Ann Based Prediction of Performance and Emission Characteristics of VCR Diesel Engine Fuelled with Biodiesel Blends

Due to the increasing demand for fossil fuels and environmental threat due to pollution a number renewable sources of energy have been studied worldwide. In the present investigation influence of injection timing on the performance and emissions of a single cylinder, four stroke stationary, variable compression ratio, diesel engine was studied using cottonseed oil (CSO) as the biodiesel blended with diesel. Experimental investigation on the Performance parameters and Exhaust emissions from the engine were done. Artificial neural networks (ANNs) were used to predict the engine performance and emission characteristics of the engine. Separate models were developed for performance parameters as well as emission characteristics. To train the network compression ratio, blend percentage, percentage load and injection timings were used as the input variables whereas engine performance parameters and engine exhaust emissions were used as the output variables. Experimental results were used to train ANN.