INFORMATION PROCESSING SYSTEM, INFORMATION PROCESSING PROCESS AND INFORMATION PROCESSING PROGRAM

Abstract

According to one aspect of the present invention, an information processing system is provided. This information processing system comprises at least one processor capable of executing a program to perform each of the following steps. In a acquisition step, test conditions for a first degradation test performed on a secondary battery and a test result of the first degradation test are acquired. The test conditions include a test time for performing the first degradation test. The test result includes the degree of capacity degradation of the secondary battery. In a rate calculation step, a capacity degradation rate of the secondary battery under the test conditions is calculated based on the degree of capacity degradation.In an estimation step, the capacity degradation rate of the secondary battery is estimated based on the calculated capacity degradation rate under at least one of untested conditions, which represent unrecorded test conditions. In a map generation step, a degradation rate map, representing the correspondence between the test conditions and the capacity degradation rate, is generated based on the calculated and estimated capacity degradation rates. In a priority calculation step, the priority of each of the untested conditions under which a second degradation test is to be performed is calculated based on the generated degradation rate map.In a candidate output step, a candidate for the second deterioration test is output, in which at least one of the untested conditions is set as the test condition, with one aspect selectable by a user based on the calculated priority.

Description

BACKGROUND

[0001] The present disclosure relates to an information processing system, an information processing procedure and an information processing program. STATE OF THE ART

[0002] Patent document 1 discloses a storage battery diagnostic device which aims to provide information on the deterioration of a storage battery with a simple configuration during charging and discharging.

[0003] This storage battery diagnostic device comprises a SOC sensing unit that detects the SOC of a storage battery, a temperature sensing unit that detects the temperature of the storage battery, a storage unit that stores a deterioration rate characteristic that specifies a relationship between the temperature and the SOC of the storage battery and the deterioration rate, a diagnostic unit that specifies the deterioration rate of the storage battery based on the detected temperature and the detected SOC and the deterioration rate characteristic and calculates a degree of deterioration of the storage battery by accumulating the deterioration rate over a predetermined duration, and an output unit that outputs information regarding the deterioration state of the storage battery based on the degree of deterioration. PRINTED FONTS Patent document

[0004] [Patent Document 1] JP 2020-38138 A SUMMARY Problem to be solved by the invention

[0005] However, the technology disclosed in patent document 1 may require a high level of effort for testing the storage battery, which is necessary when generating the deterioration rate characteristics. Means to solve the problems

[0006] According to one aspect of the present disclosure, an information processing system is provided. This information processing system has at least one processor trained to execute a program to perform the following steps. In a capture step, a test condition of an initial degradation test performed on a secondary battery and a test result of the initial degradation test are captured. The test condition includes a test time for performing the initial degradation test. The test result includes a capacity degradation rate of the secondary battery. In a rate calculation step, a capacity degradation rate of the secondary battery under the test condition is calculated based on the capacity degradation rate.In an estimation step, the capacity degradation rate of the secondary battery is estimated based on the calculated capacity degradation rate under at least one of untested conditions, which represent test conditions that were not recorded. In a map generation step, a degradation rate map is generated based on the calculated and estimated capacity degradation rates, specifying a correspondence relationship between the test condition and the capacity degradation rate. In a priority calculation step, a priority for each of the untested conditions for performing a second degradation test is calculated based on the generated degradation rate map.In a candidate output step, a candidate for the second degradation test, in which at least one of the untested conditions is a test condition, is output based on the calculated priority in a user-selectable manner.

[0007] According to this configuration, a deterioration rate map can be obtained while reducing testing effort compared to conventional testing methods. BRIEF DESCRIPTION OF THE DRAWINGS Fig. Figure 1 is a configuration diagram representing an information processing system 1. Fig. Figure 2 is a block diagram showing a hardware configuration of an information processing device 2. Fig. Figure 3 is a block diagram showing a hardware configuration of a user terminal device 3. Fig. Figure 4 shows an example of a configuration of a deterioration test device 4. Fig. Figure 5 shows an example of functional units contained in a processor 23. Fig. Figure 6 shows a flowchart that provides an overview of the information processing process carried out in information processing system 1. Fig. Figure 7 is a flowchart that shows the process of a search query. Fig. Figure 8 is a flowchart that shows the process of a correction procedure. Fig. Figure 9 shows an example of estimation results for the time dependence of a capacity deterioration magnitude ΔC. DETAILED DESCRIPTION

[0008] The following describes an embodiment of the present disclosure with reference to the drawings. Various features described in the following embodiment can be combined with one another.

[0009] A program for implementing software of the present embodiment can be provided as a non-volatile, computer-readable storage medium, can be made available for download from an external server, or can be provided in such a way that the program can be activated on an external computer to implement functions of the same on a client terminal device (so-called cloud computing).

[0010] In the present embodiment, the term "unit" can, for example, include a combination of a hardware resource implemented as a circuit in the broadest sense and information processing by software that can be specifically realized by the hardware resource. Furthermore, the present embodiment describes various types of information, and such information can be represented, for example, by physical values ​​of signals representing voltage and current, high and low signal values ​​as a group of binary bits consisting of 0s or 1s, or a quantum superposition (so-called qubits), and communication and computation can be performed on a circuit in the broadest sense.

[0011] In the broadest sense, a circuit is a circuit realized by appropriately combining at least one circuit, integrated circuit, processor, memory, and the like. In other words, a circuit includes an application-specific integrated circuit (ASIC), a programmable logic device (e.g., a simple programmable logic device (SPLD), a complex programmable logic device (CLPD), a field-programmable gate array (FPGA), and the like. 1. Hardware Configuration This section describes a hardware configuration.<Informationsverarbeitungssystem 1>

[0012] Fig. Figure 1 is a configuration diagram representing an information processing system 1. The information processing system 1 includes an information processing device 2, a user terminal 3, and a deterioration test device 4. The information processing device 2, the user terminal 3, and the deterioration test device 4 are configured to communicate over a telecommunications line. In one embodiment, the information processing system 1 consists mainly of one or more devices or components. For example, if the information processing system 1 consists only of the information processing device 2, then the information processing system 1 can be the information processing device 2. An explanation of these components follows. <Informationsverarbeitungsvorrichtung 2>

[0013] Fig. Figure 2 is a block diagram showing a hardware configuration of the information processing device 2. The information processing device 2 comprises a communication unit 21, a storage unit 22, and a processor 23, and these components are electrically connected within the information processing device 2 via a communication bus 20. Each of the components is described in more detail below.

[0014] The communication unit 21 is preferably a wired communication means such as USB, IEEE1394, Thunderbolt (registered trademark), wired LAN network communication, etc., but can also include wireless LAN network communication, mobile communication such as 3G / LTE / 5G, Bluetooth (registered trademark) communication, and the like, if necessary. Preferably, an integration of these multiple communication means is used. That is, the information processing device 2 can communicate various types of information from the outside via the communication unit 21 and a network.

[0015] The memory unit 22 stores various types of information as defined by the description above. That is, the memory unit 22 can, for example, store such information as a storage device, such as a solid-state drive (SSD), which stores various programs, etc., relating to the information device 2 executed by the processor 23, or as memory such as random access memory (RAM), which temporarily stores information (arguments, arrays, etc.) required for program calculations. The memory unit 22 stores various programs and variables relating to the information processing device 2 executed by the processor 23.

[0016] Processor 23 processes and controls overall operational processes with respect to information processing device 2. Processor 23 is, for example, a central processing unit (CPU) (not shown). Processor 23 reads a predefined program stored in memory unit 22 to perform various functions with respect to information processing device 2. That is, the information processing by software stored in memory unit 22 is specifically implemented by processor 23, as an example of hardware, and can be executed by any functional unit contained within processor 23. These will be described in more detail in a later section. Processor 23 is not limited to a single processor but can be implemented such that it has multiple processors 23 for each function.Furthermore, the processor 23 can be a combination of the structures described above. <Benutzerendgerät 3>

[0017] Fig. Figure 3 is a block diagram showing a hardware configuration of the user terminal 3. The user terminal 3 comprises a communication unit 31, a storage unit 32, a processor 33, a display unit 34, and an HMI device 35, and these components are electrically connected via a communication bus 30 within the user terminal 3. Descriptions of the communication unit 31, the storage unit 32, and the processor 33 are the same as those of the respective units in the information processing device 2 and are therefore omitted.

[0018] The display unit 34 can be contained within a housing of the user terminal 3 or attached externally to it. The display unit 34 displays a screen of a graphical user interface (GUI) that can be operated by a user. This should be implemented, for example, by using different display devices such as a CRT display, a liquid crystal display, an organic EL display, and a plasma display, depending on the type of user terminal 3.

[0019] The HMI device 35 is a human-machine interface device. The HMI device 35 can be contained within a housing of the user terminal 3 or attached to it externally. For example, the HMI device 35 can be integrated with the display unit 34 and implemented as a touch panel. With a touch panel, the user can input taps, swipes, etc. Of course, a push button, a mouse, a QWERTY keyboard, a speech recognition device, a gesture detection device, a gaze detection device, an eye-tracking device, a biometric signal detection device, an imaging device, etc., can be used instead of a touch panel. In other words, the HMI device 35 receives input from the user. Responding to this input, the HMI device 35 transmits a signal corresponding to the input via the communication bus 30 to the processor 33.The processor 33 can execute predetermined control or calculation operations as needed. The HMI device 35 can be considered to have an input unit designed to receive input from the user. <Verschlechterungstestvorrichtung 4>

[0020] Fig. Figure 4 shows an example of a configuration of a deterioration test device 4. The deterioration test device 4 has at least a constant temperature bath 41, a reference constant temperature bath 42, a charging and discharging device 43 and an impedance measuring device 44, and these components are designed to be able to communicate with each other.

[0021] Each of the constant temperature bath 41 and the reference constant temperature bath 42 is configured to receive a secondary battery B. The constant temperature bath 41 is configured to perform a deterioration test on the secondary battery B. The reference constant temperature bath 42 is configured to perform, for example, a deterioration test on the secondary battery B in a similar manner to the constant temperature bath 41. The reference constant temperature bath 42 is configured to perform a deterioration test on the secondary battery B based on the initial test conditions described below. The secondary battery B can be any type of battery, as long as it is configured to perform charging and discharging, for example, a lead-acid battery, a nickel-cadmium storage battery, a lithium-ion storage battery, an air battery, etc.

[0022] The charging and discharging device 43 is configured to perform a deterioration test on the secondary battery B by controlling the operating processes of the constant temperature bath 41, the reference constant temperature bath 42, and the secondary battery B. For example, the charging and discharging device 43 is configured to control the temperature of the constant temperature bath 41 and the reference constant temperature bath 42 according to the test conditions of the deterioration test. Furthermore, the charging and discharging device 43 is configured to control the charging and discharging of the secondary battery B, e.g., the charging and discharging rate of the secondary battery B and the voltage and current during charging and discharging, according to the test conditions.

[0023] The impedance measuring device 44 is designed to measure an impedance and an open-circuit voltage (OCV) of the secondary battery B in conjunction with the control of the secondary battery B by the charging and discharging device 43.

[0024] The test conditions of the present embodiment include a test time for performing a first deterioration test, the temperature of the constant temperature bath 41 (in other words, the temperature of secondary battery B), the current rate of secondary battery B, the mean state of charge (SOC), and the SOC range. These elements, which define the test conditions, are used as elements of the state space that represents the test conditions when a deterioration rate map described below is generated. The test conditions may include elements other than those described above as elements of such a state space. For example, the test conditions may include a temperature settling rate or a temperature settling time of the constant temperature bath 41, etc., and a waiting time after reaching the target SOC.

[0025] The test conditions are set within a predefined test range. This test range includes, for example, the temperature range of the constant temperature bath 41, the current rate range of the secondary battery B, the mean state of charge (SOC) range, the value of the SOC range, and the like. 2. Functional configuration of the information processing device 2

[0026] Fig. Figure 5 shows an example of functional units contained in the processor 23. As in Fig. As shown in Figure 5, the processor 23 comprises a sensing unit 231, a rate calculation unit 232, an estimation unit 233, a priority setting unit 234, a priority calculation unit 235, a candidate output unit 236, an exchange determination unit 237, a correction unit 238, and a characteristic map generation unit 239. This section provides an overview of these functional units. The details of each functional unit are described in connection with the information processing described below.

[0027] The acquisition unit 231 is configured to acquire information from the user terminal 3, the deterioration test device 4, or other devices. The acquisition unit 231 is configured to acquire various types of information by reading different types of information stored in a memory area that is at least a part of the memory unit 22 and writing the read information to a working area that is at least a part of the memory unit 22. The memory area is, for example, an area of ​​the memory unit 22 implemented as a storage device such as an SSD. The working area is, for example, an area implemented as memory such as RAM. It should be noted that the acquisition by the acquisition unit 231 includes the acquisition of output results from each functional unit contained in the processor 23.

[0028] The rate calculation unit 232 is designed to calculate various types of information, such as a capacity degradation rate V, based on a measurement result from the measurement unit 231. The capacity degradation rate V represents the degree of degradation per unit of time of the battery capacity C of the secondary battery B in a given environment.

[0029] The estimation unit 233 is designed to estimate different types of information such as the capacity deterioration rate V under a specific test condition based on different types of information such as the acquisition results of the acquisition unit 231 and the calculation results of the rate calculation unit 232.

[0030] The priority setting unit 234 is designed to set a priority of the test conditions of a deterioration test to be performed on the secondary battery B, based on various types of information and user actions.

[0031] The priority calculation unit 235 is designed to calculate a priority corresponding to each of the test conditions based on various types of information, such as the priority set by the priority setting unit 234. Details of the priority are described below.

[0032] The candidate output unit 236 is configured to output various types of information, such as candidates for test conditions of the deterioration test to be performed on each secondary battery B. The information can be displayed to the user via the display unit 34 of the user terminal 3 or other devices. In such a case, the candidate output unit 236 controls the display unit 34 of the user terminal 3 to display visual information such as screens, images with still or moving pictures, icons, messages, and the like. The candidate output unit 236 can only generate rendering information for displaying the visual information on the user terminal 3. The candidate output unit 236 cannot display the output information via the user terminal 3 to the user or other device users.

[0033] The replacement determination unit 237 is designed to perform a determination as to whether the secondary battery B, on which a deterioration test is to be carried out, needs to be replaced or not, based on various types of information.

[0034] The correction unit 238 is designed to correct the estimation result, etc., performed by the estimation unit 233, based on various types of information.

[0035] The map generation unit 239 is designed to generate a deterioration rate map that represents the correspondence between the deterioration rate of secondary battery B and the test conditions, based on the calculation results of the rate calculation unit 232, the estimation results of the estimation unit 233, the correction results of the correction unit 238, etc. Updating the deterioration rate map is one aspect of its generation.

[0036] The classification unit 240 is trained to classify test conditions based on different types of information. 3. Information processing

[0037] This section describes the information processing to be carried out in the information processing system 1 described above. 3.1. Information processing process

[0038] Fig. Figure 6 is a flowchart that provides an overview of the information processing sequence performed in information processing device 1. It should be noted that the information processing may include any exception handling, which is not shown. Exception handling involves interrupting the information processing or omitting a particular processing step. Selections or inputs performed in the information processing may be based on user actions or occur automatically without user action. [Step S1]

[0039] The processing first proceeds to step S1, in which the processor 23 pre-measures the initial capacitance C_ini of each of the secondary batteries B, which are placed in each of the constant-temperature baths 41 and the reference constant-temperature bath 42. These secondary batteries B have never been subjected to a degradation test before. For example, the processor 23 first controls the constant-temperature bath 41 and the reference constant-temperature bath 42 so that the temperature of each secondary battery B reaches a predetermined setpoint temperature. Next, the processor 23 sets a current value, based on the nominal capacitance C_nominal of the secondary battery B, which is used for charging and discharging the secondary battery B.Next, the processor 23 performs a charge at constant current and constant voltage until the SOC reaches 100%, and a discharge at constant current and constant voltage until the SOC reaches 0%, and the discharge capacity at this time is defined as the initial capacity C_ini. [Step S2]

[0040] The processing then proceeds to step S2, in which processor 23, acting as the acquisition unit 231, acquires a preset initial test condition. The initial test condition is a test condition of the first degradation test. For simplicity, the degradation test performed previously will be referred to as the first degradation test, and the degradation test performed next will be referred to as the second degradation test. The initial test described above is an example of the first degradation test. The first degradation test can also be considered a degradation test that was performed in the past. [Step S3]

[0041] The processing then proceeds to step S3, in which processor 23 performs a degradation test based on the captured initial test condition. The test results of the executed degradation test and its test conditions are stored, for example, in memory unit 22. [Step S4]

[0042] The processing then proceeds to step S4, in which the processor 23 measures the capacity degradation ΔC of each secondary battery B through the degradation test in step S3. The measurement method is arbitrary; for example, the processor 23 can measure the battery capacity C after the degradation test in the same way as the initial capacity C_ini and measure the capacity degradation ΔC by subtracting the battery capacity C from the initial capacity C_ini. The measurement of the battery capacity C and the capacity degradation ΔC of the secondary battery B is not limited to being performed directly by the processor 23.For example, the processor 23 can control the deterioration test device 4 so that the charging and discharging device 43 and the impedance measuring device 44 measure the battery capacity C and the like, and record the measurement results output by the deterioration test device 4. [Step S5]

[0043] Next, the processing proceeds to step S5, in which the processor 23, acting as the rate calculation unit 232, calculates the capacity degradation rate V of each secondary battery B based on the initial test condition and the capacity degradation extent ΔC. [Step S6]

[0044] The processing then proceeds to step S6, in which processor 23, acting as estimating unit 233, estimates the capacity degradation rate V under untested conditions based on the calculated capacity degradation rate V. The untested conditions represent test conditions that have not yet been recorded in this information processing and are, for example, test conditions for which no test results have yet been stored in memory unit 22 or the like. The procedure for estimating the capacity degradation rate V under untested conditions is arbitrary. For example, processor 23 creates a trained model representing a predetermined physical model of the secondary battery B by performing machine learning using the calculated degradation rate V as training data and updates it.The trained model is configured to output parameters relating to the secondary battery B, such as the capacity degradation rate V, by inputting test conditions. Processor 23 inputs untested conditions into such a trained model, thereby estimating the capacity degradation rate V under the untested conditions. The specific aspects of generating and updating the trained model are arbitrary, and examples include linear regression, ridge regression, Gaussian process regression, neural networks, and support vector machines. For example, a method for estimating the capacity degradation rate V using Gaussian process regression includes the methods disclosed in the nonpatent document "J. Wang, D. Fleet, and A. Hertzmann, "Gaussian Process Dynamical Models", NIPS 2005".The processor 23 can estimate the capacity degradation rate V under the untested conditions based on the calculated capacity degradation rate V using a statistical procedure based on the previously mentioned regression analysis without using machine learning or the like. [Step S7]

[0045] The processing then proceeds to step S7, in which processor 23, acting as the map generation unit 239, generates a deterioration rate map M based on the test condition and the capacity deterioration rate V corresponding to the test condition. The deterioration rate map M specifies a correspondence relationship between the test condition and the capacity deterioration rate V. The deterioration rate map M can be expressed in any format, such as a function, a lookup table, or a trained model. If an existing deterioration rate map M exists, processor 23 can update the existing deterioration rate map M with the generated deterioration rate map M. [Step S8]

[0046] The processing then proceeds to step S8, in which the processor 23, acting as the acquisition unit 231, acquires information relating to the first degradation test by referencing the memory unit 22 or the like. For example, the processor 23, acting as the acquisition unit 231, acquires the test conditions of the first degradation test performed on secondary battery B and the test results of the first degradation test. Specifically, the processor 23 acquires the test conditions of several first degradation tests performed on each of the several secondary batteries B and the capacity degradation extent ΔC of each of the secondary batteries obtained from each of the several first degradation tests.In the present embodiment, in addition to the test conditions and test results of the most recent first deterioration test, the processor 23 also records the history of the first deterioration test performed on the secondary battery B. The history of the first deterioration test includes test conditions and test results of the several first deterioration tests performed in the past. [Step S9]

[0047] The processing then proceeds to step S9, in which processor 23 determines, based on the recorded test conditions and test results of the first deterioration test, whether a predetermined number or more pieces of information have been accumulated with respect to the first deterioration test. For example, if any processing activity included in the current information processing has been performed a predetermined number or more times for a secondary battery B, processor 23 determines that a predetermined number or more of past test results have been accumulated. The predetermined number can be set arbitrarily depending on the accuracy of the information with respect to the measurement error and is two or more, preferably three or more. [Step S10]

[0048] When it is determined that a predetermined number or more of past test results have been accumulated, processing proceeds to step S10, and the processor 23, acting as the classification unit 240, classifies candidates for the test conditions of the second deterioration test according to the measurement error of the capacity deterioration extent ΔC.

[0049] An example of the processing in step S10 is described here. First, the processor 23 performs a determination of the measurement error of the capacity degradation magnitude ΔC for each test condition. Accordingly, the processor 23 classifies each test condition into a test condition belonging to a first classification, indicating a relatively large measurement error of the test conditions within the search range, and a test condition belonging to a second classification, indicating a relatively small measurement error of the test conditions within the search range.For example, Processor 23 performs this determination based on (1) whether the estimated capacity degradation rate V is less than or equal to the mean of the estimated capacity degradation rates V under all test conditions, and (2) whether the absolute value of the difference between the estimated capacity degradation rate V and the estimated capacity degradation rate V under the target test conditions is less than or equal to a predetermined multiple (greater than 0 and less than 1) of the estimated capacity degradation rate V. Processor 23 determines that the test condition satisfying both conditions (1) and (2) is a test condition belonging to the first classification and classifies it accordingly.On the other hand, processor 23 determines that any test condition that does not satisfy at least one of conditions (1) and (2) is a test condition belonging to the second classification and classifies it accordingly. (1) is a condition indicating whether the test condition is such that the relative measurement error of the capacity degradation extent ΔC is large or not. This condition is based on the idea that the measurement error of the battery capacity occurs at a constant level, regardless of the amount of degradation. (2) is a condition indicating whether the estimated result of the capacity degradation rate V under the test condition exhibits small variations compared to past estimates, indicating the stability of the estimates.

[0050] The processor 23 can further extract test conditions in which the temperature, mean SOC, and SOC range are equal, and classify the extracted test conditions based on a specific test condition that is one of the extracted test conditions. For example, the processor 23 treats a test condition with a relatively high current rate (more precisely, the highest) of the extracted test conditions as a specific test condition. Then, when the processor 23, acting as the classification unit 240, classifies the specific test condition into the first classification, a test condition with a lower current rate than the specific test condition (in this case, all of the extracted test conditions) is classified into the first classification in the same way as the specific test condition.At this time, the processor classifies 23, even if some of the extracted test conditions do not fall into the first classification, those extracted test conditions that meet the above conditions are classified into the first classification. This is because the capacity degradation rate V increases monotonically with respect to the current rate, regardless of the type of secondary battery B. In other words, the capacity degradation rate V tends to be smaller when the current rate is lower. This can reduce the load on the classification processing. [Step S11]

[0051] After step S10, processing proceeds to step S11. However, if it is determined that the predetermined number or more of past test results have not been accumulated, processing in step S10 is skipped, and processing proceeds to S11. In step S11, the processor 23, acting as the priority setting unit 234, sets a priority. The priority serves as an index when searching for candidates for the test conditions of the second deterioration test, which is described below. The priority is defined by at least one parameter that represents the advantage or disadvantage of the second deterioration test, for example, the reliability of the deterioration rate map M obtained by performing the second deterioration test on the secondary battery B, or the effort required to perform the second deterioration test.The priority of the present embodiment is defined at least by the standard deviation of the capacity degradation rate V, estimated by the estimating unit 233, the slope of the capacity degradation rate V in the degradation rate map M, and the reciprocal of the capacity degradation rate V. For example, the priority is defined by a weighted linear sum of these parameters. The processor 23 standardizes these parameters so that they can be compared with each other, for example by processing these parameters so that each takes a value between 0 and 1. For the sake of simplicity, hereafter “the slope of the capacity degradation rate V in the degradation rate map M” is referred to as “the slope of the capacity degradation rate V”.The slope of the capacity degradation rate V can, in the extreme case, be considered as the derivative (or gradient) of the capacity degradation rate V with respect to a parameter representing a specific test condition. The slope of the capacity degradation rate V can be expressed by a scalar quantity, a vector quantity such as a gradient vector, or a higher-order tensor quantity.

[0052] The standard deviation of the capacity degradation rate V represents the reliability of the estimate of the capacity degradation rate V under the test condition. An increase in this value suggests that the reliability of the estimate of the capacity degradation rate V under the test condition is decreasing. Thus, the lower the reliability of the estimate of the capacity degradation rate V under test conditions, the more preferable it is to calculate the capacity degradation rate V using a degradation test. Accordingly, the priority is set higher as the standard deviation of the capacity degradation rate V increases.In other words, the standard deviation of the capacity degradation rate V is one of the statistics of the capacity degradation rate V and is one of the parameters that represents the reliability of the degradation rate map M, which is obtained by performing the second degradation test on the secondary battery B.

[0053] The slope of the capacity degradation rate, V, represents the degree of change in the degradation rate around the test conditions. As this value increases, the accuracy of the estimated capacity degradation rate V around the test conditions tends to decrease. Thus, the slope of the capacity degradation rate, V, is one of the parameters that determines the reliability of the degradation rate map M obtained by performing the second degradation test on the secondary battery B. Under test conditions where the slope of the capacity degradation rate, V, is large, the degradation tests can be performed to supplement the calculated results of the capacity degradation rate, V, and efficiently improve the estimation accuracy of the degradation rate map M. Therefore, the priority is increased as the slope of the capacity degradation rate, V, increases.Calculating the standard deviation and slope of the capacity degradation rate V based on the capacity degradation magnitude ΔC of the first degradation test is an aspect of determining the reliability of the generated degradation rate map M. Thus, the reliability of the degradation rate map M is calculated based on at least one of the statistics of the calculated capacity degradation rate V and the slope of the calculated capacity degradation rate V with respect to the parameters relating to the test conditions of the degradation rate map M.

[0054] The reciprocal of the capacity degradation rate V represents the smallness of the load on secondary battery B due to the degradation test and is one of the indices that indicate the effort required to perform a second degradation test. The larger the value of the reciprocal of the capacity degradation rate V, the smaller the degree of capacity degradation ΔC during a given test time in the degradation test. Consequently, the larger this value, the smaller the load on secondary battery B due to the corresponding degradation test, which makes it easier to perform more degradation tests on a single secondary battery B.

[0055] The correspondence between the priority and these parameters is defined by a priority correspondence relationship. The priority correspondence relationship of the present embodiment specifies the correspondence between the priority and the reliability of the deterioration rate map M by performing a second deterioration test on the secondary battery B, and the effort required to perform the second deterioration test, and is defined, for example, by the weight (in other words, the coefficient) of each parameter in the linear sum included in the priority.

[0056] In the present embodiment, the processor 23, which functions as the priority setting unit 234, establishes a priority correspondence relationship based on a user input. For example, the user specifies a weight for each parameter included in the priority via input through the HMI device 35. The processor 23 updates the weights for the respective parameters included in the priority correspondence relationship so that they match the specified weights and sets the priority based on the updated parameters. The processor 23, which functions as the priority calculation unit 235, calculates the priority based on the established priority correspondence relationship. [Step S12]

[0057] The processing then proceeds to step S12, in which processor 23, based on the set priority, calculates the priority corresponding to the test condition only within the search range and, based on the calculated priority, searches for candidates for the test conditions of the second deterioration test, which is to be performed next, for each secondary battery B. For simplicity, the processing to search for such candidates will henceforth be referred to simply as the search processing. In other words, processor 23, acting as the priority calculation unit 235, calculates the priority of each of the untested conditions for performing the second deterioration test based on the calculated deterioration rate characteristic M.In the present embodiment, the processor 23 calculates the priority of each of the untested conditions for performing the second deterioration test based on at least the reliability of the deterioration rate map M obtained by continuing to perform the second deterioration test on the secondary battery B under at least one untested condition, or the effort required to perform a second deterioration test. In step S10, when the test conditions of the second deterioration test are classified, the search range is limited to the test condition that belongs to one of the classifications. In the present embodiment, the test condition that is classified as having a relatively small measurement error is set as a search range. [Step S13]

[0058] Next, processing proceeds to step S13, where processor 23, acting as the candidate output unit 236, outputs the search results from step S10. As a result, processor 23 outputs candidates for the second deterioration test, based on the calculated priority, in which at least one of the untested conditions is a test condition, in a user-selectable manner. In the present embodiment, the output candidates for the second deterioration test are displayed to the user via the display unit 34. The user can select a candidate for the second candidate deterioration test, displayed on the display unit 34, by actuating the HMI device 35.For example, processor 23 outputs the candidates whose calculated priority is higher than a specified threshold and which are in the top n places (where n is a natural number) in a way that allows the user to preferentially capture them. [Step S14]

[0059] Next, processing proceeds to step S14, in which the acquisition unit 231 captures the selection of test conditions made by the user in step S13. [Step S15]

[0060] The processing then proceeds to step S15, in which the processor 23 sets test conditions for each constant-temperature bath 41 and the reference constant-temperature bath 42 based on the acquired test condition selection. The processor 23 of the present embodiment sets a reference test condition for the reference constant-temperature bath 42. The reference test condition is common to the first deterioration test and the second deterioration test and is set such that the deterioration test is performed under the same test condition on the secondary battery B, which is immersed in the reference constant-temperature bath 42. The reference test condition of the present embodiment is the same as the initial test condition performed on the secondary battery B, which is immersed in the reference constant-temperature bath 42, in step S3.In other words, at least one of the test conditions is a reference test condition that is set independently of the test condition candidate selected by the user. [Step S16]

[0061] The processing then proceeds to step S16, in which the processor 23, acting as the replacement determination unit 237, determines whether the secondary battery B, which is immersed in the constant temperature bath 41 or the reference constant temperature bath 42, needs to be replaced. For example, the processor 23 determines that replacement of the secondary battery B is necessary if the ratio (C_deg_total / C_ini) of the sum C_deg_total (so-called total degradation extent) of the capacity degradation extent ΔC from past degradation tests to the initial capacity C_ini is greater than or equal to a standard value. Conversely, the processor 23 determines that replacement of the secondary battery B is not necessary if C_deg_total / C_ini is less than the standard value. The standard value can be set arbitrarily.In this way, the processor 23, which acts as the replacement determination unit 237, determines, based on the detected capacity degradation extent ΔC, whether the secondary battery B, on which the degradation test is performed, is replaced or not. [Step S17]

[0062] If it is determined that at least one secondary battery B needs to be replaced, processing proceeds to step S17, and the replacement determination unit 237 indicates to the user via the display unit 34 which secondary battery B needs to be replaced and prompts the user to replace the secondary battery B. If the secondary battery B is then replaced by the user, processing proceeds to step S18. [Step S18]

[0063] In step S18, processor 23 measures the initial capacity C_ini of secondary battery B after replacement. The method for measuring the initial capacity C_ini is arbitrary, but is similar, for example, to the method described in step S1. Processing then proceeds to step S19. If it is determined that neither of the secondary batteries B needs to be replaced, processing steps S17 and S18 is omitted, and processing proceeds to step S19. [Step S19]

[0064] In step S19, the processor 23 performs a second degradation test on each secondary battery B based on the test condition set in step S15. [Step S20]

[0065] The process then proceeds to step S20, in which the processor 23 measures the capacity degradation ΔC of each secondary battery B in the second degradation test. The test results, including the measurement results, are stored in the memory unit 22, etc., along with the corresponding second test conditions. The processor 23, acting as the acquisition unit 231, acquires the test conditions of the first degradation test performed on secondary battery B and the test results of the first degradation test by referencing the memory unit 22, etc. The test results indicate the capacity degradation ΔC of secondary battery B. [Step S21]

[0066] Next, processing proceeds to step S21, and the processor 23, acting as the rate calculation unit 232, calculates the capacity degradation rate V of the secondary battery B under the test condition based on the capacity degradation extent ΔC. For example, the processor 23 calculates the capacity degradation rate V based on the test time ΔT of the second degradation test performed immediately beforehand, the capacity degradation extent ΔC due to the second degradation test, and the cumulative capacity degradation extent ΔC_T, which is the sum of the capacity degradation extent ΔC up to the time immediately before performing the second degradation test.In the present embodiment, the processor 23 further calculates the cumulative test time T_s, which is the cumulative test time of the first degradation test previously performed on the secondary battery B. The cumulative test time T_s is defined, for example, as the time until the capacity degradation ΔC of a new secondary battery B, which has not yet been subjected to a degradation test, reaches the cumulative capacity degradation ΔC_T. The cumulative capacity degradation ΔC_T and the cumulative test time T_s are aspects of the history of the first degradation test. Thus, it can be said that the processor 23, which functions as the rate calculation unit 232, further calculates the capacity degradation rate V based on this history.For example, the processor 23 calculates the capacity degradation rate V and the cumulative test time T_s based on the time dependence of the battery capacity C and its first-order variation as follows. ΔCT=V×Tsa ΔCT+ΔC=V×(Ts+ΔT)a a is the order of a time dependence of the cumulative capacity degradation magnitude ΔC_T on the capacity degradation rate V. Using these dependent equations, the capacity degradation rate V and the cumulative test time T_s can be obtained as follows. Ts=ΔCT1a×ΔT(ΔCT+ΔC)1a−ΔCT1a V=ΔC(Ts+ΔT)a−Tsa

[0067] In the present embodiment, the initial value of a is set to 0.5. [Step S22]

[0068] The processing then proceeds to step S22, in which processor 23, acting as estimator 233, estimates the capacity degradation rate V of secondary battery B under the test condition of the second degradation test, based on the calculated capacity degradation rate V. As mentioned above, the test condition to be set is an untested condition. Thus, processor 23, acting as estimator 233, estimates the capacity degradation rate V of secondary battery B under at least one of the untested conditions, which represent the test conditions that were not captured, based on the calculated capacity degradation rate V.The measured capacity degradation extent ΔC, the calculated capacity degradation rate V and the estimated capacity degradation rate V are stored as test results in storage unit 22 or the like in association with the respective test conditions. [Step S23]

[0069] The processing then proceeds to step S23, in which processor 23, by reference to memory unit 22 or the like, determines whether test results from the first degradation test, which differs from the degradation test performed in step S3, exist as past test results. In other words, processor 23 determines whether the processing of step S19 has been performed in the past in a series of information processing operations. [Step S24]

[0070] If it is determined that a test result from the first degradation test differs from the degradation test performed in step S3, processing proceeds to step S24, in which processor 23, acting as the correction unit 238, performs a correction processing of the capacity degradation rate V estimates from step S22. Specifically, processor 23, acting as the correction unit 238, corrects the calculated capacity degradation rate V of secondary battery B based on the capacity degradation extent ΔC of secondary battery B from the first degradation test under the reference test condition and outputs the corrected capacity degradation rate V.For example, processor 23 updates the order a through correction processing, correcting the calculated or estimated capacity degradation rate V so that it represents the time dependency represented by the updated order a. Details of this correction processing are described below. The processing then proceeds to step S25. If it is determined that there is no test result from the first degradation test that differs from the degradation test performed in step S3, the processing of step S24 is omitted, and the processing proceeds to step S25. [Step S25]

[0071] The processing then proceeds to step S25, in which the processor 23, acting as the map generation unit 239, generates a deterioration rate map M based on the calculated capacity deterioration rate V and the estimated capacity deterioration rate V. In the present embodiment, since the deterioration rate map M was already generated in step S7, the processor 23 updates the existing deterioration rate map M with the newly generated deterioration rate map M. [Step S26]

[0072] The processing then proceeds to step S26, in which processor 23 determines whether a predetermined number or more past test results have been accumulated. The past test results and the predetermined number are the same as those used in the determination in step S9. [Step S27]

[0073] If it is determined that a predetermined number or more of past test results have been accumulated, processing proceeds to step S27, in which the measurement error of the capacity degradation magnitude ΔC under the untested condition is determined and the untested condition is extracted with a relatively large measurement error.The specific aspect of this processing is arbitrary; however, processor 23 estimates, for example, the measurement error of the capacity degradation extent ΔC under the untested condition based on the degradation rate map using a procedure similar to that in step S10. Based on the estimation result, it classifies the untested conditions into the first classification and the second classification as the classification unit 240, and extracts the untested condition classified in the first classification as an untested condition with a relatively large measurement error. In performing such a classification, processor 23 carries out the classification based on at least condition (2) described above. Therefore, the classification reflects the reliability of the degradation rate map. [Step S28]

[0074] The processing then proceeds to step S28, in which processor 23 estimates the capacity degradation rate V under the untested conditions belonging to the first classification based on the reliability of the degradation rate map M and the measurement error mentioned above. Based on this estimate, processor 23 updates the degradation rate map M. For example, processor 23 adds the capacity degradation rate V, estimated based on the existing degradation rate map M, as training data for the degradation rate map M. Consequently, processor 23 updates the trained model, which represents the physical model of the secondary battery B. Processor 23 then regenerates the degradation rate map M based on the updated trained model and updates the existing degradation rate map M.In this way, the accuracy of the degradation rate map M can be further improved by adding an estimated value of the capacity degradation rate V as training data, with a certain degree of accuracy that is guaranteed. In other words, the processor 23, acting as the estimation unit 233, estimates the capacity degradation rate V of the secondary battery B under the untested conditions based on the degradation rate map M. Furthermore, the processor 23, acting as the classification unit 240, classifies the untested conditions into the first classification and the second classification based on the estimated capacity degradation rate V of the secondary battery B.The first classification is one that specifies an untested condition under which the error with respect to the capacity degradation rate V is greater than under the untested condition belonging to the second classification. The processor 23, which acts as the map generation unit 239, updates the degradation rate map M based on the reliability of the degradation rate map M and the capacity degradation rate V, which is estimated for at least the untested condition belonging to the first classification.

[0075] According to this configuration, the deterioration rate map M can be updated using the estimated capacity deterioration rate V for the untested condition where the error in the capacity deterioration rate V is relatively large. Thus, the accuracy of the deterioration rate map M can be further improved. In the present embodiment, the processor 23 enables a deterioration test to be performed, particularly in a region of the test condition where the measurement error of the capacity deterioration rate V is relatively small. For the test condition where the measurement error is relatively large, the processor 23 adds training data corresponding to the test condition to an estimated capacity deterioration rate V that is more reliable than if an actual test were performed.Processor 23 updates the deterioration rate map M using newly added training data based on such a test result and an estimation result. This can further improve the accuracy of the deterioration rate map.

[0076] This section describes an example of a process for extracting test conditions to estimate the capacity degradation rate V from the test conditions belonging to the first classification. First, the processor 23 sets the number of test conditions to be extracted. The number of test conditions to be extracted is arbitrary, for example, as long as it is less than the total number of test conditions of the degradation tests performed so far. Next, the test condition that maximizes one of the parameters defining the priority (in this embodiment, the standard deviation of the capacity degradation rate V) is selected. The processor 23 then captures the capacity degradation rate V under the selected test conditions, based on the latest degradation rate characteristic map M, as a virtual capacity degradation rate V.Next, processor 23 adds the captured virtual capacity degradation rate V_m to the training data and updates the standard deviation of the capacity degradation rate V. This can result in a smaller standard deviation of the capacity degradation rate V around the selected test conditions. Processor 23 then selects the test condition that again maximizes the standard deviation of the capacity degradation rate V in the updated state and repeats the above processing until the number of selected test conditions equals the number of test conditions to be extracted. In this way, the accuracy of the degradation rate map M can be improved, while the overhead of degradation testing is reduced by including test conditions under which no degradation test was actually performed in the degradation rate map M. [Step S29]

[0077] The processing then proceeds to step S29, in which processor 23 determines whether the termination condition has been met. The termination condition is arbitrary; for example, processor 23 determines that the termination condition is met if the mean standard deviation of the capacity degradation rate V under all test conditions within the search range, based on the most recent degradation rate map M, becomes less than or equal to a predetermined percentage of the mean standard deviation of the capacity degradation rate V in the initial degradation rate map M. The predetermined percentage can be set arbitrarily, for example, to 1%, 5%, 10%, etc.

[0078] When it is determined that the termination condition is met, the information processing system 1 outputs the most recent deterioration rate characteristic M as the final result and terminates this information processing.

[0079] If, however, it is determined that the termination condition is not met, the processing returns to step S8, and the processing described above is repeated to perform a second degradation test and update the degradation rate map M. In this cycle, processor 23 treats the second degradation test, performed in the most recent step S19, as the first degradation test. By repeating this information processing, the test results of the first degradation test are accumulated in memory unit 22, etc. 3.2 Details of search processing

[0080] This section describes the details of the search processing in step S12. Fig. Figure 7 is a flowchart that shows the search processing sequence. [Step S101]

[0081] First, in step S101, processor 23 determines whether the search target for the candidates for the test condition is the first secondary battery B. If the search target is the first secondary battery B, the virtual capacity degradation rate V_m, which is described below, has not yet been generated. Thus, processor 23 can determine whether the virtual capacity degradation rate V_m has been generated or not. If it is determined that the search target for the candidates for the test condition is the first secondary battery B, processing proceeds to step S102. Conversely, if it is determined that the search target for the candidates for the test condition is not the first secondary battery B—in other words, if it is determined that the search target is the second or a subsequent secondary battery B—processing proceeds to step S110. [Step S102]

[0082] A case is described in which the search target for the candidates for the test condition is determined to be the first secondary battery B along a time series, and processing proceeds to step 102. In step S102, processor 23 calculates and standardizes the standard deviation, slope, and reciprocal of the capacity degradation rate V for each test condition based on the existing estimate for the capacity degradation rate V. The specific aspects of the above processing are as described above. [Step S103]

[0083] The processing then proceeds to step S103, in which processor 23 calculates a priority for each test condition based on the standardized values. The priority set in step S11 is used. [Step S104]

[0084] The processing then proceeds to step S104, in which processor 23 assigns the highest-priority test conditions to secondary battery B, which is the search target. The number of candidates for the test condition to be assigned is not limited to one, but can be more than one. [Step S105]

[0085] The processing then proceeds to step S105, in which processor 23 determines whether the test conditions have been assigned to all of the secondary batteries B or not. [Step S106]

[0086] If it is determined that the test conditions have not been assigned to all secondary batteries B, processing proceeds to step S106, in which the capacity degradation rate V under the assigned test condition is estimated based on the most recent degradation rate map M. [Step S107]

[0087] Next, processing proceeds to step S107, in which processor 23 adds the newly estimated capacity degradation rate V as training data to the capacity degradation rate V, which is used to generate the degradation rate map M. [Step S108]

[0088] The processing then proceeds to step S108, where processor 23 generates a virtual degradation rate map M based on the added capacity degradation rate V. This allows the optimal test conditions to be assigned to the other secondary batteries B when the assigned degradation test is performed. Processor 23 can update the virtual degradation rate map M as the most recent degradation rate map M. The processing then returns to step S101 to determine whether the search target is the first secondary battery B. [Step S110]

[0089] If the processing of step S101 is performed via step S108, the determination result is negative, and the processing proceeds to step S110, as described above. In step S110, processor 23 calculates and standardizes the standard deviation, slope, and reciprocal of the capacity degradation rate V based on the virtual degradation rate map M generated in step S108. The processing above is the same as that in step S102. Then, each of the processing operations from step S103 to step S105 is performed. If step S105 determines that the test conditions have been assigned to all secondary batteries B, the processing in step S12 is terminated, the assigned test conditions are output as search results, and the processing proceeds to step S13. 3.3. Details of the correction process

[0090] This section describes the details of the correction processing that is performed in step S24. Fig. Figure 18 is a flowchart that shows the process of correction processing. [Step S201]

[0091] First, in step S201, processor 23 estimates the time dependence of the capacity degradation magnitude ΔC based on the test results of the degradation tests under the previous reference test conditions. The estimation of the time dependence is performed, for example, by optimizing the order a based on the error square method, etc., for the data set expressed by the capacity degradation magnitude ΔC and the cumulative test time T_s. Fig. Figure 9 shows an example of the estimation results for the time dependence of the capacity deterioration magnitude ΔC. As in Fig. As shown in Figure 9, the degradation test results under the reference test condition are represented as points P1. For several such points P1, the time dependence of the capacity degradation magnitude ΔC, when the order a of the test time is changed with a predetermined step size starting from 0.5, is expressed as a function L1. The processor 23 estimates that the order a for which the error between the function L1 and the points P1 becomes minimal is the order representing the most recent time dependence. [Step S202]

[0092] Returning to Fig.8. Processing then proceeds to step S202, in which processor 23 determines whether a change in time dependency has occurred by comparing the order a estimated in step S201 with the most recent order a (the default is 0.5). For example, if the absolute value of the difference between the order a estimated in step S201 and the most recent order a is within the allowed value, processor 23 determines that there is no change in time dependency, and processing proceeds to step S203. [Step S203]

[0093] In step S203, the processor 23 generates correction information indicating a change in the time dependency. This correction information can also be considered an instruction to change the order a and correct the capacity degradation rate V associated with this change in step S204, described below. The processor 23 does not need to continuously update the order a with respect to its initial value (0.5 in the present embodiment), but can temporarily change the order a if, in step S202, it is determined that a change in the time dependency has occurred. [Step S204]

[0094] The processing then proceeds to step S204, in which processor 23, based on the generated correction information, corrects the capacity degradation rate V under the test condition previously performed, thus ensuring consistency with the time dependency defined by the order a estimated in step S201. This allows the time dependency due to the type of secondary battery B to be taken into account in the degradation rate characteristic map M. The correction processing then ends in step S24.

[0095] In addition, in step S202, if the absolute value of the difference between the order a estimated in step S201 and the most recent order a is within the allowed value, the processing of step S203 and step S204 is omitted, and processor 23 terminates the correction processing of step S24 without making a correction. 4. Other

[0096] The aspects of information processing described above are merely examples, and the present disclosure is not limited to them.

[0097] The processor 23 can calculate the capacity degradation ΔC based on the impedance and open-circuit voltage of the secondary battery B. These values ​​are measured by the charging and discharging device 43 or the impedance measuring device 44. For example, the processor 23 calculates the capacity degradation ΔC from the impedance and open-circuit voltage by referencing a previously constructed correspondence relationship between the battery capacity C and the impedance and open-circuit voltage of the secondary battery B. The correspondence relationship is represented, for example, by a trained model constructed in advance according to any learning algorithm such as a random forest or a support vector machine, or from a pre-measured data table, etc.

[0098] In step S13, processor 23, acting as candidate output unit 236, further outputs candidates for the second degradation test based on the transition time t12. The transition time t12 is the time required to transition from the first degradation test to the second degradation test and is one of the indices representing the effort required to perform the second degradation test. In this case, the transition time t12 is one of the parameters that define the priority. For example, the priority is further defined by a weighted linear sum of the reciprocal of the transition time t12, in addition to the standard deviation of the capacity degradation rate V, the slope of the capacity degradation rate V, and the reciprocal of the capacity degradation rate V, as described above.The inverse of the transition time t12 increases as the time between the first deterioration test and the second deterioration test decreases. Therefore, the shorter the transition time t12 is under the test condition, the higher the priority.

[0099] In this case, for example, in step S11, processor 23, which acts as the priority calculation unit 235, further calculates the transition time t12 based on the test conditions of the first deterioration test and the test conditions of the second deterioration test. For example, processor 23 calculates the transition time t12 by dividing the difference between the temperature under the test conditions of the first deterioration test and the temperature under the test conditions of the second deterioration test by the upper limit of the heating rate of the constant temperature bath 41. Processor 23 can also calculate the transition time t12 based on the mean SOC or the SOC range included in the test conditions.For example, processor 23 compares the state of charge (SOC) of secondary battery B after the end of the first degradation test with the SOC at the start of the second degradation test and calculates the transition time t12 based on the current charging rate of secondary battery B. Processor 23 can use the maximum value of these respective transition times t12, or the sum of the transition times t12, as the transition time t12, which is used as a priority parameter.

[0100] The processor 23 further calculates the priority in accordance with the test condition of the second deterioration test based on the transition time t12, which is calculated in this way, and searches for candidates for the test condition of the second deterioration test based on the priority calculated in step S12.

[0101] The priority need not be defined by a linear sum of the parameters mentioned above, but can be defined by any function or table, for example, a nonlinear coupling, etc., of each of the parameters mentioned above. For example, the priority could be defined by a linear sum of the squares of the parameters mentioned above.

[0102] The procedure for determining whether or not secondary battery B needs to be replaced is not limited to the procedure mentioned above and can be any method. For example, processor 23 can calculate the state of health (SOH) of secondary battery B based on the total C_deg_total of the capacity degradation extent ΔC and the internal resistance of secondary battery B, and make the determination based on whether the SOH is greater than or equal to a standard value. The internal resistance of secondary battery B can be calculated, for example, by comparing the closed-circuit voltage with the open-circuit voltage measured by the charge and discharge device 43 or the impedance measuring device 44 when a certain current flows through secondary battery B.In addition to the measured capacity degradation ΔC, the processor 23 can also determine, based on the selected test condition of the second degradation test, whether the secondary battery B needs to be replaced. For example, the processor 23 can change the default value, which is comparable to C_deg_total / C_ini, depending on the load of the predetermined test conditions.

[0103] The deterioration test device 4 can have any configuration as long as it is possible to measure the degree of capacitance deterioration ΔC. Furthermore, the charging and discharging device 43 and the impedance measuring device 44 can be integrated. The deterioration test device 4 need not be included in the impedance measuring device 44. The measurement function for the degree of capacitance deterioration ΔC, which is included in the deterioration test device 4, can be implemented by other devices such as the information processing device 2. In other words, the distinction between the information processing device 2, the user terminal 3, and the deterioration test device 4 is for illustrative purposes only and does not represent a limitation.

[0104] The information processing device 2 can be an on-premises system or a cloud-based system. As a cloud-based information processing system 1, the functions and processing mentioned above can be provided, for example, in the form of SaaS (Software as a Service) or cloud computing.

[0105] In the embodiment described above, the information processing device 2 performs various storage and control operations; however, multiple external devices can be used instead of the information processing device 2. In other words, different types of information and programs can be distributed and stored in multiple external devices, using blockchain technology or the like.

[0106] The embodiment described above is not limited to information processing system 1 and can be an information processing method or an information processing program. The information processing method comprises each of the steps of information processing system 1. The information processing program enables at least one computer to execute each of the steps of information processing system 1.

[0107] The information processing system 1 described above and the like can be provided according to any of the following aspects.

[0108] (1) Information processing system comprising at least one processor configured to execute a program for performing the following steps: a capture step for capturing a test condition of a first deterioration test performed on a secondary battery and a test result of the first deterioration test, wherein the test condition includes a test time for performing the first deterioration test, and wherein the test result includes a capacity deterioration level of the secondary battery; a rate calculation step for calculating a capacity deterioration rate of the secondary battery under the test condition based on the capacity deterioration level;an estimation step to estimate, based on the calculated capacity degradation rate, a capacity degradation rate of the secondary battery under at least one of untested conditions, which represent test conditions that have not been recorded; a map generation step to generate a degradation rate map that specifies a correspondence relationship between the test condition and the capacity degradation rate, based on the calculated capacity degradation rate and the estimated capacity degradation rate; a priority calculation step to calculate, based on the generated degradation rate map, a priority for each of the untested conditions to perform a second degradation test;and a candidate output step to output, based on the calculated priority, a candidate for the second degradation test where at least one of the untested conditions is a test condition, in a user-selectable manner.

[0109] According to this configuration, the conditions for the next deterioration test can be selected more efficiently from the untested conditions. This allows for a more efficient improvement in the accuracy of the deterioration rate map.

[0110] (2) Information processing system according to (1) wherein: the priority calculation step includes calculating the priority based on at least one reliability of the deterioration rate map obtained by further performing a second deterioration test on the secondary battery under at least one of the untested conditions, and an effort of performing the second deterioration test.

[0111] According to this configuration, the interpretability of the significance of the conditions for the deterioration test to be performed next can be improved.

[0112] (3) Information processing system according to (1) or (2) wherein: the acquisition step further includes recording a history of the first deterioration test carried out on the secondary battery and the rate calculation step further includes calculating the capacity deterioration rate based on the history.

[0113] According to this configuration, a deterioration rate map can be generated using a secondary battery that has been subjected to deterioration testing in the past and has deteriorated, thereby reducing the effort required to perform deterioration tests.

[0114] (4) Information processing system according to one of (1) to (3), wherein: the acquisition step includes acquiring test conditions of several first deterioration tests performed on each of several secondary batteries and a capacity deterioration extent of each of the secondary batteries obtained from each of the several first deterioration tests, wherein at least one of the test conditions is a reference test condition set independently of a test condition selected by a user, and wherein at least one processor is trained to execute a program to perform a correction step to correct the calculated capacity deterioration rate of the secondary battery based on the capacity deterioration extent of the secondary battery from the first deterioration test under the reference test condition.

[0115] According to this configuration, the accuracy of the deterioration rate map can be further improved by correcting the deterioration rate calculation results obtained from a short-term deterioration test based on information obtained from a long-term deterioration test under the same test conditions.

[0116] (5) Information processing system according to one of (1) to (4) wherein: the at least one processor is designed to execute a program to perform a replacement determination step to determine, based on the detected extent of capacity deterioration, whether the secondary battery on which the second deterioration test is carried out needs to be replaced or not.

[0117] This configuration facilitates the performance of a deterioration test under a suitable load on the secondary battery.

[0118] (6) Information processing system according to one of (1) to (5) wherein: a reliability of the deterioration rate map is calculated based on at least one of statistics of the estimated capacity deterioration rate and a slope of the calculated capacity deterioration rate with respect to parameters relating to the test condition of the deterioration rate map.

[0119] This configuration allows for a more accurate deterioration rate map.

[0120] (7) Information processing system according to one of (1) to (6) wherein: the priority calculation step further includes calculating a transition time required for a transition from the first deterioration test to the second deterioration test, based on the test condition of the first deterioration test and a test condition of the second deterioration test, and the candidate output step further includes outputting a candidate for the second deterioration test based on the transition time.

[0121] According to this configuration, the deterioration test can be performed efficiently, while taking into account the time required for the entire deterioration test.

[0122] (8) Information processing system according to one of (1) to (7), wherein: the acquisition step further includes acquiring a reliability of the generated deterioration rate map, the estimation step includes estimating a capacity deterioration rate of the secondary battery under the untested conditions based on the deterioration rate map, which is configured to execute a program for further executing a classification step for classifying the untested conditions into a first classification and a second classification based on the estimated capacity deterioration rate of the secondary battery, the first classification being a classification that specifies an untested condition where a capacity deterioration rate error is greater than that of an untested condition belonging to the second classification,and the map generation step includes updating the deterioration rate map based on the reliability of the deterioration rate map and the capacity deterioration rate estimated for at least one untested condition belonging to the first classification.

[0123] According to this configuration, the deterioration rate map can be updated using the capacity deterioration rate estimation results for the untested conditions where the capacity deterioration rate error is relatively large, further improving the accuracy of the deterioration rate map.

[0124] (9) Information processing system according to one of (1) to (8), wherein: the at least one processor is configured to execute a program for further executing a priority setting step for setting a priority correspondence relationship based on a specification by a user, wherein the priority correspondence relationship specifies at least a correspondence relationship of the priority to a reliability of the deterioration rate characteristic by further performing the second deterioration test on the secondary battery and an effort to perform the second deterioration test, and the priority calculation step further includes calculating the priority based on the set priority correspondence relationship.

[0125] According to this configuration, suitable candidates for the second deterioration test can be output according to the elements deemed important by the user.

[0126] (10) Information processing procedure with each of the steps of the information processing system according to one of (1) to (9).

[0127] (11) Information processing program trained to enable at least one computer to perform each of the steps of the information processing system according to any of (1) to (9).

[0128] Naturally, the present revelation is not limited to the aspects mentioned above.

[0129] Finally, various embodiments of the present disclosure have been described; however, these are merely examples and are not intended to limit the scope of protection of the invention. New embodiments can be implemented in various other ways, and various omissions, substitutions, and modifications can be made within the scope of protection of the invention. The embodiments and their modifications are included within the scope of protection of the invention as described in the claims and their equivalents. REFERENCE MARK LIST 1 Information processing system 2 Information processing device 20 Communication bus 21 Communication unit 22 storage units 23 processor 231 recording unit 232 Rate calculation unit 233 unit of estimation 234 Priority setting unit 235 Priority Calculation Unit 236 candidate output unit 237 Exchange determination unit 238 correction units 239 Map generation unit 3 User terminal 30 Communication bus 31 Communication unit 32 storage units 33 processor 34 Display unit 35 HMI device 4. Deterioration test device 41 Constant temperature bath 42 Reference constant temperature bath 43 Loading and unloading device 44 Impedance measuring device B Secondary battery L1 function P1 point QUOTES INCLUDED IN THE DESCRIPTION

[0000] This list of documents cited by the applicant was automatically generated and is included solely for the reader's convenience. The list is not part of the German patent or utility model application. The DPMA accepts no liability for any errors or omissions. Cited patent literature

[0000] JP 2020-38138 A

[0004] Cited non-patent literature

[0000] J. Wang, D. Fleet, and A. Hertzmann, “Gaussian Process Dynamical Models”, NIPS 2005

[0044]

Claims

[1] Information processing system comprising at least one processor designed to execute a program to perform the following steps: a data acquisition step to capture a test condition of a first deterioration test performed on a secondary battery, and a test result of the first deterioration test, where the test condition includes a test time for performing the first deterioration test, the test result shows a degree of capacity degradation of the secondary battery; a rate calculation step to calculate a capacity degradation rate of the secondary battery under the test condition based on the extent of capacity degradation; an estimation step to estimate, based on the calculated capacity degradation rate, a capacity degradation rate of the secondary battery under at least one of untested conditions, which represent test conditions that have not been recorded; a map generation step to generate a deterioration rate map that specifies a correspondence relationship between the test condition and the capacity deterioration rate, based on the calculated capacity deterioration rate and the estimated capacity deterioration rate; a priority calculation step to calculate, based on the generated deterioration rate map, a priority for each of the untested conditions to perform a second deterioration test; and A candidate output step to output, based on the calculated priority, a candidate for the second degradation test where at least one of the untested conditions is a test condition, in a user-selectable manner. [2] Information processing system according to claim 1, wherein: The priority calculation step involves calculating the priority based on at least the reliability of the deterioration rate map obtained by further performing a second deterioration test on the secondary battery under at least one of the untested conditions, or the effort required to perform the second deterioration test. [3] Information processing system according to claim 1 or 2, wherein: The data acquisition step also includes recording a history of the first deterioration test performed on the secondary battery and The rate calculation step also includes calculating the capacity deterioration rate based on historical data. [4] Information processing system according to any one of claims 1 to 3, wherein: The acquisition step includes acquiring test conditions of several first deterioration tests performed on each of several secondary batteries, and a capacity deterioration magnitude of each of the secondary batteries obtained from the several first deterioration tests, wherein at least one of the test conditions is a reference test condition set independently of a candidate test condition selected by a user, and which has at least one processor trained to execute a program to perform a correction step to correct the calculated capacity degradation rate of the secondary battery based on the extent of capacity degradation of the secondary battery by the first degradation test under the reference test condition. [5] Information processing system according to any one of claims 1 to 4, wherein: which has at least one processor trained to execute a program to perform a replacement determination step to determine, based on the detected extent of capacity degradation, whether the secondary battery on which the second degradation test is performed needs to be replaced or not. [6] Information processing system according to any one of claims 1 to 5, wherein: The reliability of the deterioration rate map is calculated based on at least statistics of the estimated capacity deterioration rate or a slope of the calculated capacity deterioration rate with respect to parameters relating to the test condition of the deterioration rate map. [7] Information processing system according to any one of claims 1 to 6, wherein: The priority calculation step further includes calculating a transition time required for a transition from the first deterioration test to the second deterioration test, based on the test condition of the first deterioration test and a test condition of the second deterioration test. The candidate output step further includes outputting a candidate for the second deterioration test based on the transition time. [8] Information processing system according to any one of claims 1 to 7, wherein: The acquisition step also includes capturing the reliability of the generated deterioration rate map, The estimation step involves estimating the capacity degradation rate of the secondary battery under the untested conditions based on the degradation rate map. the at least one processor is configured to execute a program for further executing a classification step for classifying the untested conditions into a first classification and a second classification based on the estimated capacity degradation rate of the secondary battery, wherein the first classification is a classification that specifies an untested condition where an error in a capacity degradation rate is greater than that in an untested condition belonging to the second classification, and The map generation step includes updating the deterioration rate map based on the reliability of the deterioration rate map and the capacity deterioration rate, which is estimated for at least one untested condition belonging to the first classification. [9] Information processing system according to any one of claims 1 to 8, wherein: which is configured to execute a program for further executing a priority setting step for setting a priority correspondence relationship based on a specification by a user, wherein the priority correspondence relationship specifies at least a correspondence relationship of the priority to a reliability of the deterioration rate characteristic by further performing the second deterioration test on the secondary battery and an effort to perform the second deterioration test, and The priority calculation step further includes calculating the priority based on the set priority correspondence relationship. [10] Information processing method comprising each of the steps of the information processing system according to any one of claims 1 to 9. [11] Information processing program designed to enable at least one computer to execute each of the steps of the information processing system according to any one of claims 1 to 9.

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