To establish an accurate fuel consumption prediction model of heavy-duty diesel vehicles, this paper firstly used the dataset collected by heavy-duty diesel vehicles in real road driving, and Pearson correlation coefficient to calculate the correlation between different factors and fuel consumption, then selected 7 factors with strong correlation with fuel consumption, and used Back Propagation (BP) neural network and Long Short-Term Memory (LSTM) neural network to establish fuel consumption prediction models for heavy-duty diesel vehicles. The prediction results of different driving sections show that the prediction accuracy of BP neural network for fuel consumption values in different road sections differs sharply, and the generalization of the model is low, while the prediction of different road sections of the LSTM model is very accurate, and the model generalization is strong.

Heavy-duty diesel vehicles  /  Fuel consumption prediction  /  Back Propagation (BP) neural network  /  Long Short-Term Memory (LSTM) neural network