Lower Exhaust Emissions Research Articles

Combination of high cetane diesel fuel and post injection mode in a diesel engine: A path towards lower exhaust emissions

The major objective of the presented work is to explore the effect of post injection (PI) strategy using neat diesel fuel (D100) blended with cetane number enhancer (CNE). The motive behind adding CNE in diesel fuel was to lower its self-ignition temperature and hence delay period subsequently. This can lead to more efficient combustion of post injected fuel which leads to lower incomplete combustion losses. The CNE used was Di-Tert-Butyl Peroxide (DTBP) which was blended with D100 in proportion of 1 % by volume. Initially experiments were conducted with D100 under various PI modes where variation of post injection timing (PIT) as well as post quantity (PQ) was considered. The experimental results showed that implementing PI resulted in lower smoke, unburned hydrocarbon (UHC), carbon monoxide (CO) and nitrogen oxides (NOx) emissions compared to single injection while affecting fuel consumption negatively. Then after similar experiments under various PI modes were repeated using blends of D100 and DTBP (D/DTBP) and results were compared with D100 case. It was found that addition of CNE in D100 resulted in more complete combustion of post fuel which further reduced CO and UHC emissions. The shorter delay period in case of D/DTBP blend compared to D100 case led to lower NOx emissions as well as higher smoke emissions. The obtained results revealed that PI mode with 3 mg PQ and 20° after top dead center (ATDC) PIT with D/DTBP blend offered 41.18 %, 17.55 %, 64 % and 62.5 % reduction in smoke, NOx, UHC and CO emissions respectively compared to single injection mode using D100 fuel.

Skeletal CH3OH/NOx Kinetic Model for Simulating Spark-Ignition and Turbulent Jet Ignition Engines.

Methanol is a promising renewable fuel for achieving a better engine combustion efficiency and lower exhaust emissions. Under exhaust gas recirculation conditions, trace amounts of nitrogen oxides have been shown to participate in fuel oxidation and impact the ignition characteristics significantly. Despite numerous studies that analyzed the methanol/NOx interaction, no reliable skeletal kinetic mechanism is available for computational fluid dynamics (CFD) modeling. This work focuses on developing a skeletal CH3OH/NOx kinetic model consisting of 25 species and 55 irreversible and 27 reversible reactions, used for full-cycle engine combustion simulations. New experiments of methanol with the presence of 200 ppmv NO/NO2 were conducted in a rapid compression machine (RCM) at engine-relevant conditions (20-30 bar, 850-950 K). Experimental results indicate notable enhancement effects of the presence of NO/NO2 on methanol ignition under the conditions tested, which highlights the importance of including the CH3OH/NOx interactions in predicting combustion performance. The proposed skeletal mechanism was validated against the literature and new methanol and methanol/NOx experiments over a wide range of operating conditions. Furthermore, the skeletal mechanism was applied in three-dimensional (3D) CFD full-cycle simulations of spark-ignition (SI) and turbulent jet ignition (TJI) engine combustion using methanol. Simulation results demonstrate good agreement with experimental measurements of pressure traces and engine metrics, proving that the proposed skeletal mechanism is suitable and sufficient for CFD simulations.

Analysis of the effect of the number of injector nozzles on the pressure and heat transfer coefficient in a hydrogen-diesel mixture diesel engine

In reciprocating internal combustion engines, the calculation of the heat transfer coefficient (HTC) is essential to estimate the heat transfer during combustion in the combustion chamber. The HTC calculation takes into account fluid flow and combustion processes and varies as a function of crank angle and location within the chamber. The mean HTC value is commonly used to calculate the thermo-mechanical analysis of various combustion chamber components. In this study, dynamic grids for the intake port, exhaust port and chamber are created in the chamber modelling section of the AVL-Fire software. The intake and combustion processes are then simulated and the calculated pressure data are compared with experimental data at 2800 rpm with 1, 3 and 6 hole injectors. Finally, the distribution of HTC over the chamber walls was evaluated using a time step method. The research also included verification of the HTC results with theoretical data obtained by Woschni and Hohenberg. In addition, with the decreasing availability of fossil fuels and the need for lower exhaust emissions from diesel engines, the use of blends of diesel and hydrogen fuel has become widespread. In this engine, a mixture of 10 % hydrogen and 90 % diesel fuel is used. The final results show that the heat transfer coefficient increases by approximately 1.72 % when hydrogen is added to diesel fuel due to the number of collisions between hydrogen and other fuel components.

Analysis of Gasoline Engine Exhaust Emissions Using a Hydrocarbon Crack System

The increase in the number of motorbikes as a means of transportation results in increased exhaust emissions resulting from combustion of gasoline engines and is dangerous for human health. The use of a Hydrocarbon Crack System is one solution to reduce exhaust emissions in gasoline engines. Hydrocarbon Crack System can perfect the combustion process resulting in low exhaust emissions. The aim of this research is knowing gasoline engine exhaust emissions using the Hydrocarbon Crack System. The research used experimental methods applied to gasoline engine motorbikes with a fuel injection system. Adding Hydrocarbon Crack System is a tool to break down hydrocarbon elements in fuel gas. The use of the Hydrocarbon Crack System in gasoline engines reduces the levels of HC 20 percent and CO 4 percent exhaust emissions at rpm 5500 and above and the exhaust temperature is 215 degrees celsius so that it can maximize the work of the catalyst.

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.

Technical Implications of the Use of Biofuels in Agricultural and Industrial Compression-Ignition Engines with a Special Focus on the Interactions with (Bio)lubricants

The environmental sustainability of agricultural and industrial vehicles, as well as of the transportation sector, represents one of the most critical challenges to the sustainable development of a nation. In recent decades, compression-ignition engines have been widely used in on-road and off-road vehicles due to their better fuel economy, autonomy, compactness, and mechanical performance (spec. the high torque values). Due to the consistent environmental impact of fossil fuels, scientists are searching for alternative energy sources while preserving the beneficial features of diesel engines. The utilization of blends of diesel fuel, biodiesel, and bioethanol fuel (referred to as “ternary blends”) is among the most promising solutions for replacing fossil fuels in the near term, allowing, at the same time, us to continue using existing vehicles until new technologies are developed, consolidated and adapted to the agricultural and industrial sector. These ternary blends can lower exhaust emissions without creating major problems for existing fuel-feeding systems, typically designed for low-viscosity fossil fuels. One of the concerns in using liquid biofuels, specifically biodiesel, is the high chemical affinity with conventional and bio-based lubricants, so the main parameters of lubricants can vary significantly after a long operation of the engine. The comprehensive literature review presented in this article delves into the technical challenges, the main research pathways, and the potential solutions associated with the utilization of biofuels. Additionally, it investigates the emerging application of nanoparticles as additives in lubricants and biofuels, highlighting their valuable potential. This study also discusses the potential implementation of bio-ethanol in ternary blends, offering a promising avenue for reducing reliance on fossil fuels while maintaining engine efficiency.

Calibration and Experimental Study of a Self-Developed Particle-Number Measurement Instrument

To accurately evaluate the size and distribution characteristics of the emission particles exhausted from in-use motor vehicle engines, we independently developed a condensation particle counter (CPC) known as BHCPC. It was calibrated by conducting the calibration procedures stated in the International Standard ISO 27981. After calibration, we conducted on-site measurements and offline sampling analysis of soot particles exhausted from different engines at a motor vehicle inspection center. The calibration results show that the detection efficiency is 90% when the particle diameter is 20.6 nm and the startup response time of the instrument is 3.53 s. The experiment results show that the self-developed BHCPC demonstrates good consistency in measuring particle-number concentration (PNC) in motor vehicle exhaust, with significant count fluctuations only occurring when PNC is higher than 25,000 P/cc. Under idle conditions, motor vehicles compliant with China VI emission regulations exhibit markedly lower exhaust emission PNC compared to those adhering to China IV emission regulations. Moreover, the results obtained from the offline electron microscope analysis show that fuel content in particle samples significantly decreases as engine speed increases, and a similar variation was also found in particle size. The micro-characteristics of the particle can give potential support to the combustion diagnostics.

Feasibility Evaluation and Numerical Simulation of Diesel–Diethyl Ether–2–Methoxy Ethyl Ether Blends Fueling in Stationary CI Engine

In many developed economies, the diesel engine is very important for transportation and farming. There is a lot of research being done in the field of renewable energy to replace conventional energy sources because of the major environmental issues and the rising expense of diesel. Diesel engine cannot be reinstate because of its efficient performance at higher power and reliability with alternative engines. Diesel engine emissions are very harmful to the atmosphere and human health. The main contaminants in diesel engines are smoke and NOx, which need to be effectively monitored. A numerous research is going on to diminish the emissions from CI engines by using some additives as well as the use of alternative fuels. This experimental inquiry was conducted to identify a suitable addition to lower exhaust emissions and improve CI engine performance. The trials used various mix ratios of pure diesel and blends of diesel and diethyl ether-2-methoxy ethyl ether. Mixing of 5% DEE and 5% MXEE with 90% diesel on volume basis (D90–DEE5–MXEE5) showed optimum results of emission and performance. Low exhaust emissions (HC 63.15%, CO 60.00%, and Smoke 18.29%) found to be substantial at peak loads and performance increase (decreasing in BSFC 5.00% and increasing in BTE 3.00%) were compared to mixture D90-DEE5-MXEE5 with diesel (at standard engine conditions). However, NOx rises (2.60%).

Investigation of the Impact of Castor Biofuel on the Performance and Emissions of Diesel Engines

Fossil fuel is a non-renewable fuel, and with the development of modern industry and agriculture, the storage capacity of fossil fuels is constantly decreasing. In this study, a systematic study and analysis were conducted on the combustion characteristics, engine performance, and exhaust emission characteristics of castor biodiesel–diesel blends and pure diesel fuel in different proportions at different speeds of a single-cylinder four-stroke diesel engine under constant load. The castor biodiesel required for the experiment is generated through an ester exchange reaction and mixed with diesel in proportion to produce biodiesel–diesel blends. The experimental results show that as an oxygenated fuel with a higher cetane number, the CO, HC, and smoke emissions of diesel and B80 blend fuel at 1800 rpm were reduced by 16.9%, 31.6%, and 68%, respectively. On the contrary, the NOx and CO2 emissions increased by 17.3% and 34.6% compared to diesel at 1800 rpm. In addition, due to its high viscosity and low calorific value, the brake thermal efficiency and brake-specific fuel consumption of the biodiesel–diesel blends are slightly lower than those of diesel, but the biodiesel–diesel blends exhibit lower exhaust gas temperatures. Comparing B80 and diesel fuel at 1800 rpm, the BSFC of diesel at 1800 rpm is 3.12 kg/W·h, whereas for B80 blended fuel, it increases to 4.2 kg/W·h, and BTE decreases from 25.39% to 21.33%. On the contrary, B60 blended fuel exhibits a lower exhaust emission temperature, displaying 452 °C at 1800 rpm. Based on the experimental results, it can be concluded that castor biodiesel is a very promising clean alternative fuel with low waste emissions and good engine performance.

Impact of engine control variables on low load combustion efficiency and exhaust emissions of a methane-diesel dual fuel engine

A conventional diesel engine when operated in the reactivity-controlled compression ignition (RCCI) combustion strategy faces challenges of high total hydrocarbon (THC) and carbon monoxide (CO) emissions leading to poor combustion efficiency at low engine loads. The oxides of nitrogen (NOx) versus smoke trade-off, encountered in conventional diesel combustion, is replaced by the NOx-THC trade-off in the RCCI operation. This work focuses on addressing the NOx-THC trade-off issue by systematically investigating the effects of engine control variables, such as, fuel injection timing, exhaust gas recirculation (EGR) and intake throttling, on a light duty compression ignition engine running in a methane-diesel dual fuel mode. The engine is operated at a load of 3 bar gross indicated mean effective pressure and at a speed of 1500 rev/min. Based on relationships identified between engine control variables, combustion parameters, emissions and engine performance, a bottom-up approach is used to combine the control variables synergistically to improve the NOx-THC trade-off. A combination of advanced start of injection timing of diesel (−35 degree crank angle (°CA) after top dead centre), 50% premix ratio and 55% EGR levels along with the end of port fuel injection of methane in the middle of the intake stroke (−270°CA), has resulted in a ∼34 percentage points (from 56% to 90%) improvement in combustion efficiency and a ∼9.5 percentage points improvement in thermal efficiency compared to the baseline low load dual fuel operation while maintaining good combustion stability. THC emission is reduced from 105 to ∼25 g/kWh whilst maintaining low levels of NOx (<0.3 g/kWh).

A comprehensive study on the performance and emission analysis in diesel engine via optimization of novel ternary fuel blends: Diesel, manganese, and diethyl ether

Ecosystem degradation and fossil fuel depletion are the two foremost concerns to look for alternative fuels. Rapid population growth is primarily accountable for higher consumption of fossil fuel sources, although engine technology is achieving milestones in terms of fuel efficiency and lower exhaust emissions in order to contribute towards a sustainable environment. The main root cause of global warming is carbon dioxide emissions; therefore, it is imperative to assess the impact of alternative fuels in diesel engines with an aim to minimize carbon emissions. A current study deals with the reduction of carbon emissions and improvement of efficiency through addition of manganese nano-additive to di-ethyl ether and diesel fuel blend in particulate form. Fuel blends were formed by adding various proportions of manganese to high-speed diesel fuel and stirring the mixture while heating it for 10 min. The blends were then tested in diesel engines at two distinct loads and five engine speed ranges. Emission analyzer was used to ascertain the CO2 output of engine. At higher loads for 10 % diethyl ether in diesel, the increase in brake thermal efficiency was 24.19, 28.17 and 26.86 % when the manganese amount in blend was changed as 250 mg, 375 mg and 500 mg respectively. On the other side CO2 emissions increase by 11.57, 30.52 and 20.33 % for manganese concentrations of 250 mg, 375 mg and 500 mg respectively. Analysis performed with Design Expert 13 showed that the desirability was 0.796 for a blend of 375 mg manganese at 1300 rpm and 4500 W load with 33.0611 % BTE, 334.011kg/kWh BSFC, 67.8821Nm torque, and 6.072 % CO2. Therefore, it can be deduced that manganese nanoparticle blends improved engine performance but CO2 emissions also increase which can be responsible for global warming and it should be reduced through catalytic converters.

Study on SI Engine Operation Stability at Lean Condition—The Effect of a Small Amount of Hydrogen Addition

The lean-burn mode is a solution that reduces the fuel consumption of spark-ignition internal combustion engines and keeps the low exhaust emission, but the stability of the lean-burn combustion process, especially at low loads, needs to be addressed. Enhancing gasoline with hybrid hydrogen oxygen (HHO) gas—a mixture of hydrogen and oxygen gases—is proposed to improve combustion of the lean-gasoline mixture. A three-cylinder, spark-ignition, naturally aspirated, MPI engine with HHO gas produced with an alkaline water electrolyzer and introduced as a gasoline enhancement was tested. The amount of hydrogen added to the lean-gasoline mixture (λ = 1.4) was in the range from 0.15 to 1.5%, and the results were compared to the stoichiometric (λ = 1) and pure lean mode (λ = 1.4) gasoline operation. The other authors’ results show that a minimum 3% of the mass fraction of hydrogen is necessary to affect the gasoline combustion process. This paper proved that even a small hydrogen enhancement of gasoline in the amount of 0.3% of the mass fraction improves the combustion stability.

Physical and chemical characteristics of particles emitted by a passenger vehicle at the tire-road contact

Non-exhaust emissions are now recognized as a significant source of atmospheric particulate matter and the trend towards a reduction of conventionally fueled internal combustion engine vehicles on the road is increasing their contribution to air pollution due to lower exhaust emissions. These particles include brake wear particles (BWP) and tire-road contact particles (TRCP), which are composed of tire wear particles (TWP), road wear particles (RWP) and resuspended road dust (RRD). The goal of this study has therefore been to design an original experimental approach to provide insight into the chemical composition of particles emitted at the tire-road contact, focusing on the micron (PM10–1μm) and submicron (PM1–0.1μm) fractions. Through this characterization, an examination of the different TRCP generated by different materials (tire, road surface, brake system) was conducted. To achieve this, TRCP were collected at the rear of the wheel of an instrumented vehicle during road and track tests, and a SEM-EDX analysis was performed. Our experimental conditions have allowed us to demonstrate that, at the individual particle scale, TRCP are consistently associated with road dust materials and particles solely composed of tire or road materials are practically non-existent. The contribution of BWP to TRCP is marked by the emission of Fe-rich particles, including heavy metals like Ba, Mn and Cr. TWP, which result from rubber abrasion, consist of C-rich particles abundant in Si, Zn, and S. RWP, mainly composed of Al, Si, Fe, and Ca, can be either part of RRD or internally mixed with emitted TWP. The findings of this study highlight the substantial role of RRD to TRCP emissions under real driving conditions. Consequently, it underscores the importance of examining them simultaneously to achieve a more accurate estimation of on-road traffic emissions beyond the vehicle exhaust.

The Effect Of The Addition of Copper DB Killer On Yamaha Vixion 150cc Motorcycle on Exhaust Emissions

The addition of racing exhaust to a vehicle will greatly affect the quality of exhaust emissions. Racing exhausts that use the FreeFlow system which throws the remaining combustion gases out immediately without any deflection and catalyst in the racing exhaust. The addition of DB Killer uses nest-shaped copper material, besides reducing noise it also reduces excessive emissions and the material is easy to obtain, inexpensive, and has a simple manufacturing process. The advantage of DB Killer is that using a nest model copper plate catalyst material significantly reduces emissions compared to not using DB Killer. The DB Killer is installed at the end of a racing exhaust silencer and tested at different RPMs of 3500, 4500 and 5500. Tested using a gas analyzer to obtain CO, HC and CO2 values ​​for racing exhaust emissions without DB Killer and using a copper DB Killer. Obtaining the results of reducing exhaust emissions is much better and produces less noise. The result is a lower exhaust emission value because there is a DB Killer made of copper at the end of the exhaust silencer which can withstand emissions in the DB Killer which has a hollow design.

Misfire Detection Technology with Deep Neural Network Based on Ignition Coil Signals

<div>For achieving high efficiency and low exhaust emissions, engines need to be operated near the limits of stable combustion, such as lean or exhaust gas recirculation (EGR) conditions. Sensing technologies of the combustion state by existing engine components are of high interest. And the utilization of voltage and current signals from ignition coils is discussed in this article. The discharge channel of an ignition spark is strongly affected by flow variation and spark plug surface conditions, and the behavior of discharge channel stretching and restrike event can vary greatly from cycle to cycle. As a result, the effects of flow velocity, temperature, pressure, and electrode surface resistance are compounded in the voltage-current response, making it difficult to accurately detect the combustion state for each cycle by a threshold judgment process using a single feature value.</div> <div>In this article, a method for inductively detecting misfires from voltage and current signals of ignition coils by applying deep learning image recognition is introduced. First, post-ignition for misfire detection is performed on the engine bench during the expansion stroke in an engine cycle, when the cylinder pressure is expected to differ between the combustion cycle and the ignition cycle, and the ignition coil voltage and current are measured. Next, a two-dimensional frequency distribution of voltage and current (discharge histogram) is created as an input image for deep learning, and the AlexNet model, which has been trained with more than one million images, is trained with images of the ignition and combustion cycles as a supervised learning. The accuracy of classification is then verified using a validation dataset. In addition, to making the deep learning model more explainable, the activation score distribution on the discharge histogram was visualized when the trained model judges the images, and the discharge characteristics that provided the basis for deep learning classifications were analyzed.</div>

Methanol Vehicles in China: A Review from a Policy Perspective

Mature methanol vehicle technology with low exhaust emissions and economic benefits are a viable way to mitigate oil dependency and reduce greenhouse gas emissions. As a result, pilot projects for methanol vehicles have been carried out in 10 different cities in China over the last decade. They positively affect the economy and the environment, as shown by the acceptance results. This study chronologically reviewed the previous development and adopted pertinent policies determine the feasibility of deploying methanol vehicles from national to provincial levels. Based on the analysis and evaluations, the local government is suggested to make the following dynamic policy recommendations: (a) Before reaching the “carbon peak”, development strategies should be formulated according to the resource situation of each region. Priority should be given to the deployment of coal-to-methanol vehicles and bio-methanol vehicles to maximize the economy, so as to promote the construction of transmission and distribution systems, advance the manufacturing process of methanol fuel, and prepare the technology for the next stage. (b) In the second stage, the advancement of CO2-to-methanol technology should be promoted, focusing on the development of green methanol vehicles to better contribute to the “carbon neutrality”.

Combustion performance characteristics of double-layer diverging combustion chamber compared with re-entrant chamber and omega chamber

Combustion chamber is a main component for Diesel, as it organizes the fuel-air mixing and combustion processes and eventually determines Diesel performance. In the past decades, the chamber turned into the higher radius-to-depth ratio and lower area-to-volume ratio type to increase the in-cylinder air utilization and promote the fuel spray spreading. The Double-Layer Diverging Combustion chamber (DLDC chamber) was designed in this background. In order to obtain the DLDC chamber performance characteristics comprehensively, a 135-type Diesel with a DLDC chamber, a re-entrant chamber and a ω chamber was selected. The results suggested that the DLDC chamber decreased the BSFC and soot emission, but increased the NOx with higher pmax and heat release rates during the premixed combustion phase, as it could divide the fuel into two layers and promote the fuel spreading and combustion; adjusting the injection parameters made the BSFC and exhaust emissions of the DLDC chamber change quite differently, because the different layers of the DLDC chamber had their own chamber-spray-charge motion matchings. Finally, the investigation indicated that the DLDC chamber provided lower exhaust emissions compared with the other two chambers by keeping the same fuel consumption; moreover, the DLDC chamber provided the lowest BSFC and soot emission in the three chambers under the same NOx emissions level.

Large eddy simulation of a premixed dual-fuel combustion: Effects of inhomogeneity level on auto-ignition of micro-pilot fuel

In a premixed dual-fuel (DF) methane-diesel engine, the ignition of the lean premixed methane/air mixture starts with the assistance of a pilot diesel injection. Auto-ignition of pilot fuel is important as it triggers the subsequent combustion processes. A delay in the auto-ignition process may lead to misfiring, incomplete combustion, and thus higher greenhouse emissions due to methane slip. Hence, a better understanding of the auto-ignition process for the pilot fuel can help to improve the overall engine performance, combustion efficiency, and to lower exhaust emission levels. In the present study, large eddy simulation (LES) is used to investigate the auto-ignition process of micro-pilot diesel in premixed DF combustion in a constant volume combustion chamber (CVCC). The entire DF combustion processes including methane gas injection, methane/air mixing, pilot diesel injection, and ignition are simulated. The numerical model is validated against experimental data. The present numerical model is able to capture the ignition delay time (IDT) within a maximum relative difference of 7% to the measurements. A higher relative difference of 38% is obtained when methane gas injection and mixing are omitted in the simulation and the methane/air is assumed homogeneous. This demonstrates the importance of inhomogeneity pockets. To study the effects of temperature and methane inhomogeneities separately, different idealized inhomogeneities in temperature and methane distribution are considered inside the CVCC. The inhomogeneity in the temperature is observed to have a more profound influence on the IDT than the methane inhomogeneity. The inhomogeneity pockets of temperature advance the first-stage ignition and, subsequently, the second-stage ignition. A sensitivity analysis on the effect of inhomogeneity wavelength reveals that the larger wavelengths enhance the combustion due to the presence of pilot diesel jets in the desirable regions for a longer time duration.

Support vector regression approach to optimize the biodiesel composition for improved engine performance and lower exhaust emissions

The practical applicability of biodiesel is limited due to poor fuel economy and higher emissions of oxides of nitrogen. Moreover, engine characteristics vary significantly with biodiesel type, highlighting the necessity to determine the most suitable biodiesel for improved fuel economy and emissions. Choosing the most suitable biodiesel is challenging as the relationship between biodiesel composition and engine characteristics is complex. Thus, it is intended to determine the most suitable biodiesel by developing composition-based models that predict engine characteristics and use them for optimization. This study explores the applicability of support vector machine regression to correlate biodiesel composition with engine characteristics. Two additional biodiesels not used for calibration validate the developed models with an acceptable mean absolute percentage error of less than 7%. Further, the models are fed to the genetic algorithm to determine the optimal composition for lower brake specific fuel consumption (BSFC) and emissions of unburnt hydrocarbon (HC), carbon monoxide (CO), and oxides of nitrogen (NOx). The optimized biodiesel has 8% shorter chain esters and 92% longer chain esters. Sunflower biodiesel exhibits 23% higher BSFC than diesel, whereas for optimized biodiesel, it is 4% higher. The proposed biodiesel results in 42% and 2% less HC and CO emissions than diesel and are reasonably lower than other biodiesels. The optimized biodiesel results in 42% higher NOx emissions, while sunflower biodiesel exhibits 83% higher NOx emissions than diesel. Overall, the optimized biodiesel resulted in a minimum penalty in fuel economy and NOx emissions compared to other commercially available biodiesels.

Modulation of the best conditions for improved engine performance and reduced exhaust emissions using an eco-friendly nano additive in parsley biodiesel blend

This research work aims to assess the optimal conditions that would lower exhaust emissions and enhance engine performance using a green synthesized silica nano additive added parsley biodiesel blend. Hence, the process variables were optimized and the interactive influence of engine speed, engine load, and biodiesel blend (B20SNP) concentration was examined using the central composite design tool integrated into the response surface methodology design. The findings of this study showed that the studied variables had a substantial effect on the responses. Also, the ideal conditions for improved efficiency and reduced emissions were predicted to be B20SNP (100 ppm), engine speed (1458.60 rpm), and engine load (98.07%) while the best responses for improved engine characteristics were BTE (31.91%), BSEC (5.97 MJ/kW), BSFC (0.388kg/kWh), HC (19.18%), NOx (198.21 ppm) and CO (0.050 %) at the desirability of 1.000. The results of the ANOVA analysis revealed that B20SNP had the most influence on the behavior of the investigated four-stroke single-cylinder diesel engine. Furthermore, the results of this study asserted that silica nanoparticles made from waste sugarcane bagasse greatly enhanced the diesel engine’s efficiency and reduced emission behavior.