The Analysis of Electrical Vehicles Charging Behavior Based on Charging Big Data

Electric Vehicles (EVs) play an important role in resource conservation and environmental protection, therefore have attracted a great deal of attention from both enterprises and governments. Understanding charging behavior of EV users means a lot for improvement of charging service and promotion of EVs. The charging management platform that provides service for EV users has accumulated a large volume of charging data, from which we can explore the charging behavior of EV users. In this paper, two classical data analysis algorithms are adopted for that purpose. K-means algorithm is applied to clustering users, then all categories are analyzed in detail. The other algorithm is Apriori used for the study of the effects of weather and holidays on users' charging. Moreover, we analyze the charging characteristics in three typical regions and the relationship between temperatures and charging using statistical methods, finally provide some marketing suggestions respectively.