Abstract: Example embodiments provide improved dynamic load management for an electric vehicle charging system. A cloud-based apparatus is configured to adjust maximum current ratings of charging stations when one or more charging stations drop offline based on a latest accepted request for maximum charging current of the offline charging station. An apparatus, a method, and a computer program are disclosed.

Abstract: An arrangement for managing electric vehicle charging stations comprises an arrangement for receiving an encrypted identification code of a charging station from one of the two routes for receiving the identification code. The first route comprises using a generic reader software and a browser and the second route comprises using a specific application. Then the identification code and the selected route are used to route a workflow in order to start a charging session or other charging station workflow.

Abstract: The present disclosure relates generally to electric vehicles, and more specifically to methods, apparatuses, and computer program products for requesting user authorization for electric vehicle charging sessions and responding to the requested user authorization. The methods, apparatuses, and computer program products described herein allow a user of an EV to use his/her single already-existing physical electronic key in order for him/her to be authorized for EV charging sessions at EV charging stations of different charging service providers. By so doing, it is possible to avoid the need to produce and mail new physical electronic keys each intended to be used at the EV charging stations of a different charging service provider, thereby significantly reducing the time of the user authorization.

Abstract: Example embodiments enable a scalable method (200) to manage faults of a wide network of electric vehicle charging stations comprising even thousands electric vehicle charging stations. The occurred faults may be solved automatically when possible. The faults may be prioritized based on one or more criterion. The method (200) and an apparatus (600) is provided to handle the faults more efficiently.

Abstract: Various example embodiments relate to optimization of electric vehicle charging station networks. A computer-implemented method applicable to a network comprising a plurality of electric vehicle charging stations operated by different parties may be provided. In an embodiment, public data comprising general information associated with the charging stations is used to estimate utilization of the network in different locations. Advantageously, good new locations for charging station may be determined based on the estimates without requiring detailed data from each of the parties. A computing device, a method and a computer program are disclosed.

Abstract: It is an object to provide a charging station reliability assessment device and a charging station reliability assessment method. According to an embodiment, a method comprises obtaining a history information of an electric vehicle, EV, charging station. A first and a second reliability index may be calculated based on the history information. Based on the first and the second reliability index, a third reliability index may be calculated. A method, a device, and a computer program product are provided.

Abstract: Various example embodiments generally relate to charging electric devices. An apparatus may comprise: means for determining a target amount of energy to be charged to an electric device; means for receiving, from a charging station, a charging report associated with a current reporting interval; means for estimating a remaining charging time based on at least the charging report associated with the current reporting interval and the target amount of energy; means for setting a maximum charging rate for a subsequent reporting interval, in response to determining that the remaining charging time is lower than or equal to a threshold; and means for transmitting an indication of the maximum charging rate to the charging station.

Abstract: Example embodiments enable a scalable method (200) to manage faults of a wide network of electric vehicle charging stations comprising even thousands electric vehicle charging stations. The occurred faults may be solved automatically when possible. The faults may be prioritized based on one or more criterion. The method (200) and an apparatus (600) is provided to handle the faults more efficiently.

Abstract: It is an object to provide a backup electric vehicle, EV, charging management device. According to an embodiment, a backup EV charging management device is configured to: when a primary EV charging management system is available, synchronize an identification cache of a backup EV charging management system with an identification cache of the primary EV charging management system; when the primary EV charging management system is unavailable, receive a message from the EV charging station; in response to the message being a request for charging using the EV charging station, check whether the request should be allowed by comparing an identification of the user trying to use the EV charging station to the identification cache of the backup EV charging management system; and in response to determining that the request should be allowed, transmit an acceptance message to the EV charging station.

Abstract: Example embodiments provide improved dynamic load management for an electric vehicle charging system. A cloud-based apparatus is configured to adjust maximum current ratings of charging stations when one or more charging stations drop offline based on a latest accepted request for maximum charging current of the offline charging station. An apparatus, a method, and a computer program are disclosed.

Abstract: Computing device, a system and a method for verifying electric vehicle, EV, charging, is provided. There is received, by Internet based communication such as API, encrypted energy readings certifying and verifying an amount of an energy that an electric vehicle, EV, is charged from an EV charging station, CS. Transmitting these energy readings, by the Internet based communication such as a web server, to be presented to a user who has charged the EV at the CS, wherein said energy readings is configured to be outputted to the user by the Internet-based user interface. Regulations, such as Eichrecht, compatible charging system can be conveniently updated to existing or new parts of the charging system without an individual or manual certification process.

Abstract: According to an embodiment, a client device is configured to in response to an input from a user of the client device, wherein the input indicates that the user wishes to charge an electric vehicle, EV, using an EV charging station, transmit a request for EV charging using the EV charging station to a primary EV charging management system, wherein the request for EV charging using the EV charging station comprises an identification of the EV charging station; and in response to the primary EV charging management system not responding to the request for EV charging using the EV charging station, transmit the request for EV charging using the EV charging station to a backup EV charging management system.

Abstract: It is an object to provide an electric vehicle charging monitoring device and an electric vehicle charging monitoring method. According to an embodiment, a device comprises: a current measurement device configured to measure an electrical current flowing from an electrical input to an electrical output and a computing device electrically coupled to the current measurement device, configured to: monitor a number of charging sessions based on the electrical current flow from the electrical input to the electrical output; compare the number of charging sessions to a first preconfigured value; and detect abnormal current flow based on the charging session comparison. A device, a method, and a computer program product are provided.

Abstract: Various example embodiments relate to determining an online/offline status of an electric vehicle charging station. The charging station may be determined to be online for a period of time after reception of a message from the charging station. Further, probability (100) of the charging station for being online may be determined, and one or more actions may be initiated in response to the online probability decreasing below a predetermined threshold. A computing device (200,300), a method, a system and a computer program (306) are disclosed.

Abstract: Various example embodiments relate to managing charging stations of electric vehicles based on a proximity of a user. A beacon transmitter is configured to broadcast identifiers of a charging station and of a list of allowed users. A mobile device of the user is configured to detect a proximity of the beacon transmitter and determine if the charging station can be set for charging based on an identifier of the user, the identifier of the charging station and the identifier of the user list. Apparatuses, methods, and computer programs are disclosed.

Abstract: Various example embodiments relate to identifying an electric vehicle charging station. An authentication method applicable with any electric vehicle charging station may be provided. In an embodiment, an alert or quarantine of an electric vehicle charging may be triggered based on invalid authentication. Advantageously, improved security may be provided for communication in a charging management system. A computing device, a method and a computer program are disclosed.

Abstract: According to an aspect, there is provided a computing device. The computing device is configured to store user-specific data comprising information configured to set an automatic charging mode to at least one electric vehicle charging station determined by the user in a memory, the information comprising geographical coordinates of the at least one electric vehicle charging station; track geographical coordinates of the user based on geographical information received from a device of the user; detect when the user is within a predetermined distance from the at least one electric vehicle charging station by comparing the geographical coordinates of the user and the geographical coordinates of the at least one electric vehicle charging station; notify the user that a charging mode will be set to the at least one electric vehicle charging station; and send an authorized start-command to the at least one electric vehicle charging station to set the charging mode for the user.

Abstract: Provided is a technique for monitoring energy consumption in an electric vehicle (EV) charging network. The technique is based on using messages from one or more EV charging stations, each of which comprises a timestamp, a station ID, a charging session ID, and an energy meter reading. Whenever a new message is received, it is first stored in a database, whereupon it is checked whether the database comprises an older message with the same station ID and charging session ID as the new message. If the older message is present in the database, a time difference and an energy difference between the new and older messages are calculated. Then, a time granularity level is selected based on the time difference. An energy consumption distribution between the timestamps of the new and older messages is obtained based on the time granularity level and the energy difference.

Abstract: It is an object to provide a charging station reliability assessment device and a charging station reliability assessment method. According to an embodiment, a method comprises obtaining a history information of an electric vehicle, EV, charging station. A first and a second reliability index may be calculated based on the history information. Based on the first and the second reliability index, a third reliability index may be calculated. A method, a device, and a computer program product are provided.

Abstract: A method, apparatus, and computer program product for the control of electric vehicle (EV) charging enabling non-real-time remote monitoring and adjustments of electrical current consumed at EV charging stations, without causing an electrical grid to be. At least one EV charging station is first pre-instructed to provide an EV with a station current when a charging session for the EV is initiated at the EV charging station. The station current is ?a maximum allowable current of the EV charging station. After the initiation of charging, an actual current consumed during the charging is monitored remotely in non-real time. Next, a ratio of the actual current consumed by the EV to the charging station is calculated and used to decide whether to change the current provided by the EV charging station. After that, EV charging station is instructed, on a non-real-time basis, to operate in accordance with the decision made.