Electric vehicle charging station reliability assessment method and device

Abstract

The purpose is to provide a charging station reliability assessment device and a charging station reliability assessment method. According to an embodiment, a method includes obtaining historical information of an electric vehicle EV charging station. A first reliability index and a second reliability index can be calculated based on the historical information. Based on the first reliability index and the second reliability index, a third reliability index can be calculated. A method, a device and a computer program product are provided.

Description

Technical Field

[0001] The present disclosure relates to electric vehicle charging, and more particularly, to a method and apparatus for evaluating the reliability of an electric vehicle charging station. Background Art

[0002] Electric vehicle (EV) charging stations can experience various types of problems. Sometimes, a charging station may go offline, sometimes, a charging station sends various error codes, and sometimes, a charging station may fail without clear indication of the underlying cause. From the perspective of a customer wanting to charge their EV, this is problematic: the customer never knows if the EV charging station they are about to use is functioning properly. In particular, if the customer is traveling long distances, the customer needs reliable information about the condition of the charging station they are planning to use.

[0003] In more challenging scenarios, an EV charging station may be online and communicating with the management backend system. The EV charging station may not even send any error messages to the backend system. However, it is fairly common for an EV charging station to not function properly even if these types of indicators do not show any signs of a problem. Therefore, assessing the reliability of an EV charging station can be challenging. Summary of the invention

[0004] This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.

[0005] The purpose is to provide a charging station reliability assessment device and a charging station reliability assessment method.

[0006] According to a first aspect, a method includes: obtaining historical information of an electric vehicle (EV) charging station; calculating a first reliability index based on the historical information, wherein the first reliability index corresponds to the reliability of the EV charging station during a first time period; calculating a second reliability index based on the historical information, wherein the second reliability index corresponds to the reliability of the EV charging station during a second time period; and calculating a third reliability index based on the first reliability index and the second reliability index. The method can, for example, enable reliability assessment of the EV charging station.

[0007] In an implementation form of the first aspect, the length of the first time period is shorter than the length of the second time period. The method can, for example, evaluate the reliability of the EV charging station by evaluating the short-term reliability of the EV charging station using the first reliability index and evaluating the long-term reliability of the EV charging station using the second reliability index. These can then be combined into a third reliability index to evaluate the overall reliability of the EV charging station.

[0008] In another implementation form of the first aspect, the first time period corresponds to a time period between a current time and a first time threshold. The method may, for example, implement reliability assessment of an EV charging station during a recent historical period by using a first reliability index.

[0009] In another implementation form of the first aspect, the second time period corresponds to a time period between the first time threshold and the second time threshold. The method may implement reliability assessment of the EV charging station during the less recent historical period by using the second reliability index, for example.

[0010] In another implementation form of the first aspect, the length of the first time period is in the range of 12 hours to 10 days. The method may, for example, implement reliability assessment of EV charging stations in a recent historical period by using a first reliability index.

[0011] In another implementation form of the first aspect, the length of the second time period is in the range of 30 days to 12 months. The method may, for example, implement reliability assessment of the EV charging station in the less recent historical period by using the second reliability index.

[0012] In another implementation form of the first aspect, the step of calculating the first reliability index / the second reliability index based on the historical information includes: assigning points to at least one reliability indicator based on the historical information; and calculating the first reliability index / the second reliability index based on the assigned points. The method can, for example, implement reliability assessment of an EV charging station by considering various factors.

[0013] In another implementation form of the first aspect, the at least one reliability indicator includes at least one of the following items: the percentage of offline time of the EV charging station; the percentage of failure time of the EV charging station; the number of warnings sent by the EV charging station; the number of charging times performed using the EV charging station in a time shorter than a preconfigured minimum time threshold; the number of charging times performed using the EV charging station in a time longer than a preconfigured maximum time threshold; the number of charging times performed using the EV charging station with a charging energy less than a preconfigured energy threshold; the number of failed charging times performed using the EV charging station; or the number of successful charging times performed using the EV charging station. The method can, for example, implement a reliability assessment of the EV charging station by considering various factors that can reflect the reliability of the EV charging station.

[0014] It should be understood that the implementation forms of the first aspect described above can be used in combination with each other. Several implementation forms can be combined together to form another implementation form.

[0015] According to a second aspect, there is provided a computer program product comprising a program code configured to perform the method according to the first aspect when the computer program is executed on a computer.

[0016] According to a third aspect, a computing device is configured to: obtain historical information of an electric vehicle (EV) charging station; calculate a first reliability index based on the historical information, wherein the first reliability index corresponds to the reliability of the EV charging station during a first time period; calculate a second reliability index based on the historical information, wherein the second reliability index corresponds to the reliability of the EV charging station during a second time period; and calculate a third reliability index based on the first reliability index and the second reliability index. With such a configuration, the computing device can, for example, evaluate the reliability of the EV charging station.

[0017] In an implementation form of the third aspect, the length of the first time period is shorter than the length of the second time period. With such a configuration, the computing device can evaluate the reliability of the EV charging station, for example, by evaluating the short-term reliability of the EV charging station using the first reliability index and by evaluating the long-term reliability of the EV charging station using the second reliability index. These can then be combined into a third reliability index to evaluate the overall reliability of the EV charging station.

[0018] In another implementation form of the third aspect, the length of the first time period is in the range of 12 hours to 10 days. The method may, for example, implement reliability assessment of EV charging stations in a recent historical period by using a first reliability index.

[0019] In another implementation form of the third aspect, the length of the second time period is in the range of 30 days to 12 months. With such a configuration, the computing device can, for example, evaluate the reliability of the EV charging station during the less recent history by using the second reliability index.

[0020] In another implementation form of the third aspect, the computing device is configured to calculate the first reliability index / the second reliability index based on the historical information by performing the following operations: assigning a score to at least one reliability index based on the historical information; and calculating the first reliability index / the second reliability index based on the assigned score. With such a configuration, the computing device can, for example, evaluate the reliability of the EV charging station by considering various factors.

[0021] In another implementation form of the third aspect, the at least one reliability indicator includes at least one of the following items: the percentage of offline time of the EV charging station; the percentage of failure time of the EV charging station; the number of warnings sent by the EV charging station; the number of charges performed using the EV charging station in a time shorter than a preconfigured minimum time threshold; the number of charges performed using the EV charging station in a time longer than a preconfigured maximum time threshold; the number of charges performed using the EV charging station with a charging energy less than a preconfigured energy threshold; the number of failed charges performed using the EV charging station; or the number of successful charges performed using the EV charging station. With such a configuration, the computing device can, for example, evaluate the reliability of the EV charging station by considering various factors that can reflect the reliability of the EV charging station.

[0022] In another implementation form of the third aspect, the first time period corresponds to a time period between a current time and a first time threshold. The computing device can evaluate the reliability of the EV charging station during a recent history, for example by using a first reliability index.

[0023] In another implementation form of the third aspect, the second time period corresponds to a time period between the first time threshold and the second time threshold.The computing device can evaluate the reliability of the EV charging station during the less recent history, for example by using the second reliability index.

[0024] It should be understood that the implementation forms of the third aspect described above can be used in combination with each other. Several implementation forms can be combined together to form another implementation form.

[0025] Many of the attendant features will become more apparent by reference to the following detailed description considered in conjunction with the accompanying drawings, whereby they will be readily understood. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Below, example embodiments are described in more detail with reference to the accompanying drawings, in which:

[0027] Figure 1 A flowchart representation illustrating a method for charging station reliability assessment according to an embodiment is illustrated;

[0028] Figure 2 illustrates a schematic representation of a computing device for electric vehicle charging station reliability assessment according to an embodiment;

[0029] Figure 3 illustrates a schematic representation of an electric vehicle charging system according to an embodiment;

[0030] Figure 4 illustrates a schematic representation of a timeline according to an embodiment; and

[0031] Figure 5 A schematic representation of data used for electric vehicle charging station reliability assessment according to an embodiment is illustrated.

[0032] Hereinafter, the same reference numerals are used in the drawings to designate the same parts. DETAILED DESCRIPTION

[0033] In the following description, the accompanying drawings are illustrated, which form part of the present disclosure and in which specific aspects of the present disclosure are shown by way of example in which the present disclosure may be placed. It should be understood that other aspects may be utilized and structural or logical changes may be made without departing from the scope of the present disclosure. Therefore, the following detailed description is not to be taken in a restrictive sense, as the scope of the present disclosure is defined in accordance with the appended claims.

[0034] For example, it should be understood that the disclosure related to the described method may also apply to a corresponding device or system configured to perform the method, and vice versa. For example, if specific method steps are described, the corresponding device may include a unit for performing the described method steps, even if such a unit is not explicitly described or illustrated in the drawings. On the other hand, for example, if a specific device is described based on functional units, the corresponding method may include steps for performing the described functions, even if such steps are not explicitly described or illustrated in the drawings. In addition, it should be understood that the features of the various example aspects described herein may be combined with each other unless otherwise specifically indicated.

[0035] Figure 1 A flow chart representation of a method 100 for electric vehicle (EV) charging station reliability assessment according to an embodiment is illustrated.

[0036] According to an embodiment, the method 100 comprises the following steps: obtaining 101 historical information of an electric vehicle EV charging station.

[0037] The historical information may include any information related to the use of the EV charging station. The historical information may also be referred to as history, log, log information, or the like. The historical information may include, for example, a log of individual charging events of the EV charging station. The log may also include: the length of each charging session, the amount of energy charged during the charging session, information about failed charging sessions, messages sent by the EV charging station (such as error messages), any errors that occurred, and / or the time period during which the EV charging station failed.

[0038] The obtaining step 101 may be performed by a computing device connected to the EV charging station, for example, via a telecommunications network / link. Such a computing device may, for example, collect historical information by communicating with a plurality of EV charging stations. Each EV charging station may include a computing device that may be configured to collect data about the EV charging station, such as usage data.

[0039] An EV charging station may refer to a device that can be used to charge an EV, such as an electric vehicle. An EV charging network may refer to a network of EV charging stations. Each EV charging station in the EV charging network may be connected to a computing device, such as a server, for example, via a telecommunications network or a similar network. For example, a computing device may be used to monitor and / or manage EV charging stations in the EV charging network.

[0040] The method 100 may further include the step of calculating 102 a first reliability index based on the historical information, wherein the first reliability index corresponds to the reliability of the EV charging station during the first time period.

[0041] The first reliability index may also be referred to as a first reliability value or the like. The first reliability index may quantify how reliable the EV charging station is during a first time period. A larger value may indicate that the EV charging station is more reliable, while a smaller value may indicate that the EV charging station is less reliable, and vice versa.

[0042] The first time period may also be referred to as a first period of time, a first time interval, or the like. The first time period may correspond to a time period of any length.

[0043] The first reliability index may be calculated, for example, by selecting events that have occurred during a first time period from the historical information. For example, a first subset may be selected from the historical information. The first subset may correspond to a first time interval. The first reliability index may be calculated based on the first subset.

[0044] The method may further include the step of calculating 103 a second reliability index based on the historical information, wherein the second reliability index corresponds to the reliability of the EV charging station during a second time period.

[0045] The second reliability index may also be referred to as a second reliability value or the like. The second reliability index may quantify how reliable the EV charging station is during the second time period. A larger value may indicate that the EV charging station is more reliable, while a smaller value may indicate that the EV charging station is less reliable, and vice versa.

[0046] The second reliability index may be calculated, for example, by selecting events that have occurred during the second time period from the historical information. For example, a second subset may be selected from the historical information. The second subset may correspond to the second time interval. The second reliability index may be calculated based on the second subset.

[0047] The second time period may also be referred to as a second period of time, a second time interval, or the like. The second time period may correspond to a time period of any length. The second time period may be a time period different from the first time period. The length of the second time period may be greater than the length of the first time period.

[0048] The steps of calculating 102 the first reliability index and calculating 103 may be performed in any order or substantially simultaneously.

[0049] Step 2 of reliability index.

[0050] The method 100 may further include the step of calculating 104 a third reliability index based on the first reliability index and the second reliability index.

[0051] The third reliability index may also be referred to as a third reliability value, an overall reliability index, an overall reliability value, a reliability index, or the like. The third reliability index may quantify how reliable the EV charging station is during the first time period and the second time period.

[0052] For example, the third reliability index may be calculated as an average of the first reliability index and the second reliability index. The average may be, for example, an arithmetic mean, a geometric mean, a weighted mean, a quadratic mean, or the like. For example, if the first reliability index corresponds to a more recent reliability of the EV charging station, it may be beneficial to weight the first reliability index more when calculating the third reliability index so that the third reliability index more reflects the current condition of the EV charging station.

[0053] The first reliability index / second reliability index may combine many different sources of information and indirect indicators of possible problems. These may then be combined into a single index, the third reliability index, which may indicate to the user how confident they can be that the station they are planning to use will function properly.

[0054] The first reliability index may correspond to a current state of the EV charging station. The second reliability index may correspond to a reliability history of the EV charging station. The length of the first time period may be less than the length of the second time period.

[0055] According to an embodiment, the length of the first time period is in the range of 12 hours to 10 days. The length of the first time period can be in any sub-range within this range, such as 12 hours to 48 hours, 12 hours to 5 days or 24 hours to 4 days.

[0056] According to an embodiment, the length of the second time period is in the range of 30 days to 12 months. The length of the second time period can be in any sub-range within this range, such as 30 days to 90 days, 60 days to 120 days or 30 days to 6 months.

[0057] The current status may indicate how well the EV charging station has been running, for example, during the last 24 hours. This may be useful primarily because even though the EV charging station may have worked well in the past, it may have started to malfunction today, and therefore the customer cannot trust that the EV charging station will operate properly today. Or on the other hand, the EV charging station may have had many problems in history, but these problems may have been fixed, and the station may operate normally today.

[0058] The reliability history may indicate how well the EV charging station has been running, for example, over the last 4 months. This may be a useful reliability indicator for customers to know if they can trust the station to operate correctly. Even if there have not been any issues today, if the reliability history is poor, there is a high probability that there will be issues again today.

[0059] Figure 2 A schematic representation of a computing device 200 is illustrated in accordance with an embodiment.

[0060] The computing device 200 may include at least one processor 201. The at least one processor 201 may include, for example, one or more of various processing devices, such as a coprocessor, a microprocessor, a controller, a digital signal processor (DSP), a processing circuit with or without an accompanying DSP, or various other processing devices including integrated circuits (for example, such as application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), microcontroller units (MCUs), hardware accelerators, dedicated computer chips, etc.).

[0061] The computing device 200 may also include a memory 202. The memory 202 may be configured to, for example, store computer programs, etc. The memory 202 may include one or more volatile memory devices, one or more non-volatile memory devices, and / or a combination of one or more volatile memory devices and non-volatile memory devices. For example, the memory 202 may be implemented as a magnetic storage device (such as a hard disk drive, a floppy disk, a magnetic tape, etc.), an optical magnetic storage device, and a semiconductor memory (such as a mask ROM, a PROM (programmable ROM), an EPROM (erasable PROM), a flash ROM, a RAM (random access memory), etc.).

[0062] When the computing device 200 is configured to implement a certain function, a certain component and / or some components of the computing device 200 (such as the at least one processor 201 and / or the memory 202) may be configured to implement the function. Moreover, when the at least one processor 201 is configured to implement a certain function, the function may be implemented using, for example, a program code included in the memory 202. For example, if the computing device 200 is configured to perform an operation, the at least one memory 202 and the computer program code may be configured to, together with the at least one processor 201, enable the computing device 200 to perform the operation.

[0063] According to an embodiment, the computing device 200 is configured to obtain historical information of electric vehicle EV charging stations.

[0064] Computing device 200 may also be configured to calculate a first reliability index based on the historical information, wherein the first reliability index corresponds to the reliability of the EV charging station during a first time period.

[0065] Computing device 200 may also be configured to calculate a second reliability index based on the historical information, wherein the second reliability index corresponds to the reliability of the EV charging station during a second time period.

[0066] The computing device 200 may be configured to perform the calculation of the first reliability index and the second reliability index in any order or substantially simultaneously.

[0067] The computing device 200 may also be configured to calculate a third reliability index based on the first reliability index and the second reliability index.

[0068] Figure 3 A schematic representation of a system 300 for EV charging station reliability assessment according to an embodiment is illustrated.

[0069] System 300 may include: EV charging network 301 , computing device 200 , and / or user 303 . EV charging network 301 may include multiple EV charging stations 302 .

[0070] The computing device 200 may communicate with the EV charging network 301, for example, using a data connection. The data connection may be any connection that enables the computing device 200 to communicate with the EV charging network 301. The data connection may include, for example, the Internet, Ethernet, 3G, 4G, Long Term Evolution (LTE), New Radio (NR), Wi-Fi, or any other wired or wireless connection, or some combination of these. For example, the data connection may include a wireless connection such as Wi-Fi, an Internet connection, and an Ethernet connection.

[0071] The computing device 200 may be implemented as part of a backend system. The backend system may include, for example, a plurality of servers, and the computing device 200 may correspond to one or more of those servers. The backend system may be configured to monitor and / or manage the EV charging network 301 and / or the EV charging station 302.

[0072] Computing device 200 may be configured to obtain historical information from EV charging network 301. Computing device 200 may be configured to obtain historical information from one or more EV charging stations 302.

[0073] User 303 may interact with computing device 200. The interaction may be a direct interaction, for example, via a user interface, or an indirect interaction. User 303 may be, for example, an end customer. User 303 may, for example, use a mobile device, such as a mobile phone, to send a query to computing device 200. In the query, user 303 may request a reliability index for one or more EV charging stations. Computing device 200 may calculate the reliability index in response to the query, or computing device 200 may pre-calculate the reliability index. Computing device 200 may then send the requested reliability index to user 303. After receiving the reliability index, user 303 may select which EV charging station they will use.

[0074] For the end customer, a typical communication method about reliability is a mobile application or a web-based application where the user 303 can view the status of different EV charging stations. When the user 303 opens the information about the EV charging station from the mobile application, there can be a simple traffic light view about the reliability of the EV charging station. For example, if the reliability index is in the range of 0 to 100, red can indicate 0 to 33 points, yellow can indicate 34 to 66 points, and green can indicate 67 to 100 points. This can indicate the reliability index of the EV charging station to the user 303 in a simplified format.

[0075] Alternatively, user 303 may be a charging station owner / administrator. Computing device 200 may send a more comprehensive report to such a user. Such a report may be automatically sent via email or viewed in a web-based management portal, for example. The EV charging station owner report may show an overview of all EV charging stations for the owner, for example using the aforementioned traffic light representation and / or per-station details. For example, the report may indicate the lowest scoring factor in the historical information. User 303 may then use this more detailed information to see which of their EV charging stations are not working well and which EV charging stations may need maintenance or replacement.

[0076] The method 100 may further include the following step: providing the third reliability index to the user 303. The providing step may include, for example: sending the third reliability index to the user 303.

[0077] The computing device 200 may also be configured to provide the third reliability index to the user 303. The computing device 200 may be configured to send the third reliability index to the user 303, for example.

[0078] Alternatively or additionally, computing device 200 may be configured to calculate the first reliability index / the second reliability index / the third reliability index without any input from user 303. Computing device 200 may, for example, compile statistical data on the reliability indexes of a plurality of EV charging stations 302. The administrator may then use the statistical data to infer, for example, whether a particular model of EV charging station is unsuitable for a particular application / condition based on the reliability index.

[0079] Figure 4 A schematic representation of a timeline according to an embodiment is illustrated. Figure 4 The embodiment of exemplifies three moments: current time t0 401, first time threshold t1 402, and second time threshold t2 403. Current time t0 401, first time threshold t1 402, and second time threshold t2 403 may also be referred to as moments. Figure 4 The embodiment also illustrates two time periods: a first time period T1 404 and a second time period T2 405 . Figure 4 The moments 401 to 403 and the time periods 404 and 405 presented in the embodiment are merely illustrative.

[0080] The first reliability index may correspond to the reliability of the EV charging station during a first time period T1 404. The second reliability index may correspond to the reliability of the EV charging station during a second time period T2 405.

[0081] According to an embodiment, the first time period T1 404 is shorter than the second time period T2 405 .

[0082] Additionally or alternatively, the first time period T1 404 and the second time period T2 405 may be continuous. For example, when the second time period T2 405 ends, the first time period T1 404 may begin. Figure 4 In an embodiment of the present invention, for example, the second time period T2 405 may end at the first time threshold t1 402 and the first time period T1 404 may start at the first time threshold t1 402.

[0083] Additionally or alternatively, the first time period T1 404 may correspond to a time period between a current time t0 401 and a first time threshold t1 402. The current time t0 401 may refer to a moment when the method 100 is executed and / or when the computing device 200 performs the operations disclosed herein. As one skilled in the art may appreciate, although performing the operations and / or the method 100 may take a certain period of time, the length of such a period of time may be considered insignificant.

[0084] Additionally or alternatively, the second time period T2 405 may correspond to the time period between the first time threshold t1 402 and the second time threshold t2 403. The length of the first time period T1 404 may be within any sub-range of this range, such as 12 hours to 48 hours, 12 hours to 5 days, or 24 hours to 4 days.

[0085] Additionally or alternatively, the length of the second time period T2 405 may be in the range of 30 days to 12 months. The length of the second time period T2 405 may be in any sub-range of this range, such as 30 days to 90 days, 60 days to 120 days, or 30 days to 6 months.

[0086] Figure 5 A schematic representation of data used for EV charging station reliability assessment according to an embodiment is illustrated.

[0087] Based on the historical information 501, scores may be assigned to various reliability indicators 502. The reliability indicators 502 may include, for example, one or more of the reliability indicators described herein.

[0088] Assigning a score to a reliability indicator may, for example, include calculating a value for the reliability indicator and assigning a score based on the value of the reliability indicator. For example, calculating a value for the reliability indicator may include calculating, based on historical information, that a certain EV charging station was faulty for 10% of the first time interval 404. Then, based on the value of 10%, a numerical score may be assigned to the reliability indicator "Failure Time Percentage". For example, the less time the EV charging station is faulty, the greater the numerical value of the assigned score may be. Further examples of reliability indicators and scores assigned to reliability indicators are disclosed herein.

[0089] Scores may be assigned to the reliability indicators for the first time interval 404 and the second time interval 405, respectively. For example, scores may be assigned to the reliability indicators for the first time interval 404 by selecting data corresponding to the first time interval 404 from the historical information 501. The data corresponding to the first time interval 404 may include, for example, events occurring during the first time interval 404, such as a charging session. Accordingly, scores may be assigned to the reliability indicators for the second time interval 405 by selecting data corresponding to the second time interval 405 from the historical information 501.

[0090] Based on the scores assigned to the reliability indicators 502, the first reliability index 503 may be calculated. If scores have been assigned to the reliability indicators 502 for the first and second time intervals 404 and 405, respectively, the first reliability index 503 may be calculated based on the scores assigned to the reliability indicators for the first time interval 404.

[0091] Based on the score assigned to the reliability index 502, a second reliability index 504 may be calculated. If scores have been assigned to the reliability index 502 for the first and second time intervals, respectively, the second reliability index 504 may be calculated based on the score assigned to the reliability index for the second time interval.

[0092] Based on the first reliability index 503 and the second reliability index 504 , a third reliability index 505 may be calculated.

[0093] Each reliability indicator may indicate how well or poorly the EV charging station 302 is operating. The maximum value of the scores assigned to all reliability indicators may be, for example, 100, and the minimum value of the scores may be 0. For example, 10 points may be used to assign to reliability indicator 1, 50 points may be used to assign to reliability indicator 2, and 40 points may be used to assign to reliability indicator 3. The total number of reliability indicators used and the values ​​of the scores available for assignment may vary.

[0094] Each reliability indicator can be a direct reliability indicator or an indirect reliability indicator.

[0095] Below, some reliability indicators are disclosed that may be used to assign scores to EV charging stations 302. These are merely example reliability indicators, and other reliability indicators may additionally or alternatively be used.

[0096] The at least one reliability indicator may include a percentage of offline time for the EV charging station.

[0097] The offline time percentage may refer to the percentage of the EV charging station being offline during the relevant time interval. In this document, the relevant time interval may include, for example, the first time interval 404 or the second time interval 405. The total time t of the EV charging station 302 being offline during the relevant time interval may be calculated by dividing the total time t of the EV charging station 302 being offline during the relevant time interval by t. offline Divide by the total length of the relevant time interval t period To calculate the offline time percentage p offline time :

[0098]

[0099] For example, if the length of the correlation time interval is t period = 24h = 1440min, and during this time interval, the EV charging station 302 has been offline for t offline = 27min, then the offline time percentage will be 27 / 1440 = 1.9%.

[0100] For the percentage of offline time p offline time The value of the assigned score P offline time For example, the following formula can be used to calculate:

[0101]

[0102] For example, in the case of an offline time percentage of 1%, the value of the score would be 15×(1-50×0.01)=15×0.5=7.5 points.

[0103] Alternatively or additionally, the at least one reliability indicator may include a failure time percentage of the EV charging station.

[0104] The percentage of down time may refer to the percentage of time that the EV charging station 302 was in a failed state during the relevant time interval. Failed may mean that the EV charging station 302 is online, but it has reported a failure and therefore the EV charging station 302 cannot be used. The total time t that the EV charging station 302 was in a failed state during the relevant time interval may be calculated by dividing the total time t that the EV charging station 302 was in a failed state during the relevant time interval by t. fault time Divide by the total length of the relevant time interval t period To calculate the failure time percentage pfault time :

[0105]

[0106] For example, if the length of the correlation time interval is t period = 24h = 1440min, and during this time interval, the EV charging station 302 has been faulty for t offline = 29min, then the offline time percentage will be 29 / 1440 = 2.0%.

[0107] For the failure time percentage p fault time The value of the assigned score P fault time For example, the following formula can be used to calculate:

[0108]

[0109] For example, in the case of a failure time percentage of 1%, the value of the score would be 15*(1-50*0.01)=15*0.5=7.5 points.

[0110] The percentage of offline time and the percentage of failure time may be referred to as direct reliability indicators because these reliability indicators may directly indicate a failure in the EV charging station.

[0111] Alternatively or additionally, the at least one reliability indicator may include a number of warnings sent by the EV charging station.

[0112] Warnings can refer to different messages that EV charging station 302 sends to the backend system. Warnings can indicate that something is not normal in EV charging station 302, but the station can still be used. Typical warnings may include, for example, weak wireless signal or high temperature. warnings can be calculated as the average number of warnings per hour. For example, if the station sent 10 warnings during the last 24 hours, the average number of warnings would be p warnings = 0.42 warnings / hour.

[0113] For example, the following formula can be used to calculate the number of warnings p warnings The value of the assigned score P warnings :

[0114]

[0115] For example, if the average number of warnings per hour is 0.28, the value of the score would be 10×(0.43-0.28) / 0.30=10×0.15 / 0.30=5 points.

[0116] Alternatively or additionally, the at least one reliability indicator may include a number of charging operations performed using the EV charging station in a time shorter than a preconfigured minimum time threshold.

[0117] A short charge may refer to an event where charging begins but ends before it lasts longer than a preconfigured minimum time threshold.

[0118] The minimum time threshold may be in the range of 10 seconds to 5 minutes. The minimum time threshold may be in any sub-range of this range, such as 10 seconds to 2 minutes, 1 minute to 3 minutes, or 5 seconds to 4 minutes. The minimum time threshold may be, for example, 30 seconds, 1 minute, 2 minutes, or 5 minutes.

[0119] A short charge may indicate that the EV cannot be charged using the EV charging station 302 as planned. short It can be calculated as the average number of short charges per hour. For example, if EV charging station 302 had 1 short charge during the last 24 hours, the average would be 0.042 charges / hour.

[0120] For example, the short charge times p can be calculated using the following formula: short The value of the assigned score P short :

[0121]

[0122] For example, if the average number of short charges per hour is 0.10, the value of the score will be 15×(0.16-0.10) / 0.12=15×0.06 / 0.12=7.5 points.

[0123] Alternatively or additionally, the at least one reliability indicator may include a number of charging operations performed using the EV charging station with a charging energy less than a preconfigured energy threshold.

[0124] A charge with less energy than a preconfigured energy threshold typically indicates a situation where charging started, and may even continue for several hours, but for some reason the EV did not receive a significant amount of energy through the charge.

[0125] The preconfigured energy threshold may be in the range of 10 watt-hours to 200 watt-hours, or any sub-range of this range, such as 20 watt-hours to 150 watt-hours, 50 watt-hours to 200 watt-hours, or 70 watt-hours to 130 watt-hours. The preconfigured energy threshold may be, for example, 100 watt-hours.

[0126] If the charging event is also short (see previous reliability indicators above), the charge energy is also typically less than the pre-configured energy threshold. In such a case, only short charges may be considered in the reliability indicator for this event, and the low energy reliability indicator may be ignored for this individual charging event. The number of charges with low energy may be calculated using the average number of low energy charges per hour. For example, if the charging station had 1 charge with less energy than the pre-configured energy threshold during the last 24 hours, the average would be 0.042 charges / hour.

[0127] For example, the following formula can be used to calculate the number of low energy charges p energy The value of the assigned score P energy :

[0128]

[0129] For example, if the average number of low energy charges per hour is 0.10, the value of the score would be 10×(0.16-0.10) / 0.12=10×0.06 / 0.12=5 points.

[0130] Alternatively or additionally, the at least one reliability indicator may include a number of charging operations performed using the EV charging station for a time longer than a preconfigured maximum time threshold.

[0131] A long charge may be a charge that lasts longer than a preconfigured maximum time threshold. The preconfigured maximum time threshold may, for example, be in the range of 6 hours (h) to 48h, or any sub-range of this range, such as 12h to 36h, 6h to 36h, or 18h to 32h. The maximum time threshold may, for example, be 24h. Furthermore, a charge that has not yet ended but has exceeded the preconfigured maximum time threshold from the initial start may be considered a long charge.

[0132] Long charging may indicate that the EV charging station 302 has failed to report that charging has ended. In many cases, the EV has stopped charging hours ago, but the EV charging station 302 has not reported the stop event to the backend system. Therefore, the backend system is still under the impression that charging is in progress.

[0133] The number of long charges can be calculated as the average number of long charges per hour. For example, if the charging station has 5 long charges during the last 30 days, the average value is about 0.0069 charges / hour.

[0134] For example, the following formula can be used to calculate the long charging number p long The value of the assigned score P long :

[0135]

[0136] For example, if the average number of long charges per hour is 0.0067, the value of the score would be 5×(0.0092-0.0067) / 0.005=5×0.0025 / 0.0050=2.5 ​​points.

[0137] Alternatively or additionally, the at least one reliability indicator may include a number of failed charges performed using the EV charging station.

[0138] Failed charging may correspond to the following situation: the EV charging station 302 appears to be online and functioning normally, and the user attempts to start charging using the EV charging station 302, but charging does not start. Typical reasons may be, for example, that the EV charging station 302 has some technical problems, and that the station simply does not accept or process the start command sent to the EV charging station 302.

[0139] Failed charging is usually an indicator that there is some unknown problem with EV charging station 302 that the station is not normally reporting to the backend system in the normal fault / warning messages. Failed charging can also be an indication of telecommunication problems, such as a firewall blocking certain commands or similar.

[0140] Failed charges can be calculated as the average number of failed charges per hour. For example, if the station had 1 failed charge during the last 24 hours, the average number of failed charges would be 0.042 charges / hour.

[0141] For example, the following formula can be used to calculate the number of failed charging times p failed The value of the assigned score P failed :

[0142]

[0143] For example, if the average number of warnings per hour is 0.12, the value of the score would be 10×(0.20-0.12) / 0.16=10×0.08 / 0.16=5 points.

[0144] Alternatively or additionally, the at least one reliability indicator may include a number of successful charges performed using the EV charging station.

[0145] Successful charging may be a positive indicator that many users have been able to charge via the EV charging station. Even if there are no problems (and thus the score from the previous indicator is full), it should not be assumed that EV charging station 302 is fully operational. For example, there may be an obstacle such as a snowbank in front of EV charging station 302, and users are therefore unable to use EV charging station 302. The station itself may be operating correctly, but users are still unable to use EV charging station 302 to charge because the charging station is inaccessible. However, if people always charge via the station, it may be assumed that EV charging station 302 is operating normally without any problems.

[0146] If charging has been started and ended, the charging duration is between a preconfigured minimum time threshold and a preconfigured maximum time threshold, and the charged power exceeds a preconfigured energy threshold, then charging may be considered successful. The preconfigured minimum time threshold may include any value disclosed herein. The preconfigured maximum time threshold may include any value disclosed herein. The preconfigured energy threshold may include any value disclosed herein.

[0147] The number of successful charges can be calculated as the average number of successful charges per hour. For example, if there are 10 successful charges during a 24-hour period, this would average out to about 0.42 successful charges per hour.

[0148] For example, the following formula can be used to calculate the number of successful charging times p success The value of the assigned score P success :

[0149]

[0150] For example, if the average number of successful charges per hour is 0.105, the value of the score would be 20×p success / 0.21=30×0.105 / 0.21=15 points.

[0151] The values ​​disclosed in the above examples are merely exemplary and may be adjusted for different applications and situations.

[0152] The number of warnings sent by the EV charging station, the number of charges performed using the EV charging station in a time shorter than a preconfigured minimum time threshold, the number of charges performed using the EV charging station with a charging energy less than a preconfigured energy threshold, the number of charges performed using the EV charging station in a time longer than a preconfigured maximum time threshold, the number of failed charges performed using the EV charging station, and / or the number of successful charges performed using the EV charging station may be referred to as indirect reliability indicators.

[0153] The first reliability index and / or the second reliability index may be calculated, for example, by summing all the scores assigned to the at least one reliability indicator. If the total value of the assigned scores is, for example, limited to 100 points, the maximum value of the first reliability index / the second reliability index is 100 points.

[0154] Reliability indices such as the third reliability index 505 can be calibrated based on user feedback and experience about the EV charging station. Calibration may affect the scores that can be assigned to the various reliability indicators. Calibration can be done, for example, by collecting user feedback (help desk calls, support requests through web forms, social media messages, etc.) from different EV charging stations. The feedback can be manually gathered together (e.g., once a month), and based on the feedback, a user feedback index can be created. The user feedback index can indicate how much negative feedback different EV charging stations receive from users. The customer feedback index can then be compared to the reliability index to compare whether the results match.

[0155] As an example, if the worst performing EV charging station receives 50 negative customer feedbacks per month, and the second worst performing EV charging station receives 40 negative feedbacks, then both EV charging stations should also receive low reliability indexes. If this is not the case, the reliability index can be calibrated by testing different amounts of scores that can be assigned to each reliability index and by checking whether the reliability index better matches the user feedback after adjustment. This can be repeated in an iterative manner until the reliability index better matches the user feedback.

[0156] Any range or device value given herein may be expanded or modified without losing the effect sought. Furthermore, any embodiment may be combined with another embodiment unless expressly prohibited.

[0157] Although the subject matter has been described in language specific to structural features and / or actions, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. On the contrary, the specific features and actions described above are disclosed as examples of implementing the claims, and other equivalent features and actions are intended to be within the scope of the claims.

[0158] It should be understood that the benefits and advantages described above may relate to one embodiment or may relate to multiple embodiments. The embodiments are not limited to those that solve any or all of the problems stated, or have any or all of the benefits and advantages stated. It should also be understood that reference to "an" item may refer to one or more of those items.

[0159] The steps of the methods described herein may be performed in any suitable order, or simultaneously where appropriate. In addition, individual blocks may be deleted from any of the methods described without departing from the spirit and scope of the subject matter described herein. Aspects of any of the above-described embodiments may be combined with aspects of any of the other embodiments described to form additional embodiments without losing the effects sought.

[0160] The term "comprising" is used herein to mean including the identified methods, blocks or elements, but such blocks or elements do not include an exclusive list and the method or apparatus may contain additional blocks or elements.

[0161] It should be understood that the above description is given as an example only, and various modifications may be made by those skilled in the art. The above specifications, examples, and data provide a complete description of the structure and use of the exemplary embodiments. Although various embodiments are described above with a certain degree of particularity or with reference to one or more separate embodiments, those skilled in the art may make various changes to the disclosed embodiments without departing from the spirit or scope of this specification.

Claims

1. A method (100) for evaluating the reliability of an electric vehicle charging station, the method comprising the following steps: Obtaining, by a computing device, historical information of electric vehicle (EV) charging stations; calculating, by the computing device, a first reliability index based on the historical information, wherein the first reliability index corresponds to the reliability of the EV charging station during a first time period; calculating, by the computing device, a second reliability index based on the historical information, wherein the second reliability index corresponds to the reliability of the EV charging station during a second time period; calculating, by the calculation device, a third reliability index based on the first reliability index and the second reliability index; and providing the third reliability index to a user by the computing device; The step of calculating the first reliability index or the second reliability index based on the historical information includes: assigning a score to at least one reliability indicator based on the historical information; and calculating the first reliability index or the second reliability index based on the assigned scores; The at least one reliability indicator includes at least a number of charging operations performed using the EV charging station in a time shorter than a preconfigured minimum time threshold.

2. The method (100) according to claim 1, wherein: The length of the first time period is shorter than the length of the second time period.

3. The method (100) according to claim 1 or claim 2, wherein: The first time period corresponds to a time period between a current time and a first time threshold.

4. The method (100) according to claim 3, wherein: The second time period corresponds to a time period between the first time threshold and a second time threshold.

5. The method (100) according to claim 1 or claim 2, wherein: The length of the first time period is in the range of 12 hours to 10 days.

6. The method (100) according to claim 1 or claim 2, wherein: The length of the second period of time is in the range of 30 days to 12 months.

7. The method (100) according to claim 1 or claim 2, wherein: The at least one reliability indicator also includes at least one of the following items: the percentage of time the EV charging station is offline; a percentage of failure time of the EV charging station; the number of warnings sent by the EV charging station; a number of charges performed using the EV charging station for a time longer than a preconfigured maximum time threshold; a number of charges performed using the EV charging station at a charging energy less than a preconfigured energy threshold; a number of failed charges performed using the EV charging station; or The number of successful charges performed using the EV charging station.

8. A computer program product comprising a program code, the program code being configured to perform the method according to claim 1 or claim 2 when the computer program product is executed on a computer.

9. A computing device (200), the computing device being configured to: Obtaining historical information of electric vehicle EV charging stations (501); A first reliability index is calculated based on the historical information (503), wherein: The first reliability index corresponds to the reliability of the EV charging station during a first time period; calculating a second reliability index based on the historical information (504), wherein the second reliability index corresponds to a reliability of the EV charging station during a second time period; calculating a third reliability index based on the first reliability index and the second reliability index (505); and providing the third reliability index to a user; The computing device is configured to calculate the first reliability index or the second reliability index based on the historical information by performing the following operations: assigning a score to at least one reliability indicator based on the historical information; and calculating the first reliability index or the second reliability index based on the assigned scores; The at least one reliability indicator includes at least a number of charging operations performed using the EV charging station in a time shorter than a preconfigured minimum time threshold.

10. The computing device (200) according to claim 9, wherein: The length of the first time period is shorter than the length of the second time period.

11. The computing device (200) of claim 9 or claim 10, wherein: The length of the first time period is in the range of 12 hours to 10 days.

12. The computing device (200) of claim 9 or claim 10, wherein: The length of the second period of time is in the range of 30 days to 12 months.

13. The computing device (200) of claim 9 or claim 10, wherein: The at least one reliability indicator comprises at least one of the following: the percentage of time the EV charging station is offline; a percentage of failure time of the EV charging station; the number of warnings sent by the EV charging station; a number of charges performed using the EV charging station for a time longer than a preconfigured maximum time threshold; a number of charges performed using the EV charging station at a charging energy less than a preconfigured energy threshold; a number of failed charges performed using the EV charging station; or The number of successful charges performed using the EV charging station.

Images