Information processing apparatus, 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 apparatus, an information processing method, and a program.

Background Art

[0002] Conventionally, a technique for estimating an error related to measurement of the state of a secondary battery has been known. For example, in Patent Document 1, data with a small voltage change due to charge and discharge is filtered from time-series data related to the current and voltage of a secondary battery, and the error between the filtered data and the parameters of the OCV (open circuit voltage) curve is reduced, thereby optimizing the OCV curve.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems 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 the secondary battery from the measured data. Therefore, in the conventional technology, there are cases where it is impossible to estimate the measurement error (offset error) that inherently exists in a certain secondary battery compared to other secondary batteries. As a result, there are cases where the state estimation of the secondary battery cannot be performed with high accuracy.

[0005] The present invention has been made in consideration of such circumstances, and one of its objectives is to provide an information processing apparatus, an information processing method, and a program that can enable highly accurate state estimation of a secondary battery by estimating the offset error of the secondary battery.

Means for Solving the Problems

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

[0007] (1): An information processing apparatus according to one aspect of this invention is an information processing apparatus that processes information related to a power storage device, and includes an acquisition unit that acquires first information, which is information related to charging or discharging of a plurality of the power storage devices, transmitted from the plurality of the power storage devices, and second information related to charging or discharging of a first power storage device among the plurality of 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 aspect of (1) above, the first information is stored in association with first identification information for identifying each of the plurality of the power storage devices.

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

[0010] (4): In the aspect of (3) above, the first information is stored in association with second identification information for identifying the power receiving and transmitting device.

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

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

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

[0014] (8) In the aspects (1) to (7) above, 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, and a second processing unit that outputs the third information based on the correction information and the second information.

[0015] (9) In the aspect (8) above, 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 included in the first information and second identification information that identifies a power transmission and reception device that transmits and receives power to and from 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 in the first information in which the physical quantity satisfies a predetermined condition.

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

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

Advantages of the Invention

[0019] (1) to (12) According to the aspect, by estimating the offset error of the secondary battery, it is possible to enable highly accurate state estimation of the secondary battery.

Brief Description of the Drawings

[0020]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Figure 10

Mode for Carrying Out the Invention

[0021] Hereinafter, embodiments of the information processing apparatus, information processing method, and program of the present invention will be described with reference to the drawings.

[0022] <Overall Configuration of Battery Replacement System 1> FIG. 1 is a diagram showing an example of the overall configuration of the battery replacement system 1 according to the embodiment. The battery replacement system 1 includes, for example, a plurality of detachable batteries 100, a plurality of battery replacement stations 200, and an information processing device 300. The plurality of battery replacement stations 200 and the information processing device 300 can communicate with each other via a network NW. An electric vehicle 10 may be communicably 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), etc.

[0023] The battery replacement station 200 is a device that charges and replaces (returns, lends) the detachable battery 100, which is the drive source of the electric vehicle 10. The detachable battery 100 is detachably mounted on 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 the detachable battery 100. In the example of FIG. 1, a saddle-riding type electric vehicle (electric two-wheeler) 10-1 that travels by an electric motor driven by the electric power supplied by the power storage unit 120 (described later) of the detachable battery 100, and an in-vehicle riding type electric vehicle (electric four-wheeler) 10-2 are shown. For example, two detachable batteries 100 can be mounted on the electric vehicle 10-1 shown in FIG. 1, and three detachable batteries 100 can be mounted on the electric vehicle 10-2. Thus, the number of detachable batteries that can be mounted varies depending on the type, shape, etc. of the electric vehicle 10. Also, the detachable batteries that can be used may vary depending on the vehicle type.

[0025] [Detachable Battery 100] FIG. 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 and discharge current of the power storage unit 120, estimates the SOC (positive electrode OCP and negative electrode OCP) of the power storage unit 120, and so on. The BMU 110 causes the storage unit 140 to store the measurement results of the measurement sensor 130 as battery state information.

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

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

[0029] The storage unit 140 includes, for example, a non-volatile storage device such as a flash memory. The storage unit 140 stores the battery state information measured in time series. Further, a battery ID assigned to the detachable battery 100 may be stored in the storage unit 140.

[0030] When the detachable battery 100 is attached to the electric vehicle 10, the connection part 150 is electrically connected to a battery connection part (not shown) of the electric vehicle 10. Further, when the detachable battery 100 is housed in one of a plurality of slots 210 (an example of the "power receiving and transmitting device" in the claims) existing in the battery exchange station 200, the connection part 150 is electrically connected to the battery exchange station 200, and charges the power storage part 120 or discharges from the power storage part 120 by power reception and transmission with the battery exchange station 200. The connection part 150 further includes, for example, connection terminals of power lines (battery terminals) and connection terminals of communication lines, etc., and when electrically connected to the battery exchange station 200, transmits the time-series battery state information stored in the storage part 140 to the battery exchange station 200. The battery exchange station 200 transmits the received time-series battery state information to the information processing device 300. Further, 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 apparatus 300 that processes battery state information regarding the detachable battery 100 will be described. FIG. 3 is a diagram showing an example of the configuration of the information processing apparatus 300 according to the embodiment. The information processing apparatus 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, for example, by a hardware processor such as a CPU (Central Processing Unit) executing a program (software). Some or all of these components may be realized by hardware (including a circuit unit; circuitry) such as an LSI (Large Scale Integration), an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), or a GPU (Graphics Processing Unit), or may be realized by the cooperation of software and hardware. The program may be stored in advance in a storage device (a storage device including a non-transitory storage medium) such as an HDD (Hard Disk Drive) or a flash memory, or may be stored in a removable storage medium (a non-transitory storage medium) such as a DVD or a CD-ROM, and may be installed by mounting the storage medium on a drive device. The storage unit 350 is, for example, an HDD, a flash memory, a RAM (Random Access Memory), or the like. 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 during charging and discharging of the detachable battery 100 from the battery replacement station 200, and stores it in the storage unit 350 as the time-series data 350A. Hereinafter, in the present embodiment, for clarity of explanation, it is assumed that the data acquisition unit 310 acquires time-series data such as current values during charging of the detachable battery 100. However, the processing of the present invention can be executed in the same manner even when the data acquisition unit 310 acquires time-series data such as current values during discharging of the detachable battery 100.

[0033] FIG. 4 is a graph showing an example of a target current value when charging the detachable battery 100. FIG. 4 shows an example of a target current value when a certain detachable battery 100 is housed in one of a plurality of slots 210 in the battery replacement station 200 and charged by the battery replacement station 200. As shown in FIG. 4, in the present embodiment, the battery replacement station 200 charges the detachable battery 100 by dividing the target current value into magnitudes of a plurality of stages. Hereinafter, the charging period with the target current value of each stage is referred to as a Step.

[0034] For example, the battery replacement station 200 charges the detachable battery 100 with a current value of 4A during the period from the start of charging of the detachable battery 100 to time t1 (Step 1), and charges the detachable battery 100 with a current value of 3A during the period from time t1 to time t2 (Step 2), and charges the detachable battery 100 with a current value of 2A during the period from time t2 to time t3 (Step 3), and charges the detachable battery 100 with a current value of 1A during the period from time t3 to time t4 (Step 4), thereby completing the charging. In this way, by dividing the target current value for charging the detachable battery 100 into magnitudes of a plurality of stages, charging is performed at a fixed value for a certain period of time, and measurement data for each of the plurality of stages is collected and machine learning is performed, as will be described later, the offset error uniquely present in the measurement sensor 130 of each detachable battery 100 can be estimated more accurately.

[0035] In this way, for each combination of the plurality of slots 210 and the plurality of detachable batteries 100, when one of the plurality of detachable batteries 100 is housed in one of the plurality of slots 210, the battery replacement station 200 charges the detachable battery 100 by dividing the target current value into magnitudes of a plurality of stages. The measurement sensor 130 of the detachable battery 100 measures the current value during charging and transmits it to the information processing device 300 via the battery replacement station 200. The data acquisition unit 310 acquires the current value measured in this way and stores it in the storage unit 350 as time-series data 350A.

[0036] Note that the number of Steps and the current values shown in FIG. 4 are merely examples. The number of Steps may be any number other than 4, and the corresponding current values may also be any values. Further, in FIG. 4, the battery replacement station 200 starts charging from the highest current value (i.e., 4 A) and gradually reduces the current value. However, the present invention is not limited to such a configuration, and at least as long as the target current value charges the detachable battery 100 in one or more step sizes. For example, the battery replacement station 200 may start charging from the lowest current value and gradually increase the current value, or as described later as a modification, the current value to be charged may be continuously changed. Also, even when charging the detachable battery 100 based on one target current value, the regression analysis described later can be applied as it is.

[0037] FIG. 5 is a diagram showing an example of the time-series data 350A stored in the storage unit 350. The time-series data 350A is, for example, information such as Step, battery ID, slot ID, measured current value, and timestamp associated with a data ID as a key. For example, in FIG. 5, data IDs 100 to 103 are such that the detachable battery 100 with a battery ID of B100 is housed in the slot 210 with a slot ID of S100, and the battery replacement station 200 divides the magnitude of the target current value into a plurality of parts and charges the detachable battery 100 during the periods of Steps 1 to 4 respectively. The measurement sensor 130 of the detachable battery 100 measures the current value and transmits it to the information processing device 300 as the measured current value.

[0038] Note that, for the sake of simplicity of explanation, FIG. 5 shows the case where the measurement sensor 130 measures one current value during each Step and transmits it to the information processing apparatus 300. However, the measurement sensor 130 may measure a plurality of current values during each Step and store them as time-series data 350A. The time-series data 350A is an example of the "first information" in the claims. The battery ID is an example of the "first identification information" in the claims. The slot ID is an example of the "second identification information" in the claims. The current value stored in association with each Step is an example of the "information satisfying a predetermined condition" in the claims.

[0039] The data processing unit 320 performs machine learning with the measured current value included in the time-series data 350A as the target variable and the battery ID and slot ID included in the time-series data 350A as the explanatory variables, thereby estimating the offset error uniquely present in the measured current value by the measurement sensor 130 of the detachable battery 100 corresponding to each battery ID. More specifically, in the present embodiment, the data processing unit 320 estimates the offset error by performing regression analysis with the measured current value as the target variable and the battery ID and slot ID as the explanatory variables.

[0040] For example, when there are three detachable batteries 100 corresponding to battery IDs B100 to B102 and three slots corresponding to slot IDs S100 to S102, the data processing unit 320 uses the measured current value as the target variable Z, variables X1 to X3 representing battery IDs B100 to B102, and Y1 to Y3 representing slot IDs S100 to S102 as explanatory variables to construct a regression equation Z = α1×X1 + α2×X2 + α3×X3 + α’1×Y1 + α’2×Y2 + α’3×Y3 + C ··· Equation (1), and determines the coefficients α1 to α3 and coefficients α’1 to α’3 so as to most accurately explain the data of the battery ID, slot ID, and measured current value among the time-series data 350A. In other words, the data processing unit 320 constructs a prediction model for predicting the data of the measured current value based on the data of the battery ID, slot ID, and measured current value among the time-series data 350A. Here, the coefficients α1 to α3 represent the offset errors uniquely existing in the measurement sensor 130 of each detachable battery 100, the coefficients α’1 to α’3 represent the offset errors uniquely existing in each slot 210, and C represents a constant (the target current value corresponding to each step). Further, the variables X1 to X3 become 1 when corresponding to the battery ID in the record of the time-series data 350A, and become 0 when not corresponding to the battery ID. Similarly, the variables Y1 to Y3 become 1 when corresponding to the slot ID in the record of the time-series data 350A, and become 0 when not corresponding to the slot ID. That is, Equation (1) estimates the error between the target current value and the measured current value by separating the degrees of contribution of each detachable battery 100 and slot 210.

[0041] For example, in the case of the time-series data 350A shown in FIG. 5, since the battery ID of the record with the data ID 100 regarding Step 1 is B100 and the slot ID is S100, the data processing unit 320 substitutes Z = 4.2, X1 = 1, X2 = X3 = 0, Y1 = 1, Y2 = Y3 = 0, C = 4 into the regression formula 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. The data processing unit 320 performs the above substitution for each Step of the time-series data 350A, and determines the optimal coefficients α1 to α3 and the coefficients α’1 to α’3 for each Step by regression analysis respectively. When the data processing unit 320 determines the coefficient α for each Step, the data processing unit 320 estimates the offset error (correction amount) uniquely existing in the measurement sensor 130 of each detachable battery 100 by, for example, averaging the coefficients α of each Step.

[0042] FIG. 6 is a diagram showing an example of correction amount data 350B estimated by data processing unit 320. The correction amount data 350B is associated with information such as coefficients α, β, γ, Δ and correction amount θ estimated for each Step, for example, using the battery ID as a key. For example, with respect to battery ID 100 in FIG. 6, since data processing unit 320 determines coefficient α1 for Step 1, coefficient β1 for Step 2, coefficient γ1 for Step 3, and coefficient Δ1 for Step 4, data processing unit 320 determines correction amount θ1 as θ1 = (α1 + β1 + γ1 + Δ1) / 4. Although the values of the respective coefficients α, β, γ, Δ ideally coincide, due to various factors, a deviation from the true value occurs in actual measurement. Therefore, by determining correction amount θ as the average value of these coefficients, data processing unit 320 can calculate correction amount θ with higher precision. In the present embodiment, as an example, data processing unit 320 calculates the average value of the respective coefficients α, β, γ, Δ. However, the present invention is not limited to such a configuration. When there are a plurality of target current values (i.e., a plurality of Steps), it is sufficient that the final correction amount θ is calculated in consideration of at least the plurality of coefficients calculated for each Step. When there is one target current value, the coefficient calculated for a single Step may be used as the final correction amount θ as it is.

[0043] FIG. 7 is a diagram showing an example of the use of the estimated correction amount data 350B. When the data processing unit 320 calculates the correction amount for each detachable battery 100, for example, then when the measurement sensor 130 measures the current value of the detachable battery 100, the corrected current value is calculated by adding the correction amount to the measured current value. Here, "when the measurement sensor 130 measures the current value of the detachable battery 100" is not limited to the timing when the detachable battery 100 is housed in the slot 210, and includes, for example, the timing when the detachable battery 100 is mounted on the electric vehicle 10 and the electric vehicle 10 is running. This is because the above-described regression analysis is performed by distinguishing between the battery and the slot, so that a correction value considering only the offset error specific to the measurement sensor 130 of the detachable battery 100 is added to the measured current value, so that even when the detachable battery 100 is not housed in the slot 210, it can be used as a correction value. On the other hand, when the detachable battery 100 is housed in the slot 210, the corrected current value may be calculated by adding the offset error α' specific to each slot 210 in addition to the offset error θ specific to the measurement sensor 130 of the detachable battery 100.

[0044] Note that the use of the calculated correction amount is not limited to the correction of the current value of the detachable battery 100 measured at the current time point, and can also be used for the correction of the current value of the detachable battery 100 measured at a past or future time point. Further, for example, the calculated correction amount may be added to the data of the current value used in the regression analysis to correct the data.

[0045] When the data processing unit 320 calculates the corrected current value, the calculated corrected current value is output to and stored in the storage unit 350, and can be utilized 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, apply the technique described in Patent Document 1, and estimate the SOH (state of health) of the detachable battery 100 with higher accuracy.

[0046] [Flow of processing] Next, with reference to FIG. 8, the flow of processing executed by the information processing apparatus 300 will be described. FIG. 8 is a flowchart showing an example of the flow of processing executed by the information processing apparatus 300. The processing of the flowchart shown in FIG. 8 is executed, for example, at the timing when a certain detachable battery 100 is housed in one of a plurality of slots 210 in the battery replacement station 200 and charged by the battery replacement station 200.

[0047] First, the data acquisition unit 310 acquires time-series data of the measured current value from the detachable battery 100 housed in the slot 210 (step S100). Next, the data processing unit 320 calculates, as an offset error, the regression coefficient of the detachable battery 100 and the slot for each Step based on the acquired time-series data of the current value (step S102). Here, although it is assumed that there are a plurality of detachable batteries 100 and slots 210 in steps S100 and S102, the slot 210 may be at least one. In that case, for one slot 210, a plurality of detachable batteries 100 are housed at different timings, and time-series data of each current value is acquired.

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

[0049] In the above-described 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 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 the measured current value is acquired from the detachable battery 100 housed in the slot 210, and machine learning is performed based on the acquired time-series data to calculate the offset error of the detachable battery 100 for each Step, and a correction amount is calculated from the calculated offset error for each Step. That is, by estimating the offset error of the secondary battery, it is possible to perform highly accurate state estimation of the secondary battery.

[0051] [Modification Example 1] In the above-described embodiment, the battery exchange station 200 charges the detachable battery 100 by changing the current value step by step. In Modification Example 1, the battery exchange station 200 charges the detachable 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 minute section (that is, Step) in which the current is constant, and acquires the current value for each Step.

[0052] FIG. 9 is a graph showing an example of the current value acquired during charging of the detachable battery 100 according to the modification example. As shown in FIG. 9, the data acquisition unit 310 defines, for example, the period from the start of charging until time point t1, during which charging is performed with the target current value C4, as Step1, the period from time point t1 until time point t2, during which charging is performed with the target current value C3, as Step2, the period from time point t2 until time point t3, during which charging is performed with the target current value C2, as Step3, and the period from time point t3 until time point t4, during which charging is performed with the target current value C1, as Step4.

[0053] Next, when the data acquisition unit 310 acquires the current value measured by the measurement sensor 130 of the detachable battery 100, the data acquisition unit 310 classifies the current value into Steps according to the time point when the current value is acquired. After that, the data acquisition unit 310 stores the acquired current value in the time-series data 350A in association with the classified Step. The subsequent processing by the data processing unit 320 is the same as that in the embodiment. Thus, according to the first modification, even when the battery replacement station 200 continuously changes the current value to charge the detachable battery 100, the offset error of the detachable battery 100 can be estimated.

[0054] [Second Modification] Furthermore, in the above embodiment, the single correction value obtained for each detachable battery 100 is added to the measured current value regardless of the magnitude of the measured current value to calculate the corrected power value. However, more precisely, the offset error to be corrected may change according to the magnitude of the measured current value. In the second modification, the data processing unit 320 changes the value of the correction amount to be added according to 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 according to the second modification and the error between the sensor current value and the true value. FIG. 10 shows, as an example, the relationship between the magnitude of the sensor current value measured by the measurement sensor 130 for a certain detachable battery 100 and the error between the sensor current value and the true value. As shown in FIG. 10, generally, 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 formula Y = lX + b (where b represents the estimated offset error). According to the second modification, the offset error of the detachable battery 100 can be corrected more accurately in consideration of the magnitude of the measured current value.

[0056] In the above-described embodiments, Modifications 1 and 2, an example of obtaining the offset error of the detachable battery 100 with respect to the current measurement value has been described. However, the present invention is not limited to such a configuration, and by using data under constant voltage conditions, the current measurement value in the above-described regression analysis can be read as a voltage measurement value, and the offset error of the detachable battery 100 can also be obtained. Similarly, by using data under constant temperature conditions, the offset error of the detachable battery 100 can be obtained with respect to the temperature measurement value. Also similarly, the offset error of the detachable battery 100 can be obtained with respect to any physical quantity to be measured by the measurement sensor 130 of the detachable battery 100.

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

[0058] A storage medium storing computer-readable instructions, A processor connected to the storage medium, comprising: The processor, by executing the computer-readable instructions, Obtains first information, which is information regarding charging or discharging of a plurality of the power storage devices transmitted from the plurality of power storage devices, and second information regarding charging or discharging of a first power storage device among the plurality of power storage devices, Corrects the second information based on the first information, and outputs the corrected second information as third information. An information processing apparatus configured as described above.

[0059] As described above, the embodiments for carrying out the present invention have been described using the embodiments. However, the present invention is not limited to such embodiments, and various modifications and substitutions can be made without departing from the gist of the present invention.

Description of Reference Numerals

[0060] 100 Detachable battery 200 Battery replacement station 300 Information processing device 310 Data acquisition unit 320 Data processing unit 350 Storage unit 350A Time-series data 350B Correction amount data

Claims

1. An information processing apparatus that processes information related to a power storage device, an acquisition unit that acquires first information that is information related to charging or discharging of a plurality of the power storage devices, which is transmitted from the plurality of the power storage devices, and second information that is information related to charging or discharging of a first power storage device among the plurality of 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. Information processing apparatus.

2. The first information is stored in association with first identification information for identifying each of the plurality of the power storage devices. The information processing apparatus according to claim 1.

3. The first information is information related to charging or discharging performed when a power transmission and reception device that transmits and receives power to and from each of the plurality of the power storage devices is connected to the power storage device, and is information related to charging or discharging performed between the plurality of the power storage devices and the power transmission and reception device, and / or information related to charging or discharging performed between the plurality of the power transmission and reception devices and the power storage device. The information processing apparatus according to claim 1.

4. The first information is stored in association with second identification information for identifying the power transmission and reception device. The information processing apparatus according to claim 3.

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

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

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

8. The processing unit includes a first processing unit that calculates and outputs correction information, which is information related to a correction amount specific to the first power 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. The information processing apparatus according to any one of claims 1 to 7.

9. 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 the power storage devices included in the first information, based on the first identification information for identifying each of the plurality of the power storage devices and the second identification information for identifying the power transmission and reception device that transmits and receives power to and from each of the plurality of the power storage devices, which are included in the first information. The information processing apparatus according to claim 8.

10. ​ Based on information among the information included in the first information, where physical quantities related to charging or discharging of the plurality of power storage devices included in the first information satisfy a predetermined condition, the first processing unit calculates the correction information. The information processing apparatus according to claim 8.

11. An information processing method for processing information related to a power storage device, wherein a computer acquires first information, which is information related to charging or discharging of a plurality of the power storage devices transmitted from the plurality of power storage devices, and second information related to charging or discharging of a first power storage device among the plurality of power storage devices; corrects the second information based on the first information, and outputs the corrected second information as third information. Information processing method.

12. A program for processing information related to a power storage device, which causes a computer to acquire first information, which is information related to charging or discharging of a plurality of the power storage devices transmitted from the plurality of power storage devices, and second information related to charging or discharging of a first power storage device among the plurality of power storage devices; to correct the second information based on the first information, and to output the corrected second information as third information. Program.

Images