Variable Compression Ratio Diesel Engine Research Articles

The influence of injection pressure and exhaust gas recirculation on a VCR engine fueled by microalgae biodiesel

AbstractBiodiesel has been chosen as a decent alternative to diesel in the context of establishing environmentally pleasant conditions and saving petroleum‐based resources for future generations. It is well‐established that biodiesel‐powered diesel engines may achieve outcomes equivalent to those of diesel engines. The current investigation was conducted to study the effect of injection pressure (190, 210, and 230 bar) and exhaust gas recirculation (EGR) (5%, 10%, and 15%) on a single‐cylinder variable compression ratio (VCR) diesel engine running using a B20 (20% MB + 80% PD) blend of microalgae biodiesel (MABD). This experiment was conducted in two stages. During the first stage of experimentation, the efficiency and emission characteristics of a diesel engine with a B20 blend of MABD at various fuel injection pressures and fresh air were investigated. During the second phase, fresh air was mixed with 5%, 10%, and 15% exhaust gases, and the experiment was conducted. It was discovered that increasing injection pressure to 230 bar provided considerable improvements. Brake thermal efficiency increased by 2.35%, brake‐specific fuel consumption decreased by 3.57% and pollutants such as carbon monoxide (CO), hydrocarbon, and smoke were reduced by more than 50% compared to conventional diesel. These reductions were similarly significant (over 22%) as compared to the B20 blend at lower injection pressure (210 bar). However, there was a slight trade‐off: nitrogen oxide (NOx) emissions increased partially (3.14%), while exhaust gas temperature (EGT) increased by 1.72% at a higher pressure. The study then investigated the influence of EGR (5%, 10%, and 15%) at various injection pressures. The optimal value seems to be 10% EGR at 230 bar injection pressure. This combination substantially reduced NOx emissions (by over 41% compared to the normal B20 blend) and EGT (by more than 8%), while having no notable effect on other performance or emission variables. Overall, the results show that employing a B20 MABD blend with high injection pressure (230 bar) and moderate EGR (10%) improves engine performance while reducing hazardous emissions.

Soft computing-based modelling and optimization of NOx emission from a variable compression ratio diesel engine

Machine learning method and statistical method used for model prediction and optimization of third generation biodiesel-diesel blend powered variable compression engine High R2 values of 0.9998 and 0.9994 were observed in the training and testing phase of the model, respectively, indicating that The results confirm the robustness of the forecasting system. It was shown that the model accuracy means squared errors remained low at 0.0002 and 0.0014. These results were then confirmed by desirability-based optimization, which succeeded in achieving the values of the set parameters It should be noted that the compression ratio (CR), fuel injection pressure, and engine load were optimized to meet the defined parameters, resulting in a NOx emissions reduction as 222.8 ppm. The research illustrates the efficacy of desirability-based optimization in attaining targeted performance targets across important engine parameters whilst also reducing the impact on the environment.

Exergetic performance optimization and thermoeconomic analysis of a variable compression ratio diesel engine fueled with distilled plastic oil and diesel doped with nanographene

Due to the fast depletion of fossil fuels, enormous concerns about environmental pollution, and advocacy for waste-to-energy drives from the global perspective, compression ignition engines need a sustainable alternative fuel source. Enormous plastic wastes were generated in health sectors, particularly during post-pandemic. In this context, the study intends to introduce a reasonable solution for such waste plastics recycling by converting them into liquid oil by pyrolysis followed by the distillation process. Distilled waste plastic oil (DPO) extracted from medical plastic waste is a potential alternative diesel source. The performance of the engine significantly increases when nanographene is added with DPO/diesel blends, which act as a combustion improviser. The energy efficiency (η1), exergy efficiency (η2), and brake-specific fuel consumption (BSFC), which are regarded as key performance indicators, exhibited promising results when operated with 20% DPO +100 ppm nanographene (20DPO100G) emulsified fuel mixture as compared to normal diesel. When compared to diesel and other fuel combinations, the energy efficiency (η1) and exergy efficiency (η2) for 20DPO100G fuel mixture were found enhanced by 5.78% and 10.9%, respectively, and lowest by 14.7% for BSFC in comparison to diesel. The optimum energy efficiency, exergy efficiency, and minimum BSFC were obtained for the test engine from response surface methodology multi-objective optimization analysis as 31.44%, 22.12%, and 0.32 kg/kW-hr, respectively, for the composite desirability, D of 0.974. The 100 ppm nanographene emulsified distilled waste plastic pyrolysis oil and diesel blend has the lowest relative cost variation of −14.583.

Response Surface Methodology-based Optimization of Variable Compression Ratio Diesel Engine Characteristics with Jatropha Biodiesel

The use of biodiesels as a potential alternative to fossil fuels has significantly increased in the past few decades owing to their clean and renewable nature. The present work has considered jatropha oil as the feedstock for biodiesel due to its properties similar to that of petroleum diesel, large-scale availability, and improved engine characteristics. The brake thermal efficiency and brake-specific fuel consumption have been analyzed for estimating the engine performance while the emissions of hydrocarbon, carbon monoxide, and oxides of nitrogen have been considered for the exhaust emission. Further, the response surface methodology has been adopted for the optimization of the different engine characteristics. The response surface methodology has identified optimal engine characteristics of a variable ratio compression ignition engine for biodiesel with 10% jatropha oil methyl ester at 18:1 compression ratio and 50% engine load. The desired factor of 0.615 and inaccuracy less than 5% of the present analysis can be considered as suitable and acceptable for the optimal parameters.

Response surface optimization approach to enhance the performance of diesel engine using ternary blends of biobutanol and biodiesel doped with ZnO nanoparticles

The major challenge currently is posed by the implementation of stringent emission norms with desired engine performance in the Diesel engine. To reduce India’s reliance on imported fossil fuels, an approach that combines waste reduction strategies, recycling initiative, and responsive utilization of waste to energy solutions can play a key role in addressing the environmental issues and self reliance of energy demand. The present work is based on the optimization of Zinc Oxide (ZnO) nanoparticles (NPs) on the variable compression ratio Diesel engine using ternary blends of Biobutanol, biodiesel, and diesel through Response Surface Methodology (RSM). The process parameters include ternary blends (Biobutanol: 0–10% v/v; biodiesel: 0–20% v/v; and diesel), ZnO: 0–100 ppm, and compression ratio: 16–20. The performance is achieved through the optimized values at a compression ratio of 18.13, nanoparticles concentration of 62.39 ppm, biodiesel content of 11.45% v/v, and Biobutanol content of 5.04 % v/v. The engine's optimized parameters comprise a 65.9 bar cylinder pressure (CP), 67.18 J/℃A of heat release rate (HRR), 31.27% brake thermal efficiency (BTE), 13.224 MJ/kW-h brake specific energy consumption (BSEC), 0.057% volume of carbon monoxide (CO), 31.05 ppm of unburnt hydrocarbons (HC), 555.8 ppm oxides of nitrogen (NOx), and 28.8 % smoke. Validation of the optimized parameters is conducted through actual engine experimental trials, with errors falling within permissible limits of less than 5%. The results suggest that ternary blends will serve as a feasible alternative for Compression Ignition (CI) engines.

Assessment and usability of Jatropha biodiesel blend with phenolic antioxidant to control NOx emissions of an unmodified diesel engine.

The excessive utilization of fossil fuels has worsened global warming and exacerbated the levels of air pollution in the environment, forcing us to consider alternative fuels for compression ignition engines. The current research aims to explore the possibilities of renewable fuels outperforming diesel fuel in terms of combustion, performance, and emission characteristics. Biodiesel is an environmentally friendly and renewable alternative fuel. The major drawback of biodiesel is the significant rise in nitrogen oxide (NOx) emissions. The main novelty and objective of this research is to investigate the performance and emission characteristics of variable compression ratio diesel engine using DPA antioxidant additive. For this investigation, diesel, Jatropha biodiesel (B30) and 100 ppm of phenolic antioxidant diphenylamine (DPA) blended with B30 have been used as fuel named B30+DPA100. From experimental outcomes, the inclusion of diphenylamine to B30 blend resulted in brake-specific fuel consumption (BSFC) and exhaust gas temperature (EGT) being reduced by 8.86% and 4.12%, respectively, compared to B30. Simultaneously, there was a 1.11% increase in brake thermal efficiency (BTHE). The B30+DPA100 fuel blend demonstrates effective control over NOx and other emissions. The emissions of NOx, carbon monoxide (CO), hydrocarbon (HC), and smoke from the B30+DPA100 blend have shown a reduction of 6.8%, 5.34%, 7.86%, and 15.67%, respectively, when compared to diesel. However, there has been an increase in carbon dioxide (CO2) by 7.8%. One notable advantage of the B30+DPA100 blend is the significant decrease in NOx emissions. Additionally, the cylinder pressure for B30+DPA100 has been lowered by 4.93% compared to B30. On the other hand, the net heat release rate (NHR) has experienced a 1.72% increase. The particle size of different elements present in the crankcase oil has been calculated by Zetasizer Nano. The analysis revealed varying particle sizes for different elements in the crankcase oil: aluminum (2.724 μm), chromium (2.78 μm), iron (2.423 μm), and lead (2.587 μm).

Multi-response optimization of energy, exergy, emission, economic characteristics of a variable compression ratio diesel engine fuelled with diesel–bioethanol–Al2O3 nanoparticle blend using Taguchi–Grey approach

Multi-response optimization of energy, exergy, emission, economic characteristics of a variable compression ratio diesel engine fuelled with diesel–bioethanol–Al2O3 nanoparticle blend using Taguchi–Grey approach

Taguchi and ANN-based optimization method for predicting maximum performance and minimum emission of a VCR diesel engine powered by diesel, biodiesel, and producer gas

Purpose The study aims to determine the the optimal value of output parameters of a variable compression ratio (CR) diesel engine are investigated at different loads, CR and fuel modes of operation experimentally. The output parameters of a variable compression ratio (CR) diesel engine are investigated at different loads, CR and fuel modes of operation experimentally. The performance parameters like brake thermal efficiency (BTE) and brake specific energy consumption (BSEC), whereas CO emission, HC emission, CO2 emission, NOx emission, exhaust gas temperature (EGT) and opacity are the emission parameters measured during the test. Tests are conducted for 2, 6 and 10 kg of load, 16.5 and 17.5 of CR. Design/methodology/approach In this investigation, the first engine was fueled with 100% diesel and 100% Calophyllum inophyllum oil in single-fuel mode. Then Calophyllum inophyllum oil with producer gas was fed to the engine. Calophyllum inophyllum oil offers lower BTE, CO and HC emissions, opacity and higher EGT, BSEC, CO2 emission and NOx emissions compared to diesel fuel in both fuel modes of operation observed. The performance optimization using the Taguchi approach is carried out to determine the optimal input parameters for maximum performance and minimum emissions for the test engine. The optimized value of the input parameters is then fed into the prediction techniques, such as the artificial neural network (ANN). Findings From multiple response optimization, the minimum emissions of 0.58% of CO, 42% of HC, 191 ppm NOx and maximum BTE of 21.56% for 16.5 CR, 10 kg load and dual fuel mode of operation are determined. Based on generated errors, the ANN is also ranked for precision. The proposed ANN model provides better prediction with minimum experimental data sets. The values of the R2 correlation coefficient are 1, 0.95552, 0.94367 and 0.97789 for training, validation, testing and all, respectively. The said biodiesel may be used as a substitute for conventional diesel fuel. Originality/value The blend of Calophyllum inophyllum oil-producer gas is used to run the diesel engine. Performance and emission analysis has been carried out, compared, optimized and validated.

Effect of green synthesized zinc oxide nanoadditives and rice bran oil biodiesel blend on performance and combustion characteristics of a variable compression ratio diesel engine: an experimental study

AbstractThe aim of this research was to investigate experimentally the performance and combustion characteristics of a four‐stroke, single‐cylinder, water‐cooled variable compression ratio diesel engine using rice bran oil biodiesel blends with zinc oxide nanoparticles. Rice bran oil biodiesel was prepared using a transesterification reaction with a 6:1 methanol‐oil molar ratio and 1% w/w potassium hydroxide as catalyst. Zinc oxide nanoparticles were synthesized using a green method incorporating Psidium guajava leaf extract as a capping agent to reduce precursor use and to reduce the toxicity of the nanomaterial. The synthesized zinc oxide nanoparticles were characterized by using X‐ray diffraction and Fourier‐transform infrared spectroscopy to confirm the formation of highly crystalline pure zinc oxide nanoparticles with a hexagonal wurtzite crystal structure with an average diameter of 20.963 nm. Rice bran‐oil biodiesel‐diesel blend was prepared by volumetrically mixing 20% biodiesel and 80% mineral diesel and was considered as a base fuel for comparison. Zinc oxide nanoparticles were diffused in the base fuel at dosage levels of 25, 50, and 75 ppm, with the aid of ultrasonication. Measurement of the major physicochemical properties of test fuels showed an increase in the cetane number and calorific value and a reduction in viscosity with an increase in the zinc oxide concentration. The overall properties of all the test fuels were found to be similar in comparison with commercial diesel. An experimental engine test was carried out under different loading conditions with a constant speed of 1500 RPM and two different compression ratios – that is, 17.5:1 and 15:1. Among all the test fuels at both compression ratios, engine performance and combustion properties improved with an increase in the zinc oxide concentration. Test fuel with 75 ppm of zinc oxide additive at 17.5 compression ratio resulted in an overall improvement at full load: brake thermal efficiency increased by 2.45%, brake specific fuel consumption reduced by 5.45%, cylinder peak pressure increased by 3.27% and net heat release increased by 10.32% in comparison with base fuel.

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.

Parametric optimization of a VCR diesel engine run on diesel-bioethanol-Al2O3 nanoparticles blend using Taguchi-Grey and RSM method: a comparative study

PurposeThe study aims to verify and establish the result of the most suitable optimization approach for higher performance and lower emission of a variable compression ratio (VCR) diesel engine. In this study, three types of test fuels are taken and tested in a variable compression ratio diesel engine (compression ignition). The fuels used are conventional diesel fuel, e-diesel (85% diesel-15% bioethanol) and nano-fuel (85% diesel-15% bioethanol-25 ppm Al2O3). The effect of bioethanol and nano-particles on performance, emission and cost-effectiveness is investigated at different load and compression ratios (CRs). The optimum performance and lower emission of the engine are evaluated and compared with other optimization methods.Design/methodology/approachThe test engine is run by diesel, e-diesel (85% diesel-15% bioethanol) and nano-fuel (85% diesel-15% bioethanol-25 ppm Al2O3) in three different loadings (4 kg, 8 kg and 12 kg) and CR of 14, 16 and 18, respectively. The optimum value of energy efficiency, exergy efficiency, NOX emission and relative cost variation are determined against the input parameters using Taguchi-Grey method and confirmed by response surface methodology (RSM) technique.FindingsUsing Taguchi-Grey method, the maximum energy and exergy efficiency, minimum % relative cost variation and NOX emission are 24.64%, 59.52%, 0 and 184 ppm, respectively, at 4 kg load, 18 CR and fuel type of nano-fuel. Using RSM technique, maximum energy and exergy efficiency are 24.8% and 62.9%, and minimum NOX emission and % cost variation are 208.4 ppm and –6.5, respectively, at 5.2 kg load, 18 CR and nano-fuel. The RSM is suggested as the most appropriate technique for obtaining maximum energy and exergy efficiency, and minimum % relative cost; however, for lowest possible NOX emission, the Taguchi-Grey method is the most appropriate.Originality/valueWaste rice straw is used to produce bioethanol. 4-E analysis, i.e. energy, exergy, emission and economic analysis, has been carried out, optimized and compared.

Experimentation studies of microalgae biodiesel blends influence on variable compression ratio diesel engine performance and exhaust emission characteristics

Experimentation studies of microalgae biodiesel blends influence on variable compression ratio diesel engine performance and exhaust emission characteristics

Experimental analysis of the effect of zinc oxide nano additive diesel-ethanol blend on the performance and emission characteristics of a variable compression ratio diesel engine at various compression ratios

The two significant challenges facing the world are growing pollution issues and fossil fuel depletion. Emissions emanating and consumption of fossil fuels in diesel engines are reduced by modifying engine operating parameters and by developing more efficient alternative fuels. In view of this, the current work evaluates the effect of ZnO nanoparticles mixed with diesel-ethanol blend on the working characteristics of diesel engine at different CR’s and loads. The test fuels selected for the experimental work are pure diesel, DE10, DE10ZnO50 and DE10ZnO100, and the compression ratios are 16.5, 17.5 and 18.5. Using ultrasonic agitation, ZnO nanoparticles were incorporated in fuel blends in the presence of 2% surfactant span80. All fuel blends were tested for their physicochemical properties, and it was noted that the fuel properties improved when ZnO nanoparticles were added to the test blends. The results showed that at CR 18.5, the DE10ZnO100 fuel blend shown maximum improvement in engine working characteristics as compared to other blends. In comparison to diesel at CR 18.5 for DE10ZnO100 blend, BTE enhanced by 5.73% and BSFC was reduced by 8.31%. CO, NOx and UHC emissions are reduced by 21.96%, 6.41% and 12.07%, whereas CO2 emissions have increased by 7.44%, respectively. HIGHLIGHTS Different concentration of ZnO nanoparticles incorporated diesel-ethanol blend is prepared. The effect of ZnO nanoparticles diesel-ethanol blend at various compression ratios of diesel engine was investigated Optimal results are noted for the DE10ZnO100 blend at compression ratio 18.5. Improvements in BTE and BSFC is 5.73% and 8.31% as compared to diesel at CR 18.5 for DE10ZnO100 blend. CO, UHC and NOx reduced by 21.96%, 12.07% and 6.41%.

The effects of nanoparticles as a biodiesel ingredient on the performance of a VCR diesel engine

The combustion, efficiency, and emission properties of a single-cylinder variable compression ratio diesel engine were examined in this research (B100A30C30). To create a homogeneous solution, the ultrasonicator was used in conjunction with a 30 ppm concentration of silicon carbide and carbon nanotubes, two common nanoparticles found in fuel combinations. The increased mixing and chemical reactivity offered by nanoparticles' greater surface area to volume ratio during combustion improved the combustion, performance, and emission characteristics of diesel engines. The engine with nanoparticles (B20A30C30) had a thermal efficiency of braking that is 20% higher than the engine with regular particles (B100). Following that, nitrogen oxide emissions reduced by 38%, carbon monoxide emissions by 68%, hydrocarbon emissions by 52%, and smoke emissions by 48%.

Impact of additive ethylene glycol diacetate on diesel engine working with jatropha-karanja dual biodiesel

The present study investigates ethylene glycol diacetate as a prospective oxygenated additive for jatropha-karanja dual blended biodiesel for enhanced engine characteristics of a diesel engine. The experiments have been conducted at constant speed of 1500 rpm on a variable compression ratio diesel engine working with biodiesel having 10–30% of Jatropha and karanja oil methyl ester and 1–3% of additive. The brake thermal efficiency increased by 3.6–4.2% while the brake specific fuel consumption reduced by 0.08–0.24 kg/kWh for fuel blends by adding 3% additive. The hydrocarbon and carbon monoxide emissions reduced by a maximum of 7 ppm and 0.02% respectively with slight increase in nitrogen oxide over entire range of fuel blends. The peak cylinder pressure attained 53.2 bar with maximum heat release rate 63.7 J/oCA by addition of 3% additive. Thus, the ethylene glycol diacetate can be adopted as a suitable additive for jatropha-karanja blend dual biodiesel to achieve improved engine characteristics of diesel engines.

An evaluation of biosynthesized nanoparticles in biodiesel as an enhancement of a VCR diesel engine

• Homogeneous solution is made by mixing nanoparticles such as titanium oxide (TiO 2 ) and zinc oxide (ZnO). • Enhanced mixing and improved reactivity of such nanoparticles. • Higher surface area to volume ratio is observed. • Improved engine’s performance and higher efficiency is resulted. Using three different fuel sequences –biodiesel–diesel (B20), biodiesel–chemically and biologically synthesized nanoparticles(B20A30C30), and biodiesel–chemically and biologically synthesized nanoparticles (B20A30C30). This study investigates a single-cylinder variable compression ratio diesel engine's combustion, efficiency, and emission characteristics (B100A30C30). The ultrasonicator is employed in concert with 30 parts per million (ppm) concentration of titanium oxide (TiO 2 ) and zinc oxide (ZnO), two typical nanoparticles found in fuel mixtures, to form a homogenous solution. As a result of the greater mixing and chemical reactivity offered by nanoparticles' higher surface area to volume ratio during combustion, diesel engines' combustion, performance, and emission characteristics have all been improved. The engine with nanoparticles (B20A30C30) has a 16% higher brake thermal efficiency than the engine with conventional particles (B100). Following that, nitrogen oxide emissions were reduced by 32%, carbon monoxide emissions were reduced by 62%, hydrocarbon emissions were reduced by 48%, and smoke emissions were reduced by 40%.

Experimental investigation on performance of cotton seed biofuel blended with diesel on variable compression ratio diesel engine

The reasons for the fuel energy crisis are the rapid increase in the global population and changing human lives. Fossil fuel is a leading factor involved in atmospheric pollutants. However, biofuel plays an important role in boosting engine efficiency and lowering emissions. Present research work contributes to enhancing the performance of diesel engines. In this work, cottonseed oil is used and converted into biofuel through the transesterification process. Raw cotton seed oil comes under the category of vegetable oils, both edible and non-edible. The calorific value and viscosity of biodiesel fuel are two distinct characteristics. The biofuel blends with diesel in variable proportions by volume of 20%–40 % are used. The performance was monitored, analysed and verified against pure diesel and biofuel using CB20, CB30, and CB40. The performance obtained using biofuel with varying loads at different fuel blends on the VCR engine improves BTE and BSFC. When the CR is changed from 18 to 22, the BSFC decreases by 0.310 to 0.290 kg/kwh, while the BTE increases by 0.72 percent.

Optimisation of performance parameters of a variable compression ratio diesel engine with hibiscus cocos nucifera biodiesel using Taguchi method

ABSTRACT The present experimental work describes the performance of a variable compression ratio diesel engine with hibiscus cocos nucifera biodiesel. The Taguchi method is used to optimise engine performance parameters. Compression ratios from 15:1 to 18:1, loads of 6, 9, and 12 kg, and blends B05, B10, B15, B20, B25, and diesel are the input parameters. Brake power, brake thermal efficiency, and mechanical efficiency were chosen as performance parameters. The optimum values are 23.7250% brake thermal efficiency, 3.41667 kW of brake power, and 70.0600% mechanical efficiency with a load of 12 kg, a compression ratio of 16:1, and blend B20. The CO emissions of blend B25 were reduced by 36.36% at a compression ratio of 18:1 when compared to diesel at full load. NOx emissions were increased with an increase in compression ratio and blend ratio. The mass fraction burned is higher for B20 and B25 with an 18:1 compression ratio.

Extraction and characterization of waste plastic pyrolysis oil for diesel engines

In this research work, the fuel extraction process from waste plastics through the thermal cracking method is explored. The pyrolysis process was carried out at a wide range of temperatures in the absence of oxygen. About 78% (w/w) of the liquid yield was extracted between the effective pyrolysis temperatures of 370 °C - 380 °C, resulting in a calorific value of 38.53 MJ/kg. The obtained plastic pyrolysis fuel was then characterized by thermogravimetric study, FTIR and GC-MS analysis. Thermogravimetric analysis indicates that the structures of natural plastic break at 200 °C and fully decompose at 300 °C. The presence of alkanes and aromatic components in the plastic pyrolysis fuel was confirmed through FTIR analysis. Further GC-MS studies on fuel samples have proven that hydrocarbon compounds exist within the C7–C40 range. Plastic pyrolysis fuel obtained from waste plastics is found to have similar fuel properties to diesel. The plastic pyrolysis fuel was tested in a single cylinder four stroke variable compression ratio diesel engine with different blends of plastic pyrolysis fuel and diesel ranging from 0% to 100% at varied engine loads ranging from 25% to 100%. The engine performance and exhaust emissions were studied and compared with conventional diesel fuel operation. The research revealed that the engine can operate on plastic pyrolysis fuel at full load, has a 6% improvement in brake thermal efficiency as well as 4% reduction in UBHC and 2% reduction of CO emissions, albeit NOx emissions were significantly greater. The results confirmed that plastic pyrolysis fuel could be a viable replacement option for diesel.

A computational technique for prediction and optimization of VCR engine performance and emission parameters fuelled with Trichosanthes cucumerina biodiesel using RSM with desirability function approach

Global concerns about pollution, rapidly diminishing fossil fuels, energy accessibility, and sustainability have prompted researchers to focus on alternative energy sources. Unlike fossil fuels, second-generation biofuels are considered a viable and promising substitute for the existing resources. This study utilizes waste-to-energy to produce biodiesel from trichosanthes cucumerina waste seeds. Biofuel characteristics were determined using gas chromatography-mass spectrometry and Fourier transform infrared spectroscopy analysis. The engine test blends are prepared with different trichosanthes cucumerina biodiesel (TCB) proportions (30%, 50%, 70% and 100%), and their thermophysical properties were assessed according to the ASTM standards. The performance and emission characteristics were analyzed using TCB blends in the variable compression ratio diesel engine. With the support of experimental results, the response surface methodology (RSM) was used for developing the multiple regression model. The desirability function approach minimizes the brake specific fuel consumption, exhaust gas temperature and engine exhaust emissions and maximizes brake thermal efficiency. The optimum input factors were found from the RSM modeling as 45% TCB blend, the compression ratio 17.5:1 and 1.5 kW engine load. Experimental results validate the engine's optimized response, and the observed error percentage is less than 6.5%. In comparison to the baseline diesel fuel, the 45% TCB blend delivered lower emissions of HC by 4.26%, CO by 3.74% and smoke opacity by 4.67% and produced identical engine performance. Based on the above results, the 45% TCB blend can be considered a feasible alternative source for diesel fuel.