Validation and enhancement of waste cooking sunflower oil based biodiesel production by the trans-esterification process

This article predicts the optimum conditions for the production of fatty acid ethyl ester (Biodiesel) by trans-esterification process of waste cooking sunflower oil with ethanol in the presence of homogeneous catalyst (KOH). Response surface methodology (RSM) based on central composite rotatable design (CCRD) was used for predicting the mathematical regression equation and optimizing the biodiesel yield. The optimum reaction conditions were found to be 9.05 (mole mole^?1) of (ethanol to waste cooking sunflower oil ratio), 0.99 (wt% to oil) of catalyst concentration, 57.31°C of reaction temperature, 77.12 minutes of reaction time, and 494.94 rpm of mixing rate to achieve 96.33% biodiesel yield by weight. The production rate of produced biodiesel also increased significantly. The fuel properties were measured and found closer to the ASTM standards of biodiesel. Therefore, the suggested biofuel has good scope for use in compression ignition (CI) engines.     

ANFIS modeling of biodiesels' physical and engine characteristics: A review

 Population increase has resulted in an increase in the worldwide demand for alternative fuels due to depleting resources. There is a periodic increase in concern about the engine performance, pollutant emissions, and their predictions, from an engine using biodiesels. The use of intelligent algorithms in modeling and forecasting alternative fuels characteristics and their performance in engines are critically reviewed in this study. The paper aims at demonstrating with artificial intelligence methodologies the main conclusions of the recent research done for the above topic from 2012 to 2020. This article attempted to demonstrate an exploratory examination of the adaptive neuro-fuzzy inference system (ANFIS) soft computing technique used for the exact measurement and analysis of engine performance, emissions of exhaust engines when biodiesel is used as an alternative fuel. Additionally, the yield of biodiesel and their different characteristics predicted using ANFIS are also reviewed. Integration of particle swarm optimization (PSO), genetic algorithm (GA), and response surface methodology (RSM), either for comparison or optimization with ANFIS is presented. The summary of all studies is provided in tabular form. For the demonstration purpose, the ANFIS studies predicting different biodiesel and engine characters are provided with illustrative figures. The ANFIS prediction related to biodiesel used engine and biodiesel self-characteristics is found to be excellent. The ANFIS accuracy reported is better than the artificial neural network (ANN) accuracy. A minimum of 0.9 R² value is generally obtained which is around 5% greater than the ANN modeling results reported. However, the ANFIS predictions are much more fitter than the RSM predictions. The integration of ANFIS-PSO and ANFIS-GA provided much more optimized results.     

Comparison of Response Surface Methodology (RSM) and Artificial Neural Network (ANN) in modelling of waste coconut oil ethyl esters production

The attributes of renewability and environmental friendliness have made ethanol a preferable alternative to methanol in the production of biodiesel from lipid feedstocks. For the first time, this study adopted Response Surface Methodology (RSM) and Artificial Neural Network (ANN) to model coconut oil ethyl ester (CNOEE) yield. Transesterification parameters such as reaction temperature and ethanol/coconut oil molar ratio and catalyst dosage were varied. Maximum CNOEE yield of 96.70% was attained at 73 °C reaction temperature, 11.9:1 molar ratio, and catalyst dosage of 1.25 wt. %. The experimental yield was in agreement with the predicted yield. Central Composite Design was adopted to develop the RSM while feed-forward back propagation neural network algorithm was employed for the ANN model. Statistical indices were employed to compare the models. The computed coefficient of determination (R²) of 0.9564, root-mean-squarce-error (RMSE) of 0.72739, standard error of prediction (SEP) of 0.008021, mean average error (MAE) of 0.612, and average absolute deviation (AAD) of 0.674901 for RSM model compared to those of R² (0.9980), RMSE (0.68615), SEP (0.007567), MAE (0.325), and AAD (0.3877) for ANN indicated the superiority of the ANN model over the RSM model. The key fuel properties of the CNOEE met with those of biodiesel international standards.     

Biodiesel production from castor oil using potassium hydroxide as a catalyst: Simulation and validation

The key objective of the present research is to optimize and investigate the biodiesel production from ricinuscommunis (castor) oil using microwave-assisted hybrid transesterfication process under various conditions such as microwave power, treatment time, ethanol:oil ratio and catalyst concentration (KOH). Response surface methodology (RSM) coupled with four factors with a three-level Box–Behnken response surface design (BBD) was employed to model the transesterfication technique. The obtained results were analyzed by analysis of variance (ANOVA) and a second-order polynomial model was developed to study the interactive effect of process factors on biodiesel production. Derringer’s desired function methodology was used for the optimization and optimum conditions for maximizing the biodiesel production. Under optimum conditions, the predicted biodiesel production was found to be 95% with a desirability value of 0.998. The fuel properties of the produced biodiesel were compared with the ASTM D6751 standards.     

Performance evaluation of adaptive neuro-fuzzy inference system and response surface methodology in modeling biodiesel synthesis from jatropha–algae oil

Biodiesel production from different feedstocks is an effective method of resolving problems related to the fuel crisis and environmental issues. In this study, an adaptive neuro-fuzzy inference system (ANFIS) and the response surface methodology based Box–Behnken experimental design were used to model the parameters of biodiesel production for a jatropha–algae oil blend, including the molar ratio, temperature, reaction time, and catalyst concentration. A significant regression model with an R² value of 0.9867 was obtained under a molar ratio of 6–12, KOH of 0–2% w/w, time of 60–180 min, and temperature of 35–55°C using response surface methodology (RSM). The ANFIS model was used to individually correlate the output variable (biodiesel yield) with four input variables. An R² value of 0.9998 was obtained in the training. The results demonstrated that the developed models adequately represented the processes they described.     

Effect of preheating waste cooking oil on biodiesel production and properties

Waste cooking oil from the university cafeteria was used as feedstock to produce biodiesel. The feedstock was then converted to biodiesel using two different methods. The two methods tested were with and without preheating to study the effect of preheating on biodiesel. For each one of the two methods two types of catalysts were used that is alkali and acidic. The effect on biodiesel yield, calorific value, viscosity, and density was observed. It was found that with preheating to higher temperatures, the yield was 87% with alkali catalyst and 70% with acid catalyst. On the other hand, without preheating, it was found that the yield using alkali catalyst was 98% and 75% using acidic catalyst. Further, the highest calorific value was obtained using alkali catalyst without preheating.     

Optimization and oxidative stability of biodiesel production from rice bran oil

Biorefinery approach is introduced for the biodiesel production by utilizing low cost raw material, such as rice bran oil (RBO). The valorization of RBO was carried out by homogeneous transesterification process using response surface methodology (RSM) based on a two-variable central composition design (CCD). The process variables, temperature and catalyst concentration were found to have significant influence on biodiesel yield. The optimum combination derived via RSM for high ester yield (99.4%) was found to be 0.75% wt catalyst concentration at a reaction temperature of 45 °C. As biodiesel chemically is a long-chain alkyl methyl esters, its long-term fuel properties have become of great concern to the fuel industry. In order to determine the effects of long storage on oxidation stability, RBO biodiesel sample was stored for 24 months and the different physical–chemical properties were checked with respect to time. The results show that the acid value (AV), peroxide value (PV), and viscosity (ν) increased while the iodine value (IV) decreased. Based on results, correlations were obtained in terms of AV, IV, PV and ν as a function of time. Those correlations can be used to predict how long time biodiesel can safely be stored. AV, IV and PV of the biodiesel sample which was stored were within the limits in European biodiesel specifications (EN 14214).     

A facile noncatalytic methyl ester production from waste chicken tallow using single step subcritical methanol: Optimization study

In this modern era, an increase in urbanization causes the escalating trend of fuel demand as well as environmental pollution problems. Various biofuels research with the respect of climate change and emission reduction recently intensifies, particularly in biodiesel. In Indonesia, diesel oil currently in use contains 20% of biodiesel. Utilizing waste‐based resources such as rendered chicken tallow as the feedstock could be the solution to both energy and environmental challenges. However, chicken tallow contains a significant amount of free fatty acid (FFA) which will obstruct the production yield of biodiesel. In this study, catalyst‐free subcritical methanol has been employed to convert waste chicken tallow (WCT) with high FFA into biodiesel. Design of experiment was conducted to study the effect of temperature, time, and the molar ratio of methanol to fats on the purity and recovery of fatty acid methyl esters (FAMEs). Based on the optimization study performed by response surface methodology (RSM), all three independent variables gave a significant effect on the recovery of FAME. From the experimental results, the maximum FAME yield obtained was 98.43 ± 0.22% with the optimum condition as follows: 167°C, 36.8 minutes, and 42.7:1 (methanol/WCT, mol/mol), while the predicted FAME yield obtained using RSM was 97.76%. The methyl ester composition of WCT‐based biodiesel ranges from C13 to C24.     

Comparative performance analysis of diesel engine fuelled with hydrogen enriched edible and non-edible biodiesel

In the present study, a comparative analysis of enrichment of hydrogen alongside diesel fuel and two different sources of biodiesel namely rice bran oil is an edible oil, and karanja oil being non-edible is tested. Hydrogen at a fixed flow rate of 7 lpm is inducted through the intake manifold. A total of six fuel samples are considered: diesel (D), hydrogen-enriched diesel (D + H₂), hydrogen-enriched 10, and 20% rice bran biodiesel blend (RB10 + H₂ and RB20 + H₂), and hydrogen-enriched 10 and 20% karanja biodiesel blend (KB10 + H₂ and KB20 + H₂). Results indicate that enrichment of hydrogen improves combustion and results in 2.5% and 1.6% increase in the brake thermal efficiency of diesel fuel and rice bran biodiesel, respectively. For karanja biodiesel the increment is negligible. Fuel consumption of the D + H? is 6.35% lower and for RB10 + H? and KB10 + H? it is decreased by 2.9% and 1.3%, respectively. The Presence of hydrogen shows the 4–38% lower CO emissions and 6–14% lower UHC emission due to better combustion. The blends RB10 + H? and KB10 + H? produce up to 6–13% higher NOx emission and that for the blends RB20 + H? and KB20 + H? it goes up to 25%. Overall rice bran oil is found to provide better performance than karanja biodiesel.     

Application of D-optimal design and RSM to optimize the transesterification of waste cooking oil using natural and chemical heterogeneous catalyst

This work illustrates a comparative study on the applicability of the natural calcium oxide (CaO) prepared from waste eggshells and chemical CaO as basic heterogeneous catalyst in the transesterification of waste cooking oil (WCO) with methanol for production of biodiesel. Response surface methodology (RSM) based on D-optimal design of experiments was employed to study the significance and interactive effect of methanol-to-oil (M:O) molar ratio, catalyst concentration, reaction time, and mixing rate on biodiesel yield. Second-order quadratic model equations were obtained describing the interrelationships between dependent and independent variables to maximize the response variable (biodiesel yield) and the validity of the predicted models were confirmed. The activity of the produced natural biocatalyst was comparable to that of chemical CaO, producing high yield of biodiesel ≈91 and 98% at 8.57:1 M:O, 3.99 catalyst wt%, 31 min reaction time, and 398.88 rpm mixing rate at 60°C, respectively. Fuel properties of the produced biodiesel were measured and compared with those of Egyptian petro-diesel and international biodiesel standards. The overall biodiesel characteristics either prepared using natural or chemical CaO were comparable and acceptable, encouraging the application of CaO prepared from waste eggshells for production of biodiesel as an efficient, environmentally friendly, sustainable, and low cost heterogeneous catalyst.     

Performance evaluation of artificial neural network coupled with generic algorithm and response surface methodology in modeling and optimization of biodiesel production process parameters from shea tree (Vitellaria paradoxa) nut butter

This work investigated the potential of shea butter oil (SBO) as feedstock for synthesis of biodiesel. Due to high free fatty acid (FFA) of SBO used, response surface methodology (RSM) was employed to model and optimize the pretreatment step while its conversion to biodiesel was modeled and optimized using RSM and artificial neural network (ANN). The acid value of the SBO was reduced to 1.19 mg KOH/g with oil/methanol molar ratio of 3.3, H₂SO₄ of 0.15 v/v, time of 60 min and temperature of 45 °C. Optimum values predicted for the transesterification reaction by RSM were temperature of 90 °C, KOH of 0.6 w/v, oil/methanol molar ratio of 3.5, and time of 30 min with actual shea butter oil biodiesel (SBOB) yield of 99.65% (w/w). ANN combined with generic algorithm gave the optimal condition as temperature of 82 °C, KOH of 0.40 w/v, oil/methanol molar ratio of 2.62 and time of 30 min with actual SBOB yield of 99.94% (w/w). Coefficient of determination (R²) and absolute average deviation (AAD) of the models were 0.9923, 0.83% (RSM) and 0.9991, 0.15% (ANN), which demonstrated that ANN model was more efficient than RSM model. Properties of SBOB produced were within biodiesel standard specifications.     

Fuzzy-modeling with Particle Swarm Optimization for enhancing the production of biodiesel from Microalga

Biodiesel is one of the promising energy sources that could replace petroleum oil in the near future. Microalgae is occupying a distinguished position among the promising sources for biodiesel production. Enhancement of the lipids production during the pretreatment is a key factor for the biodiesel production. High-pressure homogenizer is a better pretreatment procedure to enhance the lipid extraction from microalgae. In this research, a robust model of biodiesel system using fuzzy logic is built based on the experimental data for biodiesel system. Then, Particle Swarm Optimization (PSO) optimizer is applied for determining the best operating parameters of biodiesel system. The decision variables used in the optimization process are; pressure, number of passes, and reaction time that maximizes the percentage of recovery lipids of biodiesel. A comparison study was carried out between the optimized results thought PSO algorithm and those obtained by the experimental results and the optimized results through the Response Surface Methodology (RMS). Results demonstrated that using the proposed optimization methodology is significantly better than RSM, a nearly 78.7% increase in lipids extraction could be achieved according to the current model.     

Muskmelon (Cucumis melo) seed oil: A potential non-food oil source for biodiesel production

Methanolysis of muskmelon seed oil was optimized employing RSM (response surface methodology). Four process variables were evaluated at two levels: methanol/oil molar ratio (3:1–12:1), catalyst concentration in relation to oil mass (0.25–1.25 wt % KOH), reaction temperature (25–65 °C) and methanolysis reaction time (20–90 min). Multiple regression analysis was employed to get the quadratic polynomial equation for predicting transesterification using RSM. The result indicated that catalyst concentration and reaction temperature were the important factors that significantly affect the yield of MMOMEs (muskmelon oil methyl esters)/biodiesel. The RSM methodology was used to obtain methyl esters yield (89.5%) were found at following reaction conditions; 5.8:1 methanol-to-oil ratio, 0.79% catalyst concentration, 55 °C reaction temperature and 72.5-min reaction time. There was a linear correlation between observed and predicted values. The biodiesel was analyzed using GC/MS (gas chromatography/mass spectrometry) which indicated four FAMEs (fatty acid methyl esters) (linoleic-, oleic-, palmitic- and stearic acids) as its major components. The FT-IR (fourier transform infraRed) spectrum of MMOMEs was also acquired to ensure the confirmation of methyl esters formation. Fuel properties of MMOMEs were determined and found to satisfy the ASTM D 6751 and EU 14214 specifications.     

Partial hydrogenation and hydrogen induction: A comparative study with B20 operation in a turbocharged CRDI diesel engine

Numerous studies explored the possibility and effective strategies for supplementing hydrogen along with fossil or biofuels on internal combustion engines. Hydrogen is also being employed for formulating fuels such as hydrogen compressed natural gas in the gaseous form and hydrogenated biofuels in the liquid form. The present study evaluates (i) hydrogen usage on the fuel formulation and (ii) investigates the engine operation of an automotive turbocharged diesel engine operated with karanja biodiesel blended diesel (B20) as a reference fuel. Existing literature outlines that biodiesel blends possess lower energy content and emit higher nitric oxide (NO) emission than fossil diesel. The present research paper partially hydrogenates karanja biodiesel using an autoclave reactor with a palladium catalyst to increase the saturation levels and mitigate the biodiesel-NO penalty. Besides, the drop in energy release of B20 is compensated through the provision of hydrogen induction along the intake manifold. The hydrogen flow rates to the turbocharged engine are maintained at a fixed energy share of 10%. Both biodiesel and hydrogenated biodiesel were blended on a volume basis (20%) with fossil diesel (80%) and are designated as B20 and HB20, respectively. The test results reveal that HB20 effectively mitigates the biodiesel-NO penalty with a maximum reduction of 29.8% compared to B20. Further, hydrogen induction yielded a significant improvement (23.7%) in fuel consumption with HB20 relative to B20 without hydrogen addition. The compounding effect of hydrogen usage on the engine operation and fuel formulation exhibited a better performance and emission trade-off at mid load conditions.     

Alkaline catalyzed biodiesel production from safflower (Carthamus tinctorius L.) oil: Optimization of parameters and determination of fuel properties

In this study, the process of biodiesel production from safflower oil was optimized using a single-stage alkaline catalyst (NaOH). The optimization process was carried out depending on parameters, such as catalyst concentration, methanol-oil ratio, reaction temperature, and reaction time. The optimum biodiesel conversion efficiency was obtained to be 93.4% at 0.5% catalyst concentration, 20% methanol-oil ratio, 60 min reaction time, and 60°C reaction temperature. The fuel properties of biodiesel obtained under optimal conditions were determined.     

Assessment of tree seed oil biodiesel: A comparative review based on biodiesel of a locally available tree seed

The present investigation is undertaken to investigate prospect of seeds of a locally available tree (koroch) for biodiesel production. The middle-size, evergreen koroch tree with spreading branches are available in Assam. The characteristics of koroch biodiesel and engine performance fueled by koroch biodiesel are also analyzed reviewing similar results available in the literature so as to ascertain its status. Twelve number of different tree seed oils, reported earlier, are considered for making the present comparative assessment. Though transesterification has been the common process for converting tree seed oil into biodiesel, as evidenced from the literature consulted in this study, but there have been variations of the chemical processes. Variations of the transesterification are attributed to (i) types of catalysis viz., acid (H₂SO₄) or base (KOH, NaOH, and NaOCH₃), (ii) reaction temperature, (iii) molar ratio, (iv) nature of reaction viz., single stage or multi-stage. The outputs of the reaction have also been found varying in terms of yield as well as quality. Quality of biodiesel, however, was found to influence by the nature of feedstock. The assessment of quality parameters was made either by ASTM D 6751 or EN 14214 standards. The major fuel properties such as calorific value, kinematic viscosity, cetane number and cloud point of the reference biodiesel (koroch biodiesel) are compared with the properties of five biodiesel obtained from non-edible tree seed (karanja, mahua, polonga, jatropha and rubber seed) and then ranked them in order of desirable property. No single biodiesel type could be found at top rank with reference to more than one property. With regards to viscosity, except rubber seed biodiesel, all other biodiesels (karanja, mahua, polonga, jatropha and koroch) fulfilled the ASTM D 6751 (1.9-6 cSt) as well as EN14214 (3.5-5) standards. Koroch biodiesel ranks 3rd, 3rd and 6th in case of kinematic viscosity, cetane number and calorific value amongst the biodiesel types considered for the present study. Cloud point of koroch, polanga, mahua, rubber, karanja and jatropha biodiesels are 4, 13.2, 5, 4, 12 and 4 °C. Further, properties of biodiesel were found to have influencing correlation with the fatty acid characteristics of the feedstock. Therefore, biodiesel with desirable properties could be expected form optimum mixing of different feedstock.Eleven number of different engine performance results pertaining to uses of biodiesel are also reviewed in this paper. Varying test conditions with reference to fuel types and blends, engine size and loading pattern are discussed. Engine performance results of koroch biodiesel were then compared with five similar tree-based biodiesel. It is observed that tree seed oil with more unsaturated fatty acids exhibits lower thermal efficiency compared to biodiesel having more saturated acids.     

Biodiesel production from jatropha oil (Jatropha curcas) with high free fatty acids: An optimized process

Response surface methodology (RSM) based on central composite rotatable design (CCRD) was used to optimize the three important reaction variables—methanol quantity (M), acid concentration (C) and reaction time (T) for reduction of free fatty acid (FFA) content of the oil to around 1% as compared to methanol quantity (M′) and reaction time (T′) and for carrying out transesterification of the pretreated oil. Using RSM, quadratic polynomial equations were obtained for predicting acid value and transesterification. Verification experiments confirmed the validity of both the predicted models. The optimum combination for reducing the FFA of Jatropha curcas oil from 14% to less than 1% was found to be 1.43% v/v H₂SO₄ acid catalyst, 0.28 v/v methanol-to-oil ratio and 88-min reaction time at a reaction temperature of 60 °C as compared to 0.16 v/v methanol-to-pretreated oil ratio and 24 min of reaction time at a reaction temperature of 60 °C for producing biodiesel. This process gave an average yield of biodiesel more than 99%. The fuel properties of jatropha biodiesel so obtained were found to be comparable to those of diesel and confirming to the American and European standards.     

Cyprinus carpio fish oil: A novel feedstock for biodiesel production

Biodiesel was developed from a novel nonedible oil source, namely Cyprinus carpio fish oil. The acid value of fish oil was very low (0.70 mg KOH/g oil, 0.35 free fatty acid content). As a result, biodiesel was produced through a one-step transesterifcation process, i.e. alkali-catalyzed transesterification with methanol. The optimal conditions for producing biodiesel from fish oil were investigated. The highest biodiesel yield (97.22% ~ 96.88% w/w ester content) was obtained under optimum conditions of 0.75% KOH w/w, 7:1 methanol to oil molar ratio, 60°C reaction temperature and 60-minute duration. Properties of the produced biodiesel as well as its blends with petro-diesel fulfilled the standard limits as prescribed by ASTM D6751 and EN 14214 indicating its suitability as a fuel for diesel engines.     

The utilization of waste egg and cockle shell as catalysts for biodiesel production from food processing waste oil using stirring and ultrasonic agitation

The use of calcined egg and cockle shell as heterogeneous solid catalysts for a transesterification reaction to produce biodiesel from food processing waste has been investigated in this work. The CaO catalysts were obtained from the calcination of egg and cockle shell and were characterized by surface analysis, X-ray diffractometry (XRD), and scanning electron microscopy (SEM). The experiments employed stirring and ultrasonic agitation, which proved to be a time-efficient approach for biodiesel production from food processing waste oil. A response surface methodology (RSM) was used to evaluate the effects of the process variables methanol to oil molar ratio, catalyst concentration, and reaction time on biodiesel production. The optimal % fatty acid methyl ester values obtained when using egg and cockle shells as catalysts were found to be 94.7% and 94.4% when the methanol to oil molar ratios were 9.3:1 and 8.5:1, egg and cockle shell catalyst mass fraction percentages were 3.8% and 3.5%, and reaction times were 47 and 44 min, respectively. The study has shown that ultrasonic agitation might be employed in a practical pilot reactor for biodiesel production.     

A comparative study of vegetable oil methyl esters (biodiesels)

In the present study, rubber seed oil, coconut oil and palm kernel oil, which are locally available especially in Kerala (India), are chosen and their transesterification processes have been investigated. The various process variables like temperature, catalyst concentration, amount of methanol and reaction time were optimized. Biodiesel from rubber seed oil (with high free fatty acid) was produced by employing two-step pretreatment process (acid esterification) to reduce acid value from 48 to 1.72 mg KOH/g with 0.40 and 0.35 v/v methanol-oil ratio and 1.0% v/v H₂SO₄ as catalyst at a temperature of 63(±2) °C with 1 h reaction time followed by transesterification using methanol-oil ratio of 0.30 v/v, 0.5 w/v KOH as alkaline catalyst at 55(±2) °C with 40 min reaction time to yield 98-99% biodiesel. Coconut oil and palm oil, being edible oils, transesterification with 0.25 v/v methanol-oil ratio, 0.50% w/v KOH as at 58(±2) °C, 20 min reaction time for coconut oil and 0.25% v/v methanol-oil ratio, 0.50% w/v KOH as alkaline catalyst at 60(±2) °C for palm kernel oil will convert them to 98-99% biodiesel. The brake thermal efficiency of palm oil biodiesel was higher with lower brake specific fuel consumption, but rubber seed oil biodiesel(ROB) showed less emission (CO and NO_x) compared to other biodiesels.