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Estimation of operational parameters for a direct injection turbocharged spark ignition engine by using regression analysis and artificial neural network

Erdi Tosun, Kadir Aydin, Simona Silvia Merola, Adrian Irimescu
Published: 1 January 2017
Thermal Science , Volume 21, pp 401-412; doi:10.2298/tsci160302151t

Abstract: This study was aimed at estimating the variation of several engine control parameters within the rotational speed-load map, using regression analysis and artificial neural network (ANN) techniques. Duration of injection, specific fuel consumption, exhaust gas temperature before turbine and within the catalytic converter brick were chosen as the output parameters for the models, while engine speed and brake mean effective pressure were selected as independent variables for prediction. Measurements were performed on a turbocharged direct injection spark ignition engine fueled with gasoline. A three-layer feed-forward structure and back-propagation algorithm was used for the training the ANN. It was concluded that this technique is capable of predicting engine parameters with more accuracy than linear and non-linear regression techniques.
Keywords: Turbocharged Disi Engine / regression analysis / artificial neural network / estimation

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