysis process) oil, diesel–tire oil blend and diesel–tire oil–biodiesel blends were investigated in this study. The tire oil was derived from waste tire by pyrolysis process at a temperature of 450 °C. The tire oil was upgraded by the fractional distillation process. Different proportions (10 vol% and 20 vol%) of waste tire oil were mixed with a reference diesel fuel. Various ratios, including 10 vol% and 20 vol% biodiesel was blended with waste tire oil and waste tire oil–diesel blends to examine the fuel properties with a target to use the different fuel blends as compression ignition (CI) engine’s fuel. A novel pumpkin seed oil (Cucurbita pepo) biodiesel was chosen due to its abundant availability and renewable nature. The reason for blending pumpkin seed oil–biodiesel is to improve the waste tire oil fuel properties and investigate the influence of fuel oxygen on different fuel properties. Binary blends, including tire oil–diesel, tire oil–biodiesel, and ternary blends, including diesel–tire oil–biodiesel, were prepared for the tests. The properties tested in this investigation were density, viscosity, higher and lower heating value, smoke limit, flash point, fire point, aniline point, pour point, cloud point, cetane number, sulphur and carbon residue, proton nuclear magnetic resonance (1H NMR), Fourier transform infra-red (FTIR) spectroscopy and elemental analysis (CHONS). The comprehensive fuel property results showed that all binary and ternary blends show similar properties compared to reference diesel. Although the binary blends of tire oil and biodiesel indicate a little inferior property than reference diesel fuel, they can be used as fuels for compression ignition engines.

Numerical Investigation of the Knocking Combustion Characteristics of the N-Butanol/N-Octanol RCCI Engine

The n-butanol/n-octanol fueled reactivity-controlled compression ignition engine was numerically studied based on the KIVA-CHEMKIN code. First, the knocking combustion characteristics were analyzed while functioning with a premixed n-butanol percentage of 20% (B20), since it exhibited the most severe knocking. Ten local regions were monitored to obtain local data, such as pressure and heat release rate. The local pressure oscillation was quantified by a band-pass filter. Second, the premixed n-butanol percentage and the intake valve close (IVC) timing were varied to investigate their effects on the combustion characteristics and emissions formations, as well as their potential for mitigating knocking. The results showed that a strong pressure oscillation was observed for B20 near the cylinder wall, which indicates severe knocking. This consequence is mainly caused by the low-temperature combustion of the n-octanol/n-butanol/air mixture near the cylinder-wall region. Increasing premixed n-butanol percentage and retarding IVC timing could result in an extended ignition delay, lowered peak pressure, and reduced maximum pressure rise rate (PRR). Condition B80 with an IVC timing of −126 °ATDC could improve the indicated mean effective pressure by 11.7% and reduce the maximum PRR by 63.4% when compared to condition B20.

Production of hydroprocessed renewable diesel from Jatropha oil and evaluation of its properties

Alternative fuel research is primarily motivated by the expeditious depletion in fossil fuel supplies and the need to fulfill rigorous emission regulations, particularly greenhouse gas (GHG) emission for modern diesel engines. Hydroprocessed (or Hydrogenated) renewable diesel (HRD) is seen takes the one’s place with possible option for replacement of fuels for Diesel engines in the hunt for a substitute to fossils based petroleum diesel from diverse sustainable feedstocks such as vegetable oils from non-edible seeds, animal fats or algae oil. Because when we compare cetane number for HRD and petro diesel, it is higher for HRD than the other, which is seen as a probable drop in alternate fuels for compression ignition engines. During production of renewable diesel Hydro-deoxygenation is done first with the help of a catalyst and hydrogen gas, which may be used to upgrade bio-oil instead of hydro-desulfurization (removing of sulphur derivatives from the crude vegetable oil). A sulfided Nickel Molybdenum (NiMo) or Cobalt Molybdenum (CoMo) catalyst based on gamma alumina is utilised as a reference catalyst for HDO in the generation of renewable diesel and is used as a standard catalyst for a hydro-desulfurization process in refineries. Jatropha oil may be thoroughly transformed into paraffins in the diesel range at a pressure of 40 to 90 bar. The obtained product includes gases and different products therefore, it is then transferred for fractional distillation which gets separated at different boiling temperatures. The Physicochemical properties of a hydroprocessed renewable paraffinic fuel were assessed and compared to Biodiesel and traditional petro diesel. The major properties of hydroprocessed renewable diesel like cetane number, flash point and pour point were higher compared that of petroleum diesel, whereas kinematic viscosity and thermal stability was almost similar for both HRD and diesel.