Brake Specific Fuel Consumption Research Articles

RSM Hybrid Modeling of a BSFC for a Single Cylinder Four Stroke CI Engine Fueled with Nano-additives Added to Diesel-biodiesel Fuel Blends

Introduction: The expanding need for fossil fuels emphasizes the necessity to comprehend renewable energy sources. Methods: This study examined the performance of a single-cylinder diesel engine using Jatropha biodiesel and aluminum dioxide—the research aimed to evaluate engine reactivity to compression ratio and load variations. The experiment employed with varitaion compression ratios. Results: This study used the Response Surface Methodology to find the best Brake Specific Fuel Consumption performance indicator location. The researchers used a Central Composite Design setup for analysis. A regression model employing the response surface approach was then created to predict fuel phase-out likelihood. Conclusion: This study examines multiple factors' effects. According to studies, Jatropha biodiesel and its blends may improve engine efficiency and lower brake-specific fuel consumption compared to diesel fuel. Minor input parameter modifications are needed to gain these benefits.

Enhancing biodiesel engine performance and emission reduction using Fe and Zn coated zeolite catalytic converters

ABSTRACT This study evaluates the performance and emission characteristics of diesel, fish biodiesel (comprising 20% fish oil and 80% diesel), and fish biodiesel using Fe and Zn-coated zeolite catalytic converters. The research aims to mitigate environmental challenges associated with diesel engines by exploring the efficacy of metal-doped zeolite catalysts in reducing harmful emissions. Fish biodiesel was derived from fish waste via transesterification and tested in a single-cylinder diesel engine. Key performance metrics, including Brake Specific Fuel Consumption, Brake Thermal Efficiency, Exhaust Gas Temperature, cylinder pressure, Heat Release Rate, and ignition delay, were measured. Emission characteristics such as carbon monoxide, hydrocarbon, nitrogen oxide, and smoke opacity were also analyzed. Results showed diesel had the lowest Specific fuel consumption, ranging from 730 g/kWh at 25% load to 320 g/kWh at full load. Fish biodiesel exhibited higher Specific fuel consumption, from 770 g/kWh to 350 g/kWh. Regarding emissions, the NOx of the biodiesel increased significantly compared to diesel; the use of a catalytic converter has reduced the NOx emission to a maximum extent of 37.5% at full load for a Fe-coated converter. The Zn-coated converter also improved emissions by up to 33% for NO but was slightly less effective than the Fe-coated converter. The study concludes that Fe-coated zeolite catalytic converters significantly enhance biodiesel-fueled diesel engines’ performance and emission characteristics. Both catalytic converters reduced the smoke emission significantly. These findings highlight the potential for developing more efficient and eco-friendly emission control technologies and promoting using renewable transportation fuels.

Biofuel blends and nano-additives: a sustainable approach to diesel engine performance and emissions improvement

Abstract The utilization of compression ignition (CI) diesel engines has seen a substantial increase in recent years owing to their numerous advantages. However, the widespread adoption of these engines has also significantly contributed to environmental pollution issues, with diesel engines being recognized as major global contributors to exhaust emissions-related pollution. To address this issue, comprehensive research has been carried out on both emissions from diesel exhaust pollutants and advanced after-treatment technologies for emission control. This study aims to evaluate the efficiency and emissions of diesel fuel mixed with various ratios of biofuel derived from Karanja seeds (B10, B15, and B20). Among the different blends examined, B20 demonstrated superior performance in terms of brake thermal efficiency (BTE) and brake-specific fuel consumption (BSFC), along with lower levels of hydrocarbon (HC) and carbon dioxide (CO2) emissions compared to pure diesel. Further, the impact of nanoadditives, specifically titanium dioxide (TiO2), at different concentrations (80 ppm, 100 ppm, and 120 ppm), on B20 blends was evaluated. The findings indicated that B20 blended with 100 ppm of TiO2 exhibited superior performance in terms of BTE, BSFC, and lower emissions of HC, CO2, nitrogen oxides (NOx), and carbon monoxide (CO). From the results, the BTE increases from 1% to 33%, illustrating enhanced thermal efficiency under similar conditions. The average BSFC across all loads and speeds in the table is approximately 0.89 kg/kWh, while the average BTE stands at approximately 23.1%.

Effects of High-Density Polyethylene (HDPE) and Additives Fuel Blends on Diesel Engine’s Performance and Emissions and NOx Prediction using Boosted Tree Model

The rising demand for eco-friendly and sustainable fuel options has prompted the investigation of alternative energy sources. This study explores the use of blends of High-Density Polyethylene (HDPE), and 7% biodiesel (B7) with additives as a substitute for diesel fuel. The research involves comparing three different mix ratios of HDPE and additives with a conventional B7 blend: a control of 100% B7, a mix of 90% B7 with 10% HDPE, and a blend of 85% B7 with 10% HDPE and 5% additives. Fourier Transform Infrared (FTIR) spectroscopy was employed to identify the fuels' functional groups. The study also measured key performance metrics, including brake-specific fuel consumption (BSFC), brake power (BP), and exhaust emissions of nitrogen oxides (NOx), carbon monoxide (CO), hydrocarbons (HC), and carbon dioxide (CO2). A Boosted Tree Model was used to establish a prediction and analysis of NOx emissions. The findings indicate that incorporating additives into the HDPE blend positively influences both engine performance and emissions. The combination of HDPE and additives with B7 resulted in reduced emissions across various engine loads and speeds, decreasing hydrocarbon and carbon-containing emissions. The Boosted Tree Model, with a configuration of 4 leaf nodes, demonstrated strong predictive accuracy, with a coefficient of determination (R2) of 0.86 and a root-mean-square error (RMSE) of 0.38 for the training dataset, and R2 of 0.97 with RMSE of 0.16 for the validation dataset. The study underscores the benefits of integrating HDPE and additives into diesel blends, highlighting their potential to lower emissions and supporting the search for viable alternative fuels.

Effect of hybrid nanoparticles dispersed ternary fuel blend on diesel engine performance and emissions: Experimental and Taguchi-Grey relation study

The present study deals with the influence of hybrid nanoparticles dispersed in ternary fuel mixtures on the evaluation of the performance and emission characteristics of a single cylinder diesel engine. The fuel blend consists of 70% diesel, 20% Madhuca longifolia biodiesel, and 10% ethanol (by volume). The hybrid nanoparticles of ferric chloride (FeCl3) and graphene nanoparticles were then added to this ternary fuel mixture in different proportions, namely 50 mg/L and 75 mg/L, together with the surfactant and the dispersant in a ratio of 1:1. Moreover, the experiments were conducted on a diesel engine to evaluate the performance and emission parameters by varying different fuel samples, different loads (3, 6, 9, and 12 kgf) and injection pressures (i.e. 200, 225,and 250 bar). In addition, the Taguchi-Grey relation analysis was used for optimization, and the input parameters are fuel samples, loads and injection pressures. Experimental performance metrics, including brake specific fuel consumption (BSFC) and brake thermal efficiency (BTE), were improved when hybrid nanoparticles were added to the ternary fuel blend compared to diesel. At the same time, smoke opacity, nitrogen oxides (NOx), unburned hydrocarbons (UHC) and carbon monoxide (CO) emissions were reduced. Increasing the injection pressure also led to positive results, apart from NOx. Both performance and emissions were better for hybrid nanofuel based on surfactants and dispersants than for the base fuel, and it performed better of all dispersant-added nanofuels. The better results were obtained with D70B20E10NPs75QPAN75 mg/L than with the other fuel samples. The maximum BTE and lowest BSFC are 33.26% and 0.206 kg/kWh, while the minimized CO, UHC, NOx and smoke values at full load are 0.019%, 21 ppm, 833 ppm and 36.25%, respectively, at full load and injection pressure of 250 bar. By combining experimental investigations with the Taguchi -Grey method, a comprehensive and rapid assessment of the effects on the performance and emission characteristics of diesel engines was achieved.

Synthesis and characterisation of waste-derived biodiesel and enhancement of its energy and environmental metrics using cetane improver: an experimental study

The primary objective of this study is to produce Bauhinia monandra biodiesel (BMB) using seed waste and improve its energy and environmental properties by integrating a cetane enhancer. The methyl ester of biooil was obtained using the transesterification method, and the properties were analyzed. Different quantities of BMB were combined with diesel fuel, and 2-ethyl hexyl nitrate (EHN) was introduced to the blend of 30% BMB-diesel fuel to improve both energy and environmental performance measurements. The research findings indicate that the FAME and physicochemical properties of BMB are comparable to those of diesel fuel. The brake thermal efficiency (BTE) of the engine decreases by 4.2% for 30% BMB blended fuel, whereas hydrocarbon (HC), carbon monoxide (CO), and smoke emissions decrease by 11.6%, 6.7%, and 10.5%, respectively. As the concentration of BMB increases, there is a reduction in both the maximum value of in-cylinder pressure and the net heat release rate. Conversely, brake-specific fuel consumption (BSFC) and NOx emissions increase by 5.7% and 4.7%, respectively. The incorporation of EHN in the test fuel enhances BSFC and BTE by 4.2% and 4.3%, respectively, whereas NOx, HC, and CO emissions are reduced by 5.2%, 9.2%, and 9.9%, respectively.

Evaluation of the Possible Effects of Varying the Volumetric Ratio of Lpg on the Spark Ignition Engine's Performance, Emissions, and Combustion

This study investigated the performance, emission reactions, and combustion of liquefied petroleum gas (LPG) at various volumetric ratios with gasoline. The experiments were carried out on a single cylinder spark ignition (SI) engine at different engine loads (500 to 3000 W). In general, the use of LPG has a negative effect on performance and combustion, while making a positive contribution to emissions. The brake thermal efficiency (BTE) and brake specific fuel consumption (BSFC) values closest to 100% gasoline were obtained with 25% LPG and were lower by 0.36% and 4.55%, respectively. Conversely, using LPG resulted in lower emissions of carbon dioxide (CO2), hydrocarbons (HC), and carbon monoxide (CO). The lowest emissions were obtained with the use of 100% LPG as 0.5%, 65 ppm and 9.5%, respectively. Compared to 100% gasoline, 20.63%, 27.78% and 5.19% improvements were achieved. Finally, the cylinder gas pressure value was negatively affected using LPG. Compared to 100% gasoline, the gas pressure value obtained with 75% LPG content fuel was 7.81% lower. It has been concluded that LPG is an environmentally friendly alternative fuel in terms of emissions, and considering the decrease in performance values, 25% LPG can be used successfully in SI engines instead of 100% LPG.

Evaluating Engine Performance, Emissions, Noise, and Vibration: A Comparative Study of Diesel and Biodiesel Fuel Mixture

This study investigates the performance, emissions, noise, and vibration characteristics of a single-cylinder, air-cooled, four-stroke diesel engine running on pure diesel (D100) and biodiesel blends (B10: 90% diesel, 10% biodiesel; B20: 80% diesel, 20% biodiesel) at 1800 rpm, where the engine delivers maximum torque. Key metrics such as torque, power, brake specific fuel consumption (BSFC), exhaust gas temperature, noise, vibration, and emissions (CO, CO2, HC, O2, NOx, and smoke opacity) were analyzed. The findings indicate that B10 enhances torque, power output, and overall fuel efficiency, especially at low to medium loads, with a significant 17.54% reduction in BSFC compared to D100 at 40% engine load. Vibration levels generally increased with biodiesel addition, while B10 and B20 both reduced smoke opacity, with B20 having a more substantial effect. HC emissions decreased at idle with B10 but increased at higher loads, suggesting more complete combustion with potential thermal stress on engine components. Noise and vibration results were mixed; B20 reduced noise at higher loads but increased vibration. At 100% load, B20 decreased noise by 1.42% compared to D100. Despite benefits such as improved torque and reduced particulate emissions, biodiesel blends, particularly B20, led to increased NOx and CO2 emissions, emphasizing the need for further op-timization of blend formulations and emission control strategies. This study provides valuable insights into the tradeoffs and potential of biodiesel blends as sustainable diesel alternatives.

Enhancing the Performance and Emission characteristics of Butanol-Diesel Blend with Ethanol

—In this experimental work diesel is blended with 12% v/v ethanol(E12D88), 12% v/v butanol (B12D88), 20%v/v butanol (B20D88) separately) and a fourth blend with 12% and 8% v/v of butanol and ethanol in diesel (B12E08D88) are prepared. These blends are experimentally investigation on a VCR engine at different loadings. Their performance and emission (PE) characteristics are compared with pure diesel in order to have optimum blending ratio. From the investigation it is found that B12D88 is having better brake thermal efficiency (BTE) and Brake specific fuel consumption (BSFC) is better than all the blends at all loading condition. This is due to lower density, Cetane number and Calorific value (CV) of the alcohol as compared to pure diesel, CV of butanol is 23% more than ethanol. Emission characteristics of E12D88 is observed better than all the fuels. oxygenated fuels have lower emission. On investigating the data, it is observed that B12E08D80 blend is having better CO and HC emission than E12D88, Nox emission is larger than E12D88 but better than butanol blend and performance is close to B12D88

NUMERICAL AND EXPERIMENTAL RESEARCH ON THE DI-CI ENGINE PERFORMANCE CHARACTERISTICS UNDER LPG - DIESEL DUAL FUEL COMBUSTION MODE

Properties of Liquefied Petroleum Gas (LPG) are suitable as an alternative fuel for internal combustion engines. This work aims to combine both numerical optimization analysis of LPG injector placement angle and subsequent experiment with selected mounting injector angle to investigate the effects of using LPG as a parallel-partial substitute fuel with diesel fuel under dual-fuel combustion mode. An electronic injection fuel control system was applied to the modified intake manifold to generate the appropriate LPG injection. Three mounting angle injector positions including 450, 900 and 1350 in the upstream direction of intake air have been defined by Ansys Fluent to take into account efficient LPG-air mixing. Then, the experiment was conducted with LPG-diesel dual-fuel combustion mode (DFC mode) and compared to entirely diesel combustion mode as baseline data. Different load conditions ranging from idle to 4.0 kW were imposed at a constant engine speed of 1700rpm. The obtained results revealed that the injector’s mounting angle position by 45 opposite to the intake air flow showed the correlation with the calculated LPG-air ratio in dual fuel combustion reaction. In DFC mode, the brake thermal efficiency (BTE) decreased on average by 4.6% and the LPG substitution rate gradually decreased while brake-specific fuel consumption (BSFC) increased for all engine loads. The exhaust temperature in the dual-fuel combustion mode was found to be higher than that of full diesel fuel mode at low loads (less than 2.5 kW) and began to decrease at higher loads.

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.

Investigation of the performance and emission effects of ammonia-borane as a B–N-based amine-borane adduct in gasoline engines

This study examined the impact of varying concentrations of ammonia-borane (AB) in gasoline on engine performance and emissions across different load conditions. Four fuel formulations were tested: pure gasoline (G100) and gasoline blends containing 10%, 15%, and 20% AB (AB10, AB15, AB20). Increased AB concentration resulted in higher brake-specific fuel consumption (BSFC). While exhaust gas temperatures were highest with G100 (730.9 °C at full load), the AB blends, particularly AB20, exhibited lower temperatures, with a maximum reduction of 13.8%. The AB20 blend demonstrated elevated BSFC and increased oxygen (O₂) emissions but significantly reduced carbon monoxide (CO) emissions, with up to an 88.2% decrease at full load. Nitrogen oxide (NOx) emissions were generally lower for all AB blends. The highest NOx value was measured with G100 fuel at full load, while the lowest NOx value was measured with AB10 fuel. Under these conditions, a 23% decrease in NOx value was observed with AB10 fuel compared to G100. The engine's thermal efficiency decreased with AB blends at all load levels compared to pure gasoline. Thermal efficiency decrease of 13.76%, 22.32%, and 30.88% occurred for AB10, AB15 and AB20, respectively compared to G100.Overall, incorporating AB in gasoline reduced thermal efficiency and led to a notable decrease in NOx, hydrocarbons (HC), and CO emissions.

Applied AMT machine learning and multi-objective optimization for enhanced performance and reduced environmental impact of sunflower oil biodiesel in compression ignition engine

Biodiesel has emerged as a compelling substitute for conventional diesel fuel, providing a sustainable and eco-friendly choice for fueling compression ignition engines. This comprehensive study investigates the influence of biodiesel, specifically derived from sunflower oil, through the esterification method, on crucial engine performance parameters and environmental effects. The study examines the impact of varying engine torque on the performance of a single-cylinder, four-stroke compression ignition engine, encompassing parameters such as brake thermal efficiency (BTE) and brake specific fuel consumption (BSFC), as well as exhaust emissions, including unburned hydrocarbons (HC), carbon monoxide (CO), and nitrogen oxides (NOx). Four distinct biodiesel blends (B10, B20, B30, B40) with varying sunflower oil content are systematically compared to pure diesel (B0). The engine operates at a consistent speed of 1700 rpm, while the torque undergoes controlled adjustments from 0 to 10 Nm. Subsequently, this study explores the application of an alternating model tree (AMT) machine learning algorithm to establish relationships between independent factors, specifically torque and biodiesel volume (%vol), and dependent variables, including BTE, BSFC, CO, and NOx in a combustion engine. Additionally, the study employs a multi-objective ameliorative whale optimization algorithm (AWOA) to optimize the model's output. The objective is to identify optimal values for torque and%vol that maximize engine performance (BTE) while minimizing engine emissions (CO and NOx) and reducing fuel consumption (BSFC). The optimization process yields noteworthy results, with AWOA achieving peak BTE at 29.714 %, BSFC at 0.262 kg.kWh-1, and NOx emissions at 992 ppm at torque 7.3 N.m and 13% vol. In contrast, particle swarm optimization (PSO) secured the minimum CO level at 0.123 %, with torque set at 7.6 N.m and 26% vol. The AMT models demonstrate high prediction accuracy, with coefficient of determination (R2) values exceeding 0.98.

Comparison of machine learning algorithms on a low heat rejection diesel engine running on ternary blends

Depletion of fossil fuels and increasing the energy demand are the critical concerns for the sustainable growth of every country. These challenges highlight the need for a cleaner fuel globally. In particular, substituting the petroleum fuels with biofuels could significantly support sustainability. Hence, this study explores the impact of acetylene induction in a low heat rejection (LHR) diesel engine with ternary blend (TB) as a pilot fuel. TB includes 10%methanol + 20%WCOB + 70%diesel. During the dual fuel operation, the acetylene induction was varied (12, 18, and 24 lpm) with different pilot fuel combinations in a LHR engine. From the experimental results, it was revealed that brake thermal efficiency (BTE) is improved by 10.3% for TB with acetylene at 24 lpm and increased the exhaust gas temperature (EGT) by 10.3% at full load conditions. This study further evaluates the implementation of machine learning algorithms, namely, Random Forest regression (RFR) and Polynomial regression (PR) in predicting the performance parameters [BTE, brake-specific fuel consumption (BSFC), and EGT]. The results indicate that RFR outperforms PR in accurately predicting engine performance characteristics with a coefficient of determination R2 = 0.97, R2 = 0.98 for BTE, whereas for BSFC the R2 = 0.96, R2 = 0.95, and for EGT, the R2 = 0.95, R2 = 0.97 for the test fuels diesel and TBA3, respectively. These findings suggest that the combination of LHR technology, TB fuel, and acetylene can enhance engine efficiency and performance characteristics, and machine learning models can effectively predict these outcomes.

Parameter optimisation of marine four-stroke engine EGR systems using RSM and NSGA-III

ABSTRACT To reduce NOx emission of marine engines, an engine parameter optimisation method combining response surface method (RSM), Bayesian neural network and non-dominated sequence genetic algorithm (NSGA-III) is proposed. First, a simulation model of a marine four-stroke engine with an external exhaust gas recirculation (EGR) system was established and validated in AVL-BOOST software. Then, the five parameters of EGR valve opening, ignition advance angle, compression ratio (CR), intake valve opening (IVO) and exhaust valve closing (EVC) are selected as the decision parameters, and the three parameters of engine power, brake specific fuel consumption (BSFC) and NOx emission are taken as the target parameters to be optimised. In Design-Expert software, the response surface model is established by using the experimental design approach of central composite design (CCD), and the impact of decision parameters on target parameters are discussed by using response surface analysis. NSGA-III was used for the multi-objective optimisation of parameters, and the accuracy of NSGA-III was improved by the Bayesian neural network. The optimal solution is selected and verified by the technique for order of preference by similarity to the ideal solution (TOPSIS) approach. The results show that when the EGR valve opening is 47.5%, ignition advance angle is −18.99°CA, CR is 14.995, IVO is 15.27°CA and EVC is 7.68°CA, compared with the standard setting, the optimised power is increased by 4.17%, BSFC is reduced by 4.27%, and NOx emissions are reduced by 12.37%. Therefore, the combination of the Bayesian neural network and NSGA-III multi-objective optimisation can improve engine performance while reducing fuel consumption and NOx emissions.

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.

Numerical and experimental analyses for performance and emissions assessment of a four-stroke engine powered by oleic acid methyl ester biofuel made from waste frying oil

<p style="text-align:justify"><span style="font-size:11pt"><span style="line-height:150%"><span style="font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:12.0pt"><span style="line-height:150%"><span style="font-family:"Times New Roman",serif">Recently, several earlier works conducted research works dedicated to replacing fossil-based fuels with environmentally friendly ones. The goal of the research is to construct a multivariate linear regression model for the attributes of a four-cylinder diesel engine fueled by biodiesel. In this context, the goal of the research is to structure a multiple linear regression example for characterizing a four-cylinder engine fueled by biodiesel. In fact, experimental research was conducted on an agricultural tractor equipped with a 4-cylinder direct-injection diesel engine. The biodiesel is made from waste frying oil without blending referred to as the oleic acid methyl ester (OAME) biofuel. The biodiesel was extracted through a chemical transesterification reaction. The four-stroke engine is tested for both pure OAME biofuel and conventional diesel. One-dimensional numerical simulations were conducted. A strong correlation between numerical and experimental data was observed, validating the numerical model. Using the engine model, in-cylinder pressure, heat release rate, in-cylinder temperature, and emissions including Carbon monoxide (CO), nitrogen oxides (NO<sub>x</sub>), and Carbon dioxide (CO<sub>2</sub>) were recorded across a broad range of engine operating speeds. Additionally, brake-specific fuel consumption (BSFC) and brake power were numerically calculated and compared to experimental data. The results showed that usage of the OAME as a biofuel could be a promising solution that enables similar performances with lower CO emissions compared to petroleum diesel particularly at low engine speeds.</span></span></span></span></span></span></p>

Experimental study of diesel engine performance and emissions from microalgae fuel blends with SiO2 nanoadditives: RSM and Taguchi optimization.

In this investigation, the effects of blending microalgae biodiesel with silicon dioxide (SiO2) nanoparticles in a diesel engine are evaluated. For the study, test fuels (diesel, B20, B20n25, B20n50, B20n75, and B20n100) were prepared by blending pure diesel with microalgae biodiesel with the addition of SiO2 nanoparticles having particle sizes ranging from 25 to 100 ppm. A liquid-cooled, two-cylinder, four-stroke, compression ignition engine having a load range between 2 and 12 kW, fuel injection timing of 23° bTDC, and 16.5:1 compression ratio was chosen for this study. The results demonstrated that the test fuels enhanced the engine performance and declined emissions. Performance parameters such as brake thermal efficiency (BTE) and brake-specific fuel consumption (BSFC) were all improved by 1.6-4.8% and 8.55-15.33%, respectively, by the biodiesel containing SiO2 nanoparticles. At full engine load, emissions such as carbon dioxide (CO2), smoke opacity (BSN), and NOx declined by 1.8-9%, 6.2-21.4%, and 19-34% respectively. The study backs the use of SiO2 nanoadditives for better performance and lower emissions in diesel engines. Test results were analyzed by Taguchi and RSM method to find optimized conditions.

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.

Innovative research on waste tire recycling for sustainable biofuel production: Assessment of its usability on multi-cylinder diesel engine employing constant injection of oxyhydrogen and biogas through a premixing device

This study investigates the production of waste tire pyrolyzed oil on a laboratory scale and its potential use as a fuel along with biogas and hydrogen in a variable-speed transportation engine. The pyrolyzed oil, obtained from waste tire pieces through a lab-scale plant, undergoes distillation and is blended with diesel fuel in a 20% ratio. This blended fuel is supplied to a multi-cylinder variable-speed transportation engine, either alongside biogas or HHO separately or both combined, at fixed flow rates with air passage through a premixing device (venturi). This study aimed to assess engine combustion characteristics such as in-cylinder pressure and heat release rate; performance parameters, including brake thermal efficiency (BTE) and brake-specific fuel consumption (BSFC), as well as emissions of hydrocarbons (HC), carbon monoxide (CO), and nitrogen oxides (NOx). The results indicate that using pyrolyzed oil in unmodified diesel engines reduces combustion characteristics and performancewhile increasing HC and NOx emissions and decreasing CO emissions. In addition, supplying biogas and the fuel mixture further deteriorates combustion and performance, while increases HC and CO emissions, and reduces NOx emissions. The focus of the present research is to evaluate the impact of adding green hydrogen (HHO) gas to a pyrolyzed oil fuel mixture and a biogas-led fuel mixture in a compression ignition (CI) engine. The results indicate that the addition of hydrogen enhances combustion characteristics, engine performance and reduces emissions, except for NOx. Specifically, there is an increase in cylinder peak pressure and HRR by around 6–10% range, improvement in BTE by 16–20% and BSFC by 5–7%, along with a decrease in HC and CO emissions by 13–16% and 11–13%, respectively. However, there is an increase in NOx emissions of 6–9%. In essence, the addition of green hydrogen enhances engine performance and reduces emissions in waste tire-derived pyrolyzed oil and biogas blends, indicating a viable path for sustainable transportation fuel.