Charging station management based on usage data

Abstract

The present disclosure relates to managing multiple charging stations utilizing collected usage data. A network service receives and maintains correlated charging station usage data as time series data. The time series data corresponds to defined time windows during which individual time intervals may be characterized as use or non-use of a charging station. Non-use may be identified and compared to a threshold of non-use associated with a charging station that has been characterized as operational. If an individual time interval of non-use exceeds the threshold, the individual unit may be considered operational but unavailable for service. More specifically, the network service determines whether any particular instance of consecutive non-use corresponds to a statistically significant deviation from established periods of non-use. If such a deviation occurs, the consecutive periods of non-use may be considered indicative of unavailability of the charging station.

Description

[Technical field]

[0001] [CROSS REFERENCE TO RELATED APPLICATIONS] This application is a non-provisional application and claims priority to U.S. Provisional Patent Application No. 63 / 284,548, entitled "MANAGING CHARGING STATIONS BASED ON USAGE DATA," filed November 30, 2021, which is incorporated by reference in its entirety and for all purposes. [Background technology]

[0002] Generally described, computing devices and communication networks can be utilized to exchange data and / or information. In a typical application, a computing device can request content from another computing device over a communication network. For example, a user at a personal computing device can utilize a browser application to request a content page (e.g., a network page, a web page, etc.) from a server computing device over a network (e.g., the Internet). In such an embodiment, the user computing device can be referred to as a client computing device, and the server computing device can be referred to as a content provider. In another embodiment, the user computing device can collect or generate information and provide the collected information to the server computing device for further processing or analysis.

[0003] Generally described, infrastructure for utilization by various vehicles, such as electric vehicles, internal combustion engine vehicles, hybrid vehicles, etc., may be configured in various geographical regions. In certain scenarios, a service provider may provide vehicle infrastructure facilities, such as power charging stations, for utilization by vehicle users. Such vehicle infrastructure facilities may be deployed at various geographical charging station sites, where each geographical charging station site may include multiple charging stations. Some individual charging stations may include self-test or self-assessment capabilities that may determine the operability of electronic components of the charging station. [Brief description of the drawings]

[0004] The present disclosure is described herein with reference to drawings of specific embodiments, which are intended to illustrate, but not to limit, the disclosure. It is understood that the accompanying drawings, which are incorporated in and constitute a part of this specification, are for the purpose of illustrating the concepts disclosed herein and may not be to scale.

[0005] [Figure 1] FIG. 1 is a block diagram of an example environment for providing network services for charging station management in accordance with one or more aspects of the present application.

[0006] [Figure 2A] FIG. 1 illustrates an environment corresponding to a charging station site in accordance with one or more aspects of the present application.

[0007] [Figure 2B] FIG. 1 illustrates an environment corresponding to a vehicle, in accordance with one or more aspects of the present application.

[0008] [Diagram 3] FIG. 1 illustrates an example architecture for implementing a charging station data service in accordance with aspects of the present application.

[0009] [Figure 4A] FIG. 2 is a block diagram of an example environment for interaction between a network service and a charging station, according to one embodiment.

[0010] [Figure 4B] FIG. 2 is a block diagram of an example environment of interaction between a network service and a charging station for processing collected charging station data, according to one embodiment.

[0011] [Diagram 5] 11 is a flow diagram of an example process performed by a charging station data service to process time series data to generate an unavailability characterization in accordance with one or more embodiments disclosed herein.

[0012] [Figure 6] 1 is an example diagram of time series data characterizing usage of a charging station as "in use" or "out of use" over a set of time intervals. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] The following detailed description of certain embodiments presents various descriptions of certain embodiments. However, the innovations described herein may be implemented in many different ways, for example, as defined and encompassed by the claims. In this description, reference is made to the drawings, in which like reference numbers may indicate identical or functionally similar elements. It will be understood that the elements illustrated in the drawings are not necessarily drawn to scale. It will further be understood that certain embodiments may include more elements than are shown in the drawings and / or a subset of the elements illustrated in the drawings. Furthermore, some embodiments may incorporate any suitable combination of features from two or more drawings.

[0014] Generally described, one or more aspects of the present disclosure relate to configuration and management of infrastructure equipment based on usage data. As an illustrative example, aspects of the present application address managing operational status of vehicle charging stations based on correlated usage data of the charging stations. Illustratively, the correlated usage data is processed as time series data of usage of operational charging stations (e.g., without self-determined errors) based on defined time windows. Individual time intervals may be characterized as usage of the charging station or non-use of the charging station. Consecutive time intervals of non-use are identified, which may be further compared to a defined threshold of non-use associated with charging stations that are operational and available for use. If an individual time interval of non-use exceeds the threshold, the individual unit may be considered operational but unavailable for service. The system may then generate notifications and generate instructions for mitigation or corrective actions.

[0015] Generally described, a charging station may be deemed operational based on various forms of self-test or diagnostic processes. Such self-test or diagnostic processes are primarily focused on whether components of the charging station are capable of providing power to a connected vehicle. For example, a self-test or diagnostic module may determine whether any software modules on the charging station have experienced a failure or are otherwise not executable by a processor within the charging station. In another example, a self-test or diagnostic module may determine whether there is any detectable physical damage to a component of the charging station (e.g., a broken connector) that prevents a charging operation from being performed.

[0016] The self-test or diagnostic process is generally limited to characterizing the operational state (e.g., electrical, software, or mechanical operational functionality) of the charging station. However, in certain scenarios, environmental conditions or other external influences may affect the availability of a normally operational charging station. For example, an obstacle may be placed in proximity to the charging station that may limit a vehicle user from using the charging station. In another example, dirt, snow, and other junk may accumulate on a portion of the charging station site such that at least a portion of the otherwise operational charging station is no longer available. In yet another example, an operational charging station may be defaced or destroyed such that a vehicle user will not choose to use the charging station. In yet another example, an operational charging station may be implemented within a location such that it is not visible to a user or is not selected for use due to its location (e.g., part of a parking lot). In all these examples, and additional examples not expressly disclosed, conventional self-test or diagnostic processes may not be able to identify or diagnose that an operational charging station is not available or is not being utilized for its intended use relative to the charging station.

[0017] Furthermore, in other applications, a particular self-test or diagnostic process may not be configured to diagnose all potential operational condition errors that may occur. For example, a charging station may be configured with limited functionality self-test / diagnostic operation that tests for proper functionality of the electrical system but does not have the ability to identify potential problems with interfaces, mechanical connectors, software execution, etc. For example, an individual charging station may be subject to vandalism that may result in damage to an external portion of the charging station without impairing the functionality of the electrical system. Furthermore, other charging stations may experience a fault that prevents operation of the self-test or diagnostic functionality such that the charging station may be erroneously characterized as operational (e.g., a false negative). In all these instances, a conventional self-test or diagnostic process may not be able to identify or diagnose that a charging station is not operational or available for its intended use.

[0018] To address at least some of the above-mentioned inefficiencies, a network service provider may utilize the collected usage data to facilitate management of multiple charging stations. The network service provider receives and maintains correlated charging station usage data as time series data. The correlated charging station usage data is considered for charging stations that are deemed or characterized as operational (e.g., no self-determined or reported errors). The time series data corresponds to a defined time window, and individual time intervals may be characterized as charging station usage or non-use of the charging station. Consecutive time intervals of non-use may be identified and further compared to a defined threshold of non-use associated with charging stations that are characterized as operational and considered available for use. If an individual time interval of non-use exceeds the threshold, the individual unit may be considered operational but unavailable for service. More specifically, in an exemplary embodiment, the network service may determine whether any particular instance of consecutive non-use corresponds to a statistically significant deviation of an established period of non-use of the charging station. If such a deviation occurs, the consecutive period of non-use may be considered indicative of unavailability of the charging station. The network service can further compare whether other charging stations within the defined geographic charging station site are also experiencing such statistical deviations, which may indicate a cause of greater unavailability per charging station site.

[0019] The network service can then generate notifications and instructions for mitigating or corrective actions in response to determining and characterizing the unavailability of the charging stations. For example, the network service can initiate additional or alternative diagnostic systems, vision systems, or other detection processes to verify the identified unavailability. In other examples, the network service can schedule or have scheduled a direct service call to diagnose or potentially repair the charging stations. In other examples, the network service can generate an interface or communication identifying individual or grouped availability information of the charging stations.

[0020] Although various aspects are described according to example embodiments and feature combinations, those skilled in the art will appreciate that the examples and feature combinations are exemplary in nature and should not be construed as limiting. More specifically, aspects of the present application may be applicable to various types of vehicle infrastructure equipment or service equipment. Thus, those skilled in the art will appreciate that aspects of the present application are not necessarily completely limited to application to any particular type of charging station or charging station.

[0021] FIG. 1 illustrates a block diagram of an embodiment of a system 100. The system 100 may include one or more charging station sites 110A, 110B, and 110C, and a plurality of charging stations (e.g., units) 112A, 112B, and 112C, for each charging station area. The plurality of charging stations 112A, 112B, and 112C may provide power to one or more vehicles. The plurality of charging stations 112A, 112B, and 112C are logically and physically organized according to charging station sites 110A, 110B, and 110C that are common to a subset of the charging stations. The organization criteria utilized to define the various charging station sites may be implemented such that such individual charging stations may correspond to a single geographic charging station site. Alternatively, the individual charging station sites may be defined with some overlap such that one or more individual charging stations may be logically grouped into two or more defined charging station sites, regardless of whether the individual charging stations have a fixed geographic location. Illustratively, individual charging stations 112A, 112B, and 112C can be characterized as in use or not in use based on whether the charging station is providing power to a vehicle. The charging station (or other proxy component) can then transmit the characterized usage data to a network service.

[0022] System 100 may also include networks, i.e., network 150 connecting charging station sites 110A, 110B, and 110C, network services 120, and / or vehicles 130. Illustratively, in network services 120, various aspects related to charging station data service 122, historical usage data store 124, and usage time data store 126 may be implemented as one or more components related to one or more functions or services. Thus, the components of network services 120 should be considered as logical representations of services.

[0023] One or more of the individual charging stations 112A, 112B, and 112C may also be associated with a self-test or diagnostic module that may determine, at least in part, that one or more components of the individual charging stations 112A, 112B, and 112C are operational. As described above, the individual charging stations 112A, 112B, and 112C that are determined to be non-operational based on the self-test or diagnostic module may be excluded from further processing as described herein. Illustratively, the individual charging stations 112A, 112B, and 112C may include communication capabilities, including hardware and software, that facilitate interaction via one of a number of communication media and communication protocols. Alternatively, the geographic charging station site may include an additional computing device that is operable to communicate with the individual charging stations 112A, 112B, and 112C via physical or short-range wireless communication and then transmit charging station data via an additional network connection, such as the network 150.

[0024] As shown in FIG. 1 , network 150 enables data communication between charging station sites 110A, 110B, and 110C, vehicle 130, and network service 120. In some embodiments, network 150 can be a wired communication network such that charging station sites 110A, 110B, and 110C, network service 120, and / or vehicle 130 are connected via wired communication using any of the commercially available wired communication standards. In some embodiments, network 150 is a wireless communication network. In these embodiments, network 150 can use a short-range communication protocol, such as Bluetooth, Bluetooth low energy ("BLE"), and / or near field communication ("NFC"). Network 150 can comprise any combination of wired and / or wireless networks, such as one or more direct communication channels, a local area network, a wide area network, a personal area network, and / or the Internet. In some embodiments, network 150 may include one or more wireless networks, such as a Global System for Mobile Communications (GSM) network, a Code Division Multiple Access (CDMA) network, a Long Term Evolution (LTE) network, a 5G network, or any other type of wireless network. Network 150 may use protocols and components for communicating over the Internet or any of the other aforementioned types of networks. For example, protocols used by network 150 may include HyperText Transfer Protocol (HTTP), HTTP Secure (HTTPS), Message Queue Telemetry Transport (MQTT), Constrained Application Protocol (CoAP), etc. Protocols and components for communicating over the Internet or any of the other aforementioned types of communication networks are well known to those skilled in the art and therefore will not be described in detail herein.In some embodiments, wireless communications over network 150 may be conducted over one or more secure networks, such as communicating encrypted data via SSL (e.g., 256-bit, military-grade encryption). The various communication protocols described herein are merely examples, and the disclosure is not limited thereto.

[0025] Network services 120 illustratively correspond to one or more computing devices operable to host a charging status data service, which may facilitate processing of time series data corresponding to reported (or unreported) usage data described herein. Network services 120 may further include one or more data stores, such as historical usage data store 124, for maintaining historical usage data utilized to determine statistical deviations as described herein. Network services may further include usage time data store 126, which may store time series data as described herein. Network services 120 are represented in a simplified logical form and do not reflect all of the physical software and hardware components that may be implemented to provide functionality associated with a network-based service.

[0026] Vehicle 130 can illustratively receive the availability of individual charging stations 112A, 112B, and 112C associated with charging station sites 110A, 110B, and 110C, respectively. For example, vehicle 130 may access network service 120 to determine the available charging stations. Vehicle 130 can provide one or more available charging station sites 110A, 110B, and 110C based at least on the processed charging station data located for each charging station site 110A, 110B, and 110C.

[0027] Charging station sites 110A, 110B, and 110C, charging stations 112A, 112B, and 112C, vehicles 130, and network services 120 are shown for illustrative purposes only. The application is not limited by the representation and / or number of charging station sites 110A, 110B, and 110C, charging stations 112A, 112B, and 112C, vehicles 130, and network services 120 as shown in FIG.

[0028] For illustrative purposes, Figure 2A illustrates an environment corresponding to each charging station 112 (e.g., unit) according to one or more aspects of the present application. Each charging station 112 illustratively includes a management module 114, such as a self-test or diagnostic module. The management module 114 may be operable to implement one or more aspects of the present application described herein. In one aspect, the management module 114 may generate time series data.

[0029] In one aspect, management module 114 may be configured to perform at least a characterization of the usage of the charging stations over defined time periods corresponding to individual time intervals in the time series data. For example, management module 114 may estimate the availability of the charging stations by collecting usage data indicative of instances of usage of the charging stations. These data may be stored in data store 118. Management module 114 may communicate with network services 120 and / or vehicles 130 via communications 116.

[0030] For illustrative purposes, Figure 2B illustrates an environment corresponding to vehicles 130 according to one or more aspects of the present application. Each vehicle illustratively includes a management component 210 operable to implement one or more aspects of the present application as described herein.

[0031] The environment of the vehicle 130 may include sensors 212 that may provide input for the operation of the vehicle or collection of information, as described herein. The collection of sensors 212 may include one or more sensors or sensor-based systems included in the vehicle or accessible by the vehicle during operation. The sensors 212 may be integrated into the vehicle. Alternatively, the sensors 212 may be provided by an interface associated with the vehicle, such as a physical connection, a wireless connection, or a combination thereof.

[0032] In one aspect, the sensors 212 may include a vision system that provides input to the vehicle, such as detection of objects, attributes of detected objects (e.g., position, speed, acceleration), presence of environmental conditions (e.g., snow, rain, ice, fog, smoke, etc.). For example, the vehicle 130 may include multiple sensors 212 (including cameras, motion sensors, etc.), a managing component 210, and a data store 214. In this example, the sensors 212 may provide vehicle operating parameters to the managing component 210 in real-time or near real-time. The managing component 210 may provide data related to control of the vehicle, such as steering direction, acceleration, braking, etc. The data store 214 may store information regarding the current vehicle operating environment. In some embodiments, the vehicle 130 may rely on such a vision system for defined vehicle operating functions without assistance from or in place of other conventional detection systems.

[0033] In yet another aspect, the sensors 212 may further include one or more positioning systems that may obtain reference information from external sources, enabling various levels of accuracy in determining the vehicle's positioning information. For example, the positioning system may include various hardware and software components to process information from a GPS source, a wireless local area network (WLAN) access point information source, a Bluetooth information source, a radio frequency identification (RFID) source, and the like. In some embodiments, the positioning system may obtain a combination of information from multiple sources. Illustratively, the positioning system may obtain information from various input sources and determine the vehicle's positioning information, a particular altitude at the current location. In other embodiments, the positioning system may also determine driving-related operating parameters, such as driving direction, speed, acceleration, and the like. The positioning system 218 may be configured as part of a vehicle for multiple purposes, including automated driving applications, driving augmentation, or user-assisted navigation, and the like. Illustratively, the positioning system may include processing components and data that facilitate identification of various vehicle parameters or processing information.

[0034] In yet another aspect, the sensors 212 may include one or more navigation systems for identifying navigation-related information. Illustratively, the navigation system may obtain positioning information from a positioning system and identify characteristics or information related to the identified location, such as elevation, road grade, etc. The navigation system may also identify a proposed or intended lane position on a multi-lane road based on directions provided or expected to the vehicle user. Similar to the positioning system, the navigation system may be configured as part of the vehicle for multiple purposes, including automated driving applications, driving augmentation or user-assisted navigation, etc.

[0035] The environment may further include various additional sensor components or sensing systems operable to provide information regarding various operating parameters for use according to one or more operating conditions. The environment may further include one or more control components 216 for processing the output, such as transmitting the data via a communication output 220, generating data in a memory, or transmitting the output to other processing components.

[0036] 3, an example architecture for implementing charging station data service 122 on network service 120 will be described. Charging station data service 122 may be part of a component / system that may provide functionality related to charging station data processing. Charging station data service 122 may be further configured to evaluate and verify individual charging stations.

[0037] The architecture of Figure 3 is exemplary in nature and should not be construed as requiring a particular hardware or software configuration for the charging station data service 122. The general architecture of the charging station data service 122 shown in Figure 3 includes an arrangement of computer hardware and software components that may be used to implement aspects of the present disclosure. As shown, the charging station data service 122 may include a processing unit 302, a network interface 304, a computer readable media drive 306, and an input / output device interface 308, all of which may communicate with each other via a communication bus. The components of the charging station data service 122 may be physical hardware components that may include one or more circuits and software models.

[0038] Network interface 304 may provide connectivity to one or more networks or computer systems, such as network 150 of FIG. 1. Thus, processing unit 302 may receive information and instructions from other computer systems or services via the network. Processing unit 302 may also communicate with memory 310 and further provide output information via input / output device interfaces. In some embodiments, charging station data service 122 may include more (or fewer) components than those shown in FIG. 3.

[0039] The memory 310 may include computer program instructions that the processing unit 302 executes to implement one or more embodiments. The memory 310 typically includes RAM, ROM, or other persistent or non-transitory memory. The memory 310 may store an operating system 312 that provides computer program instructions used by the processing unit 302 in the general management and operation of the management component 210. The memory 310 may further include computer program instructions and other information for implementing aspects of the present disclosure.

[0040] Memory 310 may include a charging station data collection component 314. In some embodiments, charging station data collection component 314 is configured to receive charging station us data collected by individual charging stations. Illustratively, the charging station usage data may correspond to a characterization of at least usage of the charging station over a defined period of time corresponding to a respective time interval of the time series data, or of the current time series data. For example, the respective time interval may correspond to a selection of a fixed period of time, an estimated minimum amount of time that the vehicle will receive power, or some other selected set of times. The usage characterization may further include additional validation parameters, such as measurements of power provided to the vehicle, a vision system, a sensor, etc., that may verify that the charging station may attempt to verify that it is in use. Illustratively, the charging station may collect usage data indicative of instances of usage of the charging station. If the charging station does not register usage or the validation parameters are not met, the charging station may also characterize the time interval as “unused.” In other embodiments, the charging station may not actively communicate any non-use events, but rather the network service may infer that the reported lack of use of the charging station may be interpreted as non-use. Additionally, in some embodiments, the charging station may be monitored for network connectivity to ensure that the reported lack of use is not due to a failure or interruption in communication capabilities. In these embodiments, validation that an alternative cause, such as a network failure, is not attributable to the reported lack of use may mitigate potential false positives. Individual charging stations and / or individual charging station sites transmit usage data to the network service.

[0041] The memory 310 may include a charging station data processing component 316 configured to process incoming charging station usage data (e.g., collected by the charging station data collection component 314) and store the charging station usage data as windowed time series data. Illustratively, the processing of the usage data may include creating the time series data. Additionally, the processing of the usage data may include updating the previously processed time series data such that new charging data is added to the time series data and the oldest previously collected time series data is deleted. Illustratively, the time series data includes a fixed number of time intervals such that fluctuations in the usage of the operational and available charging stations may be considered non-statistical fluctuations. For example, in one embodiment, the time series data may be represented in consecutive intervals of 50, 75, 100, 125, 150, 175, 200, etc. Additionally, the selected number of time intervals may be dynamically selected by the network service based on the results of the processing of the time series data (e.g., characterization of potential false positives of unavailability), the time of day, the season, or other external factors (e.g., anticipated periods of high usage). The time intervals may also vary between individual charging stations or sets of charging stations (a diagram of time series data characterizing charging station usage as "in use" or "out of use" over a set of time intervals is shown in FIG. 6).

[0042] The memory 310 may include an individual charging station evaluation component 318 by determining a trigger event for the individual charging station evaluation. The trigger event may correspond to a time-based criterion based on a scheduled time or periodicity, etc. The trigger event may also correspond to a defined event, such as a power consumption metric of a charging station site (e.g., a geographic charging station site), a request generated manually (by an administrator or vehicle owner), a request received by a network service provider, etc. Illustratively, the individual charging station evaluation component 318 may determine whether any particular instance of continuous non-use (or individual charging station) corresponds to a statistically significant deviation of an established period of non-use of the charging station. If such a deviation occurs, the continuous period of non-use may be deemed to indicate unavailability of the charging station. The individual charging station evaluation component 318 may further compare whether other charging stations within the defined geographic charging station site also experience such a statistical deviation, which may indicate a cause of greater unavailability per charging station site. Thus, the individual charging station evaluation component 318 may obtain a historical session criterion for the charging station corresponding to a selection of the statistical deviation amount to be utilized for the identified evaluation period of non-use. Illustratively, in one aspect, the historical session criteria may include identification of a fixed number or formula for setting the threshold amount.

[0043] In some embodiments, the formula is based on percentiles of measured charging inactivity using the current time window. For example, the percentiles can be any percentage value, including, but not limited to, 75%, 80%, 85%, 90%, 95%, 99%, and any percentage value therebetween. Additionally, in some embodiments, the formula can also include a multiplier of the percentage value, such as 2x, 3x, 4x, 5x, etc. By identifying the threshold as a percentile of the current window of time series data, the threshold can be considered dynamic in nature to account for fluctuations in usage due to seasons, weather, or other events that may cause fluctuations in the use or non-use of operational charging stations. Additionally, in embodiments where the formula includes a multiplier, the multiplier helps establish a threshold that filters possible positives. Illustratively, the formula can be modified by adjusting the percentile or multiplier based on feedback, such as adjusting the multiplier based on some false negatives (e.g., inaccurate characterization of availability).

[0044] In some embodiments, the individual charging station assessment component 318 can obtain a current time series data window and identify periods of non-use within the time series data. The individual charging station assessment component 318 can also process the time series data to determine whether the identified periods of non-use exceed a threshold (e.g., exceed a percentile x multiplier threshold). If so, the individual charging station assessment component 318 can characterize one or more periods of inactivity indicating unavailability of the charging station. If the identified periods of non-use do not exceed a threshold, the network service can characterize the charging station as operational and available (assuming there are no self-test or diagnostic reports of failures).

[0045] The memory 310 may also include an individual charging station validation component 320 to validate any characterization of the unavailability of an individual charging station. In one embodiment, the individual charging station validation component 320 may compare the individual characterization of the unavailability of a charging station against other charging stations within a defined charging station site or set of charging station sites. Illustratively, the historical session criteria may also include a definition of a charging station site unavailability threshold as a percentage of the characterized unavailable charging stations to the total number of charging stations. For example, if the charging station site unavailability threshold is set to 60%, if the percentage of the characterized unavailable charging stations to the total number of charging stations exceeds the threshold, the individual charging station validation component 320 may characterize the charging station site as having a significant event that may not be limited to an individual charging station or a subset of charging stations. For example, a barrier to a geographic charging station site that prevents access to most (if not all) charging stations may be identified. In another example, this charging station site-level event may be used to identify or eliminate false positives in scenarios where usage is naturally decreasing due to external conditions such as increased availability of charging stations in a local area.

[0046] In some embodiments, if a charging station is characterized as unavailable and the characterization of the unavailability is verified, the individual charging station verification component 320 can generate a notification and generate instructions for mitigation or corrective actions in response to the determination and characterization of the unavailability of the charging station. For example, the individual charging station verification component 320 can initiate additional or alternative diagnostic systems, vision systems, or other detection processes to verify the identified unavailability. In other examples, the individual charging station verification component 320 can schedule or have scheduled a direct service call to diagnose or potentially repair the charging station. In other examples, the individual charging station verification component 320 can generate an interface or communication identifying individual or grouped availability information of the charging stations.

[0047] 4A-4B, an example interaction between an individual charging station and charging station data service 122 is described. Although only a single interaction is shown, the application is not limited to a single interaction. Rather, individual iterations of the illustrated interaction can result in different evaluations of an individual charging station, a set of charging stations, one or more geographic charging station sites, etc.

[0048] FIG. 4A illustrates an initial collection of charging station usage data and transmission of charging station data to form or update time series data. In (1), the charging station may collect individual charging usage data. Illustratively, the charging station usage data may correspond to at least a characterization of usage of the charging station over a defined period of time corresponding to an individual time interval in the time series data. For example, the individual time interval may correspond to a selection of a fixed period of time, an estimated minimum amount of time that the vehicle will receive power, or some other selected set of times. The characterization of usage may further include additional validation parameters, such as a measure of power provided to the vehicle, a vision system, a sensor, etc., that may verify that the charging station may attempt to verify that it is in use. Illustratively, the charging station may collect usage data indicative of instances of usage of the charging station. If the charging station does not register usage or the validation parameters are not met, the charging station may also characterize the time interval as “unused.” In other embodiments, the charging station may not actively communicate any non-use events, but rather, charging station data service 122 may infer that the reported lack of use of the charging station may be interpreted as non-use. Still further, in some embodiments, the charging station may be monitored for network connectivity to ensure that the reported lack of use is not due to a failure or interruption in communication capabilities. In these embodiments, validation that an alternative cause, such as a network failure, is not attributable to the reported lack of use may mitigate potential false positives. In (2), the individual charging station, proxy component, or management component sends usage data to charging station data service 122.

[0049] At (3), charging station data service 122 processes the incoming charging station usage data and stores the charging station usage data as windowed time series data. Illustratively, processing the usage data may include creating time series data. Additionally, processing the usage data may include updating previously processed time series data such that new charging data is added to the time series data and the oldest previously collected time series data is removed. Illustratively, the time series data includes a fixed number of time intervals such that fluctuations in the usage of operational and available charging stations may be considered non-statistical fluctuations. For example, in one embodiment, the time series data may be represented in consecutive intervals of 50, 75, 100, 125, 150, 175, 200, etc. Additionally, the selected number of time intervals may be dynamically selected by charging station data service 122 based on the results of processing the time series data (e.g., potential false positive characterization of unavailability), time of day, season, or other external factors (e.g., anticipated periods of high usage). The time intervals may also vary between individual charging stations or sets of charging stations. A diagram of time series data characterizing charging station usage as "in use" or "out of use" over a set of time intervals is shown in FIG.

[0050] 4B , charging station data service 122 can process time series data to characterize the availability of individual or groups of charging stations, where in (1) charging station data service 122 determines a trigger event for charging station evaluation. The trigger event can correspond to a time-based criteria based on a scheduled time or periodicity, etc. The trigger event can also correspond to a defined event, such as a geographic charging station site power consumption metric, a manually (administrator or vehicle owner) generated request, a request received by the charging station data service 122 provider, etc.

[0051] As described above, illustratively, charging station data service 122 can determine whether any particular instance of consecutive non-use corresponds to a statistically significant deviation of the established period of non-use of the charging station. If such a deviation occurs, the consecutive period of non-use can be deemed to be indicative of unavailability of the charging station. Charging station data service 122 can further compare whether other charging stations within the defined geographic charging station site also experience such statistical deviation, which may indicate a greater cause of unavailability per charging station site. Thus, in (2), charging station data service 122 can obtain a historical session criterion for the charging station corresponding to a selection of a statistical deviation amount to be utilized for the identified evaluation period of non-use. Illustratively, in one aspect, the historical session criterion can include identification of a fixed number or a formula for setting a threshold amount.

[0052] In some embodiments, the formula is based on percentiles of measured charging inactivity using the current time window. For example, the percentiles can be any percentage value, including, but not limited to, 75%, 80%, 85%, 90%, 95%, 99%, and any percentage value therebetween. Additionally, in some embodiments, the formula can also include a multiplier of the percentage value, such as 2x, 3x, 4x, 5x, etc. By identifying the threshold as a percentile of the current window of time series data, the threshold can be considered dynamic in nature to account for fluctuations in usage due to seasons, weather, or other events that may cause fluctuations in the use or non-use of operational charging stations. Additionally, in embodiments where the formula includes a multiplier, the multiplier helps establish a threshold that filters possible positives. Illustratively, the formula can be modified by adjusting the percentile or multiplier based on feedback, such as adjusting the multiplier based on some false negatives (e.g., inaccurate characterization of availability).

[0053] At (3), the charging station data service 122 may obtain a current time series data window and identify periods of non-use within the time series data. At (4), the charging station data service 122 may process the time series data to determine whether any identified periods of non-use exceed a threshold (e.g., exceed a percentile x multiplier threshold). If so, the charging station data service 122 may characterize one or more periods of inactivity as indicative of unavailability of the charging station. If the identified periods of non-use do not exceed a threshold, the charging station data service 122 may characterize the charging station as operational and available (assuming there are no self-test or diagnostic reports of faults).

[0054] In (5), the charging station data service 122 can further validate any characterization of the unavailability of an individual charging station. In one embodiment, the charging station data service 122 can compare the individual characterization of the unavailability of a charging station against other charging stations within a defined charging station site or set of charging station sites. Illustratively, the historical session criteria can also include a definition of a charging station site unavailability threshold as a percentage of the characterized unavailable charging stations to the total number of charging stations. For example, if the charging station site unavailability threshold is set to 60%, if the percentage of the characterized unavailable charging stations to the total number of charging stations exceeds the threshold, the charging station data service 122 can characterize the charging station site as having a significant event that may not be limited to an individual charging station or a subset of charging stations. For example, a barrier to a geographic charging station site that prevents access to most (if not all) charging stations can be identified. In another example, this charging station site-level event may be used to identify or eliminate false positives in scenarios where usage is naturally decreasing due to external conditions such as increased availability of charging stations in a local area.

[0055] If the charging station is characterized as unavailable in (6) and the characterization of the unavailability is verified, charging station data service 122 can generate a notification and generate instructions for mitigating or corrective actions in response to the determination and characterization of the unavailability of the charging station. For example, charging station data service 122 can initiate additional or alternative diagnostic systems, vision systems, or other detection processes to verify the identified unavailability. In other examples, charging station data service 122 can schedule or have scheduled a direct service call to diagnose or potentially repair the charging station. In other examples, charging station data service 122 can generate an interface or communication identifying individual or grouped availability information of the charging stations.

[0056] In some embodiments, the vehicle 130 may provide a user interface to present the availability of charging stations at a particular charging station site. For example, a user of the vehicle, such as a driver, owner, manager, technician, etc., may access the characterized availability of charging stations by using the user interface. In some embodiments, the vehicle 130 provides available charging stations and / or routing information based on the availability of the charging stations. In some embodiments, the charging station availability information presented to the vehicle may be automatically updated. In these embodiments, the charging station availability information may be presented as a charging station utilization rate at a particular charging station site, or whether the charging station site is abandoned. For example, if some of the charging stations at a particular charging station site are not operational, the charging station may be represented as a "non-abandoned charging station site," and the vehicle may use the charging station site. However, if the charging station site is abandoned, information that the charging station site is abandoned (e.g., unavailable) will be presented to the vehicle.

[0057] In some embodiments, the availability of the charging station site can be determined based on a third factor, such as wait time or utilization rate of the charging stations within the charging station site. For example, the charging station data service 122 may collect a third factor, such as the number of wait times at the charging station site. If the wait time is above a threshold, the charging station data service 122 may designate these charging station sites as abandoned, and the vehicle may receive the charging station site data as abandoned charging station data. In these embodiments, the wait time for each charging station site can be determined based on the positioning system 218 implemented in the vehicle. For example, the vehicle may provide its positioning system 218 via the com 220, and the charging station data service 122 can determine how many cars are within the geofenced area of ​​each charging station site.

[0058] The above availability of charging stations and / or charging station sites may be updated in real-time or near real-time and provided to the vehicle UI.

[0059] FIG. 5 illustrates a flow diagram of an exemplary process implemented by charging station data service 122 to process the time series data to generate an unavailability characterization. The process illustrated in FIG. 5 is exemplary in nature and should not be construed as limiting. In some embodiments, portions of the exemplary process attributed to charging station data service 122 for processing the time series data may be implemented in a distributed manner at one or individual charging stations. In this alternative, individual charging stations may implement a process for determining, characterizing, or identifying availability information. In certain embodiments, the charging station may report a potential issue that may then be verified by charging station data service 122 or may elicit a response. In yet another variation, the charging station site may implement a peer-to-peer model in which one or more charging stations may implement the exemplary process attributed to a network service for the purposes of charging station site processing by the charging station site. All such embodiments and variations are considered within the scope of the present application. Routine 500 is illustratively implemented by charging station data service 122.

[0060] In block 502, the charging station data service 122 may obtain a historical session criterion for the charging station corresponding to a selection of a statistical deviation amount to be utilized for the identified evaluation period of non-use. Illustratively, in one aspect, the historical session criterion may include identification of a fixed number or a formula for setting the threshold amount.

[0061] In some embodiments, the formula is based on percentiles of measured charging inactivity using the current time window. For example, the percentiles can be any percentage value, including, but not limited to, 75%, 80%, 85%, 90%, 95%, 99%, and any percentage value therebetween. Additionally, in some embodiments, the formula can also include a multiplier of the percentage value, such as 2x, 3x, 4x, 5x, etc. By identifying the threshold as a percentile of the current window of time series data, the threshold can be considered dynamic in nature to account for fluctuations in usage due to seasons, weather, or other events that may cause fluctuations in the use or non-use of operational charging stations. Additionally, in embodiments where the formula includes a multiplier, the multiplier helps establish a threshold that filters possible positives. Illustratively, the formula can be modified by adjusting the percentile or multiplier based on feedback, such as adjusting the multiplier based on some false negatives (e.g., inaccurate characterization of availability).

[0062] The charging station data service 122 determines a trigger event for charging station evaluation. The trigger event can correspond to a time-based criteria, such as based on a scheduled time or periodicity. The trigger event can also correspond to a defined event, such as a geographic charging station site's power consumption metrics, a manually (administrator or vehicle owner) generated request, a request received by the charging station data service 122 provider, etc.

[0063] In some embodiments, charging station data service 122 can determine whether any particular instance of consecutive non-use corresponds to a statistically significant deviation from the established periods of non-use for the charging station. If such a deviation occurs, the consecutive periods of non-use can be considered to be indicative of unavailability of the charging station. Charging station data service 122 can further compare whether other charging stations within the defined geographic charging station site also experience such a statistical deviation, which may indicate a greater source of unavailability per charging station site.

[0064] At block 504, the charging station data service 122 may obtain a current time series data window and identify periods of non-use within the time series data. At block 506, the charging station data service 122 may process the time series data to determine whether any identified periods of non-use exceed a threshold (e.g., exceed a percentile x multiplier threshold). If so, the charging station data service 122 may characterize one or more periods of inactivity as indicative of unavailability of the charging station site at block 508. If the identified periods of non-use do not exceed a threshold, the charging station data service 122 may characterize the charging station as operational and available (assuming there are no self-test or diagnostic reports of faults) and may end the routine 500 at block 512.

[0065] In block 508, the charging station data service 122 may further validate any characterization of the unavailability of an individual charging station by determining a percentage of unavailable or available charging stations within the charging station site. In one embodiment, the charging station data service 122 may compare the individual characterization of the unavailability of the charging station against other charging stations within a defined charging station site or set of charging station sites. Illustratively, the historical session criteria may also include a definition of a charging station site unavailability threshold as a percentage of the characterized unavailable charging stations relative to the total number of charging stations. For example, if the charging station site unavailability threshold is set to 60%, then if the percentage of the characterized unavailable charging stations relative to the total number of charging stations exceeds the threshold, the charging station data service 122 may characterize the charging station site as having a significant event that may not be limited to an individual charging station or a subset of charging stations. For example, a barrier to a geographic charging station site that prevents access to most (if not all) of the charging stations may be identified. In another example, the charging station site-level event may be used to identify or eliminate false positives in scenarios where usage is naturally declining due to external conditions, such as increased availability of charging stations in a local area. If the availability of charging stations within the charging station site exceeds a threshold percentage, the routine ends at block 512. In another example, the charging station data service 122 may further verify any characterization of individual charging station unavailability by comparing usage data reported by individual vehicles with respect to charging usage within the charging station site. In this aspect, the charging station data service may independently verify the number of vehicles that accessed the charging station site and utilized one or more charging stations.If the availability of charging stations within the charging station site does not exceed the threshold percentage, the routine proceeds to block 510 .

[0066] If the charging station is characterized as unavailable in block 510 and the characterization of the unavailability is verified, charging station data service 122 can generate a notification and generate instructions for mitigating or corrective actions in response to the determination and characterization of the unavailability of the charging station. For example, charging station data service 122 can initiate additional or alternative diagnostic systems, vision systems, or other detection processes to verify the identified unavailability. In other examples, charging station data service 122 can schedule or have scheduled a direct service call to diagnose or potentially repair the charging station. In other examples, charging station data service 122 can generate an interface or communication identifying individual or grouped availability information of the charging stations.

[0067] In some embodiments, the vehicle 130 may provide a user interface to present the availability of charging stations at a particular charging station site. For example, a user of the vehicle, such as a driver, owner, manager, technician, etc., may access the characterized availability of charging stations by using the user interface. In some embodiments, the vehicle 130 provides available charging stations and / or routing information based on the availability of the charging stations. In some embodiments, the charging station availability information presented to the vehicle may be automatically updated. In these embodiments, the charging station availability information may be presented as a charging station utilization rate at a particular charging station site, or whether the charging station site is abandoned. For example, if some of the charging stations at a particular charging station site are not operational, the charging station may be represented as a "non-abandoned charging station site," and the vehicle may use the charging station site. However, if the charging station site is abandoned, information that the charging station site is abandoned (e.g., unavailable) will be presented to the vehicle.

[0068] In some embodiments, the availability of the charging station site can be determined based on a third factor, such as wait time or utilization rate of the charging stations within the charging station site. For example, the charging station data service 122 may collect a third factor, such as the number of wait times at the charging station site. If the wait time is above a threshold, the charging station data service 122 may designate these charging station sites as abandoned, and the vehicle may receive the charging station site data as abandoned charging station data. In these embodiments, the wait time for each charging station site can be determined based on the positioning system 218 implemented in the vehicle. For example, the vehicle may provide its positioning system 218 via the com 220, and the charging station data service 122 can determine how many cars are within the geofenced area of ​​each charging station site.

[0069] The above availability of charging stations and / or charging station sites may be updated in real-time or near real-time and provided to the vehicle UI.

[0070] FIG. 6 illustrates an example of time series data characterizing the use of a charging station as “in use” or “out of use” over a set of time intervals. Each row of the example time series data represents usage data for an individual charging station, such as a site, or a subset of a site. As described in more detail below, the time series data can identify the use of a charging station, and the out of use of a charging station. In some cases, an out of use interval does not exceed an established threshold and is not considered to indicate the unavailability of a charging station. In other examples, as identified in FIG. 6, an out of use interval may exceed an established threshold and be utilized to characterize a particular charging station as unavailable.

[0071] The foregoing disclosure is not intended to limit the disclosure to the exact form or particular field of use disclosed. Thus, various alternative embodiments and / or modifications to the disclosure, whether expressly described or implied herein, are contemplated in light of the present disclosure. Having thus described an embodiment of the present disclosure, those skilled in the art will recognize that changes may be made in form and detail without departing from the scope of the present disclosure. Thus, the present disclosure is limited only by the scope of the claims.

[0072] Unless the context clearly dictates otherwise, words such as "comprise," "comprising," "include," "including," and the like, throughout the specification and claims, are to be construed in an inclusive sense, i.e., "including, but not limited to," as opposed to an exclusive or exhaustive sense. The word "coupled," as generally used herein, refers to two or more elements that may be directly connected or connected by one or more intermediate elements. Similarly, the word "connected," as generally used herein, refers to two or more elements that may be directly connected or connected by one or more intermediate elements. Where the context permits, words in the above detailed description using singular or plural numerals may also include plural or singular, respectively. The word "or" in connection with a list of two or more items encompasses all of the following interpretations of that word, namely, any of the items in the list, all of the items in the list, and any combination of the items in the list.

[0073] Additionally, conditional language as used herein, particularly "can," "could," "may," "for example," "such as," and the like, is generally intended to convey that certain embodiments include particular features, elements, and / or conditions, while other embodiments do not, unless specifically stated otherwise or understood otherwise within the context in which it is used. Thus, such conditional language is generally not intended to imply that features, elements, and / or conditions are in any way required for one or more embodiments.

[0074] In the above specification, the disclosure has been described with reference to certain embodiments. However, as those skilled in the art will appreciate, the various embodiments disclosed herein can be modified or embodied in various other ways without departing from the spirit and scope of the disclosure. Thus, this description should be considered as illustrative and is for the purpose of teaching those skilled in the art how to make and use the various embodiments of the disclosed ventilation assembly. It should be understood that the forms of the disclosure shown and described herein should be construed as representative embodiments. Equivalent elements, materials, processes, or steps may be substituted for those typically shown and described herein. Furthermore, certain features of the disclosure may be utilized independently of the use of other features, as will become apparent to those skilled in the art after having the benefit of this description of the disclosure. The terms "including," "comprising," "containing," "comprising," "consisting," "having," "being," and the like, used to describe and claim the disclosure, are intended to be construed in a non-exclusive manner, i.e., allowing for the presence of items, components, or elements not expressly described. References to the singular should also be construed to relate to the plural.

[0075] Furthermore, the various embodiments disclosed herein should be construed in an exemplary and explanatory sense, and should not be construed as limiting the present disclosure in any way. All joining references (e.g., attached, fastened, coupled, connected, etc.) are used only to aid the reader in understanding the present disclosure, and do not create limitations with respect to the position, orientation, or use of the systems and / or methods specifically disclosed herein. Thus, any joining references should be interpreted broadly. Moreover, such joining references do not necessarily imply that two elements are directly connected to each other.

[0076] Additionally, all numerical terms such as, but not limited to, "first," "second," "third," "primary," "secondary," "main," or any other conventional and / or numerical terms, should also be construed merely as identifiers to aid the reader in comprehension of the various elements, embodiments, variations and / or modifications of the present disclosure, and in particular do not create any limitation as to the order or priority of any element, embodiment, variation and / or modification, or with respect to another element, embodiment, variation and / or modification.

[0077] It will also be understood that, as may be useful depending on the particular application, one or more of the elements shown in the drawings / figures may also be implemented in a separate or integrated manner, or may be removed or discarded as inoperative in a particular case.

[0078] Although the present disclosure and embodiments have been described with reference to the accompanying drawings, various changes and modifications will become apparent to those skilled in the art. Such changes and modifications should be understood to be included within the scope of the present disclosure.

Claims

1. A system for managing a charging station, comprising: one or more computer processors and memory for executing computer-executable instructions for implementing a charging station data service; the charging station data service, receiving charging station usage information from at least one charging station site, the charging station site including a plurality of charging stations; determining a trigger event corresponding to the charging station site; In response to determining the trigger event, obtaining historical session metrics for the plurality of charging stations corresponding to the trigger event; obtaining current time series data associated with the plurality of charging stations; identifying a period of non-use of at least one charging station among the plurality of charging stations within the current time series data; characterizing one or more periods of non-use as indicative of at least one charging station among the plurality of charging stations being unavailable in response to determining that the periods of non-use for the at least one charging station among the plurality of charging stations identified in the current time series data have exceeded the historical session criterion; and verifying that the at least one charging station is characterized as an unavailable charging station.

2. 2. The system of claim 1, wherein the charging station data service verifies the characterization of the unavailable charging station by comparing the at least one charging station characterized as the unavailable charging station to other charging stations.

3. The system of claim 1 , wherein the trigger event corresponds to a time-based criterion, the time-based criterion being based on at least a scheduled time.

4. The system of claim 1 , wherein the trigger event corresponds to a defined event, the defined event comprising a power consumption metric of a geographic charging station site.

5. 10. The system of claim 1, wherein the charging station data service is further configured to determine that consecutive instances of non-use correspond to a statistically significant deviation from an established period of non-use for the charging station.

6. The system of claim 1 , wherein the current time series data including at least charging station usage information corresponds to a characterization of usage of the charging station over a defined period of time.

7. 2. The system of claim 1, wherein the charging station usage information corresponds to a characterization of usage of the charging station over a defined period of time, the defined period corresponding to a respective time interval of the current time series data.

8. The system of claim 1 , further comprising: generating a notification to the vehicle based at least on a result of the characterization of the unavailable charging station.

9. 1. A computer-implemented method for managing a charging station, comprising: receiving charging station usage information from at least one charging station site, the charging station site including a plurality of charging stations, the charging station usage information corresponding to time series data; obtaining a historical session metric for the charging station corresponding to the trigger event; identifying periods of non-use within the current time series data; characterizing the identified period of non-use in the current time series data as indicative of an unavailable charging station in response to determining that the identified period of non-use in the current time series data has exceeded the historical session criteria; verifying the characterization of the unavailable charging station; A computer-implemented method, comprising:

10. The computer-implemented method of claim 9 , wherein validating the characterization of the unavailable charging station comprises comparing the characterization of the unavailable charging station against other charging stations.

11. 10. The computer-implemented method of claim 9, wherein verifying the characterization of the unavailable charging station comprises obtaining usage data from at least one vehicle, the usage data corresponding to the charging station site.

12. 10. The computer-implemented method of claim 9, wherein the trigger event corresponds to a time-based criterion, the time-based criterion being based on at least a scheduled time.

13. The computer-implemented method of claim 9 , wherein the trigger event corresponds to a defined event, the defined event comprising a power consumption metric of a geographic charging station site.

14. 10. The computer-implemented method of claim 9, wherein the method further comprises determining that consecutive instances of non-use correspond to a statistically significant deviation from an established period of non-use for the charging station.

15. The computer-implemented method of claim 9 , wherein the current time-series data including at least charging station usage information corresponds to a characterization of usage of the charging station over a defined period of time.

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