The invention discloses a method for predicting spraying characteristics of an
internal combustion engine. The method comprises the following steps: establishing an
original data set comprising data of working condition parameters and data of spraying characteristic parameters; calculating the deviation between the measured value and the calculated value of the existing spray characteristic formula, and correcting the existing spray characteristic formula; constructing a physical constraint
system of spraying characteristics; extrapolating and expanding by adopting a
Gaussian process regression method; performing interpolation enhancement by adopting a
generative adversarial network; constructing a spray prediction model through
deep learning; according to the method, an existing spraying characteristic formula is corrected through the deviation value, and the
data expansion accuracy is improved; the limitation of
small sample experimental data is effectively solved through data enhancement,
Gaussian process regression extrapolation with priori knowledge is utilized to expand and cover limit working conditions, a correction formula and physical constraints are added into a
generative adversarial network, details are further complemented, data breakpoints are eliminated, and a high-
quality data set is constructed. And the generalization ability, the prediction precision and the physical rationality of the
deep learning model are improved.