Information processor, update method, and update program

Abstract

To optimize reference update frequency.SOLUTION: An information processor comprises: an acquisition section for acquiring a magnetic field distribution of a battery; and an update section. When a condition to update a magnetic field distribution of a reference referenced in battery authenticity determination is met in acquiring the magnetic field distribution of the battery, the update section updates the magnetic field distribution of the reference using the magnetic field distribution of the battery.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] The present invention relates to an information processing apparatus, an update method, and an update program. [Background technology]

[0002] In order to achieve carbon neutrality, electric vehicles (xEVs), which are powered by motors powered by electricity, are becoming more popular. As xEVs become more popular, efforts are also underway to develop battery sharing services that enable battery sharing by making xEV batteries swappable through the provision of charging equipment that can swap low-charged batteries with fully charged batteries.

[0003] On the other hand, in addition to genuine xEV batteries manufactured by manufacturers, there is also an aspect of non-genuine products being distributed. For example, counterfeit products exist that not only have the appearance of genuine modules or genuine pack casings, but also have forged two-dimensional codes that link to management information such as battery passports that manage the battery's lifecycle from material procurement to recycling.

[0004] For this reason, a technology has been proposed that uses the battery characteristics of a genuine battery as a reference and compares the battery characteristics of the reference with the battery characteristics measured from the battery to be identified, thereby determining whether the battery to be identified is genuine or not.

[0005] The battery characteristics of such batteries are subject to deterioration over time, so one aspect of updating the reference battery characteristics over time is to enable authenticity determination that responds to changes in the battery characteristics over time. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Japanese Patent Application Publication No. 2020-169932 [Patent Document 2] Japanese Patent Application Laid-Open No. 2012-75212 [Patent Document 3] Japanese Patent Application Laid-Open No. 2012-49030 Summary of the Invention [Problem to be solved by the invention]

[0007] However, even if the frequency of updating the reference used in the above-mentioned authenticity determination is increased, the accuracy of the authenticity determination does not necessarily improve. For example, when measuring the battery characteristics, disturbances from the surrounding environment other than the battery are superimposed on the measured battery characteristics. Therefore, if the reference is frequently (e.g., every time) updated to a completely newly acquired battery characteristic, an outlier may be set as the reference, which may reduce the accuracy of the authenticity determination. On the other hand, if the reference is updated too infrequently, the influence of battery deterioration over time will not be reflected in the reference, which may reduce the accuracy of the authenticity determination.

[0008] An object of the present invention is to optimize the frequency of reference updates. [Means for solving the problem]

[0009] An information processing device according to one aspect of the present invention includes an acquisition unit that acquires a magnetic field distribution of a battery, and an update unit that updates the magnetic field distribution of the reference using the magnetic field distribution of the battery when a condition for updating the magnetic field distribution of a reference that is referenced in determining the authenticity of the battery is met when the magnetic field distribution of the battery is acquired.

[0010] In one aspect of the present invention, an updating method involves a computer executing a process in which a magnetic field distribution of a battery is acquired, and if a condition for updating a reference magnetic field distribution that is referenced in determining the authenticity of the battery is met when the magnetic field distribution of the battery is acquired, the reference magnetic field distribution is updated using the magnetic field distribution of the battery.

[0011] An update program according to one aspect of the present invention causes a computer to execute a process of acquiring a magnetic field distribution of a battery, and if a condition for updating a reference magnetic field distribution that is referenced in determining the authenticity of the battery is met when the magnetic field distribution of the battery is acquired, updating the reference magnetic field distribution using the magnetic field distribution of the battery. [Effects of the Invention]

[0012] According to one embodiment, the frequency of reference updates can be optimized. [Brief explanation of the drawings]

[0013] [Figure 1] FIG. 1 is a diagram illustrating an example of the configuration of a battery sharing system. [Figure 2] FIG. 2 is a schematic diagram showing an example of battery replacement. [Figure 3] FIG. 3 is a schematic diagram showing an example of measurement of the magnetic field distribution of a battery. [Figure 4] FIG. 4 is a diagram illustrating one aspect of the problem-solving approach. [Figure 5] FIG. 5 is a block diagram (1) showing an example of the functional configuration of the server device. [Figure 6] FIG. 6 is a diagram showing an example of updating the battery replacement interval. [Figure 7] FIG. 7 is a diagram showing an example of updating the number of times that the authenticity determination of a battery is performed. [Figure 8] FIG. 8 is a schematic diagram showing an example of setting the threshold value. [Figure 9] FIG. 9 is a schematic diagram showing an example of updating a reference. [Figure 10] FIG. 10 is a flowchart (1) showing the procedure of the overall process. [Figure 11] FIG. 11 is a block diagram (2) showing an example of the functional configuration of the server device. [Figure 12] FIG. 12 is a diagram illustrating an example of updating the carry-in frequency information. [Figure 13] FIG. 13 is a schematic diagram showing an example of setting the threshold value. [Figure 14] FIG. 14 is a flowchart (2) showing the procedure of the overall process. [Figure 15] FIG. 15 is a diagram showing an application example of the reference update condition. [Figure 16] FIG. 16 is a diagram illustrating an example of a hardware configuration. DETAILED DESCRIPTION OF THE INVENTION

[0014] Hereinafter, with reference to the accompanying drawings, a description will be given of an information processing device, an update method, and an update program according to the present application (hereinafter referred to as "embodiments"). Each embodiment merely shows examples and aspects, and does not limit the range of values, functions, or usage scenarios. Each embodiment can be adaptively combined within the scope of not causing any contradiction in the processing content.

[0015] <Embodiment 1> <Overall structure> Fig. 1 is a diagram showing an example of the configuration of a battery sharing system. The battery sharing system 1 shown in Fig. 1 provides a battery sharing service that realizes battery sharing by making batteries of xEVs and the like replaceable. Note that although xEVs are used as an example of a battery usage scenario, batteries are not limited to vehicles and may be installed in general load equipment such as construction machinery, agricultural machinery, and home appliances.

[0016] The term "battery" here may refer to a secondary battery such as a lithium-ion battery or a battery pack thereof. For example, the term "battery" may refer to a "cell" which refers to a single battery, a "module" which refers to a battery pack assembled from multiple cells, or a "pack" which refers to a battery pack assembled from multiple modules.

[0017] 1, the battery sharing system 1 may include a server device 10 and stations 30A to 30N. Hereinafter, when it is not necessary to distinguish between the individual stations 30A to 30N, the stations 30A to 30N may be referred to as "stations 30."

[0018] The server device 10 and the station 30 may be communicably connected via any network NW. The network NW may be wired or wireless and may be realized by any technology such as Internet technology, industrial communication standards, or low-power wireless communication standards for IoT (Internet of Things).

[0019] The server device 10 is an example of an information processing device that provides the battery sharing service. For example, the server device 10 can provide the battery sharing service as a cloud service by being realized as a PaaS (Platform as a Service) or SaaS (Software as a Service) application. Alternatively, the server device 10 may be realized as a server that provides, on-premise, a battery sharing function that realizes the battery sharing service.

[0020] Station 30 is an example of a charging facility that exchanges low-charged batteries for charged batteries. Station 30 has multiple slots into which batteries can be attached and detached. Station 30 can charge a battery attached to an empty slot among the multiple slots, and can also remove a fully charged battery from a charged slot.

[0021] <Battery replacement> 2 is a schematic diagram showing an example of battery exchange. As shown in Fig. 2, in station 30, identification information of a user who uses the battery sharing service, for example, a user ID (IDentification), is read (step S1).

[0022] For example, when an IC (Integrated Circuit) card 2 possessed by a user is brought close to an information reading unit 31 of a station 30, the user ID recorded on the IC card 2 is read by the information reading unit 31.

[0023] The user ID read by the information reading unit 31 in this manner is used to authenticate whether the user is a legitimate user who has been pre-registered, as well as to settle the fee for using the battery sharing service described above.

[0024] Thereafter, the battery 3 removed from the vehicle such as an EV is returned by being attached to an empty slot in which no battery has been attached among a plurality of slots that the station 30 has (step S2).

[0025] When returning such a battery 3, a display associated with each slot, such as a lamp, can be displayed in a manner that distinguishes between empty slots and other slots.

[0026] After the battery 3 is returned, the battery 3 is removed from a charged slot among the multiple slots of the station 30 (step S3). Note that "charged" may refer to a fully charged state, but does not necessarily have to be a fully charged state, as an example. For example, a slot in which a battery with an SOC (State Of Charge) of 95% or higher may be installed may be identified as a charged slot.

[0027] The battery 3 thus removed from the charged slot is then attached to the user's vehicle, etc. By performing the operations from step S1 to step S3, the battery 3 can be replaced.

[0028] Note that FIG. 2 shows, as an example, an example in which a user who has been registered in advance replaces the battery, but naturally, this does not prevent a new user from replacing the battery.

[0029] <Magnetic field distribution> While xEVs are becoming more popular, there is also an aspect to the circulation of non-genuine xEV batteries in addition to genuine products manufactured by manufacturers. For example, there are counterfeit products that not only have the appearance of genuine modules or pack casings, but also have two-dimensional codes that link to management information such as battery passports that manage the battery's lifecycle from material procurement to recycling.

[0030] From this perspective, the server device 10 according to this embodiment performs authenticity checks to determine whether a battery is genuine when it is replaced. For example, the authenticity check can be performed by using the battery characteristics of a genuine battery as a reference and comparing the battery characteristics of the reference with the battery characteristics measured from the battery to be identified.

[0031] Hereinafter, as an example of the battery characteristics, an example of performing the above authenticity determination using the magnetic field distribution of the battery will be given. As just one example, the station 30 can acquire the magnetic field distribution of the battery 3 returned in step S2 shown in FIG.

[0032] Fig. 3 is a schematic diagram showing an example of measuring the magnetic field distribution of a battery. As shown in Fig. 3, the magnetic field distribution of battery 3 is measured by a measurement unit 33 realized by a two-dimensional array of magnetic sensors. For example, in the example shown in Fig. 3, measurement unit 33 is realized by arranging magnetic sensors in a 6×16 array on the side of battery 3 to be inserted into the slot of station 30.

[0033] The measurements taken by these 6 vertical × 16 horizontal magnetic sensors, for example, a map of magnetic flux density, are obtained as the magnetic field distribution 20 of the battery 3. For example, if the measurement unit 33 is realized by a three-axis magnetic sensor, the magnetic field distribution 20 of the battery 3 obtained is the magnetic field distribution 20 of the X component 20X, the magnetic field distribution 20Y of the Y component 20Y, and the magnetic field distribution 20Z of the Z component.

[0034] The magnetic field distribution of such a battery is subject to deterioration over time, so one aspect of updating the reference battery characteristics over time is to enable authenticity determination that corresponds to changes in the battery characteristics over time.

[0035] Note that FIG. 3 is merely an example. The measuring unit 33 may be realized by a single-axis magnetic sensor or a two-axis magnetic sensor. The magnetic sensors may be arranged in any manner, including a one-dimensional array. For example, the magnetic sensors may be analog or digital elements. Each magnetic element may be, for example, a Hall element, a magnetoresistive element such as anisotropic magnetoresistance effect (AMR), giant magnetoresistance effect (GMR), or tunnel magnetoresistance effect (TMR), a magneto-impedance element such as MI (Magneto-Impedance), a fluxgate, or a thin-film magnetic element based on the anomalous Hall effect using a topological magnetic material. When an AC current flows through the object to be measured, a pickup coil may be used as the magnetic element.

[0036] <One aspect of the issue> As explained in the Background Art section above, increasing the frequency of updating the reference used in the above-mentioned authentication determination does not necessarily improve the accuracy of the authentication determination. For example, when measuring battery characteristics, disturbances from the surrounding environment other than the battery are superimposed on the measured battery characteristics. Therefore, if the reference is frequently (e.g., every time) updated to completely newly acquired battery characteristics, an outlier may be set as the reference, which may reduce the accuracy of the authentication determination. On the other hand, if the reference is updated too infrequently, the influence of battery deterioration over time is less likely to be reflected in the reference, which may reduce the accuracy of the authentication determination.

[0037] <One aspect of the problem-solving approach> Therefore, the server device 10 of this embodiment provides a reference update function that updates the reference magnetic field distribution when the conditions for updating the reference magnetic field distribution referenced in determining the authenticity of the battery are met when the magnetic field distribution of the battery is acquired.

[0038] Fig. 4 is a diagram showing one aspect of the problem-solving approach. As shown in Fig. 4, the server device 10 acquires the magnetic field distribution of the battery 3 installed in an empty slot of the station 30 (1). Then, if the condition for updating the reference magnetic field distribution referred to in determining the authenticity of the battery is satisfied when the magnetic field distribution of the battery is acquired, the server device 10 updates the reference magnetic field distribution using the magnetic field distribution of the battery (2).

[0039] In this way, the server device 10 updates the reference magnetic field distribution under certain conditions. As just one example, a condition can be set that the number of times authenticity determination of the battery 3 is performed is equal to or greater than a threshold value.

[0040] As one aspect, Condition 1 can be set as a condition for limiting / prohibiting reference updates, where the time elapsed since the last reference update is less than Threshold 1 and the number of times authenticity determination of battery 3 has been performed is less than Threshold 2. When Condition 1 is satisfied, the time elapsed since the last reference update is short, so the effects of both deterioration due to the passage of time and deterioration due to repeated charging and discharging are minor and difficult to observe. In this case, reference updates are limited or prohibited, preventing excessively frequent reference updates. As a result, the risk of an outlier being set as the reference due to disturbances occurring during measurement of the battery's magnetic field distribution can be reduced.

[0041] As another aspect, condition 2 can be set as a condition for permitting reference update: that is, the time elapsed since the last reference update is less than threshold 1 and the number of times authenticity determination of battery 3 has been performed is equal to or greater than threshold 2. When condition 2 is satisfied, the time elapsed since the last reference update is short, so the impact of deterioration due to the passage of time is minor, while the number of times authenticity determination has been performed is high, so deterioration due to repeated charging and discharging may be advanced. In this case, the reference is updated, so that insufficient frequency of reference updates is prevented. As a result, the impact of deterioration due to repeated charging and discharging can be reflected in the reference.

[0042] As a further aspect, Condition 3, that the time elapsed since the last reference update is equal to or greater than Threshold 1, can be set as a condition for allowing reference updates. If Condition 3 is met, a long time has passed since the last reference update, and deterioration due to the passage of time may have had an impact. In this case, the reference is updated, which prevents reference updates from being performed insufficiently. As a result, the impact of deterioration due to the passage of time can be reflected in the reference.

[0043] In this way, the reference update function according to this embodiment can balance the risk of detecting outliers with the benefit of reflecting deterioration over time and / or deterioration due to repeated charging and discharging in the reference. Therefore, the reference update function according to this embodiment can optimize the frequency of reference updates. Furthermore, since unnecessary reference updates are not performed, calculation costs can also be reduced.

[0044] In the following, we will give an example in which the above-mentioned reference update function is packaged as one function of the above-mentioned battery sharing service, but the above-mentioned reference update function may also be provided as a service separate from the above-mentioned battery sharing service.

[0045] <Configuration of Server Device 10> Next, an example of the functional configuration of the server device 10 according to this embodiment will be described. Fig. 5 is a block diagram (1) showing an example of the functional configuration of the server device 10. Fig. 5 shows a schematic diagram of blocks related to the battery sharing service provided by the server device 10.

[0046] As shown in Fig. 5, the server device 10 includes a communication control unit 11, a storage unit 13, and a control unit 15. Note that Fig. 5 only shows a selection of functional units related to the battery sharing service, and the server device 10 may include functional units other than those shown in the figure.

[0047] The communication control unit 11 is a functional unit that controls communication with other devices such as the station 30. As just one example, the communication control unit 11 can be realized by a network interface card. As one aspect, the communication control unit 11 can receive a user ID and a battery magnetic field distribution from the station 30, and output a notification such as permission or denial of battery replacement.

[0048] The storage unit 13 is a functional unit that stores various types of data. As just one example, the storage unit 13 is realized by internal, external, or auxiliary storage of the server device 10. For example, the storage unit 13 may be realized by a storage system (cloud) on a network. For example, the storage unit 13 stores user information 13A, exchange information 13B, reference information 13C, and determination count information 13D. Note that the user information 13A, exchange information 13B, reference information 13C, and determination count information 13D will be described together when reference, generation, or registration is performed.

[0049] 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 realized by a hardware processor. As shown in FIG. 5, the control unit 15 has a providing unit 15A, a determining unit 15B, a setting unit 15C, and an updating unit 15D. Note that the control unit 15 may also be realized by hardwired logic or the like.

[0050] The providing unit 15A is a processing unit that provides the battery sharing service. For example, the providing unit 15A may correspond to an example of an acquiring unit. In one aspect, when the providing unit 15A receives a user ID from the station 30, the providing unit 15A performs user authentication by referring to the user information 13A stored in the storage unit 13. Here, the user information 13A may be a collection of data in which various information including payment information such as credit card and electronic money is associated with each user ID. For example, the user authentication may be achieved by comparing the user ID registered in the user information 13A with the user ID received from the station 30 to determine whether the user is a legitimate user whose user ID is registered in the user information 13A.

[0051] If such user authentication is successful, the providing unit 15A outputs an instruction to the station 30 to install a battery in an empty slot. Then, when the user's battery is installed in an empty 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. At this time, the providing unit 15A can also acquire the ID of the user's battery installed in the empty slot of the station 30. For example, the battery ID recorded on an IC chip mounted on the battery may be acquired. Alternatively, the battery ID of the battery last removed by the user from a charged slot may be acquired as the battery ID of the battery installed in the empty slot of the station 30. In this case, the user information 13A may store, as a history, time-series data of the battery IDs of the battery removed by the user from a charged slot and the battery installed by the user in an empty slot for each user ID. Such time-series data may include the time of removal from the charged slot or installation into the empty slot, and station identification information (station ID). Under such battery ID management, when a battery is inserted into an empty slot, the battery ID of the battery that the user last removed from a charged slot from the battery ID history corresponding to the user ID that has been successfully authenticated may be regarded as the battery ID of the battery inserted into the empty slot of station 30 and obtained.

[0052] After the battery ID and magnetic field distribution of the battery are acquired in this way, the providing unit 15A updates the replacement interval of the battery among the replacement intervals of the battery included in the replacement information 13B stored in the storage unit 13.

[0053] FIG. 6 is a diagram showing an example of updating the battery replacement interval. As shown in FIG. 6, replacement information 13B is data in which items such as the replacement interval and replacement date and time are associated with each battery ID. Among these, "replacement interval" refers to the interval at which a battery is replaced, and may be, for example, the interval (days) between when a battery is installed in an empty slot and when it is installed in the next empty slot. Furthermore, "replacement date and time" refers to the most recent date and time when the battery was replaced. Note that the upper part of FIG. 6 shows replacement information 13B before the update, and the lower part of FIG. 6 shows replacement information 13B after the update.

[0054] FIG. 6 shows, as an example only, an example in which a battery identified by battery ID "A000002" is inserted into an empty slot at 19:18:52 on June 13, 2023. In this case, the providing unit 15A references the data entry in the second row corresponding to battery ID "A000002" among the data entries included in the replacement information 13B. The providing unit 15A then 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. Thereafter, the 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, the providing unit 15A updates the replacement date and time included in the data entry in the second row corresponding to the battery ID "A000002" to the latest replacement date and time "June 13, 2023, 19:18:52."

[0055] 6 shows an example in which the interval at which the magnetic field distribution of the battery is acquired is considered to be equivalent to the interval at which the battery is replaced, but this is not limiting. For example, the interval at which the battery is replaced may be the interval between when the battery is removed from a charged slot and when it is inserted into an empty slot.

[0056] In another aspect, in addition to the above-described user authentication, the providing unit 15A can also settle the battery replacement fee. For example, in the case of a user who subscribes to a pay-per-use service in which a charge is made for each use of the service, the providing unit 15A can settle the charging fee corresponding to the pay-per-use charge each time the user ID is acquired from the station 30, using the payment information corresponding to the user ID. Also, in the case of a user who subscribes to a recurring charge system in which a charge is incurred after subscribing to the service and continues until the user cancels the service, such as a periodic charge or a pay-per-use charge, the providing unit 15A can execute the following process. For example, in the case of periodic charge, the providing unit 15A inquires whether payment of the fee up to the billing date corresponding to the time when the user ID is acquired from the station 30 has been completed. Also, in the case of pay-per-use charge, the providing unit 15A inquires whether payment of the fee corresponding to the accumulated amount of charge at the time when the user ID is acquired from the station 30 has been completed. As a result, if payment of the fee has been completed, the providing unit 15A determines that the payment is OK. Furthermore, even if the payment of the fee is incomplete, the providing unit 15A attempts to settle the fee, and if the payment of the fee is successful, determines that the payment is OK.

[0057] As a further aspect, the providing unit 15A can also output permission or denial of permission to replace the battery depending on the result of the authenticity determination by the determination unit 15B, which will be described later. For example, if the battery installed in the empty slot is determined to be genuine, the providing unit 15A notifies the station 30 that the battery replacement is permitted. The station 30 that has been notified of this permission to replace the battery is permitted to remove the battery from the charged slot. On the other hand, if the battery installed in the empty slot is determined to be non-genuine, the providing unit 15A notifies the station 30 that the battery replacement is not permitted. The station 30 that has been notified of this denial of replacement is prohibited from removing the battery from the charged slot.

[0058] The determination unit 15B is a processing unit that performs an authenticity determination to determine whether the battery is a genuine product. In one embodiment, the determination unit 15B performs the authenticity determination by comparing the magnetic field distribution of the user's battery acquired by the provision unit 15A with the magnetic field distribution of a genuine battery registered as a reference in the reference information 13C stored in the memory unit 13.

[0059] Here, the reference information 13C may be a set of data in which the magnetic field distribution of a genuine battery is associated as a reference for each battery ID that identifies the genuine battery. For example, if the measurement unit 33 of the station 30 is realized by a triaxial magnetic sensor, the reference information 13C may store three magnetic field distributions, namely, an X-component magnetic field distribution, a Y-component magnetic field distribution, and a Z-component magnetic field distribution, in association with each battery ID.

[0060] After the authenticity determination is performed, the determination unit 15B updates the number of times that the authenticity determination of the battery has been performed, among the number of times that the authenticity determination of the battery has been performed, which is included in the determination count information 13D stored in the storage unit 13.

[0061] FIG. 7 is a diagram illustrating an example of updating the number of times authenticity determination of a battery is performed. As illustrated in FIG. 7, the determination count information 13D is data in which items such as the number of times authenticity determination has been performed are associated with each battery ID. Here, the upper side of FIG. 7 illustrates the determination count information 13D before the update, and the lower side of FIG. 7 illustrates the determination count information 13D after the update. For example, as illustrated in FIG. 7, consider a case in which authenticity determination of a battery identified by a battery ID "A000002" has been performed. In this case, the determination unit 15B refers to the data entry in the second row corresponding to the battery ID "A000002" among the data entries included in the determination count information 13D. Then, the determination unit 15B updates the number of times authenticity determination has been performed, which is included in the data entry in the second row corresponding to the battery ID "A000002," by incrementing it by one from "11" to "12."

[0062] 5, the setting unit 15C is a processing unit that sets a threshold value to be compared with the number of times authenticity determination has been performed. In one embodiment, the setting unit 15C sets the threshold value Th2 based on the replacement interval of the battery for which authenticity determination has been performed by the determination unit 15B, among the replacement intervals of the batteries included in the replacement information 13B.

[0063] FIG. 8 is a schematic diagram illustrating an example of threshold setting. The horizontal axis of graph G1 in FIG. 8 indicates the battery replacement interval (days), and the vertical axis indicates the threshold (number of times). As shown in FIG. 8, graph G1 defines a function f1 in which the threshold increases as the battery replacement interval shortens, in other words, the threshold decreases as the battery replacement interval lengthens. According to this function f1, the setting unit 15C can set a threshold Th2 to be compared with the number of times authenticity determination is performed. For example, consider a case in which authenticity determination is performed on a battery identified by battery ID "A000002." In this case, the setting unit 15C refers to the data entry in the second row corresponding to the battery ID "A000002" among the data entries included in the replacement information 13B. The setting unit 15C then assigns the replacement interval "2.15" included in the data entry for battery ID "A000002" as an explanatory variable of function f1, thereby calculating a threshold value of "12" as the objective variable of function f1. Then, the setting unit 15C sets the threshold value "12" calculated as the objective variable of the function f1 as the threshold value Th2.

[0064] By setting the threshold value Th2 to be compared with the number of times authenticity determination is performed according to this function f1, it is possible to decrease the threshold value when the battery replacement interval is long and increase the threshold value when the battery replacement interval is short. This allows the threshold value to be dynamically changed according to the battery replacement interval, making it possible to tune the threshold value to balance the risk of detecting outliers and the benefit of reflecting aging degradation in the reference.

[0065] Although Fig. 8 shows a linear function f1 as an example of a function that defines the correspondence relationship between the battery replacement interval and the threshold value, the function does not necessarily have to be linear and may be non-linear. Also, Fig. 8 shows an example in which the correspondence relationship between the battery replacement interval and the threshold value is defined by a function, but the correspondence relationship may be defined by a method other than a function, such as a lookup table.

[0066] Returning to the description of FIG. 5, the update unit 15D is a processing unit that updates the reference magnetic field distribution using the magnetic field distribution of the battery when the condition for updating the reference magnetic field distribution is satisfied. In one embodiment, the update unit 15D determines whether the number of times authenticity determination has been performed on the battery, which has been authenticated by the determination unit 15B, in the determination count information 13D is equal to or greater than the threshold value Th2 set by the setting unit 15C. At this time, if the number of times authenticity determination has been performed on the battery is equal to or greater than the threshold value Th2, the update unit 15D resets the number of times authenticity determination has been performed on the battery and then starts updating the reference. Note that, although an example of resetting the number of times authenticity determination has been performed has been given here, an offset corresponding to the number of times authenticity determination has been performed may instead be added to the threshold value.

[0067] As an example, the update unit 15D updates the reference magnetic field distribution using the magnetic field distribution of a battery determined to be genuine by the determination unit 15B. For example, the update unit 15D overwrites the reference magnetic field distribution corresponding to the battery ID of the battery installed in the empty slot of the station 30 in the reference information 13C with the magnetic field distribution of the battery determined to be genuine by the determination unit 15B. This updates the reference magnetic field distribution to the latest one.

[0068] As another example, the update unit 15D can also update the reference magnetic field distribution using multiple magnetic field distributions of a battery installed in an empty slot of the station 30, which have been obtained from the battery multiple times in the past.

[0069] FIG. 9 is a schematic diagram showing an example of updating a reference. FIG. 9 shows an example of updating the magnetic field distribution of the reference for battery ID "A00002." As shown in FIG. 9, the update unit 15D can use n magnetic field distributions acquired at each point in time from the current authentication determination to the nth authentication determination, for updating the reference. According to the example shown in FIG. 9, the n magnetic field distributions for battery ID "A00002" can be combined into a single magnetic field distribution by performing statistical processing such as arithmetic averaging, weighted averaging, or moving averaging. The magnetic field distribution obtained by such combination may be referred to as a "composite magnetic field distribution." Then, the update unit 15D overwrites the reference magnetic field distribution corresponding to battery ID "A00002" in the reference information 13C onto the composite magnetic field distribution.

[0070] Although Figure 9 shows an example in which multiple magnetic field distributions are combined into one magnetic field distribution, they do not necessarily have to be combined into one magnetic field distribution, and the magnetic field distribution saved as a reference does not necessarily have to be one.

[0071] As one example, the update unit 15D can estimate a distribution (e.g., a probability density function) that each magnetic field distribution follows from multiple magnetic field distributions acquired multiple times in the past and store the estimated distribution as a reference. As another example, the update unit 15D can store all previously acquired magnetic field distributions, and use a set of measurement values ​​obtained by extracting the most recent measurement values ​​for each magnetic flux density measurement point, excluding outliers (e.g., values ​​deviating from the average ±3σ) from the magnetic flux density measurement values ​​at the measurement point, as a reference. As another example, the update unit 15D can store pseudo-data of a magnetic field distribution generated from actual measurement data of the magnetic field distribution using a machine learning model such as a VAE (Variational AutoEncoder) or a GAN (Generative Adversarial Network) generator as a reference. As another example, the update unit 15D calculates the difference between the magnetic field distribution (current magnetic field distribution) of a battery determined to be genuine by the determination unit 15B and the previous magnetic field distribution stored as a reference for the battery. If the difference from the previous magnetic field distribution is equal to or greater than a threshold, i.e., if the amount of change is large, the update unit 15D can suspend or prohibit saving the current magnetic field distribution as a reference. The application examples described above are not limited to reference updating, but can also be applied to differences between the measurement unit 33 and the battery when comparing magnetic field distributions. For example, in preparation for a positional deviation occurring during measurement by the measurement unit 33, a reference corresponding to each measurement environment can be saved, thereby addressing differences between the batteries being measured. For example, the measurement environment may include the arrangement pattern of each magnetic sensor, as well as the positional relationship between the measurement unit 33 and the battery (e.g., the distance between a specific magnetic sensor and the battery).

[0072] <Processing flow> Fig. 10 is a flowchart (1) showing the procedure of the overall processing. This processing can be started, as an example, when a user ID is received from station 30. As shown in Fig. 10, providing unit 15A compares the user ID registered in user information 13A with the user ID received from station 30, and performs user authentication to determine whether the user is a legitimate user whose user ID is registered in user information 13A (step S101).

[0073] At this time, if the user authentication is successful, that is, if the user is a legitimate user whose user ID is registered in the user information 13A (Yes in step S101), the providing unit 15A outputs an instruction to the station 30 to load a battery into an empty slot (step S102).

[0074] Then, when the user's battery is attached to an empty slot in 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).

[0075] Next, the providing unit 15A updates the replacement interval of the battery in question among the replacement intervals of the batteries included in the replacement information 13B stored in the storage unit 13 (step S104).

[0076] Next, the judgment unit 15B judges whether the battery installed in the empty slot is genuine or not 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).

[0077] At this time, if the battery is determined to be genuine (Yes in step S106), the provider 15A notifies the station 30 of permission to replace the battery (step S107). In the station 30 that has been notified of permission to replace the battery, removal of the battery from the charged slot is permitted.

[0078] On the other hand, if user authentication fails or the battery is determined to be an unauthorized product (No in step S101 or No in step S106), the providing unit 15A executes the following process. That is, the providing unit 15A notifies the station 30 that battery replacement is not permitted (step S108) and ends the process. In the station 30 that has been notified of the non-permission of battery replacement in this way, removal of a battery from a charged slot is prohibited.

[0079] After executing step S107, the determination unit 15B updates the number of times that the authenticity determination of the battery has been performed among the number of times that the authenticity determination has been performed, which is included in the determination count information 13D stored in the storage unit 13 (step S109).

[0080] Then, the setting unit 15C sets the threshold value Th2 based on the replacement interval of the battery for which the authenticity determination was performed in step S105, among the replacement intervals of the batteries included in the replacement information 13B (step S110).

[0081] Then, the update unit 15D determines whether the number of times of authenticity determination of the battery for which authenticity determination was performed in step S105 in the determination count information 13D is equal to or greater than the threshold value Th2 set in step S110 (step S111).

[0082] If the number of times the authenticity determination of the battery has been performed is equal to or greater than the threshold value Th2 (Yes in step S111), the update unit 15D resets the number of times the authenticity determination of the battery has been performed (step S112). After that, the update unit 15D updates the reference magnetic field distribution using the magnetic field distribution of the battery acquired in step S103 (step S113), and ends the process.

[0083] If the number of times the authenticity determination of the battery has been performed is not equal to or greater than the threshold value Th2 (No in step S111), the process skips steps S112 and S113 and ends.

[0084] <One aspect of the effect> As described above, the server device 10 according to this embodiment acquires the magnetic field distribution of the battery 3 installed in an empty slot of the station 30. Then, if the conditions for updating the reference magnetic field distribution that is referred to in determining the authenticity of the battery are satisfied when the magnetic field distribution of the battery is acquired, the server device 10 updates the reference magnetic field distribution using the magnetic field distribution of the battery.

[0085] In this way, the server device 10 according to the present embodiment updates the reference magnetic field distribution under certain conditions. As just one example, a condition can be set that the number of times authenticity determination of the battery 3 is performed is equal to or greater than a threshold value.

[0086] As one aspect, Condition 1 can be set as a condition for limiting / prohibiting reference updates, where the time elapsed since the last reference update is less than Threshold 1 and the number of times authenticity determination of battery 3 has been performed is less than Threshold 2. When Condition 1 is satisfied, the time elapsed since the last reference update is short, so the effects of both deterioration due to the passage of time and deterioration due to repeated charging and discharging are minor and difficult to observe. In this case, reference updates are limited or prohibited, preventing excessively frequent reference updates. As a result, the risk of an outlier being set as the reference due to disturbances occurring during measurement of the battery's magnetic field distribution can be reduced.

[0087] As another aspect, condition 2 can be set as a condition for permitting reference update: that is, the time elapsed since the last reference update is less than threshold 1 and the number of times authenticity determination of battery 3 has been performed is equal to or greater than threshold 2. When condition 2 is satisfied, the time elapsed since the last reference update is short, so the impact of deterioration due to the passage of time is minor, while the number of times authenticity determination has been performed is high, so deterioration due to repeated charging and discharging may be advanced. In this case, the reference is updated, so that insufficient frequency of reference updates is prevented. As a result, the impact of deterioration due to repeated charging and discharging can be reflected in the reference.

[0088] As a further aspect, condition 3, that the time elapsed since the last reference update is equal to or greater than threshold 1, can be set as a condition for allowing reference updates. If condition 3 is met, a long time has passed since the last reference update, and deterioration due to the passage of time may have had an impact. In this case, the reference is updated, which prevents reference updates from being performed insufficiently. As a result, the reference can be made to reflect on the effects of deterioration due to the passage of time.

[0089] In this way, the server device 10 according to the present embodiment can balance the risk of detecting outliers with the benefit of reflecting deterioration over time and / or deterioration due to repeated charging and discharging in the reference. Therefore, the server device 10 according to the present embodiment can optimize the frequency of reference updates.

[0090] <Embodiment 2> In the first embodiment, an example was given in which the threshold value to be compared with the number of times the authenticity determination of the battery is performed is set based on the battery replacement interval, but the threshold value does not necessarily have to be set based on the battery replacement interval. Therefore, in this embodiment, an example will be described in which the threshold value is set based on the frequency with which the battery is determined to be genuine at station 30.

[0091] <Configuration of server device 20> FIG. 11 is a block diagram (2) showing an example of the functional configuration of server device 20. In FIG. 11, functional units having the same functions as those shown in FIG. 5 are assigned the same reference numerals, and their description will be omitted. As shown in FIG. 11, server device 20 differs from server device 10 shown in FIG. 5 in that memory unit 23 stores carry-in frequency information 23A instead of exchange information 13B. Furthermore, server device 20 differs from determination unit 15B and setting unit 15C shown in FIG. 5 in that some of the processes executed by determination unit 25A and setting unit 25B of control unit 25 are different.

[0092] 5 in that the determination unit 25A adds a process of updating the frequency with which genuine products are brought into the station 30 where the authenticity determination of the battery was performed after updating the number of times the authenticity determination of the battery was performed. The "frequency" here may include the number of times, probability, probability distribution, etc.

[0093] FIG. 12 is a diagram showing an example of updating the carry-in frequency information 23A. As shown in FIG. 12, the carry-in frequency information 23A is data in which items such as the number of times (probability) that a genuine product has been brought in and the number of times (probability) that a non-genuine product has been brought in are associated with each station. Of these, the "number of times (probability) that a genuine product has been brought in" refers to the number of times (probability) that a battery brought in by a user to station 30 has been determined to be a genuine product. Furthermore, the "number of times (probability) that a non-genuine product has been brought in" refers to the number of times (probability) that a battery brought in by a user to station 30 has been determined to be a non-genuine product. Note that the upper part of FIG. 12 shows the carry-in frequency information 23A before the update, and the lower part of FIG. 12 shows the carry-in frequency information 23A after the update.

[0094] Here, Figure 12 shows, as an example only, an example of an update to the carry-in frequency information 23A when a battery with battery ID "A000002" brought to station "Koto-ku B" is found to be a "genuine product" as a result of authenticity determination.

[0095] In this case, an update is performed on the data entry for station "Koto Ward B" among the data entries included in carry-in frequency information 23A, i.e., the data entry in the second row. That is, since the result of the battery authenticity assessment is "genuine," the number of genuine product carry-ins for station "Koto Ward B" ("34") is incremented by one. On the other hand, the number of non-genuine product carry-ins for station "Koto Ward B" remains unchanged, so it is not updated.

[0096] In this way, the most recent number of times non-genuine products were brought in remains at "15" and is not updated, and the most recent number of times genuine products were brought in is incremented from "34" to "35." Although not shown in the figure, the total number of times products were brought in is also incremented from "49 (= 34 + 15)" to "50."

[0097] In addition, the probability of station "Koto Ward B" bringing in genuine products is updated from "69%" to "70%" by dividing the most recent number of genuine product brings in (35) by the total number of recent brings in (50). On the other hand, the probability of station "Koto Ward B" bringing in non-genuine products is updated from "31%" to "30%" by dividing the most recent number of non-genuine product brings in (15) by the total number of recent brings in (50).

[0098] 11, the setting unit 25B has a different criterion for setting the threshold value to be compared with the number of times authenticity determination of a battery is performed, compared with the setting unit 15C shown in Fig. 5. That is, the setting unit 25B sets the threshold value Th3 based on the frequency of genuine products being brought into the station 30.

[0099] FIG. 13 is a schematic diagram illustrating an example of threshold setting. The horizontal axis of graph G2 in FIG. 13 indicates the probability (%) of a genuine product, and the vertical axis indicates the threshold (number of times). As shown in FIG. 13, graph G2 defines a function f2 in which the threshold increases as the probability of a genuine product increases, in other words, the threshold decreases as the probability of a genuine product decreases. According to this function f2, the setting unit 25B can set a threshold Th3 to be compared with the number of times authenticity determination is performed. For example, consider a case where a battery authenticity determination is performed at station "Koto Ward B." In this case, the setting unit 25B references the data entry in the second row corresponding to station "Koto Ward B" among the data entries included in the carry-in frequency information 23A. Then, the setting unit 25B calculates a threshold value of "12" as the objective variable of function f2 by substituting the probability of a genuine product of "70%" included in the data entry for station "Koto Ward B" as the explanatory variable of function f2. Then, the setting unit 25B sets the threshold value "12" calculated as the objective variable of the function f2 as the threshold value Th3.

[0100] By setting the threshold value Th3 to be compared with the number of times authenticity determination is performed according to this function f2, it is possible to decrease the threshold value when the probability of a genuine product being brought in is low, and increase the threshold value when the probability of a genuine product being brought in is high. This makes it possible to dynamically change the threshold value according to the probability of a genuine product being brought in, making it possible to tune the threshold value to balance the risk of detecting outliers and the benefit of reflecting deterioration over time in the reference.

[0101] 13 shows an example of a function that defines the correspondence between the probability of a genuine product being brought in and the threshold value, which is a linear function f2, but the function does not necessarily have to be linear and may be nonlinear. Also, while FIG. 13 shows an example of a function that defines the correspondence between the probability of a genuine product being brought in and the threshold value, the correspondence may be defined by a method other than a function, such as a lookup table.

[0102] <Processing flow> Fig. 14 is a flowchart (2) showing the procedure of the overall processing. The processing shown in Fig. 14 is also merely an example and can be started when a user ID is received from station 30. Note that in Fig. 14, different step numbers are assigned to processes that are different from those in the flowchart shown in Fig. 10, while the same step numbers are assigned to processes that are the same as those in the flowchart shown in Fig. 10.

[0103] As shown in FIG. 14, the providing unit 15A compares the user ID registered in the user information 13A with the user ID received from the station 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).

[0104] At this time, if the user authentication is successful, that is, if the user is a legitimate user whose user ID is registered in the user information 13A (Yes in step S101), the providing unit 15A outputs an instruction to the station 30 to load a battery into an empty slot (step S102).

[0105] Then, when the user's battery is attached to an empty slot in 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).

[0106] Next, the judgment unit 15B judges whether the battery installed in the empty slot is genuine or not 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).

[0107] At this time, if the battery is determined to be genuine (Yes in step S106), the provider 15A notifies the station 30 of permission to replace the battery (step S107). In the station 30 that has been notified of permission to replace the battery, removal of the battery from the charged slot is permitted.

[0108] On the other hand, if user authentication fails or the battery is determined to be an unauthorized product (No in step S101 or No in step S106), the providing unit 15A executes the following process. That is, the providing unit 15A notifies the station 30 that battery replacement is not permitted (step S108) and ends the process. In the station 30 that has been notified of the non-permission of battery replacement in this way, removal of a battery from a charged slot is prohibited.

[0109] After executing step S107, the determination unit 15B updates the number of times that the authenticity determination of the battery has been performed among the number of times that the authenticity determination has been performed, which is included in the determination count information 13D stored in the storage unit 13 (step S109).

[0110] Next, the determination unit 25A updates the genuine product bring-in frequency corresponding to the station 30 for which the authenticity determination was performed in step S105, among the genuine product bring-in frequencies included in the bring-in frequency information 23A (step S301).

[0111] Then, the setting unit 25B sets the threshold value Th3 based on the frequency of genuine product carry-in of the station 30 for which the authenticity determination was performed in step S105, among the frequencies of genuine product carry-in included in the carry-in frequency information 23A (step S302).

[0112] Then, the update unit 15D determines whether the number of times of authenticity determination of the battery for which authenticity determination was performed in step S105 in the determination count information 13D is equal to or greater than the threshold value Th3 set in step S302 (step S111).

[0113] If the number of times the authenticity determination of the battery has been performed is equal to or greater than the threshold value Th3 (Yes in step S111), the update unit 15D resets the number of times the authenticity determination of the battery has been performed (step S112). After that, the update unit 15D updates the reference magnetic field distribution using the magnetic field distribution of the battery acquired in step S103 (step S113), and ends the process.

[0114] If the number of times the authenticity determination of the battery has been performed is not equal to or greater than the threshold value Th3 (No in step S111), the process skips steps S112 and S113 and ends.

[0115] <One aspect of the effect> As described above, the server device 20 according to this embodiment can optimize the frequency of reference updates, similar to the server device 10 according to the above-described embodiment 1. Furthermore, the server device 20 according to this embodiment can dynamically change the threshold value to be compared with the number of times authenticity determination is performed, according to the frequency with which the station 30 determines that the battery is genuine, similar to the server device 10 according to the above-described embodiment 1.

[0116] <Other embodiments> Although the embodiments of the present invention have been described above, the present invention is applicable to various applications, and may be implemented in various different forms other than the above-described embodiments.

[0117] In the above-described first and second embodiments, the condition for updating the reference is, for example, that the number of times the authenticity determination of the battery is performed is equal to or greater than a threshold value, but the condition is not limited to this.

[0118] For example, the update unit 15D can determine whether to update the reference magnetic field distribution using a score output by a machine learning model to which the magnetic field distribution of the battery is input. The "score" here refers to the likelihood that the battery is genuine, and may include, for example, a probability, a certainty, or a likelihood.

[0119] Examples of machine learning models that output scores related to class classification in this way include logistic regression and support vector machines.

[0120] For example, the update unit 15D can also update the reference if the time series data of the scores output for each of the multiple magnetic field distributions by a machine learning model to which each of the multiple magnetic field distributions acquired multiple times in the past is input is on a downward trend.

[0121] FIG. 15 is a diagram illustrating an application example of the reference update condition. As shown in FIG. 15, from the second authentication test onward, an approximated line is obtained by performing regression analysis on the time-series data of the scores. For example, at the time of the second authentication test, an approximated line L1 shown by a dashed-dotted line is obtained by applying regression analysis to the scores at the first authentication test and the second authentication test. Because the slope of this approximated line L1 is not equal to or less than the threshold value Th4, reference update is not performed at the time of the second authentication test. Furthermore, at the time of the third authentication test, an approximated line L2 shown by a dashed-dotted line is obtained by applying regression analysis to the time-series data of the scores from the first authentication test to the third authentication test. Because the slope of this approximated line L2 is also not equal to or less than the threshold value Th4, reference update is not performed at the time of the third authentication test. Furthermore, at the time of the fourth authentication test, an approximate line L3 shown by a solid line is obtained by applying regression analysis to the time series data of scores from the first authentication test to the fourth authentication test. Because the slope of this approximate line L3 is equal to or less than the threshold value Th4, a reference update is performed at the time of the fourth authentication test.

[0122] In this way, the condition for updating the reference can be determined by whether the slope of the approximation line is below a specific threshold, and by whether the score is on a decreasing trend, rather than depending solely on the magnitude of the score. For example, in the case of a support vector machine, a score normalized to a numerical range from -1 to +1 is output, and if the sign of the score is positive, the product is determined to be genuine. In this way, even if the sign of the score is positive, by updating the reference if the score is on a decreasing trend, the reference can be updated before the effects of deterioration over time become significant and an erroneous determination of authenticity occurs.

[0123] Other reference update conditions may be set. For example, the update unit 15D may update the reference magnetic field distribution when the cumulative number of times the battery has been charged is equal to or greater than a threshold. The update unit 15D may also update the reference magnetic field distribution when the cumulative amount of charge of the battery is equal to or greater than a threshold. The update unit 15D may also update the reference magnetic field distribution when the elapsed time since the previous authenticity determination of the battery is equal to or greater than a threshold. The update unit 15D may also update the reference magnetic field distribution every time the magnetic field distribution of the battery is acquired.

[0124] Although an example in which the above scores are derived using a machine learning model has been given here, the present invention is not limited to this, and the above scores may be derived using any model, such as a statistical model. For example, the above scores may be derived using any mathematical model, such as a state space representation, a transfer function type, an FIR (Finite Impulse Response) model, or a step response.

[0125] <Numbers, etc.> The matters described in the above embodiment, such as the number of magnetic sensors in the measuring unit 33 of the station 30 and the specific examples of the reference setting method, are merely examples and can be changed. Also, the processing order of the flowcharts described in the embodiment can be changed within a consistent range.

[0126] <System> The information, including the processing procedures, control procedures, specific names, various data, and parameters shown in the above documents and drawings, can be changed as desired unless otherwise specified. For example, any one or more of the function units of the providing unit 15A, determining unit 15B, setting unit 15C, and updating unit 15D of the server device 10 may be configured as separate devices. Also, any one or more of the function units of the providing unit 15A, determining unit 25A, setting unit 25B, and updating unit 15D of the server device 20 may be configured as separate devices.

[0127] Furthermore, the components of each device shown in the figure are functional concepts and do not necessarily have to be physically configured as shown. In other words, the specific form of distribution and integration of each device is not limited to that shown. In other words, all or part of them can be functionally or physically distributed and integrated in any unit depending on various loads, usage conditions, etc. Note that each configuration may also be a physical configuration.

[0128] Furthermore, each processing function performed by each device can be realized, in whole or in part, by a CPU (Central Processing Unit) and a program analyzed and executed by the CPU, or can be realized as hardware using wired logic.

[0129] <Hardware> Next, an example of the hardware configuration of the computer described in the above-mentioned embodiment 1 and embodiment 2 will be described. Fig. 16 is a diagram showing an example of the hardware configuration. As shown in Fig. 16, an information processing device 100 has a communication device 100a, an HDD (Hard Disk Drive) 100b, a memory 100c, and a processor 100d. Note that the components shown in Fig. 16 are connected to each other via a bus or the like.

[0130] The communication device 100a is a network interface card or the like, and communicates with other servers. The HDD 100b stores programs and DBs that operate the functions shown in FIG.

[0131] The processor 100d reads a program that executes processing similar to that of the processing unit shown in FIG. 5 or FIG. 11 from the HDD 100b, etc., and expands it into the memory 100c, thereby operating a process that executes the function described in FIG. 5 or FIG. 11.

[0132] Such a process executes the same functions as the processing units of the server device 10 and the server device 20. For example, the processor 100d reads out a program having the same functions as the providing unit 15A, the determining unit 15B, the setting unit 15C, the updating unit 15D, etc. from the HDD 100b, etc. Then, the processor 100d executes a process that executes the same processes as the providing unit 15A, the determining unit 15B, the setting unit 15C, the updating unit 15D, etc. Also, the processor 100d reads out a program having the same functions as the providing unit 15A, the determining unit 25A, the setting unit 25B, the updating unit 15D, etc. from the HDD 100b, etc. Then, the processor 100d executes a process that executes the same processes as the providing unit 15A, the determining unit 25A, the setting unit 25B, the updating unit 15D, etc.

[0133] In this way, the information processing device 100 operates as an information processing device that executes an evaluation method by reading and executing a program. The information processing device 100 can also realize functions similar to those of the above-described embodiment by reading the program from a recording medium using a medium reading device and executing the read program. Note that the program in these other embodiments is not limited to being executed by the information processing device 100. For example, the present invention can also be applied in the same way to cases where another computer or server executes the program, or where these execute the program in cooperation with each other.

[0134] The above program can be distributed via a network such as the Internet. The above program can also be recorded on any recording medium and executed by a computer by reading it from the recording medium. For example, the recording medium can be a hard disk, a flexible disk (FD), a CD-ROM, a magneto-optical disk (MO), a digital versatile disk (DVD), or the like.

[0135] <Other> Some examples of combinations of the disclosed technical features are set out below.

[0136] (1) an acquisition unit for acquiring a magnetic field distribution of a battery; an updating unit that updates a reference magnetic field distribution, which is referred to in determining the authenticity of the battery, using the magnetic field distribution of the battery when a condition for updating the reference magnetic field distribution is satisfied when the magnetic field distribution of the battery is acquired; An information processing device comprising:

[0137] (2) further comprising a determination unit that determines whether the battery is a genuine product based on a comparison between the magnetic field distribution of the battery and the magnetic field distribution of the reference; The information processing device according to (1), wherein the update unit updates the reference magnetic field distribution using the magnetic field distribution of the battery determined to be genuine.

[0138] (3) The information processing device according to (1) or (2), characterized in that the update unit updates the magnetic field distribution of the reference when the number of times the authenticity determination for the battery has been performed is equal to or greater than a threshold value.

[0139] (4) The information processing device according to (3), further comprising a setting unit that sets the threshold value based on the interval at which the magnetic field distribution of the battery is acquired.

[0140] (5) The information processing device according to (4), wherein the setting unit sets a larger threshold value as the interval becomes shorter.

[0141] (6) The information processing device described in (3) is characterized in that it further has a setting unit that sets the threshold value based on the frequency with which batteries charged at a station corresponding to the charging source of the battery are determined to be genuine.

[0142] (7) The information processing device according to (6), wherein the setting unit sets a larger threshold value as the frequency increases.

[0143] (8) The information processing device according to any one of (3) to (7), wherein the update unit resets the number of times the authenticity determination of the battery has been performed when the magnetic field distribution of the reference is updated.

[0144] (9) The information processing device according to (1) or (2), wherein the update unit updates the reference magnetic field distribution when the cumulative number of times the battery has been charged is equal to or greater than a threshold value.

[0145] (10) The information processing device according to (1) or (2), wherein the update unit updates the reference magnetic field distribution when the cumulative charge amount of the battery is equal to or greater than a threshold value.

[0146] (11) The information processing device described in (1) or (2) is characterized in that the update unit updates the magnetic field distribution of the reference when the elapsed time since the authenticity determination of the battery was last performed is greater than or equal to a threshold value.

[0147] (12) The information processing device according to (1) or (2), wherein the update unit updates the reference magnetic field distribution every time the magnetic field distribution of the battery is acquired.

[0148] (13) The information processing device described in (1) or (2) is characterized in that the update unit inputs the magnetic field distribution of the battery, each of multiple magnetic field distributions obtained from the battery multiple times in the past, into a model that takes the magnetic field distribution of the battery as input and outputs a score indicating the likelihood that the battery is genuine, and updates the reference magnetic field distribution if the slope of the approximate straight line of the scores output by the model for each of the multiple magnetic field distributions is below a threshold.

[0149] (14) The information processing device described in any one of (1) to (13), characterized in that the update unit updates the reference magnetic field distribution using multiple magnetic field distributions of the battery that have been obtained from the battery multiple times in the past.

[0150] (15) Obtain the magnetic field distribution of the battery; updating the reference magnetic field distribution using the magnetic field distribution of the battery when a condition for updating a reference magnetic field distribution referred to in determining the authenticity of the battery is satisfied when the magnetic field distribution of the battery is acquired; An updating method characterized in that the processing is executed by a computer.

[0151] (16) Obtain the magnetic field distribution of the battery; updating the reference magnetic field distribution using the magnetic field distribution of the battery when a condition for updating a reference magnetic field distribution referred to in determining the authenticity of the battery is satisfied when the magnetic field distribution of the battery is acquired; An update program that causes a computer to execute a process. [Explanation of symbols]

[0152] 1. Battery sharing system 3 Battery 10 Server device 11 Communication control section 13 Storage section 13A User Information 13B Exchange Information 13C Reference Information 13D Judgment Count Information 15 Control Unit 15A supply department 15B Judgment section 15C Setting section 15D update section 30 Stations 31 Information reading unit 33 Measuring part

Claims

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

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

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

4. 4. The information processing apparatus according to claim 3, further comprising 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 apparatus according to claim 4 , wherein the setting unit sets a larger threshold value as the interval becomes shorter.

6. 4. The information processing device according to claim 3, further comprising a setting unit that sets the threshold value based on the frequency with which batteries charged at a station corresponding to a charging source of the battery are determined to be genuine.

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

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

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

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

11. 3. The information processing apparatus according to claim 1, wherein the update unit updates the reference magnetic field distribution when the time elapsed since the previous authenticity determination of the battery is equal to or greater than a threshold value.

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

13. The information processing device described in claim 1 or 2, characterized in that the update unit inputs each of the battery's magnetic field distributions, which are multiple magnetic field distributions obtained from the battery multiple times in the past, into a model that inputs the battery's magnetic field distribution and outputs a score indicating the likelihood that the battery is genuine, and updates the reference magnetic field distribution if the slope of the approximate straight line of the scores output by the model for each of the multiple magnetic field distributions is below a threshold.

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

15. Obtain the magnetic field distribution of the battery, updating the reference magnetic field distribution using the magnetic field distribution of the battery when a condition for updating a reference magnetic field distribution referred to in determining the authenticity of the battery is satisfied when the magnetic field distribution of the battery is acquired; An updating method characterized in that the processing is executed by a computer.

16. Obtain the magnetic field distribution of the battery, updating the reference magnetic field distribution using the magnetic field distribution of the battery when a condition for updating a reference magnetic field distribution referred to in determining the authenticity of the battery is satisfied when the magnetic field distribution of the battery is acquired; An update program that causes a computer to execute a process.

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