Open Access Open Access  Restricted Access Subscription or Fee Access

Problem formulation for predicting optimum trans-esterification process parameters of biodiesel production and their performance analysis in diesel engine

Sunil Dhingra

Abstract


The various alternate fuels have been used in the past research to run the compression ignition engines. One of the fuel is the biodiesel which is used in the blended form with diesel. The emission parameters are reduced to 30-40% and the performance parameters are increased to some extent. This paper represents the various past research related to biodiesel based engines. The various steps in predicting the optimum process parameters of biodiesel production and their performance analysis using various statistical techniques like RSM, hybrid techniques of RSM-NSGA-II are applied in formulating the problem. The response surface methodology based on CCRD is used for planning the experimentation and statistical model is then used in ANN’s and GA’s. It has been observed from the research papers that the hybrid techniques RSM-GA/ANN-GA is better as compared to other technique like taguchi, RSM etc

Keywords


Formulation of problem, RSM, ANN-NSGA-II, RSM-GA, Optimization, Validation of Experiments

Full Text:

PDF

References


Ramdhas, A. S., Muraleedharan, C. and Jayaraj, S., (2005), “Performance and emission evaluation of a diesel engine fuelled with methyl esters of rubber seed oil”, Renewable Energy, Vol. 20, pp. 1-12.

Jindal, S. and Salvi, B. L., (2012), “Sustainability aspects and optimization of linseed biodiesel blends for compression gnition engine”, Journal of Renewable and Sustainable Energy, Vol. 4, 043111, DOI: 10.1063/1.4737922.

Lin, G. H. and Kuo, C. P., (2013), “Effects of the injection timing on the engine performance and the exhaust emissions of a diesel engine fuelled by tyre-pyrolysis oil-diesel blends”, Proceedings of institution of Mechanical Engineers, part D: Journal of Automobile Engineering, DOI: 10.1177/0954407013478397.

Deb, K. and Agarwal, R. B., (1995), “Simulated Binary Crossover for Continuous Search Space”, Complex Systems, Vol. 9, pp. 115-148.

Raghuwanshi, M. M. and Kakde, O. G., (2004), “Survey on multi-objective evolutionary and real coded genetic algorithms”, Proceedings of the 8th Asia Paci¯c Symposium on Intelligent and Evolutionary Systems, pp. 150-161.

Beyer, H. G. and Deb, K., (2001), “On Self-Adaptive Features in Real-Parameter Evolutionary Algorithm. IEEE Transactions on Evolutionary Computation, Vol. 5, No. 3, pp. 250-270.

Srinivas, N. and Deb, K., (1994), “Multi-objective Optimization Using Non-dominated Sorting in Genetic Algorithms”, Evolutionary Computation, Vol. 2, No. 3, pp. 221-248.

Deb, K., Pratap, A., Agarwal, S. and Meyarivan, T. A., (2002), “Fast Elitist Multi- objective Genetic Algorithm: NSGA-II”, IEEE Transactions on Evolutionary Computation, Vol. 6, No. 2, pp. 182-197.

Garg, M. P., Jain, A. and Bhushan, G., (2012), “Modelling and multi-objective optimization of process parameters of wire electrical discharge machining using non-dominated sorting genetic algorithm-II”, Proceedings of Institution of Mechanical Engineers, Part B: Journal of Engineering and Manufacture, DOI: 10.1177/0954405412462778.

M.N. Nabi, J.E. Hustad, M.A. Aren, The influence of Fischer–Tropsch-biodiesel–diesel blends on energy and exergy parameters in a six-cylinder turbocharged diesel engine, Energy Reports 6 (2020) 832–840.




DOI: https://doi.org/10.37591/joaea.v10i1.7087

Refbacks

  • There are currently no refbacks.