Energy Consumption Analysis of New Energy Vehicles Based on Computer Simulation and Intelligent Data Layering

In this paper, based on the high-frequency big data of new energy collected by the vehicle-mounted terminal, the data is intelligently layered, and the characteristic parameter set that can reflect the fine spatio-temporal changes of driving behavior is extracted. The characteristic parameter set is optimized by computer simulation method, and K-means is used. The algorithm realizes the automatic classification of driving behavior, and analyzes the energy consumption distribution of different levels of driving behavior. The analysis results show that driving behavior affects the level of energy consumption of new energy vehicles, of which the energy consumption corresponding to smooth driving is lower. The results show that the energy consumption of new energy vehicles is 12% lower than that of traditional vehicles.