WO2023224712A1

WO2023224712A1 - Systems and methods for integrating electronic calendar data into an electric vehicle charging network

Info

Publication number: WO2023224712A1
Application number: PCT/US2023/014690
Authority: WO
Inventors: Jenya Kirshtein; Daniel Feldman; Giovanni BERTOLINO
Original assignee: ENEL X Way S.r.l.
Priority date: 2022-05-16
Filing date: 2023-03-07
Publication date: 2023-11-23

Abstract

Systems and method for managing an electric vehicle charging system. There may not be enough energy available to charge a large number of electric vehicles at the same time. Accordingly, a charging management server in network communication with one or more electric vehicle chargers may calculate a charge priority score of an electric vehicle charger associated with a user or a profile of the user for a time frame prior to an event the user is scheduled attend based on calendar data from the user's electronic calendar, set a charge priority of the charger or with the profile of the user for the time, and transmit instructions to the charger to charge an electric vehicle operated by the user for the time frame. Methods for calculating the charge priority score and setting the charge priority are discussed.

Description

SYSTEMS AND METHODS FOR INTEGRATING ELECTRONIC CALENDAR DATA

INTO AN ELECTRIC VEHICLE CHARGING NETWORK

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of priority to U.S. Provisional Application No. 63/342,571, filed May 16, 2022, the entirety of which is incorporated by reference herein.

TECHNICAL FIELD

[0002] The present disclosure is generally directed to electric vehicle (EV) charging. More particularly, the present disclosure describes systems and methods for integrating users’ electronic calendars with an electric vehicle charge network and generating a priority system for charging the users’ electric vehicles.

BACKGROUND

[0003] Electric vehicles are becoming more prominent in today’s society, with EV sales increasing exponentially over the recent years and with vehicle manufacturers placing an increasing emphasis on manufacturing EVs. Some states, such as California, have even set laws in place that will require all new cars to be sold to be zero-emission vehicles, such as EVs, by a certain time deadline. Accordingly, it will become more and more important to ensure the appropriate charging infrastructure is in place to charge EVs on the road.

[0004] In preparation for an expected overflow of EV ownership, companies that operate in commercial buildings may install an EV charger network that provides energy to personal and/or company-owned EVs. The EV charger network may be connected to a power grid. However, because the power grid may only be able to supply the electric charger network with a limited amount of power throughout different portions of the day, the company may need to manage when and which EVs are charged. For example, it may be important for an EV owned by a business executive to be charged at 10AM so the business executive can drive the EV to a meeting with an important client. In a non-discriminative charger network, the charger network may have used all of the available energy from the grid to charge other EVs, leaving the business executive to find other avenues to travel to the meeting or to miss the meeting entirely. Accordingly, the electric charger network may not have a system in place to ensure EVs are sufficiently charged to travel to high priority events. BRIEF SUMMARY

[0005] Systems that attempt to charge electric vehicles to ensure EVs are sufficiently charged to drive to important events may use smart charging algorithms. Such algorithms may take into consideration the states of charge of the EVs and, in some cases, the priority of charging different users’ EVs. Such systems may use priority information to selectively charge EVs depending on how the system is configured. For instance, a system administrator may manually enter information into the smart charging algorithms, such as times in which a particular EV is needed for travel and the energy that is needed for charging, to provide information that can be used to define the priorities of charging different vehicles. However, the system may not be able to set accurate priorities for charging vehicles in instances in which information is not provided or is erroneously provided, which may be common with manual inputs. While in some cases it may be possible to estimate the energy that is required using an API integration or with ISO 15118, systems that use these methods may still not be able to charge vehicles at the correct times or with the correct amount of energy. Accordingly, systems may not be able to selectively charge vehicles such that the vehicles can travel to high priority appointments on time.

[0006] To overcome the aforementioned technical deficiencies, a computer (or other computing device) implementing the systems and methods described herein may access event data from an individual user’s electronic calendar and ensure the user’s EV is sufficiently charged to travel to scheduled events. The event data may include times, durations, and/or locations of events the user is scheduled to attend. In one example, a salesman may have an electronic calendar indicating different in-person sales meetings the salesman is scheduled to attend, with whom the salesman is scheduled to meet, and where those meetings are scheduled to take place. The computer may retrieve such event data from an application stored on the user’s computing device in communication with a calendar application on the same device. For instance, the application on the user’s computing device may query the calendar application and retrieve data indicating dates, times, durations, and/or identifications of events the user is scheduled to attend. The application may transmit the retrieved data to the computer, and the computer may analyze the data to establish charge priorities for the user for time frames prior to the events to ensure an EV charger is available and/or enabled for the user’s EV to be sufficiently charged to travel to the events.

[0007] Additionally, the computer implementing the systems and methods described herein may ensure the users in a commercial environment have enough charge in their EVs to travel to high priority events. For instance, at a commercial building, there may be a limited amount of energy available to charge every EV at the building. Accordingly, the computer may selectively choose the EVs to provide energy to ensure individuals can travel to more important events before providing energy to EVs for the less important events. To do so, the computer may retrieve event metadata (e.g., titles of individuals attending the event, a value of the event, group entities associated with the event, etc.) from devices associated with multiple EV owners of the building. The computer may evaluate the event metadata according to a set of rules to calculate charge priority scores for the different events (e.g., calculate higher charge priority scores for more important events). The computer may determine charge priorities for the different users and/or their EV chargers compared with each other based on the charge priority scores. The computer may then selectively enable EV chargers that correspond to the users to charge their EVs according to the charge priorities. In this way, the computer may use integrated calendar data to ensure EVs charged by a commercial event are sufficiently charged to travel to high priority events.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

[0008] To easily identify the discussion of any particular element or act, the most significant digit or digits in a reference number refer to the figure number in which that element is first introduced.

[0009] FIG. 1 shows a system for selectively enabling a charging station to charge an electric vehicle (EV), according to one embodiment.

[0010] FIG. 2 is a diagram of example techniques for integrating electronic calendar data into an electric vehicle charging network, according to one embodiment.

[0011] FIG. 3 is a diagram of a system that includes a power grid and a network of charging stations, according to one embodiment.

[0012] FIG. 4 shows inputs and outputs of a model used to selectively enable a charging station to charge an EV, according to one embodiment.

[0013] FIG. 5 is a flow diagram of a process for selectively enabling a charging station to charge an EV, according to one embodiment.

[0014] FIG. 6 is a flow diagram of another process for selectively enabling a charging station to charge an EV, according to one embodiment.

DETAILED DESCRIPTION

[0015] The present embodiments will become more fully apparent from the following description and appended claims, taken in conjunction with the accompanying drawings. Understanding that the accompanying drawings depict only typical embodiments and are, therefore, not to be considered limiting of the scope of the disclosure, the embodiments will be described and explained with specificity and detail in reference to the following accompanying drawings.

[0016] As mentioned above, there is a need for a computing system that can determine (e.g., automatically determine) when it is likely that a user will need an EV, such that the EV can be scheduled or prioritized to charge in an electric vehicle charging network.

[0017] A computer (or other computing device) implementing the systems and methods described herein can overcome the aforementioned technical deficiencies by communicating with EV charging applications that are stored on different users’ computing devices and are in communication with calendar applications on the same devices. An EV charging application can be integrated with a calendar application on a user’s computing device such that the EV charging application can retrieve the location and time of each event on the electronic calendar of the calendar application and communicate the retrieved data to the computer. The computer may retrieve such data from the computing devices of different users and set a prioritized schedule for charging the users’ EVs according to the users that are scheduled to attend the highest priority events. The computer may be configured to set charging priorities for the different events based on the titles of the users whose devices provided the event data (e.g., which may be determined from the users’ contact lists in memory of their respective computing devices), and/or based on the titles of the other individuals that are scheduled to attend the same event. The computer may calculate the charging priorities additionally based on whether the meeting is only with internal employees or is a meeting with customers or clients. In some cases, additional prioritization may be provided based on the public revenue size or market cap of the customers with which the meeting is to take place. For example, if the meeting is with a person from Company A, the meeting may have a higher priority than a meeting with a person from Company B. Further, a CRM-integrated prioritization can be performed to take into account identified opportunities with a customer. For example, a meeting with a customer that has an open opportunity associated with a large value may be more important than a meeting with a customer that has an open opportunity associated with a lower value.

[0018] If the EV charging application is reading or is otherwise integrated with the electronic calendar, the EV charging application (e.g., the computer in communication with the charging application) may be configured to automatically create a calendar event specifically to indicate when an EV needs to be fully charged (e.g., "Car ready at 6PM fully charged"). In some cases, the EV charging application can automatically create a calendar event for when the car is expected to charge if the driver didn't set preferences explicitly in the EV charging application or the calendar application. The EV charging application may additionally provide an option within a calendar event (e.g., a checkbox) to allow a user to indicate whether the user’s EV will be involved with traveling to the calendar event.

[0019] Additionally, from the calendar or an EV application programming interface (API) (if available), the server can learn the usage patterns of the EV and a correlation can be drawn between usage patterns (speed, distance traveled, the state of charge of the battery) and battery deterioration. The correlation can be used to predict what the state of charge of the battery is going to be based on known calendar information about a planned activity. The EV API (if available) or connectivity to the EV chargers can be used to learn about real battery capacity (and deterioration over time) to inform the correlation.

[0020] For example, FIG. 1 illustrates a present state of a system 100 that uses a charging management server 102 to control EV charging in an electric charger network 104, according to an embodiment of the present disclosure. The system 100 includes the charging management server 102, a network 106, EV chargers 108, 110, 112, and 114 of the electric charger network 104, a computing device 116, a group entity management server 118, and one or more databases 120. The charging management server 102 may communicate with the EV chargers 108, 110, 112, and 114, the computing device 116, the group entity management server 118, and/or the one or more databases 120 over the network 106. In some cases, the system 100 may also include a power grid 122. The power grid 122 may provide energy to EV chargers 108, 110, 112, and 114. Accordingly, the charging management server 102 may transmit instructions or signals to the EV chargers 108, 110, 112, and 114 to enable the EV chargers 108, 110, 112, 114 to charge EVs 124, 126, 128, 130 respectively connected to EV chargers 108, 110, 112, 114 with energy from the power grid 122. The system 100 may include more, fewer, or different components than are shown in FIG. 1. For example, there may be any number of client devices or computers that make up or are a part of the charging management server 102 or the group entity management server 118 or EVs, EV chargers, or networks in system 100.

[0021] The power grid 122 may provide energy to EV chargers 108, 110, 112, 114. The power grid 122, the EV chargers 108, 110, 112, 114, and how the components interoperate with each other to provide energy to EVs is described in greater detail below with reference to FIG. 3. As described herein, any reference to an EV charger may be a reference to electric vehicle supply equipment (EVSE).

[0022] The charging management server 102, the computing device 116, and/or the group entity management server 118 can include or execute on one or more processors or computing devices and/or communicate via the network 106. In some embodiments, the network 106 may facilitate communication between the charging management server 102, the computing device 116, and/or the group entity management server 118. Communication(s) in the system 100 may be performed using various protocols and/or standards. Examples of such protocols and standards include a 3rd Generation Partnership Project (3GPP) Long-Term Evolution (LTE) standard, such as a 4th Generation (4G) or a 5th Generation (5G) cellular standard; an Institute of Electrical and Electronics (IEEE) 802.11 standard, such as IEEE 802.11g, ac, ax, ad, aj, or ay (e.g., Wi-Fi 6® or WiGig®); an IEEE 802.16 standard (e.g., WiMAX®); a Bluetooth Classic® standard; a Bluetooth Low Energy® orBLE® standard; an IEEE 802.15.4 (e.g., Thread® or ZigBee®); other protocols and standards established or maintained by various governmental, industry, and/or academia consortiums, organizations, and/or agencies; and so forth. Therefore, the network 106 may be a cellular network, the Internet, a wide area network (WAN), a local area network (LAN), a wireless LAN (WLAN), a wireless personal-area-network (WPAN), a mesh network, a wireless wide area network (WWAN), a peer-to-peer (P2P) network, and/or a Global Navigation Satellite System (GNSS) (e.g., Global Positioning System (GPS), Galileo, Quasi-Zenith Satellite System (QZSS), BeiDou, GLObal NAvigation Satellite System (GLONASS), Indian Regional Navigation Satellite System (IRNSS), and so forth).

[0023] In addition to, or alternatively, the communications illustrated in FIG. 1, the system 100 may facilitate other unidirectional, bidirectional, wired, wireless, direct, and/or indirect communications utilizing one or more communication protocols. In some embodiments, the charging management server 102, the EV chargers 108, 110, 112, and 114, the computing device 116, the group entity management server 118, and/or the device(s) storing the one or more databases 120 may communicate with each other directly (e.g., via Bluetooth Classic® or a different short-range communication protocol) and/or indirectly (e.g., via the network 106). It is to be understood that the charging management server 102, the EV chargers 108, 110, 112, and 114, the computing device 116, the group entity management server 118, and other elements in the system 100 that may not be explicitly illustrated in FIG. 1 include appropriate wired and/or wireless interfaces to accommodate the abovementioned communication protocols and/or standards. This disclosure covers example techniques for setting priorities for different EV chargers and/or user profiles for charging in an electric charger network (e.g., the electric charger network 104) via such communication protocols.

[0024] Each of the charging management server 102, the EV chargers 108, 110, 112, and 114, the computing device 116, the group entity management server 118, and/or the device(s) storing the one or more databases 120 can include or utilize at least one processing unit or other logic devices such as a programmable logic array engine or a module configured to communicate with one another or other resources or databases. The components of the charging management server 102, the EV chargers 108, 110, 112, and 114, the computing device 116, the group entity management server 118, and/or the device(s) storing the one or more databases 120 can be separate components or a single component. The system 100 and its components can include hardware elements, such as one or more processors, logic devices, or circuits.

[0025] The charging management server 102 may comprise one or more processors that are configured to use event data from users’ electronic calendars to set priorities for electrical chargers and/or user profiles in a queue. The charging management server 102 may facilitate the EV chargers 108, 110, 112, and 114 charging a plurality of EVs using a limited amount of energy such that the owners or users associated with the EVs can drive their respective EVs to high priority events. The charging management server 102 may comprise a network interface, a processor, and/or memory. The processor may be or include an ASIC, one or more FPGAs, a DSP, circuits containing one or more processing components, circuitry for supporting a microprocessor, a group of processing components, or other suitable electronic processing components. In some embodiments, the processor may execute computer code or modules (e.g., executable code, object code, source code, script code, machine code, etc.) stored in memory to facilitate the activities described herein. The memory may be any volatile or non-volatile computer-readable storage medium capable of storing data or computer code.

[0026] In some embodiments, the system 100 includes one or more databases 120. The databases 120 may be relational databases configured to store data about EVs and the charging of EVs by EV chargers. The charging management server 102 may retrieve the stored data from the databases 120. For example, the databases 120 may store data received from and/or generated by one or more of the EV chargers 108, 110, 112, and/or 114, the charging management server 102, and/or any other device or connected to the system 100. The data may be profile data for drivers of EVs (e.g., EVs 124, 126, 128, 130) reflecting information (e.g., make, model, vehicle identification number (VIN), MAC address, amount of energy the EV charger has provided the EV or multiple EVs, etc.) of the EVs operated by, owned by, or otherwise associated with the drivers. In some cases, the databases 120 may store data about drivers of the EVs in dedicated profiles for each driver. The databases 120 may be stored by any of the computing devices of the system 100 or in memory of a separate computing device. The charging management server 102 may retrieve data from the databases 120 to determine charging patterns and/or other information about EVs that the charging management server 102 can then use to calculate charge priorities for the EV chargers and/or the individual user profiles.

[0027] The computing device 116 may be any suitable computing or other electronic device. In some embodiments, the computing device 116 may be or may include a smartphone, a navigation device, a media device, a laptop computer, a network-attached storage (NAS) device, a desktop computer, a tablet computer, a computer server, a smart appliance, a cellular base station, a broadband router, an access point, a gaming device, an internet-of-things (loT) device, a sensor, a security device, an asset tracker, a fitness management device, a wearable device, a wireless power device, and so forth.

[0028] In some embodiments, the computing device 116 may be an In-Vehicle Infotainment (IVI) system of an EV (e.g., any one of EVs 124, 126, 128, 130), where the IVI system and its associated user interface may enhance a driving or riding experience by incorporating features, such as navigation, directions to the nearest charging station, directions to a fastcharging station, traffic information, ridesharing information, a state of charge of the EV, a rear dashcam, parking assistance, hands-free phone, radio stations, and/or other features. For these features, the computing device 116 may utilize ridesharing, navigation, autonomous- driving, driver-assistance, and/or other application software.

[0029] In some embodiments, the computing device 116 includes at least one processor, memory and at least one computer-readable medium. The processor, memory, and the at least one computer-readable medium may be similar to the processor, memory, and computer- readable medium of the charging management server 102.

[0030] In some cases, the computing device 116 may store a calendar application and a charging application. The calendar application may be any application that enables a user to schedule events, schedule appointments, set notes, send meeting invites, maintain a contact list, and/or any other features related to event scheduling. The calendar application may store the data in a calendar format. The calendar format may enable a user accessing the computing device 116 and/or associated with the data calendar application to view the event data in an accessible manner (e.g., on a calendar interface). The charging application may be an application (e.g., an API) that can communicate with the charging management server 102 and/or the calendar application. In one example, the charging application may request or retrieve event data (e.g., times (event start times or time periods), identifications of events, etc.) and/or event metadata (e.g., locations, attendees, and any other information about events that are scheduled in the user’s electronic calendar in the calendar application) from the calendar application. The charging application may then transmit the retrieved event data and/or event metadata to the charging management server 102.

[0031] In some embodiments, the charging application may only retrieve event data and event metadata for events that have stored associations with flags. The flags may indicate the users associated with the electronic calendars from which the data was retrieved will travel to the events in his or her EV. For example, a user may flag different events in the user’s electronic calendar depending on whether the user will travel to the events in his or her EV. The user may set flags, for example, to differentiate flagged events from other events (e.g., intraoffice events) that the user either does not need to use an EV to travel to or will use another means of transportation. In some embodiments, the user may set the flags by selecting an option (e.g., a checkbox) for events when creating the events in the electronic calendar. The charging application or the calendar application may parse through the data for each event from the user’s electronic calendar in the calendar application. The charging application or the calendar application may identify any events that are associated with a flag indicating the user will travel to the event in his or her EV. In this way, the charging application may avoid using processing resources to retrieve data for events that do not require EV charging and the server may avoid using processing resources to calculate a charge priority score and/or a charge priority for events that do not require any EV charging.

[0032] The charging management server 102 may receive the event data and/or the event metadata for an event identified in the event data and/or the event metadata. For example, the charging management server 102 may identify an event that a user associated with the computing device 116 is scheduled to attend and a start time of the event from event data the charging application retrieved from the calendar application. The charging management server 102 may then use a set of rules on the event metadata for the event to calculate a charge priority score for a time frame prior to a start time of the event.

[0033] The charging management server 102 may calculate the charge priority score based on the event metadata for the event. For example, the event metadata for the event may include information about the event such as information about who is attending the event (the user and/or the individuals meeting with the user), the job titles of the attendees to the event, a value of the event, a topic of the event, group entities (e.g., companies) associated with the individuals attending the event, a value associated with such group entities, etc. The charging management server 102 may evaluate the event metadata according to a set of rules to calculate a charge priority score for the event. For instance, the charging management server 102 may assign higher charge priority scores to events that are attended by individuals with higher level job titles (e.g., business executives), events that are associated with higher values, particular topics, specific group entities and/or group entities associated with higher values, or any combination of such event metadata. In applying the set of rules to the event metadata, the charging management server 102 may calculate a higher or lower charge priority score for the event based on each type of metadata until the charging management server 102 has applied rules to all of the retrieved metadata.

[0034] In one example, the charging management server 102 may calculate the charge priority score for the event based on the titles of the individuals that are scheduled to attend the event. For instance, the charging management server 102 may receive identifications of the individuals that are scheduled to attend the event and/or job titles of the individuals from the charging application executing on the computing device 116. The charging management server 102 may receive such identifications for the user and/or for other individuals that are scheduled to meet with the user or otherwise attend the event. The charging application may retrieve the job title data from the data in the electronic calendar and/or from a contact list stored in the computing device 116 that has such information about users. The charging management server 102 may then compare the retrieved job titles to data in the database 120 to determine values of the different job titles (e.g., business executives may be associated with higher values in the database 120 than standard employees). The charging management server 102 may then use the determined values to calculate the priority score for the event by aggregating, determining an average, determining a weighted average (e.g., the title for the user may be weighted higher or lower than the titles of the individuals scheduled to meet with the user), or performing any other operation on the values.

[0035] In another example, the charging management server 102 may calculate the priority score for the event based on a value associated with the event. For instance, different events may be associated with different values (e.g., values of deals). The charging management server 102 may calculate the charge priority scores for the events based on the values of the events by calculating higher priority scores for events associated with higher values.

[0036] In some embodiments, the charging management server 102 may calculate the priority score for the event using data from third-party data sources. For example, upon receiving event data and event metadata from the charging application of the computing device 116, the charging management server 102 may query the group entity management server 118 for data about the event or about the participants of the event. The group entity management server 118 may be a computing device similar to the charging management server 102 that maintains customer relationship management data and may be operated by the same entity that operates the charging management server 102 or by another entity. The group entity management server 118 may store data about individuals such that when the charging management server 102 queries the group entity management server 118 using names of individuals and/or events, the group entity management server 118 may search an internal database for data (e.g., the titles of the individuals, values of the events, values associated with companies associated with the events, etc.). The group entity management server 118 may then transmit the retrieved data back to the charging management server 102, which may in turn calculate a charge priority score for the event using the retrieved data. In some embodiments, instead of querying the separate group entity management server 118, the charging management server 102 may store the same or similar information in memory. In such embodiments, the charging management server 102 may query the local memory to retrieve such data. In this way, the charging management server 102 may use data that is not available or is otherwise not included in received event data and event metadata to calculate accurate charge priority scores for events.

[0037] The charging management server 102 may determine the time frame for which to apply the charge priority score for the event. To do so, the charging management server 102 may calculate the amount of time it would take for an EV to travel to the event. The charging management server 102 may also identify a start time of the event, a current state of charge of the EV, a charge rate of the EV, and/or an amount of charge that is needed to travel to the event.

[0038] The charging management server 102 may calculate the amount of time it would take for the EV to travel to the event by identifying the location of the event. The charging management server 102 may identify the location of the event from the event metadata for the event. The charging management server 102 may then calculate a distance between an EV charger of the system 100 and the event’s location using a map application. The charging management server 102 may then calculate a travel time it will take for the EV to travel to the location based on the distance using the same map application and/or by using data from the user’s driver profile. For instance, the charging management server 102 may retrieve the average drive speed of the user from the user’s profile in the database 120 and divide the distance by the average drive speed to calculate the travel time it will take for the EV to travel to the event’s location.

[0039] The charging management server 102 may calculate the amount of energy that would be required to travel to the event. To do so, the charging management server 102 may identify the distance the EV can travel per kWh. The charging management server 102 may do so, for example, by retrieving the distance from a profile of the EV or a profile of the user that operates the EV from the database 120. The charging management server 102 may then divide the distance to the event’s location by the distance the EV can travel per kWh to obtain the amount of energy or charge the EV requires to travel to the event’s location.

[0040] In some embodiments, the charging management server 102 may identify or estimate the state of charge of the user’s EV. To do so, in some cases, the charging management server 102 may communicate with a computer that operates the EV through an API. The charging management server 102 may query the computer for the current state of charge of the EV and receive the state of the charge in response to the query. In other cases, the EV may not be able to communicate the current state of charge of the EV. In such cases, the charging management server 102 may estimate or predict the current state of charge of the EV. In some embodiments, the charging management server 102 may do so using the systems and methods described in U.S. Application No. 16/999,873, entitled “Estimated Vehicle State of Charge using Bluetooth Identification,” and filed August 21, 2020, the entirety of which is incorporated by reference herein.

[0041] In one example, the charging management server 102 may predict the state of charge of the user’s EV for the time period based on other events to which the EV is scheduled to travel. For instance, the charging management server 102 may receive event data and event metadata indicating the EV is scheduled to travel to multiple events prior to the event for which the charging management server 102 is calculating a priority. The charging management server 102 may analyze the location data to determine the distance the EV will have to travel to arrive at each of the events. In doing so, the charging management server 102 may calculate the distance to travel to and from the events or the distances to travel to the events in a chain without returning to the EV charger network 104 between events. The charging management server 102 may identify the current state (e.g., the initial state) of charge of the EV. The charging management server 102 may then calculate the amount of charge that will be required to travel the calculated distance and subtract the calculated amount of charge from the current state of charge to predict the state of charge of the EV. The charging management server 102 may then use the predicted state of charge to calculate the duration of the time frame. In this way, the charging management server 102 may account for interim trips the EV will likely take to ensure the state of charge the charging management server 102 predictions or estimations accurately reflects the amount of energy that will be in the EV when the EV needs to begin charging for the event.

[0042] The charging management server 102 may identify a charge rate of the EV. The charge rate may be the rate at which an EV charger will charge the EV when the EV is connected to the EV charger. In many cases, the charge rate may be specific to or limited by the configuration of the EV charger charging the EV. For instance, one EV charger may charge an EV at 30 kW, another EV charger may charge an EV at 150 kW, and another EV charger may charge an EV at 240kW. In other cases, the charge rate may be specific to the EVs themselves. In either case, the charging management server 102 may identify the charge rate for the EV charger the EV is scheduled to use from a profile for the EV or the EV charger in the database 120.

[0043] The charging management server 102 may calculate the duration of the time frame that the user’s EV needs to be charged based on the charge rate, the current state of charge of the EV, and/or the amount of charge the EV needs to travel to the event. For instance, the charging management server 102 may determine a difference between the amount of charge the EV needs to travel to the event and the current state of charge of the EV. In some embodiments, the charging management server 102 may determine a difference between the amount of charge the EV needs to travel to the event and back to the charger (e.g., by doubling the distance) or otherwise add a defined buffer (e.g., added distance) to the distance to the event to ensure the EV has enough energy or charge to travel after reaching the event’s location. The charging management server 102 may then calculate the duration by dividing the difference by the identified charge rate to obtain the duration of the time frame that the user’s EV needs to be charged to travel to the event’s location and/or have a buffer to return to the EV charger or to travel after reaching the event’s location.

[0044] In some embodiments, the charging management server 102 may take the EV charger’s charge capacity or a predefined percentage of the charge capacity into account when determining the duration of the time frame that the user’s EV needs to be charged. For example, the charging management server 102 may identify the charge capacity of the EV from the database 120 and the state of charge of the EV. Upon determining the amount of charge the EV requires to travel the distance to the event, the charging management server 102 may add the amount of charge to the current state of charge of the EV. Responsive to the aggregated charge exceeding the charge capacity or a predefined percentage of the charge capacity of the EV, the charging management server 102 may calculate the amount of time it will take to charge the EV to the EV’ s charge capacity or the predefined percentage of the charge capacity based on the charge rate and the state of charge. In such instances, the charging management server 102 may determine the duration of the time frame the user’s EV needs to be charged is the time it will take to charge the EV to the EV’s charge capacity or the predefined percentage of the charge capacity. Thus, the charging management server 102 may avoid scheduling the EV for charging for times in which no more charge can be added to the battery, freeing up the corresponding EV charger to charge other EVs. [0045] Upon calculating the duration of the time frame that the user’s EV needs to be charged, the charging management server 102 may set the time in which the EV will be charged to travel to the event on time. To do so, the charging management server 102 may identify the amount of time it will take for the EV to travel to the event’s location. The charging management server 102 may subtract the identified amount of time, and, in some cases, an added defined buffer amount of time from the start time of the event to calculate the time the EV needs to leave the EV charger to arrive at the event on time. The charging management server 102 may then subtract the duration of the time frame from the time the EV needs to leave the EV charger to calculate the time of the beginning of the time frame to begin charging. In this way, the charging management server 102 may calculate the time at which the EV needs to begin charging to ensure the EV can arrive at the event on time.

[0046] In some embodiments, upon calculating the beginning of the time frame to begin charging, the charging management server 102 may transmit an indication to the computing device 116 indicating the beginning time and the duration of the time frame. The computing device 116 may receive the beginning time and the duration of the time frame and execute the calendar application on the computing device. In doing so, the computing device 116 may update the data in the calendar application with a new event indicating the beginning time and duration of the time frame. The user may view the information from the new event when accessing the calendar application to view when the user’s EV will begin or needs to begin charging to ensure the EV is connected to the EV charger for the time frame.

[0047] The charging management server 102 may calculate a charge priority for the event. For example, the charging management server 102 may calculate charge priority scores for other events that are scheduled on electronic calendars owned by other users similar to the manner in which the charging management server 102 calculated the charge priority score for the event. The charging management server 102 may also similarly identify time frames for which EVs need to be charged to attend the events on time. In some embodiments, the charging management server 102 may identify any time frames that overlap with the calculated charging time frame for the event the user is scheduled to attend. In some embodiments, instead of calculating priorities for events with overlapping time frames, the charging management server 102 may organize a schedule into units (e.g., 30 minute units). The charging management server may identify the units that contain the calculated time frame for the event and identify events that have similarly calculated charging time frames for all or a portion of the same units. The charging management server 102 may then compare the charge priority scores for each of the events to each other and calculate priorities in descending or ascending order based on the charge priority scores (e.g., higher charge priority scores may have higher rankings than lower charge priority scores).

[0048] In some embodiments, the charging management server 102 may set the calculated charge priority for the event to an EV charger associated with the user scheduled to attend the event. The charging management server 102 may set the calculated charge priority by inserting a value indicating the priority in memory allocated to the EV charger. For example, the charging management server 102 may identify a profile of an EV charger that has a stored association with the user in the database 120. The stored association may indicate that the user’s EV is parked and connected to the EV charger or that the user’s EV is scheduled to be in such a state. The charging management server 102 may identify the time frame for the event for which the priority was calculated and insert the priority, and in some cases the charge priority score and/or the data that was used to calculate the charge priority score, into the EV charger’s profile for the time frame. In some cases, the charging management server 102 may insert the beginning and end time of the time frame into the EV charger profile.

[0049] In some embodiments, the charging management server 102 may set the calculated charge priority for the event to a user profile of the user scheduled to attend the event. The charging management server 102 may set the calculated charge priority by inserting a value indicating the priority in memory allocated to the user profile. For example, the charging management server 102 may identify a user profile of the user in the database 120. The charging management server 102 may identify the time frame for the event for which the priority was calculated and insert the priority, and in some cases the charge priority score and/or the data that was used to calculate the charge priority score, into the user’s profile for the time frame. The charging management server 102 may establish a queue of users for the time indicating an order for the users to charge their EVs. In this way, the charging management server 102 may establish a prioritized queue that can be used to ensure users can use their EVs to attend the highest priority events.

[0050] In some embodiments, the charging management server 102 may determine which EV chargers to enable to charge EVs based on the priorities in the EV charger profiles. The charging management server 102 may do so by comparing the priorities for the time frame. The charging management server 102 may determine which EV charger profiles are associated with the highest priorities and transmit instructions to the identified EV charger to initiate charging of the EV connected to the EV charger for the time frame. The instructions may contain an identification of the beginning time and/or the end time of the time frame. The EV charger can begin charging the EV at the beginning time using power from the power grid 122. The EV charger may power the EV until the end time, at which point the instructions may cause the EV charger to stop charging the EV.

[0051] Advantageously, by using the priority and electronic calendar integration system, the charging management server 102 may provide energy to EVs in cases in which the amount of energy from the grid that the EV charger network 104 has available to charge EVs is limited. The charging management server 102 may use the priority system to ensure users can still attend the highest priority events, despite the shortage in energy.

[0052] In some embodiments, the charging management server 102 may determine which user profiles of the user profile queue to transmit a message (e.g., an email, text message, voice message, etc.) to based on the priorities in the user profiles. The charging management server 102 may do so by comparing the priorities in the user profiles for the time frame. The charging management server 102 may determine which user profiles are associated with the highest priorities for the time frame, retrieve the contact information from the user profile with the highest charge priority score, and use the contact information to transmit a message to the user associated with the user profile indicating to move an EV associated with the user to an EV charger in the EV charger network 104. The charging management server 102 may similarly send messages to any number of users according to the priorities in the users’ profiles until determining there are not any more EV chargers in EV charger network 104 that are available to charge users’ EVs for the time frame. Upon receiving such messages, the users may move their EVs to EV chargers in the EV charger network 104 for charging for the time frame based on which the messages were sent. Thus, the charging management server 102 may generate, maintain, and use a prioritized queue to select users to charge their vehicles to travel to high priority events.

[0053] FIG. 2 shows a sequence diagram of a sequence 200 for electronic calendar integration into an EV charging network, according to one embodiment. In the sequence 200, a charging management server 202 (e.g., charging management server 102, shown and described with reference to FIG. 1) may communicate with computing devices 204 and 224 as well as EV chargers 208, 210, and 212. The charging management server 202 may do so to manage an EV charging network of a group entity or a building so users (e.g., employees) of the group entity or building can charge their EVs such that they can travel to events that are designated in their electronic calendars.

[0054] The charging management server 202 may communicate with a charging application 214 of the computing device 204. The charging application 214 may operate as an intermediate application between the charging management server 202 and a calendar application 216 of the computing device 204. The charging application may 214 may retrieve event data from the calendar application 216 for a user associated with the computing device 204. For instance, the computing device 204 may be a user’s mobile phone and the calendar application 216 may store an electronic calendar 218 that contains data and metadata for different events the user is scheduled to attend throughout different time periods (e.g., days, weeks, months, years, etc.). The charging application 214 may request event data and metadata from the calendar application 216. In response to the request, the calendar application 216 may retrieve data from the electronic calendar 218 regarding different events such as the names of the events, the locations of the events, the individuals that are scheduled to attend the events (e.g., the email addresses and/or names of such individuals), the times of the events, etc. The calendar application 216 may then transmit the event data and metadata to the charging application 214. The charging application 214 may receive the event data and metadata and forward the data to the charging management server 202.

[0055] Upon receiving the event data and metadata, the charging management server 202 may calculate a charge priority score for one or more of the events. The charging management server 202 may calculate the charge priority score by calculating an average, weighted average, aggregation, or any other operation on values representing the event metadata for the event. In some cases, the charging management server 202 may retrieve other data about the event and/or the individuals scheduled to attend the event from an external database and calculate the charge priority score based further on the externally retrieved data.

[0056] The charging management server 202 may calculate a time frame that an EV 220 associated with the user needs to begin charging to ensure the EV 220 can travel to the event. The charging management server 202 may calculate a duration of the time frame based on the state of charge (or predicted state of charge) of the EV 220, the amount of charge that is needed to travel from the location L0 of an EV charger that will be used to charge the EV 220 to the event, and/or the charge rate of the EV charger. The charging management server 202 may also calculate the time the time frame will begin such that the EV will be sufficiently charged and have enough time to travel to the event at the end of the time frame.

[0057] The charging management server 202 may calculate a charge priority for the event or time frame. To do so, the charging management server 202 may identify the charge priority scores with time frames that overlap with the event. The management server 202 may compare the charge priority scores and determine the priorities in descending or ascending order such that the time frames or events with the highest priority scores have the highest charge priorities. [0058] The charging management server 202 may set the charge priority for the event in a profile for an EV charger designated to charge an EV of the user or in a profile of the user. The charging management server 202 may do so by inserting a value of the charge priority in the respective profile.

[0059] In embodiments in which the charging management server 202 sets the priorities into profiles of EV chargers, the charging management server 202 may retrieve the priorities from the profiles of the EV chargers. The charging management server 202 may compare the priorities. The charging management server 202 may determine the priority for the EV charger 212 is the highest of the priorities. Accordingly, the charging management server 202 may send instructions to EV charger 212 to charge the EV 220 for the time frame instead of to the EV charger 210 to charge the EV 222. In some embodiments, the charging management server 202 may identify the EV charger 212 that is associated with the user profile (e.g., from an identification of the EV charger in the user profile) and transmit instructions to charge the EV 220.

[0060] In embodiments in which the charging management server 202 sets the priorities into user profiles of users. The charging management server 202 may retrieve and compare the priorities and identify the user profile that is associated with the highest priority. In some embodiments, the charging management server 202 may retrieve contact information from the user profile and transmit a message to a computing device 224 of a user 226 associated with the user profile to move an EV 228 associated with the user 226 to an EV charger for charging.

[0061] FIG. 3 shows a diagram of a system 300, according to one embodiment, with a power grid 302 (illustrated as a dashed-line box) that may be connected to a network of charging stations 304 (illustrated as a dashed-line box). In some embodiments, the network of charging stations 304 may provide electric charge (or electric power, or electric energy) to at least one electric vehicle 305 (EV 305). FIG. 3 may be described in the context of FIGs. 1 and 2. As such, the EV 305 may be similar to, or the same as, the EVs 124, 126, 128, or 130, of FIG. 1 and/or the EVs 220, 222, or 228 of FIG. 2. The power grid 302 may be similar to, or the same as, the power grid 122 of FIG. 1.

[0062] In some embodiments, the power grid 302 may be a local (e.g., county, city) power grid, a regional (e.g., Southern Idaho) power grid, a state-wide (e.g., Utah) power grid, a country-wide (e.g., United States of America) power grid, a continent-wide (e.g., Continental Europe, North America) power grid, and/or so forth. In some embodiments, the power grid 302 may be privately-owned (e.g., a privately-owned company, a privately-owned corporation, a publicly-traded corporation), government-owned, privately-owned and government-regulated, government-owned and internationally-regulated, privately-owned and internationally-regulated, and/or a combination thereof. In some embodiments, the regulations may include voltage(s), current(s), phase(s), grid protection, system protection, electric energy rates (e.g., cost), equipment protection, power industry employee protection, consumer protection, environmental protection, and/or other regulations defined by local, regional, country, international, power industry, and/or so forth entities. In some embodiments, the regulations may include an amount of a power generation capacity, energy trading, and/or an amount of power consumption (e.g., power demand, power load capacity). [0063] Power generation may utilize renewable and/or nonrenewable energy sources. Examples of renewable energy sources include solar energy from the Sun, geothermal energy from heat inside the Earth, wind energy, biomass from plants, hydropower from flowing water, and/or so forth. On the other hand, nonrenewable energy sources include petroleum, hydrocarbon gas liquids, natural gas, coal, nuclear energy, and/or so forth.

[0064] In some aspects, renewable energy sources may be more desirable than nonrenewable energy sources because, by definition, the nonrenewable energy sources are limited (e.g., with an end-of-life). On the other hand, the renewable energy source may be utilized nearly perpetually, according to some embodiments. However, using certain energy sources to produce electricity may have certain drawbacks regarding worker conditions (e.g., safety), greenhouse gases, generation capacity, baseload capacity, overall power load capacity, cost of producing electric energy, environmental impact (e.g., air quality, waste, mining), geographic availability, scarcity (e.g., nonrenewable energy sources), and/or so forth.

[0065] In some embodiments, using renewable (e.g., hydropower, solar, biomass, geothermal, wind, etc.) and/or nonrenewable (e.g., nuclear) energy sources to produce electric energy may lower the amount of greenhouse gases released in the atmosphere.

[0066] In some embodiments, using only solar energy and/or wind energy to produce electric energy may not meet a desired baseload capacity of the power grid 302, where the desired baseload capacity is a minimum level of power demand on the power grid 302 over a duration of time, for example, one day, one week, one month, one year, and/or so forth. Consequently, relying only on solar energy and/or wind energy to produce electric power may cause blackouts and/or brownouts of the power grid 302, unless, for example, excess electric energy is stored to be used when solar energy is not available (e.g., during nighttime) and/or when wind energy is not available. [0067] In some embodiments, shifting from nonrenewable energy sources (e.g., coal) to renewable energy sources (e.g., wind energy, solar energy) to produce electric energy may temporarily increase electric energy rates. Nevertheless, when using renewable energy sources to produce electric energy, the electric energy rates may decrease over time. For example, a levelized cost of energy (LCOE) of a solar-powered power plant may be lower than the LCOE of a coal-powered power plant. Note that the LCOE is a measure of the average net present cost of electricity for a power plant over a lifetime of the power plant.

[0068] In some embodiments, using renewable and/or nonrenewable sources for producing electric energy may lower the greenhouse gases while meeting the desired baseload of the power grid 302. For example, using hydropower, a renewable energy source, and/or using e energy, a nonrenewable energy source, to produce electric energy may lower the greenhouse gases and may meet the desired baseload of the power grid 302. However, in one aspect, using hydropower may have an adverse environmental impact on wildlife (e.g., fish), rivers, and/or humanity (e.g., building large dams may displace towns and/or villages). Also, unfortunately, accidents involving nuclear energy may have devastating effects on humanity, the environment, and/or the wildlife. Further, currently, only select countries have adequate resources (e.g., nuclear material, nuclear engineers and/or scientists) to use nuclear energy to produce electric energy.

[0069] In some embodiments, an availability of a type of energy source (e.g., renewable and/or nonrenewable) may limit the use of such type of energy source for producing electric energy. For example, Norway receives less solar energy than Egypt; therefore, Norway may not be able to produce enough electric energy by using solar energy to meet the desired baseload of a power grid (e.g., 302). Therefore, in addition to, or alternatively of, the solar energy, Norway may use another energy source to produce enough electric energy to meet the desired baseload.

[0070] In some embodiments, it is desirable to use energy sources that lower the electric energy rates, lower the impact on the environment, lower greenhouse gases, are plentiful, are renewable, and/or pose little danger to humanity. To this end, this disclosure focuses on meeting some of these desirable usages of the energy sources for charging EVs, as is further described below. However, the techniques and systems described herein are not limited to transportation needs and/or charging EVs.

[0071] Continuing with the power grid 302, a utility company may purchase (e.g., in an energy marketplace) and/or generate electric energy using at least one power plant(s) 306 (power plant 306). The power plant 306 may be centralized (e.g., in a particular location), decentralized in various locations, and may utilize renewable and/or nonrenewable energy sources to produce electric energy. The power plant 306 may generate a first electric power 308 (electric power 308). The utility company may then utilize at least one first transformer(s) 310 (transformer 310) to transform the electric power 308 to a second electric power 312 (electric power 312). The electric power 312 may have an accompanying set of characteristics, such as an alternating current (AC) power with three phases that is transmitted using a high voltage line and/or an extremely-high voltage line (e.g., for voltages 50,000 V to 200,000 V), and/or other characteristics. In some embodiments, the electric power 312 may be part of a transmission network (not explicitly illustrated in FIG. 3). The transmission network may be regulated by local, regional, country, international, power industry, and/or other entities. It is to be understood, however, that for the high voltage lines and/or the extremely-high voltage lines, some regulations may allow transmission of the AC power, a direct current (DC) power, and/or a combination thereof that may be referred to as “hybrid” power.

[0072] In some embodiments, the power grid 302 uses the electric power 312 for transmitting electric power over a first range of distances, for example, from a country to another country, from a state to another second state, from a region to another second region, from a city to another city, and/or so forth.

[0073] In some embodiments, the power grid 302 may also include at least one second transformer(s) 314 (transformer 314) to transform the electric power 312 to a third electric power 316 (electric power 316). The electric power 316 may have another accompanying set of characteristics, such as an AC power with three phases transmitted using a medium voltage line (e.g., for voltages 1,000 V to 50,000 V) and/or other power characteristics. In some embodiments, the electric power 316 may be part of a distribution network (not explicitly illustrated in Figure 3). For example, the distribution network may provide the electric power 316 to a small country, a small principality, a small city-state, a small state, a county, a municipality, a city, a town, a village, and/or so forth.

[0074] Given that the baseload of the power grid 302 may change over a duration of time, for example, one day, one week, one month, one year, and/or so forth, the utility company may also utilize a first peaking power plant(s) 318 (peaking power plant 318) and/or a second peaking power plant(s) 320 (peaking power plant 320) during a high power consumption, a high power demand, a high power load, and/or a peak power load. For example, the high power load may be during a particular time duration or period of a weekday, such as Monday through Friday from 7:00 AM to 9:00 AM, when some residents get ready for work; Monday through Friday from 5:00 PM to 7:00 PM, when the some residents come back from work; and/or so forth. As another example, the high power load may be during a certain period of a year, for example, at the end of July, when some farmers may increase the use of water pumps to water their crops and/or so forth.

[0075] In some embodiments, the peaking power plant 318 may generate a fourth electric power 322 (electric power 322). The utility company may then use at least one third transformer(s) 324 (transformer 324) to transform the electric power 322 to the electric power 312. Therefore, the power grid 302 may utilize the peaking power plant 318 to supply electric power to the transmission network.

[0076] In some embodiments, the peaking power plant 320 may generate a fifth electric power 326 (electric power 326). The utility company may then use at least one fourth transformer(s) 328 (transformer 328) to transform the electric power 326 to the electric power 316. Therefore, the power grid 302 may utilize the peaking power plant 320 to supply electric power to the distribution network.

[0077] Although not illustrated in FIG. 3, the distribution network of the power grid 302 may also include other transformers to transform the electric power 316 to other electric powers having, for example, lower voltages, and/or sometimes fewer phases (e.g., two phases, one phase) to supply electric power to various establishments. The various establishments may include charging stations, residential homes, apartment complexes, offices, stores, educational institutions, government buildings, factories, and/or so forth.

[0078] Generally, utility-scale generation, storage, transmission, and/or distribution of electric power may be referred to as a front-of-the-meter (FTM) electric power (and/or FTM electric energy). Therefore, as is illustrated in FIG. 3, the electric power (e.g., 308, 312, 316, 322, 326) of the power grid 302 may be referred to as an FTM electric power. Energy rates of the FTM electric power may change depending on an amount of electric power used by an establishment during a time of a day, a day of a week, a month of a year, and/or any combination thereof. For example, an establishment may pay a first energy rate for a first amount of the FTM electric power (e.g., the first 400 kWh), a second energy rate for a second amount of the FTM electric power (e.g., 400 kWh to 800 kWh), and/or a third energy rate for a third amount of the FTM electric power (e.g., over 800 kWh), wherein the third energy rate may be higher than the second energy rate, and the second energy rate may be higher than the first energy rate. As another example, an establishment may pay a fourth energy rate of the FTM electric power during non-peak power load hours (e.g., at 11 :00 AM) and a fifth energy rate of the FTM electric power during peak power load hours (e.g., 7:00 AM to 9:00 AM, 5:00 PM to 7:00 PM), wherein the fifth energy rate may be higher than the fourth energy rate. As yet another example, an establishment may pay a sixth energy rate of the FTM electric power during a month of a year (e.g., March) and a seventh energy rate of the FTM electric power during another month of the year (e.g., July), wherein the seventh energy rate may be higher than the sixth energy rate.

[0079] Fortunately, the various establishments, including charging stations of the network of charging stations 304, are increasingly utilizing renewable energy sources to generate electric energy, in part, to reduce their greenhouse gas emissions and/or carbon (e.g., CO2) footprints and to lower their cost of electric power. Alternatively, or in addition, the charging stations may also utilize nonrenewable energy sources (e.g., fossil fuels) to generate electric energy, for example, for backup generation in cases of blackouts, brownouts, and/or staying “off the grid.” The electric energy and/or electric power generated by the charging stations of the network of charging stations 304 may be referred to as a behind-the-meter (BTM) electric power (and/or BTM electric energy).

[0080] In aspects, BTM resources (e.g., solar panels, on-site batteries) may be distributed energy resources (DERs). In addition to the network of charging stations 304, the BTM resources may provide numerous benefits to communities and other establishments because they may help provide alternative means to using peaking power plants (e.g., 318, 320). Specifically, the peaking power plants 318 and 320 may be costly to operate, and the utility company may transfer operating costs to establishments with BTM resources and/or without BTM resources. Therefore, even establishments without BTM resources may benefit from less usage of the peaking power plants 318 and 320. Further, the peaking power plants 318 and 320 may use fossil fuels (e.g., natural gas) that increase greenhouse gases emitted to the atmosphere. To this end, numerous entities (e.g., countries, states, cities) may offer incentives (e.g., financial incentives) to the network of charging stations 304 to increase the BTM resources. The incentives may include lower borrowing rates to build more BTM resources, monetary credits for using less FTM electric power, carbon credits, ease of integrating BTM-generated electric power to the power grid 302, and/or other incentives.

[0081] In some embodiments, the power grid 302 may partly support a decentralized system of generating and/or transferring electric power, whether the electric power is an FTM electric power and/or a BTM electric power. However, sustaining a stable power grid (e.g., without blackouts and/or brownouts) poses some challenges. One of many challenges may include storing a decentralized energy. In some embodiments, the decentralized energy may be stored in various forms, including chemically, potentially, gravitationally, electrically, thermally, and/or kinetically. For example, the network of charging stations 304 may use batteries (e.g., lithium-ion batteries) to store electric energy (electric charge) generated during the daytime using solar panels. EVs (e.g., 306) can then use the stored energy in the batteries of the charging stations during nighttime, peak power load hours, and/or anytime when necessary.

[0082] FIG. 3 also illustrates how the network of charging stations 304 may utilize the BTM and/or the FTM electric power to charge the EVs (e.g., EV 305), according to some embodiments. The network of charging stations 304 may include two (e.g., FIGs. 1 and 2) or more (e.g., FIG. 3) charging stations. FIG. 3 illustrates that the network of charging stations 304 includes a first charging station 330 (charging station 330), a second charging station 332 (charging station 332), a third charging station 334 (charging station 334), and a fourth charging station 336 (charging station 336).

[0083] As is illustrated in FIG. 3, the charging station 330 is coupled to the power grid 302 using an accompanying power meter 330-1. The charging station 332 is coupled to the power grid 302 using an accompanying power meter 332-1. The charging station 334 is coupled to the power grid 302 using an accompanying power meter 334-1. Lastly, the charging station 336 is not coupled to the power grid 302; therefore, the charging station 336 is off the grid.

[0084] Since typically, utility companies own the power meters, therefore, the power meters 330-1, 332-1, and 334-1 are illustrated as being inside the power grid 302. Nevertheless, as it will become apparent, the power meters (330-1, 332-1, and 334-1) delineate the FTM electric power from the BTM electric power. Therefore, even though not illustrated as such in FIG. 3, in one aspect, the power meters 330-1, 332-1, and 334-1 may define a separation (e.g., an abstract electric power border) of the power grid 302 from the network of charging stations 304, and the FTM electric power from the BTM electric power.

[0085] In some embodiments, the charging stations (e.g., 330 to 336) may supply electric power using different charging speeds. For example, a charging station in a location may be capable of supplying a first amount of electric charge and/or electric power (e.g., 3 kW) during a first duration of time (e.g., one hour). As another example, another charging station in another location may be capable of supplying a second amount of electric charge and/or electric power (e.g., 40 kW to 50 kW) during a second duration of time (e.g., 30 minutes). Differently stated, the first amount of electric charge during the first amount of time may be a faster charging time for a same electric charge compared to the second amount of electric charge during the second amount of time. Understandably, a driver of the EV 305 prefers to spend as little time as possible at a charging station (e.g., 330 to 336).

[0086] In some aspects, charging speeds may depend on an input AC power at a charger and an ability of an AC-to-DC converter to convert the AC power to DC power to charge a battery of the EV 305. For example, typically, home chargers utilize an AC power from the power grid 302, for example, the distribution network. Also, a relatively small transformer (e.g., a 15 kVA transformer, not illustrated) may transform the AC power from the distribution network (e.g., 316) to a home with the home charger. The relatively small transformer, however, supplies an AC power with a relatively low AC current. Further, an EV 305 may use an AC-to-DC converter located inside the EV (e.g., an onboard charger) to charge a battery of the EV 305. Due to physical constraints, the onboard AC-to-DC converter of the EV 305 is relatively small. Therefore, the charging speed of the home charger is relatively low. This home-style charging approach works well if a driver (e.g., owner, family member, an authorized person to charge) of the EV 305 spends a considerable amount of time (e.g., multiple hours) to charge the battery of the EV 305 while they may be doing something else (e.g., sleeping). This home-style charging approach, however, may not be convenient to be used in charging stations.

[0087] To lower time spent at a charging station, charging stations 330 to 336 offer higher charging speeds than home chargers. Further, the charging stations 330 to 336 may offer different charging speeds. In some aspects, the charging speeds of the charging stations 330 to 336, in part, may depend on whether the charging stations are AC charging stations or DC charging stations. The AC charging stations may operate similarly to the home charger and may utilize the onboard AC-to-DC converter of the EV 305. However, the AC charging stations can usually supply a higher AC current than the home charging station, for example, by using a bigger than 15 kVA transformer to receive power from the power grid 302. Therefore, the AC charging stations can often charge the battery of the EV 305 faster than the home charging stations. To increase the charging speeds even further, the DC charging stations utilize DC charging. To do so, the DC charging stations perform an AC-to-DC power conversion before power enters the EV 305. Therefore, the DC charging stations may have an on-site AC-to-DC converter, which enables the DC charging station to bypass the onboard AC-to-DC converter of the EV 305 and charge the battery of the EV 305 directly. Regardless, the AC and the DC charging stations have a considerable associated cost to produce, install, and operate the charging stations.

[0088] In some embodiments, the operating costs of the charging stations 330 to 336 partly depend on the electric energy rates of the FTM electric power. For example, assume the charging station 330 does not have BTM resources. As such, the charging station 330 may rely solely on the AC power of the power grid 302 to supply electric charge to the EV 305. Consequently, depending on the time of the day, the day of the week, or the month of the year, a driver of the EV 305 may pay different electric energy rates that may increase a cost to charge and/or to operate (e.g., drive) the EV 305. Furthermore, as is illustrated in FIG. 3, power flow concerning the charging station 330 is unidirectional, from the power grid 302 to the power meter 330-1.

[0089] In some embodiments, the charging station 332 includes a BTM resource. Specifically, the charging station 332 may include an associated storage device 332-2 (storage device 332-2) and an on-site AC-to-DC converter (not illustrated) to charge the storage device 332-2 (e.g., an on-site battery). In addition, or alternatively, the on-site AC-to-DC converter may provide DC power to the EV 305, increasing the charging speed. The charging station 332, however, does not include BTM resources that generate electric power (e.g., solar panels). Therefore, like the charging station 330, power flow regarding the charging station 332 is unidirectional, from the power grid 302 to the power meter 332-1, as illustrated in FIG. 3. Further, unlike the charging station 330, the charging station 332 can use the storage device 332-2 to supply electric power to the EV 305 during, for example, peak power load hours, avoiding higher electric energy rates. In one aspect, the charging station 332 may be configured to charge the storage device 332-2 during non-peak load hours and use the stored energy (or charge) in the storage device 322-2 to supply electric power to the EV 305 during the peak power load hours.

[0090] In some embodiments, the charging station 334 includes BTM resources. For example, the charging station 334 includes an associated energy storage device 334-2 (storage device 334-2) and an on-site AC-to-DC converter (not illustrated) to charge the storage device 334-2. In addition, or alternatively, the on-site AC-to-DC converter can provide DC power to the EV 305, increasing the charging speeds. As another example, the charging station 334 may also include an associated energy generating device 334-3 (energy generating device 334-3). The energy generating device 334-3 may utilize renewable (e.g., solar) and/or renewable (e.g., petroleum) energy sources. Unlike the charging stations 330 and 332, power flow regarding the charging station 334 may be bidirectional, from the power grid 302 to the power meter 334-1 and/or from the power meter 334-1 to the power grid 302, as is illustrated in FIG. 3. It may be assumed that the network of charging stations 304 strives to lower the amount of greenhouse gases released to the atmosphere; to this end, the energy generating device 334-3 may include solar panels. In some aspects, the charging station 334 is configured to supply energy generated from the solar panels (e.g., 334-3) to the power grid 302, the storage device 334-2, and/or the EV 305. DERs, such as a combination of energy generating devices (e.g., 334-3) and energy storage devices (e.g., 334-2), may enable the charging station 334 to decrease the amount of the FTM power used to charge the EV 305; off-set the amount of the FTM power used to charge the EV 305 during, for example, peak power load hours; use mainly the BTM power to charge the EV 305 and supply excess BTM power to the power grid 302; and/or any combination thereof. Further, the storage device 334-2 and the energy generating device 334-3 may increase a power load capacity at the charging station 334.

[0091] In some embodiments, the network of charging stations 304 may also include the charging station 336, which, as is illustrated in FIG. 3, is not coupled to the power grid 302 (e.g., off the grid). The charging station 336 may also include an associated storage device 336-1 (storage device 336-1) and an associated energy generating device 336-2 (energy generating device 336-2). Depending on a type of energy generating device, the energy generating device 336-2 may generate AC or DC power. If the energy generating device 336- 2 generates AC power, the charging station 336 may also include an on-site AC-to-DC converter (not illustrated) to charge the storage device 336-1. In addition, or alternatively, the on-site AC-to-DC converter can provide DC power to the EV 305, increasing the charging speed. Advantages of using off-the-grid charging stations include an independence from the power grid 302. The independence from the power grid 302 allows the network of charging stations 304 to build at least one charging station off the grid, for example, in a remote location without FTM electric power. Also, in such a case, a cost of electric energy is independent of the FTM electric power. Therefore, all power associated with the charging station 336 is BTM electric power.

[0092] In some embodiments, the network of charging stations 304 may also utilize a power load capacity algorithm to measure, monitor, and/or predict the power load capacity of at least one location (e.g., the location of the charging station 334). To predict the power load capacity, the algorithm may use data of FTM power and BTM power availability at the location of the charging station 334. In one aspect, the network of charging stations 304 (e.g., utilizing the power load capacity algorithm) may predict the FTM power availability at the charging station 334 by considering the size of the transformer (not illustrated) used to supply AC power from the power grid 302 to the charging station 334. In one aspect, the network of charging stations 304 may communicate with the utility company to gather FTM electric power data. The FTM electric power data may be communicated in real-time or at time intervals. In one aspect, the network of charging stations 304 may predict the BTM power availability by considering past measurements and/or current measurements of electric energy produced and/or stored using the BTM resources (e.g., 334-2, 334-3) at the charging station 334, for example, during a time of a day, a day of a week, a week of a month, a month of a year, meteorological events (e.g., a cloudy day, a rainy day, a clear and sunny day), and/or so forth. Next, this disclosure partly describes techniques and/or apparatuses used by the system 100 of FIG. 1 and/or the network of charging stations 304 of FIG. 3 to increase revenue, incentivize virtuous driving behavior (e.g., promote carpooling, ridesharing), lower greenhouse gases, lower energy rates, and help a community.

[0093] FIG. 4 illustrates a diagram 400 of a model 402 that can be used to selectively enable a first or a second charging station of at least two charging stations to charge one or more EVs, according to one embodiment. The model 402, may be a machine learning model or artificial intelligence model (e.g., a neural network, random forest, support vector machine, clustering model, etc.), a rule-based model, an analytical model, etc., that is configured to generate a charge priority score for EVs in a system (e.g., the system 100). As is described herein, such a charge priority score may enable a processor to calculate priorities that can be used to selectively charge EVs such that the users associated with the EVs can travel to events scheduled on their electronic calendars.

[0094] The model 402 may analyze and/or use one or more inputs 404 to 418 to generate an output 420. The one or more inputs 404 to 418 may be characteristics of an event that is scheduled on a user’s electronic calendar. For instance, the one or more inputs 404 to 418 may include data such as titles of individuals scheduled to meet with the user at the event (or otherwise scheduled to attend the same event), a job title of the user, a value associated with the event, value’s associated with group entities associated with the event, a distance to the event, etc. Each or a portion of these values may be concatenated or inserted into a single feature vector that can be used as input into the model 402.

[0095] The model 402 may output a charge priority score as the output 420 based on the inputs 404 to 418 in the input feature vector. For instance, the model 402 may be trained to contain a series of weights, functions, and/or parameters to output charge priority scores for different events. The model 402 may receive the inputs 404 to 418 as numerical values and apply the series of weights, functions, and/or parameters to the inputs 404 to 418 to calculate a charge priority score for the event.

[0096] A computer (e.g., the charging management server 102, shown and described with reference to FIG. 1) may execute the model 402 and receive the output charge priority score. The computer may then compare the output charge priority to similarly calculated charge priority scores associated with other events and that are associated with the same time frame (e.g., have overlapping times with the same time frames or units). The computer may calculate a charge priority for the event based on the charge priority score for the event compared with charge priority scores of the other events that are associated with the same time frame. [0097] FIG. 5 is a flow diagram of a process 500 for selectively enabling a charging station to charge an EV, according to one embodiment. The process 500 can be performed by a data processing system (a client device or the charging management server 102, shown and described with reference to FIG. 1, a server system, etc.). The process 500 may include more or fewer operations and the operations may be performed in any order. Performance of the process 500 may enable the data processing system to manage an EV charging network to prioritize charging of EVs such that the EVs are sufficiently charged to travel to high priority events. In brief overview, the data processing system may use event data and event metadata retrieved from users’ electronic calendars to determine when the users are scheduled to attend events. The data processing system may then use the metadata to determine which events are the most important to be attended. The data processing system may then assign priorities to user profiles and/or EV chargers associated with the users to enable the EV chargers to charge the EVs of users associated with the highest priority to travel in their EVs to the events. Performance of the process 500 may enable the data processing system to manage an EV charging network when there is a limited amount of power available, such as when the EV charging network relies on renewable energy or a power grid does not allocate an unlimited amount energy to the EV charging network.

[0098] At stage 502, the data processing system may receive event data and event metadata of an event. The event data may include information such as a name or time (e.g., time period or beginning time) of the event. The event metadata may include other information about the event, such as the event’s location, the individuals attending the event, the titles of the individuals attending the event, the value of the event, group entities associated with the event, values of the group entities attending the event, etc.

[0099] The data processing system may receive the event data and event metadata from an application executing on a computing device associated with a user. The application may retrieve the data from a calendar application operating on the same device that stores such event data for the user in an electronic calendar (e.g., a data file that contains an event schedule with data for the individual events on the event schedule).

[0100] At stage 504, the data processing system may calculate a charge priority score for the event. The data processing system may calculate the charge priority score using analytical, rule, or machine learning-based techniques on the event metadata the data processing system received from the application. For example, the data processing system may calculate the charge priority score based on the titles of the individuals attending the event, including the title of the user him or herself and/or the titles of individuals that are scheduled to attend the same event as the user. The data processing system may calculate the charge priority based on any type of event metadata (e.g., values of the event, the group entities associated with the event, values associated with the group entities, etc.).

[0101] The data processing system may also calculate a time frame prior to the event. The time frame may be a charging time frame indicating a specific time period, including a duration, to charge an EV associated with the user that will take the user to the event. The data processing system may calculate the duration of the time period as the time it will take for an EV charger associated with the user and/or the EV to charge the EV such that the EV can travel to the event. The data processing system may calculate the time frame (e.g., the beginning time and/or end time of the time frame) such that there is time for the EV to travel to the event and arrive on time or a predefined amount of time before the start of the event.

[0102] At stage 506, the data processing system may set a charge priority of an EV charger or a user profile for the time frame. To do so, the data processing system may first calculate the charge priority for the event compared to other events with charge time frames that occur at overlapping times. The data processing system may compare the charge priority scores of the different events and determine charge priorities (e.g., values) for the events in ascending or descending order based on the charge priority scores.

[0103] Upon calculating the charge priority for the event, the data processing system may insert the charge priority into a profile for an EV charger associated with the user (e.g., an EV charger dedicated to charging the user’s EV) or into a user profile of the user. The data processing system may identify the profile for the EV charger or the user profile and insert the charge priority for the event into the identified profile.

[0104] At stage 508, the data processing system may transmit instructions to the EV charger for the EV charger to charge an EV associated with the user and connected to the EV charger. The data processing system may transmit the instructions to the EV charger responsive to determining the charge priority for the user profile or the EV charger exceeds a charge priority for the same time frame of another user profile or EV charger. For example, the data processing system may have a limited amount of energy available to supply to an EV charger network in a commercial complex with EVs connected to multiple EV chargers of an EV charger network. For the time frame, the data processing system may use a charge priority of a user profile or an EV charger within the EV charger network to determine which EV chargers to enable charging. The data processing system may identify an EV charger based on the EV charger being associated with the highest priority for the time frame and transmit instructions to the EV charger to charge an EV connected to the EV charger. Thus, the user associated with the EV connected to the EV charger may travel to the high priority event identified on the user’s electronic calendar while the EVs of users scheduled to attend the lower priority events may not receive any charge.

[0105] FIG. 6 is a flow diagram of another process 600 for selectively enabling a charging station to charge an EV, according to one embodiment. The process 600 can be performed by a data processing system (a client device or the charging management server 102, shown and described with reference to FIG. 1, a server system, etc.). The process 600 may include more or fewer operations and the operations may be performed in any order. Performance of the process 600 may enable the data processing system to manage an EV charging network to prioritize charging of EVs in a prioritized queue. In the process 600, profiles of users may be assigned different charging priorities for charging for a specific time frame. The profiles may be assigned such charging priorities based on event metadata of events that users are scheduled to attend. The data processing system may identify the highest priority profiles in the queue and transmit messages to the computing devices associated with the profiles indicating for the users associated with the profiles to move their vehicles to be charged by the EV charging network. Performance of the process 600 may enable the data processing system to selectively charge EVs based on event data when there are not enough EV chargers in the EV charging network to charge every EV that is associated with the EV charging network.

[0106] At stage 602, the data processing system may receive event data and event metadata of an event. At stage 604, the data processing system may calculate a charge priority score a time frame prior to the event. At stage 606, the data processing system may set a charge priority of a user for the time frame based on the charge priority score. The data processing system may perform the operations in stages 602 to 606 in the same or a similar manner to the manner described with respect to stages 502-506, described with reference to FIG. 5.

[0107] At stage 608, the data processing system may transmit a message to a mobile device associated with the user. The message may indicate to move an EV associated with the user to an EV charger. The message may indicate to move the EV for the calculated time frame. In some instances, the data processing system may transmit the message in response to determining a priority of a user profile of the user is higher than a priority of another user profile for the time frame. In this way, the data processing system may manage a prioritized queue for charging EVs in an EV charging network.

Example Embodiments

[0108] Example 1. A method of a charging management server, comprising: receiving, by a charging management server from an application executing on a computing device associated with a user, event data comprising a time of an event and event metadata comprising one or more characteristics of the event; calculating, by the charging management server, a charge priority score for a time frame prior to the time of the event based on the one or more characteristics of the event; setting, by the charging management server, a first charge priority of a first electric vehicle (EV) charger associated with the user or a profile of the user, the first charge priority for the time frame prior to the time of the event, the setting of the first charge priority based on the charge priority score compared to charge priority scores of one or more second EV chargers or second user profiles; and responsive to the first charge priority exceeding a second charge priority of a second EV charger or a second user for the time frame, transmitting, by the charging management server to the first EV charger, instructions to charge an EV connected to the first EV charger.

[0109] Example 2. The method of Example 1, further comprising: identifying, by the charging management server, a plurality of charge priorities of a plurality of EV chargers or user profiles for the time frame, the plurality of charge priorities comprising the first charge priority; comparing, by the charging management server, the plurality of charge priorities between each other; and identifying, by the charging management server, the first charge priority responsive to the first charge priority having a highest value of the plurality of charge priorities.

[0110] Example 3. The method of Example 1, wherein receiving the event metadata comprises receiving, by the charging management server, a title of an individual associated with the event; and wherein calculating the charge priority score comprises calculating, by the charging management server, the charge priority score based on the title of the individual linked to the event.

[0111] Example 4. The method of Example 3, wherein receiving the title of the individual associated with the event comprises receiving, by the charging management server, a job title of the user.

[0112] Example 5. The method of Example 3, wherein receiving the title of the individual associated with the event comprises receiving, by the charging management server, a job title of an entity scheduled to meet with the user at the event.

[0113] Example 6. The method of Example 1, wherein the application executing on the computing device is configured to communicate with a calendar application stored in memory of the computing device, and wherein the application is configured to retrieve the event data for the event from the calendar application. [0114] Example 7. The method of Example 6, wherein the application executing on the computing device is configured to retrieve the event data for the event responsive to the event having a stored association with a flag indicating the user will travel to the event in the EV.

[0115] Example 8. The method of Example 1, further comprising: identifying, by the charging management server, an event location of the event and a charger location of the first EV charger; calculating, by the charging management server, a distance between the event location and the charger location; calculating, by the charging management server, a duration of the time frame based on the calculated distance and a charge speed of the first EV charger; and setting, by the charging management server, the time frame based on the calculated duration and the time of the event.

[0116] Example 9. The method of Example 8, further comprising: transmitting, by the charging management server, the time frame to the application executing on the computing device, receipt of the time frame causing the application to add a calendar entry indicating the time frame to a calendar application stored in memory of the computing device.

[0117] Example 10. The method of Example 8, wherein the time is a first time, and further comprising: predicting, by the charging management server, a state of charge of an energy storage device of the EV for one or more times of a time period prior to the first time, wherein calculating the duration of the time frame comprises calculating, by the charging management server, the duration of the time frame based on the predicted state of charge of the energy storage device of the EV for the one or more times.

[0118] Example 11. The method of Example 10, wherein predicting the state of charge of the energy storage device comprises: receiving, by the charging management server from the application, second event data comprising a plurality of times of a plurality of events prior to the time and location data of the plurality of events; calculating, by the charging management server, an energy usage of the EV based on the plurality of times and the location data; and subtracting, by the charging management server, energy usage from an initial state of charge of the EV.

[0119] Example 12. The method of Example 8, wherein receiving the event metadata comprising one or more characteristics of the event comprises receiving, by the charging management server, the event location of the event.

[0120] Example 13. The method of Example 1, wherein receiving the event metadata comprises receiving, by the charging management server, a value associated with the event; and wherein calculating the charge priority score comprises calculating, by the charging management server, the charge priority score based on the value. [0121] Example 14. A system for charging a management server, comprising one or more processors coupled with memory, the one or more processors configured to: receive, from an application executing on a computing device associated with a user, event data comprising a time of an event and event metadata comprising one or more characteristics of the event; calculate a charge priority score for a time frame prior to the time of the event based on the one or more characteristics of the event; set a first charge priority of a first electric vehicle (EV) charger associated with the user or a profile of the user, the first charge priority for the time frame prior to the time of the event, the setting of the first charge priority based on the charge priority score compared to charge priority scores of one or more second EV chargers or second user profiles; and responsive to the first charge priority exceeding a second charge priority of a second EV charger or a second user for the time frame, transmit, to the first EV charger, instructions to charge an EV connected to the first EV charger.

[0122] Example 15. The system of Example 14, wherein the one or more processors are further configured to identify a plurality of charge priorities of a plurality of EV chargers or user profiles for the time frame, the plurality of charge priorities comprising the first charge priority; compare the plurality of charge priorities between each other; and identify the first charge priority responsive to the first charge priority having a highest value of the plurality of charge priorities.

[0123] Example 16. The system of Example 14, wherein the one or more processors are configured to receive the event metadata by receiving a title of an individual associated with the event; and wherein the one or more processors are configured to calculate the charge priority score by calculating the charge priority score based on the title of the individual linked to the event.

[0124] Example 17. A method of a charging management server, comprising receiving, by a charging management server from an application executing on a computing device associated with a user, event data comprising a time of an event and event metadata comprising one or more characteristics of the event; calculating, by the charging management server, a charge priority score for a time frame prior to the time of the event based on the one or more characteristics of the event; setting, by the charging management server, a first charge priority of a profile of the user, the first charge priority for the time frame prior to the time of the event, the setting of the first charge priority based on the charge priority score compared to charge priority scores of one or more second user profiles; and responsive to the first charge priority exceeding a second charge priority of a second user for the time frame, transmitting, by the charging management server, a message to a mobile device associated with the user indicating to move an electric vehicle (EV) associated with the user to an EV charger. [0125] Example 18. The method of Example 17, further comprising: identifying, by the charging management server, a plurality of charge priorities of a plurality of EV chargers or user profiles for the time frame, the plurality of charge priorities comprising the first charge priority; comparing, by the charging management server, the plurality of charge priorities between each other; and identifying, by the charging management server, the first charge priority responsive to the first charge priority having a highest value of the plurality of charge priorities.

[0126] Example 19. The method of Example 17, wherein receiving the event metadata comprises receiving, by the charging management server, a title of an individual associated with the event; and wherein calculating the charge priority score comprises calculating, by the charging management server, the charge priority score based on the title of the individual linked to the event.

[0127] Example 20. The method of Example 19, wherein receiving the title of the individual associated with the event comprises receiving, by the charging management server, a job title of the user.

[0128] Example 21. A method, comprising receiving, by a server from an application executing on a computing device associated with a user, event data comprising a time of an event and event metadata comprising one or more characteristics of the event; responsive to identifying a flag in memory indicating to charge an EV for the event, determining, by the server for a time frame prior to the time of the event based on the one or more characteristics of the event, a first charge priority of a first electric vehicle (EV) charger associated with the user or a profile of the user, the first charge priority for the time frame prior to the time of the event; and based on the first charge priority, transmitting, by the server to the first EV charger, instructions to charge an EV connected to the first EV charger.

[0129] Example 22. A method comprising receiving, by a server from an application executing on a computing device associated with a user, event data comprising a time of an event and event metadata comprising one or more characteristics of the event; determining, by the server for a time frame prior to the time of the event based on the one or more characteristics of the event, a first charge priority of a first electric vehicle (EV) charger associated with the user or a profile of the user, the first charge priority for the time frame prior to the time of the event; and based on the first charge priority, transmitting, by the server to the first EV charger, instructions to charge an EV connected to the first EV charger.

[0130] Example 23. A method comprising receiving, by a server from an application executing on a computing device associated with a user, event data comprising a time of an event and event metadata comprising one or more characteristics of the event; determining, by the server for a time frame prior to the time of the event based on the one or more characteristics of the event, a first charge priority of a profile of the user, the first charge priority for the time frame prior to the time of the event; and based on the first charge priority, transmitting, by the server, a message to a mobile device associated with the user indicating to move an electric vehicle (EV) associated with the user to an EV charger.

[0131] The foregoing specification has been described with reference to various embodiments, including the best mode. However, those skilled in the art appreciate that various modifications and changes can be made without departing from the scope of the present disclosure and the underlying principles of the invention. Accordingly, this disclosure is to be regarded in an illustrative rather than a restrictive sense, and all such modifications are intended to be included within the scope thereof. Likewise, benefits, other advantages, and solutions to problems have been described above with regard to various embodiments. However, benefits, advantages, solutions to problems, and any element(s) that may cause any benefit, advantage, or solution to occur or become more pronounced are not to be construed as a critical, required, or essential feature or element.

[0132] As used herein, the terms “comprises,” “comprising,” or any other variation thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.

[0133] Embodiments herein may include various engines, which may be embodied in machine-executable instructions to be executed by a general-purpose or special-purpose computer (or other electronic device). Alternatively, the engine functionality may be performed by hardware components that include specific logic for performing the function(s) of the engines, or by a combination of hardware, software, and/or firmware.

[0134] Principles of the present disclosure may be reflected in a computer program product on a tangible computer-readable storage medium having stored instructions thereon that may be used to program a computer (or other electronic device) to perform processes described herein. Any suitable computer-readable storage medium may be utilized, including magnetic storage devices (hard disks, floppy disks, and the like), optical storage devices (CD-ROMs, DVDs, Blu-ray discs, and the like), flash memory, and/or other types of medium/machine readable medium suitable for storing electronic instructions. These instructions may be loaded onto a general-purpose computer, special-purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions that execute on the computer or other programmable data processing apparatus create means for implementing the functions specified. These instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means that implement the function specified. The instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified.

[0135] Principles of the present disclosure may be reflected in a computer program implemented as one or more software modules or components. As used herein, a software module or component may include any type of computer instruction or computer-executable code located within a memory device and/or computer-readable storage medium. A software module may, for instance, comprise one or more physical or logical blocks of computer instructions, which may be organized as a routine, a program, an object, a component, a data structure, etc., that perform one or more tasks or implement particular data types.

[0136] In certain embodiments, a particular software module may comprise disparate instructions stored in different locations of a memory device, which together implement the described functionality of the module. Indeed, a module may comprise a single instruction or many instructions, and may be distributed over several different code segments, among different programs, and across several memory devices. Some embodiments may be practiced in a distributed computing environment where tasks are performed by a remote processing device linked through a communications network. In a distributed computing environment, software modules may be located in local and/or remote memory storage devices. In addition, data being tied or rendered together in a database record may be resident in the same memory device, or across several memory devices, and may be linked together in fields of a record in a database across a network.

[0137] Suitable software to assist in implementing the invention is readily provided by those of skill in the pertinent art(s) using the teachings presented here and programming languages and tools, such as Java, JavaScript, Pascal, C++, C, database languages, APIs, SDKs, assembly, firmware, microcode, and/or other languages and tools. [0138] Embodiments as disclosed herein may be computer-implemented in whole or in part on a digital computer. The digital computer includes a processor performing the required computations. The computer further includes a memory in electronic communication with the processor to store a computer operating system. The computer operating systems may include, but are not limited to, MS-DOS, Windows, Linux, Unix, AIX, CLIX, QNX, OS/2, and MacOS. Alternatively, it is expected that future embodiments will be adapted to execute on other future operating systems.

[0139] It will be obvious to those having skill in the art that many changes may be made to the details of the above-described embodiments without departing from the underlying principles of the invention. The scope of the present invention should, therefore, be determined only by the following claims.

Claims

1. A method of a charging management server, comprising: receiving, by a charging management server from an application executing on a computing device associated with a user, event data comprising a time of an event and event metadata comprising one or more characteristics of the event; calculating, by the charging management server, a charge priority score for a time frame prior to the time of the event based on the one or more characteristics of the event; setting, by the charging management server, a first charge priority of a first electric vehicle (EV) charger associated with the user or a profile of the user, the first charge priority for the time frame prior to the time of the event, the setting of the first charge priority based on the charge priority score compared to charge priority scores of one or more second EV chargers or second user profiles; and responsive to the first charge priority exceeding a second charge priority of a second EV charger or a second user for the time frame, transmitting, by the charging management server to the first EV charger, instructions to charge an EV connected to the first EV charger.

2. The method of claim 1, further comprising: identifying, by the charging management server, a plurality of charge priorities of a plurality of EV chargers or user profiles for the time frame, the plurality of charge priorities comprising the first charge priority; comparing, by the charging management server, the plurality of charge priorities between each other; and identifying, by the charging management server, the first charge priority responsive to the first charge priority having a highest value of the plurality of charge priorities.

3. The method of claim 1, wherein receiving the event metadata comprises receiving, by the charging management server, a title of an individual associated with the event; and wherein calculating the charge priority score comprises calculating, by the charging management server, the charge priority score based on the title of the individual linked to the event.

4. The method of claim 3, wherein receiving the title of the individual associated with the event comprises receiving, by the charging management server, a job title of the user.

5. The method of claim 3, wherein receiving the title of the individual associated with the event comprises receiving, by the charging management server, a job title of an entity scheduled to meet with the user at the event.

6. The method of claim 1, wherein the application executing on the computing device is configured to communicate with a calendar application stored in memory of the computing device, and wherein the application is configured to retrieve the event data for the event from the calendar application.

7. The method of claim 6, wherein the application executing on the computing device is configured to retrieve the event data for the event responsive to the event having a stored association with a flag indicating the user will travel to the event in the EV.

8. The method of claim 1, further comprising: identifying, by the charging management server, an event location of the event and a charger location of the first EV charger; calculating, by the charging management server, a distance between the event location and the charger location; calculating, by the charging management server, a duration of the time frame based on the calculated distance and a charge speed of the first EV charger; and setting, by the charging management server, the time frame based on the calculated duration and the time of the event.

9. The method of claim 8, further comprising: transmitting, by the charging management server, the time frame to the application executing on the computing device, receipt of the time frame causing the application to add a calendar entry indicating the time frame to a calendar application stored in memory of the computing device.

10. The method of claim 8, wherein the time is a first time, and further comprising: predicting, by the charging management server, a state of charge of an energy storage device of the EV for one or more times of a time period prior to the first time, wherein calculating the duration of the time frame comprises calculating, by the charging management server, the duration of the time frame based on the predicted state of charge of the energy storage device of the EV for the one or more times.

11. The method of claim 10, wherein predicting the state of charge of the energy storage device comprises: receiving, by the charging management server from the application, second event data comprising a plurality of times of a plurality of events prior to the time and location data of the plurality of events; calculating, by the charging management server, an energy usage of the EV based on the plurality of times and the location data; and subtracting, by the charging management server, energy usage from an initial state of charge of the EV.

12. The method of claim 8, wherein receiving the event metadata comprising one or more characteristics of the event comprises receiving, by the charging management server, the event location of the event.

13. The method of claim 1, wherein receiving the event metadata comprises receiving, by the charging management server, a value associated with the event; and wherein calculating the charge priority score comprises calculating, by the charging management server, the charge priority score based on the value.

14. A system for charging a management server, comprising: one or more processors coupled with memory, the one or more processors configured to: receive, from an application executing on a computing device associated with a user, event data comprising a time of an event and event metadata comprising one or more characteristics of the event; calculate a charge priority score for a time frame prior to the time of the event based on the one or more characteristics of the event; set a first charge priority of a first electric vehicle (EV) charger associated with the user or a profile of the user, the first charge priority for the time frame prior to the time of the event, the setting of the first charge priority based on the charge priority score compared to charge priority scores of one or more second EV chargers or second user profiles; and responsive to the first charge priority exceeding a second charge priority of a second EV charger or a second user for the time frame, transmit, to the first EV charger, instructions to charge an EV connected to the first EV charger.

15. The system of claim 14, wherein the one or more processors are further configured to: identify a plurality of charge priorities of a plurality of EV chargers or user profiles for the time frame, the plurality of charge priorities comprising the first charge priority; compare the plurality of charge priorities between each other; and identify the first charge priority responsive to the first charge priority having a highest value of the plurality of charge priorities.

16. The system of claim 14, wherein the one or more processors are configured to receive the event metadata by receiving a title of an individual associated with the event; and wherein the one or more processors are configured to calculate the charge priority score by calculating the charge priority score based on the title of the individual linked to the event.

17. A method of a charging management server, comprising: receiving, by a charging management server from an application executing on a computing device associated with a user, event data comprising a time of an event and event metadata comprising one or more characteristics of the event; calculating, by the charging management server, a charge priority score for a time frame prior to the time of the event based on the one or more characteristics of the event; setting, by the charging management server, a first charge priority of a profile of the user, the first charge priority for the time frame prior to the time of the event, the setting of the first charge priority based on the charge priority score compared to charge priority scores of one or more second user profiles; and responsive to the first charge priority exceeding a second charge priority of a second user for the time frame, transmitting, by the charging management server, a message to a mobile device associated with the user indicating to move an electric vehicle (EV) associated with the user to an EV charger.

18. The method of claim 17, further comprising: identifying, by the charging management server, a plurality of charge priorities of a plurality of EV chargers or user profiles for the time frame, the plurality of charge priorities comprising the first charge priority; comparing, by the charging management server, the plurality of charge priorities between each other; and identifying, by the charging management server, the first charge priority responsive to the first charge priority having a highest value of the plurality of charge priorities.

19. The method of claim 17, wherein receiving the event metadata comprises receiving, by the charging management server, a title of an individual associated with the event; and wherein calculating the charge priority score comprises calculating, by the charging management server, the charge priority score based on the title of the individual linked to the event.

20. The method of claim 19, wherein receiving the title of the individual associated with the event comprises receiving, by the charging management server, a job title of the user.