Cetane number is one of the indispensable parameters in the study and selection of fuels for CI engines. Hence it is an important criterion for selection of bio-diesels, which exhibit a wide variety of characteristics based upon their source, method of preparation etc. Since the conventional techniques for evaluating cetane number are tedious, alternate methods are being developed. This paper attempts to find cetane number based on the properties of the bio-diesel so that cetane number can be found without operating an engine. If a correlation between fuel properties and cetane number is established, the influence of each of the fuel properties on cetane number can be analyzed. This paper uses artificial neural networks (ANNs), which are a recently developed computational technique used to correlate non-linear data, to predict cetane number and analyze the influence of the various fuel properties namely density, viscosity, flash and fire points on the cetane number of a bio-diesel and its various blends.Oils produced from seeds of Sunflower, Palm, Pungam plant (Honge) and their Methyl Esters are used for this analysis. Standard diesels with known cetane numbers are used. The fuel properties are found by standard techniques. Different combinations of ANNs are formed by varying the number of hidden layer neurons, activation functions and other network parameters and are trained to predict cetane number from fuel properties using a series of train data. The networks so formed are validated using a series of test data. The best network is chosen based on the least value of mean squared error. By analyzing the weight matrix of the trained network, the relative impacts of the properties on the cetane number are analyzed. It is hoped that this work would aid in the selection of the suitable source and method of preparation to obtain the bio-diesel with the desired physical properties so that optimal cetane number is achieved.


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    Titel :

    Prediction of Cetane Number of a Biodiesel Based on Physical Properties and a Study of Their Influence on Cetane Number


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:

    Kongress:

    2007 Fuels and Emissions Conference ; 2007



    Erscheinungsdatum :

    23.01.2007




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch





    Prediction of Cetane Number of a Biodiesel Based on Physical Properties and a Study of Their Influence on Cetane Number

    Suryanarayanan, S. / Janakiraman, V. M. / Sekar, J. et al. | British Library Conference Proceedings | 2007


    NRCC Cetane Index – 1: An Improved Cetane Number Predictor

    Burton, Gordon F. / Whyte, Robert B. / Gülder, Ömer L. | SAE Technical Papers | 1986


    Empirical approach for predicting the cetane number of biodiesel

    Bose, P. K. | British Library Online Contents | 2009


    DIESEL COMBUSTION CETANE NUMBER EFFECTS

    Lenane, D. L. / Olree, R. M. | SAE Technical Papers | 1984