Information processing apparatus, information processing method, and program

Abstract

To evaluate safety of an alkali ion secondary battery accurately in a shorter time.SOLUTION: An information processing apparatus 2 comprises: a differential value calculation unit 21 that calculates a differential value dV / dQ that is a ratio of an amount of change in a battery voltage V to an amount of change in a battery capacity Q of an alkali ion secondary battery 4; a function calculation unit 22 that calculates a function (Q-dV / dQ) indicating a relation between the battery capacity Q and the differential value dV / dQ; an index value calculation unit 23 that calculates, as an index value 36, at least one of a height Hp and a width Wp of a peak of at least one peak shape part of the function (Q-dV / dQ); and a determination unit 24 that specifies a direction of change of the index value 36 relative to a change of the number of charge-discharge cycles on the basis of the index value 36 calculated on the basis of measurement results in at least two conditions different from each other in the number of charge-discharge cycles, and determines the presence or absence of the risk of precipitation of alkali metal in the alkali ion secondary battery on the basis of the direction of change of the index value 36.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an information processing device, an information processing method, and a program, and, for example, to an information processing device, an information processing method, and a program for evaluating the future safety of a secondary battery. [Background technology]

[0002] In recent years, secondary batteries (hereinafter also referred to as "alkali ion secondary batteries") that charge and discharge through the movement of alkaline ions such as lithium ions and sodium ions have been adopted in a wide range of products, such as mobile devices such as smartphones and tablet terminals, electric vehicles, and stationary power storage devices.

[0003] It is generally known that the battery capacity of an alkali ion secondary battery decreases with repeated charging and discharging. Therefore, estimating the future usable period of an alkali ion secondary battery is important in determining the residual value or replacement timing of the alkali ion secondary battery. In addition, repeated charging and discharging may cause alkali metal to precipitate on the negative electrode of an alkali ion secondary battery, which is known to cause a rapid decrease in battery capacity and a decrease in safety.

[0004] For example, a conventional technique for predicting alkali metal precipitation in an alkali ion secondary battery is disclosed in Patent Document 1. Specifically, Patent Document 1 discloses predicting alkali metal precipitation based on a graph showing the relationship between the battery capacity Q of an alkali ion secondary battery and the differential value dV / dQ of the ratio of the amount of change dV in the battery voltage V to the amount of change dQ in the battery capacity Q.

[0005] It is generally known that the above graph has a waveform including a shape in which the differential value dV / dQ gradually increases as the battery capacity Q increases, and then gradually decreases again after the differential value dV / dQ reaches a peak value (hereinafter also referred to as the "peak shape portion").

[0006] Patent Document 1 discloses a method for estimating the width of the peak shape portion of the above graph, and determining that there is a high risk of alkali metal precipitation in the secondary battery when the estimated width is greater than a threshold value. [Prior art documents] [Patent documents]

[0007] [Patent Document 1] JP 2023-60840 A Summary of the Invention [Problem to be solved by the invention]

[0008] However, the method of Patent Document 1 may not be able to properly estimate the risk of alkali metal precipitation in an alkali ion secondary battery. That is, depending on the conditions of cycle operation of the alkali ion secondary battery, when the deterioration (reduction in battery capacity) of the alkali ion secondary battery progresses, alkali metal may precipitate even if the width of the peak shape part of the graph is smaller than a threshold value. In such a case, the method of Patent Document 1 cannot detect the risk of alkali metal precipitation in an alkali ion secondary battery in advance. Patent Document 1 also describes that it takes a long time (about 25 hours) to measure the battery capacity Q and battery voltage V of an alkali ion secondary battery from the discharge end region to the charge end region.

[0009] The present invention has been made in consideration of the above-mentioned problems, and has an object to make it possible to evaluate the safety of an alkali ion secondary battery accurately and in a shorter period of time. [Means for solving the problem]

[0010] An information processing device according to a representative embodiment of the present invention is characterized in that it comprises: a measurement result acquisition unit that acquires measurement results of a battery capacity of an alkali ion secondary battery, which is a secondary battery that can be charged and discharged by the movement of alkali ions, and a battery voltage, which is the voltage of the alkali ion secondary battery; a differential value calculation unit that calculates a differential value that is a ratio of an amount of change in the battery voltage to an amount of change in the battery capacity based on the measurement results; a function calculation unit that calculates a function that indicates the relationship between the battery capacity and the differential value; an index value calculation unit that calculates at least one of the height of an apex of at least one peak shape portion of the function and a width that indicates the degree of spread of the peak shape portion in a direction perpendicular to the height direction of the peak shape portion as an index value; and a determination unit that identifies a direction of change in the index value relative to a change in the number of charge and discharge cycles based on the index value calculated based on the measurement results under at least two conditions in which the number of charge and discharge cycles is different from each other, and determines whether or not there is a risk of alkali metal precipitation in the alkali ion secondary battery based on the direction of change in the index value. Effect of the Invention

[0011] According to the information processing device of the present invention, it is possible to evaluate the safety of an alkali ion secondary battery accurately and in a shorter period of time. [Brief description of the drawings]

[0012] [Figure 1] 1 is a diagram showing a functional block configuration of an information processing device according to an embodiment of the present invention; [Diagram 2] 1 is a diagram illustrating a hardware configuration of an information processing device according to an embodiment of the present invention. [Figure 3A] FIG. 1 is a graph showing the results of measuring the characteristics of battery voltage V versus battery capacity Q of an alkali ion secondary battery in which alkali metal deposition has occurred. [Figure 3B] FIG. 1 is a graph showing the measurement results of the characteristic of the differential value dV / dQ versus the battery capacity Q of an alkali ion secondary battery in which deposition of an alkali metal has occurred. [Figure 4A]FIG. 1 is a graph showing the measurement results of the characteristics of battery voltage V versus battery capacity Q of an alkali ion secondary battery in which no alkali metal deposition occurred. [Figure 4B] FIG. 13 is a graph showing the measurement results of the characteristic of the differential value dV / dQ versus the battery capacity Q of an alkali ion secondary battery in which no alkali metal deposition occurred. [Figure 5A] FIG. 1 is a diagram showing a linear function expressing the relationship between the battery capacity Q of an alkali ion secondary battery in which deposition of an alkali metal has occurred and the height Hp as an index value. [Figure 5B] FIG. 1 is a diagram showing a linear function expressing the relationship between the battery capacity Q of an alkali ion secondary battery in which deposition of an alkali metal has occurred and the width Wp as an index value. [Figure 6A] FIG. 1 is a diagram showing a linear function expressing the relationship between the battery capacity Q and the height Hp as an index value of an alkali ion secondary battery in which no alkali metal deposition occurred. [Figure 6B] FIG. 1 is a diagram showing a linear function expressing the relationship between the battery capacity Q and the width Wp as an index value of an alkali ion secondary battery in which no alkali metal deposition occurred. [Figure 7] 5 is a flowchart showing an example of a process flow for determining a risk of alkali metal precipitation in an alkali ion secondary battery, performed by an information processing device according to an embodiment. [Figure 8] 1 is a diagram showing a configuration of a distributed power system to which an information processing device according to an embodiment is applied; DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] 1. Overview of the embodiment First, a typical embodiment of the invention disclosed in this application will be outlined. In the following description, as an example, reference numerals in the drawings corresponding to components of the invention are given in parentheses.

[0014] [1] An information processing device (2) according to a representative embodiment of the present invention includes a measurement result acquisition unit (20) that acquires measurement results (31) of a battery capacity of an alkali ion secondary battery (4), which is a secondary battery capable of being charged and discharged by the movement of alkali ions, and a battery voltage that is the voltage of the alkali ion secondary battery, a differential value calculation unit (21) that calculates a differential value (dV / dQ) that is the ratio of an amount of change in the battery voltage to an amount of change in the battery capacity based on the measurement results, a function calculation unit (22) that calculates a function (Q-dV / dQ) that indicates the relationship between the battery capacity and the differential value, and a height (Hp and a width (Wp) indicating the extent of spread of the peak shape portion in a direction perpendicular to the height direction of the peak shape portion as an index value (36, 36_1 to 36_n); and a determination unit (24) specifying a direction of change in the index value relative to a change in the number of charge-discharge cycles based on the index values ​​(36_1 to 36_n) calculated based on the measurement results under at least two conditions having different numbers of charge-discharge cycles, and determining whether or not there is a risk of alkali metal precipitation in the alkali ion secondary battery based on the direction of change in the index value.

[0015] [2] In the information processing device described in [1] above, the judgment unit may determine that there is a risk of precipitation of the alkali metal when the height as the index value increases with an increase in the number of charge / discharge cycles.

[0016] [3] In the information processing device described in [1] or [2] above, the judgment unit may determine that there is a risk of precipitation of the alkali metal when the range as the index value decreases with an increase in the number of charge / discharge cycles.

[0017] [4] In the information processing device described in any one of [1] to [3] above, the judgment unit may determine a direction of change of the second index value relative to the first index value based on a first index value (36_1), which is the index value calculated based on the measurement result when the number of charge / discharge cycles is a predetermined value, and a second index value (36_n), which is the index value calculated based on the measurement result when the number of charge / discharge cycles is a value greater than the predetermined value.

[0018] [5] In the information processing device described in [4] above, the judgment unit may determine that there is a risk of precipitation of the alkali metal when the height as the second index value is larger than the height as the first index value.

[0019] [6] In the information processing device described in [4] above, the judgment unit may determine that there is a risk of precipitation of the alkali metal when the range as the second index value is smaller than the range as the first index value.

[0020] [7] In the information processing device described in [4] above, the judgment unit may determine that there is a risk of precipitation of the alkali metal when the height as the second index value is larger than the height as the first index value and the width as the second index value is smaller than the width as the first index value.

[0021] [8] In the information processing device described in any one of [1] to [7] above, the determination unit may identify a direction of change in the index value based on the polarity of a slope (αh, αw) of a linear function representing the relationship between the battery capacity and the index value.

[0022] [9] An information processing method according to a representative embodiment of the present invention includes a first step (S1) of acquiring measurement results of a battery capacity of an alkali ion secondary battery, which is a secondary battery capable of charging and discharging by the movement of alkali ions, and a battery voltage, which is the voltage of the alkali ion secondary battery; a second step (S2) of calculating a differential value, which is a ratio of an amount of change in the battery voltage to an amount of change in the battery capacity, based on the measurement results; a third step (S3) of calculating a function indicating the relationship between the battery capacity and the differential value; a fourth step (S4) of calculating an index value indicating at least one of the magnitudes of the height of an apex of a peak shape portion of the function and a width indicating the degree of spread of the peak shape portion in a direction perpendicular to the height direction of the peak shape portion; and a fifth step (S6 to S9) of identifying a direction of change in the index value relative to a change in the number of charge and discharge cycles based on the index value calculated based on the measurement results under at least two conditions having different numbers of charge and discharge cycles, and determining the presence or absence of a risk of alkali metal precipitation in the alkali ion secondary battery based on the direction of change in the index value.

[0023] 2. Specific examples of embodiments DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, specific examples of embodiments of the present invention will be described with reference to the drawings. In the following description, components common to the respective embodiments are designated by the same reference numerals, and repeated description will be omitted.

[0024] <Embodiment> FIG. 1 is a diagram showing a functional block configuration of an information processing device according to an embodiment of the present invention. FIG. 2 is a diagram showing a hardware configuration of an information processing device according to an embodiment of the present invention.

[0025] The information processing device 2 is a device having a function of determining the risk of alkali metal precipitation in an alkali ion secondary battery (also referred to as a "precipitation risk determination function"). Examples of the alkali ion secondary battery include a lithium ion battery and a sodium ion battery.

[0026] The information processing device 2 is realized by, for example, a program processing device (computer) such as a server or a personal computer (PC). The information processing device 2 executes data processing according to an installed program to determine whether or not there is a risk of alkali metal precipitation in the alkali ion secondary battery to be determined.

[0027] As shown in Fig. 1, the information processing device 2 includes, as functional blocks for realizing the precipitation risk assessment function, a measurement result acquisition unit 20, a differential value calculation unit 21, an index value calculation unit 23, a assessment unit 24, an output unit 25, and a storage unit 26. As will be described later, each of these functional blocks is realized by the hardware resources constituting the information processing device 2 shown in Fig. 2 working together with software (various programs including a program related to the precipitation risk assessment function) installed in the information processing device 2. The hardware configuration of the information processing device 2 will be described below.

[0028] As shown in FIG. 2, the information processing device 2 includes, as hardware resources, an arithmetic unit 101, a storage device 102, an input device 103, an I / F (Interface) device 104, an output device 105, and a bus 106, for example.

[0029] The arithmetic device 101 is composed of processors such as a CPU (Central Processing Unit) and a DSP (Digital Signal Processor). The storage device 102 has a storage area for storing a program 1021 for causing the arithmetic device 101 to execute various data processing operations and data 1022 used in the data processing operations by the arithmetic device 101, and is composed of, for example, a ROM (Read Only Memory), a RAM (Random Access Memory), a HDD, and a flash memory.

[0030] The program 1021 stored in the storage device 102 includes a program for realizing the basic functions of the information processing device 2, as well as a program for realizing a precipitation risk determination function of the information processing device 2. The program 1021 is pre-installed in the storage device 102, for example.

[0031] The data 1022 stored in the memory device 102 includes, for example, various parameters used for data processing by the calculation device 101, as well as the measurement results 31, differential values ​​34, functions 35, index values ​​36, and judgment results 39 described below.

[0032] The program 1021 and the data 1022 may be distributed via a network, or may be written to a non-transitory computer readable medium such as a CD-ROM or a memory card and distributed.

[0033] The input device 103 is a device that detects input of information from the outside, and examples of such devices include a keyboard, a mouse, a pointing device, a button, a touch panel, etc. The I / F device 104 is a device that transmits and receives data to and from the outside, and is composed of, for example, a communication control circuit, an input / output port, an antenna, etc. for performing wired or wireless communication.

[0034] The output device 105 is a device that outputs information obtained by data processing by the arithmetic device 101. Examples of the output device 105 include external storage devices such as SSDs and HDDs, and display devices such as LCDs (Liquid Crystal Displays) and organic EL (Electro Luminescence) displays. The bus 106 interconnects the arithmetic device 101, the storage device 102, the input device 103, the I / F device 104, and the output device 105, enabling data to be transmitted and received between these devices.

[0035] In the information processing device 2, the arithmetic device 101 executes calculations according to a program 1021 stored in the storage device 102, and controls the storage device 102, the input device 103, the I / F device 104, the output device 105, and the bus 106, thereby realizing each of the functional blocks of the information processing device 2 shown in Fig. 2 (the measurement result acquisition unit 20, the differential value calculation unit 21, the index value calculation unit 23, the determination unit 24, the output unit 25, and the storage unit 26). Each of the functional blocks of the information processing device 2 will be described in detail below.

[0036] The measurement result acquisition unit 20 is a functional unit for acquiring measurement results of physical quantities of the alkali ion secondary battery to be evaluated. The measurement result acquisition unit 20 acquires measurement results 31 including, for example, a measurement value 32 of the battery capacity Q of the alkali ion secondary battery to be evaluated and a measurement value 33 of the battery voltage V, which is the voltage of the alkali ion secondary battery to be evaluated.

[0037] The measured value 32 of the battery capacity Q and the measured value 33 of the battery voltage V are data measured, for example, by a capacity test of the alkaline ion secondary battery to be evaluated. For example, the measured value 32 of the battery capacity Q and the measured value 33 of the battery voltage V are data obtained by measuring the battery capacity Q and the battery voltage V of the alkaline ion secondary battery every unit time during at least one of charging and discharging the alkaline ion secondary battery.

[0038] The measurement result acquiring unit 20 acquires the measurement result 31 by communicating with an external device via a known network such as a LAN or a WAN. The measurement result acquiring unit 20 may also acquire the measurement result 31 by reading data from a storage medium such as a memory card connected to the information processing device 2 or an external storage device. The measurement result acquiring unit 20 may also acquire the measurement result 31 by reading the measurement result 31 from data stored in advance in the storage device 102 of the information processing device 2. The measurement result acquiring unit 20 stores the acquired measurement result 31 in the storage unit 26.

[0039] The differential value calculation unit 21 is a functional unit that calculates a differential value dV / dQ, which is a ratio of a change amount ΔV in the battery voltage V to a change amount ΔQ in the battery capacity Q, based on a measurement result 31. The differential value calculation unit 21 calculates the differential value dV / dQ based on, for example, a measured value 32 of the battery capacity Q per unit time and a measured value 33 of the battery voltage V. The differential value calculation unit 21 stores the calculated differential value dV / dQ in the storage unit 26.

[0040] The function calculation unit 22 is a functional unit that calculates a function (Q-dV / dQ) that indicates the relationship between the battery capacity Q and the differential value dV / dQ. Specifically, the function calculation unit 22 calculates the function (Q-dV / dQ) that indicates the relationship between the battery capacity Q and the differential value dV / dQ based on the measured value 32 of the battery capacity Q per unit time included in the measurement result 31 and the differential value dV / dQ per unit time calculated by the differential value calculation unit 21, and stores the function in the storage unit 26.

[0041] The index value calculation unit 23 is a functional unit that calculates an index value 36 that serves as an index for determining the risk of alkali metal precipitation in an alkali ion secondary battery.

[0042] In this embodiment, the index value 36 is at least one of the height Hp of the apex of at least one peak shape portion of a graph representing the function (Q-dV / dQ) and the width Wp indicating the degree of spread of the peak shape portion in a direction perpendicular to the height direction of the peak shape portion, as described below.

[0043] The index value calculation unit 23 calculates at least one of the height Hp and the width Wp based on the function 35 calculated by the function calculation unit 22, and stores it in the storage unit 26 as an index value 36.

[0044] The determination unit 24 is a functional unit that determines whether or not there is a risk of alkali metal precipitation in the alkali ion secondary battery to be determined. The determination unit 24 determines whether or not there is a risk of alkali metal precipitation in the alkali ion secondary battery to be determined, based on the index value 36 calculated by the index value calculation unit 23. A method for determining the risk of alkali metal precipitation will be described in detail below.

[0045] FIG. 3A is a graph showing the measurement results of the characteristics of battery voltage V versus battery capacity Q of an alkali ion secondary battery in which alkali metal deposition has occurred. FIG. 3B is a graph showing the measurement results of the characteristic of the differential value dV / dQ versus the battery capacity Q of an alkali ion secondary battery in which deposition of an alkali metal has occurred.

[0046] FIG. 4A is a graph showing the measurement results of the characteristics of battery voltage V versus battery capacity Q of an alkali ion secondary battery in which no alkali metal deposition occurred. FIG. 4B is a graph showing the measurement results of the characteristic of the differential value dV / dQ versus the battery capacity Q of an alkali ion secondary battery in which no alkali metal deposition occurred.

[0047] 3A and 3B, the alkali ion secondary battery in which alkali metal deposition occurred is also referred to as "battery A." In the explanations of Fig. 4A and 4B, the alkali ion secondary battery in which alkali metal deposition did not occur is also referred to as "battery B."

[0048] 3A, reference numeral 501A indicates a charging curve (graph) showing the change in battery voltage V versus battery capacity Q during charging immediately after starting operation of battery A (when new), and reference numeral 601A indicates a discharging curve (graph) showing the change in battery voltage V versus battery capacity Q during discharging immediately after starting operation of battery A. Reference numeral 502A indicates a charging curve showing the change in battery voltage V versus battery capacity Q during charging after 400 charge / discharge cycle tests (number of charge / discharge cycles=400), and reference numeral 602A indicates a discharging curve showing the change in battery voltage V versus battery capacity Q during discharging after 400 charge / discharge cycle tests of battery A. Reference numeral 503A indicates a charging curve showing the change in battery voltage V versus battery capacity Q during charging after 2000 charge / discharge cycle tests (number of charge / discharge cycles = 2000) were performed on battery A, and reference numeral 603A indicates a discharging curve showing the change in battery voltage V versus battery capacity Q during discharging after 2000 charge / discharge cycle tests were performed on battery A.

[0049] 3B, reference numeral 701A indicates a graph showing the change in the differential value dV / dQ calculated based on the charging curve 501A immediately after the start of operation of Battery A (when new) versus the battery capacity Q. Reference numeral 702A indicates a graph showing the change in the differential value dV / dQ calculated based on the charging curve 502A after 400 charge / discharge cycle tests of Battery A versus the battery capacity Q. Reference numeral 703A indicates a graph showing the change in the differential value dV / dQ calculated based on the charging curve 503A after 2000 charge / discharge cycle tests of Battery A versus the battery capacity Q.

[0050] In Fig. 3B, the graphs indicated by reference numerals 701A to 703A are enlarged ranges including one peak in the graphs showing the change in the differential value dV / dQ with respect to the battery capacity Q calculated based on the charging curves 501A to 503A shown in Fig. 3A. In addition, when calculating the differential value dV / dQ, noise processing such as data smoothing and resampling is performed. As a result, the position of the inflection point of the graph in Fig. 3A differs from the position of the peak of the graph in Fig. 3B, but the tendency (increase or decrease) of the peak in the dV / dQ direction is not affected.

[0051] 4A, reference numeral 501B indicates a charging curve (graph) showing the change in battery voltage V versus battery capacity Q during charging immediately after starting operation of battery B (new product), and reference numeral 601B indicates a discharging curve (graph) showing the change in battery voltage V versus battery capacity Q during discharging immediately after starting operation of battery B. Reference numeral 502B indicates a charging curve showing the change in battery voltage V versus battery capacity Q during charging after 400 charge / discharge cycle tests (number of charge / discharge cycles=400), and reference numeral 602B indicates a discharging curve showing the change in battery voltage V versus battery capacity Q during discharging after 400 charge / discharge cycle tests of battery B. Reference numeral 503B indicates a charging curve showing the change in battery voltage V versus battery capacity Q during charging after 2000 charge / discharge cycle tests (number of charge / discharge cycles = 2000) of battery B, and reference numeral 603B indicates a discharging curve showing the change in battery voltage V versus battery capacity Q during discharging after 2000 charge / discharge cycle tests of battery B.

[0052] 4B, reference numeral 701B indicates a graph showing the change in the differential value dV / dQ calculated based on the charging curve 501B immediately after the start of operation of battery B (brand new) versus the battery capacity Q. Reference numeral 702B indicates a graph showing the change in the differential value dV / dQ calculated based on the charging curve 502B after 400 charge / discharge cycle tests of battery B versus the battery capacity Q. Reference numeral 703B indicates a graph showing the change in the differential value dV / dQ calculated based on the charging curve 503B after 2000 charge / discharge cycle tests of battery B versus the battery capacity Q.

[0053] In Fig. 4B, the graphs indicated by reference numerals 701B to 703B are enlarged ranges including one peak in the graphs showing the change in the differential value dV / dQ with respect to the battery capacity Q, calculated based on the charging curves 501B to 503B shown in Fig. 4A. In addition, when calculating the differential value dV / dQ, noise processing such as data smoothing and resampling is performed. As a result, the position of the inflection point of the graph in Fig. 4A differs from the position of the peak of the graph in Fig. 4B, but the tendency (increase or decrease) of the peak in the dV / dQ direction is not affected.

[0054] 3A, for Battery A, an alkali ion secondary battery in which alkali metal precipitation has occurred, it can be seen that there are flat portions of the charge curve 503A and the discharge curve 603A after 2000 charge / discharge cycle tests in the ranges indicated by reference numerals 505 and 506. The occurrence of these flat portions indicates the occurrence of alkali metal precipitation.

[0055] 4A, for Battery B, an alkali ion secondary battery in which alkali metal precipitation did not occur, the flat portion does not exist in either the charge curve 503B or the discharge curve 603B after 2000 charge / discharge cycle tests. This also shows that alkali metal precipitation did not occur in Battery B.

[0056] As shown in FIG. 3B and FIG. 4B, the graph of the function (Q-dV / dQ) of an alkali ion secondary battery has a waveform that includes a peak-shaped portion.

[0057] The precipitation risk determination function according to the present embodiment focuses on the peak shape portion of the function (Q-dV / dQ). Specifically, it focuses on the change in the height Hp and width Wp of the peak shape portion with respect to the change in the number of charge / discharge cycles (battery capacity Q).

[0058] Here, the height Hp of the apex of the peak shape portion is, for example, the maximum differential value dV / dQ in one peak shape portion of the function (Q-dV / dQ), and the width Wp of the peak shape portion is, for example, the half-width (full width at half maximum or half width at half maximum) in one peak shape portion of the function (Q-dV / dQ).

[0059] As shown in Figure 3B, in Battery A, which is an alkali ion secondary battery in which alkali metal precipitation has occurred, it can be seen that the heights Hp1, Hp2, and Hp3 of the apexes of the peak-shaped portions tend to increase as the number of charge-discharge cycles increases (battery capacity Q decreases), and the widths Wp1, Wp2, and Wp3 of the peak-shaped portions tend to decrease as the number of charge-discharge cycles increases (battery capacity Q decreases).

[0060] On the other hand, as shown in Figure 4B, in Battery B, which is an alkali ion secondary battery in which no alkali metal precipitation occurred, it can be seen that the heights Hp1, Hp2, and Hp3 of the apexes of the peak-shaped portions tend to decrease as the number of charge-discharge cycles increases (battery capacity Q decreases), and the widths Wp1, Wp2, and Wp3 of the peak-shaped portions tend to increase as the number of charge-discharge cycles increases (battery capacity Q decreases).

[0061] Thus, in the future, the manner in which the height Hp and width Wp of the peak shape portion of the function (Q-dV / dQ) change with respect to the change in the number of charge-discharge cycles (battery capacity Q) will differ between an alkali ion secondary battery in which alkali metal precipitation occurs and an alkali ion secondary battery in which alkali metal precipitation does not occur.

[0062] Therefore, in the information processing device 2 of this embodiment, the judgment unit 24 identifies the direction of change in the index value 36 relative to the change in the number of charge / discharge cycles (battery capacity Q) based on the index value 36 measured under at least two conditions with different numbers of charge / discharge cycles, and judges the presence or absence of a risk of alkali metal precipitation in the alkali ion secondary battery based on the direction of change.

[0063] Specifically, the judgment unit 24 determines whether or not there is a risk of alkali metal precipitation in the alkali ion secondary battery by identifying the direction of change in at least one of the height Hp and width Wp of the apex of at least one peak shape portion of the function (Q-dV / dQ).

[0064] More specifically, the determination unit 24 determines that there is a risk of alkali metal precipitation when the height Hp as the index value 36 increases with respect to an increase in the number of charge / discharge cycles (a decrease in the battery capacity Q). Also, the determination unit 24 determines that there is a risk of alkali metal precipitation when the width Wp as the index value 36 decreases with respect to an increase in the number of charge / discharge cycles (a decrease in the battery capacity Q).

[0065] For example, the judgment unit 24 determines the direction of change of the second index value 36_n relative to the first index value 36_1 based on a first index value 36_1, which is an index value 36 calculated based on the measurement result 31 when the number of charge / discharge cycles of the alkali ion secondary battery is a predetermined value, and a second index value 36_n (n is an integer greater than or equal to 2), which is an index value 36 calculated based on the measurement result 31 when the number of charge / discharge cycles of the alkali ion secondary battery is a value greater than the predetermined value, and determines the presence or absence of a risk of alkali metal precipitation in the alkali ion secondary battery based on the determined direction of change.

[0066] Here, as the index value 36, at least one of the height Hp and width Wp of the apex of the peak shape portion in the function (Q-dV / dQ) can be used.

[0067] In the case of Figures 3B and 4B described above, the judgment unit 24 determines the direction of change of the second index value 36_n relative to the first index value 36_1, for example, based on the height Hp2 and width Wp2 which are the index value 36_1 when the number of charge / discharge cycles is 400, and the height Hp3 and width Wp3 which are the index value 36_n when the number of charge / discharge cycles is 2000.

[0068] For example, as shown in Fig. 3B, when the height Hp3 as the second index value 36_n is larger (rising) than the height Hp2 as the first index value 36_1, the determination unit 24 may determine that there is a risk of alkali metal precipitation. On the other hand, as shown in Fig. 4B, when the height Hp3 as the second index value 36_n is smaller (decreasing) than the height Hp2 as the first index value 36_1, the determination unit 24 may determine that there is no risk of alkali metal precipitation.

[0069] Also, for example, as shown in Fig. 3B, when the width Wp3 as the second index value 36_n is smaller (decreasing) than the width Wp2 as the first index value 36_1, the determination unit 24 may determine that there is a risk of alkali metal precipitation. On the other hand, as shown in Fig. 4B, when the width Wp3 as the second index value 36_n is larger (increasing) than the width Wp2 as the first index value 36_1, the determination unit 24 may determine that there is no risk of alkali metal precipitation.

[0070] Also, for example, as shown in Fig. 3B, when the height Hp3 as the second index value 36_n is larger than the height Hp2 as the first index value 36_1 and the width Wp3 as the second index value 36_n is smaller than the width Wp2 as the first index value 36_1, the determination unit 24 may determine that there is a risk of alkali metal precipitation. On the other hand, as shown in Fig. 4B, when the height Hp3 as the second index value 36_n is smaller than the height Hp2 as the first index value 36_1 and the width Wp3 as the second index value 36_n is larger than the width Wp2 as the first index value 36_1, the determination unit 24 may determine that there is no risk of alkali metal precipitation.

[0071] Furthermore, the determination unit 24 may identify the direction of change in the index value 36 based on the polarity of the gradient of a linear function that represents the relationship between the battery capacity Q and the index value 36 .

[0072] FIG. 5A is a diagram showing a linear function that expresses the relationship between the battery capacity Q of an alkali ion secondary battery (battery A) in which deposition of an alkali metal has occurred and the height Hp as the index value 36. As shown in FIG. FIG. 5B is a graph showing a linear function representing the relationship between the battery capacity Q and the width Wp as the index value 36 of an alkali ion secondary battery (battery A) in which deposition of an alkali metal has occurred.

[0073] FIG. 6A is a diagram showing a linear function expressing the relationship between the battery capacity Q and the height Hp as the index value 36 of an alkali ion secondary battery (battery B) in which no alkali metal deposition occurred. FIG. 6B is a graph showing a linear function representing the relationship between the battery capacity Q and the width Wp as the index value 36 of an alkali ion secondary battery (battery B) in which no alkali metal deposition occurred.

[0074] In Figures 5A and 6A, the horizontal axis represents the battery capacity Q, and the vertical axis represents the height Hp. In Figures 5B and 6B, the horizontal axis represents the battery capacity Q, and the vertical axis represents the width Wp.

[0075] The linear function 801A shown in Fig. 5A is obtained by performing regression analysis on the heights Hp1, Hp2, and Hp3 for each battery capacity Q shown in Fig. 3B. The linear function 802A shown in Fig. 5B is obtained by performing regression analysis on the widths Wp1, Wp2, and Wp3 for each battery capacity Q shown in Fig. 3B. The linear function 801B shown in Fig. 6A is obtained by performing regression analysis on the heights Hp1, Hp2, and Hp3 for each battery capacity Q shown in Fig. 4B. The linear function 802B shown in Fig. 6B is obtained by performing regression analysis on the widths Wp1, Wp2, and Wp3 for each battery capacity Q shown in Fig. 4B.

[0076] 5A and 5B, in the case of an alkali ion secondary battery in which alkali metal precipitation has occurred (battery A), the slope αh of linear function 801A expressing the relationship between battery capacity Q and height Hp is "negative," and the slope αw of linear function 802A expressing the relationship between battery capacity Q and width Wp is "positive." On the other hand, as shown in Figures 6A and 6B, in the case of an alkali ion secondary battery in which alkali metal precipitation has not occurred (battery B), the slope αh of linear function 801A expressing the relationship between battery capacity Q and height Hp is "positive," and the slope αw of linear function 802A expressing the relationship between battery capacity Q and width Wp is "negative."

[0077] Therefore, the judgment unit 24 may calculate the slope (αh, αw) of a linear function expressing the relationship between the battery capacity Q and the index value 36 based on the measurement results 31 and the index values ​​36_1 to 36_n (n is an integer greater than or equal to 2) under multiple conditions with different numbers of charge / discharge cycles, and determine the presence or absence of a risk of alkali metal precipitation in the alkali ion secondary battery by identifying the direction of change in the index value based on the polarity of the slope.

[0078] For example, as shown in Fig. 5A, when the slope of the linear function representing the relationship between the battery capacity Q and the height Hp is "negative," the determination unit 24 may determine that the height Hp changes in an increasing direction with respect to an increase in the number of charge / discharge cycles (a decrease in the battery capacity Q), and determine that there is a risk of alkali metal precipitation in the alkali ion secondary battery. On the other hand, as shown in Fig. 6A, when the slope of the linear function representing the relationship between the battery capacity Q and the height Hp is "positive," the determination unit 24 may determine that the height Hp changes in a decreasing direction with respect to an increase in the number of charge / discharge cycles (a decrease in the battery capacity Q), and determine that there is no risk of alkali metal precipitation in the alkali ion secondary battery.

[0079] Also, for example, as shown in Fig. 5B, when the slope of the linear function expressing the relationship between the battery capacity Q and the width Wp is "positive", the determination unit 24 may determine that the width Wp changes in a direction to become smaller with an increase in the number of charge / discharge cycles (a decrease in the battery capacity Q) and determine that there is a risk of alkali metal precipitation in the alkali ion secondary battery. On the other hand, as shown in Fig. 6B, when the slope of the linear function expressing the relationship between the battery capacity Q and the width Wp is "negative", the determination unit 24 may determine that the width Wp changes in a direction to become larger with an increase in the number of charge / discharge cycles (a decrease in the battery capacity Q) and determine that there is no risk of alkali metal precipitation in the alkali ion secondary battery.

[0080] Also, for example, when the slope of the linear function representing the relationship between the battery capacity Q and the height Hp is "negative" and the slope of the linear function representing the relationship between the battery capacity Q and the width Wp is "positive," the determination unit 24 may determine that there is a risk of alkali metal precipitation in the alkali ion secondary battery. On the other hand, as shown in Fig. 6A, when the slope of the linear function representing the relationship between the battery capacity Q and the height Hp is "positive" and the slope of the linear function representing the relationship between the battery capacity Q and the width Wp is "negative," the determination unit 24 may determine that there is no risk of alkali metal precipitation in the alkali ion secondary battery.

[0081] The determination unit 24 stores in the memory unit 26 a determination result 39 indicating whether or not there is a risk of alkali metal precipitation in the alkali ion secondary battery, determined by the above-mentioned method.

[0082] The output unit 25 is a functional unit that outputs the determination result 39. For example, when the determination unit 24 determines that there is a risk of alkali metal precipitation, the output unit 25 outputs the determination result 39 to the outside. For example, the output unit 25 may output the determination result 39 to an external information processing device connected to the information processing device 2 by wire or wirelessly, or may display the determination result 39 on a screen of a display device (e.g., a liquid crystal display, etc.) connected to the information processing device 2.

[0083] Next, a process flow for determining the risk of alkali metal precipitation in an alkali ion secondary battery by the information processing device 2 will be described.

[0084] FIG. 7 is a flowchart showing an example of a process flow for determining the risk of alkali metal precipitation in an alkali ion secondary battery, performed by the information processing device 2 according to the present embodiment.

[0085] First, the information processing device 2 acquires, by the measurement result acquisition unit 20, the measurement result 31 including the measurement value 32 of the battery capacity Q and the measurement value 33 of the battery voltage V of the alkali ion secondary battery to be determined (step S1). Next, in the information processing device 2, the differential value calculation unit 21 calculates the differential value dV / dQ, which is the ratio of the amount of change in the battery voltage V to the amount of change in the battery capacity Q, based on the measurement result 31 acquired in step S1 by the above-mentioned method (step S2). Next, in the information processing device 2, the function calculation unit 22 calculates the function (Q-dV / dQ) based on the measurement result 31 acquired in step S1 and the differential value dV / dQ calculated in step S1 by the above-mentioned method (step S3).

[0086] Next, in the information processing device 2, the index value calculation unit 23 calculates the index value 36 (at least one of the height Hp and the width Wp) based on the function (Q-dV / dQ) by the above-mentioned method (step S4). Next, the information processing device 2 determines whether or not the index value 36 has been calculated under at least two conditions with different numbers of charge / discharge cycles (step S5). If the index value 36 has not been calculated under at least two conditions with different numbers of charge / discharge cycles (step S5: NO), the information processing device 2 executes the processes of steps S1 to S5 again.

[0087] On the other hand, when the index value 36 has been calculated under at least two conditions with different numbers of charge / discharge cycles (step S5: YES), the determination unit 24 in the information processing device 2 identifies the direction of change in the index value 36 relative to the change in the number of charge / discharge cycles (battery capacity Q) (step S6). Specifically, as described above, the determination unit 24 identifies the direction of change in at least one of the height Hp and the width Wp relative to the change in the number of charge / discharge cycles (battery capacity Q).

[0088] Next, the determination unit 24 determines whether or not the height Hp (the width Wp) is increasing with respect to an increase in the number of charge / discharge cycles (a decrease in the battery capacity Q) (step S7). If the height Hp is increasing (the width Wp is decreasing) with respect to an increase in the number of charge / discharge cycles (a decrease in the battery capacity Q) (step S7: YES), the determination unit 24 determines that there is a risk of alkali metal precipitation in the alkali ion secondary battery being determined (step S8). In this case, the output unit 25 outputs the determination result 39 by the determination unit 24.

[0089] On the other hand, if the height Hp decreases (the width Wp increases) with respect to an increase in the number of charge / discharge cycles (a decrease in the battery capacity Q) (step S7: NO), the determination unit 24 determines that there is no risk of alkali metal precipitation in the alkali ion secondary battery being determined (step S9). In this case, the output unit 25 may or may not output the determination result 39 by the determination unit 24.

[0090] In step S6, the determination unit 24 may specify the polarity of the slope (αh, αw) of the linear function expressing the relationship between the battery capacity Q and the index value 36 (at least one of the height Hp and the width Wp), as described above. In this case, in step S7, the determination unit 24 may determine the presence or absence of a risk of alkali metal precipitation in the alkali ion secondary battery based on the polarity of the slope, as described above.

[0091] Next, an application example of the information processing device 2 having a precipitation risk determination function will be described.

[0092] FIG. 8 is a diagram showing a configuration of a distributed power system 100 to which an information processing device 2 according to an embodiment is applied.

[0093] A distributed power supply system 100 shown in FIG. 8 is a system in which distributed power supplies such as photovoltaic power generation facilities and power storage facilities are connected to a power grid.

[0094] The distributed power system 100 includes a plurality of consumer facilities 1, an information processing device 2, and a power distribution line 9. The power distribution line 9 receives power from a substation (not shown), and is connected to the plurality of consumer facilities 1 and a large-scale power source (not shown).

[0095] Each consumer facility 1 is capable of receiving power from a distribution line 9 and supplying power to the distribution line 9. Examples of consumer facilities 1 include general consumer facilities equipped with household solar power generation facilities and storage batteries, and high-voltage private consumer facilities such as mega solar power plants.

[0096] Each customer facility 1 includes, for example, a distributed power source 10, a power control device (PCS) 5, a distribution board 6, a load 7, and a control device 8.

[0097] The distributed power source 10 includes, for example, a photovoltaic power generation facility (PV) 3 and a storage battery 4. The photovoltaic power generation facility 3 is a device that generates DC power based on light energy. The storage battery 4 is an alkaline ion secondary battery. The storage battery 4 is capable of storing, for example, power generated by the photovoltaic power generation facility 3. Note that the distributed power source 10 is only required to include at least the storage battery 4, and is not necessarily required to include the photovoltaic power generation facility 3.

[0098] The power control device 5 is a power conditioning system (PCS). Hereinafter, the power control device 5 is also referred to as "PCS 5." The PCS 5 includes hardware resources such as a DC / DC converter, an AC / DC converter, various switch circuits, a program processing device such as a microcontroller, and a communication device.

[0099] The PCS 5 controls the DC power output from the distributed power sources 10 (the photovoltaic power generation equipment 3 and the storage battery 4), and also converts the DC power into AC power and controls the supply of the AC power to the power system (distribution line 9) via the distribution board 6. The PCS 5 also converts the AC power supplied from the power system (distribution line 9) via the distribution board 6 into DC power and supplies the DC power to the storage battery 4.

[0100] The distribution board 6 is connected to the distribution line 9. For example, the distribution board 6 is connected to the distribution line 9 via a service line connected to the secondary side of a pole transformer (not shown) whose primary side is connected to the distribution line 9. The distribution board 6 supplies the power supplied from the distribution line 9 via the pole transformer to the load 7 and also to the PCS 5. The distribution board 6 also supplies the power supplied from the distributed power source 10 via the PCS 5 to the distribution line 9 via the pole transformer.

[0101] The load 7 is a device that operates based on the power supplied via the distribution board 6.

[0102] The control device 8 is a device that performs comprehensive monitoring and control of the entire customer facility 1. The control device 8 is configured to include, for example, a data processing device having a processor such as a CPU (Central Processing Unit), a storage device such as a RAM (Random Access Memory) and a ROM (Read Only Memory), and a peripheral circuit such as an I / F circuit.

[0103] The control device 8 is capable of communicating with the information processing device 2 as an external server via a communication network 11. Examples of the communication network 11 include various wireless communication networks such as a wireless LAN, and various wired communication networks such as optical communication using optical fibers and power line communication (PLC).

[0104] For example, the control device 8 has a function as a BMU (Battery Management Unit) that sequentially acquires physical quantities measured by a voltage sensor and a current sensor (not shown) connected to the storage battery 4 and monitors the state of the storage battery 4 based on the physical quantities. The control device 8 measures, for example, the battery voltage V and battery capacity Q of the storage battery 4 every unit time when charging and discharging the storage battery 4, stores the measurement results 31 in a storage device within the PCS 5, and transmits them to the information processing device 2 via the communication network 11.

[0105] In addition, the control device 8 has a function of controlling the charge and discharge of the storage battery 4 by controlling the PCS 5. For example, the control device 8 controls the charge and discharge of the storage battery 4 by driving the PCS 5 based on the monitoring results of the physical quantities of the storage battery 4.

[0106] The information processing device 2 is an external server that performs overall control of the entire distributed power system 100, and monitors the status of the power system and each of the customer facilities 1. The information processing device 2 is installed, for example, at a location different from the location where the customer facilities 1 are installed, and communicates with the control device 8 in each of the customer facilities 1 via a communication network 11.

[0107] The information processing device 2 has the above-mentioned precipitation risk determination function according to this embodiment. The information processing device 2 acquires measurement results 31 of the battery voltage V and battery capacity Q during charging and discharging of the storage battery 4 by communicating with the control device 8 in each consumer facility 1 via the communication network 11. The information processing device 2 determines the presence or absence of a risk of alkali metal precipitation in the storage battery 4 by the above-mentioned method based on the measurement results 31 of the battery voltage V and battery capacity Q acquired from the PCS 5.

[0108] When the information processing device 2 determines that there is a risk of alkali metal precipitation in the storage battery 4, for example, it transmits information indicating a warning regarding the storage battery 4 to the control device 8 via the communication network 11. The control device 8 displays the warning regarding the storage battery 4 on a monitor for displaying information provided in the distributed power source 10, for example.

[0109] In this way, the external server that monitors and controls each consumer facility 1 of the distributed power system 100 can be provided with the precipitation risk determination function according to this embodiment. This makes it possible to monitor the state of the storage battery 4 in each consumer facility 1 by the external server, while also determining the risk of alkali metal precipitation in the storage battery 4.

[0110] Furthermore, the control device 8 of each consumer facility 1 may be provided with the precipitation risk determination function according to the present embodiment. This allows the load of data processing required for determining the risk of alkali metal precipitation in the storage battery 4 to be distributed to the control device 8 of each consumer facility 1, thereby making it possible to reduce the data processing load on the external server compared to a case in which the external server is provided with the precipitation risk determination function.

[0111] As described above, the information processing device 2 according to the embodiment calculates the differential value dV / dQ, which is the ratio of the change in the battery voltage V to the change in the battery capacity Q, based on the measurement results 31 of the battery capacity Q and the battery voltage V of the alkali ion secondary battery, and calculates a function (Q-dV / dQ) showing the relationship between the battery capacity Q and the differential value dV / dQ. As described above, the information processing device 2 calculates at least one of the height Hp of the apex of at least one peak shape portion and the width Wp of the peak shape portion of the function (Q-dV / dQ) as an index value 36. Then, the information processing device 2 specifies the direction of change in the index value 36 relative to the change in the number of charge / discharge cycles (battery capacity Q) based on the index value 36 calculated based on the measurement results 31 under at least two conditions in which the number of charge / discharge cycles is different from each other, as described above, and determines the presence or absence of a risk of alkali metal precipitation in the alkali ion secondary battery based on the direction of change in the index value 36.

[0112] As described above, the manner of change in the height Hp and width Wp of the apex of the peak shape part of the function (Q-dV / dQ) relative to the change in the number of charge / discharge cycles (battery capacity Q) differs between an alkali ion secondary battery in which alkali metal precipitation will occur in the future and an alkali ion secondary battery in which alkali metal precipitation will not occur. Therefore, by adopting at least one of the height Hp and width Wp as index value 36 and identifying the direction of change in index value 36, the risk of alkali metal precipitation can be accurately determined.

[0113] Furthermore, since the index value 36 can be calculated by obtaining a waveform of at least one peak shape portion, rather than a waveform of the entire range that the function (Q-dV / dQ) can take, the time required to measure the alkaline ion secondary battery to be evaluated can be shortened compared to the method of Patent Document 1.

[0114] In this way, the information processing device 2 and the information processing method according to the present embodiment make it possible to evaluate the safety of an alkali ion secondary battery accurately and in a shorter period of time.

[0115] Furthermore, in the information processing device 2, the determination unit 24 identifies the direction of change of the second index value 36_n relative to the first index value 36_1 based on the first index value 36_1 calculated based on the measurement result 31 when the number of charge / discharge cycles is a predetermined value (e.g., 400 times) and the second index value 36_n calculated based on the measurement result 31 when the number of charge / discharge cycles is a value greater than the predetermined value (e.g., 2000 times). This makes it possible to easily know the direction of change of the index value relative to the change in the number of charge / discharge cycles.

[0116] Furthermore, the determination unit 24 may determine that there is a risk of alkali metal precipitation when the height Hp as the second index value 36_n is increased relative to the height Hp as the first index value 36_1. Alternatively, the determination unit 24 may determine that there is a risk of alkali metal precipitation when the width Wp as the second index value 36_n is decreased relative to the width Wp as the first index value 36_1. This makes it possible to easily determine the presence or absence of a risk of alkali metal precipitation by simply identifying the direction of change of one parameter as the index value 36.

[0117] Furthermore, the determination unit 24 may determine that there is a risk of alkali metal precipitation when the height Hp as the second index value 36_n is increased relative to the height Hp as the first index value 36_1 and the width Wp as the second index value 36_n is decreased relative to the width Wp as the first index value 36_1. In this way, since two parameters are used as the index value 36, it is possible to more reliably determine the presence or absence of a risk of alkali metal precipitation.

[0118] As described above, the determination unit 24 may determine the direction of change in the index value 36 based on the polarity of the gradient (αh, αw) of the linear function that represents the relationship between the battery capacity Q and the index value 36 (at least one of the height Hp and the width Wp). This makes it possible to more reliably determine the direction of change in the index value 36.

[0119] <<Extension of the embodiment>> The invention made by the inventor has been specifically described above based on an embodiment, but it goes without saying that the invention is not limited thereto and can be modified in various ways without departing from the spirit of the invention.

[0120] For example, the function (Q-dV / dQ) may include a plurality of peak-shaped portions depending on the range of the battery capacity Q. In the present embodiment, as an example, the height Hp and width Wp of one of the plurality of peak-shaped portions is used as the index value 36. However, the height Hp and width Wp of each of the plurality of peak-shaped portions may be used as the index value 36.

[0121] In addition, in the above embodiment, as an example, a case was given in which height Hp2 and width Wp2 are used as the first index value 36_1 and height Hp3 and width Wp3 are used as the second index value 36_n, but this is not limited to this, and height Hp1 and width Wp1 may be used as the first index value 36_1 and height Hp2 and width Wp2 or height Hp3 and width Wp3 may be used as the second index value 36_n.

[0122] In addition, the above-mentioned flowchart shows an example for explaining the operation, and is not limited to this. That is, the steps shown in each figure of the flowchart are specific examples, and are not limited to this flow. For example, the order of some processes may be changed, other processes may be inserted between each process, and some processes may be performed in parallel.

[0123] In the above embodiment, as an example, a case has been described in which a risk of alkali metal precipitation in the storage battery 4 of the distributed power source 10 provided in the customer facility 1 is determined, but the storage battery to be determined is not limited to the above example. For example, when an electric vehicle (EV) is charged using the customer facility 1, the information processing device 2 may obtain measurement results of the battery capacity and battery voltage during charging and discharging of the electric vehicle's storage battery, and based on the measurement results, determine the risk of alkali metal precipitation in the electric vehicle's storage battery using a method similar to that described above. Also, an information processing device such as a microcontroller built into the electric vehicle may determine the risk of alkali metal precipitation in the storage battery of the electric vehicle. For example, a program relating to the above-mentioned method for determining the risk of alkali metal precipitation is installed in a microcontroller in the electric vehicle that monitors the state of the storage battery of the electric vehicle and controls charging and discharging. This allows the microcontroller or the like to determine the risk of alkali metal precipitation in the storage battery of the electric vehicle in a similar manner to the information processing device 2, based on the measurement results of the battery capacity and battery voltage when the storage battery of the electric vehicle is charged and discharged. [Explanation of symbols]

[0124] 1...customer equipment, 2...information processing device, 3...photovoltaic power generation equipment, 4...storage battery, 5...PCS, 6...distribution board, 7...load, 8...control device, 9...power distribution line, 10...distributed power source, 11...communication network, 20...measurement result acquisition unit, 21...differential value calculation unit, 22...function calculation unit, 23...index value calculation unit, 24...judgment unit, 25...output unit, 26...memory unit, 31...measurement result, 32...measured value of battery capacity Q, 33...measured value of battery voltage V, 34...differential value dV / dQ, 35...function (Q-dV / dQ), 36,36_1 to 36_n...index value, 39...judgment result, Hp,Hp1,Hp2,Hp3...height, Wp,Wp1,Wp2,Wp3...width, αh,αw...slope.

Claims

1. a measurement result acquisition unit that acquires measurement results of a battery capacity of an alkali ion secondary battery, which is a secondary battery that can be charged and discharged by the movement of alkali ions, and a battery voltage of the alkali ion secondary battery; a differential value calculation unit that calculates a differential value, which is a ratio of an amount of change in the battery voltage to an amount of change in the battery capacity, based on the measurement result; a function calculation unit that calculates a function indicating a relationship between the battery capacity and the differential value; an index value calculation unit that calculates at least one of the height of an apex of at least one peak shape portion of the function and a width indicating the extent of spread of the peak shape portion in a direction perpendicular to the height direction of the peak shape portion as an index value; a determination unit that specifies a direction of change in the index value relative to a change in the number of charge / discharge cycles based on the index value calculated based on the measurement results under at least two conditions with different numbers of charge / discharge cycles, and determines whether or not there is a risk of alkali metal precipitation in the alkali ion secondary battery based on the direction of change in the index value. Information processing device.

2. 2. The information processing device according to claim 1, The determination unit determines that there is a risk of precipitation of the alkali metal when the height as the index value increases with an increase in the number of charge / discharge cycles. Information processing device.

3. 2. The information processing device according to claim 1, The determination unit determines that there is a risk of precipitation of the alkali metal when the range as the index value decreases with an increase in the number of charge / discharge cycles. Information processing device.

4. 4. The information processing device according to claim 1, The determination unit identifies a direction of change of the second index value relative to the first index value based on a first index value, which is the index value calculated based on the measurement result when the number of charge / discharge cycles is a predetermined value, and a second index value, which is the index value calculated based on the measurement result when the number of charge / discharge cycles is a value larger than the predetermined value. Information processing device.

5. 5. The information processing device according to claim 4, The determination unit determines that there is a risk of precipitation of the alkali metal when the height as the second index value is greater than the height as the first index value. Information processing device.

6. 5. The information processing device according to claim 4, The determination unit determines that there is a risk of precipitation of the alkali metal when the range as the second index value is smaller than the range as the first index value. Information processing device.

7. 5. The information processing device according to claim 4, The determination unit determines that there is a risk of precipitation of the alkali metal when the height as the second index value is greater than the height as the first index value and the width as the second index value is smaller than the width as the first index value. Information processing device.

8. 4. The information processing device according to claim 1, The determination unit identifies a direction of change in the index value based on a polarity of a slope of a linear function that represents a relationship between the battery capacity and the index value. Information processing device.

9. A first step of acquiring measurement results of a battery capacity of an alkali ion secondary battery, which is a secondary battery capable of being charged and discharged by the movement of alkali ions, and a battery voltage of the alkali ion secondary battery; A second step of calculating a differential value, which is a ratio of an amount of change in the battery voltage to an amount of change in the battery capacity, based on the measurement result; A third step of calculating a function indicating a relationship between the battery capacity and the differential value; a fourth step of calculating an index value indicating at least one of the height of an apex of a peak shape portion of the function and a width indicating the extent of spread of the peak shape portion in a direction perpendicular to the height direction of the peak shape portion; and a fifth step of identifying a direction of change in the index value relative to a change in the number of charge / discharge cycles based on the index value calculated based on the measurement results under at least two conditions with different numbers of charge / discharge cycles, and determining whether or not there is a risk of alkali metal precipitation in the alkali ion secondary battery based on the direction of change in the index value. Information processing methods.

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