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Emissions Prediction of Cashew Nut Shell Liquid Biodiesel Using Machine Learning

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Abstract

Biodiesel is a type of alternative diesel fuel made from transesterification vegetable or animal oils. It is used in ignition engines for locomotives, heat generation, stationary power, and aviation fuels. Cashew nut shell liquid (CNSL) biodiesel is blended with diesel in different ratios to study the behavior of diesel engines against different environment emissions parameters such as carbon dioxide (CO2), carbon monoxide (CO), hydrocarbons (HC), nitrogen oxides (NOx), and smoke. The performance of the diesel emission parameters is assessed using machine learning based on multiple linear regression, artificial neural networks (ANN), and random forest regression models.

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Acknowledgements

Thanks go to Vijay Kumar Chhibber (Ex-Scientist, IIP, Dehradun) and Ajay Singh (Uttaranchal University) for evaluating the work.

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Authors and Affiliations

  1. Department of Chemistry, Uttarakhand Technical University, Dehradun, India

    Deepak Kumar

  2. Indian School of Petroleum (IIP), Dehradun & Dean Baba Farid Institute of Technology, Dehradun, India

    Vijay Kumar Chhibber

  3. Department of Chemistry, Uttaranchal University, Dehradun, India

    Ajay Singh

Authors
  1. Deepak Kumar
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  2. Vijay Kumar Chhibber
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  3. Ajay Singh
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Correspondence to Deepak Kumar.

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Significance statement: The blended biodiesels affect the performance of the diesel engine. In comparison with typical 2005 petroleum diesel fuel, biodiesel reduces greenhouse gas emissions by 76.4 percent over its lifetime. The emission characteristics in diesel engines can be analyzed and evaluated using artificial intelligence and machine-learning techniques.

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Kumar, D., Chhibber, V.K. & Singh, A. Emissions Prediction of Cashew Nut Shell Liquid Biodiesel Using Machine Learning. Natl. Acad. Sci. Lett. 45, 397–400 (2022). https://doi.org/10.1007/s40009-022-01142-6

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  • DOI: https://doi.org/10.1007/s40009-022-01142-6

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