Multi-source information fusion applied in EV´s intelligent integrated station

While EVs partially rely on electricity from the power grid, they have the potential to be used as generation resources to provide energy and ancillary services into the grid. But the existing EVs´ charge and exchange system has significant room for improvement through automation and information management, condition monitoring, and battery management, especially on the grid-connected control system. Therefore, a novel EV´s intelligent integrated station (IIS) including bidirectional converters, exchange system, cascaded system and dispatch center, is proposed in this paper to pave the way for a more sustainable power grid. In this paper, we explore both the battery management system (BMS) and control strategy of grid-connection based on the technique of multi-source information fusion, focusing first on batteries information in IIS and then on operational information of power grid from energy management system (EMS). Based on the information in control center received from BMS and EMS, an effort is made to develop a novel control strategy of grid-connection to well take into account of the operational state of power grid and battery energy level of IIS, and further to improve the efficiency of power/energy flow between IIS and power grid. Moreover, an algorithm for power flow estimation between IIS and power grid based on Kalman filtering theory is proposed to get accurate information. Actual operation results indicate that the proposed system is an ideal power interface for EVs and power networks.