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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. General TermsArtificial Neural Networks, Engine Operation, ANN approaches to management of Engine operations, ANN algorithms, architecture

Conditioning monitoring is constantly helpful in scheduling maintenance activity and deciding the oil drain period for engines to ascertain the highest performance. Conditioning monitoring assures increased availability, higher design efficiency, and reduced maintenance cost. In the present work, experiments were performed on two identical singlecylinder engines by running them for 144 hours at a constant speed of 1500 rpm. The first engine was fueled with butanol blended fuel and the second with neat diesel fuel. Three samples of engine oil from each engine were collected after 48, 96, and 144 hours respectively. The engine oil (multigrade servo 20W-40) samples were examined to determine the condition of the engine by two methods: wear metal analysis; and physical and chemical tests. The wear metal analysis was monitored by the ICE 3000 series atomic absorption spectrometer. The viscosity was measured using the Anton Paar Rheolab QC rheometer at a constant speed of 1200 rpm and 40 C temperature and the total acid number was measured by the titration method. The metal wear, total acid number, and viscosity in the butanol-fueled engine were slightly greater than those of the diesel-fueled engine.

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