Date of Publication :22nd February 2018

Abstract: Increasing demand for limited natural resources is leading to a situation of the global energy crisis. Energy consumption patterns have to be changed in order to face the energy crisis and more focus has to be brought on utilizing the renewable energy resources. Major challenges faced in the implementation of renewable energy resources include the development of technology with ensured commercial viability and awareness on environmental concerns. Exhaust emissions from the diesel engines are found to be toxic and carcinogenic in nature. Artificial intelligence techniques can be applied as an effective method for attaining the future goals of renewable energy and also for the prediction of exhaust emission characteristics from compression ignition engines. Artificial Neural Network is a proven technique in modelling of nitrate and soot emissions from the diesel engines and acts as an alternative for real-time experimentation which is time-consuming and expensive. In this paper, a detailed study has been carried out on the application of single and hybrid artificial intelligence approaches in the research and development of renewable energy resources. Also, the effectiveness of Artificial Neural Network (ANN) technique in the prediction of diesel engine exhaust emissions has been reviewed.

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