Abstract
This paper presents a study on the performance of different modelling techniques for engine response models. The work focuses on modelling Diesel engine response features including fuel flow, noise and emissions. Models included in the study are cubic polynomials, radial basis function and Gaussian kriging. The main conclusion drawn from the study is that Gaussian kriging performs consistently well across all engine responses, and generally outperforms the RBFs. On this basis it can be recommended as a preferred tool for modelling local Diesel engine responses.
Keywords: Model Based Calibration, Engine Response Features, Radial Basis Functions, Gaussian Kriging