Information processing system

Abstract

To provide an information processing system capable of estimating the full-charge capacity of a power storage device early and with high accuracy.SOLUTION: An information processing system includes a control device that executes a capacity estimation process for estimating a full-charge capacity of a power storage device. The capacity estimation process is the process that estimates the full-charge capacity of the power storage device on the basis of a fitting curve of a Nyquist plot on which results of AC impedance measurement of the power storage device are plotted. An OCV-SOC curve of the power storage device in an initial-state in which an internal pressure of the power storage device is lower than a reference pressure includes a flat region and a steep region. The control device executes the capacity estimation process in a state where an OCV of the power storage device is within a first flat region when the internal pressure of the power storage device is lower than the reference pressure, and executes the capacity estimation process in a state where the OCV of the power storage device is within a second flat region when the internal pressure of the power storage device is higher than the reference pressure. The second flat region is narrower than the first flat region.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present disclosure relates to an information processing system. [Background technology]

[0002] Japanese Patent Application Laid-Open Publication No. 2019-192517 (Patent Document 1) discloses an information processing system that calculates the full charge capacity of a battery module using a Nyquist plot. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2019-192517 Summary of the Invention [Problem to be solved by the invention]

[0004] As described above, by using a Nyquist plot to determine the full charge capacity of a power storage device (e.g., a battery module), it is possible to determine the full charge capacity of the power storage device in a short time. However, the capacity estimation method described in Patent Document 1 leaves room for improvement in terms of the accuracy of estimating the full charge capacity. With this method, the accuracy of estimating the full charge capacity tends to decrease, especially when the power storage device deteriorates.

[0005] The present disclosure has been made to solve the above-mentioned problems, and has an object to provide an information processing system that can estimate the full charge capacity of a power storage device early and with high accuracy. [Means for solving the problem]

[0006] The information processing system according to the present disclosure includes a control device that executes a capacity estimation process to estimate the full charge capacity of a power storage device. The capacity estimation process is a process for estimating the full charge capacity of the power storage device based on a fitting curve of a Nyquist plot in which AC impedance measurement results of the power storage device are plotted. An OCV-SOC curve of the power storage device in an initial state in which the internal pressure of the power storage device is lower than a reference pressure includes a flat region in which the OCV change rate (=OCV increase / SOC increase), which is the ratio of the increase in OCV to the increase in SOC of the power storage device, is below a reference value, and a steep region in which the OCV change rate exceeds the reference value. When the internal pressure of the power storage device is lower than the reference pressure, the control device is configured to execute the capacity estimation process with the OCV of the power storage device in a first flat region, and when the internal pressure of the power storage device is higher than the reference pressure, to execute the capacity estimation process with the OCV of the power storage device in a second flat region. The second flat region is narrower than the first flat region. Note that OCV indicates open circuit voltage. SOC indicates state of charge.

[0007] When the internal pressure of the power storage device is higher than the reference pressure (e.g., in a deteriorated state), the OCV-SOC curve of the power storage device tends to deviate from the OCV-SOC curve of the power storage device in its initial state. However, in a power storage device such as a nickel-metal hydride battery, these OCV-SOC curves do not deviate over the entire flat region, but tend to deviate very little in a portion of the flat region (e.g., a low SOC region). Therefore, in the above configuration, when the internal pressure of the power storage device becomes higher than the reference pressure, the capacity estimation process is performed in a second flat region that is narrower than the first flat region. This makes it easier to estimate the full charge capacity of the power storage device with high accuracy. [Effects of the Invention]

[0008] According to the present disclosure, it is possible to provide an information processing system that can estimate the full charge capacity of a power storage device quickly and with high accuracy. [Brief explanation of the drawings]

[0009] [Figure 1] 1 is a diagram illustrating a configuration of an information processing system according to an embodiment of the present disclosure. [Figure 2] 4 is a flowchart showing a process for estimating the capacity of the power storage device according to the present embodiment. [Figure 3] 10 is a flowchart illustrating an example of a method for calculating the internal pressure of the power storage device. [Figure 4] FIG. 2 is a diagram for explaining an OCV-SOC curve of a power storage device. [Figure 5] 10A and 10B are diagrams for explaining a specific example of a capacity estimation process according to the present embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0010] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present disclosure will be described in detail with reference to the accompanying drawings. In the drawings, the same or corresponding parts are designated by the same reference numerals and their description will not be repeated.

[0011] FIG. 1 is a diagram illustrating the configuration of an information processing system 200 (hereinafter simply referred to as "system 200") according to this embodiment. System 200 estimates the full charge capacity of a module M, which can function as a power storage device, by measuring AC impedance. This method is also referred to as the "AC impedance method." Specifically, system 200 sequentially applies AC signals of frequencies within a predetermined range to module M and measures the response signals of module M at that time. System 200 then calculates the real and imaginary components of the impedance of module M based on the applied AC signals (applied signals) and the measured response signals, and discretely plots the calculation results on a complex plane. This complex impedance plot is called a "Nyquist plot." Analysis of the Nyquist plot allows evaluation of the characteristics of the battery module.

[0012] The full charge capacity of a power storage device can be calculated by discharging a fully charged power storage device to a fully discharged state. However, while this method can accurately calculate the full charge capacity, it takes a long time to charge and discharge the power storage device. Therefore, in situations where it is necessary to obtain the full charge capacities of a large number of power storage devices, there is room for improvement in the length of time required. In contrast, if the AC impedance method is used, the required time can be shortened because charging and discharging (large charging and discharging) of secondary batteries is not necessary. On the other hand, when the AC impedance method is used, it is necessary to improve the accuracy of estimating the full charge capacity of the power storage device. If the full charge capacity can be estimated with high accuracy, it will also be possible to accurately determine whether the power storage device can be reused.

[0013] In this embodiment, a battery 11 used in a vehicle 10 is removed from the vehicle 10, and a power storage unit constituting a part of the battery 11 is set in the system 200 as a module M. The vehicle 10 includes the battery 11, a battery management system (BMS) 11a that monitors the state of the battery 11, a communication device 12, and an electronic control unit (ECU) 50. The ECU 50 is, for example, a computer including a processor and a storage device. The ECU 50 wirelessly communicates with a mobile terminal 20 (user terminal) carried by a user of the vehicle 10 via the communication device 12.

[0014] The vehicle 10 is an electric vehicle configured to be able to run using power output from a battery 11. The battery 11 is a battery pack including a plurality of electrically connected cells 100. The cells 100 are secondary batteries. In this embodiment, each of the plurality of cells 100 is a nickel-metal hydride battery. More specifically, the positive electrode is nickel hydroxide (Ni(OH)2) to which a cobalt oxide additive has been added. The negative electrode is a hydrogen storage alloy (for example, a nickel-based alloy such as MmNi5). The electrolyte is potassium hydroxide (KOH).

[0015] The cell 100 includes an electrode assembly 101, a case 102, a gas release valve 103, and a tag 105. Note that FIG. 1 shows the electrode assembly 101 with a portion of the case 102 in perspective. The case 102 is, for example, a rectangular metal case (main body and lid). The lid may be sealed by welding the entire periphery of the opening of the case body. The case 102 contains the electrode assembly 101 and electrolyte, which constitute a nickel-metal hydride battery (NiMH). The electrode assembly 101 includes a positive electrode plate, a negative electrode plate, and an insulating separator. The electrode assembly 101 has, for example, a bipolar structure. A gas release valve 103 is provided on the top of the case 102. The gas release valve 103 opens when the pressure inside the case 102 exceeds a predetermined value (valve opening pressure), thereby releasing a portion of the gas inside the case 102 to the outside. However, the above is merely an example of a cell configuration, and the cell configuration is not limited to the above. For example, the electrode body 101 may have a monopolar structure. Furthermore, the type of secondary battery is not limited to a nickel-metal hydride battery, and other secondary batteries may also be used.

[0016] In this embodiment, at least one of the plurality of cells 100 included in the battery 11 is provided with a tag 105. For example, the plurality of cells 100 included in the battery 11 (e.g., 100 to 500 cells) are modularized into units of the number of cells (e.g., 10 to 50 cells), and a tag 105 is provided for each module. However, tags 105 may also be provided for all of the cells 100 included in the battery 11. The BMS 11a includes various sensors that detect the state of the battery 11 (e.g., voltage, current, and temperature), and outputs the detection results to the ECU 50. Each sensor included in the BMS 11a may be provided for each cell or for each module.

[0017] The tag 105 is provided, for example, on the outer surface of the case 102, and stores information in a readable and writable manner. The tag 105 functions as a non-volatile memory. The ECU 50 writes information to the tag 105 and erases information stored in the tag 105. The tag 105 may be a magnetic recording tag or an RFID (Radio Frequency IDentification) tag. The tag 105 stores information about the cell 100. The ECU 50 may write information to the tag 105 when acquiring new information about the cell 100. In this embodiment, the internal pressure of the cell 100 (pressure inside the case 102) is recorded in the tag 105 (see FIG. 3 described later). The information in the tag 105 is updated successively by the ECU 50.

[0018] The system 200 includes a voltage sensor 211, a reader 212, a charger / discharger 220, a measuring device 230, a curve storage device 240, a correlation storage device 250, a control device 260, and an HMI (Human Machine Interface) 270. The voltage sensor 211 detects the voltage of the module M and outputs the detection result to the control device 260. The reader 212 reads information (such as internal pressure information and model information, which will be described later) stored in the tag 105 of the module M and outputs the read information to the control device 260. The reading method of the reader 212 may be a contactless method or a contact method. The reader 212 may be fixed in a position where it can read information from the tag 105, or may be a movable reader controlled by the control device 260.

[0019] The charger / discharger 220 is configured to be able to charge and discharge the module M. The charger / discharger 220 has a power conversion circuit and charges or discharges the module M in accordance with a control command from the control device 260. The charger / discharger 220 may convert power supplied from a power source (not shown) into power suitable for the module M and use the converted power to charge the module M. The charger / discharger 220 may also convert power discharged from the module M into power suitable for a power load (not shown) and supply the converted power to the power load.

[0020] The measurement device 230 includes an oscillator 231, a potentiostat 232, a lock-in amplifier 233, and a plotting unit 234. As will be described in detail later, the measurement device 230 measures the AC impedance of the module M and outputs a Nike plot indicating the measurement results to the control device 260. The control device 260 has a built-in computer configured to be able to analyze the Nyquist plot of the module M. The control device 260 includes a processor 261 and a storage device 262. The storage device 262 is configured to be able to save stored information. The processor 261 executes programs stored in the storage device 262, thereby performing various processes. As will be described in detail later, the control device 260 analyzes the Nyquist plot of the module M using the information stored in the curve storage device 240 and the correlation storage device 250, and acquires information regarding the reuse of the module M (hereinafter also referred to as "reuse information").

[0021] The HMI 270 functions as an interface between the control device 260 and a user. The HMI 270 includes an input device and an output device (announcement device). The HMI 270 may include a touch panel display. The HMI 270 displays information specified by the control device 260 (e.g., reuse information).

[0022] 2 is a flowchart showing the process (including the capacity estimation process) for reusing module M. In the flowchart, "S" indicates a step. The process flow shown in FIG. 2 is started when, for example, a user inputs a start instruction into HMI 270 in system 200 in which module M is installed. However, the start conditions can be changed as appropriate.

[0023] 2, in S11, the control device 260 acquires the internal pressure and open circuit voltage (OCV) of the module M. The internal pressure of the module M is stored in the tag 105. Information indicating the internal pressure of the module M (internal pressure information) is calculated by the ECU 50 while the battery 11 (module M) is in use in the vehicle 10, and is stored in the tag 105. The control device 260 acquires the internal pressure information from the tag 105 via the reader 212.

[0024] The ECU 50 updates the internal pressure information in the tag 105 by repeatedly executing the processing flow shown in Fig. 3 while the battery 11 is being used in the vehicle 10. Fig. 3 is a flowchart showing an example of a method for calculating the internal pressure of the battery 11 (module M).

[0025] The ECU 50 estimates the pressure (internal pressure) inside the case 102 of a cell 100 (hereinafter referred to as a "target cell") in the battery 11 that has a tag 105 attached thereto, and stores the estimated value of the internal pressure in the corresponding tag 105. If the battery 11 includes multiple target cells, the ECU 50 executes the processing flow shown below in parallel for each of the multiple target cells.

[0026] Referring to FIG. 3, in S111, the ECU 50 acquires the current closed circuit voltage (CCV), current, and temperature of the target cell and saves each acquired data in a storage device. The CCV, current, and temperature of the target cell are detected by the BMS 11a. In S111, the ECU 50 also acquires the internal pressure P0. The internal pressure P0 is the internal pressure determined in the previous processing routine (the internal pressure calculated in S116, which will be described later). In S111 of the initial processing routine, the internal pressure P0 may be set to a predetermined value, or the value of the internal pressure P0 may be determined using a map, for example.

[0027] In S112, the ECU 50 calculates the current OCV of the target cell according to equation (1), such as "OCV = V + (I × R)." Equation (1) is information indicating the relationship between the current I (the charging side is negative), voltage V, internal resistance R, and open circuit voltage (OCV) of the target cell, and is stored in the storage device of the ECU 50. The ECU 50 may calculate the internal resistance R of the target cell from the temperature T of the target cell, for example, using map L10 shown in FIG. 3. As shown in map L10, the internal resistance R tends to decrease as the temperature T increases. Map L10 is information indicating the relationship between the temperature T and internal resistance R of the target cell, and is stored in the storage device of the ECU 50. The ECU 50 may periodically detect the current I and voltage V to correct map L10.

[0028] In S113, the ECU 50 estimates the amount of gas generated per unit time in the target cell (hereinafter referred to as "Gout") using the temperature acquired in S111 and the OCV acquired in S112. In this example, the cycle of the processing routine (the time from the previous execution of S113 to the current execution of S113) corresponds to the unit time. The ECU 50 estimates Gout from the temperature T and OCV using, for example, maps L21 and L22 shown in FIG. 3. In the maps L21 and L22, lines L21 and L22 indicate the relationship between OCV and Gout when the temperature T is 25°C and 45°C, respectively. As shown in the maps L21 and L22, Gout tends to increase as the OCV increases. Furthermore, Gout tends to increase as the temperature T increases. The maps L21 and L22 contain information indicating the relationship between the temperature T, OCV, and Gout of the target cell, and are stored in a storage device of the ECU 50.

[0029] In S114, the ECU 50 estimates the amount of gas absorbed per unit time in the target cell (hereinafter referred to as "Gin") using the temperature T and internal pressure P0 acquired in S111. In this example, the cycle of the processing routine (the time from the previous execution of S114 to the current execution of S114) corresponds to the unit time. The ECU 50 estimates Gin from the temperature T and internal pressure P0, for example, using maps L31 and L32 shown in FIG. 3. In the maps L31 and L32, lines L31 and L32 indicate the relationship between the internal pressure P0 and Gin when the temperature T is 25°C and 45°C, respectively. As shown in the maps L31 and L32, Gin tends to increase as the internal pressure P0 increases. Furthermore, Gin tends to increase as the temperature T increases. The maps L31 and L32 contain information indicating the relationship between the temperature T, internal pressure P0, and Gin of the target cell, and are stored in a storage device of the ECU 50.

[0030] In S115, the ECU 50 calculates ΔG expressed by equation (2) such as "ΔG=Gin-Gout." Equation (2) is an example of correspondence information indicating the relationship between Gin, Gout, and ΔG, and is stored in advance in a storage device of the ECU 50. The ECU 50 can obtain ΔG by subtracting Gout (i.e., the amount of gas generated per unit time) from Gin (i.e., the amount of gas absorbed per unit time). If Gin is greater than Gout, ΔG will be positive (+), and if Gin is less than Gout, ΔG will be negative (-).

[0031] In S116, the ECU 50 estimates the internal pressure P1 of the target cell according to equation (3) such as "P1 = P0 - ΔG." Equation (3) is information indicating the relationship between ΔG of the target cell, the internal pressure P0 (previous value), and the internal pressure P1 (current value), and is stored in the memory device of the ECU 50. ΔG corresponds to the amount of change in internal pressure per unit time. The ECU 50 stores the internal pressure P1 acquired in S116 in the memory device, distinguishing between the acquisition time. The ECU 50 can read out the current value (P1) and the previous value (P0) from the internal pressure data stored in the memory device. The internal pressure P1 acquired in S116 and stored in the memory device of the ECU 50 is referred to as "internal pressure P1" in the current processing routine and as "internal pressure P0" in the next processing routine.

[0032] In S117, ECU 50 writes internal pressure P1 (internal pressure of the target cell) to tag 105 provided in the target cell. This updates the internal pressure information in tag 105 to the latest information. After that, the process returns to the first step (S111). This ends the current processing routine, and the next processing routine begins.

[0033] When the battery 11 is removed from the vehicle 10, the latest internal pressure information is stored in the tag 105. Then, a portion of the battery 11 is set in the system 200 as a module M. A fixed reader 212 reads the internal pressure information from the tag 105 of the module M located at a predetermined position. If only one cell 100 in the module M has a tag 105, the movable reader 212 reads the internal pressure information from that tag 105. If multiple cells 100 included in the module M have tags 105, the movable reader 212 moves to read the internal pressure information from the tag 105 of each cell in turn. If the control device 260 acquires internal pressure information for only one cell 100, it regards the internal pressure of that cell as the internal pressure of the module M. If the control device 260 acquires internal pressure information for multiple cells 100, it regards the maximum value of the internal pressures of the cells as the internal pressure of the module M.

[0034] The method by which the system 200 (control device 260) acquires the internal pressure information is not limited to the above. For example, the control device 260 may acquire the internal pressure information from the vehicle 10 through communication by directly communicating (e.g., wirelessly communicating) with the vehicle 10 (ECU 50) without using the tag 105. Alternatively, the system 200 may include a device (internal pressure measuring device) that detects the internal pressure of the module M. The system 200 (control device 260) may estimate the internal pressure of the module M based on, for example, the degree of expansion of the case of the module M.

[0035] Referring again to FIG. 2, in S11, the control device 260 acquires the OCV of the module M in addition to the internal pressure of the module M. The control device 260, for example, places the module M in a predetermined state and acquires the OCV of the module M using the voltage sensor 211. For example, the voltage sensor 211 may detect the closed circuit voltage (CCV) of the module M after it has been left for a predetermined period of time (e.g., several tens of minutes or more) without being charged or discharged, thereby eliminating polarization. The voltage (CCV) detected for the module M in such a state indicates the OCV of the module M. However, the method for detecting the OCV is not limited to the above method, and other methods (publicly known OCV detection methods) may also be employed.

[0036] In S12, the control device 260 determines whether the internal pressure of the module M acquired in S11 is equal to or lower than a predetermined pressure (hereinafter referred to as the "reference pressure"). The reference pressure is a boundary pressure for determining whether the electrodes of the module M have deteriorated. If the internal pressure of the module M is higher than the reference pressure, it means that the electrodes of the module M have deteriorated.

[0037] If the internal pressure of module M is lower than the reference pressure (YES in S12), the state of module M is adjusted to be within the first flat region of the OCV-SOC curve. On the other hand, if the internal pressure of module M is higher than the reference pressure (NO in S12), the state of module M is adjusted to be within the second flat region of the OCV-SOC curve. FIG. 4 is a diagram for explaining the OCV-SOC curve. Note that SOC (State Of Charge) indicates the remaining amount of electricity stored, and is expressed as the ratio of the current amount of electricity stored to the amount of electricity stored in a fully charged state, for example, from 0 to 100%.

[0038] Line L1 in Figure 4 shows the OCV-SOC curve (horizontal axis: SOC, vertical axis: OCV) of module M (nickel-metal hydride battery) in the initial state. As shown in Figure 4, the OCV-SOC curve increases monotonically, and there is a one-to-one correspondence between OCV and SOC. The OCV-SOC curve is divided into a flat region and a steep region. The flat region is the SOC region and OCV region where the ratio of the increase in OCV to the increase in SOC of module M (hereinafter also referred to as the "OCV change rate") is below a reference value. On the other hand, the steep region is the SOC region and OCV region where the OCV change rate exceeds the reference value. With respect to line L1, the SOC region from S1 to S2 and the OCV region from V1 to V2 are both flat regions, while the other regions (SOC region and OCV region) are steep regions.

[0039] Power storage devices of the same type have similar OCV-SOC curves when the power storage devices are in an undegraded initial state (e.g., unused, brand new state). The type of power storage device can be identified, for example, by its model. Power storage devices of the same model also use the same materials for each element (electrodes, electrolyte, separator, etc.). Information indicating the flat and steep regions of the OCV-SOC curve of the module M in its initial state (hereinafter referred to as "OCV curve information") is stored, for example, in the curve storage device 240. The curve storage device 240 may store OCV curve information for multiple types of power storage devices. The control device 260 may acquire OCV curve information corresponding to the type (e.g., model) of the module M from the curve storage device 240. The control device 260 may read the model information of the module M from the tag 105. Alternatively, a user may input the model information of the module M to the control device 260 via the HMI 270. In this embodiment, the OCV-SOC curve of the module M in the initial state is line L1, and the OCV curve information of the module M includes S1, S2, V1, and V2.

[0040] When the internal pressure of the cell 100 increases due to gas generation within the case 102 of the cell 100, the positive and / or negative electrodes of the cell 100 are more likely to deteriorate. In the initial state, the OCV-SOC curve of the module M is line L1. However, as the positive and / or negative electrodes deteriorate and the internal resistance of the module M increases, the OCV-SOC curve of the module M changes to, for example, the curve shown by line L2 or L3. Comparing lines L1 to L3, the change in the OCV-SOC curve when the module M deteriorates is greater in the high SOC region. Lines L1 to L3 diverge in the high SOC region. On the other hand, lines L1 to L3 become almost identical in the low SOC region. In the example shown in FIG. 4, the degree of divergence between lines L1 to L3 in the SOC region higher than S3 and the OCV region higher than V3 is greater than the degree of divergence between lines L1 to L3 in the SOC region lower than S3 and the OCV region lower than V3. The degree of deviation can be expressed, for example, as the sum of squares of the errors. Regarding lines L1 to L3, V3 is located approximately halfway between V1 and V2 (close to the average value). V3 is the OCV value corresponding to S3 on line L1.

[0041] Referring again to FIG. 2, if the internal pressure of module M is equal to or lower than the reference pressure (YES in S12), control device 260 determines in S131 whether the OCV of module M acquired in S11 is within the first flat region. The first flat region in this embodiment is the flat region in the initial state (OCV region between V1 and V2). If the OCV of module M is not within the first flat region (NO in S131), control device 260 controls charge / discharge device 220 in S141 so that the OCV of module M approaches the first flat region. Control device 260 charges / discharges module M until the OCV of module M falls within the first flat region. Thereafter, the process proceeds to S21. On the other hand, if the OCV of module M is within the first flat region (YES in S131), the process skips S141 and proceeds to S21.

[0042] If the internal pressure of module M is higher than the reference pressure (NO in S12), the control device 260 determines in S132 whether the OCV of module M acquired in S11 is within a second flat region. The second flat region is a portion of the first flat region and is narrower than the first flat region. The second flat region is an OCV region that is equal to or greater than V1 and equal to or less than a region boundary value. The region boundary value is an OCV value that is higher than V1 and lower than V2. The control device 260 may use the aforementioned V3 (FIG. 4) as the region boundary value. V3 may be pre-stored in the curve storage device 240 along with the OCV curve information. However, this is not limited thereto, and the control device 260 may also determine the region boundary value using V1 and V2. The control device 260 may set the average value (fixed value) of V1 and V2 as the region boundary value. The control device 260 may also determine the region boundary value using the internal pressure of module M acquired in S11. The control device 260 may bring the region boundary value closer to V1 as the internal pressure of module M increases. The control device 260 may bring the region boundary value closer to V2 as the internal pressure of module M decreases. V1, V2, and the region boundary values ​​in this embodiment correspond to examples of the "first boundary value," "second boundary value," and "third boundary value" according to the present disclosure, respectively.

[0043] If the OCV of module M is not within the second plateau region (NO in S132), control device 260 controls charger / discharger 220 in S142 so that the OCV of module M approaches the second plateau region. Control device 260 charges and discharges module M until the OCV of module M is within the second plateau region. Thereafter, the process proceeds to S21. On the other hand, if the OCV of module M is within the second plateau region (YES in S132), the process skips S142 and proceeds to S21.

[0044] In S21, the control device 260 requests the measurement device 230 to measure the module M and acquires a Nyquist plot of the module M from the measurement device 230. In response to the request from the control device 260, the measurement device 230 acquires the Nyquist plot by measuring AC impedance. Specifically, the oscillator 231 outputs an in-phase sine wave to the potentiostat 232 and the lock-in amplifier 233. The potentiostat 232 generates an application signal by superimposing a predetermined DC voltage on an AC voltage (e.g., a voltage with an amplitude of approximately 10 mV) in-phase with the sine wave from the oscillator 231, and applies the generated application signal to the module M. The potentiostat 232 detects the current flowing through the module M and outputs the detection result to the lock-in amplifier 233 as a response signal from the module M. The potentiostat 232 also outputs the application signal and the response signal to the plotting unit 234. The potentiostat 232 may detect a voltage response when an AC current is applied to the module M.

[0045] The lock-in amplifier 233 compares the phase of the sine wave received from the oscillator 231 with the phase of the response signal detected by the potentiostat 232 and outputs the comparison result (the phase difference between the sine wave and the response signal) to the plotting unit 234. The plotting unit 234 plots the AC impedance measurement results of the module M on a complex plane based on the signal from the potentiostat 232 (a signal indicating the amplitude ratio between the applied signal and the response signal) and the signal from the lock-in amplifier 233 (a signal indicating the phase difference between the applied signal and the response signal). More specifically, the frequency of the sine wave output from the oscillator 231 is swept within a predetermined frequency range, and the potentiostat 232 and the lock-in amplifier 233 repeatedly perform the above-described processing. As a result, the AC impedance measurement results of the module M are plotted on a complex plane for each frequency of the sine wave, thereby obtaining a Nyquist plot of the module M (see plot D1 in FIG. 5, described later). The obtained Nyquist plot is output to the control device 260.

[0046] In the following S22, the control device 260 performs a fitting process (curve regression) of the impedance curve Z(M) of the module M, for example, by the nonlinear least squares method, so as to minimize the error with respect to the AC impedance of the module M (the measured value in S21). The impedance curve Z(M) is expressed by an equation using parameters of an equivalent circuit model that indicates the frequency characteristics of the AC impedance of the module M (more specifically, a plurality of circuit constants included in the model Mc shown in FIG. 5, which will be described later). In this embodiment, the impedance curve Z(M) expresses the composite impedance of the module M.

[0047] An impedance curve Z (initial impedance curve Z), in which initial values ​​are set for the circuit constants, is stored in the curve storage device 240. The curve storage device 240 outputs the initial impedance curve Z to the control device 260 in response to a request from the control device 260. Then, for each frequency of the applied signal, the control device 260 calculates the coordinates plotted at that frequency and the coordinates on the impedance curve Z corresponding to that frequency. The control device 260 calculates the square of the distance (error) between these coordinates for all frequencies of the applied signal and sums up the calculated values. The control device 260 calculates the sum of squares of the error and adjusts the values ​​of the circuit constants included in the equivalent circuit model so that this sum of squares of the error is minimized. When the circuit constants are adjusted in this way and converge to satisfy predetermined conditions, the impedance curve Z(M) is identified. The impedance curve Z(M) corresponds to a fitting curve.

[0048] 5 is a diagram for explaining the processes of S21 and S22. In FIG. 5, plot D1 is a Nyquist plot, curve D2 is an impedance curve Z(M), and model Mc is an equivalent circuit model of module M.

[0049] For plot D1 shown in Figure 5, the horizontal axis represents the real component Z of the complex impedance of module M. Re , the vertical axis is the imaginary component of the complex impedance of module M -Z Im Plot D1 is an example of the AC impedance measurement results when the frequency of the applied signal is swept in the range of 100 mHz to 1 kHz. In S21 of FIG. 2, the AC impedance measurement results of module M according to the frequency of the applied signal are plotted as discrete values ​​on a complex plane, thereby obtaining, for example, plot D1.

[0050] The circuit constants of the model Mc include junction inductance L, junction resistance R, solution resistance Rsol, charge transfer resistance Rct, diffusion resistance (CPE1), and electric double layer capacitance (CPE2). The diffusion resistance and electric double layer capacitance each correspond to a CPE (Constant Phase Element). The junction inductance L is the inductance component at the junction between the cells in the module M (the junction between the positive and negative electrodes). The junction resistance R is the resistance component at the junction. The solution resistance Rsol is the resistance component of the electrolyte present between the positive and negative electrodes. The charge transfer resistance Rct is the resistance component associated with charge transfer (exchange of charge) at the electrode / electrolyte interface (the surface of the positive and negative active materials). The diffusion resistance is the resistance component associated with the diffusion of salt in the electrolyte or charge transport material in the active materials. The electric double layer capacitance is the capacitance component of the electric double layer formed at the electrode / electrolyte interface. Each of these circuit constants is a combination of the corresponding components for all the cells in the module M.

[0051] As shown in Figure 5, the junction inductance L and the junction resistance R are connected in parallel. The solution resistance Rsol is connected in series to the parallel circuit of the junction inductance L and the junction resistance R. The charge transfer resistance Rct and the diffusion resistance are connected in series. The series circuit of the charge transfer resistance Rct and the diffusion resistance is connected in parallel to the electric double weight capacitance. Furthermore, the composite circuit including the junction inductance L, the junction resistance R, and the solution resistance Rsol is connected in series to the composite circuit including the charge transfer resistance Rct, the diffusion resistance, and the electric double weight capacitance.

[0052] In S22 of FIG. 2, a fitting process using the above circuit constants as fitting parameters identifies, for example, curve D2 as the impedance curve Z(M) corresponding to module M. The control device 260 may repeat the fitting process for the impedance curve Z, for which initial values ​​(predetermined values) of each circuit constant are set, until a predetermined convergence condition is met (until a value indicating the goodness of fit of the fitting process, such as a chi-squared value, falls below a judgment value). Then, when the convergence condition of the fitting process is met, the control device 260 may identify the impedance curve Z(M) from the circuit constants at the time of convergence. Note that the fitting algorithm is not limited to the least squares method, and other algorithms (for example, maximum likelihood estimation) may be used.

[0053] 2, after the control device 260 identifies the impedance curve Z(M) as described above, in S23, it extracts from the impedance curve Z(M) a specific feature value F(M) that has been confirmed to have a correlation with the full charge capacity Q(M). Such a feature value F(M) can be extracted from the impedance curve Z(M) by a statistical method such as multiple regression analysis.

[0054] In the following S24, the control device 260 calculates the full charge capacity Q(M) of the module M based on the feature F(M) extracted in S23. In detail, the correlation storage device 250 stores in advance the correlation between the feature F of the module and the full charge capacity Q as, for example, a relational expression, a map, or a table. The control device 260 refers to the correlation stored in the correlation storage device 250 and acquires the full charge capacity Q(M) of the module M from the feature F(M) of the module M.

[0055] In the next S25, the control device 260 acquires reuse information based on the full charge capacity Q(M) of the module M. The reuse information may indicate whether the module M can be used to rebuild an in-vehicle battery pack, or may indicate an application for which reuse of the module M is recommended (e.g., an application other than an in-vehicle application). The control device 260 may determine that the module M can be used to rebuild an assembled battery when the full charge capacity or capacity maintenance rate of the module M is equal to or greater than a predetermined determination value, and may determine that the module M cannot be used to rebuild an assembled battery when the full charge capacity or capacity maintenance rate of the module M is less than the determination value. The reuse information may indicate the value of the module M (e.g., the price at which the module M is sold for reuse).

[0056] Furthermore, in S25, the control device 260 causes the HMI 270 to display the reuse information. This allows a user of the system 200 (e.g., a worker preparing for reuse) to know what process should be performed on the module M. Furthermore, the control device 260 may transmit the reuse information to a user terminal (e.g., a mobile terminal 20) of the vehicle 10. The mobile terminal 20 (e.g., a smartphone or a wearable device) may display the reuse information received from the system 200. This allows the vehicle user to know the reuse state and / or residual value of the power storage device (module M) that they have used.

[0057] As described above, the method for estimating the capacity of a power storage device according to this embodiment includes the processes shown in FIG. 2. These processes are executed by the control device 260 of the system 200. The system 200 executes the capacity estimation process (FIG. 2) in a plateau region (first plateau region / second plateau region) corresponding to the state (before / after degradation) of the power storage device, thereby enabling early and highly accurate estimation of the full charge capacity of the power storage device. In addition to the control device 260, the measuring device 230 may also be provided with a computer, and the control device 260 and the measuring device 230 may cooperate to execute the processes shown in FIG. 2. In this embodiment, the processes are executed by one or more processors executing programs stored in one or more memories. However, these processes may also be executed by hardware (electronic circuits) alone, without using software. It is not essential that the lower limit value of the second plateau region be the same as the lower limit value of the first plateau region, V1, and the lower limit value of the second plateau region may be a value higher than V1. The configuration of the measuring device 230 is not limited to that shown in FIG. 1. For example, the measurement device 230 may include a frequency response analyzer instead of the lock-in amplifier 233 .

[0058] The method for creating a Nyquist plot is not limited to the above. For example, an applied signal (either a voltage signal or a current signal) containing various frequency components within a predetermined frequency range may be generated, a response signal (the other of the voltage signal and the current signal) when the applied signal is applied may be detected, and a fast Fourier transform (FFT) may be performed on each of the applied signal and the response signal to perform frequency resolution. Then, a Nyquist plot may be created by calculating the AC impedance for each frequency.

[0059] The vehicle is not limited to a passenger car, but may be a bus, a truck, a work vehicle (tractor, forklift, etc.), or an automated guided vehicle (AGV).

[0060] The embodiments disclosed herein should be considered to be illustrative in all respects and not restrictive. The scope of the present invention is defined by the claims, not by the description of the above embodiments, and is intended to include all modifications within the meaning and scope of the claims. [Explanation of symbols]

[0061] 10 Vehicle, 11 Battery, 200 Information Processing System, 230 Measuring Device, 260 Control Device, 50 ECU, M Module.

Claims

1. An information processing system including a control device that executes a capacity estimation process to estimate a full charge capacity of a power storage device, the capacity estimation process is a process of estimating a full charge capacity of the power storage device based on a fitting curve of a Nyquist plot in which AC impedance measurement results of the power storage device are plotted, an OCV-SOC curve of the power storage device in an initial state in which the internal pressure of the power storage device is lower than a reference pressure includes a flat region in which an OCV change rate, which is a ratio of an increase in OCV to an increase in SOC of the power storage device, is below a reference value, and a steep region in which the OCV change rate exceeds the reference value; the flat region includes a first flat region and a second flat region; the control device is configured to execute the capacity estimation process in a state where an OCV of the power storage device is within the first flat region when the internal pressure of the power storage device is lower than the reference pressure, and to execute the capacity estimation process in a state where an OCV of the power storage device is within the second flat region when the internal pressure of the power storage device is higher than the reference pressure, The information processing system, wherein the second flat area is narrower than the first flat area.

2. the first plateau region is an OCV region in the plateau region that is equal to or greater than a first boundary value and equal to or less than a second boundary value, the second plateau region is an OCV region in the plateau region that is equal to or greater than the first boundary value and equal to or less than a third boundary value, The information processing system according to claim 1 , wherein the third boundary value is lower than the second boundary value.

3. 3. The information processing system according to claim 2, wherein a degree of deviation between an OCV-SOC curve of the power storage device in the initial state and an OCV-SOC curve of the power storage device in a state in which the internal pressure of the power storage device is higher than the reference pressure is larger in an OCV region higher than the third boundary value than in an OCV region lower than the third boundary value.

4. the information processing system further includes a storage device that stores the first boundary value and the second boundary value; The information processing system according to claim 2 , wherein the control device is configured to determine the third boundary value using the first boundary value, the second boundary value, and an internal pressure of the power storage device.

5. the power storage device is a battery module including a plurality of nickel-metal hydride batteries, The information processing system includes: a charger / discharger configured to be able to charge and discharge the power storage device; a storage device that stores a correlation between a feature that can be extracted from the fitting curve and the full charge capacity; Furthermore, the control device is configured to control the charger / discharger so that the OCV of the power storage device is within the first flat region when the internal pressure of the power storage device is lower than the reference pressure and the OCV of the power storage device is within the steep region, and to control the charger / discharger so that the OCV of the power storage device is within the second flat region when the internal pressure of the power storage device is higher than the reference pressure and the OCV of the power storage device is within the steep region, 2. The information processing system according to claim 1, wherein the control device is configured to acquire the Nyquist plot by measuring AC impedance of the power storage device, acquire the fitting curve by performing a fitting process on the Nyquist plot, extract the feature amount from the fitting curve, and estimate the full charge capacity from the extracted feature amount by referring to the correlation stored in the storage device, when an OCV of the power storage device is in the first flat region or the second flat region.

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