Numerical Model for Calculating Compression Ignition Engine Performance

This paper presents a computationally efficient model of the working cycle for a compression ignition engine. Parameters of the model are identified on the basis of experimental measurements carried out for a CI engine with Common Rail system. The identification process is formulated as a dynamic optimisation task. Genetic algorithms are used in order to obtain the values of model parameters. Next, in order to generalize the results of identification, an approximation task was formulated and solved by using an artificial neural network. The paper shows an example of using the model to assess the influence of the kinetic combustion phase. Results obtained from the model in comparison with the validation measurements show that an acceptable accuracy of the model was achieved.