2014International Journal of Computer ApplicationsOpen access

Artificial Neural Networks for Internal Combustion Engine Performance and Emission Analysis

Anant BhaskarGarg, Parag Diwan, Mukesh Saxena

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Abstract

This paper presents an analytical work for better design system that contributes to the reduction of fuel consumption and emission for vehicle performance.The main technological issue on engines today is to comply with emission standards with cost-effective measures in order to keep the engine price still attractive to customer.The experimental research of engine performance are time consuming and quite expensive.The purpose of this work is to optimize engine performance using artificial neural networks (ANN).Back propagation neural network was used to optimize prediction model performance.The paper analyzed data from various experimental tests in which different engine operating parameters are measured.The paper highlights the framework and suitable model of ANN to optimize several operating parameters of the engine.The optimization includes a range of standards engine-operating conditions, with specified limits in emissions.

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What this paper is about

This paper presents an analytical work for better design system that contributes to the reduction of fuel consumption and emission for vehicle performance.The main technological issue on engines today is to comply with emission standards with cost-effective measures in order to keep the engine price still attractive to customer.The experimental research of engine performance are time consuming and quite expensive.The purpose of this work is to optimize engine performance using artificial neural networks (ANN).Back propagation neural network was used to optimize prediction model performance.The paper analyzed data from various experimental tests in which different engine operating parameters are measured.The paper highlights the framework and suitable model of ANN to optimize several operating parameters of the engine.The optimization includes a range of standards engine-operating conditions, with specified limits in emissions.

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Available abstract

This paper presents an analytical work for better design system that contributes to the reduction of fuel consumption and emission for vehicle performance.The main technological issue on engines today is to comply with emission standards with cost-effective measures in order to keep the engine price still attractive to customer.The experimental research of engine performance are time consuming and quite expensive.The purpose of this work is to optimize engine performance using artificial neural networks (ANN).Back propagation neural network was used to optimize prediction model performance.The paper analyzed data from various experimental tests in which different engine operating parameters are measured.The paper highlights the framework and suitable model of ANN to optimize several operating parameters of the engine.The optimization includes a range of standards engine-operating conditions, with specified limits in emissions.

Key concepts: Computer science, Artificial neural network, Internal combustion engine, Fuel efficiency, Range (aeronautics), Automotive engineering, Combustion, Work (physics)

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