Engineering Science and Technology, an International Journal (Jun 2016)

Exploration of waste cooking oil methyl esters (WCOME) as fuel in compression ignition engines: A critical review

  • S. Kathirvel,
  • Apurba Layek,
  • S. Muthuraman

DOI
https://doi.org/10.1016/j.jestch.2016.01.007
Journal volume & issue
Vol. 19, no. 2
pp. 1018 – 1026

Abstract

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The ever growing human population and the corresponding economic development of mankind have caused a relentless surge in the energy demand of the world. The fast diminishing fossil fuel reserves and the overdependence of petroleum based fuels have already prompted the world to look for alternate sources of energy to offset the fuel crisis in the future. Waste Cooking Oil Methyl Ester (WCOME) has proven itself as a viable alternate fuel that can be used in Compression Ignition (CI) engines due to its low cost, non-toxicity, biodegradability and renewable nature. It also contributes a minimum amount of net greenhouse gases, such as CO2, SO2 and NO emissions to the atmosphere. The main objective of this paper is to focus on the study of the performance, combustion and emission parameters of CI engines using WCOME and to explore the possibility of utilizing WCOME blends with diesel extensively in place of diesel. The production methods used for transesterification play a vital role in the physiochemical properties of the methyl esters produced. Various production intensification technologies such as hydrodynamic cavitation and ultrasonic cavitation were employed to improve the yield of the methyl esters during transesterification. This review includes the study of WCOME from different origins in various types of diesel engines. Most of the studies comply with the decrease in carbon monoxide (CO) emissions and the increase in brake thermal efficiency while using WCOME in CI engines. Many researchers reported slight increase in the emissions of oxides of nitrogen. ANN modeling has been widely used to predict the process variables of the diesel engine while using WCOME. The versatility of ANN modeling was proven by the minimum error percentages of the actual and predicted values of the performance and emission characteristics.

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