INVESTIGATIONS ON THE EFFECT OF MAHUA BIOFUEL BLENDS AND LOAD ON PERFORMANCE AND NOX EMISSIONS OF DIESEL ENGINE USING RESPONSE SURFACE METHODOLOGY

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1 International Journal of Mechanical Engineering and Technology (IJMET) Volume 8, Issue 8, August 2017, pp , Article ID: IJMET_08_08_146 Available online at ISSN Print: and ISSN Online: IAEME Publication Scopus Indexed INVESTIGATIONS ON THE EFFECT OF MAHUA BIOFUEL BLENDS AND LOAD ON PERFORMANCE AND NOX EMISSIONS OF DIESEL ENGINE USING RESPONSE SURFACE METHODOLOGY V. Praveena, Venkatesan S, Ashwin Anand and Ronak M Jain Department of Mechanical Engineering, SRM University, Chennai, Tamilnadu, India ABSTRACT This paper aims at investigating the effect of parameters like load and blend on the performance and emission characteristics of a CI engine fueled with Mahua oil. By varying the two input parameters, the performance responses such as Brake thermal efficiency, Brake specific fuel consumption, exhaust gas temperature and emission responses such as NOx emissions were investigated. Though biodiesel helps in better fuel consumption due to enhanced CO 2, negative impact like increased NOx emissions occurs. Hence optimization of biofuel content is important. Optimization of these input variables were performed using Response Surface Methodology (RSM), a statistical tool in Design of Experiments(DoE). The desirability approach was used for this optimization. Experimental validation of the optimized results was done. The performance parameters for different Mahua oil blends were found near to diesel with a slight rise in NOx emissions. The RSM study revealed that at the optimum input parameters, the values of BTE, BSFC, EGT and NOx are 31%, 0.26kg/kW-hr, 348 C and 749 ppm respectively. The optimum input parameters for the blend with diesel are B20 and 4.32 kw. The interaction between the input parameters are best understood by this statistical tool. Keywords: emissions, Mahua, RSM, DoE Cite this Article: V. Praveena, Venkatesan S, Ashwin Anand and Ronak M Jain, Investigations on the Effect of Mahua Biofuel Blends and Load on Performance and Nox Emissions of Diesel Engine Using Response Surface Methodology, International Journal of Mechanical Engineering and Technology 8(8), 2017, pp INTRODUCTION Fossil fuels remain an important source of energy for all day to day applications. Also, the demand for these fuels increases based on our requirements. Hence alternate sources of energy like biomass fuels are gaining importance. Vegetable oils, non-edible oils and animal editor@iaeme.com

2 Investigations on the Effect of Mahua Biofuel Blends and Load on Performance and Nox Emissions of Diesel Engine Using Response Surface Methodology fats are experimented. Their properties vary based on the feedstock and their availability. Jatropha, Neem, Karanja and Mahua are the most commonly used non-edible type of oils. These oils cannot be used directly in diesel engines. They must be modified using methods like transesterification, emulsification, thermal cracking or pyrolysis [1-4]. Syed et al. studied the impact of high fuel injection pressure in a common rail direct injection diesel engine using Mahua methyl ester. They found that BSFC was reduced to 7.5% by raising the fuel injection pressure to 88 MPa. Also, the NOx emissions were decreased due to shortened ignition delay [5]. Sudheer Nandi et al. investigated the combustion characteristics of various blends of Mahua biodiesel. They noticed a significant drop in BSFC for B75 blend [6]. The effect of adding dimethyl carbonate Mahua biodiesel was studied and it was found that the brake thermal efficiency raised significantly with increased additives [7]. Najafi G et al. carried out response surface methodology study to find out the optimum combination of ethanol with gasoline blend for a petrol engine [8]. This paper deals with analysis of two parameters such as varying loads and blends in a CI engine. Various blends B10, B20 and B30 were used to understand the effect of load and blends on BTE and BSFC. The emission values of HC and CO were less compared to diesel except for NOx emissions. Response surface methodology helps in understanding the interaction between the independent parameters. Experiments are carried out to validate the optimum combination. The basic acid composition and properties of Mahua oil is given in Table 1. Table 1 Composition and properties of Mahua oil Types of fatty acid % Oleic acid 36.0 Palmitic acid 25.5 Stearic acid 22.6 Calorific value MJ/kWhr Cetane Number 34 Density g/cc EXPERIMENTAL SETUP AND PROCEDURE A single cylinder, four stroke, 4.4 kw, constant speed, air-cooled diesel engine is used to experimentally study the effect of different loads and blends on the performance and emission characteristics. Load is varied using an eddy current dynamometer. The specifications of the test engine are given in Table 2. Figure 1 Experimental set up editor@iaeme.com

3 V. Praveena, Venkatesan S, Ashwin Anand and Ronak M Jain Schematic representation of the experimental set-up is shown in Figure 1. Pressure built inside the combustion chamber for various crank angle positions are measured using AVL GH12D model piezoelectric pressure transducer and encoder. The resolution of AVL 364 angle encoder is 0.1_e1_ Crank angle. Interpretation of the P- diagram helps in calculating Heat release rate and ignition delay period. AVL 444 exhaust gas analyzer was used to measure HC, CO and NOx emissions. The engine was run for half an hour till the steady state was reached and then the readings were taken. Speed is maintained as constant and load was varied. Make Table 2 Specifications of the engine Kirloskar Engine Model TV1 No. of strokes 4 No. of cylinders 1 Bore and stroke 87.5 mm and 110 mm Compression ratio 17.5:1 Fuel injection timing 23 CA btdc Rated speed 1500 rpm Rated output 4.4 kw at 1500 rpm The range and accuracy of different measured parameters with instruments used are listed in Table 3. Table 3 Range and accuracy of different instruments Instruments Range Accuracy NOx ppm ± 5 ppm Pressure pick up bar ± Response surface Methodology (RSM) RSM is a statistical tool used to analyze the various parameters involved in a problem and arrive at an optimized solution for the response parameters. The steps followed in RSM are listed as below: 1. Selection of independent variables (load and blend) affecting the performance and emission characteristics of the engine. 2. The blends are varied as 0%, 10%, 20% and 30%. The loads are varied as 1 kw, kw, kw and 4.320kW respectively. 3. DoE helps in reducing the number of experiments. A design matrix is formed for the experimental runs. 4. The responses such as BSFC, BTE were evaluated and EGT, NOx was measured. 5. Minitab software was used to fit the experimental readings onto a second order polynomial equation. 6. Finally, desirability approach of RSM was used to get the optimal values of the input parameters editor@iaeme.com

4 Investigations on the Effect of Mahua Biofuel Blends and Load on Performance and Nox Emissions of Diesel Engine Using Response Surface Methodology 3. RESULTS AND DISCUSSION 3.1. Analysis of the model Analysis of Variance (ANNOVA) is a statistical tool used to find out the most significant factors and to measure the effect of those factors on the responses. The probability p-value of less than 0.05 is chosen as the reference limit. The quadratic model developed for the responses are given in equations (1) (4) (1) (2) (3) (4) 3.2. Evaluation of the model The difference between the predicted R 2 and adjusted R 2 is less than 0.2. This shows the perfectness in predicting the results of new observations. Table 4 and 5 shows that the data is fitted by the model well. Table 4 Analysis of Variance for responses (Values of P) Source BP(kW) BTE (%) Table 5 Model evaluation BSFC(kg/kWh) EGT( C) NO x Mean Std. Deviation Model Degree Quadratic Quadratic Quadratic Quadratic Quadratic R Adj. R Pred. R Interactive effect of Mahua oil blends and loads The response surface plot between bends and loads on BTE is shown in Figure. It is evident that as the blend increases, the Brake thermal efficiency decreases. Though the oxygen editor@iaeme.com

5 V. Praveena, Venkatesan S, Ashwin Anand and Ronak M Jain content is high in the fuel, its viscosity and volatility leads to poor combustion characteristics. RSM analysis shows that 30% blend at 4.32 kw gives BTE of 31%. Figure 2 Interactive effect of blend and load on BTE Variation of BSFC for various loads and blends are shown in Figure. At the rated load condition of 4.32 kw, BSFC increases with increase in blend. This is attributed to the lower calorific value of Mahua oil. BSFC of 0.19 kg/kw-hr is achieved from B20 blend through RSM analysis. Figure 3 Interactive effect of blend and load on BSFC Figure 4 shows the surface plot between load and blend on EGT. Minimum EGT of 273 C is attained at B20 through RSM analysis. EGT increases as the blend increases. This is due to the volatility and viscosity of the oil. Figure 4 Interactive effect of blend and load on EGT editor@iaeme.com

6 Investigations on the Effect of Mahua Biofuel Blends and Load on Performance and Nox Emissions of Diesel Engine Using Response Surface Methodology Figure 5 shows the response surface plot between load and blend on NOx emissions. There is an increase in NOx as the blend increases. By RSM analysis, the optimum value of NOx is 788 ppm. The emission levels show a trend similar to that of diesel but are relatively higher at all loads Figure 5 Interactive effect of blend and load on NOx emissions 3.4. Optimization The desirability approach was used in attaining the best solution. The solution that possess the highest desirability was selected. The optimization is met based on the limits and weightages given in Table 6 Table 2 Optimization criteria of emission and performance parameters Constraints Target Lower limit Upper limit Weight ( Lower) Weight (Upper) Importance Fuel In range B0 B Load In range NOx Minimize BSFC Minimize EGT Minimize BTE Maximize Validation of optimized results To validate the optimized results, experimental runs were carried thrice at the optimum blend and load. Table 7 shows that the experimental results were in close agreement with the predicted values. The error in predicted values were less than 2%. Table 3: Validation of test results Blend Load BTE BSFC EGT NOx Predicted Actual % Error editor@iaeme.com

7 V. Praveena, Venkatesan S, Ashwin Anand and Ronak M Jain 4. CONCLUSIONS RSM statistical tool used in this paper for analyzing the effect of load and blend helped in optimizing the performance and emission parameters of Mahua oil fuelled diesel engine. DoE helps in forming statistically feasible model with less number of experiments. BTE decreases with increase in blend. A desirability of 0.91 was obtained at 20% Mahua oil blend and 4.32 kw of load. The responses of the optimum blend are 31% BTE, 0.26 kg/kw hr, BSFC, 348 C EGT and 749 ppm NOx respectively. Validation of results proved the accuracy of the developed models. REFERENCES [1] B. Rajesh Kumar, S. Saravanan, D. Rana, A. Nagendran, Combined effect of injection timing and exhaust gas recirculation (EGR) on performance and emissions of a DI diesel engine fuelled with next generation advanced biofuel diesel blends using response surface methodology, Energy Conversion and Management 123,2016,pp [2] S. Nigade,S. Mutalikdesai, Optimization of Transesterification Process Using Homogeneous and Heterogeneous Catalysts for Madhuca Indica Biodiesel Derived from Triglycerides of Madhuca Indica Kernel Oil, SAE Technical Paper,DOI: / [3] V. Praveena, M. Leenus Jesu Martin (2017), A review on various after treatment techniques to reduce NOx emissions in a CI engine, Journal of the Energy Institute, 2017, ISSN , [4] Aydin HS, Bayindir H, (2010) Performance and emission analysis of cottonseed oil methyl ester in a diesel engine. Renew Energy 2010; 35:pp [5] C. Syed Aalam, C.G. Saravanan, B. Prem Anand, Impact of high fuel injection pressure on the characteristics of CRDI diesel engine powered by mahua methyl ester blend, Applied Thermal Engineering, Volume 106, 2016, pp [6] Sudheer nandi, Performance of C.I Engine by Using Biodiesel-Mahua Oil, American Journal of Engineering Research (AJER), Volume-02, Issue-10, pp [7] Swarup Kumar Nayaka, Bhabani Prasanna Pattanaika, Experimental Investigation on Performance and Emission Characteristics of a Diesel Engine Fuelled with Mahua Biodiesel Using Additive, Energy Procedia 54,2014, pp [8] Gholamhassan Najafi, Barat Ghobadian et al, Optimization of performance and exhaust emission parameters of a SI (spark ignition) engine with gasoline ethanol blended fuels using response surface methodology, Energy, Volume 90, 2015, pp [9] A.V.Krishna C Investigation On Variable Compression Ratio Diesel Engine Fuelled With Mahua Oil and Diesel Blends, International Journal of Civil Engineering and Technology 2017, pp [10] K. Sandeep Kumar, NEC Prasad and P. Bridjesh. Effect of Mahua Oil Methyl Ester with Additive as an IC Engine Fuel in Combination with Diesel in CI Engine: An Experimental Investigation. International Journal of Mechanical Engineering and Technology, 8(5), 2017, pp [11] Ravinder Kumar and Navdeep Sharma Dugala, Exhaust Gas Analysis and Temperature Effect of Mahua Oil Bio-Diesel on Single Cylinder Diesel Engine, International Journal of Mechanical Engineering and Technology, 8(7), 2017, pp editor@iaeme.com

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