Parametric Optimization of Single Cylinder Ci Engine Fuel with Diesel-Waste Plastic Oil Blend Using Diffuser at Intake Manifold |
Author(s): |
Dr. Kiran Patel , LDRP-ITR, KSV, Gandhinagar; Shaishav Shah, LDRP-ITR, KSV, Gandhinagar; Pragna Patel, LDRP-ITR, KSV, Gandhinagar; Dr. Saumil Patel, LDRP-ITR, KSV, Gandhinagar |
Keywords: |
Diesel, Biodiesel, Engine Performance, Taguchi's Method |
Abstract |
In this study, a Taguchi's method is used to determine the optimal combinations of diffuser, compression ratio, injection pressure, blend ratio and load of a diesel engine fueled with diesel-biodiesel blend. The previous researchers had done research on combined effect of compression ratio and blend ratio but in this research. Experiments has been carried out using various sets of parameters like diffuser at intake manifold, compression ratio, injection pressure and engine output. The optimum results for selected responses are achieved with optimum sets of parameters. Peak pressure of the cylinder is also measured and optimized within all set of experiments. These experiments are carried out with and without diffuser at intake manifold. The optimum set achieved from experiments for SFC is without use of diffuser at intake manifold, 17 compression ratio, 0D100B blend, low injection pressure (160 bar) at 12 kg of load. The optimum set achieved from experiment for Brake Thermal Efficiency from experiments is without use of diffuser at intake manifold, 17 compression ratio, 0D100B blend, low injection pressure (160 bar) at 12 kg of load. The optimum set achieved from experiment for peak pressure from experiments is without use of diffuser at intake manifold, 16 compression ratio, 50D50B blend, low injection pressure (160 bar) at 12 kg of load. At the end, the experiments are carried out using optimum set of parameters in order to validate the optimum predicted results. Experiment results shows that predicted values by Taguchi's method are closer to the experiment values. Taguchi's method gives accurate results with less number of experiments. |
Other Details |
Paper ID: LDRPTCP012 Published in: Conference 12 : LDRP TECON23 Publication Date: 23/12/2023 Page(s): 56-66 |
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