With the rapid development of electric vehicles (EVs), the need for intelligent systems to manage their collective behavior and interaction with the grid has become critical. An electric vehicle aggregation model based on integrated clustering is proposed. The model can group electric vehicles with similar charge and discharge modes to achieve efficient grid interactive aggregation. In addition, the response capability and characteristics of EVs were determined and quantified by combining the classified and aggregated EV charging load data set, and the multi-dimensional characteristics of EVs as flexible and adjustable resources were utilized to predict the response potential of the aggregated EV fleet and promote its optimal access to the network. This research contributes to the advancement of smart grid technology and the seamless integration of electric vehicles into the future energy landscape.