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Renewable energy is an important issue for substituting fossil fuels in the world. Biofuel is one of the most used fuels for transportation, mining, and the industrial sector. The government of Indonesia’s policy has mandatorily used biofuel for the blend to fossil fuel. Biodiesel production from palm oil base has good characteristics for substitute/blend to high-speed diesel (HSD) in the market. The objective of this study was to investigate the effects of cetane number value of variant HSD-biodiesel blend and the methodology with blending two types HSD and biodiesel (0%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 50%, 60%, 70%, 80%, 90%, 100%). The measurement of cetane number used a CFR engine in accordance with ASTM D 613. The result of this study was that the increasing percentage of biodiesel blend influenced the increasing value of cetane number, but the increasing value of cetane number was not linear. Therefore, biodiesel can be used as a cetane booster for HSD.

Artificial intelligence-based computing systems like artificial neural networks (ANN) have recently found increasing applications in predicting complex chemical phenomena like combustion properties. The present work deals with the development of an ANN model that can predict the derived cetane number (DCN) of oxygenated fuels containing alcohol and ether functionalities. Experimental DCNs of 499 fuels comprised of 116 pure compounds, 222 pure compound blends, and 159 real fuel blends were used as the dataset for model development. DCN measurements of sixty new fuels were carried out in the present work, and the data for the rest were collected from the literature. Fuel chemical composition expressed in the form of eight functional groups, namely, paraffinic CH3 groups, paraffinic CH2 groups, paraffinic CH groups, olefinic -CH=CH2 groups, naphthenic CH-CH2 groups, aromatic C-CH groups, alcoholic OH groups, and ether O groups, along with two structural parameters, namely, molecular weight and branching index (BI), were used as the ten input features of the model. The qualitative and quantitative determination of functional groups present in real fuels was performed using ¹H nuclear magnetic resonance (NMR) spectroscopy. A robust ANN methodology was then applied to prevent overfitting, using a multilevel grid search and genetic algorithm. The final developed model with two hidden layers was tested with 15% of randomly generated unseen points from the dataset, and a regression coefficient (R²) of 0.992 was observed between the experimental and predicted DCN values. An average absolute error of 0.91 obtained from the test set indicates that the developed ANN model is successful in predicting the DCN of oxygenated fuels and captures the dependence of the fuel’s ignition quality (i.e., DCN) on its constituent functional groups.

In the current phase of world economy, the utilization of the petroleum-based fossil fuels has drastically surpassed the supply. This scenario supplements to the fact that there is an ever increasing necessity for industrialization, specifically in the transportation sector. This requirement and supply of the petroleum and diesel fuels have an astounding impact over the market economy and related commodities. Low viscous and low cetane number biofuels are getting more attention for their usage in engine applications without any further processing. In the present work, lemon peel oil is being fuelled in diesel engine at different timing of injection and exhaust gas recirculation rates. Operation of lemon peel oil (LPO) at standard operating conditions results in increased brake thermal efficiency by consuming less fuel when compared with diesel fuel. The LPO biofuel properties such as boiling point and viscosity being lower leads to better evaporation capacity and thereby results in complete combustion. The advancement in injection timing of 25° bTDC and 27° bTDC resulted in the efficiency increment of 2.17% and 6.19% respectively. Furthermore, the smoke, carbon monoxide and hydrocarbon emissions are decreased in consequence on increased nitrogen oxide (NOx) emissions. Hence, in order to decrease the content of nitrogen oxide emissions in the exhaust, exhaust gas recirculation (EGR) has been implemented in the present work. For EGR rate of 10% and 20%, the NOx emissions is reduced by 43% and 46% respectively for 27° bTDC injection timing. Thus, the advancement of injection timing with optimum EGR is a viable option for the lemon peel oil biofuel in diesel engine with superior performance and emission output.

The ignition tendency of diesel fuels is highly sensitive to ambient conditions and fuel properties. In this study, the ignition characteristics of different diesel surrogate fuels with the same derived cetane numbers (DCN) were measured and compared in varied thermodynamic and oxidizing environments. The combustion pressures, heat release rates, ignition delays, and combustion delays of the test fuels were compared. The experimental results showed that the diesel surrogate fuels with the same DCNs exhibit similar ignition propensity at standard DCN test conditions. Further, for the test conditions of high cetane fuels, high ambient temperatures, and sufficient oxygen concentrations, surrogate fuels with the same DCN have similar ignition behaviors, and using the DCN to evaluate fuel ignition tendency is appropriate. However, for the test conditions of low cetane fuels, low ambient temperatures, and reduced oxygen concentrations, different ignition behaviors are observed for the surrogate fuels with the same DCN, so at these conditions using DCN as the evaluation index for fuel ignition tendency may lead to higher uncertainty.

For enhancing the cetane number (CN) of diesel fraction, the selective oxidative ring opening method was applied to upgrade ring hydrocarbons. Organic acids, one of the main products from this oxidative reaction, being esterified by the phase transfer catalysis (PTC) approach were studied. Adipic acid, benzoic acid, and phthalic acid were used as model compounds. Reaction time, reaction temperature, the amount of water, and the amount of catalyst in the esterification process were investigated and optimized using orthogonal experimental design method. The kinetics of esterification process was then conducted under the optimal condition. The types of catalysts and organic acids, the amount of catalyst and water were also investigated. The PTC esterification was one rate controlling reaction on the interface between the aqueous phase and the oil phase. Hydrophobicity is a key factor for converting benzoic acid, adipic acid, and phthalic acid to the corresponding esters. It was found that around 5–8% water is the optimal quantity for the given reaction system. Two cases of esterification processes of PTC were proposed.

The cetane number is a key indicator for evaluating the ignition performance of diesel fuels in compression ignition engines, and the diesel cetane number determination methods based on constant volume combustion technology have received widespread attention. The ignition characteristics of diesel fuels in a constant-volume combustion chamber were analyzed, and the testing characteristics of six constant-volume combustion chamber methods were compared and studied from the aspects of experimental conditions and determination precision. The results show that different constant volume combustion determination methods have different ignition delay periods for the same sample, which are negatively correlated with the fuel injection speed of each method. Within the precision coverage range, NB/SH/T 6035-2021 and ASTM D7668-23 have the highest precision. The reproducibility of ASTM D8183-22 and ASTM D7668-23 and the standard engine method is superior to other determination methods.

The cetane number is the most significant property for measuring the ignition quality of fuels for compression ignition diesel engines. In this study, the derived cetane number (DCN) of several types of biodiesel, biodiesel components and ultra-low sulfur diesel (ULSD) was determined using an Ignition Quality Tester (IQT™). The chemical structure of FAME leads to a higher cetane number of biodiesel compared to ULSD. The contribution to DCN from minor components present in biodiesel is not significant. Oxidation of biodiesel samples results in higher DCN values while depending on the conditions of oxidation. A greater than 25% increase was observed when oxidation was carried out in a way to retain volatile oxidative products such as carboxylic acids and aldehydes. Accelerated oxidation of cotton seed oil (CSO) biodiesel at 110 °C and 10 L/min air flow rate after 210 min resulted in a loss of 14% of the FAME content, of which 10% can be attributed to the oxidation of methyl linoleate (C18:2), whereas oxidation of soy bean oil (SBO) biodiesel resulted in a loss of 21% total FAME after 210 min. A significant amount of methyl linolenate (C18:3) remained un-reacted after 210 min of oxidation. Ambient oxidation of distilled biodiesel samples resulted in a very high cetane number. Oxidative products such as aldehydes, hydroperoxides and oligomers of FAME are probably responsible for this higher DCN. This study enhances the understanding of the effect of composition on the cetane number of biodiesel as well as the effect of oxidative aging on both biodiesel composition and the resultant DCN.

The world is facing two serious problems: energy crises and pollution. The daily increase in industrialization and the number of automobiles is the reason for these two problems. This work focus on to analyse the performance characteristics and emission parameters of the diesel engine for the blend of calophyllum inophyllum (Honne oil) Biodiesel blend (B10, B20 and B30) and Also find out how they affect the performance of the I.C Engine. While testing, the compression ratio of the engine was in the range of 15 to 18. Then speed of the engine is constant (1500 rpm). In conventional diesel engines and exhaust gases such as carbon monoxide (CO), oxides of nitrogen (Nox), hydrocarbons (HC) has been reduced. Considering that, by using this hybrid system, the thermal performance and the emission system must be investigated.

Sixteen biodiesel cetane number (CN) predictive models developed since the early 1980s have been gathered and compared in order to assess their predictive capability, strengths and shortcomings. All are based on the fatty acid (FA) composition and/or the various metrics derived directly from it, namely, the degree of unsaturation, molecular weight, number of double bonds and chain length. The models were evaluated against a broad set of experimental data from the literature comprising 50 series of measured CNs and FA compositions. It was found that models based purely on compositional structure manifest the best predictive capability in the form of coefficient of determination R2. On the other hand, more complex models incorporating the effects of molecular weight, degree of unsaturation and chain length, although reliable in their predictions, exhibit lower accuracy. Average and maximum errors from each model’s predictions were also computed and assessed.

‘Higher’ alcohols, which contain more than two carbons, have a higher boiling point, higher cetane number, and higher energy density than ethanol. Blends of biodiesel and higher alcohols can be used in internal combustion engines as next-generation biofuels without any modification and are minimally corrosive over extensive use. Producing higher alcohols from biomass involves fermenting and metabolizing amino acids. In this review, we describe the pathways and regulatory mechanisms involved in amino acid bioprocessing to produce higher alcohols and the effects of amino acid supplementation as a nitrogen source for higher alcohol production. We also discuss the most recent approaches to improve higher alcohol production via genetic engineering technologies for three microorganisms: Saccharomyces cerevisiae, Clostridium spp., and Escherichia coli. Proteins are polymers of various amino acids, connected via peptide bonds and classified as a major feedstock for bioenergy production. Higher alcohols are high-density alternative fuels that increase the longevity of transportation fuels. Proteins have a significant role in the fermentation process by providing amino acids for the growth of microorganisms, and enhancement of sugar permeability, in carbohydrate-rich sources. Due to the environmental and economic advantages of recombinant DNA technology, fermentation is the most used process for industrial-scale alcohol production. Applying this technology to higher alcohols can significantly improve industrialization for advanced fuel production. Extraction techniques are used to separate and mitigate the toxicity of alcohols produced in the fermentation broth to maintain the microbial cell viability for longer.