Performance, Combustion and Emission analysis of Sunflower oil based Biodiesel using Non-Dominated Sorting Genetic Algorithm-II

Year : 2023 | Volume : 01 | Issue : 01 | Page : 1-6

    Sunil Dhingra

  1. Assistant Professor, Department of Mechanical Engineering, University Institute of Engineering & Technology, Haryana, India


Biodiesel is used as alternate fuel of I. C. Engines for so many years. It is obtained from various edible and non-edible oils including waste cooking oils through trans-esterification process in the presence of catalyst. The suitable amount of biodiesel mix with commercial diesel can be used to run the compression ignition engines. The optimum combination of engine input parameters is the challenging task as required by the design engineer depending upon the output of the engine. The various
optimization techniques has been applied to engine for predicting optmum solutions such as OFAT approach, MOGA, RSM, Taguchi etc. Hence, this current research work applied the genetic algorithm for predicting optimum engine input parameters using sunflower oil based biodiesel. The statistical models are obtained from response surface methodology approach and these models are further used in design the ANN-GA program. The obtained program when run in MATLAB tool, multi solutions will be predicted. The validation of obtained solutions revealed the feasibility of the engine output parameters model.

Keywords: Genetic Algorithm, ANN, RSM, sunflower oil, Validation of Experiments

[This article belongs to International Journal of Energy and Thermal Applications(ijeta)]

How to cite this article: Sunil Dhingra Performance, Combustion and Emission analysis of Sunflower oil based Biodiesel using Non-Dominated Sorting Genetic Algorithm-II ijeta 2023; 01:1-6
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Regular Issue Subscription Review Article
Volume 01
Issue 01
Received July 1, 2023
Accepted July 5, 2023
Published July 17, 2023