The invention discloses an electronic injection
fuel injection strategy intelligent optimization method based on
deep learning, and the method comprises the following steps: S1, collecting and preprocessing multi-source working condition data of an engine, and generating a standard
data set; s2, constructing a Bayesian neural
network model, and outputting an integrated
fuel injection parameter prediction value and an
uncertainty estimation value; s3, optimizing model structure parameters and hyper-parameters by using an
ant lion optimization
algorithm to obtain an optimal structure and parameters; s4, training the model by using the optimal structure and parameters, and performing performance evaluation by using a standard
data set; s5, collecting working condition data in real time, and outputting an optimal integrated
fuel injection parameter prediction value and an
uncertainty estimation value; and S6, periodically collecting feedback data, training the model in combination with the standard
data set increment, and re-executing
ant lion optimization in good time. According to the method, high-precision intelligent optimization of the oil injection strategy of the engine is achieved, the fuel economy is improved, emission is reduced, and the self-
adaptive capacity under the complex working condition is enhanced.