In view of the problem that charging facilities in intelligent park cannot meet the development demand of electric vehicles, a modeling and analysis method suitable for orderly shared charging demand of electric vehicles in intelligent park is proposed. Charging plans are provided by analyzing charging data, and orderly charging strategies are formulated in the energy management system of the park. Power spectral density estimation method using statistical analysis of single EV charging current, and complete EV on-line identification in artificial intelligence network classification work, based on the correlation between insertion time, energy, and working day statistical analysis each EV charging habits, the grid side current is measured using to predict the charging demand, based on kernel density estimate charging demand statistics model is set up. The validity and applicability of the model are verified by the actual data collected from a charging facility in a residential area, which can provide help for EV charging in the intelligent park.