Battery state estimation device, power system

Abstract

To provide a technique which allows for accurately estimating SOH (of a battery) without relying on a computation standard for capacity change when obtaining SOH.SOLUTION: A battery state estimation device of the present invention is configured to identify a first period and a second period within a rest period after the completion of charging or discharging of a battery, and refer to a relationship between an estimated value of the state of deterioration of the battery obtained using an output voltage difference in the second period and a measured value of the state of deterioration to estimate the measured value.SELECTED DRAWING: Figure 5A

Description

[Technical field]

[0001] The present invention relates to a technique for estimating a state of a battery. [Background technology]

[0002] The state of health (SOH) of a battery can be estimated or measured by various methods. One method of measuring SOH is to calculate the SOH by the ratio of a specified charge / discharge capacity to the actual charge / discharge capacity when the battery is charged / discharged to its upper or lower limit.

[0003] The following Patent Document 1 describes a method for estimating the SOH of a battery. The document aims to "provide a degradation state estimation device and a degradation state estimation method for estimating the degradation state of a battery mounted in an energy storage device with little power consumption," and discloses a technology in which "the battery degradation state estimation device discharges power from a secondary battery charged to a charging upper limit voltage, starts discharging, and measures the discharge voltage within a predefined time range after the time has elapsed when the transient response associated with the charge transfer in the secondary battery disappears, and estimates the degradation state of the battery from at least one estimated value of the remaining capacity, the charge / discharge efficiency, and the plateau end capacity using the difference voltage between the obtained discharge voltage and the charging upper limit voltage" (see abstract). [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2016-145795 A Summary of the Invention [Problem to be solved by the invention]

[0005] When estimating or measuring the SOH, for example, the SOH may be calculated based on the capacity change from full charge to full discharge, or the SOH may be calculated based on the capacity change from slightly before full charge to slightly before full discharge. In this way, when the capacity change that serves as the standard for calculating the SOH is not determined, it is difficult to obtain the SOH accurately. Therefore, it would be desirable to be able to obtain the SOH without relying on a calculation standard.

[0006] The present invention has been made in consideration of the above-mentioned problems, and aims to provide a technology that can accurately estimate SOH without relying on the calculation standard of capacity change when obtaining SOH. [Means for solving the problem]

[0007] The battery state estimation device of the present invention identifies a first period and a second period in a rest period after a battery has finished charging or discharging, and estimates the actual value by referring to the relationship between an estimated value of the battery's state of deterioration obtained using the difference in output voltage in the second period and the actual measured value of the state of deterioration. Effect of the Invention

[0008] According to the battery state estimating device of the present invention, it is possible to accurately estimate the SOH without relying on the calculation standard of the capacity change when acquiring the SOH. [Brief description of the drawings]

[0009] [Figure 1] FIG. 2 is a schematic diagram showing a procedure for actually measuring the deterioration state of a battery. [Diagram 2] 11A and 11B are schematic diagrams showing another procedure for actually measuring the deterioration state of a battery. [Diagram 3] 4 is a graph showing the change over time in the current and voltage output by a battery during a rest period after discharge. [Figure 4] 1 is an example of relational data describing the relationship between ΔVb and SOH. [Figure 5A]FIG. 10 is a diagram for explaining a procedure for estimating an actual measured value of SOH. [Figure 5B] 11A and 11B are diagrams illustrating another procedure for estimating the actual measured value of SOH. [Figure 5C] 11A and 11B are diagrams illustrating another procedure for estimating the actual measured value of SOH. [Figure 6] FIG. 1 is a circuit diagram of a battery pack that performs passive balance control. [Figure 7] 11 is a graph illustrating an example of the change over time in the output voltage of each battery cell when passive balance control is performed. [Figure 8] FIG. 11 is a diagram illustrating a learning process in the second embodiment. [Figure 9] FIG. 11 is a diagram for explaining the application process in the second embodiment. [Figure 10] 11 is a graph illustrating an example of the change over time in the output voltage of each battery cell when active balance control is performed. [Figure 11] 11 is a graph illustrating an example of variation in output voltage for each battery cell during a rest period after a discharge operation. [Figure 12] 13 is a diagram for explaining a procedure for estimating the SOH and internal resistance of a battery pack in the third embodiment. FIG. [Figure 13] 13 is a schematic diagram illustrating an application of a battery state estimating device according to a fourth embodiment. FIG. [Figure 14] FIG. 11 is a diagram illustrating an example of the configuration of a battery state estimating device 100 according to a fourth embodiment. [Figure 15] 13 is a diagram illustrating another example of the configuration of the battery state estimating device 100. FIG. [Figure 16] 1 shows a configuration example in which the detection unit 130 is connected to a battery 200. [Figure 17] 10 is a flowchart illustrating a procedure for a calculation unit 120 to calculate the SOH. [Figure 18] 1 is a graph showing the change over time in the current and voltage output by a battery 200 during a rest period after discharging. [Figure 19] 1 is a graph showing the change over time in the current and voltage output by a battery 200 during a rest period after charging. [Figure 20] 13 is a diagram showing a configuration of a relational table 141 and an example of data. FIG. [Figure 21] 2 is an example of a user interface presented by the battery state estimating device 100. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] <Embodiment 1> Figure 1 is a schematic diagram showing the procedure for measuring the deterioration state of a battery. The vertical axis indicates the output voltage of the battery, and the horizontal axis indicates the amount of charge stored in the battery. When a battery is discharged at a constant discharge current starting from a fully charged state, the capacity gradually decreases in proportion to the discharge time. The time required to discharge a battery to a fully discharged state represents the chargeable capacity of the battery. Therefore, the horizontal axis of Figure 1 corresponds to the capacity of the battery.

[0011] By actually fully discharging the battery, the chargeable capacity of the battery at that point in time can be measured. Figure 1 shows two measured values ​​(capacity 1 and capacity 2) as examples. If the chargeable capacity when there is no degradation is capacity 0, the ratio of the measured capacity to capacity 0 represents the degradation state at that point in time. For example, if the measured chargeable capacity is 95% of the capacity that should be able to be charged, then the SOH is 95%. Therefore, the SOH corresponding to each measurement result in Figure 1 can be calculated as follows:

[0012] SOH1[%]=capacity 1 / capacity 0×100 SOH2[%]=Capacity 2 / Capacity 0×100

[0013] Figure 2 is a schematic diagram showing another procedure for measuring the deterioration state of a battery. Unlike Figure 1, discharge starts when the battery output voltage is slightly lower than the fully charged state, and ends when the output voltage is slightly higher than the fully discharged state. The rest is the same as Figure 1. Therefore, the SOH corresponding to each measurement result in Figure 2 can be calculated as follows:

[0014] SOH3[%] = Capacity 3 / Capacity 0 x 100 SOH4[%] = Capacity 4 / Capacity 0 x 100

[0015] As can be seen from the comparison between Figures 1 and 2, the measured value of SOH varies depending on the definition of the start and end values ​​when actually charging and discharging. If the definition of the start and end values ​​is not shared among the parties involved, it is difficult to share the accurate value of SOH. Therefore, in the first embodiment of the present invention, a method is provided that can accurately obtain SOH without relying on the definition of the start and end values.

[0016] FIG. 3 is a graph showing the change over time in the current and voltage output by the battery during the rest period after discharge. ΔVa is the variation in the output voltage of the battery from the first calculation point after the end of the rest period to the first time when the first period ta has elapsed. ΔVb is the variation in the output voltage of the battery from the second calculation point after the first time to the second time when the second period tb has elapsed. The inventor has found that ΔVa is correlated with the internal resistance of the battery, and ΔVb is correlated with the SOH of the battery. In the present embodiment 1, this is utilized to estimate the SOH from ΔVb. Furthermore, the internal resistance of the battery can also be estimated from ΔVa. A specific estimation method will be described again in the following embodiment 5, and in the present embodiment 1, it is assumed that the SOH can be estimated using ΔVb.

[0017] Fig. 4 is an example of the relationship data describing the relationship between ΔVb and SOH. Here, an example is shown in which the relationship between the two can be expressed by a linear function, but the present invention is not limited to this. The relationship shown in Fig. 4 is obtained in advance and described in the relationship data, and the actual measurement value of ΔVb is applied to the relationship data, thereby obtaining an estimated value SOH_E of SOH.

[0018] When acquiring the actual value of ΔVb, it is not necessary to perform a discharge operation from full charge (or upper limit output voltage) to full discharge (or lower limit output voltage), but it is sufficient to perform a short discharge operation and measure the change in the output voltage thereafter. In other words, the procedure of estimating SOH using ΔVb can be performed in a short time. The discharge start voltage and discharge end voltage may each be any value. Details will be explained again in the embodiment 5 described later.

[0019] Fig. 5A is a diagram for explaining a procedure for estimating an actual measurement value of SOH. In the present embodiment 1, in consideration of the problems explained in Fig. 1 and Fig. 2, instead of actually measuring the actual measurement value of SOH, the current actual measurement value of SOH is estimated using the past actual measurement value of SOH. This method is divided into a learning process and an application process.

[0020] The learning process is a process of learning the relationship between SOH_E estimated using ΔVb and the measured SOH (called SOH_fig1). The actual value of ΔVb during the rest period after discharging the battery is obtained. SOH_E is calculated by applying ΔVb to the relationship in Figure 4. On the other hand, SOH_fig1 is measured for the same battery using the procedure described in Figure 1. The relationship between the two is plotted on a two-dimensional graph. This allows one measurement point to be obtained, as shown in the graph in the upper right of Figure 5A. By performing a similar procedure when the battery's deterioration state progresses, other measurement points can be obtained in the same way. For example, the time required to obtain measurement points can be shortened by progressing the battery's deterioration state through accelerated testing.

[0021] By following the above procedure, a plot showing the relationship between SOH_E and SOH_fig1 can be obtained in the learning process. A function that approximates this relationship can be obtained to show the relationship between the two. Here, an example of approximation using a linear function is shown, but the present invention is not limited to this.

[0022] In the application process, the actual measured value of ΔVb is obtained again. SOH_E is calculated by applying ΔVb to the relationship in Figure 4. SOH_fig1 can be calculated by applying the calculated SOH_E to the function that represents the relationship between SOH_E and SOH_fig1 obtained in the learning process. This makes it possible to estimate the actual value of SOH without actually measuring it.

[0023] FIG. 5B is a diagram for explaining another procedure for estimating the actual value of SOH. The learning process is the same as FIG. 5A, except that the actual value of SOH is measured according to FIG. 2. Here, the actual value of SOH is set as SOH_fig2. Since the procedure for measuring SOH is different from that of FIG. 5A, the function expressing the relationship between SOH_E and SOH_fig2 may be different from that of FIG. 5A. The subsequent procedure is the same as that of FIG. 5A.

[0024] FIG. 5C is a diagram for explaining another procedure for estimating the actual measured value of SOH. In FIG. 5A and FIG. 5B, the actual measured value of SOH is measured in the learning process. In contrast, there may be a case where information describing the results of measuring the SOH of a battery together with an actual battery sample is received from, for example, a battery shipping factory. FIG. 5C shows a procedure in such a case. In FIG. 5C, it is not necessary to actually measure the SOH in the learning process, but it is necessary to associate the SOH with ΔVb for the same battery sample.

[0025] In the learning process, ΔVb is obtained for each battery sample, and this is used to calculate SOH_E. Since the measured SOH value (called SOH_U) of that battery sample is already available as information, it is possible to associate SOH_E and SOH_U for that battery. The relationship between the two is plotted on a two-dimensional graph. This makes it possible to obtain one measurement point, as shown in the graph in the upper right of Figure 5C. Similarly, the relationship between SOH_E and SOH_U is plotted for other battery samples. If the SOH of each battery sample is different, it is possible to obtain the graph in the upper right of Figure 5C without performing an accelerated test. The subsequent steps are the same as those in Figure 5A.

[0026] <First embodiment: Summary> In the first embodiment, the first period ta and the second period tb in the rest period after discharge are specified, and the difference ΔVb in the output voltage in the second period tb is used to obtain an estimated SOH value SOH_E, and the actual measured value of SOH is obtained, thereby obtaining the relationship between the two in advance. The actual measured value of ΔVb is used again to newly calculate SOH_E, which is then used to estimate the actual measured value of SOH. When estimating the actual measured value of SOH, it is sufficient to newly obtain the actual measured value of ΔVb, so there is no effect due to the difference in the measurement procedures as in FIG. 1 and FIG. 2. This allows the actual measured value of SOH to be accurately estimated regardless of the measurement procedure of the actual measured value of SOH.

[0027] <Embodiment 2> An assembled battery composed of multiple battery cells may perform balance control to balance the operation of the battery cells. For example, passive balance control is a method in which a battery cell with a high state of charge (SOC) is discharged via a resistor to match it with a battery cell with the lowest SOC. A similar operation is performed when matching it with the most deteriorated battery cell. In a second embodiment of the present invention, a method for estimating an actual measured value of SOH in an assembled battery that performs passive balance control will be described.

[0028] Figure 6 is a circuit diagram of a battery pack that performs passive balance control. This circuit diagram is just one example, and other circuit configurations can be used as long as they can perform passive balance control. In the following, it is assumed that the actual measured value of SOH is estimated in a battery pack such as the one shown in Figure 6.

[0029] FIG. 7 is a graph illustrating the change over time in the output voltage of each battery cell when passive balance control is performed. The battery cell with the most advanced degradation is the first to reach a fully discharged state (or a lower limit voltage). The discharging operation of the battery pack also ends at this point. In this case, even though the battery pack as a whole is still capable of discharging, the discharging operation is terminated, so there is a possibility that the actual measured value of SOH cannot be accurately estimated using a method similar to that of the first embodiment. Therefore, in the second embodiment, a method is provided for estimating the SOH of the entire battery pack in consideration of the variations σ1 and σ2 in the output voltage of each battery cell shown in FIG. 7.

[0030] σ1 is the variation in output voltage caused by the variation in SOH of each battery cell, and the variation between battery cells is significant at the end of discharge. σ2 is the variation in output voltage caused by the variation in internal resistance of each battery cell, and occurs during discharge. The result of estimating the actual measured value of SOH is also affected by these variations. In the second embodiment, the result of estimating the actual measured value of SOH is corrected by a correction coefficient calculated based on these variations. Since σ1 and σ2 are the variations in output voltage, they can be treated as the standard deviation of the output voltage of each battery cell.

[0031] FIG. 8 is a diagram for explaining the learning process in the second embodiment. In the learning process, first, for the most deteriorated battery cell, the relationship between the SOH estimate value (called SOH_E_MIN) using ΔVb and the actual SOH value (called SOH_MIN) is obtained in the same manner as in the first embodiment. This relationship is shown in the first graph from the top of FIG. 8. This makes it possible to estimate the actual SOH value for the most deteriorated battery cell. Since the most deteriorated battery cell has the largest ΔVb, the SOH_E of the battery cell with the largest ΔVb can be set as SOH_E_MIN.

[0032] The SOH of each battery cell in Fig. 7 can be estimated in the same manner as in the first embodiment, using ΔVb of each battery cell. Since the SOH_E of each battery cell varies, a value representing the variation (e.g., standard deviation SOH_E_σ) can be obtained. On the other hand, the variation σ1 of the output voltage caused by the variation in SOH can be measured by actually performing a discharge operation. By obtaining the relationship between them each time the battery deterioration progresses, the relationship shown in the third graph from the top in Fig. 8 can be obtained.

[0033] The inventors have found that ΔVa in FIG. 2 correlates with the internal resistance of the battery. Therefore, by acquiring an actual measurement value of ΔVa for each battery cell, an estimated value R_E of the internal resistance of each battery cell can be calculated. The estimation procedure will be described again in the fifth embodiment described later. Since the internal resistance of each battery cell varies, a value representing the variation (e.g., standard deviation R_E_σ) can be obtained. On the other hand, the variation σ2 of the output voltage caused by the variation in the internal resistance can be actually measured by actually performing a discharge operation. By acquiring the relationship between them as the deterioration of the battery progresses, the relationship shown in the second graph from the top in FIG. 8 can be obtained.

[0034] FIG. 9 is a diagram for explaining the application process in the second embodiment. ΔVb is acquired for each battery cell constituting the battery pack, and SOH_E of each battery cell is calculated. The SOH_E of the battery cell with the largest ΔVb is used as SOH_E_MIN, and the actual measured value of SOH_MIN can be estimated by applying this to the relationship shown in the first graph from the top of FIG. 8. σ1 can be estimated by applying the standard deviation SOH_E_σ of SOH_E to the relationship shown in the third graph from the top of FIG. 8. Furthermore, ΔVa is acquired for each battery cell, and R_E of each battery is calculated, and σ2 can be estimated by applying the standard deviation R_E_σ to the relationship shown in the second graph from the top of FIG. 8.

[0035] SOH_MIN is an estimate of the actual measured SOH value of the most deteriorated battery cell. Since the SOH of the battery pack is considered to be greater than SOH_MIN, the SOH of the battery pack can be estimated by correcting SOH_MIN upward. This upward correction amount can be defined by a function f1(σ1) of σ1 and a function f2(σ2) of σ2. The specific content of each function can be obtained in advance, for example, by an experiment. Each function can be configured as a coefficient by which SOH_MIN is multiplied, or can be configured as any other correction amount. FIG. 9 shows an example of calculation configured as a multiplication coefficient.

[0036] <Embodiment 2: Summary> In the second embodiment, the SOH of each battery cell constituting the battery pack undergoing passive balance control is estimated by ΔVb of each battery cell, and the deterioration state (SOH_MIN) of the battery cell with the most advanced deterioration is corrected upward to estimate the actual SOH value of the battery pack. In this way, the actual SOH value can be estimated in the battery pack undergoing passive balance control in the same way as in the first embodiment.

[0037] In the second embodiment, SOH_E is calculated for each battery cell constituting the battery pack, and its standard deviation SOH_E_σ is calculated, and the relationship between SOH_E_σ and σ1 is obtained in advance. By referring to the relationship using the newly calculated SOH_E_σ, the actual value of σ1 can be estimated in the same way as SOH. This makes it possible to estimate the actual value of SOH_MIN and to estimate the upward correction amount. The internal resistance R_E of the battery cell and σ2 resulting from this can also be estimated in the same way.

[0038] <Embodiment 3> Active balance control may be used as a balance control method for a battery pack. Active balance control is a method for redistributing the energy of a battery cell with a high SOC to a battery cell with a low SOC. In a third embodiment of the present invention, a method for estimating the SOH in a battery pack that implements active balance control will be described.

[0039] Figure 10 is a graph illustrating the change over time in the output voltage of each battery cell when active balance control is performed. In active balance control, the capacity of each battery is smoothed, so the change over time in the output voltage converges to the average of each battery cell (line 1 in Figure 10). Therefore, when estimating the SOH and internal resistance of a battery pack, it is generally considered to be the case that the average of each battery cell is used.

[0040] However, if an out-of-group battery cell is present, the average value is influenced by the out-of-group cell, and the SOH and internal resistance of the battery pack are also estimated. Therefore, in the third embodiment, a procedure for estimating the SOH and internal resistance of the battery pack after removing the influence of the out-of-group cell will be described.

[0041] 11 is a graph illustrating the variation of the output voltage for each battery cell during the idle period after the discharge operation. By performing active balance control, the output voltage of each battery cell converges to the average value, but since the balance control is not completed immediately after the idle period, the variation for each cell can be clearly identified. Therefore, as in the first and second embodiments, the SOH of each cell can be estimated using ΔVb, and the internal resistance of each cell can be estimated using ΔVa.

[0042] FIG. 12 is a diagram for explaining the procedure for estimating the SOH and internal resistance of the battery pack in the third embodiment. As in the first embodiment, SOH_E is calculated using ΔVb of each battery cell. The calculated SOH_E is statistically processed to remove outliers, and then the average of SOH_E is calculated. This average value can be regarded as the SOH of the battery pack. Furthermore, as in the second embodiment, R_E is calculated using ΔVa of each battery cell. The calculated R_E is statistically processed to remove outliers, and then the average of R_E is calculated. This average value can be regarded as the internal resistance of the battery pack.

[0043] <Fourth embodiment> In a fourth embodiment of the present invention, a configuration example of a battery state estimating device that implements the method for estimating the SOH (or internal resistance, the same applies below) of a battery described in the first to third embodiments will be described.

[0044] FIG. 13 is a schematic diagram illustrating an application of the battery state estimation device according to the fourth embodiment. The battery state estimation device estimates the SOH of a battery according to each procedure described in the first to third embodiments. A battery (e.g., a battery cell, a battery module, a battery pack, etc.) that needs to be charged or discharged is connected to various devices. For example, a tester, a BMS (battery management system), a charger, etc. When a battery is connected to these devices, it is in a charging operation / discharging operation / resting state. Depending on where the algorithm for calculating the SOH is implemented, the SOH can be calculated, for example, on the above-mentioned device, or on a computer connected via a network such as a cloud server. The advantage of calculating on a device to which the battery is connected is that the battery state (voltage output by the battery, current output by the battery, temperature of the battery, etc.) can be acquired frequently.

[0045] The SOH calculated on the cloud system can also be sent to a user's computer. The user computer can use this data for a specific purpose, such as inventory management. The SOH calculated on the cloud system can be stored in the cloud platform operator's database and used for other purposes, such as optimizing electric vehicle exchange routes, energy management, etc.

[0046] Fig. 14 is a diagram showing an example of the configuration of a battery state estimating device 100 according to embodiment 4. In Fig. 14, the battery state estimating device 100 is a device that is connected to a battery 200 and receives a supply of power from the battery 200, and corresponds to the tester in Fig. 8. The battery state estimating device 100 includes a communication unit 110, a calculation unit 120, a detection unit 130, and a storage unit 140.

[0047] The detection unit 130 acquires a detected value V of the voltage output by the battery 200 and a detected value I of the current output by the battery 200. Optionally, a detected value T of the temperature of the battery 200 may also be acquired. These detected values ​​may be detected by the battery 200 itself and notified to the detection unit 130, or may be detected by the detection unit 130. Details of the detection unit 130 will be described later.

[0048] The calculation unit 120 estimates the SOH of the battery 200 using the detection value acquired by the detection unit 130. The estimation procedure is as described in the first to third embodiments. The communication unit 110 transmits the SOH estimated by the calculation unit 120 to the outside of the battery state estimation device 100. For example, these can be transmitted to a memory provided in a cloud system. The storage unit 140 stores the relationship data described in the first to third embodiments.

[0049] The calculation unit 120 can be configured by hardware such as a circuit device that implements its functions, or can be configured by a calculation device such as a CPU (Central Processing Unit) executing software that implements its functions.

[0050] Fig. 15 is a diagram showing another example configuration of battery state estimating device 100. Battery state estimating device 100 does not necessarily have to be a device that is directly connected to battery 200 to receive power supply, and shows a form that does not include communication unit 110 and detection unit 130 shown in Fig. 14. In Fig. 15, battery state estimating device 100 acquires voltage V, current I, and temperature T of battery 200 from communication unit 110. Specifically, detection unit 150 included in battery state estimating device 100 receives these detection values ​​via a network, for example, and calculation unit 120 calculates the SOH using these detection values.

[0051] 16 shows a configuration example when the detection unit 130 is connected to the battery 200. The detection unit 130 may be configured as a part of the battery state estimation device 100, or may be configured as a module separate from the battery state estimation device 100. The detection unit 130 includes a voltage sensor 131, a temperature sensor 132, and a current sensor 133 to acquire the voltage V, the temperature T, and the current I during charging and discharging operations of the battery 200.

[0052] The voltage sensor 131 measures the voltage across the battery 200 (the voltage output by the battery 200). The temperature sensor 132 is connected to, for example, a thermocouple provided in the battery 200, and measures the temperature of the battery 200 via the thermocouple. The current sensor 133 is connected to one end of the battery 200, and measures the current output by the battery 200. The temperature sensor 132 is optional and is not necessarily provided.

[0053] <Embodiment 5> In the fifth embodiment of the present invention, a specific method for estimating SOH using ΔVb and a specific method for estimating internal resistance using ΔVa will be described. The configuration of the battery state estimating device 100 is the same as in the fourth embodiment. After estimating the SOH and internal resistance, the process is the same as in the first to third embodiments.

[0054] Fig. 17 is a flowchart explaining the procedure for calculating the SOH by calculation unit 120. Calculation unit 120 starts this flowchart at an appropriate timing, such as when battery state estimation device 100 is started, when instructed to start this flowchart, or at a predetermined interval. Each step in Fig. 17 will be explained below.

[0055] (FIG. 17: Step S1701) The calculation unit 120 judges whether or not it is a rest period after charging or a rest period after discharging. If it is not currently in a rest period, this flowchart ends. If it is currently in a rest period, proceed to S1702. For example, a rest period after discharging can be judged by (a) the current output by the battery 200 changing from a negative value (I<0) toward zero, or (b) changing from a negative value to a value close to zero and stabilizing (|I|<threshold value), etc.

[0056] (FIG. 17: Step S1702) The calculation unit 120 calculates ΔVa and ΔVb. ΔVa is the amount of change in the output voltage of the battery 200 from a first calculation start point after the end of the rest period to a first time when a first period ta has elapsed. ΔVb is the amount of change in the output voltage of the battery 200 from a second calculation start point after the first time to a second time when a second period tb has elapsed. The calculation procedure will be described later.

[0057] (FIG. 17: Step S1703) The calculation unit 120 calculates the internal resistance Ri and SOH of the battery 200 according to the following formulas 1 and 2. Ri defines Ri as a function of ΔVa. Ri has a parameter (c_Ri_T) that varies with the temperature of the battery 200 and a parameter (c_Ri_I) that varies with the output current of the battery 200. SOH defines SOH as a function of ΔVb. SOHhas a parameter (c_SOH_T) that varies with the temperature of the battery 200, and a parameter (c_SOH_I) that varies with the output current of the battery 200. These parameters are defined by a relationship table 141 stored in the storage unit 140. Specific examples of each function and the relationship table 141 will be described later. Ri and f SOH is an equation formed based on experimental data for each lot, for example.

[0058] (Figure 17: Step S1703: Calculation formula) Ri=f Ri (ΔVa,c_Ri_T_1,c_Ri_T_2,···,c_Ri_I_1,c_Ri_I_2,···) (1) SOH=f SOH (ΔVb,c_SOH_T_1,c_SOH_T_2,···,c_SOH_I_1,c_SOH_I_2,···) (2)

[0059] FIG. 18 is a graph showing the change over time of the current and voltage output by the battery 200 during the rest period after discharge. ΔVa in S1702 is the fluctuation of the output voltage of the battery 200 from the first calculation time point at or after the end of discharge to the first time when the first period ta has elapsed. The inventor has found that the voltage fluctuation due to the internal resistance of the battery 200 is well reflected in the output voltage immediately after the end of discharge. In other words, it can be said that the fluctuation of the output voltage during this period (ΔVa) has a strong correlation with Ri. In this embodiment, this fact is utilized to estimate Ri by ΔVa. The optimal values ​​of the start time and duration of ta can be obtained based on the section from after the end of discharge to the maximum point of the slope change rate in the voltage change over time curve. In addition, when specifying the above-mentioned section, it is only necessary to appropriately operate it in a preferable manner, such as near both ends of the above-mentioned section or including both ends, depending on the type of battery, device, accuracy, etc.

[0060] The start time of ta does not necessarily have to be the same as the end time of discharge, but it is preferably close to the end time of discharge. The start time of tb does not necessarily have to be the same as the end time of ta. In any case, ta and tb have a relationship of ta < tb. Regarding the magnitudes of ΔVa and ΔVb, there may be cases where ΔVa is larger, or there may be cases where ΔVb is larger. Here, ta < tb is assumed, but depending on the type of battery, device, accuracy, etc., there may also be cases where ta > tb or ta = tb, so an appropriate preferable relationship may be set as needed.

[0061] It has been found from the experimental results of the present inventor that Ri and SOH can be accurately estimated even if the total of ta and tb is, for example, about several seconds. Therefore, according to the present embodiment, both Ri and SOH can be quickly estimated during the rest period.

[0062] FIG. 19 is a graph showing the change over time of the current and voltage output by the battery 200 during the rest period after charging. ΔVa in S1702 may be the variation in the output voltage of the battery 200 from the time when charging has ended or a later first starting point until the first time when the first period ta has elapsed. In this case, ΔVb in S1702 is the variation in the output voltage of the battery 200 from the time when the period ta has elapsed or a later second starting point until the second time when the second period tb has elapsed. The present inventor has found that even during the rest period after charging, ΔVa has a correlation with Ri, and ΔVb has a correlation with SOH. Therefore, in the present embodiment, ΔVa and ΔVb in S1702 may be obtained after either charging or discharging.

[0063] FIG. 20 is a diagram showing a configuration of the relationship table 141 and an example of data. The relationship table 141 is a data table that defines each parameter in Equation 1 and Equation 2. c_Ri_I and c_SOH_I vary depending on the output current of the battery 200, and are therefore defined for each output current value. c_Ri_T and c_SOH_T vary depending on the temperature of the battery 200, and are therefore defined for each temperature. These parameters may have different characteristics between the rest period after discharging and the rest period after charging, and therefore the relationship table 141 defines each parameter for each of these periods. The relationship table 141 may be configured as a part of the relationship tables described in the first to third embodiments, or may be configured as separate data.

[0064] f Ri When is a linear function of ΔVa, Ri can be expressed by, for example, the following formula 3. This is because the slope of Ri is affected by temperature and the intercept is affected by current. In this case, c_Ri_T and c_Ri_I are each one.

[0065] Ri=c_Ri_T_1×ΔVa+c_Ri_I_1 (3)

[0066] f SOH When is a linear function of ΔVb, SOH can be expressed by, for example, the following formula 4. This is because the slope of SOH is affected by temperature and the intercept is affected by current. In this case, there is one c_SOH_T and one c_SOH_I.

[0067] SOH=c_SOH_T_1×ΔVb+c_SOH_I_1 (4)

[0068] Fig. 21 is an example of a user interface presented by battery state estimation device 100. The user interface can be presented on a display device such as a display device. The user interface presents the results of calculations performed by calculation unit 120. Fig. 21 presents the results of estimating the actual measured values ​​of the SOH and internal resistance of the battery.

[0069] <Modifications of the present invention> The present invention is not limited to the above-described embodiment, and includes various modified examples. For example, the above-described embodiment has been described in detail to clearly explain the present invention, and is not necessarily limited to those having all of the configurations described. In addition, it is possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. In addition, it is possible to add, delete, or replace a part of the configuration of each embodiment with another configuration.

[0070] In the above embodiment, the SOH and internal resistance are estimated in the rest period after the discharge operation of the battery, but if a time-dependent change in the output voltage corresponding to these appears in the rest period after the charge operation, the SOH and internal resistance can be estimated in the same manner as in the above embodiment. Whether a time-dependent change correlated with the SOH and internal resistance appears in the rest period after the discharge operation, the rest period after the charge operation, or both depends on the characteristics of the battery. Therefore, the SOH and internal resistance can be estimated in any of these periods depending on the characteristics of the battery.

[0071] In the above embodiment, the battery state estimation device 100 and the battery 200 can also be configured as a power grid system made up of a plurality of batteries 200. The battery state estimation device 100 may estimate the SOH and internal resistance of the battery and control the operation of the battery 200, or the control of the battery 200 may be performed by a separate device. [Explanation of symbols]

[0072] 100: Battery state estimation device 110: Communications Department 120: Arithmetic section 130: Detection unit 140: Storage section 200:Battery

Claims

1. A battery state estimation device that estimates a state of a battery, a detection unit that acquires a detection value of a voltage output by the battery; A calculation unit that estimates the state of the battery; Equipped with The calculation unit specifies a first period from a first calculation start point after a termination point when charging or discharging of the battery is terminated to a first point when a first time has elapsed; The calculation unit specifies a second period from a second starting point after the first point in time to a second point in time when a second time has elapsed; The calculation unit obtains a difference in the voltage from a start to an end of the second period as a second period difference, the calculation unit obtains the estimated value of the state of deterioration by referring to data describing a relationship between the second period difference and the state of deterioration of the battery; the calculation unit acquires an actual measurement value of the deterioration state obtained by charging or discharging the battery, the calculation unit obtains the estimated value and the actual measured value for each degree of deterioration of the battery to obtain a first correlation between the estimated value and the actual measured value; The calculation unit acquires the second period difference again after acquiring the first correlation, and estimates the actual measurement value by referring to the first correlation using the acquired second period difference. A battery state estimating device comprising:

2. The calculation unit is A capacity change of the battery when the battery is not deteriorated and the battery is fully charged or fully discharged; and A capacity fluctuation of the battery when the battery is fully charged or fully discharged when the deterioration of the battery progresses; and The deterioration state is determined according to the ratio between 2. The battery state estimating device according to claim 1.

3. The calculation unit is When the battery is not deteriorated, a capacity change of the battery when the battery is charged or discharged so that the voltage changes from an upper limit voltage lower than the voltage at a fully charged state to a lower limit voltage higher than the voltage at a fully discharged state; and When the deterioration of the battery progresses, a capacity fluctuation of the battery when the battery is charged or discharged so that the voltage fluctuates from the upper limit voltage to the lower limit voltage; and The deterioration state is determined according to the ratio between 2. The battery state estimating device according to claim 1.

4. the calculation unit acquires information describing the actual measurement value for each of the plurality of batteries having different degradation states, thereby acquiring the actual measurement value for each of the batteries; the calculation unit obtains the second period difference for each of the batteries to obtain the estimated value for each of the batteries; The calculation unit obtains the first correlation by using the actual measurement value obtained for each of the batteries and the estimated value obtained for each of the batteries.

2. The battery state estimating device according to claim 1.

5. the calculation unit estimates the actual measurement value for a reference battery that is most deteriorated among the plurality of batteries on which passive balance control is being performed, in accordance with the first correlation; The calculation unit estimates a deterioration state of the battery pack formed by the plurality of batteries by correcting the actual measurement value estimated for the reference battery using the variation in the voltage at the time of completion of charging or discharging of each of the batteries.

2. The battery state estimating device according to claim 1.

6. The calculation unit calculates a first standard deviation of the estimated value by acquiring the estimated value for each of the batteries; the calculation unit calculates a second standard deviation of the voltage at the completion of charging or discharging by acquiring the voltage at the completion of charging or discharging for each of the batteries; The calculation unit obtains a second correlation between the first standard deviation and the second standard deviation for each degree of deterioration of the battery; the calculation unit acquires the second period difference again after acquiring the second correlation, and estimates the second standard deviation by referring to the second correlation using the acquired second period difference; The calculation unit estimates a deterioration state of the battery pack by correcting the actual measurement value estimated for the reference battery by the estimated second standard deviation.

6. The battery state estimating device according to claim 5.

7. the calculation unit obtains, for each of the batteries, a difference in the voltage from a start to an end of the first period as a first period difference; The calculation unit calculates a variation in the internal resistance of each of the batteries as a third standard deviation using the first period difference acquired for each of the batteries; the calculation unit calculates a fourth standard deviation of the voltage during charging or discharging by acquiring the voltage during charging or discharging for each of the batteries; The calculation unit obtains a third correlation between the third standard deviation and the fourth standard deviation for each degree of deterioration of the battery; the calculation unit acquires the third standard deviation again after acquiring the third correlation, and estimates the fourth standard deviation by referring to the third correlation using the acquired third standard deviation; The calculation unit estimates a deterioration state of the battery pack by correcting the actual measurement value estimated for the reference battery by the estimated fourth standard deviation.

6. The battery state estimating device according to claim 5.

8. The calculation unit acquires a degradation state for each of the plurality of batteries for which active balance control is being performed, and estimates a degradation state of the assembled battery formed by the plurality of batteries by removing outliers from the acquired degradation states and calculating an average value.

2. The battery state estimating device according to claim 1.

9. the calculation unit acquires, for each of the plurality of batteries for which active balance control is being performed, a difference in the voltage from a start to an end of the first period as a first period difference; The calculation unit obtains an internal resistance of each of the batteries using the first period difference obtained for each of the batteries; The calculation unit estimates the internal resistance of a battery pack formed by the plurality of batteries by removing outliers from the acquired internal resistance and calculating an average value.

2. The battery state estimating device according to claim 1.

10. The battery state estimation device further includes a user interface that presents the estimated actual measurement value.

2. The battery state estimating device according to claim 1.

11. The battery state estimation device according to claim 1 , The battery, A power system comprising:

Images