Physico-chemical properties of ethanol–diesel blend fuel and its effect on performance and emissions of diesel engines

The effects of different ethanol–diesel blended fuels on the performance and emissions of diesel engines have been evaluated experimentally and compared in this paper. The purpose of this project is to find the optimum percentage of ethanol that gives simultaneously better performance and lower emissions. The experiments were conducted on a water-cooled single-cylinder Direct Injection (DI) diesel engine using 0% (neat diesel fuel), 5% (E5–D), 10% (E10–D), 15% (E15–D), and 20% (E20–D) ethanol–diesel blended fuels. With the same rated power for different blended fuels and pure diesel fuel, the engine performance parameters (including power, torque, fuel consumption, and exhaust temperature) and exhaust emissions [Bosch smoke number, CO, NO_x, total hydrocarbon (THC)] were measured. The results indicate that: the brake specific fuel consumption and brake thermal efficiency increased with an increase of ethanol contents in the blended fuel at overall operating conditions; smoke emissions decreased with ethanol–diesel blended fuel, especially with E10–D and E15–D. CO and NO_x emissions reduced for ethanol–diesel blends, but THC increased significantly when compared to neat diesel fuel.     

Application of artificial neural networks for the prediction of performance and exhaust emissions in SI engine using ethanol- gasoline blends

This study deals with artificial neural network (ANN) modeling of a spark ignition engine to predict the engine brake power, output torque and exhaust emissions (CO, CO₂, NO_x and HC) of the engine. To acquire data for training and testing of the proposed ANN, a four-cylinder, four-stroke test engine was fuelled with ethanol-gasoline blended fuels with various percentages of ethanol (0, 5, 10,15 and 20%), and operated at different engine speeds and loads. An ANN model based on standard back-propagation algorithm for the engine was developed using some of the experimental data for training. The performance of the ANN was validated by comparing the prediction dataset with the experimental results. Results showed that the ANN provided the best accuracy in modeling the emission indices with correlation coefficient equal to 0.98, 0.96, 0.90 and 0.71 for CO, CO₂, HC and NO_x, and 0.99 and 0.96 for torque and brake power respectively. Generally, the artificial neural network offers the advantage of being fast, accurate and reliable in the prediction or approximation affairs, especially when numerical and mathematical methods fail.     

Performance and exhaust emissions of a gasoline engine using artificial neural network

This study deals with artificial neural network (ANN) modelling of a gasoline engine to predict the brake specific fuel consumption, brake thermal efficiency, exhaust gas temperature and exhaust emissions of the engine. To acquire data for training and testing the proposed ANN, a four-cylinder, four-stroke test engine was fuelled with gasoline having various octane numbers (91, 93, 95 and 95.3), and operated at different engine speeds and torques. Using some of the experimental data for training, an ANN model based on standard back-propagation algorithm for the engine was developed. Then, the performance of the ANN predictions were measured by comparing the predictions with the experimental results which were not used in the training process. It was observed that the ANN model can predict the engine performance, exhaust emissions and exhaust gas temperature quite well with correlation coefficients in the range of 0.983–0.996, mean relative errors in the range of 1.41–6.66% and very low root mean square errors. This study shows that, as an alternative to classical modelling techniques, the ANN approach can be used to accurately predict the performance and emissions of internal combustion engines.     

Artificial Neural Network based prediction of performance and emission characteristics of a variable compression ratio CI engine using WCO as a biodiesel at different injection timings

Due to the increasing demand for fossil fuels and environmental threat due to pollution a number renewable sources of energy have been studied worldwide. In the present investigation influence of injection timing on the performance and emissions of a single cylinder, four stroke stationary, variable compression ratio, diesel engine was studied using waste cooking oil (WCO) as the biodiesel blended with diesel. The tests were performed at three different injection timings (24°, 27°, 30° CA BTDC) by changing the thickness of the advance shim. The experimental results showed that brake thermal efficiency for the advanced as well as the retarded injection timing was lesser than that for the normal injection timing (27° BTDC) for all sets of compression ratios. Smoke, un-burnt hydrocarbon (UBHC) emissions were reduced for advanced injection timings where as NO_x emissions increased. Artificial Neural Networks (ANN) was used to predict the engine performance and emission characteristics of the engine. Separate models were developed for performance parameters as well as emission characteristics. To train the network, compression ratio, injection timing, blend percentage, percentage load, were used as the input parameters where as engine performance parameters like brake thermal efficiency (BTE), brake specific energy consumption (BSEC), exhaust gas temperature (T_exh) were used as the output parameters for the performance model and engine exhaust emissions such as NO_x, smoke and (UBHC) values were used as the output parameters for the emission model. ANN results showed that there is a good correlation between the ANN predicted values and the experimental values for various engine performance parameters and exhaust emission characteristics and the relative mean error values (MRE) were within 8%, which is acceptable.     

Comparative engine performance and emission analysis of CNG and gasoline in a retrofitted car engine

A comparative analysis is being performed of the engine performance and exhaust emission on a gasoline and compressed natural gas (CNG) fueled retrofitted spark ignition car engine. A new 1.6 L, 4-cylinder petrol engine was converted to the computer incorporated bi-fuel system which operated with either gasoline or CNG using an electronically controlled solenoid actuated valve mechanism. The engine brake power, brake specific fuel consumption, brake thermal efficiency, exhaust gas temperature and exhaust emissions (unburnt hydrocarbon, carbon mono-oxide, oxygen and carbon dioxides) were measured over a range of speed variations at 50% and 80% throttle positions through a computer based data acquisition and control system. Comparative analysis of the experimental results showed 19.25% and 10.86% reduction in brake power and 15.96% and 14.68% reduction in brake specific fuel consumption (BSFC) at 50% and 80% throttle positions respectively while the engine was fueled with CNG compared to that with the gasoline. Whereas, the retrofitted engine produced 1.6% higher brake thermal efficiency and 24.21% higher exhaust gas temperature at 80% throttle had produced an average of 40.84% higher NO_x emission over the speed range of 1500–5500 rpm at 80% throttle. Other emission contents (unburnt HC, CO, O₂ and CO₂) were significantly lower than those of the gasoline emissions.     

Experimental study of a single-cylinder engine fueled with natural gas–hydrogen mixtures

The objective of this study is to evaluate the power, efficiency and emissions of an electronic-controlled single-cylinder engine fueled with pure natural gas and natural gas–hydrogen blends, respectively. Replacing the nature gas with hydrogen/methane blend fuels was found to have a significant influence on engine performance. The effects of excess air ratio and spark timing were discussed. The results show that under certain engine conditions the maximum cylinder gas pressure, maximum heat release rate increased with the increase of hydrogen fraction. The increase of hydrogen fraction in the blends contributed to the increase of NO_x and the decrease of HC and CO. The brake specific fuel consumption decreased with the increase of hydrogen fraction. Using HCNG at relatively leaner fuel–air mixtures and retarded spark timing totally improved the engine emissions without incurring the performance penalty.     

Diesel engine performance and exhaust emission analysis using waste cooking biodiesel fuel with an artificial neural network

This study deals with artificial neural network (ANN) modeling of a diesel engine using waste cooking biodiesel fuel to predict the brake power, torque, specific fuel consumption and exhaust emissions of the engine. To acquire data for training and testing the proposed ANN, a two cylinders, four-stroke diesel engine was fuelled with waste vegetable cooking biodiesel and diesel fuel blends and operated at different engine speeds. The properties of biodiesel produced from waste vegetable oil was measured based on ASTM standards. The experimental results revealed that blends of waste vegetable oil methyl ester with diesel fuel provide better engine performance and improved emission characteristics. Using some of the experimental data for training, an ANN model was developed based on standard Back-Propagation algorithm for the engine. Multi layer perception network (MLP) was used for non-linear mapping between the input and output parameters. Different activation functions and several rules were used to assess the percentage error between the desired and the predicted values. It was observed that the ANN model can predict the engine performance and exhaust emissions quite well with correlation coefficient (R) 0.9487, 0.999, 0.929 and 0.999 for the engine torque, SFC, CO and HC emissions, respectively. The prediction MSE (Mean Square Error) error was between the desired outputs as measured values and the simulated values were obtained as 0.0004 by the model.     

Prediction of performance,combustion and emission characteristics of diesel-thermal cracked cashew nut shell liquid blends using artificial neural network

This paper explores the use of artificial neural networks (ANN) to predict performance, combustion and emissions of a single cylinder, four stroke stationary, diesel engine operated by thermal cracked cashew nut shell liquid (TC-CNSL) as the biodiesel blended with diesel. The tests were performed at three different injection timings (21°, 23°, 25°CA bTDC) by changing the thickness of the advance shim. The ANN was used to predict eight different engine-output responses, namely brake thermal efficiency (BTE), brake specific fuel consumption (BSFC), exhaust gas temperature (EGT), carbon monoxide (CO), oxide of nitrogen (NO _x ), hydrocarbon (HC), maximum pressure (P _max) and heat release rate (HRR). Four pertinent engine operating parameters, i.e., injection timing (IT), injection pressure (IP), blend percentage and pecentage load were used as the input parameters for this modeling work. The ANN results show that there is a good correlation between the ANN predicted values and the experimental values for various engine performances, combustion parameters and exhaust emission characteristics. The mean square error value (MSE) is 0.005621 and the regression value of R ² is 0.99316 for training, 0.98812 for validation, 0.9841 for testing while the overall value is 0.99173. Thus the developed ANN model is fairly powerful for predicting the performance, combustion and exhaust emissions of internal combustion engines.     

Studies on the use of orange peel oil and ethanol in an unmodified agricultural diesel engine

The aim of the present study is to investigate the suitability of Orange peel oil and ethanol blends as an alternative fuel for CI engine. Various blends of ethanol with Orange peel oil were prepared on volumetric basis and named as E5OPO95 (5% ethanol and 95% Orange peel oil), E10OPO90 (10% ethanol and 90% Orange peel oil), E15OPO85 (15% ethanol and 85% Orange peel oil) and E20OPO80 (20% ethanol and 80% Orange peel oil). All blends were found to be homogeneous and various physicochemical properties are evaluated in accordance with relevant standards. In the subsequent phase of this investigation, exhaustive engine trials were carried out on a single cylinder medium capacity diesel engine using the different test fuel samples. The result shows a marginal reduction in the brake thermal efficiency for all blends as compared to diesel. At the same time, NOx decreased slightly for all blends. The HC emissions were found to increase while CO₂ emissions decrease for different ethanol Orange peel oil blends as ethanol content increased. Moreover, the smoke opacity and exhaust gas temperature were found lower than neat diesel for all the blends.     

A novel approach to utilize esterified rice bran oil as an additive with gasoline and ethanol blends in MPFI SI engine.

ABSTRACT

In this work, we have attempted to add biodiesel as an additive with gasoline and ethanol blend to analyze the effect on performance and emission characteristics. The esterified rice bran oil is chosen as an additive. This focus of this work is to study the behavior of an SI engine for various blend proportions and to identify the optimum blend proportion that yields better results. MPFI engine was used to conduct the load test with gasoline as the base reference fuel. Blends of gasoline-ethanol and rice bran oil were prepared, and the tests were done for all the blends. The observed results were presented and discussed. Adding ethanol to the gasoline results in improved combustion that causes an increase in brake thermal efficiency and brake power. With esterified rice bran oil as an additive gives a reduction in specific fuel consumption, hydrocarbon emission, and carbon monoxide emissions. The optimum blends that have excellent benefits are identified.     

CNG-diesel engine performance and exhaust emission analysis with the aid of artificial neural network

This study investigates the use of artificial neural network (ANN) modelling to predict brake power, torque, break specific fuel consumption (BSFC), and exhaust emissions of a diesel engine modified to operate with a combination of both compressed natural gas CNG and diesel fuels. A single cylinder, four-stroke diesel engine was modified for the present work and was operated at different engine loads and speeds. The experimental results reveal that the mixtures of CNG and diesel fuel provided better engine performance and improved the emission characteristics compared with the pure diesel fuel. For the ANN modelling, the standard back-propagation algorithm was found to be the optimum choice for training the model. A multi-layer perception network was used for non-linear mapping between the input and output parameters. It was found that the ANN model is able to predict the engine performance and exhaust emissions with a correlation coefficient of 0.9884, 0.9838, 0.95707, and 0.9934 for the engine torque, BSFC, NO_x and exhaust temperature, respectively.     

Performance,emission and combustion characteristic of a multicylinder DI diesel engine running on diesel–ethanol–biodiesel blends of high ethanol content

Feasibility of using high percentage of ethanol in diesel–ethanol blends, with biodiesel as a co-solvent and properties enhancer has been investigated. The blends tested are D70/E20/B10 (blend A), D50/E30/B20 (blend B) D50/E40/B10 (blend C), and Diesel (D100). The blends are prepared to get maximum percentage of oxygen content but keeping important properties such as density, viscosity and Cetane index within acceptable limits. Experiments are conducted on a multicylinder, DI diesel engine, whose original injection timing was 13° CA BTDC. The engine did not run on blends B and C at this injection timing and it was required to advance timing to 18° and 21° CA BTDC to enable the use of blends B and C respectively. However advancing injection timing almost doubled the NO emissions and increased peak firing pressure. The P–θ and net heat release diagrams shows that the combustion process of these blends delayed at low loads but approaches to the diesel fuel at high loads. The comparison of blend results with baseline diesel showed that brake specific fuel consumption increased considerably, thermal efficiency improved slightly, smoke opacity reduced remarkably at high loads. NO variation depends on operating conditions while CO emissions drastically increased at low loads. Blend B which replaced 50% diesel and having oxygen content up to 12.21% by weight has given satisfactory performance for steady state running mode up to 1600 RPM however, it does not showed any benefit on peak smoke emission during free acceleration test.     

A nonlinear regression based multi-objective optimization of parameters based on experimental data from an IC engine fueled with biodiesel blends

This study reports the results of an experimental investigation of the performance of an IC engine fueled with a Karanja biodiesel blends, followed by multi-objective optimization with respect to engine emissions and fuel economy, in order to determine the optimum biodiesel blend and injection timings complying with Bharat Stage II emission norms. Nonlinear regression has been used to regress the experimentally obtained data to predict the brake thermal efficiency, NO_x, HC and smoke emissions based on injection timing, blend ratio and power output. To acquire the data, experimental studies have been conducted on a single cylinder, constant speed (1500 rpm), direct injection diesel engine under variable load conditions and injection timings for neat diesel and various Karanja biodiesel blends (5%, 10%, 15%, 20%, 50% and 100%). Retarding the injection timing for neat Karanja biodiesel resulted in an improved efficiency and lower HC emissions. A tradeoff relationship between the NO_x and smoke emissions is observed, which makes it difficult to determine the optimum blend ratio. The functional relationship developed between the correlating variables using nonlinear regression is able to predict the performance and emission characteristics with a correlation coefficient (R) in the range of 0.95-0.99 and very low root mean square errors. The outputs obtained using these functions are used to evaluate the multi-objective function of optimization process in the 0-20% blend range. The overall optimum is found to be 13% biodiesel-diesel blend with an injection timing of 24°bTDC, when equal weightage is given to emissions and efficiency.     

Performance and combustion characteristics of alcohol–gasoline blends at wide-open throttle

This study discusses the performance and exhaust emissions of a vehicle fueled with low content alcohol (ethanol and methanol) blends and pure gasoline. The vehicle tests were performed at wide-open throttle and at vehicle speeds of 40 km h⁻¹, 60 km h⁻¹, 80 km h⁻¹ and 100 km h⁻¹ by using an eddy current chassis dynamometer. The test results obtained with the use of alcohol-gasoline blends (5 and 10 percent alcohol by volume) were compared to pure gasoline test results. The test results indicated that when the vehicle was fueled with alcohol-gasoline blends, the peak wheel power and fuel consumption slightly increased. And also, in general, alcohol-gasoline blends provided higher combustion efficiency compared to pure gasoline use. In exhaust emission results, a stable trend was not seen, especially for CO emission. But, on average, alcohol-gasoline blends exhibited decreasing HC emissions. In 100 km h⁻¹ vehicle speed test, the alcohol-gasoline blends provided lower vehicle performance and lower NO_x emission values compared to pure gasoline. At all vehicle speeds, minimum CO₂ emission was obtained when 5% methanol was added in gasoline. The low content alcohol blends did not reveal any starting problem, or irregular operation on the engine.     

Hydrogen–ethanol blending as an alternative fuel of spark ignition engines

The performance and pollutant emission of a four-stroke spark ignition engine using hydrogen–ethanol blends as fuel have been studied. The tests were performed using 2, 4, 6, 8, 10 and 12 mass% hydrogen–ethanol blends. Gasoline fuel was used as a basis for comparison. The effect of using different blends of hydrogen–ethanol on engine power, specific fuel consumption, CO and NO_x emission was studied. Operating test results for a range of compression ratio (CR) and equivalent ratio are presented. The results show that the supplemental hydrogen in the ethanol–air mixture improves the combustion process and hence improves the combustion efficiency, expands the range of combustibility of the ethanol fuel, increases the power, reduces the s.f.c., and reduces toxic emissions. The important improvement of hydrogen addition is to reduce the s.f.c. of ethanol engines. Results were compared to those with gasoline fuel at 7 CR and stoichiometric equivalence ratio.     

The effects of ethanol–unleaded gasoline blends on engine performance and exhaust emissions in a spark-ignition engine

Alcohols have been used as a fuel for engines since 19th century. Among the various alcohols, ethanol is known as the most suited renewable, bio-based and ecofriendly fuel for spark-ignition (SI) engines. The most attractive properties of ethanol as an SI engine fuel are that it can be produced from renewable energy sources such as sugar, cane, cassava, many types of waste biomass materials, corn and barley. In addition, ethanol has higher evaporation heat, octane number and flammability temperature therefore it has positive influence on engine performance and reduces exhaust emissions. In this study, the effects of unleaded gasoline (E0) and unleaded gasoline–ethanol blends (E50 and E85) on engine performance and pollutant emissions were investigated experimentally in a single cylinder four-stroke spark-ignition engine at two compression ratios (10:1 and 11:1). The engine speed was changed from 1500 to 5000 rpm at wide open throttle (WOT). The results of the engine test showed that ethanol addition to unleaded gasoline increase the engine torque, power and fuel consumption and reduce carbon monoxide (CO), nitrogen oxides (NO_x) and hydrocarbon (HC) emissions. It was also found that ethanol–gasoline blends allow increasing compression ratio (CR) without knock occurrence.     

Effect of hydrogen addition on combustion and emissions performance of a spark-ignited ethanol engine at idle and stoichiometric conditions

Regarding the limited fossil fuel reserves, the renewable ethanol has been considered as one of the substitutional fuels for spark ignition (SI) engines. But due to its high latent heat, ethanol is usually hard to be well evaporated to form the homogeneous fuel–air mixture at low temperatures, e.g., at idle condition. Compared with ethanol, hydrogen possesses many unique combustion and physicochemical properties that help improve combustion process. In this paper, the performance of a hydrogen-enriched SI ethanol engine under idle and stoichiometric conditions was investigated. The experiment was performed on a modified 1.6 L SI engine equipped with a hydrogen port-injection system. The ethanol was injected into the intake ports using the original engine gasoline injection system. A self-developed hybrid electronic control unit (HECU) was adopted to govern the opening and closing of hydrogen and ethanol injectors. The spark timing and idle bypass valve opening were governed by the engine original electronic control unit (OECU), so that the engine could operate under its original target idle speed for each testing point. The engine was first fueled with the pure ethanol and then hydrogen volume fraction in the total intake gas was gradually increased through increasing hydrogen injection duration. For a specified hydrogen addition level, ethanol flow rate was reduced to keep the hydrogen–ethanol–air mixture at stoichiometric condition. The test results showed that hydrogen addition was effective on reducing cyclic variations and improving indicated thermal efficiency of an ethanol engine at idle. The fuel energy flow rate was reduced by 20% when hydrogen volume fraction in the intake rose from 0% to 6.38%. Both flame development and propagation periods were shortened with the increase of hydrogen blending ratio. The heat transfer to the coolant was decreased and the degree of constant volume combustion was enhanced after hydrogen addition. HC and CO emissions were first reduced and then increased with the increase of hydrogen blending fraction. The acetaldehyde emission from the hydrogen-enriched ethanol engine is lower than that from the pure ethanol engine. However, the addition of hydrogen tended to increase NO_x emissions from the ethanol engine at idle and stoichiometric conditions.     

Effect of ethanol blending with biodiesel on engine performance and exhaust emissions in a CI engine

The use of biodiesel as an alternative diesel engine fuel is increasing rapidly. However, due to technical deficiencies, they are rarely used purely or with high percentages in unmodified diesel engines. Therefore, in this study, we used ethanol as an additive to research the possible use of higher percentages of biodiesel in an unmodified diesel engine. Commercial diesel fuel, 20% biodiesel and 80% diesel fuel, called here as B20, and 80% biodiesel and 20% ethanol, called here as BE20, were used in a single cylinder, four strokes direct injection diesel engine. The effect of test fuels on engine torque, power, brake specific fuel consumption, brake thermal efficiency, exhaust gas temperature, and CO, CO₂, NO_x and SO₂ emissions was investigated. The experimental results showed that the performance of CI engine was improved with the use of the BE20 especially in comparison to B20. Besides, the exhaust emissions for BE20 were fairly reduced.     

An experimental study on performance and emission characteristics of a methane–hydrogen fuelled gasoline engine

In this paper, the performance and emission characteristics of a conventional twin-cylinder, four stroke, spark-ignited (SI) engine that is running with methane–hydrogen blends have been investigated experimentally. The engine was modified to realize hydrogen port injection by installing hydrogen feeding line in the intake manifolds. The experimental results have been demonstrated that the brake specific fuel consumption (BSFC) increased with the increase of hydrogen fraction in fuel blends at low speeds. On the other hand, as hydrogen percentage in the mixture increased, BSFC values decreased at high speeds. Furthermore, brake thermal efficiencies were found to decrease with the increase in percentage of hydrogen added. In addition, it has been found that CO₂, NO_x and HC emissions decrease with increasing hydrogen. However, CO emissions tended to increase with the addition of hydrogen generally increase. It has been showed that hydrogen is a very good choice as a gasoline engine fuel. The data are also very useful for operational changes needed to optimize the hydrogen fuelled SI engine design.     

Experimental investigation on the performance and emissions of a diesel engine fuelled with ethanol–diesel blends

An experimental investigation on the application of the blends of ethanol with diesel to a diesel engine was carried out. First, the solubility of ethanol and diesel was conducted with and without the additive of normal butanol (n-butanol). Furthermore, experimental tests were carried out to study the performance and emissions of the engine fuelled with the blends compared with those fuelled by diesel. The test results show that it is feasible and applicable for the blends with n-butanol to replace pure diesel as the fuel for diesel engine; the thermal efficiencies of the engine fuelled by the blends were comparable with that fuelled by diesel, with some increase of fuel consumptions, which is due to the lower heating value of ethanol. The characteristics of the emissions were also studied. Fuelled by the blends, it is found that the smoke emissions from the engine fuelled by the blends were all lower than that fuelled by diesel; the carbon monoxide (CO) were reduced when the engine ran at and above its half loads, but were increased at low loads and low speed; the hydrocarbon (HC) emissions were all higher except for the top loads at high speed; the nitrogen oxides (NO_x) emissions were different for different speeds, loads and blends.