Prediction of Fuel Consumption of Heavy Commercial Vehicles Based on Random Forest

Abstract

In order to explore the relationship between the operating parameters and fuel consumption of heavy commercial vehicles. In this paper, the fuel consumption is predicted based on the data collected from a heavy commercial vehicle T-BOX. Build a fuel consumption prediction model based on random forest (RF), and optimize the grid parameters of the random forest fuel consumption model. The results show that the MSE, MAE, and R2 coefficients of the random forest fuel consumption prediction model are 0.0016, 0.1717, and 0.9969, respectively, and the prediction accuracy is higher than that of the LSTM neural network fuel consumption prediction model, which can provide a certain theoretical basis for subsequent research on the fuel consumption of heavy commercial vehicles. Show more