Battery monitoring device, program, and battery monitoring method

Abstract

To provide a battery monitoring device with which it is possible to identify the prescribed capacity of a storage battery without using a voltage change amount of the storage battery.SOLUTION: A battery monitoring device 53 is applied to a storage battery 40 in which a change of reaction calorimetry occurs at a prescribed capacity. The battery monitoring device 53 acquires a parameter that correlates to the reaction calorimetry of the storage battery when power is up and divides time-series calorimetry data consisting of the parameter and the power storage capacity into a low capacity first data group lower than a boundary and a high capacity second data group. Then, the battery monitoring device 53 calculates a first approximate function in which the first data group is approximated by a primary function and a second approximate function in which the second data group is approximated by a primary function, and calculates an error sum which is the sum of approximation errors of the first and second approximate functions. The boundary is changed to the low capacity or the high capacity side, and calculation is made of an error sum for each boundary changed, and the prescribed capacity of the storage battery is identified on the basis of the first and second approximate functions corresponding to the minimum error sum among the plurality of acquired error sums.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a battery monitoring device for monitoring a storage battery. , program, and battery monitoring method - Patents.com Regarding. [Background technology]

[0002] In recent years, lithium-ion batteries have been attracting attention as a lightweight, high-energy-density storage battery. Some lithium-ion batteries have a plateau region, where the change in battery voltage due to the change in the storage capacity of the battery is small. In the plateau region, it is difficult to calculate the storage capacity of the battery using the capacity-voltage characteristic that shows the correlation between the storage capacity and the battery voltage.

[0003] A known technique for calculating the storage capacity of a lithium-ion battery is to use a singularity where the battery voltage changes stepwise with a change in capacity within a plateau region. In a storage battery having a singularity, the singularity appears at a predetermined capacity of the storage battery regardless of the deterioration of the storage battery, so the predetermined capacity of the storage battery can be obtained by detecting the singularity. For example, in Patent Document 1, the battery voltage of the storage battery is detected, and the singularity is detected based on the voltage change amount, which is the amount of change in the battery voltage over time. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2014-167457 A Summary of the Invention [Problem to be solved by the invention]

[0005] The amount of voltage change at the singular point is very small. Therefore, in a situation where a large current flows through the storage battery, such as during high-speed charging, noise generated in the battery voltage makes it impossible to detect the singular point based on the amount of voltage change, and there is a concern that the specified capacity of the storage battery cannot be calculated appropriately.

[0006] The present invention has been made in view of the above problems, and an object of the present invention is to provide a battery monitoring device capable of specifying a predetermined capacity of a storage battery without using a voltage change amount of the storage battery. , program, and battery monitoring method - Patents.com The purpose of this invention is to provide [Means for solving the problem]

[0007] A first means for solving the above problem is applied to a storage battery in which a change in reaction heat amount occurs at a predetermined capacity when the storage capacity changes with the passage of current, and includes a data storage unit that acquires a parameter correlated with the reaction heat amount of the storage battery when current is passed through it, and stores time-series heat amount data consisting of the parameter and the storage capacity, a division unit that divides the heat amount data stored by the data storage unit into a first data group having a capacity lower than a predetermined boundary and a second data group having a capacity higher than the boundary, and an approximation calculation unit that calculates a first approximation function that approximates the first data group with a linear function and a second approximation function that approximates the second data group with a linear function, the first approximation function and the second approximation function and the error sum calculation unit calculates an error sum for each of the heat quantity data in the second data group; an acquisition unit that changes the boundary to the low capacity side or the high capacity side, and causes the approximation calculation unit to calculate the first approximation function and the second approximation function and the error sum calculation unit to calculate an error sum for each of the changed boundaries, thereby acquiring a plurality of error sums; and an identification unit that identifies the specified capacity of the storage battery based on the first approximation function and the second approximation function corresponding to the smallest error sum among the plurality of error sums.

[0008] In a storage battery in which a change in the amount of reaction heat occurs at a predetermined capacity as current is passed, an inflection point occurs at the predetermined capacity in the relationship between the storage capacity and a parameter correlating with the amount of reaction heat of the storage battery. The inventors have focused on the fact that a highly accurate linear approximation is possible on the lower capacity side and the higher capacity side of the predetermined capacity in the relationship between the storage capacity and the parameter correlating with the amount of reaction heat of the storage battery, and that the slope of the straight line changes at the predetermined capacity, and have found a method for specifying the predetermined capacity of a storage battery based on the relationship between the parameter and the storage capacity.

[0009] Specifically, time-series heat quantity data consisting of a parameter correlated with the reaction heat quantity of the storage battery and the storage capacity is divided into a first data group with a capacity lower than a predetermined boundary and a second data group with a capacity higher than the boundary, a first approximation function approximating the first data group with a linear function and a second approximation function approximating the second data group with a linear function are calculated, and an error sum is calculated as the sum of an approximation error between the first approximation function and each heat quantity data in the first data group and an approximation error between the second approximation function and each heat quantity data in the second data group.The boundary is then changed to the low capacity side or the high capacity side, and multiple error sums are obtained by calculating the first approximation function and the second approximation function and the error sum for each changed boundary, and the predetermined capacity of the storage battery is identified based on the first approximation function and the second approximation function corresponding to the smallest error sum among the multiple error sums.

[0010] According to the above configuration, the predetermined capacity of the storage battery can be determined based on the correlation between the parameter correlating with the reaction heat amount of the storage battery and the storage capacity, and the predetermined capacity of the storage battery can be determined without using the voltage change amount of the storage battery. In addition, the parameter has a characteristic of increasing in a situation where a large current flows through the storage battery. Therefore, even when a large current flows through the storage battery, such as during high-speed charging, and it is difficult to appropriately determine the predetermined capacity of the storage battery based on the voltage change amount, the predetermined capacity of the storage battery can be determined.

[0011] In a second method, the data storage unit stores the heat quantity data in a time series when the storage battery is being charged, and the acquisition unit gradually changes the boundary from a storage capacity on the fully charged side of the storage battery to a lower capacity side.

[0012] When charging a storage battery, it is assumed that charging starts from an arbitrary storage capacity, and then ends when the battery is fully charged. In other words, the storage capacity at the start of charging is arbitrary, whereas the storage capacity at the end of charging is considered to be an approximately constant storage capacity (full charge capacity). In the above configuration, when changing the boundary between the first data group and the second data group, the storage capacity of the storage battery is gradually changed from the fully charged side to the lower capacity side. In this way, when dividing the data into the first data group with a capacity lower than the boundary and the second data group with a capacity higher than the boundary, the boundary can be set based on an approximately constant storage capacity, making it difficult for a situation to occur in which the heat quantity data of the first data group does not exist, and making it possible to appropriately specify the predetermined capacity of the storage battery.

[0013] In a third means, the parameter is a battery temperature indicating the temperature of the storage battery, and the approximation calculation unit calculates the first approximation function and the second approximation function using time-series heat data consisting of the battery temperature and the storage capacity.

[0014] In a storage battery in which a change in reaction heat quantity occurs at a predetermined capacity as current is applied, the battery temperature changes with the change in reaction heat quantity, and an inflection point occurs at the predetermined capacity in the relationship between the battery temperature and the storage capacity. According to the above configuration, the first approximation function and the second approximation function are calculated using time-series heat quantity data consisting of the battery temperature and the storage capacity, so that the inflection point can be detected using these first approximation function and second approximation function, and the predetermined capacity of the storage battery can be identified.

[0015] In a fourth means, the parameter is an impedance of the storage battery, and the approximation calculation unit calculates the first approximation function and the second approximation function using time-series heat quantity data consisting of the impedance and the storage capacity.

[0016] In a storage battery in which a change in reaction heat quantity occurs at a predetermined capacity as current is passed, the impedance changes due to a temperature change when the change in reaction heat quantity occurs, and an inflection point occurs at the predetermined capacity in the relationship between the impedance and the storage capacity. According to the above configuration, the first approximation function and the second approximation function are calculated using time-series heat quantity data consisting of the impedance and the storage capacity, so that the inflection point can be detected using these first approximation function and second approximation function, and the predetermined capacity of the storage battery can be identified.

[0017] The fifth means includes an impedance calculation unit that acquires a response signal of the storage battery to a predetermined AC signal while applying the AC signal to the storage battery and calculates the impedance based on the response signal, and the frequency of the AC signal is set to a frequency lower than or equal to an ohmic frequency corresponding to the ohmic resistance of the storage battery.

[0018] In the above configuration, when calculating the impedance of the storage battery, the frequency of the AC signal is set to a frequency equal to or lower than the ohmic frequency. In particular, at frequencies lower than the ohmic frequency, the effect of reaction resistance on the calculated impedance becomes strong. Since reaction resistance has a strong temperature dependency, the amount of change in impedance at a given capacity tends to be large. Therefore, by using the reaction resistance, the given capacity of the storage battery can be accurately determined.

[0019] The sixth means includes a slope determination unit that determines whether the absolute value of the slope of the first approximation function is greater than the absolute value of the slope of the second approximation function, and the error sum calculation unit calculates the error sum on the condition that the slope determination unit determines that the absolute value of the slope of the first approximation function is greater than the absolute value of the slope of the second approximation function.

[0020] In the relationship between the parameter correlated with the reaction heat quantity of the storage battery and the storage capacity, when a boundary is set in a region including the predetermined capacity of the storage battery and its vicinity, the absolute value of the slope of the first approximation function (approximation function on the low capacity side) becomes larger than the absolute value of the slope of the second approximation function (approximation function on the high capacity side). However, in a wide range of storage capacity, the relationship of the slopes of the approximation functions may be reversed depending on the boundary setting, and if the relationship of the slopes of the approximation functions is not taken into consideration, there is a concern that the predetermined capacity may be erroneously determined based on an approximation function based on an incorrect approximation. In this regard, according to the above configuration, the predetermined capacity can be correctly determined based on the first approximation function and the second approximation function.

[0021] The seventh means includes a charging current memory unit that stores time-series charging current data until the storage battery is fully charged when the storage battery is charged, an accumulation value calculation unit that uses the charging current data to calculate an accumulated current value of the charging current that flows through the storage battery during the period from the specified capacity identified by the identification unit to the fully charged state, and a degradation state determination unit that determines a degradation state of the storage battery based on the accumulated current value.

[0022] The deterioration state of the storage battery is determined based on the predetermined capacity and the current integrated value. Here, the storage capacity at which the reaction heat quantity changes in the storage battery, i.e., the predetermined capacity, does not change even if the storage battery deteriorates, while the storage capacity at which the battery is fully charged changes due to the deterioration of the storage battery. In this case, the deterioration state of the storage battery can be appropriately determined by determining the predetermined capacity of the storage battery as described above and calculating the current integrated value up to the full charge capacity based on the predetermined capacity.

[0023] In an eighth embodiment, the storage battery includes graphite in the negative electrode. In a storage battery including graphite in the negative electrode, when the storage capacity reaches a predetermined capacity, the electrode structure of the negative electrode changes, causing a change in the amount of heat of reaction. Therefore, by utilizing this change in the amount of heat of reaction, the predetermined capacity of the storage battery can be determined.

[0024] In a ninth aspect, the storage battery includes lithium iron phosphate in the positive electrode. In an olivine-based storage battery including lithium iron phosphate in the positive electrode, the voltage change amount of the storage battery associated with the change in the storage capacity of the storage battery is small, and it is difficult to determine the specified capacity of the storage battery based on the voltage change amount. In the above configuration, the specified capacity of the storage battery is determined based on a parameter correlated with the reaction heat amount of the storage battery, so that the specified capacity of the storage battery can be determined without using the voltage change amount of the storage battery. [Brief description of the drawings]

[0025] [Figure 1] Circuit diagram of the power supply system. [Diagram 2] FIG. 1 shows the configuration of a storage battery. [Diagram 3] FIG. 4 is a graph showing the correlation between the storage capacity and the battery voltage and the amount of reaction heat. [Figure 4] FIG. 4 is a graph showing the correlation between storage capacity and battery temperature. [Diagram 5] 4 is a flowchart of a determination process in the first embodiment. [Figure 6] 13 is a flowchart of a predetermined capacity specification process. [Figure 7] FIG. 13 is a diagram showing a plurality of boundary candidates. [Figure 8] FIG. 11 is a graph showing changes in a first approximation function and a second approximation function when a boundary is changed. [Figure 9] FIG. 13 is a graph showing a change in the sum of errors when the boundary is changed. [Figure 10] FIG. 13 is a diagram showing the correlation between storage capacity and impedance. [Figure 11] 13 is a flowchart of a determination process in the second embodiment. [Figure 12] FIG. 11 is a graph showing changes in a first approximation function and a second approximation function when a boundary is changed. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0026] (First embodiment) Hereinafter, a first embodiment in which a battery monitoring device is applied to a power supply system of a vehicle (for example, a hybrid vehicle or an electric vehicle) will be described with reference to the drawings.

[0027] 1, the power supply system 10 is a system that supplies power to an electric load 20 such as a rotating machine (motor generator), and includes a storage battery 40. At least one of a positive-side power supply path L1 that connects the positive electrode of the storage battery 40 to the electric load 20 and a negative-side power supply path L2 that connects the negative electrode of the storage battery 40 to the electric load 20 is provided with a relay switch SMR (system main relay switch), and is configured to be able to switch between energization and cut-off of energization between the storage battery 40 and the electric load 20 by the relay switch SMR. In this embodiment, a lithium-ion storage battery is used as the storage battery 40.

[0028] A positive charging path L3 is connected to the positive power supply path L1, and a negative charging path L4 is connected to the negative power supply path L2, and each of these charging paths L3, L4 is provided with a pair of connection terminals 21. The storage battery 40 is configured to be connectable to an external charging device outside the power supply system 10 via the pair of connection terminals 21, and is charged by the external charging device.

[0029] The configuration of the storage battery 40 will be described with reference to Fig. 2. The storage battery 40 includes an electrode assembly 44, an electrolyte 45, and a storage case 46 that stores the electrode assembly 44 and the electrolyte 45. The electrolyte 45 is a non-aqueous electrolyte solution, such as an organic solvent such as ethylene carbonate or diethyl carbonate. The storage case 46 is formed of, for example, an aluminum alloy, and external terminals 47 are provided on both ends of the upper surface in the longitudinal direction.

[0030] The electrode body 44 is composed of a positive electrode conductive plate 44a as a positive electrode, a negative electrode conductive plate 44b as a negative electrode, and a separator 44c disposed between the positive electrode conductive plate 44a and the negative electrode conductive plate 44b.

[0031] The positive electrode conductive plate 44a is composed of a positive electrode metal foil 44d made of a metal foil such as aluminum, and a positive electrode active material 44e applied to the front and back surfaces of the positive electrode metal foil 44d. The positive electrode active material 44e is olivine-type iron phosphate, i.e., lithium iron phosphate. The negative electrode conductive plate 44b is composed of a negative electrode metal foil 44f made of a metal foil such as copper, and a negative electrode active material 44g applied to the front and back surfaces of the negative electrode metal foil 44f. The negative electrode active material 44g is graphite such as graphite or carbon. The separator 44c is a porous insulating film formed of polyethylene resin. The electrode body 44 is energized by the movement of lithium ions between the positive electrode conductive plate 44a and the negative electrode conductive plate 44b through the separator 44c.

[0032] FIG. 2 shows an equivalent circuit model of the complex impedance Zm of the storage battery 40. In this equivalent circuit model, the complex impedance Zm of the storage battery 40 is composed of a series connection of an ohmic resistance Rohm, a reaction resistance Rct, and a diffusion resistance Rw. The ohmic resistance Rohm is a current flow resistance in the electrodes and electrolyte that constitute the storage battery 40. The reaction resistance Rct represents a resistance due to an electrode interface reaction in the electrodes, and is represented as a parallel connection of a resistance component 42a and a capacitance component 42b. The diffusion resistance Rw represents a resistance associated with the diffusion of lithium ions into the electrode active material applied to the electrode surface.

[0033] 1, the power supply system 10 includes a battery measuring device 50 that measures the state of the storage battery 40, and an ECU 60 that controls the electric load 20. The battery measuring device 50 is a device that measures the storage capacity Q and SOH (state of health) of the storage battery 40. The battery measuring device 50 includes a current modulation circuit 51, a first voltmeter 52, and a control device 53 that serves as a battery monitoring device.

[0034] The current modulation circuit 51 is a circuit that applies a predetermined AC signal to the storage battery 40 that is the measurement target. The current modulation circuit 51 has an oscillator 51a and a first ammeter 51b connected in series to the oscillator 51a, and is connected to the storage battery 40 by a first electrical path 81.

[0035] The oscillator 51a generates an AC signal instructed by the control device 53 and applies the AC signal to the storage battery 40. The AC signal is, for example, a sine wave signal or a square wave signal. The first ammeter 51b measures a current signal generated in the first electrical path 81 and outputs the measured current signal data to the control device 53.

[0036] The first voltmeter 52 is connected to the storage battery 40 by a second electrical path 82 different from the first electrical path 81. When an AC signal is applied to the first voltmeter 52, a response signal (voltage fluctuation) reflecting the complex impedance Zm of the storage battery 40 is generated. The first voltmeter 52 measures this response signal and outputs the measured response signal data to the control device 53.

[0037] The battery measurement device 50 also includes a second ammeter 54, a second voltmeter 55, and a thermometer 56. The second ammeter 54 is provided on the positive power supply path L1. The second ammeter 54 measures the battery current I of the storage battery 40 and outputs the measured battery current data to the control device 53. The second voltmeter 55 is connected in parallel to the electric load 20. The second voltmeter 55 measures the battery voltage V of the storage battery 40 and outputs the measured battery voltage data to the control device 53. The thermometer 56 is, for example, a thermocouple or a thermistor, and is disposed near the storage battery 40. The thermometer 56 measures the battery temperature T of the storage battery 40 and outputs the measured battery temperature data to the control device 53.

[0038] The control device 53 is mainly composed of a microcomputer and realizes various control functions by executing programs stored in a storage device provided in the control device 53. The control device 53 grasps the driving state of the electric load 20 based on the battery current I and the battery voltage V, and outputs the driving state to the ECU 60.

[0039] Furthermore, the control device 53 calculates the complex impedance Zm of the storage battery 40, that is, the real part ReZm and the imaginary part ImZm of the complex impedance Zm, based on the response signal and the current signal. The control device 53 creates, for example, a complex impedance plane plot (Cole-Cole plot) based on the calculation result, and grasps the characteristics of the positive electrode conductive plate 44a, the negative electrode conductive plate 44b, the electrolyte 45, etc.

[0040] 2 shows a complex impedance planar plot of the storage battery 40. In the complex impedance planar plot, in order to show a vector locus focusing on the capacitance component in the first quadrant, the upper side of the vertical axis is drawn to be "-ImZm", that is, the imaginary part is inverted.

[0041] On the complex impedance plane plot, the complex impedance Zm changes according to the frequency ωr of the AC signal specified by the command signal, and a semicircular arc Cr appears in the low frequency region. At the end point PA on the high frequency side of the arc Cr, the imaginary part ImZm of the complex impedance Zm becomes zero. The value of the real part ReZm of the complex impedance Zm at this end point PA represents the ohmic resistance Rohm.

[0042] A straight line Pr, which is a linear locus, appears on the low-frequency side of the arc Cr. If the connection point between the arc Cr and the straight line Pr is the end point PB on the low-frequency side of the arc Cr, the difference between the value of the real part ReZm of the complex impedance Zm at the end point PB and the value of the real part ReZm of the complex impedance Zm at the end point PA represents the reaction resistance Rct.

[0043] Furthermore, the control device 53 grasps the storage capacity Q and SOH of the storage battery 40 based on the battery current I and the battery voltage V. Fig. 3 shows the correlation between the storage capacity Q and the battery voltage V of the storage battery 40. As shown in Fig. 3, the olivine-based storage battery 40 using lithium iron phosphate as the positive electrode active material 44e has a region where the change in the battery voltage V associated with the capacity change is small, that is, a plateau region. In the plateau region, it is difficult to calculate the storage capacity Q of the storage battery 40 using the correlation between the storage capacity Q and the battery voltage V.

[0044] Within the plateau region, there is a singular point where the battery voltage V changes stepwise with a change in capacity. In the storage battery 40, the singular point appears at the predetermined capacity QA of the storage battery 40 regardless of the deterioration of the storage battery 40, so the predetermined capacity QA of the storage battery 40 can be identified by detecting the singular point using the voltage change amount of the battery voltage V. However, the voltage change amount at the singular point is very small. Therefore, in a situation where a large current flows through the storage battery 40, such as during high-speed charging, the singular point cannot be detected based on the voltage change amount due to noise generated in the battery voltage V, and it is difficult to properly identify the predetermined capacity QA of the storage battery 40.

[0045] FIG. 3 shows the correlation between the storage capacity Q and the reaction heat amount H in the storage battery 40. The reaction heat amount H is the product of the battery temperature T, the battery current I, and the heat coefficient dV / dT, which is the amount of change in open circuit voltage per unit temperature and has a unique value for each storage capacity Q. In an olivine-based storage battery 40 using graphite as the negative electrode active material 44g, when the storage capacity Q changes with current flow, the reaction heat amount H changes at a predetermined capacity QA, and the battery temperature T, which is a parameter correlated with the reaction heat amount H, changes at the predetermined capacity QA. As a result, as shown in FIG. 4, an inflection point occurs at the predetermined capacity QA in the correlation between the storage capacity Q and the battery temperature T.

[0046] The inventors have noticed that in the correlation between the storage capacity Q and the battery temperature T, a highly accurate linear approximation is possible on the lower capacity side and the higher capacity side of the predetermined capacity QA, and the slope of the straight line changes at the predetermined capacity QA. In the storage battery 40, the slope of the linear approximation is positive on both the lower capacity side and the higher capacity side of the predetermined capacity QA, and the battery temperature T increases monotonically with an increase in the storage capacity Q, and the slope of the linear approximation becomes smaller on the higher capacity side than on the lower capacity side. The inventors have found a method for identifying the predetermined capacity QA of the storage battery 40 based on the correlation between the storage capacity Q and the battery temperature T.

[0047] 8, the control device 53 acquires time-series heat quantity data consisting of the power storage capacity Q and the battery temperature T during power supply, and divides the acquired heat quantity data into a first data group DA having a capacity lower than a predetermined boundary B and a second data group DB having a capacity higher than the boundary B. The control device 53 calculates a first approximation function F1 that approximates the first data group DA with a linear function, and a second approximation function F2 that approximates the second data group DB with a linear function, and calculates an error sum G that is the sum of the approximation error between the first approximation function F1 and each heat quantity data in the first data group DA and the approximation error between the second approximation function F2 and each heat quantity data in the second data group DB. Then, the boundary B is changed to the low capacity side or the high capacity side, and for each changed boundary B, the first approximation function F1 and the second approximation function F2 are calculated, and the error sum G is calculated to obtain a plurality of error sums G. A predetermined capacity specification process is performed to specify the predetermined capacity QA of the storage battery 40 based on the first approximation function F1 and the second approximation function F2 corresponding to the smallest error sum G among the plurality of error sums G. According to the predetermined capacity specification process, the predetermined capacity QA of the storage battery 40 can be specified based on the correlation between the storage capacity Q and the battery temperature T, and the predetermined capacity QA of the storage battery 40 can be specified without using the amount of change in voltage of the storage battery 40.

[0048] 5 shows a flowchart of the determination process of this embodiment. The determination process includes the above-mentioned predetermined capacity specification process, and is a process for determining the SOH based on the predetermined capacity QA of the storage battery 40 specified by the predetermined capacity specification process. The control device 53 repeatedly performs the determination process at every predetermined control period when the storage battery 40 is being charged.

[0049] When the determination process starts, in step S11, it is determined whether or not charging of the storage battery 40 has been completed. If the storage battery 40 is not in a fully charged state and charging of the storage battery 40 continues, the process proceeds to step S12. On the other hand, if the storage battery 40 is in a fully charged state, the process proceeds to step S14. Note that the fully charged state of the storage battery 40 refers to, for example, a state in which the battery voltage V of the storage battery 40 has reached a predetermined fully charged voltage, or a state in which the storage battery 40 has left the plateau region with an increase in capacity and the change in the battery voltage V with the change in capacity has become large.

[0050] In step S12, the battery current I is measured and stored as charging current data. In the following step S13, the battery temperature T is measured, and the charge capacity Q of the storage battery 40 is calculated by current integration using the charging current data, and heat quantity data consisting of the charge capacity Q and the battery temperature T is stored.

[0051] During charging of the storage battery 40, the processes of steps S12 and S13 are repeatedly performed. As a result, in step S12, time-series charging current data until the storage battery 40 is fully charged is stored, and in step S13, time-series heat quantity data until the storage battery 40 is fully charged is stored. In this embodiment, the process of step S12 corresponds to a "charging current storage unit", and the process of step S13 corresponds to a "data storage unit".

[0052] In step S14, a predetermined capacity specification process is performed. A flowchart of the predetermined capacity specification process is shown in Fig. 6. When the predetermined capacity specification process is started, in step S21, an initial boundary B for calculating the first approximation function F1 and the second approximation function F2 is set.

[0053] As shown in Fig. 7, in this embodiment, a plurality of boundary candidates BA arranged at equal intervals are determined within the range of the storage capacity Q in which the battery temperature data is acquired, and one boundary candidate BA selected from the plurality of boundary candidates BA is set as the boundary B. At this time, the calorific value data with a capacity lower than the boundary B is the first data group DA, and the calorific value data with a capacity higher than the boundary B is the second data group DB. In step S21, the boundary candidate BA located on the highest capacity side among the plurality of boundary candidates BA is set as the boundary B. As a result, the calorific value data included in the second data group DB is minimized.

[0054] In step S22, the first approximation function F1 and the second approximation function F2 are calculated. The first approximation function F1 and the second approximation function F2 are calculated, for example, using the least squares method. In the following step S23, it is determined whether or not the absolute value of the first slope θ1, which is the slope of the first approximation function F1, is greater than the absolute value of the second slope θ2, which is the slope of the second approximation function F2. If the absolute value of the first slope θ1 is greater than the absolute value of the second slope θ2, the process proceeds to step S24. On the other hand, if the absolute value of the first slope θ1 is smaller than the absolute value of the second slope θ2, the process proceeds to step S27 without calculating the error sum G. In this embodiment, the process of step S22 corresponds to the "approximation calculation unit", and the process of step S23 corresponds to the "slope determination unit".

[0055] In step S24, the error sum G is calculated. The error sum G is calculated using, for example, a residual. As shown in FIG. 8(A), in the time-series heat quantity data, the storage capacity Q and battery temperature T indicated by the heat quantity data stored at the i-th time (i is a natural number) are set as the storage capacity Qi and battery temperature Ti. In the first approximation function F1 and the second approximation function F2, the value corresponding to the storage capacity Qi is set as the approximate value Fi. In this case, if the number of data points in the time-series heat quantity data is n, the error sum G can be expressed as the following formula (1). In this embodiment, the process of step S24 corresponds to an "error sum calculation unit."

number

[0056] In step S25, it is determined whether the error sum G calculated in step S24 is the minimum. At this time, if the currently calculated error sum G is smaller than the minimum value of the error sum G up to the previous time, the current error sum G is determined to be the minimum. If the error sum G is the minimum, in step S26, the first approximation function F1 and the second approximation function F2 calculated in step S22 are stored, and the process proceeds to step S27. On the other hand, if the error sum G is not the minimum, the process proceeds to step S27 without storing the first approximation function F1 and the second approximation function F2 calculated in step S22.

[0057] In step S27, it is determined whether or not to move the boundary B to the low capacity side. In this embodiment, the setting range of the boundary B is determined in advance, and the boundary B is gradually changed from the storage capacity Q on the full charge side of the storage battery 40 to the low capacity side. Specifically, the boundary candidate BA set as the boundary B is changed in sequence from the boundary candidate BA located on the highest capacity side to the boundary candidate BA located on the lowest capacity side. In step S27, it is determined whether the current boundary B for which the error sum G is calculated is the boundary candidate BA on the lowest capacity side among the multiple boundary candidates BA in the setting range of the boundary B, and if it is not the boundary candidate BA on the lowest capacity side, it is determined that the boundary B can be moved to the low capacity side, and the process proceeds to step S28. In step S28, the boundary B is moved to the low capacity side, and the process returns to step S22. On the other hand, if the current boundary B is the boundary candidate BA on the lowest capacity side, the process proceeds to step S29. In this embodiment, the processes in steps S21 and S28 correspond to the "division unit".

[0058] That is, in the predetermined capacity specification process, each boundary candidate BA is set once as the boundary B. Each time each boundary candidate BA is set as the boundary B, the first approximation function F1 and the second approximation function F2 are calculated, and an error sum G is obtained. Then, from among the multiple error sums G obtained, the smallest error sum G is selected. In this embodiment, the repetition of the processes of steps S22 to S26 corresponds to an "obtaining unit."

[0059] In step S29, the predetermined capacity QA of the storage battery 40 is identified based on the first approximation function F1 and the second approximation function F2 stored in step S26, and the predetermined capacity identification process is terminated. If a plurality of first approximation functions F1 and second approximation functions F2 are stored in step S26, the predetermined capacity QA of the storage battery 40 is identified based on the last stored first approximation function F1 and second approximation function F2 among the plurality of first approximation functions F1 and second approximation functions F2. In this embodiment, the storage capacity Q of the intersection X of the first approximation function F1 and the second approximation function F2 is identified as the predetermined capacity QA. In this embodiment, the process of step S29 corresponds to the "identification unit".

[0060] Returning to FIG. 6, when the predetermined capacity specification process is completed, the process proceeds to step S15. In step S15, it is determined whether or not the slope difference Δθ, which is the difference between the absolute value of the first slope θ1 and the absolute value of the second slope θ2, is greater than the threshold value θth in the first approximation function F1 and the second approximation function F2 used in the calculation of the predetermined capacity QA in step S29. If the predetermined capacity QA is not included in the range of the storage capacity Q for which the battery temperature data is acquired and the slope difference Δθ is smaller than the threshold value θth, the determination process is terminated. On the other hand, if the predetermined capacity QA is included in the range of the storage capacity Q for which the battery temperature data is acquired and the slope difference Δθ is greater than the threshold value θth, the process proceeds to step S16.

[0061] In step S16, the time-series charging current data stored in step S12 is used to calculate an integrated current value ΔQ of the battery current I flowing through the storage battery 40 during the period until the storage battery 40 is fully charged, from the predetermined capacity QA identified in step S29. In the following step S17, the SOH is determined based on the integrated current value ΔQ calculated in step S17, and the determination process ends. In this embodiment, the process of step S16 corresponds to an "integrated value calculation unit", and the process of step S17 corresponds to a "degradation state determination unit".

[0062] A method for determining the SOH will be described. When the storage battery 40 is new, the storage capacity Q in a fully charged state can be expressed as Q=QA+ΔQN using the current integrated value ΔQN when the storage battery 40 is new. Therefore, the SOH of the storage battery 40 can be expressed as the following formula (2). When the predetermined capacity QA is specified by the predetermined capacity specification process and the current integrated value ΔQN when the storage battery 40 is new is acquired in advance, the SOH can be determined based on the current integrated value ΔQ.

number

[0063] Next, an example of the predetermined capacity specification process is shown in Fig. 8. Fig. 8(A) to (C) show a first approximation function F1 and a second approximation function F2 in the case where three different boundary candidates BA among the multiple boundary candidates BA shown in Fig. 7 are set as the boundary B.

[0064] 8A, the boundary B is set on the higher capacity side than the predetermined capacity QA. In this case, the approximation accuracy of the second approximation function F2 is good, but the approximation accuracy of the first approximation function F1 is poor. Therefore, although the approximation error between the second approximation function F2 and each heat quantity data in the second data group DB is small, the approximation error between the first approximation function F1 and each heat quantity data in the first data group DA is large, and the error sum G is large.

[0065] In Fig. 8(B), the boundary B is set near the predetermined capacity QA. In this case, the approximation accuracy of the first approximation function F1 and the second approximation function F2 is improved. Therefore, the approximation error between the first approximation function F1 and each heat quantity data in the first data group DA and the approximation error between the second approximation function F2 and each heat quantity data in the second data group DB are both reduced, and the error sum G is reduced.

[0066] In Fig. 8(C), the boundary B is set on the lower capacity side than the predetermined capacity QA. In this case, the approximation accuracy of the first approximation function F1 is good, but the approximation accuracy of the second approximation function F2 is poor. Therefore, while the approximation error between the first approximation function F1 and each heat quantity data in the first data group DA is small, the approximation error between the second approximation function F2 and each heat quantity data in the second data group DB is large, and the error sum G is large.

[0067] As a result, as shown in Fig. 9, when the boundary B is gradually changed from the high capacity side to the low capacity side, the error sum G decreases and then increases, and the minimum error sum G appears between the decreasing range and the increasing range of the error sum G. In this embodiment, the boundary B corresponding to the minimum error sum G is the boundary B in Fig. 8(B). In this case, the predetermined capacity QA is specified by the storage capacity Q of the intersection X of the first approximate function F1 and the second approximate function F2 in Fig. 8(B).

[0068] According to the present embodiment described above in detail, the following effects can be obtained.

[0069] According to this embodiment, the predetermined capacity QA of the storage battery 40 can be determined based on the correlation between the battery temperature T, which correlates with the reaction heat amount H of the storage battery 40, and the storage capacity Q. Therefore, the predetermined capacity QA of the storage battery 40 can be determined without using the voltage change amount of the storage battery 40. In addition, the battery temperature T has a characteristic of becoming high in a situation where a large current flows through the storage battery 40. Therefore, even if a large current flows through the storage battery 40, such as during high-speed charging, and it is difficult to appropriately determine the predetermined capacity QA of the storage battery 40 based on the voltage change amount, the predetermined capacity QA of the storage battery 40 can be determined.

[0070] When charging the storage battery 40, charging is started from an arbitrary storage capacity Q, and then charging is terminated when the battery is fully charged. That is, the storage capacity Q at the start of charging is arbitrary, whereas the storage capacity Q at the end of charging is considered to be a generally constant storage capacity (full charge capacity). In this embodiment, when changing the boundary B between the first data group DA and the second data group DB, the storage capacity Q of the storage battery 40 is gradually changed from the fully charged side to the lower capacity side. As a result, when dividing the first data group DA with a capacity lower than the boundary B and the second data group DB with a capacity higher than the boundary B, the boundary B can be set based on a generally constant storage capacity Q, making it difficult for a situation to occur in which the heat quantity data of the first data group DA does not exist, and the predetermined capacity QA of the storage battery 40 can be appropriately specified.

[0071] In the storage battery 40 in which the reaction heat quantity H changes at a predetermined capacity QA as current is applied, the battery temperature T changes with the change in the reaction heat quantity H, and an inflection point occurs at the predetermined capacity QA in the relationship between the battery temperature T and the storage capacity Q. According to this embodiment, the first approximation function F1 and the second approximation function F2 are calculated using time-series heat quantity data consisting of the battery temperature T and the storage capacity Q, so that the inflection point can be detected using these first approximation function F1 and second approximation function F2. Therefore, even if it is difficult to appropriately specify the predetermined capacity QA of the storage battery 40 based on the amount of voltage change, the predetermined capacity QA of the storage battery 40 can be specified.

[0072] Furthermore, the degree of change in the battery temperature T accompanying a change in the reaction heat quantity H varies depending on factors outside the storage battery 40, such as the amount of heat released into the outside air, and the degree of change may not be determined in general. In this embodiment, regardless of the magnitude of the degree of change in the battery temperature T, the specified capacity QA is determined from the minimum boundary B of the error sum G. This makes it possible to strengthen the resistance to factors outside the storage battery 40.

[0073] In the relationship between the battery temperature T and the storage capacity Q, when the boundary B is set in a region including the predetermined capacity QA of the storage battery 40 and its vicinity, the absolute value of the first slope θ1 of the first approximation function F1 becomes larger than the absolute value of the second slope θ2 of the second approximation function F2. However, in a wide range of the storage capacity Q, the relationship of the slopes of the approximation functions may be reversed depending on the setting of the boundary B, and if the relationship of the slopes of the approximation functions is not taken into consideration, there is a concern that the predetermined capacity QA may be erroneously determined based on an approximation function based on an incorrect approximation. In this regard, according to the present embodiment, the predetermined capacity QA can be correctly determined based on the first approximation function F1 and the second approximation function F2.

[0074] The SOH of the storage battery 40 is determined based on the predetermined capacity QA and the current integrated value ΔQ. Here, the storage capacity Q at which the reaction heat quantity H of the storage battery 40 changes, i.e., the predetermined capacity QA, does not change even if the storage battery 40 deteriorates, whereas the storage capacity Q at which the battery is fully charged changes due to deterioration of the storage battery 40. In this case, the SOH of the storage battery 40 can be appropriately determined by determining the predetermined capacity QA of the storage battery 40 as in this embodiment and calculating the current integrated value ΔQ up to the full charge capacity based on the predetermined capacity QA.

[0075] Since the storage battery 40 contains graphite in the negative electrode, when the storage capacity Q becomes the predetermined capacity QA, the electrode structure of the negative electrode changes, causing a change in the reaction heat H. On the other hand, since the storage battery 40 contains lithium iron phosphate in the positive electrode, the amount of change in the voltage of the storage battery 40 associated with a change in the storage capacity Q of the storage battery 40 is small, making it difficult to determine the predetermined capacity QA of the storage battery 40 based on the amount of voltage change. In this embodiment, the predetermined capacity QA of the storage battery 40 is determined based on the battery temperature T that correlates with the reaction heat H of the storage battery 40, so that the predetermined capacity QA of the storage battery 40 can be determined without using the amount of voltage change of the storage battery 40.

[0076] Second embodiment The second embodiment will be described below with reference to Figures 10 to 12, focusing on the differences from the first embodiment. This embodiment differs from the first embodiment in that the parameter correlated with the reaction heat amount H is the complex impedance Zm.

[0077] Fig. 10 shows the correlation between the charge storage capacity Q and the real part ReZm of the complex impedance Zm. In an olivine-based storage battery 40 using graphite as the negative electrode active material 44g, when the charge storage capacity Q changes with current flow, the complex impedance Zm changes with the temperature change that accompanies the change in the reaction heat quantity H at a given capacity QA. As a result, as shown in Fig. 10, in the correlation between the charge storage capacity Q and the real part ReZm of the complex impedance Zm, an inflection point occurs at the given capacity QA.

[0078] In the correlation between the storage capacity Q and the real part ReZm of the complex impedance Zm, a highly accurate linear approximation is possible on the lower capacity side and the higher capacity side of the predetermined capacity QA, and the slope of the straight line changes at the predetermined capacity QA. In the storage battery 40, the slope of the straight line approximation on both the lower capacity side and the higher capacity side of the predetermined capacity QA is negative, and the battery temperature T monotonically decreases with an increase in the storage capacity Q, and the slope of the straight line approximation becomes larger on the high capacity side than on the low capacity side. In this embodiment, the predetermined capacity QA of the storage battery 40 is specified based on the correlation between the storage capacity Q and the real part ReZm of the complex impedance Zm.

[0079] A flowchart of the determination process of this embodiment is shown in Fig. 11. Note that in Fig. 11, the same processes as those shown in Fig. 6 are denoted by the same step numbers for convenience, and the description thereof will be omitted.

[0080] In the determination process of this embodiment, once the charging current data is stored in step S12, the process proceeds to step S31. In step S31, complex impedance Zm is calculated. In this embodiment, the frequency of the AC signal applied to the storage battery 40 when calculating the complex impedance Zm is set to a constant frequency equal to or lower than the ohmic frequency corresponding to the ohmic resistance Rohm of the storage battery 40, which is indicated by the end point PA in FIG. 2. Specifically, the frequency is set to the frequency corresponding to the end point PB in FIG. 2. In this embodiment, the process of step S31 corresponds to an "impedance calculation unit."

[0081] In the next step S13, heat quantity data consisting of the electricity storage capacity Q and the complex impedance Zm calculated in step S31 is stored. In the predetermined capacity specification process of this embodiment, the first approximation function F1 and the second approximation function F2 are calculated using the real part ReZm of the complex impedance Zm stored in step S13, and the error sum G is calculated to specify the predetermined capacity QA.

[0082] Next, an example of the predetermined capacity specification process is shown in Fig. 12. Fig. 12(A) to (C) show a first approximation function F1 and a second approximation function F2 in the case where three different boundary candidates BA are set as the boundary B among a plurality of boundary candidates BA defined in the range of the storage capacity Q in which the complex impedance Zm is acquired.

[0083] In Fig. 12(A), boundary B is set on the higher capacity side than the specified capacity QA, and the sum of errors G is large. In Fig. 12(B), boundary B is set near the specified capacity QA, and the sum of errors G is small. In Fig. 12(C), boundary B is set on the lower capacity side than the specified capacity QA, and the sum of errors G is large.

[0084] As a result, as shown in Fig. 9, when the boundary B is gradually changed from the high capacity side to the low capacity side, the minimum error sum G appears. In this embodiment, the boundary B corresponding to the minimum error sum G is the boundary B in Fig. 12(B). In this case, the predetermined capacity QA is specified by the storage capacity Q of the intersection X of the first approximate function F1 and the second approximate function F2 in Fig. 12(B).

[0085] According to the present embodiment described above in detail, the following effects can be obtained.

[0086] In the storage battery 40 in which the reaction heat quantity H changes at a predetermined capacity QA due to energization, the complex impedance Zm changes due to the temperature change when the reaction heat quantity H changes, and an inflection point occurs at the predetermined capacity QA in the relationship between the complex impedance Zm and the storage capacity Q. According to this embodiment, the first approximation function F1 and the second approximation function F2 are calculated using time-series heat quantity data consisting of the complex impedance Zm and the storage capacity Q, so that the inflection point can be detected using these first approximation function F1 and second approximation function F2. Therefore, even if it is difficult to appropriately specify the predetermined capacity QA of the storage battery 40 based on the amount of voltage change, the predetermined capacity QA of the storage battery 40 can be specified.

[0087] In this embodiment, when the complex impedance Zm of the storage battery 40 is calculated, the frequency of the AC signal is set to a frequency equal to or lower than the ohmic frequency. In particular, at a frequency lower than the ohmic frequency, the effect of reaction resistance on the calculated complex impedance Zm becomes strong. Since reaction resistance has a strong temperature dependency, the amount of change in the complex impedance Zm at the predetermined capacity QA tends to be large. Therefore, by using the reaction resistance, the predetermined capacity QA of the storage battery 40 can be accurately determined.

[0088] (Other embodiments) The present invention is not limited to the above-described embodiment, and may be implemented as follows.

[0089] In the above embodiment, an example was shown in which time-series heat quantity data was stored when the storage battery 40 was being charged, but time-series heat quantity data may also be stored when the storage battery 40 was being discharged. However, the positive and negative signs of the reaction heat quantity H are reversed during discharging. This reversal changes the tendency of temperature change in the reaction heat quantity H at the specified capacity QA, and the sign of the inequality in step S23 is reversed.

[0090] In the above embodiment, an example is shown in which the boundaries B are changed at equal intervals, but the intervals of the boundaries B may be unequal. For example, the storage capacity range determined as the setting range of the boundaries B may be divided into a low capacity range, a medium range, and a high capacity range in order from the low capacity side, and the intervals of the boundaries B may be made relatively large in the low capacity range and the high capacity range, and relatively small in the medium range. Also, by referring to a previously calculated predetermined capacity QA, the intervals of the boundaries B may be made relatively small in a nearby range including the predetermined capacity QA, and the intervals of the boundaries B may be made relatively large outside the nearby range.

[0091] In the above embodiment, an example of calculating the error sum G using the residual has been shown, but this is not limiting. For example, the square root of the sum of the variance between the first approximation function F1 and each heat quantity data in the first data group DA and the variance between the first approximation function F1 and each heat quantity data in the first data group DA may be calculated as the error sum G. Also, for example, in Fig. 8 and Fig. 12, the sum of the area between the graph indicated by the first approximation function F1 and the graph indicated by the first data group DA and the area between the graph indicated by the second approximation function F2 and the graph indicated by the second data group DB may be calculated as the error sum G.

[0092] In the above embodiment, when the boundary B is gradually changed from the storage capacity Q on the fully charged side of the storage battery 40 to the lower capacity side, the boundary candidate BA set as the boundary B is changed in sequence from the boundary candidate BA located on the highest capacity side to the boundary candidate BA located on the lowest capacity side, but this is not limited to the above. For example, by referring to a previously calculated predetermined capacity QA, instead of the boundary candidate BA located on the highest capacity side, the boundary candidate BA based on the predetermined capacity QA may be changed to the lower capacity side.

[0093] Also, the boundary candidate BA located at the lowest capacity side may be changed as follows. According to the predetermined capacity specification process in Fig. 6, as the boundary B is gradually changed from the storage capacity Q on the fully charged side to the lower capacity side, the error sum G gradually decreases and then starts to increase. In this case, in step S27, a configuration may be used in which it is determined whether or not to move the boundary B to the lower capacity side based on the fact that the error sum G has changed from decreasing to increasing.

[0094] In other words, if the control device 53 determines that the error sum G has changed from decreasing to increasing as a result of changing the boundary B to the lower capacity side, it may determine that it is not necessary to change the boundary B to a lower capacity side, and may determine not to move the boundary B to the lower capacity side (set step S27 to NO).

[0095] In the above embodiment, an example was shown in which all stored heat quantity data was used, but this is not limited to this. For example, if there is a part of the heat quantity data in which the battery temperature T does not monotonically increase with respect to the storage capacity Q, or in which the complex impedance Zm does not monotonically decrease with respect to the storage capacity Q, then there is a possibility that this heat quantity data contains disturbance. In this case, only the heat quantity data that is monotonically increasing or decreasing may be extracted and used.

[0096] In the above embodiment, when the predetermined capacity QA of the storage battery 40 is determined based on the first approximation function F1 and the second approximation function F2 corresponding to the minimum error sum G, the storage capacity Q of the intersection X of the first approximation function F1 and the second approximation function F2 is determined as the predetermined capacity QA, but this is not limited to the above. The storage capacity Q of the boundary B corresponding to the minimum error sum G may be determined as the predetermined capacity QA.

[0097] In the above embodiment, an example has been shown in which a storage battery having a plateau region is used as the storage battery 40. However, the technique of this embodiment may be used for a storage battery that does not have a plateau region.

[0098] In the above embodiment, an example has been described in which the storage battery 40 has one singular point (predetermined capacity QA). However, the present invention is not limited to this, and the storage battery 40 may have a plurality of singular points (predetermined capacity QA).

[0099] In the above second embodiment, an example was shown in which the real part ReZm of the complex impedance Zm was used to determine the specified capacity QA of the storage battery 40. However, the imaginary part ImZm may also be used, or both the real part ReZm and the imaginary part ImZm may also be used.

[0100] In the second embodiment, an AC signal is applied by the oscillator 51a when the complex impedance Zm is calculated, but the present invention is not limited to this. For example, when the frequency characteristics of the electric load 20 change during energization, the complex impedance Zm may be calculated by dividing the change in the battery voltage V by the change in the battery current I.

[0101] In the above embodiment, the predetermined capacity determination process is performed when the storage battery 40 is in a fully charged state. In addition, the predetermined capacity determination process may be performed on the condition that a predetermined number of heat quantity data items are stored before the storage battery 40 is in a fully charged state.

[0102] The control device and the method described in the present disclosure may be realized by a dedicated computer provided by configuring a processor and a memory programmed to execute one or more functions embodied in a computer program. Alternatively, the control device and the method described in the present disclosure may be realized by a dedicated computer provided by configuring a processor with one or more dedicated hardware logic circuits. Alternatively, the control device and the method described in the present disclosure may be realized by one or more dedicated computers configured by a combination of a processor and a memory programmed to execute one or more functions and a processor configured with one or more hardware logic circuits. In addition, the computer program may be stored in a computer-readable non-transitory tangible recording medium as instructions executed by the computer. [Explanation of symbols]

[0103] 40...storage battery, 53...control device.

Claims

1. This is applied to a storage battery (40) in which a change in reaction heat amount occurs at a predetermined capacity when the storage capacity changes due to the passage of current, a data storage unit that acquires a parameter that correlates with a reaction heat amount of the storage battery during energization and stores time-series heat amount data consisting of the parameter and the storage capacity; a division unit that divides the heat quantity data stored by the data storage unit into a first data group having a capacity lower than a predetermined boundary and a second data group having a capacity higher than the boundary; an approximation calculation unit that calculates a first approximation function obtained by approximating the first data group with a linear function and a second approximation function obtained by approximating the second data group with a linear function; an error sum calculation unit that calculates an error sum that is a sum of an approximation error between the first approximation function and each of the heat quantity data in the first data group and an approximation error between the second approximation function and each of the heat quantity data in the second data group; an acquisition unit that changes the boundary to a low capacity side or a high capacity side, and causes the approximation calculation unit to calculate the first approximation function and the second approximation function and the error sum calculation unit to calculate an error sum for each changed boundary, thereby acquiring a plurality of error sums; a determination unit that determines the predetermined capacity of the storage battery based on the first approximation function and the second approximation function that correspond to a minimum error sum among the plurality of error sums, the parameter is a battery temperature indicating a temperature of the storage battery; The approximation calculation unit calculates the first approximation function and the second approximation function using time-series heat quantity data consisting of the battery temperature and the power storage capacity.

2. This is applied to a storage battery (40) in which a change in reaction heat amount occurs at a predetermined capacity when the storage capacity changes due to the passage of current, a data storage unit that acquires a parameter that correlates with a reaction heat amount of the storage battery during energization and stores time-series heat amount data consisting of the parameter and the storage capacity; a division unit that divides the heat quantity data stored by the data storage unit into a first data group having a capacity lower than a predetermined boundary and a second data group having a capacity higher than the boundary; an approximation calculation unit that calculates a first approximation function obtained by approximating the first data group with a linear function and a second approximation function obtained by approximating the second data group with a linear function; an error sum calculation unit that calculates an error sum that is a sum of an approximation error between the first approximation function and each of the heat quantity data in the first data group and an approximation error between the second approximation function and each of the heat quantity data in the second data group; an acquisition unit that changes the boundary to a low capacity side or a high capacity side, and causes the approximation calculation unit to calculate the first approximation function and the second approximation function and the error sum calculation unit to calculate an error sum for each changed boundary, thereby acquiring a plurality of error sums; a determination unit that determines the predetermined capacity of the storage battery based on the first approximation function and the second approximation function that correspond to a minimum error sum among the plurality of error sums, The parameter is the impedance of the battery; The approximation calculation unit calculates the first approximation function and the second approximation function using time-series heat quantity data consisting of the impedance and the power storage capacity.

3. an impedance calculation unit that acquires a response signal of the storage battery in response to a predetermined AC signal while the storage battery is being applied with the AC signal, and calculates the impedance based on the response signal; The battery monitoring device according to claim 2 , wherein the frequency of the AC signal is set to a frequency equal to or lower than an ohmic frequency corresponding to an ohmic resistance of the storage battery.

4. This is applied to a storage battery (40) in which a change in reaction heat amount occurs at a predetermined capacity when the storage capacity changes due to the passage of current, a data storage unit that acquires a parameter that correlates with a reaction heat amount of the storage battery during energization and stores time-series heat amount data including the parameter and the storage capacity; a division unit that divides the heat quantity data stored by the data storage unit into a first data group having a capacity lower than a predetermined boundary and a second data group having a capacity higher than the boundary; an approximation calculation unit that calculates a first approximation function obtained by approximating the first data group with a linear function and a second approximation function obtained by approximating the second data group with a linear function; a slope determination unit that determines whether an absolute value of a slope of the first approximation function is greater than an absolute value of a slope of the second approximation function; an error sum calculation unit that calculates an error sum that is a sum of an approximation error between the first approximation function and each of the heat quantity data in the first data group and an approximation error between the second approximation function and each of the heat quantity data in the second data group, on condition that the slope determination unit determines that the absolute value of the slope of the first approximation function is greater than the absolute value of the slope of the second approximation function; an acquisition unit that changes the boundary to a low capacity side or a high capacity side, and causes the approximation calculation unit to calculate the first approximation function and the second approximation function and the error sum calculation unit to calculate an error sum for each changed boundary, thereby acquiring a plurality of error sums; A battery monitoring device (53) comprising: an identification unit that identifies the specified capacity of the storage battery based on the first approximation function and the second approximation function that correspond to the smallest error sum among the multiple error sums.

5. This is applied to a storage battery (40) in which a change in reaction heat amount occurs at a predetermined capacity when the storage capacity changes due to the passage of current, a data storage unit that acquires a parameter that correlates with a reaction heat amount of the storage battery during energization and stores time-series heat amount data consisting of the parameter and the storage capacity; a division unit that divides the heat quantity data stored by the data storage unit into a first data group having a capacity lower than a predetermined boundary and a second data group having a capacity higher than the boundary; an approximation calculation unit that calculates a first approximation function obtained by approximating the first data group with a linear function and a second approximation function obtained by approximating the second data group with a linear function; an error sum calculation unit that calculates an error sum that is a sum of an approximation error between the first approximation function and each of the heat quantity data in the first data group and an approximation error between the second approximation function and each of the heat quantity data in the second data group; an acquisition unit that changes the boundary to a low capacity side or a high capacity side, and causes the approximation calculation unit to calculate the first approximation function and the second approximation function and the error sum calculation unit to calculate an error sum for each changed boundary, thereby acquiring a plurality of error sums; an identification unit that identifies the predetermined capacity of the storage battery based on the first approximation function and the second approximation function corresponding to a minimum error sum among the plurality of error sums; a charging current storage unit that stores, when the storage battery is charged, charging current data in a time series until the storage battery is fully charged; an integrated value calculation unit that uses the charging current data to calculate an integrated current value of a charging current that flows through the storage battery during a period from the predetermined capacity specified by the specification unit to a fully charged state; and a degradation state determination unit that determines a degradation state of the storage battery based on the current integrated value.

6. the data storage unit stores the heat quantity data in chronological order during charging of the storage battery; The battery monitoring device according to claim 1 , wherein the acquisition unit gradually changes the boundary from a fully charged side of the storage capacity of the storage battery to a lower capacity side.

7. The battery monitoring device according to any one of claims 1 to 6, wherein the storage battery includes graphite in a negative electrode.

8. The battery monitoring device according to claim 7 , wherein the storage battery contains lithium iron phosphate in a positive electrode.

9. A program applied to a storage battery (40) in which a change in reaction heat quantity occurs at a predetermined capacity when the storage capacity changes with the passage of current, A computer (53), a data storage process for acquiring parameters correlated with the reaction heat amount of the storage battery during energization, and storing time-series heat amount data consisting of the parameters and the storage capacity; a division process of dividing the heat quantity data stored by the data storage process into a first data group having a capacity lower than a predetermined boundary and a second data group having a capacity higher than the boundary; an approximation calculation process for calculating a first approximation function obtained by approximating the first data group with a linear function and a second approximation function obtained by approximating the second data group with a linear function; an error sum calculation process for calculating an error sum which is the sum of an approximation error between the first approximation function and each of the heat quantity data in the first data group and an approximation error between the second approximation function and each of the heat quantity data in the second data group; an acquisition process of changing the boundary to a low capacity side or a high capacity side, and for each changed boundary, performing the calculation of the first approximation function and the second approximation function by the approximation calculation process and the calculation of an error sum by the error sum calculation process, thereby acquiring a plurality of error sums; a determination process for determining the predetermined capacity of the storage battery based on the first approximation function and the second approximation function corresponding to a minimum error sum among the plurality of error sums; the parameter is a battery temperature indicating a temperature of the storage battery; a program for calculating the first approximation function and the second approximation function using time-series heat quantity data including the battery temperature and the power storage capacity in the approximation calculation process;

10. A program applied to a storage battery (40) in which a change in reaction heat quantity occurs at a predetermined capacity when the storage capacity changes with the passage of current, A computer (53), a data storage process for acquiring parameters correlated with the reaction heat amount of the storage battery during energization, and storing time-series heat amount data consisting of the parameters and the storage capacity; a division process of dividing the heat quantity data stored by the data storage process into a first data group having a capacity lower than a predetermined boundary and a second data group having a capacity higher than the boundary; an approximation calculation process for calculating a first approximation function obtained by approximating the first data group with a linear function and a second approximation function obtained by approximating the second data group with a linear function; an error sum calculation process for calculating an error sum which is the sum of an approximation error between the first approximation function and each of the heat quantity data in the first data group and an approximation error between the second approximation function and each of the heat quantity data in the second data group; an acquisition process of changing the boundary to a low capacity side or a high capacity side, and for each changed boundary, performing the calculation of the first approximation function and the second approximation function by the approximation calculation process and the calculation of an error sum by the error sum calculation process, thereby acquiring a plurality of error sums; a determination process for determining the predetermined capacity of the storage battery based on the first approximation function and the second approximation function corresponding to a minimum error sum among the plurality of error sums; The parameter is the impedance of the battery; a program for calculating the first approximation function and the second approximation function using time-series heat quantity data including the impedance and the power storage capacity in the approximation calculation process;

11. A program applied to a storage battery (40) in which a change in reaction heat quantity occurs at a predetermined capacity when the storage capacity changes with the passage of current, A computer (53), a data storage process for acquiring parameters correlated with the reaction heat amount of the storage battery during energization, and storing time-series heat amount data consisting of the parameters and the storage capacity; a division process of dividing the heat quantity data stored by the data storage process into a first data group having a capacity lower than a predetermined boundary and a second data group having a capacity higher than the boundary; an approximation calculation process for calculating a first approximation function obtained by approximating the first data group with a linear function and a second approximation function obtained by approximating the second data group with a linear function; a gradient determination process for determining whether an absolute value of a gradient of the first approximation function is greater than an absolute value of a gradient of the second approximation function; an error sum calculation process for calculating an error sum which is the sum of an approximation error between the first approximation function and each of the heat quantity data in the first data group and an approximation error between the second approximation function and each of the heat quantity data in the second data group, on condition that it is determined by the slope determination process that the absolute value of the slope of the first approximation function is greater than the absolute value of the slope of the second approximation function; an acquisition process of changing the boundary to a low capacity side or a high capacity side, and for each changed boundary, performing the calculation of the first approximation function and the second approximation function by the approximation calculation process and the calculation of an error sum by the error sum calculation process, thereby acquiring a plurality of error sums; and a determination process for determining the specified capacity of the storage battery based on the first approximation function and the second approximation function corresponding to the smallest error sum among the plurality of error sums.

12. A program applied to a storage battery (40) in which a change in reaction heat quantity occurs at a predetermined capacity when the storage capacity changes with the passage of current, A computer (53), a data storage process for acquiring parameters correlated with the reaction heat amount of the storage battery during energization, and storing time-series heat amount data consisting of the parameters and the storage capacity; a division process of dividing the heat quantity data stored by the data storage process into a first data group having a capacity lower than a predetermined boundary and a second data group having a capacity higher than the boundary; an approximation calculation process for calculating a first approximation function obtained by approximating the first data group with a linear function and a second approximation function obtained by approximating the second data group with a linear function; an error sum calculation process for calculating an error sum which is the sum of an approximation error between the first approximation function and each of the heat quantity data in the first data group and an approximation error between the second approximation function and each of the heat quantity data in the second data group; an acquisition process of changing the boundary to a low capacity side or a high capacity side, and for each changed boundary, performing the calculation of the first approximation function and the second approximation function by the approximation calculation process and the calculation of an error sum by the error sum calculation process, thereby acquiring a plurality of error sums; a determination process for determining the predetermined capacity of the storage battery based on the first approximation function and the second approximation function corresponding to a minimum error sum among the plurality of error sums; a charging current storage process for storing time-series charging current data until the storage battery is fully charged when the storage battery is charged; an integrated value calculation process that uses the charging current data to calculate an integrated current value of the charging current that flows through the storage battery during a period from the predetermined capacity identified by the identification process to a fully charged state; and a degradation state determination process for determining a degradation state of the storage battery based on the current integrated value.

13. A battery monitoring method applied to a storage battery (40) in which a change in reaction heat quantity occurs at a predetermined capacity when the storage capacity changes with the passage of current, a data storage step of acquiring parameters correlated with the amount of heat of reaction of the storage battery during energization, and storing time-series heat amount data consisting of the parameters and the storage capacity; a division step of dividing the heat quantity data stored in the data storage step into a first data group having a capacity lower than a predetermined boundary and a second data group having a capacity higher than the boundary; an approximation calculation step of calculating a first approximation function obtained by approximating the first data group with a linear function and a second approximation function obtained by approximating the second data group with a linear function; an error sum calculation step of calculating an error sum which is the sum of an approximation error between the first approximation function and each of the heat quantity data in the first data group and an approximation error between the second approximation function and each of the heat quantity data in the second data group; an acquisition step of changing the boundary to a low capacity side or a high capacity side, and for each changed boundary, performing the calculation of the first approximation function and the second approximation function in the approximation calculation step and the calculation of an error sum in the error sum calculation step, thereby acquiring a plurality of error sums; and determining the predetermined capacity of the storage battery based on the first approximation function and the second approximation function corresponding to a minimum error sum among the plurality of error sums, the parameter is a battery temperature indicating a temperature of the storage battery; In the approximation step, the first approximation function and the second approximation function are calculated using time-series heat quantity data consisting of the battery temperature and the power storage capacity.

14. A battery monitoring method applied to a storage battery (40) in which a change in reaction heat quantity occurs at a predetermined capacity when the storage capacity changes with the passage of current, a data storage step of acquiring parameters correlated with the amount of heat of reaction of the storage battery during energization, and storing time-series heat amount data consisting of the parameters and the storage capacity; a division step of dividing the heat quantity data stored in the data storage step into a first data group having a capacity lower than a predetermined boundary and a second data group having a capacity higher than the boundary; an approximation calculation step of calculating a first approximation function obtained by approximating the first data group with a linear function and a second approximation function obtained by approximating the second data group with a linear function; an error sum calculation step of calculating an error sum which is the sum of an approximation error between the first approximation function and each of the heat quantity data in the first data group and an approximation error between the second approximation function and each of the heat quantity data in the second data group; an acquisition step of changing the boundary to a low capacity side or a high capacity side, and for each changed boundary, performing the calculation of the first approximation function and the second approximation function in the approximation calculation step and the calculation of an error sum in the error sum calculation step, thereby acquiring a plurality of error sums; and determining the predetermined capacity of the storage battery based on the first approximation function and the second approximation function corresponding to a minimum error sum among the plurality of error sums, The parameter is the impedance of the battery; In the approximation step, the first approximation function and the second approximation function are calculated using time-series heat quantity data made up of the impedance and the power storage capacity.

15. A battery monitoring method applied to a storage battery (40) in which a change in reaction heat quantity occurs at a predetermined capacity when the storage capacity changes with the passage of current, a data storage step of acquiring parameters correlated with the amount of heat of reaction of the storage battery during energization, and storing time-series heat amount data consisting of the parameters and the storage capacity; a division step of dividing the heat quantity data stored in the data storage step into a first data group having a capacity lower than a predetermined boundary and a second data group having a capacity higher than the boundary; an approximation calculation step of calculating a first approximation function obtained by approximating the first data group with a linear function and a second approximation function obtained by approximating the second data group with a linear function; a slope determination step of determining whether an absolute value of the slope of the first approximation function is greater than an absolute value of the slope of the second approximation function; an error sum calculation step of calculating an error sum which is the sum of an approximation error between the first approximation function and each of the heat quantity data in the first data group and an approximation error between the second approximation function and each of the heat quantity data in the second data group, on condition that it is determined in the slope determination step that the absolute value of the slope of the first approximation function is greater than the absolute value of the slope of the second approximation function; an acquisition step of changing the boundary to a low capacity side or a high capacity side, and for each changed boundary, performing the calculation of the first approximation function and the second approximation function in the approximation calculation step and the calculation of an error sum in the error sum calculation step, thereby acquiring a plurality of error sums; a determination step of determining the specified capacity of the storage battery based on the first approximation function and the second approximation function corresponding to the smallest error sum among the multiple error sums.

16. A battery monitoring method applied to a storage battery (40) in which a change in reaction heat quantity occurs at a predetermined capacity when the storage capacity changes with the passage of current, a data storage step of acquiring parameters correlated with the amount of heat of reaction of the storage battery during energization, and storing time-series heat amount data consisting of the parameters and the storage capacity; a division step of dividing the heat quantity data stored in the data storage step into a first data group having a capacity lower than a predetermined boundary and a second data group having a capacity higher than the boundary; an approximation calculation step of calculating a first approximation function obtained by approximating the first data group with a linear function and a second approximation function obtained by approximating the second data group with a linear function; an error sum calculation step of calculating an error sum which is the sum of an approximation error between the first approximation function and each of the heat quantity data in the first data group and an approximation error between the second approximation function and each of the heat quantity data in the second data group; an acquisition step of changing the boundary to a low capacity side or a high capacity side, and for each changed boundary, performing the calculation of the first approximation function and the second approximation function in the approximation calculation step and the calculation of an error sum in the error sum calculation step, thereby acquiring a plurality of error sums; determining the predetermined capacity of the storage battery based on the first approximation function and the second approximation function corresponding to a minimum error sum among the plurality of error sums; a charging current storage step of storing time-series charging current data until the storage battery is fully charged when the storage battery is charged; an integrated value calculation step of calculating an integrated current value of a charging current flowing through the storage battery during a period from the predetermined capacity specified in the specification step to a fully charged state, using the charging current data; and determining a deterioration state of the storage battery based on the current integrated value.

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