Information processing device, information processing method, and program

Abstract

To estimate an offset error in a secondary battery to allow accurate estimation of the state of the secondary battery.SOLUTION: An information processing apparatus processes information on power storage devices, and comprises: an acquisition unit that acquires first information that is transmitted from the plurality of power storage devices and that is information on charging or discharging of the plurality of power storage devices, and second information on charging or discharging of a first power storage device of the plurality of power storage devices; and a processing unit that corrects the second information on the basis of the first information, and outputs the corrected second information as third information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Conventionally, there are known techniques for estimating errors associated with measurement of the state of a secondary battery. For example, Patent Document 1 discloses a technique for optimizing an open circuit voltage (OCV) curve by filtering data with small voltage changes due to charging and discharging from time-series data related to the current and voltage of a secondary battery and reducing errors between the filtered data and the parameters of the OCV curve. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2023-48545 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the conventional technology measures the state of a single secondary battery and estimates the measurement error of that secondary battery from the measured data. Therefore, the conventional technology may not be able to estimate the measurement error (offset error) that is unique to a certain secondary battery compared to other secondary batteries. As a result, it may not be possible to estimate the state of the secondary battery with high accuracy.

[0005] The present invention has been made in consideration of the above circumstances, and one of its objects is to provide an information processing device, an information processing method, and a program that can estimate the offset error of a secondary battery, thereby enabling highly accurate estimation of the state of the secondary battery. [Means for solving the problem]

[0006] The information processing device, the information processing method, and the program according to the present invention employ the following configuration.

[0007] (1): An information processing device according to one embodiment of the present invention is an information processing device that processes information related to power storage devices, and includes an acquisition unit that acquires first information, which is information related to charging or discharging of the power storage devices transmitted from the power storage devices, and second information related to charging or discharging of a first power storage device among the power storage devices, and a processing unit that corrects the second information based on the first information and outputs the corrected second information as third information.

[0008] (2): In the above aspect (1), the first information is stored in association with first identification information that identifies each of the plurality of power storage devices.

[0009] (3): In the above aspect (1), the first information is information relating to charging or discharging performed by connecting a power transfer device that transfers power between each of the plurality of power storage devices and the power storage devices, and is information relating to charging or discharging performed between the plurality of power storage devices and the power transfer device and / or information relating to charging or discharging performed between the plurality of power transfer devices and the power storage devices.

[0010] (4) In the above aspect (3), the first information is stored in association with second identification information that identifies the power transfer device.

[0011] (5): In the above aspect (1), the first information, the second information, and the third information include data on physical quantities related to charging or discharging of the power storage device.

[0012] (6): In the above aspect (5), the physical quantity is a current or a voltage.

[0013] (7): In the above aspect (6), the physical quantity is an electric current.

[0014] (8): In the above aspects (1) to (7), the processing unit includes a first processing unit that calculates and outputs correction information, which is information regarding a correction amount specific to the first storage device, based on the first information, and a second processing unit that outputs the third information based on the correction information and the second information.

[0015] (9): In the above aspect (8), the first processing unit calculates the correction information by constructing a prediction model that predicts measured values ​​of physical quantities related to charging or discharging of the plurality of power storage devices included in the first information, based on first identification information that identifies each of the plurality of power storage devices included in the first information and second identification information that identifies a power transfer device that transfers power between each of the plurality of power storage devices.

[0016] (10): In the aspect (8) above, the first processing unit calculates the correction information based on information included in the first information, in which the physical quantity satisfies a predetermined condition.

[0017] (11): Another aspect of the information processing method of the present invention is an information processing method for processing information relating to power storage devices, in which a computer acquires first information, which is information relating to charging or discharging of a plurality of the power storage devices, transmitted from the plurality of the power storage devices, and second information relating to charging or discharging of a first power storage device among the plurality of the power storage devices, corrects the second information based on the first information, and outputs the corrected second information as third information.

[0018] (12): Another aspect of the present invention provides a program for processing information relating to power storage devices, which program causes a computer to acquire first information, which is information relating to the charging or discharging of a plurality of the power storage devices and is transmitted from the plurality of the power storage devices, and second information relating to the charging or discharging of a first power storage device among the plurality of the power storage devices, correct the second information based on the first information, and output the corrected second information as third information. [Effects of the Invention]

[0019] According to aspects (1) to (12), by estimating the offset error of the secondary battery, it is possible to estimate the state of the secondary battery with high accuracy. [Brief explanation of the drawings]

[0020] [Figure 1] 1 is a diagram illustrating an example of the overall configuration of a battery exchange system 1 according to an embodiment. [Figure 2] 1 is a block diagram showing an example of the configuration of a detachable battery 100 according to an embodiment. [Figure 3] FIG. 2 is a diagram illustrating an example of a configuration of an information processing device 300 according to an embodiment. [Figure 4] 10 is a graph showing an example of a target current value when charging a detachable battery 100. [Figure 5] 10 is a diagram showing an example of time-series data 350A stored in a storage unit 350. FIG. [Figure 6] 10 is a diagram showing an example of correction amount data 350B estimated by the data processing unit 320. FIG. [Figure 7] FIG. 10 is a diagram showing an example of the use of estimated correction amount data 350B. [Figure 8] 10 is a flowchart showing an example of the flow of processing executed by information processing device 300. [Figure 9] 10 is a graph showing an example of a target current value when charging a detachable battery 100 according to Modification 1. [Figure 10] 10 is a graph showing the relationship between the magnitude of the sensor current value and the error between the sensor current value and the true value according to Modification 2. DETAILED DESCRIPTION OF THE INVENTION

[0021] Hereinafter, an information processing device, an information processing method, and a program according to an embodiment of the present invention will be described with reference to the drawings.

[0022] <Overall configuration of battery exchange system 1> 1 is a diagram showing an example of the overall configuration of a battery exchange system 1 according to an embodiment. The battery exchange system 1 includes, for example, a plurality of removable batteries 100, a plurality of battery exchange stations 200, and an information processing device 300. The plurality of battery exchange stations 200 and the information processing device 300 are capable of communicating with each other via a network NW. An electric vehicle 10 may be communicatively connected to the network NW. The network NW includes, for example, the Internet, a cellular network, a Wi-Fi network, a WAN (Wide Area Network), a LAN (Local Area Network), Bluetooth (registered trademark), and the like.

[0023] The battery exchange station 200 is a device that charges and exchanges (returns or lends out) the detachable battery 100 that is the driving source of the electric vehicle 10. The detachable battery 100 is detachably attached to the electric vehicle 10. The detachable battery 100 may be a power supply device used for applications such as a mobile portable power source.

[0024] The electric vehicle 10 is a vehicle that detachably mounts a removable battery 100. The example in FIG. 1 shows a saddle-ride type electric vehicle (electric two-wheeler) 10-1 and an in-cabin type electric vehicle (electric four-wheeler) 10-2, both of which travel using an electric motor driven by power supplied by a power storage unit 120 (described below) of the removable battery 100. For example, the electric vehicle 10-1 shown in FIG. 1 can be equipped with two removable batteries 100, and the electric vehicle 10-2 can be equipped with three removable batteries 100. In this way, the number of removable batteries that can be mounted varies depending on the type and shape of the electric vehicle 10. Furthermore, the removable batteries that can be used may vary depending on the vehicle model.

[0025] [Detachable Battery 100] 2 is a block diagram showing an example of the configuration of the detachable battery 100 according to the embodiment. The detachable battery 100 includes, for example, a BMU 110, a power storage unit 120, and a connection unit 150. The BMU 110 also includes a measurement sensor 130 and a storage unit 140.

[0026] The BMU 110 controls charging and discharging of the power storage unit 120, performs cell balancing, detects abnormalities in the power storage unit 120, derives the cell temperature of the power storage unit 120, derives the charge / discharge current of the power storage unit 120, and estimates the SOC (positive electrode OCP and negative electrode OCP) of the power storage unit 120. The BMU 110 stores the measurement results of the measurement sensor 130 in the memory unit 140 as battery state information.

[0027] The power storage unit 120 is, for example, a battery pack in which a plurality of cells are connected in series. The cells constituting the power storage unit 120 are, for example, lithium-ion secondary batteries (LIBs), nickel-metal hydride batteries, all-solid-state batteries, etc.

[0028] The measurement sensor 130 includes a voltage sensor for measuring the charging state of the power storage unit 120 in chronological order, a current sensor for measuring in chronological order the current flowing through the power storage unit 120 via the connection unit 150 for charging and discharging, and a temperature sensor for measuring the temperature of the removable battery 100. The measurement sensor 130 outputs battery state information such as the voltage, current, and temperature measured in chronological order to the BMU 110.

[0029] The storage unit 140 includes a non-volatile storage device such as a flash memory. The storage unit 140 stores battery state information measured in chronological order. The storage unit 140 may also store a battery ID assigned to the removable battery 100.

[0030] The connection unit 150 is electrically connected to a battery connection unit (not shown) of the electric vehicle 10 when the removable battery 100 is attached to the electric vehicle 10. Furthermore, when the removable battery 100 is accommodated in one of a plurality of slots 210 (an example of a "power transfer device" in the claims) present in the battery exchange station 200, the connection unit 150 is electrically connected to the battery exchange station 200, and charges or discharges the power storage unit 120 by transferring power to or from the battery exchange station 200. The connection unit 150 further includes, for example, a power line connection terminal (battery terminal) and a communication line connection terminal, and when electrically connected to the battery exchange station 200, transmits the time-series battery status information stored in the memory unit 140 to the battery exchange station 200. The battery exchange station 200 transmits the received time-series battery status information to the information processing device 300. Furthermore, for example, the BMU 110 may include a wired or wireless communication module and transmit the time-series battery state information to the battery exchange station 200 or the information processing device 300 via a wired or wireless network.

[0031] [Configuration of information processing device] Next, an example of an information processing device 300 that processes battery state information related to the removable battery 100 will be described. FIG. 3 is a diagram showing an example of the configuration of the information processing device 300 according to an embodiment. The information processing device 300 includes, for example, a data acquisition unit 310 and a data processing unit 320. The data acquisition unit 310 and the data processing unit 320 are realized by, for example, a hardware processor such as a central processing unit (CPU) executing a program (software). Some or all of these components may be realized by hardware (including circuitry) such as a large-scale integration (LSI), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a graphics processing unit (GPU), or may be realized by a combination of software and hardware. The program may be stored in advance in a storage device (a storage device having a non-transitory storage medium) such as a hard disk drive (HDD) or flash memory, or may be stored in a removable storage medium (a non-transitory storage medium) such as a DVD or CD-ROM, and installed by inserting the storage medium into a drive device. The storage unit 350 is, for example, a HDD, a flash memory, a RAM (Random Access Memory), etc. The storage unit 350 stores, for example, time-series data 350A and correction amount data 350B.

[0032] The data acquisition unit 310 acquires time-series data such as current values ​​when the removable battery 100 is charged or discharged from the battery exchange station 200, and stores the data as time-series data 350A in the storage unit 350. For clarity of explanation, in the following description of the present embodiment, the data acquisition unit 310 is assumed to acquire time-series data such as current values ​​when the removable battery 100 is charged, but the processing of the present invention can be similarly executed when the data acquisition unit 310 acquires time-series data such as current values ​​when the removable battery 100 is discharged.

[0033] Fig. 4 is a graph showing an example of the target current value when charging a removable battery 100. Fig. 4 shows an example of the target current value when a removable battery 100 is accommodated in one of multiple slots 210 in the battery exchange station 200 and is charged by the battery exchange station 200. As shown in Fig. 4, in this embodiment, the battery exchange station 200 charges the removable battery 100 by dividing the target current value into multiple stages. Hereinafter, the charging period based on the target current value of each stage will be referred to as a "Step."

[0034] For example, the battery exchange station 200 charges the removable battery 100 at a current value of 4 A from the start of charging of the removable battery 100 to time t1 (Step 1), charges the removable battery 100 at a current value of 3 A from time t1 to time t2 (Step 2), charges the removable battery 100 at a current value of 2 A from time t2 to time t3 (Step 3), and charges the removable battery 100 at a current value of 1 A from time t3 to time t4 (Step 4), thereby completing charging. In this way, by dividing the target current value for charging the removable battery 100 into multiple stages, charging at a fixed value for a certain period of time, collecting measurement data for each of the multiple stages, and performing machine learning, it is possible to more accurately estimate the offset error inherent in the measurement sensor 130 of each removable battery 100, as will be described later.

[0035] In this way, for each combination of multiple slots 210 and multiple removable batteries 100, when one of the multiple removable batteries 100 is accommodated in one of the multiple slots 210, the battery exchange station 200 divides the target current value into multiple levels and charges the removable battery 100. The measurement sensor 130 of the removable battery 100 measures the current value during charging and transmits it to the information processing device 300 via the battery exchange station 200. The data acquisition unit 310 acquires the current value measured in this way and stores it in the memory unit 350 as time-series data 350A.

[0036] Note that the number of steps and current values ​​shown in FIG. 4 are merely examples; the number of steps may be any number other than four, and the corresponding current values ​​may also be any value. Furthermore, in FIG. 4, the battery exchange station 200 starts charging from the highest current value (i.e., 4 A) and gradually reduces the current value, but the present invention is not limited to such a configuration and may charge the removable battery 100 at least with a target current value of one or more steps. For example, the battery exchange station 200 may start charging from the lowest current value and gradually increase the current value, or, as a modified example described below, may continuously change the charging current value. Furthermore, even when charging the removable battery 100 based on a single target current value, the regression analysis described below can be applied as is.

[0037] 5 is a diagram showing an example of time-series data 350A stored in the storage unit 350. The time-series data 350A is, for example, data IDs used as keys to associate information such as Step, battery ID, slot ID, measured current value, and timestamp. For example, in FIG. 5, data IDs 100 to 103 are data obtained when a removable battery 100 with a battery ID of B100 is accommodated in a slot 210 with a slot ID of S100, the battery exchange station 200 divides the magnitude of the target current value into multiple parts, charges the removable battery 100 in each of the periods of Step 1 to Step 4, and the measurement sensor 130 of the removable battery 100 measures the current value and transmits it to the information processing device 300 as the measured current value.

[0038] For the sake of simplicity, FIG. 5 illustrates a case in which the measurement sensor 130 measures one current value during each step period and transmits the measured current value to the information processing device 300. However, the measurement sensor 130 may measure multiple current values ​​during each step period and store them as time-series data 350A. The time-series data 350A is an example of "first information" in the claims. The battery ID is an example of "first identification information" in the claims. The slot ID is an example of "second identification information" in the claims. The current value associated with each step and stored is an example of "information satisfying a predetermined condition" in the claims.

[0039] The data processing unit 320 estimates the offset error inherent in the current value measured by the measurement sensor 130 of the removable battery 100 corresponding to each battery ID by performing machine learning using the measured current value included in the time-series data 350A as the dependent variable and the battery ID and slot ID included in the time-series data 350A as the explanatory variables. More specifically, in this embodiment, the data processing unit 320 estimates the offset error by performing regression analysis using the measured current value as the dependent variable and the battery ID and slot ID as the explanatory variables.

[0040] For example, if there are three removable batteries 100 corresponding to battery IDs B100-B102 and three slots corresponding to slot IDs S100-S102, the data processing unit 320 constructs a regression equation Z=α1×X1+α2×X2+α3×X3+α'1×Y1+α'2×Y2+α'3×Y3+C (1) using the measured current value as the objective variable Z and variables X1-X3 representing battery IDs B100-B102 and Y1-Y3 representing slot IDs S100-S102 as explanatory variables, and determines coefficients α1-α3 and α'1-α'3 so as to most accurately explain the battery ID, slot ID, and measured current value data of the time-series data 350A. In other words, the data processing unit 320 constructs a prediction model for predicting measured current value data based on the battery ID, slot ID, and measured current value data of the time-series data 350A. Here, coefficients α1 to α3 represent offset errors inherent to the measurement sensors 130 of each removable battery 100, coefficients α'1 to α'3 represent offset errors inherent to each slot 210, and C represents a constant (target current value corresponding to each step). Furthermore, variables X1 to X3 are 1 if they correspond to a battery ID in the record of the time-series data 350A, and 0 if they do not correspond to a battery ID. Similarly, variables Y1 to Y3 are 1 if they correspond to a slot ID in the record of the time-series data 350A, and 0 if they do not correspond to a slot ID. In other words, equation (1) estimates the error between the target current value and the measured current value by separating the degree of contribution of each removable battery 100 and slot 210.

[0041] 5, the battery ID of the record with data ID 100 for Step 1 is B100 and the slot ID is S100, so data processing unit 320 substitutes Z=4.2, X1=1, X2=X3=0, Y1=1, Y2=Y3=0, and C=4 into the regression equation Z=α1×X1+α2×X2+α3×X3+α'1×Y1+α'2×Y2+α'3×Y3+C to obtain 4.2=α1+α'1+4. Data processing unit 320 performs the above substitutions for each Step of time series data 350A and determines the optimal coefficients α1 to α3 and coefficients α'1 to α'3 for each Step by regression analysis. After determining the coefficient α for each step, the data processing unit 320 estimates the offset error (correction amount) inherently present in the measurement sensor 130 of each detachable battery 100 by, for example, averaging the coefficient α for each step.

[0042] FIG. 6 is a diagram illustrating an example of correction amount data 350B estimated by the data processing unit 320. The correction amount data 350B is, for example, a data set in which information such as estimated coefficients α, β, γ, and Δ for each step and a correction amount θ is associated with each other, using a battery ID as a key. For example, for battery ID 100 in FIG. 6, the data processing unit 320 determines a coefficient α1 for Step 1, a coefficient β1 for Step 2, a coefficient γ1 for Step 3, and a coefficient Δ1 for Step 4. Therefore, the data processing unit 320 determines the correction amount θ1 by θ1=(α1+β1+γ1+Δ1) / 4. Ideally, the values ​​of the coefficients α, β, γ, and Δ coincide with each other. However, deviations from the true values ​​occur in actual measurements due to various factors. Therefore, by determining the correction amount θ as the average value of these coefficients, the data processing unit 320 can more accurately calculate the correction amount θ. In this embodiment, as an example, the data processing unit 320 calculates the average value of each of the coefficients α, β, γ, and Δ, but the present invention is not limited to such a configuration, and when there are multiple target current values ​​(i.e., multiple steps), it is sufficient that the final correction amount θ is calculated taking into account at least the multiple coefficients calculated for each step.When there is only one target current value, it is sufficient to use the coefficient calculated for a single step as the final correction amount θ.

[0043] FIG. 7 is a diagram showing an example of how the estimated correction amount data 350B is used. After calculating the correction amount for each removable battery 100, the data processing unit 320 calculates a corrected current value by adding the correction amount to the measured current value when the measurement sensor 130 subsequently measures the current value of the removable battery 100. Here, "when the measurement sensor 130 measures the current value of the removable battery 100" does not necessarily mean the timing when the removable battery 100 is inserted into the slot 210, but also includes, for example, the timing when the removable battery 100 is attached to the electric vehicle 10 and the electric vehicle 10 is running. This is because the regression analysis described above is performed separately for the battery and the slot. By adding a correction value that takes into account only the offset error specific to the measurement sensor 130 of the removable battery 100 to the measured current value, the correction value can be used even when the removable battery 100 is not inserted into the slot 210. On the other hand, when the removable battery 100 is housed in the slot 210, the offset error α' that exists uniquely in each slot 210 can be added to the offset error θ that is unique to the measurement sensor 130 of the removable battery 100 to calculate the corrected current value.

[0044] The calculated correction amount can be used not only to correct the current value of the removable battery 100 measured at the present time, but also to correct the current value of the removable battery 100 measured at a past or future time. Also, for example, the calculated correction amount may be added to the current value data used in the regression analysis to correct the data.

[0045] After calculating the corrected current value, the data processing unit 320 outputs and stores the calculated corrected current value in the storage unit 350, where it can be used for various purposes. For example, as shown in Fig. 7, the information processing device 300 can use the corrected current value as new time-series data and apply the technology described in Patent Document 1 to estimate the SOH (state of health) of the removable battery 100 with higher accuracy.

[0046] [Processing flow] Next, the flow of processing executed by the information processing device 300 will be described with reference to Fig. 8. Fig. 8 is a flowchart showing an example of the flow of processing executed by the information processing device 300. The processing of the flowchart shown in Fig. 8 is executed, for example, when a certain removable battery 100 is accommodated in one of the multiple slots 210 present in the battery exchange station 200 and is charged by the battery exchange station 200.

[0047] First, the data acquisition unit 310 acquires time-series data of measured current values ​​from the removable battery 100 accommodated in the slot 210 (step S100). Next, the data processing unit 320 calculates the regression coefficients of the removable battery 100 and the slot as offset errors for each step based on the acquired time-series data of current values ​​(step S102). Here, it is assumed that there are multiple removable batteries 100 and multiple slots 210 in steps S100 and S102, but there may be at least one slot 210. In this case, multiple removable batteries 100 are accommodated in one slot 210 at different times, and time-series data of the current values ​​for each is acquired.

[0048] Next, the data processing unit 320 calculates the average value of the regression coefficients calculated for each step as the correction amount (step S104). Next, the data processing unit 320 acquires the current value of the removable battery 100 at a time point different from the time series data acquisition time (step S106). Next, the data processing unit 320 adds the correction amount to the acquired current value and outputs the corrected power value (step S108). This completes the processing of this flowchart.

[0049] In the above embodiment, an example has been described in which the secondary battery for which the offset error is to be estimated is the detachable battery 100 mounted on the electric vehicle 10. However, the present invention is not limited to such a configuration, and the detachable battery 100 may be a secondary battery that is fixedly mounted on the electric vehicle 10. In that case, the battery exchange station 200 may be, for example, a charging station for the electric vehicle 10.

[0050] According to the embodiment described above, time-series data of measured current values ​​is acquired from removable battery 100 accommodated in slot 210, machine learning is performed based on the acquired time-series data to calculate the offset error of removable battery 100 for each step, and a correction amount is calculated from the calculated offset error for each step. In other words, by estimating the offset error of the secondary battery, it is possible to estimate the state of the secondary battery with high accuracy.

[0051] [Variation 1] In the above embodiment, the battery exchange station 200 changes the current value in stages to charge the removable battery 100. In Modification 1, the battery exchange station 200 charges the removable battery 100 by continuously changing the current value, and the data acquisition unit 310 regards, for example, a predetermined section of the continuously changing target current value as a small section (i.e., a step) where the current is constant, and acquires the current value for each step.

[0052] Fig. 9 is a graph showing an example of current values ​​acquired during charging of removable battery 100 according to a modified example. As shown in Fig. 9, data acquisition unit 310 defines, for example, Step 1 as the period from the start of charging to time t1 when charging is performed at target current value C4, Step 2 as the period from time t1 to time t2 when charging is performed at target current value C3, Step 3 as the period from time t2 to time t3 when charging is performed at target current value C2, and Step 4 as the period from time t3 to time t4 when charging is performed at target current value C1.

[0053] Next, when the data acquisition unit 310 acquires the current value measured by the measurement sensor 130 of the removable battery 100, it classifies the current value into a Step according to the time point at which the current value was acquired. The data acquisition unit 310 then associates the acquired current value with the classified Step and stores it in the time-series data 350A. The subsequent processing by the data processing unit 320 is the same as in the embodiment. In this way, according to the first modification, the offset error of the removable battery 100 can be estimated even when the battery exchange station 200 charges the removable battery 100 by continuously changing the current value.

[0054] [Variation 2] Furthermore, in the above embodiment, a single correction value determined for each removable battery 100 is added to the measured current value, regardless of the magnitude of the current value, to calculate the corrected power value. However, more strictly speaking, the offset error to be corrected may change depending on the magnitude of the measured current value. In Modification 2, the data processing unit 320 changes the value of the correction amount to be added depending on the magnitude of the current value to be corrected.

[0055] FIG. 10 is a graph showing the relationship between the magnitude of the sensor current value and the error between the sensor current value and the true value according to Modification 2. As an example, FIG. 10 shows the relationship between the magnitude of the sensor current value measured by the measurement sensor 130 for a certain removable battery 100 and the error between the sensor current value and the true value. As shown in FIG. 10, the larger the sensor current value, the smaller the error from the true value tends to be. Therefore, the data processing unit 320 derives a regression line L that fits each data and corrects the measured current value according to the slope l of the derived regression line L. More specifically, the data processing unit 320 calculates the corrected power value by substituting the measured current value for X in the equation Y=lX+b (where b represents the estimated offset error). Modification 2 allows for more accurate correction of the offset error of the removable battery 100 by taking into account the magnitude of the measured current value.

[0056] In the above-described embodiment and modifications 1 and 2, an example has been described in which the offset error of the removable battery 100 is calculated with respect to a current measurement value. However, the present invention is not limited to such a configuration. By using data under a constant voltage condition, the current measurement value in the regression analysis described above can be converted into a voltage measurement value, and the offset error of the removable battery 100 can also be calculated. Similarly, by using data under a constant temperature condition, the offset error of the removable battery 100 can also be calculated with respect to a temperature measurement value. Similarly, the offset error of the removable battery 100 can also be calculated with respect to any physical quantity to be measured by the measurement sensor 130 of the removable battery 100.

[0057] The above-described embodiment can be expressed as follows.

[0058] a storage medium for storing computer-readable instructions; a processor connected to the storage medium; The processor executes the computer-readable instructions to: acquiring first information, which is information relating to charging or discharging of the plurality of power storage devices, transmitted from the plurality of power storage devices, and second information relating to charging or discharging of a first power storage device among the plurality of power storage devices; correcting the second information based on the first information, and outputting the corrected second information as third information; The information processing device is configured as follows.

[0059] The above describes the form for carrying out the present invention using an embodiment, but the present invention is not limited to such an embodiment, and various modifications and substitutions can be made within the scope that does not deviate from the gist of the present invention. [Explanation of symbols]

[0060] 100 Removable Battery 200 Battery Swap Stations 300 Information processing device 310 Data Acquisition Unit 320 Data Processing Unit 350 Storage section 350A Time Series Data 350B correction amount data

Claims

1. An information processing device that processes information related to a power storage device, an acquisition unit that acquires first information, which is information relating to charging or discharging of the plurality of power storage devices, transmitted from the plurality of power storage devices, and second information relating to charging or discharging of a first power storage device among the plurality of power storage devices; a processing unit that corrects the second information based on the first information and outputs the corrected second information as third information, the processing unit includes a first processing unit that calculates and outputs correction information, which is information regarding a correction amount specific to the first power storage device, based on the first information; a second processing unit that outputs the third information based on the correction information and the second information, the first processing unit calculates the correction information by constructing a prediction model that predicts measurement values ​​of physical quantities related to charging or discharging of the plurality of power storage devices included in the first information, based on first identification information that identifies each of the plurality of power storage devices and second identification information that identifies a power transfer device that transfers power between each of the plurality of power storage devices and the plurality of power storage devices, the prediction model being included in the first information. Information processing device.

2. The first information is stored in association with first identification information that identifies each of the plurality of power storage devices. The information processing device according to claim 1 .

3. the first information is information relating to charging or discharging performed by connecting a power transfer device that transfers power between each of the plurality of power storage devices and the power storage devices, and is information relating to charging or discharging performed between the plurality of power storage devices and the power transfer device, and / or information relating to charging or discharging performed between the plurality of power transfer devices and the power storage devices; The information processing device according to claim 1 .

4. The first information is stored in association with second identification information that identifies the power transfer device. The information processing device according to claim 3 .

5. the first information, the second information, and the third information include data on physical quantities related to charging or discharging of the power storage device; The information processing device according to claim 1 .

6. The physical quantity is a current or a voltage. The information processing device according to claim 5 .

7. The physical quantity is a current. The information processing device according to claim 6 .

8. the first processing unit calculates the correction information based on information included in the first information, in which physical quantities related to charging or discharging of the plurality of the power storage devices included in the first information satisfy a predetermined condition. The information processing device according to claim 1 .

9. An information processing method for processing information related to a power storage device, comprising: acquiring first information, which is information relating to charging or discharging of the plurality of power storage devices, transmitted from the plurality of power storage devices, and second information relating to charging or discharging of a first power storage device among the plurality of power storage devices; correcting the second information based on the first information and outputting the corrected second information as third information; the processing includes calculating and outputting correction information, which is information regarding a correction amount specific to the first power storage device, based on the first information, and outputting the third information based on the correction information and the second information; The calculation of the correction information is performed by constructing a prediction model that predicts measurement values ​​of physical quantities related to charging or discharging of the plurality of power storage devices included in the first information, based on first identification information that identifies each of the plurality of power storage devices and second identification information that identifies a power transfer device that transfers power between each of the plurality of power storage devices and the plurality of power storage devices, which are included in the first information. Information processing methods.

10. A program for processing information about a power storage device, the program being configured to: acquiring first information, which is information relating to charging or discharging of the plurality of power storage devices, transmitted from the plurality of power storage devices, and second information relating to charging or discharging of a first power storage device among the plurality of power storage devices; correcting the second information based on the first information and outputting the corrected second information as third information; the processing includes calculating and outputting correction information, which is information regarding a correction amount specific to the first power storage device, based on the first information, and outputting the third information based on the correction information and the second information; The calculation of the correction information is performed by constructing a prediction model that predicts measurement values ​​of physical quantities related to charging or discharging of the plurality of power storage devices included in the first information, based on first identification information that identifies each of the plurality of power storage devices and second identification information that identifies a power transfer device that transfers power between each of the plurality of power storage devices and the plurality of power storage devices, which are included in the first information. program.

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