Information processing device, deterioration diagnosis method, and deterioration diagnosis program

Abstract

The challenge is to optimize the frequency of deterioration assessments. [Solution] The information processing device includes an acquisition unit that acquires battery-specific information of a battery, a first determination unit that performs a genuineness determination to determine whether the battery is genuine or not based on the battery-specific information, and a second determination unit that performs a battery degradation diagnosis if the number of times the genuineness determination of the battery has been performed is equal to or greater than a threshold.

Description

Technical Field

[0001] The present invention relates to an information processing apparatus, a deterioration diagnosis method, and a deterioration diagnosis program.

Background Art

[0002] From the aspect of achieving carbon neutrality, electric vehicles (so-called xEVs) driven by motors powered by electricity are becoming widespread. Along with the spread of such xEVs, efforts are also being made to realize battery sharing services by making the batteries of xEVs replaceable through the provision of charging facilities that replace batteries with low charge levels and batteries with defects.

[0003] The above charging facilities, for example, perform various deterioration diagnoses of the batteries of xEVs, such as diagnoses of capacity, performance, and safety, from the aspect of suppressing the provision of defective batteries in exchange for batteries with low charge levels.

Prior Art Documents

[0006] The present invention aims to optimize the frequency of deterioration diagnosis. [Means for solving the problem]

[0007] An information processing device according to one aspect of the present invention includes: an acquisition unit that acquires battery-specific information of a battery; a first determination unit that performs a genuineness determination to determine whether the battery is genuine or not based on the battery-specific information; and a second determination unit that performs a battery degradation diagnosis if the number of times the genuineness determination of the battery has been performed is equal to or greater than a threshold.

[0008] In a degradation diagnosis method according to one aspect of the present invention, a computer performs the following processes: acquires battery-specific information of a battery, performs a genuineness determination to determine whether the battery is genuine or not based on the battery-specific information, and if the number of times the genuineness determination of the battery has been performed is equal to or greater than a threshold, performs a degradation diagnosis of the battery.

[0009] A degradation diagnosis program according to one aspect of the present invention causes a computer to perform the following processes: acquire battery-specific information of a battery, perform a genuineness determination to determine whether the battery is genuine or not based on the battery-specific information, and if the number of times the genuineness determination of the battery has been performed is equal to or greater than a threshold, perform a degradation diagnosis of the battery. [Effects of the Invention]

[0010] According to one embodiment, it is possible to optimize the frequency of deterioration diagnosis. [Brief explanation of the drawing]

[0011] [Figure 1] Figure 1 is a diagram showing a configuration example of a battery sharing system. [Figure 2] Figure 2 is a schematic diagram showing an example of battery replacement. [Figure 3] Figure 3 is a diagram showing one aspect of a problem-solving approach. [Figure 4] Figure 4 is a diagram showing an example of the execution probability of deterioration diagnosis. [Figure 5] Figure 5 is a block diagram (1) showing a functional configuration example of a server device. [Figure 6] Figure 6 is a diagram showing an example of updating the replacement interval of a battery. [Figure 7] Figure 7 is a diagram showing an example of updating the number of execution times of authenticity determination of a battery. [Figure 8] Figure 8 is a schematic diagram showing an example of setting a threshold value. [Figure 9] Figure 9 is a flowchart (1) showing the procedure of overall processing. [Figure 10] Figure 10 is a flowchart showing the procedure of deterioration diagnosis processing. [Figure 11] Figure 11 is a block diagram (2) showing a functional configuration example of a server device. [Figure 12] Figure 12 is a diagram showing an example of updating the bringing-in frequency information. [Figure 13] Figure 13 is a schematic diagram showing an example of setting a threshold value. [Figure 14] Figure 14 is a flowchart (2) showing the procedure of overall processing. [Figure 15] Figure 15 is a flowchart of the overall processing according to an application example. [Figure 16] Figure 16 is a diagram showing a hardware configuration example.

Mode for Carrying Out the Invention

[0012] The following describes embodiments (hereinafter referred to as "embodiments") for implementing the information processing device, degradation diagnosis method, and degradation diagnosis program according to the present application, with reference to the attached drawings. Each embodiment is merely an example or shows an aspect, and such examples do not limit the range of numerical values, functions, or usage scenarios. Furthermore, each embodiment can be adaptively combined within a range that does not contradict the processing content.

[0013] <Embodiment 1> <Overall Structure> Figure 1 shows an example configuration of a battery sharing system. The battery sharing system 1 shown in Figure 1 provides a battery sharing service that enables battery sharing by making the batteries of xEVs and other vehicles interchangeable. Although xEVs are given as an example of battery usage scenarios, batteries are not limited to vehicles and may be installed in construction machinery, agricultural machinery, and general load equipment such as home appliances.

[0014] The term "battery" as used here may refer to secondary batteries such as lithium-ion batteries or battery packs made of such batteries. For example, "battery" may refer to a single "cell," a battery pack made of multiple cells, or a battery pack made of multiple modules.

[0015] As shown in Figure 1, the battery sharing system 1 may include a server device 10 and stations 30A to 30N. Hereafter, when it is not necessary to distinguish between individual stations 30A to 30N, stations 30A to 30N may be referred to as "station 30".

[0016] These server devices 10 and stations 30 may be connected to each other via any network NW. The network NW may be wired or wireless, and may be implemented using any technology such as internet technology, industrial communication standards, or low-power wireless communication standards for IoT (Internet of Things).

[0017] Server device 10 is an example of an information processing device that provides the battery sharing service described above. For example, server device 10 can be implemented as a PaaS (Platform as a Service) or SaaS (Software as a Service) application to provide the battery sharing service as a cloud service. Alternatively, server device 10 may be implemented as a server that provides the battery sharing function for realizing the battery sharing service on-premises.

[0018] Station 30 corresponds to an example of a charging facility that performs the exchange of low-charge batteries and fully charged batteries. Station 30 has multiple slots from which batteries can be inserted and removed. In such a station 30, it is possible to charge batteries installed in empty slots and to remove fully charged batteries from the charged slots.

[0019] <Battery Replacement> Figure 2 is a schematic diagram showing an example of battery replacement. As shown in Figure 2, at station 30, the identification information of the user using the battery sharing service, such as the user ID (IDentification), is read (step S1).

[0020] For example, when a user brings their IC (Integrated Circuit) card 2 close to the information reading unit 31 of the station 30, the user ID recorded on the IC card 2 is read by the information reading unit 31.

[0021] In this way, the user ID read by the information reading unit 31 is used to perform user authentication to determine whether the user is a legitimate user who has been pre-registered, as well as to process payment for using the battery sharing service.

[0022] Subsequently, the battery 3, which was removed from an EV or other vehicle, is returned by installing it in one of the empty slots on the station 30 that does not currently have a battery installed (step S2).

[0023] When such batteries 3 are returned, the display unit associated with each slot, such as a lamp, can display a different display format for empty slots and other slots.

[0024] After battery 3 is returned, it is removed from one of the charged slots on station 30 (step S3). Note that "charged" may refer to a fully charged state, but it does not necessarily have to be fully charged. For example, a slot in which a battery with a State of Charge (SOC) of 95% or higher is installed may be identified as a charged slot.

[0025] The battery 3, removed from the charged slot, is then installed in the user's vehicle. These operations from step S1 to step S3 enable the replacement of the battery 3.

[0026] Figure 2 shows an example of a pre-registered user performing a battery replacement, but naturally, this does not prevent new users from performing battery replacements.

[0027] <Battery-specific information> While xEVs are becoming more widespread, there is also a growing trend of counterfeit batteries circulating in the market, in addition to genuine batteries manufactured by manufacturers. For example, some counterfeit batteries not only mimic the appearance of genuine modules or battery packs, but also the QR code that links to management information such as the Battery Passport, which manages the battery's lifecycle from material procurement to recycling.

[0028] From this perspective, the server device 10 according to this embodiment performs a genuineness determination to determine whether the battery is genuine or not when the battery is replaced. The above genuineness determination can be performed by comparing the battery-specific information of a genuine battery as a reference with the battery-specific information obtained from the battery to be identified.

[0029] Here, "battery-specific information" refers to information that can uniquely identify each individual battery. For example, a battery ID that can uniquely identify a battery can be used as an example of battery-specific information. The battery ID may be attached to the battery as a barcode, or it may be recorded on an IC chip and the IC chip attached to the battery. In this case, when replacing a battery, the battery ID can be read, and the authenticity of the battery can be determined by comparing the read battery ID with a list of genuine battery IDs.

[0030] Furthermore, as an example of battery-specific information, the battery's characteristics can be used (see Patent Document 4). In this case, the battery characteristics are managed in association with the battery's ID, and when a battery is replaced, the battery characteristics and ID of that battery are obtained and compared with the battery characteristics of a reference linked to the ID to determine authenticity.

[0031] Furthermore, as an example of battery-specific information, the inductance of the battery can be used (see Patent Document 5). In this case, a specific current is applied to the target battery, the voltage response of the target battery to the applied current is measured, and the inductance value of the target battery is calculated based on the applied current value and the measured voltage value. Then, the authenticity of the target battery can be determined using the specified inductance value according to the type of target battery and the inductance value of the target battery calculated earlier.

[0032] Furthermore, as an example of battery-specific information, the magnetic field characteristics of the battery can be used (see Patent Document 6). In this case, a predetermined value for the magnetic field characteristics according to the type of battery is stored in advance. Then, when replacing a battery, a magnetic field is generated by applying a specific current to the battery, and the magnetic field characteristics of the generated magnetic field are measured. The server device 10 can determine the authenticity of the battery by comparing the measured magnetic field characteristics with the predetermined value stored in advance.

[0033] In this way, the server device 10 can perform a genuineness determination to determine whether a battery is genuine or not using arbitrary battery-specific information.

[0034] Furthermore, the server device 10 of this embodiment may perform authenticity determination using any one of the battery-specific information described above, or it may perform authenticity determination using a combination of two or more battery-specific information. Performing authenticity determination using two or more battery-specific information improves the accuracy of the authenticity determination.

[0035] <Deterioration Diagnosis> Furthermore, in order to prevent the provision of defective batteries at Station 30 in exchange for batteries with reduced charge levels, the server device 10 in this embodiment performs various degradation diagnoses of the xEV's battery, such as diagnoses of capacity, performance, and safety.

[0036] <One aspect of the problem> As explained in the background technology section above, the degradation diagnostic technology described above tends to take longer to perform as the level of detail and precision required for diagnosing the battery condition increases. Therefore, increasing the frequency of degradation diagnostics can lead to a decrease in the battery turnover rate at charging facilities. However, if the frequency of degradation diagnostics is decreased in order to increase the battery turnover rate, the occurrence rate of defects in batteries provided by charging facilities in exchange for batteries with reduced charge levels will increase.

[0037] <One aspect of a problem-solving approach> Therefore, the server device 10 according to this embodiment provides a degradation diagnosis function that performs a degradation diagnosis of the battery when the number of times the authenticity judgment of the battery has been performed exceeds a threshold.

[0038] Figure 3 shows one aspect of the problem-solving approach. As shown in Figure 3, the server device 10 acquires battery-specific information of the battery 3 installed in an empty slot of the station 30 (1). Then, the server device 10 performs a genuineness determination to determine whether the battery 3 is genuine or not based on the battery-specific information of the battery 3 (2). Subsequently, if the number of times the genuineness determination of the battery 3 has been performed by the server device 10 exceeds a threshold, it performs a degradation diagnosis of the battery 3 (3).

[0039] Here, the probability of performing a degradation diagnosis can be controlled based on the cumulative number of charging cycles and the charging frequency, as an example. Figure 4 shows an example of the probability of performing a degradation diagnosis. For example, Figure 4 shows an example where the probability of performing a degradation diagnosis is switched between four levels based on the cumulative number of charging cycles and the charging frequency. In the graph shown in Figure 4, the horizontal axis represents the cumulative number of charging cycles, and the vertical axis represents the charging frequency, for example, the number of charges per unit time.

[0040] As shown in Figure 4, the probability of performing a degradation diagnosis can be switched between four levels: "10%", "20%", "40%", and "60%". For example, in Figure 4, a lighter hatching indicates a lower probability of performing a degradation diagnosis, while a darker hatching indicates a higher probability.

[0041] For example, if the cumulative number of charge cycles is less than threshold p1 and the charging frequency is less than threshold q1, that is, if the cumulative number of charge cycles and the charging frequency fall within the lightest hatching area shown in Figure 4, a degradation diagnosis is performed with a "10%" probability.

[0042] If the cumulative number of charge cycles is between threshold p1 and threshold p2, and the charging frequency is between threshold q1 and threshold q2, that is, if the cumulative number of charge cycles and the charging frequency fall within the second lightest hatching region shown in Figure 4, then a degradation diagnosis is performed with a "20%" probability.

[0043] If the cumulative number of charge cycles is between threshold p2 and threshold p3, and the charging frequency is between threshold q2 and threshold q3, that is, if the cumulative number of charge cycles and the charging frequency fall within the second darkest hatched area shown in Figure 4, then a degradation diagnosis is performed with a "40%" probability.

[0044] If the cumulative number of charge cycles is between threshold p3 and threshold p4, and the charging frequency is between threshold q3 and threshold q4, that is, if the cumulative number of charge cycles and charging frequency fall within the darkest hatched area shown in Figure 4, then a degradation diagnosis is performed with a "60%" probability.

[0045] By switching the probability of performing the degradation diagnosis as shown in Figure 4, the following becomes possible. One aspect is that if the cumulative number of charging cycles is large, there is a higher probability that battery 3 has already been used many times by the user since it was shipped. Also, if the charging frequency is high, there is a higher probability that battery 3 is degrading already and is being consumed quickly. If at least one of these two cases is met, the probability of performing the degradation diagnosis can be increased.

[0046] Another aspect is that if both the cumulative number of charge cycles and the charging frequency are low, there is a higher probability that battery 3 has not degraded significantly since being shipped. In this case, the probability of performing a degradation diagnosis can be reduced. This helps to mitigate the decrease in battery 3's turnover rate.

[0047] Note that the multiple thresholds shown in Figure 4 do not necessarily have to be set at equal intervals. For example, since the rate of degradation progresses as the cumulative number of charging cycles and charging frequency increase, the interval between thresholds may be set to be smaller as the cumulative number of charging cycles and charging frequency increase. Also, although Figure 4 shows an example of switching the execution probability of degradation diagnosis in four stages, it is not limited to four stages, and the execution probability of degradation diagnosis can be switched in any number of stages.

[0048] Thus, the degradation diagnosis function according to this embodiment performs degradation diagnosis at a frequency that eliminates the trade-off between a decrease in battery turnover rate and the provision of defective batteries. Therefore, the degradation diagnosis function according to this embodiment makes it possible to optimize the frequency of degradation diagnosis. Furthermore, since unnecessary degradation diagnosis is not performed, computation costs can also be reduced.

[0049] In the following example, the degradation diagnosis function described above is packaged as a feature of the battery sharing service, but the degradation diagnosis function may also be provided as a separate service from the battery sharing service.

[0050] <Configuration of Server Device 10> Next, an example of the functional configuration of the server device 10 according to this embodiment will be described. Figure 5 is a block diagram (1) showing an example of the functional configuration of the server device 10. Figure 5 schematically shows the blocks related to the battery sharing service that the server device 10 has.

[0051] As shown in Figure 5, the server device 10 includes a communication control unit 11, a storage unit 13, and a control unit 15. Note that Figure 5 only shows a selection of the functions related to the battery sharing service described above, and the server device 10 may also be equipped with functions other than those shown.

[0052] 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 implemented using a network interface card. In one aspect, the communication control unit 11 can receive user IDs and battery-specific information from the station 30, send notifications such as permission or denial of battery replacement, and output the results of battery degradation diagnosis to the station 30.

[0053] The storage unit 13 is a functional unit that stores various types of data. As an example, the storage unit 13 can be implemented by internal, external, or auxiliary storage of the server device 10. For example, the storage unit 13 stores user information 13A, exchange information 13B, reference information 13C, and determination count information 13D. The user information 13A, exchange information 13B, reference information 13C, and determination count information 13D will be explained in conjunction with the scenes in which referencing, generation, or registration is performed.

[0054] 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. As shown in Figure 5, the control unit 15 has a supply unit 15A, a first determination unit 15B, a setting unit 15C, and a second determination unit 15D. The control unit 15 may also be implemented by hardwired logic or the like.

[0055] The provisioning unit 15A is a processing unit that provides the above-mentioned battery sharing service. For example, the provisioning unit 15A may correspond to an example of an acquisition unit. In one aspect, when the provisioning unit 15A receives a user ID from the station 30, it 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 to which various information, including payment information such as credit card or electronic money, is associated with each user ID. For example, the above-mentioned 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 and determining whether or not the user is a legitimate user whose user ID is registered in the user information 13A.

[0056] If user authentication is successful, the supply unit 15A outputs an instruction to the station 30 to install a battery into an empty slot. When the battery brought by the user is installed in an empty slot of the station 30, the supply unit 15A obtains the battery-specific information of the battery measured by the measurement unit 33 of the station 30. Hereinafter, the battery brought by the user to the station 30 may be referred to as the "brought-in battery". If information other than the battery ID is used as the battery-specific information, the supply unit 15A may obtain the battery ID of the brought-in battery in addition to the battery-specific information. For example, the battery ID recorded on the IC chip installed in the battery may be obtained. Alternatively, the battery ID of the battery last removed by the user from a charged slot may be considered as the battery ID of the battery installed in an empty slot of the station 30 and obtained. In this case, the user information 13A may store as a history time series data of the battery IDs of batteries removed by the user from charged slots and batteries installed by the user in empty slots for each user ID. Such time-series data may include the time when a battery was removed from a charged slot or installed in an empty slot, as well as station identification information (station ID). Under this battery ID management, when a battery is installed in an empty slot, the battery ID of the battery last removed by the user from a charged slot from the history of battery IDs corresponding to the user ID that successfully authenticated the user may be considered and obtained as the battery ID of the battery installed in the empty slot of station 30.

[0057] After obtaining the battery ID and battery-specific information of the battery in this manner, the supply unit 15A updates the battery replacement interval of the battery in question from the battery replacement intervals included in the replacement information 13B stored in the storage unit 13.

[0058] Figure 6 shows an example of updating the battery replacement interval. As shown in Figure 6, the replacement information 13B is data in which items such as the replacement interval and replacement date and time are associated with each battery ID. Of these, "replacement interval" refers to the interval at which the battery is replaced, and may be, for example, the interval (in days) from when a battery is installed in an empty slot until it is installed in the next empty slot. Also, "replacement date and time" refers to the most recent date and time when the battery was replaced. Note that the upper part of Figure 6 shows the replacement information 13B before the update, and the lower part of Figure 6 shows the replacement information 13B after the update.

[0059] Here, Figure 6 shows, as an example, a battery identified by battery ID "A00002" being installed in an empty slot at 19:18:52 on June 13, 2023. In this case, the supply unit 15A refers to the second data entry in the data entries included in the replacement information 13B that corresponds to battery ID "A00002". The supply unit 15A then calculates the difference (approximately 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 "A00002" as the latest replacement interval. Subsequently, the supply unit 15A updates the replacement interval included in the second data entry corresponding to battery ID "A00002" to the latest replacement interval "2.15 days". Furthermore, the supply unit 15A updates the replacement date and time included in the second line of data entry corresponding to battery ID "A00002" to the latest replacement date and time, "June 13, 2023, 19:18:52".

[0060] Note that Figure 6 shows, as an example, an example in which the interval at which battery-specific information is acquired is considered equivalent to the battery replacement interval, but it is not limited to this. For example, the battery replacement interval may be the interval from when the battery is removed from a charged slot until it is installed in an empty slot.

[0061] In addition to user authentication, the service provider 15A can also process payments for battery replacements. For example, if a user subscribes to a pay-per-use service, the service provider 15A can process the charge for the pay-per-use service using the payment information corresponding to the user ID each time the user ID is obtained from the station 30. Furthermore, if a user subscribes to a recurring billing service, such as a periodic billing or pay-per-use service, where charges begin after subscribing and payments continue until the user cancels their subscription, the service provider 15A can perform the following processes. For example, in the case of a periodic billing service, the service provider 15A checks whether payment has been completed up to the billing date corresponding to the time the user ID was obtained from the station 30. In the case of pay-per-use, the service provider 15A checks whether payment has been completed for the cumulative charge amount at the time the user ID was obtained from the station 30. If payment has been completed, the service provider 15A determines that the payment is OK. Furthermore, even if payment of the fee has not been completed, the service unit 15A will attempt to settle the fee, and if the payment is successful, it will determine that the payment is OK.

[0062] As a further aspect, the supply unit 15A can also output permission or denial of battery replacement depending on the result of the authenticity determination by the first determination unit 15B described later. Here is an example of the operation of permission or denial of battery replacement. For example, if a battery installed in an empty slot is determined to be genuine, the supply unit 15A notifies station 30 of permission to replace the battery. At station 30, which has been notified of this permission, removal of the battery from the charged slot is permitted. On the other hand, if a battery installed in an empty slot is determined to be counterfeit, the supply unit 15A notifies station 30 of denial of battery replacement. At station 30, which has been notified of denial of replacement, removal of the battery from the charged slot is prohibited. Here, as an example of operation, an example of immediate prohibition when a counterfeit product is determined to be counterfeit is given, but it is not limited to this. For example, the number of times a user brings in a counterfeit battery can be accumulated and recorded in association with the user ID, and countermeasures such as caution, warning, and prohibition can be implemented in stages when the accumulated value exceeds a threshold.

[0063] The first determination unit 15B is a processing unit that performs a determination of whether or not a battery is genuine. In one embodiment, the first determination unit 15B performs the above-mentioned determination of authenticity by comparing the battery-specific information of the user's battery brought in by the supply unit 15A with the battery-specific information of a genuine battery registered as a reference in the reference information 13C stored in the storage unit 13.

[0064] Here, the reference information 13C may be a set of data in which the battery-specific information of a legitimate battery is associated as a reference for each battery ID that identifies a legitimate battery.

[0065] After the authenticity determination is performed in this manner, the first determination unit 15B updates the number of times the authenticity determination of the battery has been performed from the number of times the authenticity determination of the battery has been performed, which is included in the determination count information 13D stored in the storage unit 13.

[0066] Figure 7 shows an example of updating the number of times a battery's authenticity check has been performed. As shown in Figure 7, the check count information 13D is data in which items such as the number of times an authenticity check has been performed are associated with each battery ID. Here, the upper part of Figure 7 shows the check count information 13D before the update, and the lower part of Figure 7 shows the check count information 13D after the update. For example, let's take the case where an authenticity check is performed on a battery identified by battery ID "A0002". In this case, the first check unit 15B refers to the data entry in the second row of the data entries included in the check count information 13D that corresponds to the battery ID "A00002". Then, the first check unit 15B updates the number of times an authenticity check has been performed included in the data entry in the second row that corresponds to the battery ID "A00002" by incrementing it by one, from "11" to "12".

[0067] Returning to the explanation of Figure 5, the setting unit 15C is a processing unit that sets a threshold value to be compared with the number of times the authenticity determination has been performed. In one embodiment, the setting unit 15C sets the threshold value Th2 based on the battery replacement intervals for which the authenticity determination has been performed by the first determination unit 15B, among the battery replacement intervals included in the replacement information 13B.

[0068] Figure 8 is a schematic diagram showing an example of threshold setting. In the graph G1 shown in Figure 8, the horizontal axis represents the battery replacement interval (days), and the vertical axis represents the threshold (number of times). As shown in Figure 8, graph G1 defines a function f1 in which the threshold increases as the battery replacement interval shortens, or in other words, the threshold decreases as the battery replacement interval lengthens. According to such a function f1, the setting unit 15C can set a threshold Th2 to be compared with the number of times the authenticity check is performed. For example, let's take the case where the authenticity check is performed on a battery identified by battery ID "10002". In this case, the setting unit 15C refers to the second row of data entries in the replacement information 13B that corresponds to battery ID "A00002". Then, the setting unit 15C calculates the threshold "12" as the target variable of function f1 by substituting the replacement interval "2.15" contained in the data entry for battery ID "A00002" as an explanatory variable of function f1. Then, the setting unit 15C sets the threshold value "12", which was calculated as the target variable of function f1, to the threshold value Th2.

[0069] By setting a threshold Th2 that is compared with the number of times authenticity checks are performed according to such a function f1, the threshold can be decreased when the battery replacement interval is long and increased when the battery replacement interval is short. Therefore, since the threshold can be dynamically changed according to the battery replacement interval, it is possible to tune the threshold to eliminate the trade-off between reduced battery turnover and the provision of defective batteries in accordance with the usage characteristics of the users who use the batteries.

[0070] Note that Figure 8 shows a linear function f1 as an example of a function that defines the relationship between battery replacement intervals and thresholds, but the function does not necessarily have to be linear; it can be nonlinear. Also, while Figure 8 shows an example where the relationship between battery replacement intervals and thresholds is defined by a function, it may also be defined by other methods, such as a lookup table.

[0071] Returning to the explanation of Figure 5, the second determination unit 15D is a processing unit that performs battery degradation diagnosis. In one embodiment, the second determination unit 15D determines whether the number of times authenticity judgments have been performed by the first determination unit 15B, as shown in the determination count information 13D, is equal to or greater than the threshold Th2 set by the setting unit 15C. In this case, if the number of times authenticity judgments have been performed for a battery is equal to or greater than the threshold Th2, the second determination unit 15D resets the number of times authenticity judgments have been performed for that battery and then starts the battery degradation diagnosis. Here, an example of resetting the number of times authenticity judgments have been performed is given, but instead, an offset equal to the number of times authenticity judgments have been performed may be added to the threshold.

[0072] Here, the second determination unit 15D can perform multiple degradation diagnoses in stages. As just one example, the second determination unit 15D performs a first degradation diagnosis on a battery installed in an empty slot, and if degradation of the battery is determined in the first degradation diagnosis, it performs a second degradation diagnosis. The algorithm for such a second degradation diagnosis may be more precise than that of the first degradation diagnosis, and if it is more precise than the first degradation diagnosis, it may be acceptable for the computational cost to be greater than that of the first degradation diagnosis.

[0073] More specifically, the second determination unit 15D performs a first degradation diagnosis using a simplified estimate of the State of Health (SOH). As an example, the second determination unit 15D can calculate a simplified estimate of the SOH according to a calculation formula in which the relationship between the number of charge cycles and the SOH is defined by a power law. Generally, if the vertical axis is SOH, the horizontal axis is elapsed time (time), and the SOH of a new battery is set to 1, then applying the square root rule, which is representative of empirical methods, it can be expressed as equation (1) below. In equation (1) below, "k" refers to a coefficient. Here, assuming that the cumulative number of charge cycles (charge_count) ∝ elapsed time, equation (1) below can be expressed as equation (2) below. By substituting the cumulative number of charge cycles of the battery into equation (2) obtained in this way, a simplified estimate of the SOH can be calculated. Then, the second determination unit 15D determines whether the simplified estimate of the SOH is less than the threshold Th3.

[0074] SOH = 1 - k(time)^0.5 ... (1) SOH=1-k´(charge_count)^0.5···(2)

[0075] Here, if the simplified estimate of SOH is less than the threshold Th3, the battery is diagnosed as degraded. In this case, the second determination unit 15D calculates a precise estimate of SOH. Such a precise estimate of SOH can be calculated according to an algorithm that is more precise than the algorithm that calculates the simplified estimate of SOH. For example, the second determination unit 15D can calculate a precise estimate of SOH according to a known charging curve analysis method, or it can output a precise estimate of SOH using a neural network trained by deep learning. Then, the second determination unit 15D determines whether the precise estimate of SOH is less than the threshold Th4. If the precise estimate of SOH is less than the threshold Th4, the second determination unit 15D outputs instructions to the station 30 for disposal of the battery, such as reuse or recycling.

[0076] Furthermore, if the simplified estimate of SOH is not less than the threshold Th3, or if the precise estimate of SOH is not less than the threshold Th4, the second determination unit 15D notifies the station 30 that the battery degradation diagnosis is complete. When the completion of the degradation diagnosis is notified in this way, the station 30 can remove the battery after charging is complete.

[0077] <Processing flow> Next, the processing flow of the server device 10 according to this embodiment will be described. Here, we will first describe (1) the overall processing performed by the server device 10, and then describe (2) the degradation diagnosis processing, which is performed as a subroutine of the overall processing.

[0078] (1) Overall processing Figure 9 is a flowchart (1) showing the procedure for the overall process. This process can be started as an example when a user ID is received from station 30. As shown in Figure 9, the supply 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 or not it is a legitimate user whose user ID is registered in user information 13A (step S101).

[0079] At this point, if user authentication is successful, that is, if the user is a legitimate user whose user ID is registered in user information 13A (step S101 Yes), the supply unit 15A outputs an instruction to the station 30 to install the battery into an empty slot (step S102).

[0080] Then, when a user's battery is installed in an empty slot of the station 30, the supply unit 15A acquires the battery's unique information measured by the measurement unit 33 of the station 30 (step S103).

[0081] Next, the supply unit 15A updates the battery replacement interval among the battery replacement intervals included in the replacement information 13B stored in the storage unit 13 (step S104).

[0082] Next, the first determination unit 15B determines whether the battery installed in the empty slot is genuine or not based on the result of comparing the battery-specific information of the battery acquired in step S103 with the battery-specific information of the reference stored in the reference information 13C (step S105).

[0083] If the battery is determined to be genuine (step S106 Yes), the supply unit 15A notifies station 30 of permission to replace the battery (step S107). Upon receiving this permission, station 30 is permitted to remove the battery from the charged slot.

[0084] On the other hand, if user authentication fails, or if the battery is determined to be counterfeit (step S101No or step S106No), the supply unit 15A performs the following process: the supply unit 15A notifies station 30 that battery replacement is not permitted (step S108) and terminates the process. At station 30, which has been notified of the denial of replacement in this way, removal of the battery from the charged slot is prohibited. Note that the permission or denial of battery replacement in the flowchart shown in Figure 9 is merely one example of operation and does not prevent the adoption of other operations as described above.

[0085] After step S107 is executed, the first determination unit 15B updates the number of times the authenticity determination of the battery has been performed among the number of times the authenticity determination has been performed included in the determination count information 13D stored in the storage unit 13 (step S109).

[0086] Then, the setting unit 15C sets a threshold Th2 based on the battery replacement intervals for which authenticity determination was performed in step S105 among the battery replacement intervals included in the replacement information 13B (step S110).

[0087] Then, the second determination unit 15D determines whether the number of times the authenticity determination was performed on the battery in step S105 is equal to or greater than the threshold Th2 set in step S110, based on the determination count information 13D (step S111).

[0088] If the number of times the battery authenticity check has been performed is equal to or greater than the threshold Th2 (step S111Yes), the second determination unit 15D resets the number of times the battery authenticity check has been performed (step S112). After that, the second determination unit 15D performs a "degradation diagnosis process" to determine the degradation of the battery (step S113) and then terminates the process.

[0089] If the number of times the battery authenticity check has been performed is not equal to or greater than the threshold Th2 (step S111No), the processes in steps S112 and S113 are skipped and the process terminates.

[0090] (2) Deterioration diagnosis treatment Figure 10 is a flowchart showing the procedure for the degradation diagnosis process. This process corresponds to step S113 shown in Figure 9. As shown in Figure 10, the second determination unit 15D calculates a simplified estimate of SOH (step S201). Then, the second determination unit 15D determines whether the simplified estimate of SOH calculated in step S201 is less than the threshold Th3 (step S202).

[0091] Here, if the simplified estimate of SOH is less than the threshold Th3 (step S202 Yes), it is diagnosed that the battery is degraded. In this case, the second determination unit 15D calculates a precise estimate of SOH (step S203). Then, the second determination unit 15D determines whether or not the precise estimate of SOH is less than the threshold Th4 (step S204).

[0092] At this point, if the precise estimated value of SOH is less than the threshold Th4 (step S204 Yes), the second determination unit 15D outputs an instruction to the station 30 regarding the disposal of the battery, such as reuse or recycling (step S205), and terminates the process.

[0093] If the simplified estimate of SOH is not less than the threshold Th3, or if the precise estimate of SOH is not less than the threshold Th4 (step S202No or step S204No), the second determination unit 15D notifies the station 30 that the battery degradation diagnosis is complete (step S206) and terminates the process. When the completion of the degradation diagnosis is notified in this way, the station 30 can remove the battery after charging is complete.

[0094] <One aspect of the effect> As described above, the server device 10 in this embodiment acquires battery-specific information of the battery 3 installed in an empty slot of the station 30. The server device 10 then performs a genuineness determination to determine whether the battery 3 is genuine or not based on the battery-specific information of the battery 3. If the number of times the genuineness determination of the battery 3 has been performed exceeds a threshold, the server device 10 then performs a degradation diagnosis of the battery 3.

[0095] For example, the probability of performing a degradation diagnosis can be controlled based on the cumulative number of charging cycles and the charging frequency, as one example:

[0096] One aspect of this is that a high cumulative number of charging cycles suggests that battery 3 has likely been used many times by the user since it was shipped. Additionally, frequent charging increases the likelihood that battery 3 is already degrading and depleting faster. If at least one of these two conditions is met, the probability of performing a degradation diagnosis can be increased.

[0097] Another aspect is that if both the cumulative number of charge cycles and the charging frequency are low, there is a higher probability that battery 3 has not degraded significantly since being shipped. In this case, the probability of performing a degradation diagnosis can be reduced. This helps to mitigate the decrease in battery 3's turnover rate.

[0098] Thus, in the server device 10 according to this embodiment, degradation diagnosis is performed at a frequency that eliminates the trade-off between a decrease in battery turnover rate and the provision of defective batteries. Therefore, the server device 10 according to this embodiment makes it possible to optimize the frequency of degradation diagnosis.

[0099] Furthermore, the server device 10 in this embodiment sets a threshold based on the interval at which battery-specific information is acquired. Therefore, the threshold can be dynamically changed according to the battery replacement interval, making it possible to tune the threshold to eliminate the trade-off between reduced battery turnover and the provision of defective batteries, in accordance with the usage characteristics of the users of the batteries.

[0100] <Embodiment 2> Now, in the above embodiment 1, we gave an example of setting a threshold that is compared with the number of times the battery's authenticity check is performed based on the battery replacement interval, but it is not necessary to set the threshold based on the battery replacement interval. Therefore, in this embodiment, we will explain an example of setting a threshold based on the frequency with which the battery is determined to be genuine at station 30.

[0101] <Configuration of Server Device 20> Figure 11 is a block diagram (2) showing an example of the functional configuration of the server device 20. In Figure 11, functional units having the same functions as those shown in Figure 5 are denoted by the same reference numerals, and their descriptions are omitted. As shown in Figure 11, the server device 20 differs from the server device 10 shown in Figure 5 in that the storage unit 23 stores data transfer frequency information 23A instead of exchange information 13B. Furthermore, the server device 20 differs from the first determination unit 15B and setting unit 15C shown in Figure 5 in that some of the processing performed by the first determination unit 25A and setting unit 25B in the control unit 25 is different.

[0102] The first determination unit 25A differs from the first determination unit 15B shown in Figure 5 in that, after updating the number of times the battery authenticity determination has been performed, it adds a process to update the frequency at which a genuine product is brought to the station 30 where the authenticity determination was performed. The term "frequency" here may include the number of times, probability, probability distribution, etc.

[0103] Figure 12 shows an example of updating the bring-in frequency information 23A. As shown in Figure 12, the bring-in frequency information 23A is data that associates items such as the number of times genuine products are brought in (probability) and the number of times counterfeit products are brought in (probability) for each station. Of these, "number of times genuine products are brought in (probability)" refers to the number of times (probability) that a battery brought in by a user to station 30 was determined to be genuine. Also, "number of times counterfeit products are brought in (probability)" refers to the number of times (probability) that a battery brought in by a user to station 30 was determined to be counterfeit. Note that the upper part of Figure 12 shows the bring-in frequency information 23A before the update, and the lower part of Figure 12 shows the bring-in frequency information 23A after the update.

[0104] Here, Figure 12 shows, as an example, an update to the frequency information 23A for batteries brought to station "Koto Ward B" when the authenticity determination result for battery ID "A00002" is determined to be "genuine".

[0105] In this case, an update is performed on the data entry for station "Koto-ku B" included in the data entry frequency information 23A, that is, the data entry on the second line. In other words, since the result of the battery authenticity check is "genuine," the number of genuine batteries brought in to station "Koto-ku B" "34" is incremented by 1. On the other hand, the number of counterfeit batteries brought in to station "Koto-ku B" does not change, so it is not updated.

[0106] Thus, the latest count of bringing in counterfeit goods remains unchanged at "15," while the latest count of bringing in genuine goods is incremented from "34" to "35." Although not shown in the diagram, the total number of brought-in counts is also incremented from "49 (=34+15)" to "50."

[0107] In addition, the probability of bringing in genuine products at Station "Koto Ward B" is updated from "69%" to "70%" by dividing the most recent number of genuine products brought in ("35") by the total number of recent products brought in ("50"). On the other hand, the probability of bringing in counterfeit products at Station "Koto Ward B" is updated from "31%" to "30%" by dividing the most recent number of counterfeit products brought in ("15") by the total number of recent products brought in ("50").

[0108] Returning to the explanation of Figure 11, the setting unit 25B differs from the setting unit 15C shown in Figure 5 in that it sets a threshold that is compared to the number of times the battery authenticity check has been performed. Specifically, the setting unit 25B sets the threshold Th5 based on the frequency of genuine products being brought into the station 30.

[0109] Figure 13 is a schematic diagram showing an example of threshold setting. In the graph G2 shown in Figure 13, the horizontal axis represents the probability of bringing in genuine products (%), and the vertical axis represents the threshold (number of times). As shown in Figure 13, the graph G2 defines a function f2 in which the threshold increases as the probability of bringing in genuine products increases, or in other words, the threshold decreases as the probability of bringing in genuine products decreases. According to such a function f2, the setting unit 25B can set a threshold Th5 to be compared with the number of times the authenticity check is performed. For example, let's take the case where the authenticity check of a battery is performed at station "Koto-ku B". In this case, the setting unit 25B refers to the second row of data entries in the data entries included in the introduction frequency information 23A that corresponds to station "Koto-ku B". Then, the setting unit 25B calculates a threshold "12" as the target variable of function f2 by substituting the probability of bringing in genuine products "70%" included in the data entry for station "Koto-ku B" as the explanatory variable of function f2. Then, the setting unit 25B sets the threshold "12", which was calculated as the target variable of function f2, to threshold Th5.

[0110] By setting a threshold Th5 that is compared with the number of times authenticity checks are performed according to such a function f2, the threshold can be decreased when the probability of bringing in a genuine product is low, and increased when the probability of bringing in a genuine product is high. Therefore, since the threshold can be dynamically changed according to the probability of bringing in a genuine product, it is possible to tune the threshold to eliminate the trade-off between a decrease in battery turnover rate and the provision of defective batteries, according to the quality of the user base, such as the morality and integrity of the customers.

[0111] Note that Figure 13 shows a linear function f2 as an example of a function that defines the correspondence between the probability of bringing in genuine goods and the threshold, but the function does not necessarily have to be linear and may be nonlinear. Also, although Figure 13 shows an example where the correspondence between the probability of bringing in genuine goods and the threshold is defined by a function, it may also be defined by other methods other than a function, such as a lookup table.

[0112] <Processing flow> Figure 14 is a flowchart (2) showing the procedure for the overall process. The process shown in Figure 14 is also just one example and can be started when a user ID is received from station 30. Note that in Figure 14, different steps are assigned to processes that are different from the flowchart in Figure 9, while the same steps are assigned to processes that are the same as those in the flowchart in Figure 9.

[0113] As shown in Figure 14, the supply 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 or not the user is a legitimate user whose user ID is registered in user information 13A (step S101).

[0114] At this point, if user authentication is successful, that is, if the user is a legitimate user whose user ID is registered in user information 13A (step S101 Yes), the supply unit 15A outputs an instruction to the station 30 to install the battery into an empty slot (step S102).

[0115] Then, when a user's battery is installed in an empty slot of the station 30, the supply unit 15A acquires the battery's unique information measured by the measurement unit 33 of the station 30 (step S103).

[0116] Next, the first determination unit 15B determines whether the battery installed in the empty slot is genuine or not based on the result of comparing the battery-specific information of the battery acquired in step S103 with the battery-specific information of the reference stored in the reference information 13C (step S105).

[0117] If the battery is determined to be genuine (step S106 Yes), the supply unit 15A notifies station 30 of permission to replace the battery (step S107). Upon receiving this permission, station 30 is permitted to remove the battery from the charged slot.

[0118] On the other hand, if user authentication fails, or if the battery is determined to be counterfeit (step S101No or step S106No), the supply unit 15A performs the following process: the supply unit 15A notifies station 30 that battery replacement is not permitted (step S108) and terminates the process. At station 30, which has been notified of the denial of replacement in this way, removal of the battery from the charged slot is prohibited. Note that the permission or denial of battery replacement in the flowchart shown in Figure 14 is merely one example of operation and does not prevent the adoption of other operations as described above.

[0119] After step S107 is executed, the first determination unit 15B updates the number of times the authenticity determination of the battery has been performed among the number of times the authenticity determination has been performed included in the determination count information 13D stored in the storage unit 13 (step S109).

[0120] Next, the first determination unit 25A updates the frequency of genuine product introductions included in the introduction frequency information 23A, corresponding to the station 30 for which authenticity determination was performed in step S105 (step S301).

[0121] Then, the setting unit 25B sets a threshold Th5 based on the frequency of genuine product introductions from the station 30 for which authenticity determination was performed in step S105, among the frequency of genuine product introductions included in the introduction frequency information 23A (step S302).

[0122] Then, the second determination unit 15D determines whether the number of times the authenticity determination was performed on the battery in step S105 is equal to or greater than the threshold Th5 set in step S302, based on the determination count information 13D (step S111).

[0123] If the number of times the battery authenticity check has been performed is equal to or greater than the threshold Th5 (step S111Yes), the second determination unit 15D resets the number of times the battery authenticity check has been performed (step S112). After that, the second determination unit 15D performs a "degradation diagnosis process" to determine the degradation of the battery (step S113) and then terminates the process.

[0124] If the number of times the battery authenticity check has been performed is not equal to or greater than the threshold Th5 (step S111No), the processes in steps S112 and S113 are skipped and the process terminates.

[0125] <One aspect of the effect> As described above, the server device 20 according to this embodiment, like the server device 10 according to Embodiment 1, can optimize the frequency of degradation diagnosis. Furthermore, the server device 20 according to this embodiment, like the server device 10 according to Embodiment 1, can dynamically change the threshold value compared to the number of times authenticity judgment is performed, according to the probability of genuine products being brought into the station 30. Therefore, since the threshold value can be dynamically changed according to the probability of genuine products being brought in, it is possible to tune the threshold value to eliminate the trade-off between a decrease in battery turnover rate and the provision of defective batteries, according to the quality of the user's customer base, such as the quality of morals and dignity.

[0126] <Other Embodiments> Now, while embodiments of the present invention have been described, the present invention has various applications and may be implemented in various different forms other than those described above.

[0127] For example, the second determination unit 15D may apply the first degradation diagnosis to the battery if the number of times the battery authenticity determination has been performed is equal to or greater than the threshold Th11 of the first stage, and may also apply a second degradation diagnosis, which is more precise than the first degradation diagnosis, to the battery if the number of times the battery authenticity determination has been performed is equal to or greater than the threshold Th12 of the second stage.

[0128] Figure 15 is a flowchart of the overall process for an application example. The process shown in Figure 15 is also just one example and can be started when a user ID is received from station 30. Note that in Figure 15, different steps are assigned to processes that are different from the flowchart in Figure 9, while the same steps are assigned to processes that are the same as those in the flowchart in Figure 9.

[0129] In the flowchart shown in Figure 15, the process up to step S110 is the same as in the flowchart shown in Figure 9, so we will begin the explanation from the process after step S110.

[0130] After step S110 is executed, the second determination unit 15D determines whether the number of times the authenticity determination was performed on the battery in step S105 is equal to or greater than the threshold Th11 of the first stage, based on the determination count information 13D (step S401).

[0131] Then, if the number of times the battery authenticity check has been performed is equal to or greater than the threshold Th11 of the first stage (step S401 Yes), the second determination unit 15D performs the following process. That is, the second determination unit 15D determines whether the number of times the authenticity check has been performed for the battery whose authenticity check was performed in step S105 is equal to or greater than the threshold Th12 of the second stage (step S402).

[0132] In this case, if the number of times the battery authenticity check has been performed is not equal to or greater than the threshold Th12 of the second stage (step S402 No), the second determination unit 15D calculates a simplified estimate of the SOH (step S403). On the other hand, if the number of times the battery authenticity check has been performed is equal to or greater than the threshold Th12 of the second stage (step S402 Yes), the second determination unit 15D calculates a precise estimate of the SOH (step S404).

[0133] Subsequently, the second determination unit 15D resets the number of times the authenticity determination of the battery has been performed (step S405). Next, the second determination unit 15D determines whether or not the battery is degraded based on the simplified estimate of SOH calculated in step S403 or the precise estimate of SOH calculated in step S404 (step S406).

[0134] If it is determined that the battery is degraded (step S406 Yes), the second determination unit 15D outputs an instruction to the station 30 regarding the disposal of the battery, such as reuse or recycling (step S407), and terminates the process.

[0135] Furthermore, if the number of times the battery authenticity check has been performed is not equal to or greater than the threshold Th11 of the first stage, or if it is determined that the battery is not degraded (step S401No or step S406No), the second determination unit 15D notifies the station 30 that the battery degradation diagnosis is complete (step S408) and terminates the process.

[0136] This process minimizes the frequency with which the second degradation diagnosis, which requires more computation than the first degradation diagnosis, is performed, thereby minimizing the decrease in battery turnover rate at station 30.

[0137] <Numerical values, etc.> The details described in the above embodiment, such as the number of magnetic sensors in the measuring unit 33 of station 30, are merely examples and can be changed. Furthermore, the flowchart described in the embodiment can also be modified within a consistent range.

[0138] <System> The processing procedures, control procedures, specific names, and information including various data and parameters shown in the above documents and drawings may be changed at will unless otherwise specified. For example, one or more of the functional units of the server device 10, including the supply unit 15A, the first determination unit 15B, the setting unit 15C, and the second determination unit 15D, may be composed of separate devices. Similarly, one or more of the functional units of the server device 20, including the supply unit 15A, the first determination unit 25A, the setting unit 25B, and the second determination unit 15D, may be composed of separate devices.

[0139] Furthermore, the components of each illustrated device are functionally conceptual and do not necessarily need to be physically configured as shown. In other words, the specific forms of distribution and integration of each device are not limited to those shown. That is, all or part of them can be functionally or physically distributed and integrated in any units according to various loads and usage conditions. Note that each configuration may also be a physical configuration.

[0140] Furthermore, each processing function performed by each device may be implemented, in whole or in part, by a CPU (Central Processing Unit) and a program executed by that CPU, or by wired logic hardware.

[0141] <Hardware> Next, we will describe an example of the hardware configuration of the computer described in Embodiment 1 and Embodiment 2 above. Figure 16 is a diagram showing an example of the hardware configuration. As shown in Figure 16, the information processing device 100 has a communication device 100a, an HDD (Hard Disk Drive) 100b, memory 100c, and a processor 100d. Note that each part shown in Figure 16 is interconnected by a bus or the like.

[0142] The communication device 100a is a network interface card or the like, and communicates with other servers. The HDD 100b stores programs and databases that operate the functions shown in Figure 5 or Figure 11.

[0143] The processor 100d runs a process that performs the functions described in Figure 5 or Figure 11 by reading a program that performs the same processing as the processing unit shown in Figure 5 or Figure 11 from the HDD 100b or the like and loading it into memory 100c.

[0144] Such processes perform functions similar to those of the processing units in server devices 10 and 20. For example, processor 100d reads a program having functions similar to those of the supply unit 15A, the first determination unit 15B, the setting unit 15C, and the second determination unit 15D from HDD 100b or the like. Then, processor 100d executes a process that performs the same processing as those of the supply unit 15A, the first determination unit 15B, the setting unit 15C, and the second determination unit 15D. Alternatively, processor 100d reads a program having functions similar to those of the supply unit 15A, the first determination unit 25A, the setting unit 25B, and the second determination unit 15D from HDD 100b or the like. Then, processor 100d executes a process that performs the same processing as those of the supply unit 15A, the first determination unit 25A, the setting unit 25B, and the second determination unit 15D.

[0145] Thus, the information processing device 100 operates as an information processing device that executes an evaluation method by reading and executing a program. Furthermore, the information processing device 100 can also achieve the same functionality as the embodiment described above by reading the program from a recording medium using a media reader and executing the read program. It should be noted that the program referred to in this other embodiment is not limited to being executed by the information processing device 100. For example, the present invention can be similarly applied when another computer or server executes the program, or when they collaborate to execute the program.

[0146] The above program can be distributed via a network such as the Internet. Furthermore, the program can be recorded on any storage medium and executed by reading it from the medium by a computer. For example, the storage medium can be a hard disk, flexible disk (FD), CD-ROM, MO (Magneto-Optical disk), DVD (Digital Versatile Disc), etc.

[0147] <Other> Some examples of the combinations of technical features that will be disclosed are listed below.

[0148] (1) An acquisition unit that acquires battery-specific information, A first determination unit performs a genuine determination to determine whether the battery is genuine or not based on the battery-specific information, If the number of times the authenticity check of the battery has been performed exceeds a threshold, a second determination unit performs a degradation diagnosis of the battery, An information processing device characterized by having the following features.

[0149] (2) The information processing device according to (1), characterized in that the second determination unit resets the number of times the authenticity determination of the battery is performed when the battery degradation diagnosis is performed.

[0150] (3) The information processing apparatus according to (1) or (2), wherein the second determination unit applies a first degradation diagnosis to the battery if the number of times the authenticity determination of the battery has been performed is equal to or greater than a first threshold, and applies a second degradation diagnosis which is more precise than the first degradation diagnosis to the battery if the number of times the authenticity determination of the battery has been performed is equal to or greater than a second threshold which is greater than the first threshold.

[0151] (4) The information processing apparatus according to any one of (1) to (3), further comprising a setting unit that sets the threshold based on the interval at which the battery-specific information of the battery is acquired.

[0152] (5) The information processing apparatus according to (4), characterized in that the setting unit sets a threshold that becomes larger as the interval becomes shorter, or a threshold that becomes smaller as the interval becomes longer.

[0153] (6) The information processing device according to any one of (1) to (3), further comprising a setting unit that sets the threshold based on the frequency at which the battery is determined to be genuine in a charging facility where the battery on which the authenticity determination has been performed is charged.

[0154] (7) The information processing apparatus according to (6), characterized in that the setting unit sets a threshold that becomes larger as the frequency increases, or a threshold that becomes smaller as the frequency decreases.

[0155] (8) Obtain battery-specific information, Based on the battery-specific information, a determination is made to determine whether the battery is genuine or not. If the number of times the authenticity check of the battery has been performed exceeds a threshold, the battery degradation diagnosis will be performed. A method for diagnosing deterioration, characterized in that the processing is performed by a computer.

[0156] (9) Obtain battery-specific information, Based on the battery-specific information, a determination is made to determine whether the battery is genuine or not. If the number of times the authenticity check of the battery has been performed exceeds a threshold, the battery degradation diagnosis will be performed. A degradation diagnosis program characterized by having a computer perform the processing. [Explanation of Symbols]

[0157] 1. Battery sharing system 3 Batteries 10 Server devices 11. Communication Control Unit 13 Storage section 13A User Information 13B Exchange Information 13C Reference Information 13D Result Count Information 15 Control Unit 15A supply department 15B First determination section 15C Setting section 15D Second determination unit 30 stations 31 Information Reading Unit 33 Measuring part

Claims

1. An acquisition unit that acquires battery-specific information, A first determination unit performs a determination of whether the battery is genuine or not based on the battery-specific information, If the number of times the authenticity check of the battery has been performed exceeds a threshold, a second determination unit performs a battery degradation diagnosis, An information processing device characterized by having the following features.

2. The information processing apparatus according to claim 1, characterized in that the second determination unit resets the number of times the authenticity determination of the battery has been performed when the degradation diagnosis of the battery has been performed.

3. The information processing apparatus according to claim 1, characterized in that the second determination unit applies a first degradation diagnosis to the battery if the number of times the authenticity determination of the battery has been performed is equal to or greater than a first threshold, and applies a second degradation diagnosis which is more precise than the first degradation diagnosis to the battery if the number of times the authenticity determination of the battery has been performed is equal to or greater than a second threshold which is greater than the first threshold.

4. The information processing apparatus according to any one of claims 1 to 3, further comprising a setting unit that sets the threshold based on the interval at which the battery-specific information of the battery is acquired.

5. The information processing apparatus according to claim 4, characterized in that the setting unit sets a threshold that becomes larger as the interval becomes shorter, or a threshold that becomes smaller as the interval becomes longer.

6. The information processing device according to any one of claims 1 to 3, further comprising a setting unit that sets the threshold value based on the frequency at which the battery is determined to be genuine in a charging facility where the battery for which the authenticity determination has been performed is charged.

7. The information processing apparatus according to claim 6, characterized in that the setting unit sets a threshold that becomes larger as the frequency increases, or a threshold that becomes smaller as the frequency decreases.

8. Obtain the battery's unique information, Based on the battery-specific information, a determination is made to determine whether the battery is genuine or not. If the number of times the authenticity check of the battery has been performed exceeds a threshold, the battery degradation diagnosis will be performed. A method for diagnosing deterioration, characterized in that the processing is performed by a computer.

9. Obtain the battery's unique information, Based on the battery-specific information, a determination is made to determine whether the battery is genuine or not. If the number of times the authenticity check of the battery has been performed exceeds a threshold, the battery degradation diagnosis will be performed. A degradation diagnosis program characterized by having a computer perform the processing.

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