Predicting the Engine Performance and Exhaust Emissions of a Diesel Engine Fueled With Hazelnut Oil Methyl Ester: The Performance Comparison of Response Surface Methodology and LSSVM

2016 ◽  
Vol 138 (5) ◽  
Author(s):  
Nadir Yilmaz ◽  
Erol Ileri ◽  
Alpaslan Atmanlı ◽  
A. Deniz Karaoglan ◽  
Umut Okkan ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Diesel Engine ◽  
Methyl Ester ◽  
Response Surface ◽  
Fuel Injection ◽  
Engine Performance ◽  
Experimental Results ◽  
Hazelnut Oil ◽  
Injection Timing ◽  
Fuel Injection Timing

An experimental investigation was conducted to evaluate the suitability of hazelnut oil methyl ester (HOME) for engine performance and exhaust emissions responses of a turbocharged direct injection (TDI) diesel engine. HOME was tested at full load with various engine speeds by changing fuel injection timing (12, 15, and 18 deg CA) in a TDI diesel engine. Response surface methodology (RSM) and least-squares support vector machine (LSSVM) were used for modeling the relations between the engine performance and exhaust emission parameters, which are the measured responses and factors such as fuel injection timing (t) and engine speed (n) parameters as the controllable input variables. For this purpose, RSM and LSSVM models from experimental results were constructed for each response, namely, brake power, brake-specific fuel consumption (BSFC), brake thermal efficiency (BTE), exhaust gas temperature (EGT), oxides of nitrogen (NOx), carbon dioxide (CO2), carbon monoxide (CO), and smoke opacity (N), which are affected by the factors t and n. The results of RSM and LSSVM were compared with the observed experimental results. These results showed that RSM and LSSVM were effective modeling methods with high accuracy for these types of cases. Also, the prediction performance of LSSVM was slightly better than that of RSM.

Parameter optimization of a diesel engine to reduce noise, fuel consumption, and exhaust emissions using response surface methodology

2005 ◽  
Vol 219 (10) ◽  
pp. 1181-1192 ◽  
Author(s):  
Z Win ◽  
R P Gakkhar ◽  
S C Jain ◽  
M Bhattacharya
Keyword(s):  
Response Surface Methodology ◽  
Diesel Engine ◽  
Response Surface ◽  
Fuel Consumption ◽  
Parameter Optimization ◽  
Direct Injection ◽  
Engine Performance ◽  
Optimization Techniques ◽  
Injection Timing ◽  
Test Engine

The conflicting effects of the operating parameters and the injection parameter (injection timing) on engine performance and environmental pollution factors is studied in this paper. As an optimization objective, a 3.5 kW small direct injection diesel engine was used as the test engine, and its speed, load, and static injection timing were varied as per 4 × 4 × 3 full factorial design array. Radiated engine noise, smoke level, brake specific fuel consumption, and emissions of unburned hydrocarbons and nitrogen oxides were captured for all test runs. Objective functions relating input and output parameters were obtained using response surface methodology (RSM). Parameter optimization was carried out to control output responses under their mean limit using multi-objective goal programming and minimax programming optimization techniques.

Performance Analysis of Diesel Engine Using Bio Ethanol (Water Hyacinth) by Response Surface Methodology (RSM)

2015 ◽  
Vol 737 ◽  
pp. 53-59
Author(s):  
Akhilesh Kumar Choudhary ◽  
H. Chelladurai ◽  
C. Kannan
Keyword(s):  
Response Surface Methodology ◽  
Diesel Engine ◽  
Response Surface ◽  
Water Hyacinth ◽  
Alternative Fuels ◽  
Fuel Injection ◽  
Engine Performance ◽  
Injection Pressure ◽  
Performance And Emission ◽  
Brake Mean Effective Pressure

In current years, many researches have been worked to find new sources of alternative fuels. In this situation, the water hyacinth will be a new source for bioethanol. In this study, bioethanol extracted from water hyacinth is blended with diesel (5-BED, 5% bioethanol and 95% diesel v/v) and has been used to experimentally investigate the diesel engine performance and emission. The response surface methodology (RSM) technique with three engine operating variables like (i) Load, (ii) Compression ratio (CR) and (iii) Fuel Injection pressure (FIP) has been implemented to evaluate diesel engine performance using bioethanol diesel blend. The equations were obtained for Brake power (BP), Brake mean effective pressure (BMEP), Brake thermal efficiency (BTHE), and NO emission by using quadratic polynomial

Effect of process parameters on the diesel engine performance fuelled with Prosopis juliflora biodiesel response surface methodology approach

2021 ◽  
pp. 095440892110430
Author(s):  
Abhishek Sharma ◽  
Avdhesh Tyagi ◽  
Yashvir Singh ◽  
Nishant K Singh ◽  
Navneet K Pandey
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Fuel Injection ◽  
Engine Performance ◽  
Injection Pressure ◽  
Prosopis Juliflora ◽  
Injection Timing ◽  
Gas Temperature ◽  
Input Parameters ◽  
Fuel Injection Pressure

The rapid consumption of crude oil and resulting pollution are very severe problems in modern energy sectors. To meet these global problems, biodiesels obtained from non-edible plants can play a very crucial role. Keeping this idea in mind the present study focuses on making some efforts for the best utilization of innovative blends of Prosopis juliflora biodiesel in the operation of diesel engines. Four engine input parameters viz. fuel injection pressure (16–24 MPa), P. Juliflora biodiesel blends (0–10%), shaft loads (20–100%) and injection timing (15–31°bTDC (before top dead centre)) are selected for optimization process. The experiments were executed in accordance with response surface methodology. The results of the experiments revealed that the optimum combination for engine input parameters were at fuel injection timing 30°bTDC, fuel injection pressure 22 MPa, 4% P. juliflora biodiesel blending at 59% of engine load to achieve best performance. The individual desirability of brake thermal efficiency, brake specific fuel consumption, exhaust gas temperature and peak cylinder pressure were found to be 0.888, 0.949, 0.624 and 0.749, respectively, and the composite desirability of engine responses was found to be 0.7923 which makes the results acceptable.

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