Secondary battery evaluation system and secondary battery evaluation method

Abstract

A secondary battery evaluation system according to one aspect of the present invention determines whether or not a secondary battery to be inspected is normal on the basis of a comparison of a plurality of first measurement values, obtained from a plurality of normal secondary batteries including at least normal secondary batteries having different SoCs from each other, and a second measurement value, obtained from the secondary battery to be inspected, or a comparison of a plurality of first calculated values, obtained on the basis of the plurality of first measurement values, and a second calculated value, obtained on the basis of the second measurement value.

Description

Secondary battery evaluation system and secondary battery evaluation method

[0001] The present technology relates to a secondary battery evaluation system and a secondary battery evaluation method.

[0002] In recent years, the use of lithium-ion secondary batteries has expanded to larger devices such as electric vehicles (EVs) and stationary battery storage systems (ESSs). Lithium-ion secondary batteries use rare metals such as lithium and cobalt as raw materials. Therefore, from the perspective of effective resource utilization, repurposing and reusing used batteries is being considered, particularly for lithium-ion secondary batteries used in large-scale devices. Repurposing refers to reusing used batteries for a purpose other than their original purpose. Reusing refers to reusing used batteries for the same purpose.

[0003] To promote the repurposing and reuse of used batteries, a technology is needed to evaluate whether used batteries can be reused. However, many conventional evaluation technologies require a long evaluation time. For example, the State of Health (SoH), which is often used for evaluation, is defined as the ratio of the discharge capacity of a test battery to the discharge capacity of a new battery. To measure the SoH, the test battery must be fully charged and then completely discharged. Therefore, when using the SoH for evaluation, a diagnostic time of several hours is required.

[0004] Simple evaluation methods without using SoH are disclosed in, for example, Patent Documents 1 and 2. Patent Document 1 discloses a technique for extracting battery impedance information from a transient response waveform after current interruption and evaluating the battery using the extracted impedance information. Patent Document 2 also discloses a technique for analyzing the results of AC impedance measurement using a unique method.

[0005] JP 2000-299137 A International Publication No. WO2013 / 115038 A

[0006] Incidentally, both of the techniques described in Patent Documents 1 and 2 are premised on adjusting the state of charge (SoC) of the battery under test before measurement. This is because the battery impedance is highly dependent on the SoC. However, adjusting the SoC often requires bringing the battery under test into a fully charged or fully discharged state. Therefore, the need to adjust the SoC makes it difficult to sufficiently shorten the evaluation time. Therefore, it is desirable to provide a secondary battery evaluation system and a secondary battery evaluation method that can shorten the evaluation time compared to methods that adjust the SoC.

[0007] A secondary battery evaluation system according to a first aspect of the present technology includes a memory and a processing circuit. The memory stores a plurality of first measured values ​​or a plurality of first calculated values. The plurality of first measured values ​​are measured values ​​obtained by responding to an external stimulus for each of a plurality of normal secondary batteries, the plurality of normal secondary batteries including at least normal secondary batteries having different SoCs. The plurality of first calculated values ​​are calculated values ​​obtained based on the plurality of first measured values. The processing circuit is capable of determining whether a test secondary battery is normal or not based on a first comparison or a second comparison. The first comparison refers to a comparison between the plurality of first measured values ​​obtained from the memory and a second measured value obtained by responding to an external stimulus for a test secondary battery having an unknown SoC. The second comparison refers to a comparison between the plurality of first calculated values ​​obtained from the memory and a second calculated value obtained based on the second measured values.

[0008] A secondary battery evaluation method according to a second aspect of the present technology includes the following three steps: (A) acquiring a plurality of first measured values ​​obtained by responding to an external stimulus for each of a plurality of normal secondary batteries having different OCs and known SoCs, or a plurality of first calculated values ​​obtained based on the plurality of first measured values; (B) acquiring a second measured value obtained by responding to an external stimulus for a test secondary battery having an unknown SoC, or a second calculated value obtained based on the second measured value; and (C) determining whether the test secondary battery is normal or not based on a comparison between the plurality of first measured values ​​and the second measured value, or a comparison between the plurality of first calculated values ​​and the second calculated value.

[0009] In a secondary battery evaluation system according to a first aspect of the present technology and a secondary battery evaluation method according to a second aspect of the present technology, whether a test secondary battery is normal or not is determined based on a comparison between a plurality of first measurement values ​​obtained from a plurality of normal secondary batteries having different SoCs and known SoCs and a second measurement value obtained from the test secondary battery. Also, in the secondary battery evaluation system according to the first aspect of the present technology and the secondary battery evaluation method according to the second aspect of the present technology, whether a test secondary battery is normal or not is determined based on a comparison between a plurality of first calculation values ​​obtained based on the plurality of first measurement values ​​and a second calculation value obtained based on the second measurement values.

[0010] In this way, multiple first measured values ​​or multiple first calculated values ​​obtained from multiple normal secondary batteries with different known SoCs are used as reference values. This makes it possible to determine whether a secondary battery under test is normal in an unknown state without adjusting the SoC in advance. As a result, evaluation time can be shortened compared to methods that adjust the SoC.

[0011] Note that the effects of the present technology are not necessarily limited to the effects described here, but may be any of a series of effects related to the present technology described below.

[0012] FIG. 1 is a diagram illustrating an example of functional blocks of a secondary battery evaluation system according to a first embodiment of the present technology. FIG. 2 is a diagram illustrating an example of an equivalent circuit of a secondary battery to be evaluated by the secondary battery evaluation system of FIG. 1. FIG. 3 is a diagram illustrating an example of an impedance spectrum of a normal battery at SoC 100% (fully charged). FIG. 4 is a diagram illustrating an example of Mahalanobis distances (degrees of abnormality) of multiple normal batteries. FIG. 5 is a diagram illustrating an example of Mahalanobis distances (degrees of abnormality) of multiple normal batteries (indexes 1 to 250) and an example of Mahalanobis distances (degrees of abnormality) of multiple secondary batteries to be evaluated (indexes 251 to 290). FIG. 6 is a diagram illustrating an example of Euclidean distances (degrees of abnormality) of multiple normal batteries (indexes 1 to 250) and an example of Euclidean distances (degrees of abnormality) of multiple secondary batteries to be evaluated (indexes 251 to 290). FIG. 7 is a diagram illustrating an example of an evaluation procedure for a test secondary battery in the secondary battery evaluation system of FIG. 1. FIG. 8 is a diagram illustrating an example of functional blocks of a secondary battery evaluation system according to a second embodiment of the present technology. Fig. 9 is a diagram showing a modified example of data used to evaluate a test secondary battery in the first and second embodiments and their modifications. Fig. 10 is a diagram showing a modified example of data used to evaluate a test secondary battery in the first and second embodiments and their modifications. Fig. 11 is a diagram showing a modified example of an equivalent circuit of a secondary battery to be evaluated by the secondary battery evaluation system according to the first and second embodiments and their modifications.

[0013] Hereinafter, embodiments of the present technology will be described in detail with reference to the drawings. The description will be made in the following order: 1. First embodiment (FIGS. 1 to 7) 2. Second embodiment (FIG. 8) 3. Modifications common to each embodiment (FIGS. 9 to 11)

[0014] 1. First Embodiment [Configuration] A secondary battery evaluation system according to a first embodiment of the present technology will be described. FIG. 1 illustrates an example of functional blocks of the secondary battery evaluation system according to the first embodiment of the present technology. For example, as shown in FIG. 1 , the secondary battery evaluation system includes a power supply device 100 and a server device 300. The server device 300 corresponds to a specific example of a "secondary battery evaluation device" according to an embodiment of the present disclosure. The power supply device 100 and the server device 300 are capable of communicating with each other via a communication network 400. The communication network 400 is configured to include, for example, the Internet, a cloud network, or a network specific to a business operator.

[0015] A secondary battery 200, which is the subject of evaluation in the secondary battery evaluation system, is connected to the power supply device 100. The secondary battery 200 is a lithium-ion secondary battery. The secondary battery 200 may be a unit cell, a battery block in which a plurality of unit cells are connected, or an assembled battery in which a battery block and accessories are integrally packed. In the assembled battery, a plurality of lithium-ion secondary batteries are connected in series. The assembled battery may also include a plurality of lithium-ion secondary batteries electrically connected in parallel.

[0016] FIG. 2 shows an example of an equivalent circuit of the secondary battery 200. As shown in FIG. 2, the secondary battery 200 is represented by an equivalent circuit consisting of six elements (impedance parameters): inductance L, solution resistance Rs, charge transfer resistance Rct, Warburg impedance σ, constant phase element CPE related to electric double layer capacitance Cdl, and differential capacitance C'. The six impedance parameters correspond to the evaluation parameters of the secondary battery. The following seven circuit constants of these six elements are calculated by curve fitting to the impedance spectrum of the secondary battery 200 (see FIG. 3):

[0017] (Seven circuit constants) Inductance L Solution resistance Rs Charge transfer resistance Rct Warburg impedance σ Parameters p and T for describing the constant phase element CPE (hereinafter referred to as CPE(p) and CPE(T) respectively) Differential capacitance C′

[0018] The inductance L, solution resistance Rs, charge transfer resistance Rct, Warburg impedance σ, parameter CPE(p), parameter CPE(T), and differential capacitance C' can be obtained, for example, as the output of analysis software EIS manufactured by Hokuto Denko Corporation. The electric double layer capacitance Cdl can also be used as the eighth circuit constant. Cdl is calculated using the following formula described in "Electrochemical Impedance Method" by Itagaki Masayuki, Maruzen Publishing (p. 84): Cdl = CPE(T) (1 / CPE(p)) Rct ((1-CPE(p)) / CPE(p))

[0019] The power supply device 100 is a device that charges and discharges the secondary battery 200, and is a network communication type device that has the function of communicating with external devices. The power supply device 100 has, for example, a charge / discharge circuit 110, an IV measurement circuit 120, a data processing unit 130, a memory unit 140, a display unit 150, and a communication unit 160.

[0020] The charge / discharge circuit 110 charges and discharges the secondary battery 200. The IV measurement circuit 120 measures the voltage and current of the secondary battery 200. In the secondary battery evaluation mode, the charge / discharge circuit 110 applies a voltage to the secondary battery 200 for a predetermined time while sweeping the frequency of the voltage applied as an external stimulus to the secondary battery 200 in a range from 100 kHz to 10 mHz, for example.

[0021] In the secondary battery evaluation mode, the IV measurement circuit 120 measures the voltage and current of the secondary battery 200 for a predetermined time to obtain measurement values ​​(current values, voltage values), and outputs the obtained measurement values ​​to the data processing unit 130. If the secondary battery 200 is a used secondary battery, the IV measurement circuit 120 outputs the obtained measurement values ​​to the data processing unit 130 as test measurement values ​​141. The secondary battery 200 may also be a new (unused) secondary battery. In this case, the IV measurement circuit 120 outputs the obtained measurement values ​​to the data processing unit 130 as normal measurement values ​​142. The test measurement values ​​141 and normal measurement values ​​142 are time-series data of current values ​​and voltage values ​​obtained during frequency sweeping.

[0022] In the secondary battery evaluation mode, the IV measurement circuit 120 may acquire measurement values ​​(current values, voltage values) by measuring the voltages and currents of multiple secondary batteries 200 (normal secondary batteries) that are different from each other and have known SoCs for a predetermined time, and output the acquired multiple measurement values ​​as multiple normal measurement values ​​142 to the data processing unit 130. The "normal" in the case of a normal secondary battery refers to the fact that the normal electrical characteristics do not deviate from the design values ​​(e.g., standard set values) of the secondary battery.

[0023] The data processing unit 130 includes, for example, a central processing unit (CPU). The data processing unit 130 processes the measurement values ​​input from the charge / discharge circuit 110. When the data processing unit 130 receives a test measurement value 141 of the secondary battery 200 (test secondary battery) from the charge / discharge circuit 110, the data processing unit 130 first stores the test measurement value 141 in the storage unit 140. The data processing unit 130 then outputs the test measurement value 141 to the server device 300 via the communication unit 160. In response to the output of the test measurement value 141, the data processing unit 130 acquires an evaluation result of the secondary battery 200 (test secondary battery) from the server device 300 via the communication unit 160. The data processing unit 130 generates a video signal for displaying a video including the acquired evaluation result, and outputs the video signal to the display unit 150.

[0024] When the normal measurement value 142 of the secondary battery 200 (normal secondary battery) is input from the charge / discharge circuit 110, the data processing unit 130 first stores the normal measurement value 142 in the storage unit 140. The data processing unit 130 then outputs the input normal measurement value 142 to the server device 300 via the communication unit 160.

[0025] The storage unit 140 is configured, for example, by a non-volatile memory such as a flash memory. The storage unit 140 stores data input from the data processing unit 130 (for example, a test measurement value 141 and a plurality of normal measurement values ​​142). The display unit 150 is configured, for example, to include a liquid crystal panel or an organic EL panel. The display unit 150 displays an image based on the image signal input from the data processing unit 130.

[0026] The communication unit 160 is a communication interface that communicates with the server device 300 via the communication network 400. The communication unit 160 transmits data input from the data processing unit 130 (e.g., the test measurement value 141 and the plurality of normal measurement values ​​142) to the server device 400 via the communication network 400. In response to the transmission of the test measurement value 141, the communication unit 160 receives an evaluation result of the secondary battery 200 (test secondary battery) from the server device 400 via the communication network 400. The communication unit 160 outputs the received evaluation result to the data processing unit 130.

[0027] The server device 300 includes, for example, a communication unit 310, a data processing unit 320, and a storage unit 330. The communication unit 310 is a communication interface that communicates with the power supply device 100 via the communication network 400. When the communication unit 310 receives data (e.g., the test measurement value 141 and the normal measurement value of the secondary battery 200 (normal secondary battery)) from the power supply device 100 via the communication network 400, the communication unit 310 outputs the received data to the data processing unit 320. In response to the output of the test measurement value 141 to the data processing unit 320, the communication unit 310 acquires the evaluation result of the secondary battery 200 (test secondary battery) from the data processing unit 320. The communication unit 310 transmits the acquired evaluation result to the power supply device 100 via the communication network 400.

[0028] The storage unit 330 is configured with a nonvolatile memory such as a flash memory, and stores data input from the data processing unit 320 (e.g., the test measurement value 141, the plurality of normal measurement values ​​142, the normal impedance parameter 331 described below, and the test impedance parameter 332 described below).

[0029] When the test measurement value 141 and the plurality of normal measurement values ​​142 are input from the communication unit 310, the data processing unit 320 stores the input test measurement value 141 and the plurality of normal measurement values ​​142 in the storage unit 330. When the normal measurement values ​​142 are input, the data processing unit 320 calculates the impedance spectrum of the secondary battery 200 (normal secondary battery) based on the input normal measurement values ​​142 (see FIG. 3 ). Every time a normal measurement value 142 is input, the data processing unit 320 calculates the impedance spectrum of the secondary battery 200 (normal secondary battery) based on the input normal measurement values ​​142.

[0030] The data processing unit 320 further calculates a plurality of impedance parameters of the secondary battery 200 (normal secondary battery) by performing curve fitting on the calculated impedance spectrum. At this time, the calculated plurality of impedance parameters include at least two of the six impedance parameters shown in FIG. 2 . The combination of the calculated plurality of impedance parameters is not particularly limited. The data processing unit 320 stores the calculated plurality of impedance parameters in the storage unit 330 as normal impedance parameters 331.

[0031] The data processing unit 320 calculates a plurality of impedance parameters of the secondary battery 200 (normal secondary battery) each time a normal measurement value 142 is input. The data processing unit 320 stores the calculated plurality of impedance parameters as normal impedance parameters 331 in the storage unit 330. As a result, the storage unit 330 stores a plurality of normal impedance parameters 331.

[0032] Note that the plurality of normal impedance parameters 331 obtained from the plurality of secondary batteries 200 (normal secondary batteries) whose SoCs are different from one another and known may be stored in advance in the storage unit 330. In the following, it is assumed that the plurality of normal impedance parameters 331 obtained from the plurality of secondary batteries 200 (normal secondary batteries) whose SoCs are different from one another and known are stored in advance in the storage unit 330. In other words, it is assumed that the plurality of normal impedance parameters 331 obtained from the plurality of secondary batteries 200 (normal secondary batteries) whose SoCs are different from one another and known are stored in the storage unit 330 in advance before evaluation of the secondary battery 200 (test secondary battery) is performed.

[0033] When the test measurement values ​​141 are input, the data processing unit 320 calculates the impedance spectrum of the secondary battery 200 (test secondary battery) based on the input test measurement values ​​141. The data processing unit 320 further calculates a plurality of impedance parameters of the secondary battery 200 (test secondary battery) by performing curve fitting on the calculated impedance spectrum. At this time, the calculated plurality of impedance parameters include at least two of the six impedance parameters shown in FIG. 2 . The combination of the calculated plurality of impedance parameters is not particularly limited. The data processing unit 320 stores the calculated plurality of impedance parameters in the storage unit 330 as test impedance parameters 332.

[0034] The data processing unit 320 further calculates a plurality of impedance parameters of the secondary battery 200 (normal secondary battery) by performing curve fitting on the calculated impedance spectrum. At this time, the calculated plurality of impedance parameters include at least two of the six impedance parameters shown in Fig. 2. The combination of the calculated plurality of impedance parameters is not particularly limited.

[0035] The data processing unit 320 determines whether the secondary battery 200 (test secondary battery) is normal or not based on a comparison between a plurality of normal impedance parameters 331 and test impedance parameters 332. Specifically, the data processing unit 320 first sets each normal impedance parameter 331 as a first vector and each test impedance parameter 332 as a second vector. The data processing unit 320 then calculates the distances between the plurality of first vectors and the second vector, and determines whether the secondary battery 200 (test secondary battery) is normal or not based on the plurality of distances obtained by the calculation.

[0036] The data processing unit 320 calculates the Mahalanobis distance as, for example, the distance between a plurality of first vectors and a plurality of second vectors. The Mahalanobis distance can be calculated using, for example, the formula shown in Fig. 4. In Fig. 4, among the normal impedance parameters 331 of 250 normal secondary batteries, the Mahalanobis distance between a specific normal impedance parameter 331 and a plurality of other normal impedance parameters 331 is expressed as an abnormality degree d.

[0037] 4, if it is desired to determine that 99% of the Mahalanobis distances (degrees of abnormality d) are normal values ​​among 250 Mahalanobis distances (degrees of abnormality d), the threshold value th1 used for this determination can be, for example, the average value of the second Mahalanobis distance (degrees of abnormality d) from the left in Fig. 4 and the third Mahalanobis distance (degrees of abnormality d) from the left in Fig. 4. The reason for focusing on the second and third distances is that, since 99% of the total 250 distances are normal values ​​and 1% are abnormal values, when the abnormal values ​​are sorted in ascending order, 250 x 0.01 = 2.5 is considered to be the threshold value. 4, if it is desired to determine that 95% of the Mahalanobis distances (degrees of abnormality d) among 250 Mahalanobis distances (degrees of abnormality d) are normal, the threshold value th2 used for this determination can be, for example, the average value of the twelfth Mahalanobis distance (degrees of abnormality d) from the left in FIG. 4 and the thirteenth Mahalanobis distance (degrees of abnormality d) from the left in FIG. 4. The reason for focusing on the twelfth and thirteenth distances is that, since 95% of the total 250 values ​​are considered to be normal values ​​and 5% are considered to be abnormal values, when the abnormal values ​​are sorted in ascending order, 250 x 0.05 = 12.5 is considered to be the threshold value. Threshold value th1 or threshold value th2 may be stored in advance in the storage unit 330.

[0038] 5 shows an example of the Mahalanobis distances (degrees of abnormality d) of a plurality of normal secondary batteries (indexes 1 to 250) and an example of the Mahalanobis distances (degrees of abnormality d) of a plurality of test secondary batteries (indexes 251 to 290). When threshold value th1 is used as the threshold for determining whether secondary battery 200 (test secondary battery) is normal or not, it can be seen that most of the Mahalanobis distances (degrees of abnormality d) for indexes 251 to 290 exceed threshold value th1. It can also be seen that when threshold value th2 is used as the threshold for determining whether secondary battery 200 (test secondary battery) is normal or not, the number of normal value samples is greater than when threshold value th1 is used.

[0039] Fig. 6 shows examples of Euclidean distances (abnormality levels d) for multiple normal secondary batteries (indexes 1 to 250) and examples of Euclidean distances (abnormality levels d) for multiple test secondary batteries (indexes 251 to 290). In Fig. 6, threshold value th3 is a threshold value for determining that 99% of the 250 Euclidean distances (abnormality levels d) are normal. In Fig. 6, threshold value th4 is a threshold value for determining that 95% of the 250 Euclidean distances (abnormality levels d) are normal.

[0040] It can be seen that the distribution of the plots in Figure 6 is wider than the distribution of the plots in Figure 5. Mahalanobis distance is a generalization of Euclidean distance and is an index that fairly evaluates each parameter that makes up a vector. Therefore, when evaluating whether a secondary battery under test is normal by applying a threshold value to a vector, it is preferable to use Mahalanobis distance rather than Euclidean distance.

[0041] [Evaluation Procedure] Next, a procedure for evaluating whether the secondary battery 200 (test secondary battery) is normal or not will be described. Fig. 7 shows an example of a procedure for evaluating whether the secondary battery 200 (test secondary battery) is normal or not.

[0042] The power supply device 100 applies a voltage to the secondary battery 200 (test secondary battery) for a predetermined time while sweeping the frequency of the voltage to be applied as an external stimulus to the secondary battery 200, for example, in a range from 100 kHz to 10 mHz. At this time, the power supply device 100 measures the voltage and current of the secondary battery 200 (test secondary battery) for the predetermined time and acquires the measurement values ​​as test measurement values ​​141. The power supply device 100 transmits the acquired test measurement values ​​141 to the server device 400 via the communication network 400.

[0043] The server device 400 receives (acquires) the test measurement values ​​141 of the secondary battery 200 (test secondary battery) from the power supply device 100 via the communication network 400 (step S101). The server device 400 calculates the impedance spectrum of the secondary battery 200 (test secondary battery) based on the received (acquired) test measurement values ​​141. The server device 400 further calculates a plurality of impedance parameters of the secondary battery 200 (test secondary battery) by performing curve fitting on the calculated impedance spectrum (step S102). The server device 400 stores the calculated plurality of impedance parameters in the storage unit 330 as test impedance parameters 332.

[0044] The server device 400 acquires a plurality of normal impedance parameters 331 from the storage unit 330 (step S103). The server device 400 determines whether the secondary battery 200 (test subject secondary battery) is normal or not based on a comparison between the plurality of normal impedance parameters 331 and the test impedance parameters 332. Specifically, the data processing unit 320 first sets each normal impedance parameter 331 as a first vector and the test impedance parameter 332 as a second vector.

[0045] The data processing unit 320 then determines whether the secondary battery 200 (test secondary battery) is normal based on a comparison between the multiple first vectors and the second vectors. Specifically, the data processing unit 320 first calculates the distance between each first vector and the second vector for each first vector. The data processing unit 320 calculates the Mahalanobis distance as the distance between each first vector and the second vector (step S104).

[0046] The server device 400 then applies the k-nearest neighbor algorithm to the calculated distances to determine whether the secondary battery 200 (test secondary battery) is normal. Specifically, the data processing unit 320 first selects the kth longest distance from the calculated distances as the evaluation distance ds (step S105). The data processing unit 320 then compares the evaluation distance ds with a threshold th (e.g., threshold th1 or threshold th2) (step S106). If the evaluation distance ds is greater than the threshold th (step S107; Y), the server device 400 evaluates the secondary battery 200 (test secondary battery) as normal (reusable) (step S108). On the other hand, if the evaluation distance ds is equal to or less than the threshold th (step S107; N), the server device 400 evaluates the secondary battery 200 (test secondary battery) as abnormal (unusable) (step S109).

[0047] [Effects] Next, effects of the secondary battery evaluation system according to this embodiment will be described.

[0048] In this embodiment, whether the secondary battery 200 (test secondary battery) is normal or not is determined based on a comparison between a normal impedance parameter 331 obtained from a plurality of secondary batteries 200 (normal secondary batteries) whose SoCs are different from one another and known, and a test impedance parameter 332 obtained from the secondary battery 200 (test secondary battery). In this manner, the normal impedance parameter 331 obtained from a plurality of secondary batteries 200 (normal secondary batteries) whose SoCs are different from one another and known, is used as a reference value. This makes it possible to determine whether the secondary battery 200 (test secondary battery) is normal or not in an unknown state, without adjusting the SoC in advance. As a result, the evaluation time can be shortened compared to a method of adjusting the SoC.

[0049] In this embodiment, when each normal impedance parameter 331 is defined as a first vector and the test impedance parameter 332 is defined as a second vector, the distance between each first vector and the second vector is calculated, and based on the multiple distances obtained, it is determined whether the secondary battery 200 (test secondary battery) is normal. This makes it possible to determine whether the secondary battery 200 (test secondary battery) is normal in an unknown state without adjusting the SoC in advance. As a result, the evaluation time can be shortened compared to a method that adjusts the SoC.

[0050] In this embodiment, the Mahalanobis distance is used to determine whether the secondary battery 200 (test secondary battery) is normal or not. This allows for a more accurate determination of whether the secondary battery 200 (test secondary battery) is normal or not compared to when the Euclidean distance is used to determine whether the secondary battery 200 (test secondary battery) is normal or not.

[0051] In this embodiment, whether or not the secondary battery 200 (test secondary battery) is normal is determined by applying the k-nearest neighbor method to a plurality of distances. This makes it possible to accurately determine whether or not the secondary battery 200 (test secondary battery) is normal, even if the values ​​of the normal impedance parameters 331 are not normally distributed.

[0052] 2. Second Embodiment A secondary battery evaluation system according to a second embodiment of the present technology will be described. FIG. 8 illustrates an example of functional blocks of the secondary battery evaluation system according to the second embodiment of the present technology. The secondary battery evaluation system includes, for example, a secondary battery evaluation device 500 as shown in FIG. 8. The secondary battery evaluation device 500 corresponds to a specific example of a "secondary battery evaluation device" according to an embodiment of the present disclosure. The secondary battery evaluation device 500 is a device that charges and discharges a secondary battery 200, and is a standalone device that does not have a function of communicating with an external device.

[0053] 8, the secondary battery evaluation device 500 includes a charge / discharge circuit 110, an IV measurement circuit 120, a data processing unit 510, a storage unit 520, and a display unit 150. A secondary battery 200 is connected to the secondary battery evaluation device 500 (charge / discharge circuit 110).

[0054] The storage unit 520 is configured by a non-volatile memory such as a flash memory, etc. The storage unit 520 stores the test measurement value 141, the normal measurement value 142, the normal impedance parameters 331, and the test impedance parameters 332.

[0055] The data processing unit 510 performs processing common to the data processing units 130 and 320 in the above-described embodiments, thereby generating a test measurement value 141, a normal measurement value 142, a plurality of normal impedance parameters 331, and a test impedance parameter 332, and storing them in the memory unit 520.

[0056] In this embodiment, the secondary battery evaluation device 500 determines whether the secondary battery 200 (test secondary battery) is normal based on a comparison between a normal impedance parameter 331 obtained from a plurality of secondary batteries 200 (normal secondary batteries) having different and known SoCs and a test impedance parameter 332 obtained from the secondary battery 200 (test secondary battery). In this manner, the normal impedance parameter 331 obtained from the plurality of secondary batteries 200 (normal secondary batteries) having different and known SoCs is used as a reference value. This makes it possible to determine whether the secondary battery 200 (test secondary battery) is normal in an unknown state without adjusting the SoC in advance. As a result, the evaluation time can be shortened compared to a method of adjusting the SoC.

[0057] 3. Modifications common to all embodiments [Modification 3-1] FIG. 9 shows a modification of the data used to evaluate the secondary battery 200 (test secondary battery) in the first and second embodiments and their modifications.

[0058] In the above-described first and second embodiments and their modifications, the data processing unit 331, 510 may calculate the impedance data 410 of the secondary battery 200 (normal secondary battery) based on, for example, the normal measurement value 142. In this case, the data processing unit 331, 510 may calculate the normal impedance data 410 of the secondary battery 200 (normal secondary battery) for each normal measurement value 142. The data processing unit 331, 510 calculates the real part and imaginary part of the impedance of the secondary battery 200 (normal secondary battery) as the normal impedance data 410.

[0059] In the above-described first and second embodiments and their modifications, the data processing unit 331, 510 may further calculate test impedance data 420 of the secondary battery 200 (test secondary battery) based on, for example, the test measurement value 141. In this case, the data processing unit 331, 510 calculates the real part and imaginary part of the impedance of the secondary battery 200 (test secondary battery) as the test impedance data 410.

[0060] In this modification, the data processing unit 331, 510 determines whether the secondary battery 200 (test secondary battery) is normal or not based on a comparison between a plurality of normal impedance data 410 and the test impedance data 420. Specifically, the data processing unit 320 first sets each normal impedance data 410 as a first vector and the test impedance data 420 as a second vector. The data processing unit 320 then calculates the distances between the plurality of first vectors and the second vector, and determines whether the secondary battery 200 (test secondary battery) is normal or not based on the plurality of distances obtained by the calculation.

[0061] In this modification, whether the secondary battery 200 (test secondary battery) is normal or not is determined based on a comparison between a plurality of normal impedance data 410 and test impedance data 420. Even in this case, the evaluation time can be shortened compared to the method of adjusting the SoC.

[0062] [Modification 3-2] FIG. 10 shows a modification of the data used to evaluate the secondary battery 200 (test secondary battery) in the first and second embodiments and their modifications.

[0063] In the first and second embodiments and their modifications, the charge / discharge circuit 110 may interrupt the current and voltage applied to the secondary battery 200 as an external stimulus at a predetermined timing. At this time, the IV measurement circuit 120 measures a transient response after the current and voltage applied to the secondary battery 200 are interrupted at the predetermined timing. The data processing unit 331, 510 calculates multiple impedance parameters of the secondary battery 200 (normal secondary battery) based on the measurement value (normal voltage data 430) of the transient response of the secondary battery 200 (normal secondary battery) measured by the IV measurement circuit 120. The data processing unit 331, 510 calculates multiple impedance parameters of the secondary battery 200 (test secondary battery) based on the measurement value (normal voltage data 440) of the transient response of the secondary battery 200 (test secondary battery) measured by the IV measurement circuit 120.

[0064] In this modification, a plurality of impedance parameters 311 of the secondary battery 200 (normal secondary battery) and a plurality of impedance parameters 312 of the secondary battery 200 (test secondary battery) are calculated based on the transient response measurement values ​​measured by the IV measurement circuit 120. Even in this case, the evaluation time can be shortened compared to the method of adjusting the SoC.

[0065] [Variation 3-3] Fig. 11 shows a variation of the equivalent circuit of the secondary battery 200 to be evaluated by the secondary battery evaluation systems according to the first and second embodiments and their variations. In the first and second embodiments and their variations, the secondary battery 200 may be represented by an equivalent circuit consisting of two elements (impedance parameters), namely, the solution resistance Rs and the differential capacitance C', as shown in Fig. 11. Even in this case, the evaluation time can be shortened compared to the method of adjusting the SoC.

[0066] [Variation 3-4] In the first and second embodiments and their variations, the multiple secondary batteries 200 (normal secondary batteries) are multiple secondary batteries with different SoCs and known SoCs. In this case, the multiple secondary batteries 200 (normal secondary batteries) can efficiently cover the entire SoC range. However, in the first and second embodiments and their variations, the multiple secondary batteries 200 (normal secondary batteries) may be multiple secondary batteries with known SoCs that are not all the same. Even in this case, although the range of SoC coverage is limited, the evaluation time can be shortened compared to the method of adjusting the SoC.

[0067] In the first and second embodiments and their modifications, the plurality of secondary batteries 200 (normal secondary batteries) may be a plurality of secondary batteries including at least normal secondary batteries with different SoCs. In this case, the SoC of each of the plurality of secondary batteries 200 (normal secondary batteries) does not need to be known. Even in such a case, although the range of SoCs covered is limited, the evaluation time can be shortened compared to the method of adjusting the SoC.

[0068] The present technology may also be configured as follows: <1> A secondary battery evaluation system comprising: a memory that stores a plurality of first measurement values ​​obtained by responding to an external stimulus for each of a plurality of normal secondary batteries, the memory storing a plurality of first calculated values ​​obtained based on the plurality of first measurement values, the plurality of first measurement values ​​being obtained by responding to an external stimulus for each of a plurality of normal secondary batteries, the plurality of normal secondary batteries including at least normal secondary batteries having different SoCs; and a processing circuit that is capable of determining whether the test secondary battery is normal or not based on a comparison of the plurality of first measurement values ​​obtained from the memory with a second measurement value obtained by responding to an external stimulus for a test secondary battery having an unknown SoC, or a comparison of the plurality of first calculated values ​​obtained from the memory with a second calculated value obtained based on the second measurement values. <2> The secondary battery evaluation system described in <1>, wherein the first measurement values ​​are measurement values ​​obtained by applying a current and a voltage to the normal secondary battery, and the second measurement values ​​are measurement values ​​obtained by applying a current and a voltage to the test secondary battery. <3> The secondary battery evaluation system according to <1>, wherein the first measured value is a measured value obtained by a transient response after a current and a voltage applied to the normal secondary battery are cut off. The second measured value is a measured value obtained by a transient response after a current and a voltage applied to the secondary battery under test are cut off. <4> The first calculated value is a value of a plurality of evaluation parameters of the secondary battery obtained based on the first measured value when the first measured value is a measured value obtained by applying a current and a voltage to the normal secondary battery. The second calculated value is a value of a plurality of evaluation parameters of the secondary battery obtained based on the second measured value when the second measured value is a measured value obtained by applying a current and a voltage to the secondary battery under test. The secondary battery evaluation system according to <1>, wherein the evaluation parameter is an impedance parameter of an equivalent circuit of the secondary battery. <6> The secondary battery evaluation system according to <1>, wherein the first calculated value is an impedance spectrum of the normal secondary battery, and the second calculated value is an impedance spectrum of the secondary battery under test.<7> The secondary battery evaluation system according to any one of <1> to <3>, wherein the processing circuit is capable of calculating a distance between each of the first vectors and the second vectors when each of the first measured values ​​is a first vector and when each of the second measured values ​​is a second vector, and determining whether the test secondary battery is normal or not based on the plurality of distances obtained thereby. <8> The secondary battery evaluation system according to any one of <1>, <4>, <5>, or <6>, wherein the processing circuit is capable of calculating a distance between each of the first vectors and the second vector when each of the first calculated values ​​is a first vector and when each of the second calculated values ​​is a second vector, and determining whether the test secondary battery is normal or not based on the plurality of distances obtained thereby. <9> The secondary battery evaluation system according to <7> or <8>, wherein the distance is a Mahalanobis distance. <10> The secondary battery evaluation system according to <7> or <8>, wherein the processing circuit is capable of determining whether the test secondary battery is normal or not by applying a k-nearest neighbor algorithm to the plurality of distances. <11> A secondary battery evaluation method comprising: acquiring a plurality of first measured values ​​obtained by a response to an external stimulus for each of a plurality of normal secondary batteries, the plurality of normal secondary batteries including at least normal secondary batteries having different SoCs, or a plurality of first calculated values ​​obtained based on the plurality of first measured values; acquiring a second measured value obtained by a response to an external stimulus for a test secondary battery having an unknown SoC, or a second calculated value obtained based on the second measured values; and determining whether the test secondary battery is normal or not based on a comparison between the plurality of first measured values ​​and the second measured values ​​or a comparison between the plurality of first calculated values ​​and the second calculated value. <12> The secondary battery evaluation system described in <11>, wherein the first measured values ​​are measured values ​​obtained by applying a current and a voltage to the normal secondary batteries, and the second measured values ​​are measured values ​​obtained by applying a current and a voltage to the test secondary battery.<13> The secondary battery evaluation system according to <11>, wherein the first measured value is a measured value obtained by a transient response after a current and a voltage applied to the normal secondary battery are cut off, and the second measured value is a measured value obtained by a transient response after a current and a voltage applied to the test secondary battery are cut off. <14> The secondary battery evaluation system according to <11>, wherein the first calculated value is a value of a plurality of evaluation parameters of the secondary battery obtained based on the first measured value when the first measured value is a measured value obtained by applying a current and a voltage to the normal secondary battery, and the second calculated value is a value of a plurality of evaluation parameters of the secondary battery obtained based on the second measured value when the second measured value is a measured value obtained by applying a current and a voltage to the test secondary battery. <15> The secondary battery evaluation method according to <14>, wherein the evaluation parameters are a plurality of impedance parameters of an equivalent circuit of the secondary battery. <16> The secondary battery evaluation method according to <11>, wherein the first calculated value is the impedance spectrum of the normal secondary battery, and the second calculated value is the impedance spectrum of the test secondary battery. <17> The secondary battery evaluation method according to any one of <11> to <13>, further comprising: calculating a distance between each of the first measured values ​​as a first vector and each of the second measured values ​​as a second vector, and determining whether the test secondary battery is normal or not based on the plurality of distances obtained thereby. <18> The secondary battery evaluation method according to any one of <11>, <14>, <15>, and <16>, further comprising: calculating a distance between each of the first calculated values ​​as a first vector and each of the second calculated values ​​as a second vector, and determining whether the test secondary battery is normal or not based on the plurality of distances obtained thereby. <19> The secondary battery evaluation method according to <17> or <18>, wherein the distance is a Mahalanobis distance. <20> The secondary battery evaluation method according to <17> or <18>, further comprising: determining whether the test secondary battery is normal by applying a k-nearest neighbor algorithm to a plurality of the distances.

Claims

1. A secondary battery evaluation system comprising: a memory that stores a plurality of first measurement values ​​obtained in response to an external stimulus for each of a plurality of normal secondary batteries, the plurality of normal secondary batteries including at least normal secondary batteries having different SoCs, or a plurality of first calculated values ​​obtained based on the plurality of first measurement values; and a processing circuit that is capable of determining whether the test secondary battery is normal or not based on a comparison between the plurality of first measurement values ​​obtained from the memory and a second measurement value obtained in response to an external stimulus for a test secondary battery having an unknown SoC, or a comparison between the plurality of first calculated values ​​obtained from the memory and a second calculated value obtained based on the second measurement values.

2. A secondary battery evaluation system as described in claim 1, wherein the first measurement value is a measurement value obtained by applying a current and a voltage to the normal secondary battery, and the second measurement value is a measurement value obtained by applying a current and a voltage to the test secondary battery.

3. The secondary battery evaluation system described in claim 1, wherein the first measurement value is a measurement value obtained by a transient response after the current and voltage applied to the normal secondary battery are cut off, and the second measurement value is a measurement value obtained by a transient response after the current and voltage applied to the test secondary battery are cut off.

4. The secondary battery evaluation system described in claim 1, wherein the first calculated value is a value of a plurality of evaluation parameters of the secondary battery obtained based on the first measured value when the first measured value is a measured value obtained by applying a current and a voltage to the normal secondary battery, and the second calculated value is a value of a plurality of evaluation parameters of the secondary battery obtained based on the second measured value when the second measured value is a measured value obtained by applying a current and a voltage to the test secondary battery.

5. The secondary battery evaluation system according to claim 4, wherein the evaluation parameter is an impedance parameter of an equivalent circuit of the secondary battery.

6. The secondary battery evaluation system according to claim 1, wherein the first calculated value is the impedance spectrum of the normal secondary battery, and the second calculated value is the impedance spectrum of the test secondary battery.

7. A secondary battery evaluation system as claimed in any one of claims 1 to 3, wherein the processing circuit is capable of calculating the distance between each of the first vectors and the second vector when each of the first measurement values ​​is a first vector and the second measurement value is a second vector, and determining whether or not the test secondary battery is normal based on the multiple distances obtained thereby.

8. The secondary battery evaluation system of any one of claims 1, 4, 5 and 6, wherein the processing circuit calculates the distance between each of the first vectors and the second vector when each of the first calculated values ​​is a first vector and the second calculated value is a second vector, and is capable of determining whether or not the test secondary battery is normal based on the multiple distances obtained thereby.

9. The secondary battery evaluation system according to claim 7 or 8, wherein the distance is a Mahalanobis distance.

10. A secondary battery evaluation system as described in claim 7 or claim 8, wherein the processing circuit is capable of determining whether the test secondary battery is normal or not by applying a k-nearest neighbor method to a plurality of the distances.

11. A secondary battery evaluation method comprising: obtaining a plurality of first measurement values ​​obtained in response to an external stimulus for each of a plurality of normal secondary batteries, the plurality of normal secondary batteries having different SoCs, or a plurality of first calculated values ​​obtained based on the plurality of first measurement values; obtaining a second measurement value obtained in response to an external stimulus for a test secondary battery having an unknown SoC, or a second calculated value obtained based on the second measurement values; and determining whether the test secondary battery is normal or not based on a comparison between the plurality of first measurement values ​​and the second measurement values, or a comparison between the plurality of first calculated values ​​and the second calculated value.

12. A secondary battery evaluation system as described in claim 11, wherein the first measurement value is a measurement value obtained by applying a current and a voltage to the normal secondary battery, and the second measurement value is a measurement value obtained by applying a current and a voltage to the test secondary battery.

13. A secondary battery evaluation system as described in claim 11, wherein the first measurement value is a measurement value obtained in a transient response after a current and voltage applied to the normal secondary battery is cut off; and the second measurement value is a measurement value obtained in a transient response after a current and voltage applied to the test secondary battery is cut off.

14. The secondary battery evaluation system described in claim 11, wherein the first calculated value is a value of an evaluation parameter of a secondary battery obtained based on the first measured value when the first measured value is a measured value obtained by applying a current and a voltage to the normal secondary battery, and the second calculated value is a value of an evaluation parameter of a secondary battery obtained based on the second measured value when the second measured value is a measured value obtained by applying a current and a voltage to the test secondary battery.

15. The secondary battery evaluation method according to claim 14, wherein the evaluation parameters are a plurality of impedance parameters of an equivalent circuit of the secondary battery.

16. The method for evaluating a secondary battery according to claim 11, wherein the first calculated value is the impedance spectrum of the normal secondary battery, and the second calculated value is the impedance spectrum of the test secondary battery.

17. A secondary battery evaluation method as described in any one of claims 11 to 13, further comprising: calculating a distance between each of the first vectors and the second vector when each of the first measurement values ​​is a first vector and the second measurement value is a second vector; and determining whether the test secondary battery is normal or not based on the multiple distances obtained thereby.

18. A secondary battery evaluation method as claimed in any one of claims 11, 14, 15 and 16, further comprising: calculating a distance between each of the first vectors and the second vector when each of the first calculated values ​​is a first vector and each of the second calculated values ​​is a second vector; and determining whether or not the test secondary battery is normal based on the multiple distances thus obtained.

19. The secondary battery evaluation method according to claim 17 or 18, wherein the distance is a Mahalanobis distance.

20. The method for evaluating a secondary battery according to claim 17 or 18, further comprising determining whether the test secondary battery is normal or not by applying a k-nearest neighbor method to a plurality of the distances.

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