Information processing apparatus, update method, and computer-readable recording medium

Abstract

The invention relates to an information processing apparatus, an updating method, and a computer-readable recording medium that optimize the frequency of a reference update. An information processing device includes: an acquisition unit that acquires a magnetic field distribution of a battery; and an updating unit that updates the reference magnetic field distribution using the magnetic field distribution of the battery when a condition for updating the reference magnetic field distribution referred to in the authenticity determination of the battery when the magnetic field distribution of the battery is acquired is satisfied.

Description

Technical Field

[0001] The present invention relates to an information processing device, an updating method, and a computer-readable recording medium. Background Art

[0002] To achieve carbon neutrality, so-called xEVs (electric vehicles)—electric vehicles powered by electric motors—are gaining popularity. With the spread of xEVs, efforts are underway to create battery-sharing services that facilitate battery replacement by providing charging facilities that replace batteries with low or fully charged capacity.

[0003] On the other hand, xEV batteries, in addition to legitimate products manufactured by manufacturers, also have the potential for the circulation of unauthorized products. For example, unauthorized products may mimic the appearance of legitimate modules or battery packs, while also replicating a QR code that links to management information such as the battery passport, which manages the battery's life cycle from material procurement to recycling.

[0004] Therefore, a technology has been proposed that uses the battery characteristics of a genuine battery as a reference and compares the reference battery characteristics with the battery characteristics measured based on the battery to be identified, thereby performing authenticity determination on whether the battery to be identified is a genuine product.

[0005] The battery characteristics of such a battery are affected by degradation over time. Therefore, in order to achieve authenticity determination corresponding to the temporal change in the battery characteristics of the battery, the reference battery characteristics are updated over time.

[0006] Patent Document 1: Japanese Patent Application Laid-Open No. 2020-169932

[0007] Patent Document 2: Japanese Patent Application Laid-Open No. 2012-75212

[0008] Patent Document 3: Japanese Patent Application Laid-Open No. 2012-49030

[0009] However, even if the frequency of updating the reference used for the above-mentioned authenticity determination is increased, the accuracy of the authenticity determination may not necessarily be improved. For example, when measuring the battery characteristics of a battery, external interference from the surrounding environment other than the battery is superimposed on the measured battery characteristics. Therefore, if the reference is updated to completely newly acquired battery characteristics at a high frequency (for example, each time), the deviation value is set as the reference, and the accuracy of the authenticity determination may be reduced. On the other hand, if the frequency of updating the reference is too low, it is difficult to reflect the influence of battery degradation caused by the passage of time in the reference, so the accuracy of the authenticity determination may be reduced. Summary of the Invention

[0010] The object of the present invention is to optimize the frequency of reference updates.

[0011] An information processing device involved in one aspect of the present invention comprises: an acquisition unit, which acquires the magnetic field distribution of a battery; and an update unit, which updates the reference magnetic field distribution using the magnetic field distribution of the battery when a condition for updating the reference magnetic field distribution used in the authenticity determination of the battery when acquiring the magnetic field distribution of the battery is met.

[0012] An aspect of the present invention relates to an updating method in which a computer performs the following processing: obtaining the magnetic field distribution of a battery, and updating the reference magnetic field distribution using the magnetic field distribution of the battery when obtaining the magnetic field distribution of the battery is satisfied when a condition for updating the reference magnetic field distribution used in determining the authenticity of the battery is met.

[0013] One aspect of the present invention relates to a computer-readable recording medium having an update program recorded thereon, which causes a computer to perform the following processing: obtaining the magnetic field distribution of a battery, and updating the reference magnetic field distribution using the magnetic field distribution of the battery when the condition for updating the reference magnetic field distribution used in the authenticity determination of the battery when obtaining the magnetic field distribution of the battery is met.

[0014] Effects of the Invention

[0015] According to one embodiment, the frequency of reference updates can be optimized. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a diagram showing a configuration example of a battery sharing system.

[0017] Figure 2 This is a schematic diagram showing an example of battery replacement.

[0018] Figure 3 It is a schematic diagram showing an example of measuring the magnetic field distribution of a battery.

[0019] Figure 4 This is a diagram showing one aspect of a method for solving a problem.

[0020] Figure 5 This is a block diagram (1) showing an example of the functional configuration of a server device.

[0021] Figure 6 This is a diagram showing an example of updating the battery replacement interval.

[0022] Figure 7 This is a diagram showing an example of updating the number of times the battery authenticity determination is performed.

[0023] Figure 8 It is a schematic diagram showing an example of setting a threshold value.

[0024] Figure 9 It is a schematic diagram showing an update example for reference.

[0025] Figure 10 This is a flowchart (1) showing the overall processing flow.

[0026] Figure 11 This is a block diagram (2) showing an example of the functional configuration of a server device.

[0027] Figure 12 1 is a diagram showing an example of updating incorporating frequency information.

[0028] Figure 13 It is a schematic diagram showing an example of setting a threshold value.

[0029] Figure 14 This is a flowchart (2) showing the overall processing flow.

[0030] Figure 15 This is a diagram showing an application example of the reference update condition.

[0031] Figure 16 This is a diagram showing an example of a hardware configuration. DETAILED DESCRIPTION

[0032] The information processing device, update method, and implementation method for the update program (hereinafter referred to as "embodiments") of this application are described below with reference to the accompanying drawings. Each embodiment merely represents an example or aspect and does not limit numerical values, functional ranges, usage scenarios, etc. Furthermore, the various embodiments may be appropriately combined to the extent that the processing content does not conflict.

[0033] <Implementation Method 1>

[0034] Overall Structure

[0035] Figure 1 This is a diagram showing a configuration example of a battery sharing system. Figure 1 The battery sharing system 1 shown here uses a swappable battery structure for xEVs and other vehicles, providing a battery sharing service that enables battery sharing. While xEVs are used as an example of battery usage, batteries are not limited to vehicles and can be installed in a variety of loads, including construction and agricultural machinery, as well as home appliances.

[0036] The term "battery" as used herein refers to secondary batteries such as lithium-ion batteries, as well as battery packs thereof. For example, a "battery" can refer to a single battery cell (a single cell), a battery pack (a module) composed of multiple single cells, or a battery pack (a battery pack) composed of multiple modules.

[0037] like Figure 1 As shown, the battery sharing system 1 may include a server device 10 and sites 30A to 30N. Hereinafter, when the sites 30A to 30N do not need to be distinguished from each other, the sites 30A to 30N may be referred to as "sites 30".

[0038] The server device 10 and the site 30 can be connected to each other via any network NW for communication. The network NW can be implemented by any technology, whether wired or wireless, such as Internet technology, industrial communication standards, or power-saving wireless communication standards for IoT (Internet of Things).

[0039] Server device 10 is an example of an information processing device that provides the aforementioned battery sharing service. For example, server device 10 can be implemented as a PaaS (Platform as a Service) or SaaS (Software as a Service) application, enabling the aforementioned battery sharing service to be provided as a cloud service. Alternatively, server device 10 can be implemented as a server that provides the battery sharing functionality that implements the aforementioned battery sharing service within a company.

[0040] Station 30 represents an example of a charging facility that replaces batteries with depleted batteries with fully charged ones. Station 30 has multiple slots for inserting and removing batteries. Station 30 can charge batteries installed in vacant slots among the multiple slots and remove fully charged batteries from fully charged slots.

[0041] Battery Replacement

[0042] Figure 2 is a diagram showing an example of battery replacement. Figure 2 As shown, identification information of a user who utilizes the battery sharing service, for example, a user ID (IDentification), is read at the station 30 (step S1).

[0043] For example, the user brings the IC (Integrated Circuit) card 2 held by the user close to the information reading unit 31 of the station 30 , whereby the user ID recorded on the IC card 2 is read by the information reading unit 31 .

[0044] In addition to user authentication to determine whether the user is a pre-registered authorized user, fee settlement for using the battery sharing service is performed using the user ID read by the information reading unit 31 .

[0045] Then, the battery 3 removed from the vehicle such as the EV is mounted in an empty slot where no battery is mounted among the plurality of slots provided in the station 30 , and the battery 3 is returned (step S2 ).

[0046] When returning the battery 3, a display unit associated with each slot, such as a lamp, can be used to differentiate between a vacant slot and other slots.

[0047] After returning the battery 3, the battery 3 is removed from a fully charged slot among the multiple slots provided by the station 30 (step S3). "Completely charged" is merely an example and may refer to a fully charged state, but this is not necessarily the case. For example, a slot containing a battery whose SOC (State of Charge) is greater than or equal to the lower limit of 95% may be identified as a fully charged slot.

[0048] The battery 3 thus removed from the charged slot is mounted on a user's vehicle, etc. The battery 3 can be replaced by the operations of steps S1 to S3 described above.

[0049] In addition, Figure 2 The example of a user who has registered in advance replacing a battery is merely given as an example, but this does not prevent a new user from replacing a battery.

[0050] Magnetic field distribution

[0051] While the popularity of xEVs is accelerating, the distribution of non-authentic xEV batteries, in addition to legitimate products manufactured by manufacturers, is also increasing. For example, these counterfeit products appear to resemble legitimate modules or battery packs, but feature a counterfeit QR code linking to management information such as the battery passport, which manages the battery's lifecycle from material procurement to recycling.

[0052] Based on this aspect, the server device 10 according to this embodiment can perform an authentication check on whether the battery is a genuine product when the battery is replaced. For example, the authentication check can be performed by using the battery characteristics of a genuine battery as a reference and comparing the reference battery characteristics with the battery characteristics measured for the battery to be identified.

[0053] Below, as an example of the battery characteristics, the example of using the magnetic field distribution of the battery to perform the above-mentioned authenticity determination is given. However, as an example, the station 30 can Figure 2 The battery 3 returned in step S2 shown acquires the magnetic field distribution of the battery 3 .

[0054] Figure 3 Schematic diagram showing an example of measuring the magnetic field distribution of a battery. Figure 3 As shown in FIG. 1 , the magnetic field distribution of the battery 3 is measured by the measuring unit 33 implemented by the two-dimensional array of magnetic sensors. Figure 3 In the example shown, the measuring unit 33 is implemented by arranging magnetic sensors in a vertical 6×horizontal 16 array on the side surface of the battery 3 mounted in the slot of the station 30 .

[0055] The corresponding map of the measured values, such as magnetic flux density, measured by the 6-axis x 16-axis magnetic sensors is obtained as the magnetic field distribution 20 of the battery 3. For example, when the measuring unit 33 is implemented by a three-axis magnetic sensor, the magnetic field distribution 20X of the X component, the magnetic field distribution 20Y of the Y component, and the magnetic field distribution 20Z of the Z component are obtained as the magnetic field distribution 20 of the battery 3.

[0056] The magnetic field distribution of such a battery is affected by degradation due to the passage of time. Therefore, in order to achieve authenticity determination corresponding to the temporal change of the battery characteristics, there is an aspect of updating the reference battery characteristics according to the passage of time.

[0057] also, Figure 3 This is just an example. The measuring unit 33 can be implemented by a single-axis magnetic sensor or a two-axis magnetic sensor, and the arrangement of the magnetic sensors can also be implemented by any arrangement represented by a one-dimensional arrangement. For example, the magnetic sensor can be an analog element or a digital element. Each magnetic element can be, for example, a Hall element, a magnetoresistive element such as AMR (Anisotropic magnetoresistance effect), GMR (Giant magnetoresistance effect), TMR (Tunnel magnetoresistance effect), a magnetoresistive element such as MI (Magneto-Impedance), a fluxgate, or a thin-film magnetic element based on the anomalous Hall effect of a topological magnetic body. When an alternating current flows through the object to be measured, a pickup coil can be used as a magnetic element.

[0058] One aspect of the problem

[0059] Here, as described in the above background technology section, even if the frequency of updating the reference used for the above-mentioned authenticity determination is increased, the accuracy of the authenticity determination may not necessarily be improved. For example, when measuring the battery characteristics of a battery, external interference from the surrounding environment other than the battery is superimposed on the measured battery characteristics. Therefore, if the reference is updated to a completely newly acquired battery characteristic at a high frequency (for example, each time), the deviation value is set as the reference, and sometimes the accuracy of the authenticity determination is reduced. On the other hand, if the frequency of updating the reference is too low, it is difficult to reflect the influence of the battery's degradation caused by the passage of time in the reference, so sometimes the accuracy of the authenticity determination is reduced.

[0060] <One aspect of the problem-solving approach>

[0061] Therefore, when the conditions for updating the reference magnetic field distribution used for battery authenticity determination are satisfied when the battery magnetic field distribution is acquired, the server device 10 involved in this embodiment provides a reference update function for updating the reference magnetic field distribution.

[0062] Figure 4 is a diagram that shows one aspect of the solution to a problem. Figure 4 As shown, the server device 10 obtains the magnetic field distribution (1) of the battery 3 installed in the vacant slot of the station 30. Furthermore, when the conditions for updating the reference magnetic field distribution used for battery authenticity determination are satisfied when obtaining the magnetic field distribution of the battery, the server device 10 updates the reference magnetic field distribution (2) using the magnetic field distribution of the battery.

[0063] In this way, the server device 10 updates the reference magnetic field distribution conditionally. As just one example, a condition can be set that the number of times the authenticity determination of the battery 3 is executed is greater than or equal to a threshold.

[0064] As one aspect, condition 1, in which the time elapsed since the last reference update is less than threshold 1 and the number of times battery 3 authenticity determinations have been performed is less than threshold 2, can be set as a condition for limiting / prohibiting reference updates. When condition 1 is met, the time elapsed since the last reference update is short, so the effects of both degradation due to the passage of time and degradation due to repeated charging and discharging are minor and difficult to observe. In this case, reference updates are limited or prohibited, thus preventing excessive frequency of reference updates. As a result, the risk of setting a deviated value as the reference due to external interference during measurement of the battery's magnetic field distribution can be reduced.

[0065] Alternatively, condition 2, which states that the time elapsed since the last reference update is less than threshold 1 and the number of times battery 3 authenticity checks have been performed is greater than or equal to threshold 2, can be set as a condition for allowing reference updates. When condition 2 is met, the time elapsed since the last reference update is short, minimizing the effects of degradation due to the passage of time. On the other hand, the number of times authenticity checks have been performed is high, potentially leading to increased degradation due to repeated charge and discharge cycles. In this case, updating the reference prevents inadequate frequency of reference updates. As a result, the effects of degradation due to repeated charge and discharge cycles can be reflected in the reference.

[0066] Alternatively, condition 3, that the time elapsed since the last reference update is greater than or equal to threshold 1, can be set as a condition for allowing reference updates. If condition 3 is met, the time elapsed since the last reference update is long, and thus, degradation due to the passage of time may progress and have an impact. In this case, updating the reference prevents inadequate frequency of reference updates. As a result, the effects of degradation due to the passage of time can be reflected in the reference.

[0067] Thus, the reference update function of this embodiment balances the risk of adopting deviated values ​​with the advantage of reflecting degradation over time and / or degradation caused by repeated charge and discharge cycles in the reference. Therefore, the reference update function of this embodiment optimizes the frequency of reference updates. Furthermore, by eliminating unnecessary reference updates, computational costs can be reduced.

[0068] In addition, the following merely illustrates an example in which the reference update function is packaged as a function of the battery sharing service. However, the reference update function may be provided as a service separate from the battery sharing service.

[0069] <Configuration of Server Device 10>

[0070] Next, a functional configuration example of the server device 10 according to this embodiment will be described. Figure 5 This is a block diagram (1) showing an example of the functional configuration of the server device 10. Figure 5 Modules related to the battery sharing service provided by the server device 10 are schematically shown in FIG.

[0071] like Figure 5 As shown, the server device 10 includes a communication control unit 11, a storage unit 13, and a control unit 15. Figure 5 In FIG. 1 , only functional units related to the battery sharing service are selectively shown, but the server device 10 may include functional units other than those shown in the figure.

[0072] The communication control unit 11 is a functional unit that controls communications with other devices, such as the station 30. As an example, the communication control unit 11 can be implemented by a network interface card. As one example, the communication control unit 11 can receive information from the station 30 regarding a user ID, the battery's magnetic field distribution, and output a notification indicating whether battery replacement is permitted or not.

[0073] The storage unit 13 is a functional unit that stores various data. As just one example, the storage unit 13 is implemented by internal, external, or auxiliary storage of the server device 10. For example, the storage unit 13 may be implemented by a storage system (cloud) on a network. For example, the storage unit 13 stores user information 13A, replacement information 13B, reference information 13C, and number of determinations information 13D. Furthermore, the user information 13A, replacement information 13B, reference information 13C, and number of determinations information 13D are described together in the context of reference, generation, or registration.

[0074] The control unit 15 is a functional unit that performs overall control of the server device 10. For example, the control unit 15 can be implemented by a hardware processor. Figure 5 As shown, the control unit 15 includes a providing unit 15A, a determining unit 15B, a setting unit 15C, and an updating unit 15D. The control unit 15 can be implemented by hard-wired logic or the like.

[0075] The providing unit 15A is a processing unit that provides the above-mentioned battery sharing service. For example, the providing unit 15A may correspond to an example of an acquiring unit. As one aspect, if the providing unit 15A receives a user ID from the site 30, user authentication is performed with reference to the user information 13A stored in the storage unit 13. Here, the user information 13A may be a collection of data that associates various information including settlement information such as credit cards and electronic money with each user ID. For example, the above-mentioned user authentication can be achieved by comparing the user ID registered in the user information 13A with the user ID received from the site 30, and determining whether the user is a regular user with a user ID registered in the user information 13A.

[0076] In the case where the user authentication is successful, the providing unit 15A outputs the installation instruction of the battery to the vacant slot to the site 30. Moreover, if the user's battery is installed in the vacant slot of the site 30, the providing unit 15A obtains the magnetic field distribution of the battery measured by the measuring unit 33 of the site 30. At this time, the providing unit 15A can also obtain the user's battery ID installed in the vacant slot of the site 30. For example, the battery ID recorded in the IC chip carried by the battery can be obtained. In addition, the battery ID of the battery that the user last removed from the charged slot can be regarded as the battery ID of the battery installed in the vacant slot of the site 30. In this case, in the user information 13A, time series data of the battery IDs of the batteries removed from the charged slot by the user and the batteries installed in the vacant slot by the user can be stored as a resume for each user ID. This time series data can include the time of removal from the charged slot or installation to the vacant slot, and the identification information of the site (site ID). When a battery is installed in an empty slot under this battery ID management, the battery ID of the battery that the user last removed from the charged slot in the history of the battery ID corresponding to the user ID for which the user authentication was successful can be obtained as the battery ID of the battery installed in the empty slot of station 30.

[0077] After acquiring the battery ID and magnetic field distribution of the battery in this manner, the providing unit 15A updates the replacement interval of the battery included in the replacement information 13B stored in the storage unit 13 .

[0078] Figure 6 : is a diagram showing an example of updating the battery replacement interval. Figure 6 As shown, the replacement information 13B is data that associates items such as replacement interval and replacement date and time with each battery ID. Among them, "replacement interval" refers to the interval between battery replacement, for example, it can be the interval (day) after the battery is installed in the empty slot until it is installed in the next empty slot. In addition, "replacement date and time" refers to the latest date and time among the dates and times when the battery was replaced. In addition, Figure 6 The upper side shows the replacement information 13B before the update, and Figure 6 The updated replacement information 13B is shown below.

[0079] Here, in Figure 6, the example of a battery identified by battery ID "A000002" being installed in an empty slot at 19:18:52 on June 13, 2023 is shown as an example only. In this case, providing unit 15A refers to the data entry in the second row corresponding to battery ID "A000002" in the data entry included in replacement information 13B. Moreover, providing unit 15A calculates the difference (≈2.15 days) between the current date and time "19:18:52 on June 13, 2023" and the replacement date and time "15:36:27 on June 11, 2023" included in the data entry for battery ID "A000002" as the latest replacement interval. Then, providing unit 15A updates the replacement interval included in the data entry in the second row corresponding to battery ID "A000002" to the latest replacement interval of "2.15 days." Furthermore, providing unit 15A updates the replacement date and time included in the data entry in the second row corresponding to battery ID “A000002” to the latest replacement date and time “19:18:52 on June 13, 2023”.

[0080] In addition, Figure 6 In the example, the interval for obtaining the magnetic field distribution of the battery is considered to be equivalent to the battery replacement interval, but the present invention is not limited to this. For example, the battery replacement interval can be the interval between removing the battery from the charged slot and installing it in the vacant slot.

[0081] As another aspect, in addition to the above-mentioned user authentication, the providing unit 15A can also settle the battery replacement fee. For example, in the case of a user who joins a pay-per-use service in which a fee is charged each time the service is used, the providing unit 15A can use the settlement information corresponding to the user ID each time the user ID is obtained from the site 30 to settle the charging fee corresponding to the pay-per-use fee. In addition, in the case of a user who joins a continuous charge service in which fees are incurred after joining the service and are continuously paid until the user cancels the service, such as a periodic charge or a charge-by-volume charge, the providing unit 15A can perform the following processing. For example, in the case of periodic charges, the providing unit 15A inquires whether the payment of fees up to the request date corresponding to the time point when the user ID was obtained from the site 30 has been completed. In addition, in the case of a charge-by-volume charge, the providing unit 15A inquires whether the payment of fees corresponding to the cumulative charge amount at the time point when the user ID was obtained from the site 30 has been completed. As a result, if the payment of the fees is completed, the providing unit 15A determines that the settlement is successful (OK). Even when the payment of the fee is not completed, the providing unit 15A attempts to settle the fee, and when the payment of the fee is successful, it is determined that the settlement is successful.

[0082] As another aspect, the providing unit 15A can also output permission or non-permission for battery replacement based on the authenticity determination result of the determination unit 15B described later. For example, if the battery installed in the empty slot is determined to be a genuine product, the providing unit 15A notifies the station 30 that the battery replacement is permitted. Upon notification of the permission for replacement, the station 30 permits the battery to be removed from the charged slot. On the other hand, if the battery installed in the empty slot is determined to be a non-genuine product, the providing unit 15A notifies the station 30 that the battery replacement is not permitted. Upon notification of the non-permission for replacement, the station 30 prohibits the battery from being removed from the charged slot.

[0083] Determination unit 15B is a processing unit that performs an authenticity determination to determine whether the battery is a genuine product. In one embodiment, determination unit 15B performs the authenticity determination by comparing the magnetic field distribution of the user's battery obtained by providing unit 15A with the magnetic field distribution of genuine batteries registered as a reference in reference information 13C stored in storage unit 13.

[0084] Here, reference information 13C may be a collection of data that associates the magnetic field distribution of the legitimate battery with each battery ID used to identify the legitimate battery. For example, if the measurement unit 33 of the station 30 is implemented by a three-axis magnetic sensor, the reference information 13C may store three magnetic field distributions, namely, the X-component magnetic field distribution, the Y-component magnetic field distribution, and the Z-component magnetic field distribution, for a single battery ID.

[0085] After executing the authenticity determination, the determination unit 15B updates the number of times the authenticity determination of the battery is executed, which is included in the number of times the authenticity determination of the battery is executed and stored in the determination count information 13D of the storage unit 13 .

[0086] Figure 7 : is a diagram showing an example of updating the number of times the battery authenticity determination is performed. Figure 7 As shown, the determination number information 13D is data that associates items such as the number of times the authenticity determination is performed with each battery ID. Figure 7 The upper side shows the number of determination information 13D before the update, and Figure 7 The updated determination number information 13D is shown below. Figure 7As shown in the example, the case where the authenticity check is performed on a battery identified by battery ID "A000002" is described. In this case, determination unit 15B refers to the data entry in the second row corresponding to battery ID "A000002" in the data entry included in the number of times the authentication check is performed 13D. Determination unit 15B then increments the number of times the authentication check is performed, contained in the data entry in the second row corresponding to battery ID "A000002," by 1, thereby updating the number from "11" to "12."

[0087] Back to Figure 5 As described above, setting unit 15C is a processing unit that sets a threshold value to be compared with the number of times authentication determinations are performed. In one embodiment, setting unit 15C sets threshold value Th2 based on the replacement interval of batteries included in replacement information 13B, for which authentication determination unit 15B has performed authentication determinations.

[0088] Figure 8 It is a schematic diagram showing an example of setting a threshold value. Figure 8 The horizontal axis of the graph G1 shown in FIG. 1 is the battery replacement interval (day), and the vertical axis is the threshold value (number of times). Figure 8 As shown, graph G1 defines a function f1 that increases the threshold as the battery replacement interval shortens, or in other words, a function f1 that decreases the threshold as the battery replacement interval lengthens. Based on this function f1, setting unit 15C can set threshold Th2, which is compared with the number of times the authenticity determination is performed. For example, consider the case where the authenticity determination of a battery identified by battery ID "A000002" is performed. In this case, setting unit 15C refers to the data entry in the second row corresponding to battery ID "A000002" in the data entry included in replacement information 13B. Setting unit 15C then substitutes the replacement interval "2.15" contained in the data entry for battery ID "A000002" as an explanatory variable for function f1, thereby calculating threshold "12" as the target variable for function f1. Setting unit 15C then sets the threshold "12" calculated as the target variable for function f1 as threshold Th2.

[0089] By setting the threshold Th2, which is compared with the number of authenticity determination executions, based on this function f1, the threshold can be reduced when the battery replacement interval is long, and increased when the battery replacement interval is short. Therefore, the threshold can be dynamically changed according to the battery replacement interval, allowing for adjustment of the threshold to balance the risk of adopting a deviating value with the advantage of reflecting deterioration over time in the reference.

[0090] In addition, Figure 8In the example of the function that defines the correspondence between the battery replacement interval and the threshold value, a linear function f1 is given, but the function may not be linear but may be nonlinear. Figure 8 An example is given in which the correspondence between the battery replacement interval and the threshold value is defined by a function, but the relationship may be defined by other methods other than a function, such as a lookup table.

[0091] Back to Figure 5 As described above, the updating unit 15D is a processing unit that updates the reference magnetic field distribution using the magnetic field distribution of the battery when the conditions for updating the reference magnetic field distribution are met. As an embodiment, the updating unit 15D determines whether the number of times the authenticity determination of the battery, which has been authenticated by the authentication unit 15B, in the authentication count information 13D is greater than or equal to the threshold value Th2 set by the setting unit 15C. In this case, if the number of times the authenticity determination of the battery has been executed is greater than or equal to the threshold value Th2, the updating unit 15D resets the number of times the authenticity determination of the battery is executed and then begins updating the reference. In addition, here, an example of resetting the number of times the authenticity determination is executed is given, but instead of this method, an offset value corresponding to the number of times the authenticity determination is executed can be added to the threshold.

[0092] As an example, updating unit 15D updates the reference magnetic field distribution using the magnetic field distribution of a battery determined by determination unit 15B to be a genuine product. For example, updating unit 15D overwrites the reference magnetic field distribution corresponding to the battery ID of the battery installed in the vacant slot of station 30 in reference information 13C with the magnetic field distribution of the battery determined by determination unit 15B to be a genuine product. This updates the reference magnetic field distribution to the latest one.

[0093] As another example, the updating unit 15D may update the reference magnetic field distribution using a plurality of magnetic field distributions obtained from a battery installed in an empty slot of the station 30 a plurality of times in the past.

[0094] Figure 9 is a schematic diagram showing an update example for reference. Figure 9 An example of the magnetic field distribution of the reference for updating the battery ID "A00002" is shown in FIG. Figure 9 As shown, the updating unit 15D can use n magnetic field distributions acquired at each time point from the current authenticity judgment to the nth authenticity judgment before as reference for updating. Figure 9In the example shown, n magnetic field distributions for battery ID "A00002" can be synthesized into a single magnetic field distribution by performing statistical processing such as arithmetic averaging, weighted averaging, or moving averaging. The magnetic field distribution obtained through such synthesis is sometimes referred to as a "synthesized magnetic field distribution." Based on this, update unit 15D overwrites the reference magnetic field distribution corresponding to battery ID "A00002" in reference information 13C with the synthesized magnetic field distribution.

[0095] In addition, Figure 9 , an example is shown in which a plurality of magnetic field distributions are combined into one magnetic field distribution. However, it is not necessary to combine them into one magnetic field distribution. In addition, the magnetic field distribution stored as a reference is not necessarily one.

[0096] As an example, the update unit 15D can also estimate the distribution, such as a probability density function, that each magnetic field distribution follows based on multiple magnetic field distributions acquired multiple times in the past, and save the estimated distribution as a reference. As another example, the update unit 15D can also pre-save all magnetic field distributions acquired in the past, and can also, for each magnetic flux density measurement point, use as a reference a set of measured values ​​obtained by excluding deviations, such as values ​​that deviate from the mean ±3σ, from the measured values ​​of the magnetic flux density at that measurement point and extracting the most recent measured value. As another example, the update unit 15D can also use a machine learning model such as a VAE (Variational AutoEncoder) or a GAN (Generative Adversarial Networks) generator to save as a reference simulated magnetic field distribution data generated from actual magnetic field distribution measurement data. As another example, the update unit 15D calculates the difference between the magnetic field distribution (this magnetic field distribution) of a battery determined by the determination unit 15B to be a genuine product and the previous magnetic field distribution saved as a reference for that battery. Moreover, when the difference relative to the previous magnetic field distribution is greater than or equal to the threshold, that is, when the amount of change is large, the update unit 15D can retain or prohibit the storage of this magnetic field distribution as a reference. In addition, the application examples cited so far are not limited to reference updates, and can also be applied to the mechanical differences of the measuring unit 33 and the battery during the comparison of the magnetic field distribution. For example, in order to prevent the situation where misalignment occurs during the measurement of the measuring unit 33, a reference corresponding to the measuring environment is saved in advance for each measuring environment, so that the mechanical differences of the measured batteries can be coped with. For example, in the above-mentioned measuring environment, in addition to the arrangement pattern of each magnetic sensor, the positional relationship between the measuring unit 33 and the battery (such as the distance between a specific magnetic sensor and the battery) and the like can also be included.

[0097] <Processing Flow>

[0098] Figure 10This is a flowchart (1) showing the overall processing flow. This processing is just an example and can be started when the user ID is received from the site 30. Figure 10 As shown, the providing unit 15A compares the user ID registered in the user information 13A with the user ID received from the site 30 and performs user authentication to determine whether the user is a legitimate user whose user ID is registered in the user information 13A (step S101).

[0099] At this time, if user authentication is successful, that is, if the user is a legitimate user with a user ID registered in user information 13A (Yes in step S101), providing unit 15A outputs a battery installation instruction to the vacant slot to station 30 (step S102).

[0100] Then, when the user's battery is installed in the vacant slot of the station 30 , the providing unit 15A acquires the magnetic field distribution of the battery measured by the measuring unit 33 of the station 30 (step S103 ).

[0101] Next, the providing unit 15A updates the battery replacement interval included in the battery replacement information 13B stored in the storage unit 13 (step S104 ).

[0102] Next, the determination unit 15B performs an authenticity determination on whether the battery installed in the vacant slot is a genuine product based on the result of comparing the magnetic field distribution of the battery acquired in step S103 with the reference magnetic field distribution stored in the reference information 13C (step S105).

[0103] If the battery is determined to be a genuine product (Yes in step S106), the providing unit 15A notifies the station 30 that the battery replacement is permitted (step S107). The station 30 notified of the replacement permission permits the battery to be removed from the charged slot.

[0104] On the other hand, if user authentication fails or the battery is determined to be non-genuine (No in step S101 or No in step S106), the providing unit 15A performs the following processing. Specifically, the providing unit 15A notifies the station 30 that battery replacement is not permitted (step S108), and the processing ends. At the station 30 notified of the non-permission for replacement, the battery is prohibited from being removed from the charged slot.

[0105] After executing step S107, the determination unit 15B updates the number of times the authenticity determination of the battery is executed, which is included in the number of times the authenticity determination is executed and stored in the determination count information 13D of the storage unit 13 (step S109).

[0106] Then, the setting unit 15C sets the threshold value Th2 based on the replacement interval of the battery whose authenticity has been determined in step S105 among the replacement intervals of the batteries included in the replacement information 13B (step S110 ).

[0107] Based on this, the updating unit 15D determines whether the number of times the authentication of the battery authenticated in step S105 in the authentication count information 13D is executed is greater than or equal to the threshold value Th2 set in step S110 (step S111).

[0108] Here, if the number of times the battery authenticity determination is performed is greater than or equal to the threshold value Th2 (Yes in step S111), the update unit 15D resets the number of times the battery authenticity determination is performed (step S112). Then, the update unit 15D updates the reference magnetic field distribution using the magnetic field distribution of the battery obtained in step S103 (step S113), and the process ends.

[0109] If the number of times the battery authenticity determination has been performed is not greater than or equal to the threshold value Th2 (No in step S111), the processing of steps S112 and S113 is skipped and the processing ends.

[0110] <One aspect of the effect>

[0111] As described above, the server device 10 according to this embodiment acquires the magnetic field distribution of the battery 3 installed in the vacant slot of the station 30. Furthermore, when the conditions for updating the reference magnetic field distribution used for battery authenticity determination when acquiring the battery's magnetic field distribution are met, the server device 10 updates the reference magnetic field distribution using the battery's magnetic field distribution.

[0112] In this manner, the server device 10 according to this embodiment updates the reference magnetic field distribution conditionally. As just one example, a condition may be set that the number of times the authenticity determination of the battery 3 is performed is greater than or equal to a threshold.

[0113] As one aspect, condition 1, in which the time elapsed since the last reference update is less than threshold 1 and the number of times battery 3 authenticity determinations have been performed is less than threshold 2, can be set as a condition for restricting / prohibiting reference updates. When condition 1 is met, the time elapsed since the last reference update is short, so the effects of both degradation due to the passage of time and degradation due to repeated charging and discharging are minor and difficult to observe. In this case, reference updates are restricted or prohibited, thus preventing excessive frequency of reference updates. As a result, the risk of setting a deviated value as the reference due to external interference during measurement of the battery's magnetic field distribution can be reduced.

[0114] Alternatively, condition 2, that the time elapsed since the last reference update is less than threshold 1 and the number of times battery 3 authenticity checks have been performed is greater than or equal to threshold 2, can be set as a condition for permitting reference updates. When condition 2 is met, the time elapsed since the last reference update is short, so the effects of time-related degradation are minimal. On the other hand, the number of times authenticity checks have been performed is high, so degradation due to repeated charge and discharge cycles may progress. In this case, updating the reference prevents inadequate frequency of reference updates. As a result, the effects of degradation due to repeated charge and discharge cycles can be reflected in the reference.

[0115] In another aspect, condition 3, that the time elapsed since the last reference update is greater than or equal to threshold 1, can be set as a condition for allowing reference updates. If condition 3 is met, the time elapsed since the last reference update is long, and thus, degradation due to the passage of time may have progressed and affected the reference. In this case, updating the reference prevents inadequate frequency of reference updates. As a result, the effects of degradation due to the passage of time can be reflected in the reference.

[0116] In this way, the server device 10 according to this embodiment can balance the risk of adopting a deviated value with the advantage of reflecting degradation caused by the passage of time and / or degradation caused by repeated charging and discharging in the reference. Therefore, the server device 10 according to this embodiment can optimize the frequency of reference updates.

[0117] <Implementation Method 2>

[0118] Furthermore, while the first embodiment described above illustrates an example in which a threshold value is set based on the battery replacement interval and compared with the number of times the battery authenticity determination is performed, it is not essential to set the threshold value based on the battery replacement interval. Therefore, this embodiment describes an example in which a threshold value is set based on the frequency with which batteries are determined to be genuine at station 30.

[0119] <Configuration of Server Device 20>

[0120] Figure 11 This is a block diagram showing an example of the functional configuration of the server device 20 (2). Figure 11 In the Figure 5 Functional parts with the same functions as those shown in the figure are marked with the same reference numerals and their descriptions are omitted. Figure 11 As shown, the server device 20 and Figure 5 The server device 10 shown in FIG. 1 is different in that the storage unit 23 stores the frequency information 23A instead of the replacement information 13B. Figure 5The determination unit 15B and the setting unit 15C shown are different in that a part of the processing executed by the determination unit 25A and the setting unit 25B included in the control unit 25 is different.

[0121] The determination unit 25A and Figure 5 The difference between the judgment unit 15B and the above-mentioned one is that, after updating the number of times the battery authenticity judgment is performed, it also updates the frequency of bringing genuine products to the authenticity judgment station 30. The "frequency" mentioned here can include the number of times, probability, probability distribution, etc.

[0122] Figure 12 2 is a diagram showing an example of updating the frequency information 23A. Figure 12 As shown, the frequency information 23A is data that associates items such as the number of times (probability) regular products are brought in and the number of times (probability) irregular products are brought in with each station. Among them, the "number of times (probability) regular products are brought in" refers to the number of times (probability) that the battery brought in by the user to the station 30 is determined to be a regular product. In addition, the "number of times (probability) irregular products are brought in" refers to the number of times (probability) that the battery brought in by the user to the station 30 is determined to be an irregular product. In addition, Figure 12 The upper side of the diagram shows the frequency information 23A before the update, and Figure 12 The updated frequency information 23A is shown below .

[0123] Here, in Figure 12 The figure shows, as an example, an update example of the brought-in frequency information 23A when a battery with the battery ID "A000002" brought into the station "Koto-ku B" is found to be a "genuine product" as a result of authenticity determination.

[0124] In this case, the data entry for the site "Koto-gu B" in the data entry included in the frequency of bringing-in information 23A, that is, the data entry in the second row, is updated. Specifically, because the battery authenticity test result is "authentic," the number of times authentic products were brought in at site "Koto-gu B," "34," is incremented by 1. Meanwhile, the number of times illegitimate products were brought in at site "Koto-gu B," which remains unchanged, is not updated.

[0125] Thus, the latest number of times non-standard products are brought in remains at "15" and is not updated, while the latest number of times standard products are brought in increases from "34" to "35." Although not shown in the figure, the total number of times brought in also increases from "49 (=34+15)" to "50."

[0126] Furthermore, the probability of legitimate product introductions at site "Gangdong-gu B" is updated from "69%" to "70%" by dividing the latest number of legitimate product introductions (35) by the latest total number of introductions (50). Meanwhile, the probability of illegitimate product introductions at site "Gangdong-gu B" is updated from "31%" to "30%" by dividing the latest number of illegitimate product introductions (15) by the latest total number of introductions (50).

[0127] Back to Figure 11 Description, setting unit 25B and Figure 5 The setting unit 15C shown in FIG. 1 has a different basis for setting the threshold value compared with the number of times the battery authenticity determination is performed. Specifically, the setting unit 25B sets the threshold value Th3 based on the frequency of bringing in genuine products to the station 30 .

[0128] Figure 13 It is a schematic diagram showing an example of setting a threshold value. Figure 13 The horizontal axis of the graph G2 shown in FIG. 2 is the probability (%) of bringing in regular products, and the vertical axis is the threshold (number of times). Figure 13 As shown, graph G2 defines a function f2 that increases the threshold value as the probability of genuine product introduction increases, or, in other words, decreases the threshold value as the probability of genuine product introduction decreases. Based on this function f2, setting unit 25B can set threshold value Th3, which is compared with the number of times authenticity verification is performed. For example, consider the case where battery authenticity verification is performed at station "Jiangdong District B." In this case, setting unit 25B refers to the data entry in the second row corresponding to station "Jiangdong District B" contained in the introduction frequency information 23A. Setting unit 25B then substitutes the probability of genuine product introduction "70%" contained in the data entry for station "Jiangdong District B" as an explanatory variable for function f2, thereby calculating threshold value "12" as the target variable for function f2. Based on this, setting unit 25B sets threshold value "12," calculated as the target variable for function f2, as threshold value Th3.

[0129] By setting a threshold value Th3, which is compared with the number of authenticity checks performed, based on this function f2, the threshold value can be reduced when the probability of legitimate product introduction is low, and increased when the probability of legitimate product introduction is high. Therefore, the threshold value can be dynamically changed based on the probability of legitimate product introduction, allowing for adjustment of the threshold value to balance the risk of adopting a deviating value with the advantage of reflecting degradation over time in the reference.

[0130] In addition, Figure 13 In the example of defining the relationship between the probability of the normal product and the threshold, a linear function f2 is given, but the function does not have to be linear and can be nonlinear. Figure 13 An example of defining the correspondence between the probability of bringing in a regular product and the threshold value using a function is given, but it can also be defined by other methods other than functions, such as a lookup table.

[0131] <Processing Flow>

[0132] Figure 14 This is a flowchart (2) showing the overall processing flow. Figure 14 The processing shown is just an example and can be started when a user ID is received from the site 30. Figure 14 Marked with Figure 10 The flowchart shown has different step numbers for different processes. Figure 10 In the flowchart shown, the same processing is assigned the same step number.

[0133] like Figure 14 As shown, the providing unit 15A compares the user ID registered in the user information 13A with the user ID received from the site 30 to perform user authentication to determine whether the user is a legitimate user whose user ID is registered in the user information 13A (step S101 ).

[0134] At this time, if user authentication is successful, that is, if the user is a legitimate user with a user ID registered in user information 13A (Yes in step S101), providing unit 15A outputs a battery installation instruction to the vacant slot to station 30 (step S102).

[0135] Then, when the user's battery is installed in the vacant slot of the station 30 , the providing unit 15A acquires the magnetic field distribution of the battery measured by the measuring unit 33 of the station 30 (step S103 ).

[0136] Next, the determination unit 15B performs an authenticity determination on whether the battery installed in the vacant slot is a genuine product based on the result of comparing the magnetic field distribution of the battery acquired in step S103 with the reference magnetic field distribution stored in the reference information 13C (step S105).

[0137] If the battery is determined to be a genuine product (Yes in step S106), the providing unit 15A notifies the station 30 that the battery replacement is permitted (step S107). The station 30 notified of the replacement permission permits the battery to be removed from the charged slot.

[0138] On the other hand, if user authentication fails or the battery is determined to be non-genuine (No in step S101 or No in step S106), the providing unit 15A performs the following processing. Specifically, the providing unit 15A notifies the station 30 that battery replacement is not permitted (step S108), and the processing ends. At the station 30 notified of the non-permission for replacement, the battery is prohibited from being removed from the charged slot.

[0139] After executing step S107, the determination unit 15B updates the number of times the authenticity determination of the battery is executed, which is included in the number of times the authenticity determination is executed and stored in the determination count information 13D of the storage unit 13 (step S109).

[0140] Next, the determination unit 25A updates the genuine product bringing frequency corresponding to the site 30 that performed the authenticity determination in step S105 , among the genuine product bringing frequencies included in the bringing frequency information 23A (step S301 ).

[0141] Then, the setting unit 25B sets the threshold value Th3 based on the genuine product bringing frequency of the site 30 where the authenticity determination was performed in step S105 , among the genuine product bringing frequencies included in the bringing frequency information 23A (step S302 ).

[0142] Based on this, the updating unit 15D determines whether the number of times the authentication of the battery authenticated in step S105 in the authentication count information 13D is executed is greater than or equal to the threshold value Th3 set in step S302 (step S111).

[0143] Here, if the number of times the battery authenticity determination is performed is greater than or equal to the threshold value Th3 (Yes in step S111), the update unit 15D resets the number of times the battery authenticity determination is performed (step S112). Then, the update unit 15D updates the reference magnetic field distribution using the magnetic field distribution of the battery obtained in step S103 (step S113), and the process ends.

[0144] If the number of times the battery authenticity determination has been performed is not equal to or greater than the threshold value Th3 (No in step S111), the processing of steps S112 and S113 is skipped and the processing ends.

[0145] <One aspect of the effect>

[0146] As described above, the server device 20 of this embodiment, like the server device 10 of the first embodiment, can optimize the reference update frequency. Furthermore, like the server device 10 of the first embodiment, the server device 20 of this embodiment can dynamically change the threshold value used for comparison with the number of authentication executions based on the frequency with which batteries are determined to be genuine at the site 30.

[0147] <Other implementation methods>

[0148] Furthermore, although the embodiments of the present invention have been described so far, the present invention can be applied in various ways and can be implemented in various different forms in addition to the above-described embodiments.

[0149] In the first and second embodiments, as an example of the condition for updating the reference, the number of times the battery authenticity determination is performed is equal to or greater than the threshold value, but the present invention is not limited thereto.

[0150] For example, the update unit 15D can also use the score output by the machine learning model that has been fed with the battery's magnetic field distribution as input to determine whether the reference magnetic field distribution has been updated. The "score" here refers to the likelihood that the battery is a genuine product and can include, for example, probability, reliability, likelihood, etc.

[0151] Examples of machine learning models that output scores for category classification include logistic regression and support vector machines.

[0152] For example, when the time series data of the scores output for each of the multiple magnetic field distributions by the machine learning model that has been input with multiple magnetic field distributions acquired multiple times in the past shows a decreasing trend, the update unit 15D can also update the reference.

[0153] Figure 15 FIG is a diagram showing an application example of the reference update condition. Figure 15As shown, after the second authenticity determination, recursive analysis is performed on the time series data of the scores to obtain an approximate straight line. For example, at the time of the second authenticity determination, recursive analysis is applied to the scores from the first and second authenticity determinations, resulting in an approximate straight line L1 indicated by a dashed line. The slope of approximate straight line L1 is not less than or equal to the threshold value Th4, so no reference update is performed at the time of the second authenticity determination. Furthermore, at the time of the third authenticity determination, recursive analysis is applied to the time series data of the scores from the first to the third authenticity determinations to obtain an approximate straight line L2 indicated by a dashed line. The slope of approximate straight line L2 is also not less than or equal to the threshold value Th4, so no reference update is performed at the time of the third authenticity determination. Furthermore, at the time of the fourth authenticity determination, recursive analysis is applied to the time series data of the scores from the first to the fourth authenticity determinations to obtain an approximate straight line L3 indicated by a solid line. Since the slope of the approximate straight line L3 is less than or equal to the threshold value Th4, the reference update is executed at the time of the fourth authenticity determination.

[0154] The condition for updating the reference is determined by determining whether the slope of the approximate line is less than or equal to a specific threshold, not only by the score itself but also by whether the score is decreasing. For example, using a support vector machine as an example, a normalized score is outputted within the range of -1 to +1, but if the sign of the score is positive, it is determined to be a normal product. Even in such a situation where the sign of the score is positive, if the score is decreasing, updating the reference will make the effects of degradation over time more significant, allowing the reference to be updated before false positives occur.

[0155] It does not prevent the update conditions of the other references from being set. For example, when the cumulative number of times the battery has been charged is greater than or equal to a threshold, the update unit 15D can update the reference magnetic field distribution. In addition, when the cumulative charge amount of the battery is greater than or equal to a threshold, the update unit 15D can update the reference magnetic field distribution. Furthermore, when the time elapsed since the last authenticity determination of the battery is greater than or equal to a threshold, the update unit 15D can update the reference magnetic field distribution. In addition, the update unit 15D can update the reference magnetic field distribution every time the magnetic field distribution of the battery is acquired.

[0156] While the example herein uses a machine learning model to derive the above score, this is not limiting and can be achieved using any model, such as a statistical model. For example, in addition to state-space representation and transfer function models, the score can be derived using any mathematical model, such as an FIR (Finite Impulse Response) model or a step response.

[0157] <Numerical values, etc.>

[0158] The matters described in the above embodiment, such as the number of magnetic sensors provided by the measuring unit 33 of the station 30 and the specific examples of the reference setting method, are merely examples and may be changed. In addition, the flowcharts described in the embodiment may also change the order of processing within the range of no contradiction.

[0159] <System>

[0160] The information, including the processing flow, control flow, specific names, various data, and parameters described above and shown in the accompanying drawings, can be arbitrarily modified, except where otherwise noted. For example, any one or more of the functional units of the provision unit 15A, determination unit 15B, setting unit 15C, and update unit 15D included in the server device 10 may be comprised of different devices. Furthermore, any one or more of the functional units of the provision unit 15A, determination unit 25A, setting unit 25B, and update unit 15D included in the server device 20 may be comprised of different devices.

[0161] Furthermore, the components of the devices shown in the diagrams are functional concepts and do not necessarily need to be physically configured as shown. Specifically, the specific methods of distributing and integrating the devices are not limited to those shown. Specifically, all or part of the components can be functionally or physically distributed / integrated in arbitrary units based on various loads, usage conditions, and other factors. Furthermore, each structure can be a physical one.

[0162] Furthermore, all or any part of each processing function performed by each device may be realized by a CPU (Central Processing Unit) and a program analyzed and executed by the CPU, or may be realized as hardware based on wired logic.

[0163] Hardware

[0164] Next, a hardware configuration example of the computer described in the first and second embodiments will be described. Figure 16 FIG is a diagram showing an example of a hardware configuration. Figure 16As shown, the information processing device 100 includes a communication device 100a, a HDD (Hard Disk Drive) 100b, a memory 100c, and a processor 100d. Figure 16 The components shown are connected to each other by a bus or the like.

[0165] The communication device 100a is a network interface card, etc., and performs communication with other servers. Figure 5 or Figure 11 The program, DB, etc. that execute the functions shown are stored.

[0166] The processor 100d will execute the Figure 5 or Figure 11 The program for the same processing as that of the processing unit shown is read from the HDD 100b or the like and expanded in the memory 100c, thereby executing Figure 5 or Figure 11 The process execution action of the function described in.

[0167] This process performs the same functions as the processing units included in server devices 10 and 20. For example, processor 100d reads a program having the same functions as providing unit 15A, determining unit 15B, setting unit 15C, and updating unit 15D from HDD 100b, etc. Processor 100d then executes a process that performs the same processing as providing unit 15A, determining unit 15B, setting unit 15C, and updating unit 15D. Furthermore, processor 100d reads a program having the same functions as providing unit 15A, determining unit 25A, setting unit 25B, and updating unit 15D from HDD 100b, etc. Processor 100d then executes a process that performs the same processing as providing unit 15A, determining unit 25A, setting unit 25B, and updating unit 15D.

[0168] In this manner, the information processing device 100 operates as an information processing device that performs the evaluation method by reading and executing the program. Furthermore, the information processing device 100 can also achieve the same functions as the above embodiment by reading the program from a recording medium using a media reader and executing the read program. Furthermore, the program described in this other embodiment is not limited to being executed by the information processing device 100. For example, the present invention can also be applied to other computers or servers executing the program, or to other computers or servers operating in collaboration to execute the program.

[0169] The above program can be distributed via a network such as the Internet. In addition, the above program can be recorded on any recording medium and read from the recording medium by a computer for execution. For example, the recording medium can be implemented by a hard disk, a floppy disk (FD), a CD-ROM, an MO (Magneto-Optical disk), a DVD (Digital Versatile Disc), etc.

[0170] <Other>

[0171] Several examples of combinations of disclosed technical features are described below.

[0172] (1) An information processing device, characterized in that:

[0173] The information processing device comprises:

[0174] an acquisition unit that acquires a magnetic field distribution of the battery; and

[0175] An updating unit updates the reference magnetic field distribution using the magnetic field distribution of the battery when a condition for updating the reference magnetic field distribution referred to in the authenticity determination of the battery is satisfied when the magnetic field distribution of the battery is acquired.

[0176] (2) The information processing device according to (1), characterized in that

[0177] The information processing device further includes a determination unit that performs authenticity determination of whether the battery is a genuine product based on a comparison between the magnetic field distribution of the battery and the reference magnetic field distribution.

[0178] The updating unit updates the reference magnetic field distribution using the magnetic field distribution of the battery determined to be a genuine product.

[0179] (3) The information processing device according to (1) or (2), characterized in that

[0180] The updating unit updates the reference magnetic field distribution when the number of times the authenticity determination on the battery is performed is greater than or equal to a threshold value.

[0181] (4) The information processing device according to (3), characterized in that

[0182] The information processing device further includes a setting unit that sets the threshold value based on an interval at which the magnetic field distribution of the battery is acquired.

[0183] (5) The information processing device according to (4), characterized in that

[0184] The setting unit sets a larger threshold value as the interval becomes shorter.

[0185] (6) The information processing device according to (3), characterized in that

[0186] The information processing device further includes a setting unit configured to set the threshold value based on a frequency of determining that a battery charged at a station corresponding to a charging source of the battery is a genuine product.

[0187] (7) The information processing device according to (6), characterized in that

[0188] The setting unit sets a larger threshold value as the frequency increases.

[0189] (8) The information processing device according to any one of (3) to (7), characterized in that:

[0190] When the reference magnetic field distribution is updated, the updating unit resets the number of times the authenticity determination of the battery is performed.

[0191] (9) The information processing device according to (1) or (2), characterized in that

[0192] The updating unit updates the reference magnetic field distribution when the cumulative number of times the battery has been charged is greater than or equal to a threshold value.

[0193] (10) The information processing device according to (1) or (2), characterized in that

[0194] The updating unit updates the reference magnetic field distribution when the cumulative charge amount of the battery is greater than or equal to a threshold value.

[0195] (11) The information processing device according to (1) or (2), characterized in that

[0196] The updating unit updates the reference magnetic field distribution when an elapsed time after the authenticity determination on the battery was last performed is greater than or equal to a threshold value.

[0197] (12) The information processing device according to (1) or (2), characterized in that

[0198] The updating unit updates the reference magnetic field distribution every time the magnetic field distribution of the battery is acquired.

[0199] (13) The information processing device according to (1) or (2), characterized in that

[0200] For a model that takes the magnetic field distribution of a battery as input and outputs a score indicating the possibility that the battery is a regular product, the magnetic field distribution of the battery is input separately, and multiple magnetic field distributions obtained from the battery multiple times in the past are input respectively. Thus, when the slope of the approximate straight line of the scores output by the model for each of the multiple magnetic field distributions is less than or equal to a threshold value, the update unit updates the reference magnetic field distribution.

[0201] (14) The information processing device according to any one of (1) to (13), characterized in that

[0202] The updating unit updates the reference magnetic field distribution using a plurality of magnetic field distributions of the battery acquired from the battery a plurality of times in the past.

[0203] (15) An updating method, characterized in that:

[0204] The updating method is performed by a computer as follows:

[0205] Get the magnetic field distribution of the battery,

[0206] When a condition for updating a reference magnetic field distribution referred to in the authenticity determination of the battery when the magnetic field distribution of the battery is acquired is satisfied, the reference magnetic field distribution is updated using the magnetic field distribution of the battery.

[0207] (16) An update program, characterized in that:

[0208] The update program causes the computer to execute the following processing:

[0209] Get the magnetic field distribution of the battery,

[0210] When a condition for updating a reference magnetic field distribution referred to in the authenticity determination of the battery when the magnetic field distribution of the battery is acquired is satisfied, the reference magnetic field distribution is updated using the magnetic field distribution of the battery.

[0211] Description of the label

[0212] 1. Battery Sharing System

[0213] 3 Batteries

[0214] 10 Server Device

[0215] 11 Communication Control Unit

[0216] 13 Storage

[0217] 13A User Information

[0218] 13B Replacement Information

[0219] 13C Reference Information

[0220] 13D judgment count information

[0221] 15 Control Unit

[0222] 15A Provision Department

[0223] 15B Judgment Department

[0224] 15C Setting section

[0225] 15D Update Department

[0226] 30 sites

[0227] 31 Information reading unit

[0228] 33 Measurement Department

Claims

1. An information processing device, characterized in that The information processing device comprises: an acquisition unit that acquires a magnetic field distribution of the battery; and An updating unit updates the reference magnetic field distribution using the magnetic field distribution of the battery when a condition for updating the reference magnetic field distribution referred to in the authenticity determination of the battery is satisfied when the magnetic field distribution of the battery is acquired.

2. The information processing device according to claim 1, wherein The information processing device further includes a determination unit that performs authenticity determination of whether the battery is a genuine product based on a comparison between the magnetic field distribution of the battery and the reference magnetic field distribution. The updating unit updates the reference magnetic field distribution using the magnetic field distribution of the battery determined to be a genuine product.

3. The information processing device according to claim 1, wherein The updating unit updates the reference magnetic field distribution when the number of times the authenticity determination on the battery is performed is greater than or equal to a threshold value.

4. The information processing device according to claim 3, wherein The information processing device further includes a setting unit that sets the threshold value based on an interval at which the magnetic field distribution of the battery is acquired.

5. The information processing device according to claim 4, wherein The setting unit sets a larger threshold value as the interval becomes shorter.

6. The information processing device according to claim 3, wherein The information processing device further includes a setting unit configured to set the threshold value based on a frequency of determining that a battery charged at a station corresponding to a charging source of the battery is a genuine product.

7. The information processing device according to claim 6, wherein The setting unit sets a larger threshold value as the frequency increases.

8. The information processing device according to claim 3, wherein When the reference magnetic field distribution is updated, the updating unit resets the number of times the authenticity determination of the battery is performed.

9. The information processing device according to claim 1, wherein The updating unit updates the reference magnetic field distribution when the cumulative number of times the battery has been charged is greater than or equal to a threshold value.

10. The information processing device according to claim 1, wherein The updating unit updates the reference magnetic field distribution when the cumulative charge amount of the battery is greater than or equal to a threshold value.

11. The information processing device according to claim 1, wherein The updating unit updates the reference magnetic field distribution when an elapsed time after the authenticity determination on the battery was last performed is greater than or equal to a threshold value.

12. The information processing device according to claim 1, wherein The updating unit updates the reference magnetic field distribution every time the magnetic field distribution of the battery is acquired.

13. The information processing device according to claim 1, wherein For a model that takes the magnetic field distribution of a battery as input and outputs a score indicating the possibility that the battery is a regular product, the magnetic field distribution of the battery is input separately, and multiple magnetic field distributions obtained from the battery multiple times in the past are input respectively. Thus, when the slope of the approximate straight line of the scores output by the model for each of the multiple magnetic field distributions is less than or equal to a threshold value, the update unit updates the reference magnetic field distribution.

14. The information processing device according to claim 1, wherein The updating unit updates the reference magnetic field distribution using a plurality of magnetic field distributions of the battery acquired from the battery a plurality of times in the past.

15. An updating method, characterized in that: The updating method is performed by a computer as follows: Get the magnetic field distribution of the battery, When a condition for updating a reference magnetic field distribution referred to in the authenticity determination of the battery when the magnetic field distribution of the battery is acquired is satisfied, the reference magnetic field distribution is updated using the magnetic field distribution of the battery.

16. A computer-readable recording medium having an update program recorded thereon, characterized in that: The update program causes the computer to execute the following processing: Get the magnetic field distribution of the battery, When a condition for updating a reference magnetic field distribution referred to in the authenticity determination of the battery when the magnetic field distribution of the battery is acquired is satisfied, the reference magnetic field distribution is updated using the magnetic field distribution of the battery.

Images