Exhaust NOx Emissions Research Articles

Investigation on the dual-stage SCR system control strategy based on NOx and exhaust temperature prediction model

With the advancements in deep learning and neural network technologies within the engine technology domain, intelligent control of exhaust after-treatment systems has become viable. The exhaust temperature significantly affects the NOx conversion efficiency of the SCR system. In this study, a time-series prediction model for exhaust temperature and NOx emissions was first developed using the LSTM neural network based on experimental data, and a Multi-Head Attention Mechanism was introduced to enhance the model’s predictive performance (LSTM-MA model). Subsequently, a dual-stage SCR system’s ammonia-to-NOx ratio control method (LSTM-ANR) was developed based on LSTM-MA model. The potential of the dual-stage SCR system using the LSTM-ANR control method to reduce NOx emissions during the WHTC cycle was analyzed using GT-Power and Simulink software. Finally, the experimental results show that the cold-state and hot-state WHTC cycle’ weighted NOx emission and conversion efficiency are 0.165 g/kW·h and 98.6%, respectively. Compared to the original data from the engine, NOx emission was reduced by 64.13%. This proves that the control method can effectively lower NOx emission.

Impact on Green Synthesised Al2O3 Nanoparticles on Performance and Emission Properties as Biodiesel operated diesel engine

<p style="text-align:justify;"><span style="font-family:"Times New Roman","serif";font-size:12pt;line-height:150%;">Global warming and pollution are two of the numerous causes of environmental issues due to industrial wastes and greenhouse gases. As a result, efforts are being made to limit emissions in order to mitigate these issues and reduce pollution. Given that fuel supplies are running low, biodiesel is one of the best alternatives to diesel fuel. One of the main obstacles to biodiesel's commercialization is its higher cost than diesel. One of the more superior substitute fuels for diesel is biodiesel, which is a fuel with great potential. When combined with 20% commercial diesel (B20), the resulting biodiesel is known as Pongamia. Improving engine performance and combustion characteristics while decreasing atmospheric NOX, CO, and HC exhaust emissions are the primary goals of this research. In comparison to neat diesel, BSFC and BTE were found to have increased by 12.27% and 15.34% respectively, while NOx, CO, and HC concentrations were decreased by 15.46%, 54%, 7.30%, and 25.67% respectively. Biodiesel mixed with Al<sub>2</sub>O<sub>3</sub> nano additive significantly improves the performance and combustion characteristics of diesel engines.</span></p>

Effects of metal doping on the methanol deep oxidation activity of the Pd/CeO2 monolithic catalyst

The Pd/CeLa, with a complete conversion temperature of 155 °C, shows the best methanol oxidation activity at low temperatures. It is due to the high-valence Pdδ+ (δ > 2) species produced by electron transfer from Pd at the interface to CeLa support.

A study on the relationship between vehicle operating conditions and NOx emission characteristics

To address the challenges faced by vehicles during actual operation when passing through traffic lights or intersections, where rapid changes in operating conditions can lead to a decrease in SCR efficiency and an increase in NOx emissions, this study focuses on defining characteristic position scenarios and analyzing the NOx emission characteristics of vehicles when passing through these scenarios based on real-time vehicle conditions. Through the analysis of several specific events, several road condition factors and driver behavior factors that may contribute to increased NOx emissions at characteristic position scenarios are identified. The findings indicate that when vehicles pass through traffic lights and intersections, the main causes of increased NOx emissions are low SCR temperature resulting from prolonged idling or engine shutdown, and high exhaust NOx emissions resulting from sudden excessive fuel injection. The driver behaviors associated with these situations primarily include coasting when approaching intersections, frequent stop-start behaviour due to traffic congestion or road crowding, choosing to shut off the engine for fuel efficiency during prolonged traffic congestion, and aggressive acceleration by stepping on the accelerator when the green light is about to turn red.

Effect of Diethyl Ether on Performance and Exhaust Gas Emissions of Heavy-Duty Diesel Engines Fueled with Biodiesel-Diesel Blend (B35)

To accelerate the energy transition, starting February 1, 2023, the Indonesian government has made it mandatory to use biodiesel (B35). Biodiesel has different characteristics from diesel oil, especially its greater viscosity and density, lower heating value, and high NOx emission. Therefore, this research has been carried out by adding the additive diethyl ether (DEE) to B35 to reduce the viscosity and density, increase the cetane number, and reduce emissions. The effects of diethyl ether on engine performances have been evaluated, including parameters of torque, power, brake thermal efficiency, brake-specific fuel consumption, exhaust emissions, and lubricants. The fuels used are B35 (35% FAME palm oil + 65% diesel oil), and B35 + DEE, with a DEE volume percentage of 3% to 6%. Diesel fuel (B0) was used as a comparison. Tests were carried out in the engine performance test laboratory using the heavy-duty diesel engine Komatsu SAA12V140E-3 at various engine speeds. The test results showed that adding diethyl ether slightly increases the average maximum power, increases brake thermal efficiency, and reduces brake-specific fuel consumption and emissions compared to B35. Very significant effects were seen in NOx and SO2 exhaust emissions. At maximum load, the mixture with 4% diethyl ether gave the greatest brake thermal efficiency, the lowest brake-specific fuel consumption, and the greatest reduction in NOx and SO2 emissions, respectively 7.69%, 6.30%, 53.48%, and 40.89% compared to B35, and 2.24%, (-0.90%), 48.88% and 71.17% compared to B0, respectively. Evaluation of lubricating oil during the performance test did not show a significant difference for all types of fuel used.

Co-optimization of miller degree and geometric compression ratio of a large-bore natural gas generator engine with novel Knock models and machine learning

Large-bore natural gas reciprocating generator engines will play crucial roles in future low-carbon energy systems. Knock, as an abnormal combustion phenomenon, is a bottleneck for long time to restrict the engine performance improvement. Development and application of the reliable knock model can contribute the predictive engine control and optimization to further improve the engine efficiency and performance. The biggest challenge of developing the predictive knock model is the stochastic nature of the knock phenomenon. To bridge the technological gap, this study aims to develop a novel predictive knock model for a large-bore natural gas engine and showcase its application for co-optimization of the engine design and control parameters, together with the machine learning. The knock model, taking the effects of hot spots heat release rate and energy density into account, is calibrated by the statistical phenomenological knock factor. The 1-D engine simulation model embedded with the knock model is built and calibrated. The data-driven model based on machine learning is developed and used to predict the relation between the key parameters and the engine performance. The genetic algorithms are employed to achieve the multi-objectives global optimization of geometric compression ratio, Miller degree and other control parameters of the engine to reduce the exhaust gas temperature and improve the engine performance. The co-optimized results show that the engine exhaust gas temperature can be remarkably lowered and the indicated thermal efficiency is increased by 1–3% depending on the operational conditions, without degrading the engine power output and increasing the exhaust NOx emissions.

Dynamic quantification of on-road emissions in Hong Kong: Impact from traffic congestion and fleet composition variation

Policymakers need a good understanding of on-road air pollutant emission patterns to manage air quality effectively, but it can be challenging to dynamically capture emission patterns with high spatial and temporal resolutions in cities. In this study, we used traffic congestion index extracted from Google Map, traffic density model and local emission factors to develop a dynamic on-road emission inventory for Hong Kong. The pollutants include NOx, CO, NMVOC, CO2, PM2.5, PM10, and CH4. On weekdays, exhaust emissions increased by up to 50.0% compared with those on Sunday due to higher traffic congestion index. High emission rates were observed on highways during weekday evening peak hours and shifted to regional centers on Sunday evenings. Public light buses, goods vehicles, and taxis were the most significant contributors of NMVOC, NOx, and CO emissions, respectively. Control policy testing showed that replacing diesel-fueled buses with electric buses could significantly reduce NOx and PM exhaust emissions, whereas replacing liquefied petroleum gas fueled public light buses with electric buses could efficiently control NMVOC emissions. Eliminating private cars older than 15 years could effectively reduce CO emissions. This study provides a dynamic on-road emission inventory for Hong Kong with high temporal and spatial resolutions. The results can be extended to real-time air quality simulations and human exposure research in the future.

Experimental investigation of the effect of fuel oil, graphene and HHO gas addition to diesel fuel on engine performance and exhaust emissions in a diesel engine

Today, research for alternative fuels continues due to the increasing energy demand, exhaust emission restrictions, and depletion of fossil fuels. It is important to use diesel engines for the opening of new oil fields in Turkey and for the utilization of fuel oil to be produced in these oil fields. In this study, pure diesel (D) diesel 60% and fuel oil 40% (DF40) were supplied by volume with an ultrasonic mixer. 50 (DF4050 N) and 100 ppm (DF40100 N) graphene have been added to eliminate fuel oil's adverse combustion effects by keeping the fuel oil constant. In addition, HHO gas was added to improve the combustion even more with a flow rate of 5 (DF4050N5H and DF40100N5H) and 10 (DF4050N10H and DF40100N10H) lt/min into the intake manifold by using the HHO generator. Experiments were carried out at 3000 RPM constant speed at 3.2, 6.4, 7.9, and 12.8 Nm engine torque without any modification on the diesel engine. The effects of these mixtures on combustion performance and exhaust emissions were investigated. Exhaust gas temperature and emissions were measured in the experiments. According to the measurements, thermal efficiency, brake specific energy consumption (BSEC), HC, CO, CO2, particle emission, and NOx emission values are given. Brake specific energy consumption (BSEC), CO, HC, and particle emissions decreased, and thermal efficiency, NOx, CO2, and exhaust gas temperature increased with the engine torque value increased as a result of the experiments. Thermal efficiency and CO2 emission decreased, and BSEC, exhaust gas temperature, HC, CO, NOx, and particulate emissions increased by adding fuel oil to diesel fuel. The thermal efficiency was increased by adding graphene and HHO gas from the intake manifold to DF40 fuel. The thermal efficiency improved, and emissions decreased with the more addition of graphene and HHO gas. Adding HHO gas improved thermal efficiency significantly at the 12.8 Nm engine load. With the addition of graphene and HHO gas to DF40 fuel, the BSEC value was improved at high torque values. The effect of improving thermal efficiency is also understood from the decrease in CO emissions and the increase in CO2 emissions. HC and PM emissions decreased with the addition of graphene and HHO gas. It was observed that NOx and exhaust gas temperature increased with increasing thermal efficiency.

NOx Emissions Control Area (NECA) scenario for ports in the North Adriatic Sea

In response to global warming, the International Maritime Organisation (IMO) set rules of 50% Greenhouse Gas (GHG) reduction by 2050, from 2008 levels. Signatory countries to the IMO's regulation require frequent assessment of the contribution of GHG emissions from shipping calling at their ports or trading in their territorial waters to ensure their compliance with the regulations. This demands a rapid and accurate method to assess shipping's contribution to GHG emissions.Current methodologies for estimating emissions from ships can be described on a scale between bottom-up and top-down methods. Top-down methods provide rapid estimates – primarily based on fuel sales reports - without considering individual vessel details. Therefore, they are less accurate and do not provide a breakdown of emissions by ship types or in specific regions. Bottom-up methodologies are detailed vessel-based estimates; however, they are data and time-demanding.The Ship Emissions Assessment method (SEA) (Topic et al., 2021) fills the gap between bottom-up and top-down methods by providing an innovative hybrid solution for rapid but accurate ship emission estimation. It uses publicly available, cost-effective data sets for emission estimates. The SEA method is capable of estimating ships' emissions in designated areas to understand regulations' effectiveness and provide emission quantification evidence. This research objective was to apply the SEA method to quantify CO2, SOX and NOX exhaust emissions from containerships for the three crucial containership ports: Trieste, Rijeka and Venice, in the North of the Adriatic Sea.The SEA methodology was applied to assess emissions and forecast efficiency in scenarios of different regulatory measures. A reduction in NOx emissions was estimated for the event of the implementation of NECA in all three ports. Results showed that 447.13 tonnes of NOx could be reduced each year in the North Adriatic Sea area around the ports of Rijeka, Trieste and Venice in the event that NECA regulations are stipulated.

Numerical analysis of ammonia HCCI combustion in a free piston engine through trajectory-based combustion control

Ammonia is a promising carbon–neutral fuel, able to power heavy-duty vehicles, non-road machineries and ocean ships with zero CO2 emission. However, practical challenges still exist when applying ammonia in traditional internal combustion engines (ICEs) due to its high ignition energy, slow flame propagation and significant NOx emissions. Free piston engine (FPE) is a flexible alternative to ICE whose piston can move freely without the constraints of crankshaft. Therefore, its piston trajectory can be leveraged as a new control means to facilitate ammonia combustion. In this paper, a numerical analysis investigating ammonia HCCI combustion in FPE was presented. A physical-based model was developed at first, including a unique trajectory synthesizing mechanism and a detailed reaction mechanism of ammonia oxidation. Various asymmetric piston trajectories were then employed into the model and the simulated HCCI combustion were analyzed through six characteristics, namely indicated thermal efficiency, location of peak pressure, exhaust gas temperature, combustion duration, ignition delay, and NOx emissions. This investigation not only determines the best compression ratio (CR = 25) for ammonia ignition, but also shape the optimal piston trajectory (symmetric trajectory with Ω = 0.5) for ammonia HCCI combustion to enhance thermal efficiency and reduce NOx emission simultaneously.

Applied Intelligent Grey Wolf Optimizer (IGWO) to Improve the Performance of CI Engine Running on Emulsion Diesel Fuel Blends

Water-in-diesel (W/D) emulsion fuel is a potential alternative fuel that can simultaneously lower NOx exhaust emissions and improves combustion efficiency. Additionally, there are no additional costs or engine modifications required when using W/D emulsion fuel. The proportion of water added and engine speed is crucial factors influencing engine behavior. This study aims to examine the impact of the W/D emulsion diesel fuel on engine performance and NOx pollutant emissions using a compression ignition (CI) engine. The emulsion fuel had water content ranging from 0 to 30% with a 5% increment, and 2% surfactant was employed. The tests were performed at speeds ranging from 1000 to 3000 rpm. All W/D emulsion fuel was compared to a standard of pure diesel in all tests. A four-cylinder, four-stroke, water-cooled, direct-injection diesel engine test bed was used for the experiments. The performance and exhaust emissions of the diesel engine were measured at full load and various engine speeds using a dynamometer and an exhaust gas analyzer, respectively. The second purpose of this study is to illustrate the application of two optimizers, grey wolf optimizer (GWO) and intelligent grey wolf optimizer (IGOW), along with using multivariate polynomial regression (MPR) to identify the optimum (W/D) emulsion blend percentage and engine speed to enhance the performance, reduce fuel consumption, and reduce NOX exhaust emissions of a diesel engine operating. The engine speed and proportion of water in the fuel mixture were the independent variables (inputs), while brake power (BP), brake thermal efficiency (BTE), brake-specific fuel consumption (BSFC), and NOx were the dependent variables (outcomes). It was experimentally observed that utilizing emulsified gasoline generally enhances engine performance and decreases emissions in general. Experimentally, at 5% water content and 2000 rpm, the BSFC has a minimal value of 0.258 kJ/kW·h. Under the same conditions, the maximum BP of 11.6 kW and BTE of 32.8% were achieved. According to the IGWO process findings, adding 9% water to diesel fuel and running the engine at a speed of 1998 rpm produced the highest BP (11.2 kW) and BTE (33.3%) and the lowest BSFC (0.259 kg/kW·h) and reduced NOx by 14.3% compared with the CI engine powered by pure diesel. The accuracy of the model is high, as indicated by a correlation coefficient R2 exceeding 0.97 and a mean absolute error (MAE) less than 0.04. In terms of the optimizer, the IGWO performs better than GWO in determining the optimal water addition and engine speed. This is attributed to the IGWO has excellent exploratory capability in the early stages of searching.

Expanding swirl combustor operability on methane-ammonia-air mixtures using a distributed fuel injection technique and inlet air preheating

The necessity to reduce greenhouse gas emissions has prompted the search for carbon-free fuel alternatives. One such carbon-free fuel source that can be used for power generation in a gas turbine-based system is ammonia. Ammonia combustion poses challenges due to reduced flame speed and reactivity, which can be alleviated by addition of methane or natural gas. However, NOx emissions continue to be an issue, which needs resolution before practical consideration of ammonia as a fuel source. One of the potential solutions that has been proposed is a two-stage, rich-lean combustion process to minimize NOx while ensuring complete reactant consumption. This work evaluates the use of two strategies to widen stability limits for swirl combustors operating on premixed methane-ammonia-air mixtures, which would facilitate the two-stage combustion approach. The first strategy involves the use of a distributed fuel injection approach utilizing a novel micro fuel injection swirler to facilitate homogeneous mixing in a highly compact manner while preventing flashback concerns. The second strategy involves use of inlet air preheating to increase flame stability and delay blow-off. The effectiveness of these strategies in expanding combustor operability limits is studied using experiments conducted in a model swirl-combustor setup designed to measure blow-off limits and evaluate exhaust NOx emissions. Complementary numerical simulations, particularly aimed at understanding NOx production pathways, are carried out using a reactor network model, wherein key inputs pertaining to recirculation volume and mass fraction are generated through detailed reacting flow simulations. The influence of the proposed strategies on NOx emissions are studied and underlying reaction pathways leading to NOx production are analyzed. Results of the study indicate that a distributed fuel injection strategy is able to significantly expand stability limits of a swirl combustor operating on methane-ammonia-air mixtures. Inlet air preheating provides additional expansion of stability limits, ≈ 7% for rich and lean blow-off, however, this is accompanied by increased NOx production, up to 14%, which is undesirable from an emissions standpoint. NOx is found to be significantly lower for rich fuel-air mixtures primarily through the effect of NHi reaction pathways responsible for NO consumption facilitated by the presence of excess NH3.

Engine Performance and Exhaust Emission Effect of Increasing Euro5 Diesel Fuel Blended with 7% to 30% Palm Biodiesel

Biodiesel blend fuels have gained popularity over the year due to their ability to be used in conventional diesel engines without any modifications and have proven to be a cleaner fuel. The Malaysian National Automotive Policy (NAP) 2020 projects the usage of biodiesel blend B30 (30%) to be implemented by the year 2025 or earlier. Most manufacturers approve its usage but do not suggest using a higher blend than 20%. This paper focuses on the difference in engine performance and exhaust emissions between 7 % and 30% Euro 5 diesel-biodiesel blend. The fuels used are Euro 5 diesel fuel blend with 7% (B7) and 30% (B30) palm biodiesel. The fuel is tested on a Toyota Hilux model KUN 25 with a 2KD-FTV engine. Chassis dynamometer tests were conducted on a steady-state condition for speeds 30, 60, 90, and 110 km/h with accelerator pedal positions (APP) of 45% and 90% measuring its brake power, BSFC, and exhaust emissions of CO2, CO, and NOx. It was found that B30 produced slightly lower brake power than B7 and slightly higher BSFC than B7. Both CO2 and CO emissions for B30 are lower than B7, with a more significant difference at speed 30 km/h at all APP conditions. NOx emission for B30 is higher at speed 30 km/h but slightly lower at speed 60, 90, and 110 km/h than B7. Therefore, increasing Euro 5 biodiesel blend from 7% to 30% slightly lowers brake power, increases BSFC, lowers CO2 and CO emissions, and increases NOx emissions.

Exergetic performance, combustion and emissions studies in a CI engine fueled with Al2O3 nano additive in a mixture of two different biodiesel and diesel blends

ABSTRACT This study uses an equal proportion of two different biodiesels obtained from waste cooking, neem oil and blended with diesel fuel to investigate the diesel engine’s combustion, emission, and exergetic performance. Al2O3 nano additive of 50ppm and 100ppm is used in diesel-biodiesel blends of B10 and B20 to improve the overall performance of the engine. The experimentations are conducted on a single-cylinder, four-stroke diesel engine at a fixed speed. The results reveal that 50ppm in the B10 blend improves the combustion with high exergetic efficiency and low exergy destruction. The various heat loss factors like exhaust, cooling, and radiation from the engine are determined using the second law of thermodynamics and the loss factor results reveal that the blend B10 with 50ppm shows high useful work of 32.84% with low radiation losses of 32.05% at 75% load. At 100% load, the blend B20 with 50ppm dominate the other blends. Finally, the addition of Al2O3 in biodiesel blends refines the combustion as a result, low exhaust emissions of NOx, CO, UHC, and smoke are reported.

Raw Jojoba Oil as a Sustainable Fuel to Diesel Engines and Comparison with Diesel Fuel

Raw Jojoba oil was used in a direct-injection diesel engine without any engine modifications and compared with both diesel fuel and 50/50 raw Jojoba/diesel. The measured parameters included the rheological properties measured in the range of shear rate from 100 to 500 1/s. Distillation data were presented for raw Jojoba oil compared to diesel. The parameters included exhaust gas analysis, block vibration, sound noise, and the combustion pressure and its rise rate. Averaged pressure-crank angle, vibration, and its frequency spectrum and sound level were presented. Data also included brake power, specific fuel consumption, and exhaust temperatures for all fuels used. For Jojoba oil, the engine did not exhibit low power output or specific fuel consumption. Exhaust temperatures, smoke opacity, and NOx emissions were lower than diesel case. Noise for Jojoba was higher than diesel case. The engine block vibration was concentrated towards the low frequency range.

Artificial neural network prediction of performance and emissions of a diesel engine fueled with palm biodiesel

Increasing of energy consumption, depletion of petroleum fuels and harmful emissions have triggered the interest to find substitute fuels for diesel engines. Palm ethyl ester was synthesized from palm oil through transesterification process. The physicochemical properties of palm biodiesel have been measured and confirmed in accordance with ASTM standards. The aim of the paper is to show the effect of different diesel-palm biodiesel blends on performance, combustion and emissions in diesel engine at engine load variation. Artificial Neural Network was used for the prediction of engine performance, exhaust emission and combustion characteristics parameters. Palm ethyl ester and diesel oil were blended in 5, 10, 15 and 20 by volume percentage. The maximum decreases in thermal efficiency, fuel–air equivalence ratio for B20 were 1.5, 3.5, 6 and 8% but the maximum increases in BSFC, exhaust gas temperature and NOx emission for B20 at full load about diesel fuel were 9, 8 and 10%, respectively. The highest decreases in CO, HC and smoke emissions of B20 about diesel oil at full load were 2, 35 and 18.5% at full load, respectively. Biodiesel blend B20 achieved the maximum declines in peak HRR, cylinder temperature and combustion duration about diesel fuel. The results of ANN were compared with experimental results and showed that ANN is effective modeling method with high accuracy. Palm biodiesel blends up to 20% showed the highest enhancements in engine performance, combustion and emission reductions compared to diesel fuel.

Investigation of the effect of JP-8 fuel and biodiesel fuel mixture on engine performance and emissions by experimental and statistical methods

In this study, the effects of JP-8 military aviation fuel and biodiesel sunflower oil on the performance and emissions of the internal combustion engine were investigated by creating a mixture of fuel in different concentrations. Experimental and statistical methods were used in the study process. All of the experiments were carried out on an experimental setup with a single-cylinder compression-ignition engine at 7.5, 12.5 and 17.5 Nm engine load conditions. A total of 5 different fuels were used, including pure JP-8 fuel, 3 different blended fuels and pure biodiesel fuel. The design of the Response Surface Method, which is used as a statistical method, was carried out with Central Composite Design in the Design Exper 11 program environment. After the created design, 13 different experiments were carried out. With the tests performed, the values of IMEP, BSFC, COVimep, ignition delay, equivalence ratio, exhaust gas temperature, CO, and NOx emission response parameters were determined. Quadratic models were created by performing variance analysis for the response parameters obtained. After the optimization, it was concluded that the engine load should be 14.49 Nm and the JP-8 fuel biodiesel ratio should be 2.47%. In case the internal combustion engine is operated with optimum input parameters, IMEP value is 3.71 bar, BSFC value is 193.46 g/kWh, COVimep value is 5.99 bar, CO value is 724 ppm and NOx value is 168.62 ppm.

Experimental evaluation of the impacts of diesel-nanoparticles-waste tire pyrolysis oil ternary blends on the combustion, performance, and emission characteristics of a diesel engine

In the present research, pyrolytic oil is obtained from the waste tire chips, and then acid washing process, clay and calcium oxide process, distillation process, and oxidative sulfur removal processes are used to improve its properties. Then it is blended into conventional diesel fuel with/without Al2O3 nanoparticles, and the performance, combustion, and emission characteristics of a single-cylinder, air cooled, and naturally aspired diesel engine are discussed in this study. Tests were performed at varying engine loads from 3 to 12 Nm with the gaps of 3 Nm under a constant engine speed of 2400 rpm. In this study, three types of fuels were tested, namely D100 (100% diesel fuel), P10 (90% diesel fuel and 10% pyrolytic oil), and P10 + 1 g Al2O3 (obtained by adding 1 g of Al2O3 nanoparticles to P10 fuel). The addition of Al2O3 nanoparticles increased the brake thermal efficiency while reducing the maximum in-cylinder pressure, heat release rate, specific fuel consumption, exhaust gas temperature, hydrocarbon emissions, NOx emissions, and CO emissions compared to other test fuels. Namely, with the addition of Al2O3 nanoparticles, BTE was improved by 4.51% and 1.59% compared to P10 and pure diesel fuel, respectively. According to this, the BSFC value increased by 4.29% for P10 test fuel and then is reduced by 2% for P10 + 1 g Al2O3 test fuel as compared with conventional diesel fuel. Compared to diesel fuel, the CO, NOx, and HC emission values deteriorated by 17.5%, 5.69%, and 18.6%, respectively, with the addition of pyrolysis oil, and these deteriorated properties were improved by 10%, 6.82%, and 13.95%, respectively, with the addition of Al2O3 nanoparticles. In the light of this study, it was observed that while waste tire pyrolysis oil worsened engine performance, emission, and combustion characteristics, these deteriorations could be improved with nano Al2O3 supplementation.

A REVIEW OF BIODIESEL PRODUCTION FROM NON-EDIBLE RAW MATERIALS USING THE TRANSESTERIFICATION PROCESS WITH A FOCUS ON INFLUENCE OF FEEDSTOCK COMPOSITION AND FREE FATTY ACIDS

The main resources needed for an alternative fuel are availability and renewability, that is, less dependence on restricted raw materials accompanied by no or less pollution. Due to being eco-friendly and non-toxic to nature, biodiesel is attracting more and more interest. Biodiesel has many important technical advantages compared to petroleum diesel, such as inherent lubricity, low toxicity, derivation of renewable and domestic raw materials, biodegradability, insignificant sulfur content, and lower exhaust emissions. However, they have some important disadvantages that include the high cost of the raw material, lower storage and oxidative stability, lower volumetric energy content, lower low-temperature operability, and in some cases, higher NOx exhaust emissions. One of the major challenge obstacles is the high cost of refined vegetable oil as raw material, which consists of almost 70% of the total production costs. Therefore, in order to reduce the cost of biodiesel, non-edible sources such as residual cooking oil (WCO), algae oil, non-edible vegetable oil, and residual fats are commonly used for the production of biodiesel due to its low cost and don’t affect the food chain. The most common method used in the production of biodiesel is the transesterification of vegetable oils and animal fats. Production and process are influenced by several factors, such as temperature and reaction time, the molar ratio of alcohol to oil, and type and concentration of catalyst. Therefore, this review focuses on the recent discovery of the transesterification of inedible sources for biodiesel, the influence of the composition of the raw material on the quality of biodiesel, and the possible solutions to its disadvantages for the production of biodiesel.

Multi-objective optimization of DI diesel engine performance and emission parameters fueled with Jet-A1 – Diesel blends

This study performed the performance and emission effects of adding Jet-A1 aviation fuel to diesel fuel in a direct injection, single-cylinder diesel engine. In addition, the response surface method was used to investigate combustion, performance, and emissions of the test fuel obtained by mixing Jet-A1 with diesel blends fuel under various engine conditions. Central Composite Design was used to create a design matrix. The input parameters were selected as brake torque and fuel type. On the other hand, the responses were selected as ignition delay time, specific fuel consumption, exhaust gas temperature, COVIMEP, CA50, CA10-90, CO, NOx, and soot emission. In order to determine the optimum operating range of the diesel engine, a desirability function was used. The optimum operating range of the diesel engine was found as brake torque of 11.25 Nm and Fuel Type of A25 by using the response surface method. Besides, response parameters were determined under optimum operating conditions as the specific fuel consumption of 0.257 kg/kWh, the ignition delay time of 1.296 ms, exhaust gas temperature of 367.53 °C, COVIMEP of 8.751%, CA50 of 14,984 °CA, CA10-90 of 95.319 °CA, CO of 264.06 ppm, soot emission of 0.715 (k factor (m-1)), and NOx of 132.279 ppm, respectively.