The study of charging choice for electric vehicle holds significant importance for the promotion of new energy vehicles, the realization of energy saving and emission reduction. Based on one month's global positioning system data of electric vehicles, this study segments the daily usage behaviors of electric vehicles. It identifies the starting and ending points of trips and extracts the instantaneous state information of vehicles at trip endpoints. This information is used as independent variables for electric vehicle charging choice, with the presence of charging at trip endpoints as the dependent variable. A binary Logit model is employed to establish a model analyzing the charging choice behavior at the endpoints of electric vehicle trips. The model's parameters are then estimated and tested. The results indicate that the state of charge, cumulative mileage, and time significantly impact the charging choice of electric vehicle at trip endpoints.