Management system, and management method

Abstract

To provide a management system capable of properly evaluating the performance of rapid charging of secondary batteries according to a request of customers.SOLUTION: A management system 100 has an estimation unit 130 and a ranking unit 140. The estimation unit 130 estimates a fast charging performance of each battery cell by using a pre-generated estimation model based on manufacturing data relevant to the manufacturing step of each battery cell as a secondary battery. The ranking unit 140 ranks each battery cell based on the estimated fast charging performance.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to a management system and a management method, and more particularly to a management system and a management method for managing a secondary battery. [Background technology]

[0002] Patent Document 1 discloses a battery management system. The battery management system in Patent Document 1 evaluates the degree of deterioration of a plurality of batteries based on the voltage and current of the batteries charged and discharged by a power conversion device. The battery management system in Patent Document 1 also ranks each of the plurality of batteries according to its degree of deterioration. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2022-147157 A Summary of the Invention [Problem to be solved by the invention]

[0004] For customers of secondary batteries and products equipped with secondary batteries, quick charging performance is an important factor in evaluating secondary batteries. However, the technology disclosed in Patent Document 1 does not take quick charging performance into consideration when ranking batteries. Therefore, the technology disclosed in Patent Document 1 makes it difficult to appropriately evaluate the quick charging performance of secondary batteries in accordance with customer needs.

[0005] The present disclosure provides a management system and a management method capable of appropriately evaluating the rapid charging performance of a secondary battery in accordance with customer needs. [Means for solving the problem]

[0006] The management system according to the present disclosure is a management system for managing secondary batteries, and includes an estimation unit that estimates the rapid charging performance of each battery cell using an estimation model generated in advance based on manufacturing data relating to the manufacturing process of each battery cell that is a secondary battery, and a ranking unit that ranks each battery cell based on the estimated rapid charging performance.

[0007] The management method disclosed herein is a method for managing secondary batteries, which estimates the quick charging performance of each battery cell using a pre-generated estimation model based on manufacturing data related to the manufacturing process for each battery cell that is a secondary battery, and ranks each battery cell based on the estimated quick charging performance. Effect of the Invention

[0008] According to the present disclosure, it is possible to provide a management system and a management method that are capable of appropriately evaluating the rapid charging performance of a secondary battery in accordance with customer requests. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 illustrates a configuration of a management system according to a first embodiment. [Diagram 2] 4 is a flowchart showing a management method executed by the management system according to the first embodiment. [Diagram 3] FIG. 4 is a diagram illustrating manufacturing data according to the first embodiment. [Figure 4] FIG. 4 is a diagram for explaining the process of the ranking unit according to the first embodiment. [Diagram 5] FIG. 4 is a diagram illustrating an example of rank information according to the first embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, the present embodiment will be described with reference to the drawings. However, the present invention is not limited to the following embodiment. In addition, the following description and drawings are appropriately simplified for clarity of explanation.

[0011] (Embodiment 1) 1 is a diagram showing a configuration of a management system 100 according to the first embodiment. The management system 100 according to the first embodiment is, for example, a computer such as a server. The management system 100 may be realized by, for example, cloud computing. The management system 100 may also be realized by a plurality of computers. In this case, a plurality of components of the management system 100, which will be described later, may be realized by physically different computers.

[0012] The management system 100 estimates the quick charge performance of each battery cell using an estimation model generated in advance based on manufacturing data related to the manufacturing process of each battery cell, which is a secondary battery. The management system 100 also ranks each battery cell based on the estimated quick charge performance. This will be described in detail later.

[0013] The management system 100 has, as its main hardware components, a control unit 102, a storage unit 104, a communication unit 106, and an interface unit 108 (IF; Interface). The control unit 102, the storage unit 104, the communication unit 106, and the interface unit 108 are connected to each other via a data bus or the like. When the management system 100 is realized by multiple computers, each of the multiple computers may have the hardware configuration shown in FIG. 1.

[0014] The control unit 102 is a processor such as a CPU (Central Processing Unit). The control unit 102 has a function as a calculation device that performs control processing and calculation processing. The control unit 102 may have multiple processors. The storage unit 104 is a storage device such as a memory or a hard disk. The storage unit 104 is, for example, a ROM (Read Only Memory) or a RAM (Random Access Memory). The storage unit 104 has a function for storing a control program and a calculation program executed by the control unit 102. That is, the storage unit 104 (memory) stores one or more instructions. The storage unit 104 also has a function for temporarily storing processing data and the like. The storage unit 104 may include a database. The storage unit 104 may also have multiple memories.

[0015] The communication unit 106 performs processing required for communicating with other devices via a network. The communication unit 106 may include a communication port, a router, a firewall, and the like. The interface unit 108 is, for example, a user interface (UI). The interface unit 108 has an input device such as a keyboard, a touch panel, or a mouse, and an output device such as a display or a speaker. The interface unit 108 may be configured such that the input device and the output device are integrated, such as a touch screen (touch panel). The interface unit 108 accepts data input operations by a user (operator), and outputs information to the user.

[0016] Moreover, the management system 100 according to the first embodiment has, as its components, an estimation model generating unit 112, an estimation model storage unit 114, a manufacturing data acquiring unit 120, and a manufacturing data storage unit 122. Moreover, the management system 100 according to the first embodiment has, as its components, an estimation unit 130, a ranking unit 140, a rank storage unit 142, a rank display unit 144, a request acquiring unit 150, and a selection unit 160.

[0017] Each of the above-mentioned components can be realized, for example, by executing a program under the control of the control unit 102. More specifically, each of the components can be realized by the control unit 102 executing a program (instruction) stored in the storage unit 104. Also, each of the components may be realized by recording a necessary program in an arbitrary non-volatile recording medium and installing it as necessary. Also, each of the components may be realized not only by software by a program, but also by any combination of hardware, firmware, and software. Also, each of the components may be realized by using an integrated circuit programmable by a user, such as an FPGA (field-programmable gate array) or a microcomputer. In this case, the integrated circuit may be used to realize a program composed of each of the above-mentioned components.

[0018] 2 is a flowchart showing a management method executed by the management system 100 according to the first embodiment. The estimation model generating unit 112 of the management system 100 generates an estimation model (step S102). The generated estimation model is stored in the estimation model storage unit 114.

[0019] Specifically, the estimation model generation unit 112 uses manufacturing data related to the manufacturing process when manufacturing the battery cell to generate an estimation model that estimates the quick charge performance of the battery cell. For example, the estimation model generation unit 112 may estimate quick charge time as the quick charge performance. Also, for example, the estimation model generation unit 112 may estimate high-rate resistance (the number of quick charge operations allowed per day: hereinafter simply referred to as "the number of quick charge operations") as the quick charge performance. Note that the shorter the quick charge time, the better the quick charge performance. Also, the more the number of quick charge operations, the better the quick charge performance. Note that the estimated quick charge performance is not limited to the quick charge time and high-rate resistance.

[0020] More specifically, the estimation model generation unit 112 may generate an estimation model that is a multiple regression equation by multiple regression analysis with multiple factors that affect the quick charge performance indicated in the manufacturing data as explanatory variables and the quick charge performance as a response variable. For example, the estimation model generation unit 112 may generate an estimation model that estimates the quick charge time by multiple regression analysis with multiple factors that affect the quick charge time as explanatory variables and the quick charge time as a response variable. Also, for example, the estimation model generation unit 112 may generate an estimation model that estimates high-rate resistance by multiple regression analysis with multiple factors that affect the high-rate resistance as explanatory variables and the high-rate resistance as a response variable.

[0021] FIG. 3 is a diagram illustrating manufacturing data according to the first embodiment. Values ​​indicated by the manufacturing data may differ for each battery cell related to the manufacturing data. The manufacturing data includes material data and process data. The material data is data related to materials used in the manufacture of the battery cell. The material data indicates the quality and specifications of the material, such as the physical property values ​​of the material. The material data is obtained, for example, at the time of delivery of the material, that is, before the manufacturing process. Values ​​indicated by the material data may vary for each material. Thus, the material data may differ for each corresponding battery cell. In the example of FIG. 3, the material data indicates the Li / M ratio of the positive electrode, the Ni / M ratio of the positive electrode, and the specific surface area of ​​the positive electrode. The material data also indicates the specific surface area of ​​the negative electrode. For example, the material data also indicates the air permeability of the separator and the coating amount of the separator. For example, the material data also indicates the additive ratio of the electrolyte.

[0022] The process data is data determined in the manufacturing process of the battery cell. The process data is obtained in the manufacturing process of the battery cell. The value indicated by the process data may vary for each manufacturing process. Thus, the process data may differ for each corresponding battery cell. The process data indicates, for example, the coating amount of the positive electrode and the density of the positive electrode. Also, for example, the process data indicates the coating amount of the negative electrode and the density of the negative electrode. Also, for example, the process data indicates the liquid amount (amount of electrolyte) and the opposing capacity ratio (ratio of the basis weight of the positive electrode and the negative electrode) in a process ("combination") after using a wound body or a laminate using a positive electrode, a negative electrode, and a separator. Also, for example, the process data indicates the thickness of the battery cell.

[0023] Here, in the example of FIG. 3, the items marked with a circle in the "quick charge time" of the manufacturing data are factors that affect the quick charge time of the battery cell. Therefore, in the example of FIG. 3, the specific surface area of ​​the negative electrode, the coating amount of the separator, the coating amount of the negative electrode, the density of the negative electrode, and the opposing capacity ratio of the "combination" are factors that affect the quick charge time. Therefore, the estimation model generation unit 112 performs multiple regression analysis using these multiple factors shown in the manufacturing data of each of the multiple battery cells as explanatory variables and the quick charge time of the corresponding battery cell as the objective variable. As a result, the estimation model generation unit 112 generates an estimation model that estimates the quick charge time. It is assumed that the quick charge time of the battery cell related to the manufacturing data used in generating the estimation model has been known in advance.

[0024] In the example of FIG. 3, the items marked with a circle in the "high rate resistance" of the manufacturing data are factors that affect the high rate resistance of the battery cell. Therefore, in the example of FIG. 3, the specific surface area of ​​the negative electrode, the coating amount of the positive electrode, the density of the positive electrode, the coating amount of the negative electrode, the density of the negative electrode, the liquid amount of the "combination", and the thickness of the battery cell are factors that affect the high rate resistance. Therefore, the estimation model generation unit 112 performs multiple regression analysis using these multiple factors shown in the manufacturing data of each of the multiple battery cells as explanatory variables and the high rate resistance (number of fast charges) of the corresponding battery cell as the objective variable. As a result, the estimation model generation unit 112 generates an estimation model that estimates the high rate resistance. It is assumed that the high rate resistance of the battery cell related to the manufacturing data used in generating the estimation model has been determined in advance.

[0025] The management system 100 assesses the rapid charging performance of the battery cells (step S110). Specifically, the management system 100 performs the processes of S120 to S140, which will be described later, for each battery cell to be assessed. The manufacturing data acquisition unit 120 acquires manufacturing data of the battery cell to be assessed (step S120). The acquired manufacturing data is stored in the manufacturing data storage unit 122.

[0026] The estimation unit 130 estimates the quick charge performance of the battery cell to be assessed (step S130). Specifically, the estimation unit 130 estimates the quick charge performance of the battery cell to be assessed using an estimation model stored in the estimation model storage unit 114 based on manufacturing data of the battery cell to be assessed. That is, the estimation unit 130 estimates the quick charge performance of each battery cell using an estimation model generated in advance based on manufacturing data related to the manufacturing process of each battery cell. The estimation unit 130 may estimate at least one of the quick charge time and high rate resistance of each battery cell as the quick charge performance.

[0027] For example, the estimation unit 130 estimates the quick charge time of the battery cell to be assessed using an estimation model for estimating the quick charge time. Specifically, the estimation unit 130 substitutes values ​​of multiple factors that affect the quick charge time, which are included in the manufacturing data of the battery cell to be assessed, as explanatory variables into a multiple regression equation, which is the estimation model. The estimation unit 130 obtains the value calculated by the multiple regression equation (objective variable) as an estimate of the quick charge time.

[0028] Also, for example, the estimation unit 130 estimates the high-rate resistance of the battery cell to be assessed using an estimation model for estimating high-rate resistance (number of rapid charging operations). Specifically, the estimation unit 130 inputs values ​​of multiple factors that affect the high-rate resistance, which are included in the manufacturing data of the battery cell to be assessed, as explanatory variables into a multiple regression equation, which is the estimation model. The estimation unit 130 acquires a value (objective variable) calculated by the multiple regression equation as an estimated value of the high-rate resistance (number of rapid charging operations).

[0029] The ranking unit 140 ranks the battery cells to be assessed (step S140). Specifically, the ranking unit 140 ranks each battery cell based on the rapid charging performance estimated in the process of S130. More specifically, the ranking unit 140 ranks each battery cell so that the higher the rapid charging performance of the battery cell, the higher the rank. In addition, when the rapid charging time is estimated, the ranking unit 140 may rank each battery cell based on the estimated rapid charging time. In addition, when the high-rate resistance is estimated, the ranking unit 140 may rank each battery cell based on the estimated high-rate resistance. The ranking unit 140 may generate rank information indicating the rank assigned to each battery cell. The rank information is stored in the rank storage unit 142.

[0030] FIG. 4 is a diagram for explaining the processing of the ranking unit 140 according to Embodiment 1. FIG. 4 shows an example of a ranking method. As indicated by arrow RaA, the ranking unit 140 may perform ranking for each battery cell based on the rapid charging time estimated in the process of S130. In this case, the ranking unit 140 performs ranking such that a battery cell with a shorter rapid charging time has a higher rank.

[0031] Specifically, when the rapid charging time estimated for the battery cell to be evaluated is shorter than a predetermined threshold ThAa (when the rapid charging time is "short"), the ranking unit 140 may assign the highest rank A. Also, when the rapid charging time estimated for the battery cell to be evaluated is equal to or greater than a predetermined threshold ThAb (when the rapid charging time is "long"), the ranking unit 140 may assign the lowest rank C. Here, ThAa < ThAb. Further, when the rapid charging time estimated for the battery cell to be evaluated is equal to or greater than the threshold ThAa and shorter than the threshold ThAb (when the rapid charging time is "medium"), the ranking unit 140 may assign a rank B that is lower than rank A and higher than rank C.

[0032] Also, as indicated by arrow RaB, the ranking unit 140 may perform ranking for each battery cell based on the high rate tolerance (number of rapid charging times) estimated in the process of S130. In this case, the ranking unit 140 performs ranking such that a battery cell with a larger number of rapid charging times has a higher rank.

[0033] Specifically, the ranking unit 140 may assign the highest rank A when the estimated number of quick charges for the battery cell to be assessed is greater than a predetermined threshold ThBa (when the number of quick charges is "high"). The ranking unit 140 may also assign the lowest rank C when the estimated number of quick charges for the battery cell to be assessed is equal to or less than a predetermined threshold ThBb (when the number of quick charges is "low"), where ThBa>ThBb. The ranking unit 140 may also assign rank B, which is lower than rank A and higher than rank C, when the estimated number of quick charges for the battery cell to be assessed is equal to or less than a threshold ThBa and greater than the threshold ThBb (when the number of quick charges is "medium").

[0034] Furthermore, as indicated by an arrow RaC, the ranking unit 140 may rank each battery cell based on the quick charge time and high rate resistance (number of quick charges) estimated in the process of S130. In this case, the ranking unit 140 may rank the battery cells such that the shorter the quick charge time and the more times the quick charges are performed, the higher the rank of the battery cell.

[0035] Specifically, the ranking unit 140 may assign the highest rank A to a battery cell whose estimated quick charge time is shorter than a threshold ThAa and whose estimated number of quick charges is greater than a threshold ThBa. The ranking unit 140 may also assign rank B (rank B1), which is the next highest rank after rank A, to a battery cell whose estimated quick charge time is equal to or greater than a threshold ThAa and shorter than a threshold ThAb and whose estimated number of quick charges is greater than a threshold ThBa. The ranking unit 140 may also assign rank B (rank B2) to a battery cell whose estimated quick charge time is shorter than a threshold ThAa and whose estimated number of quick charges is equal to or less than a threshold ThBa and greater than a threshold ThBb. The ranks B1 and B2 may be the same rank or different ranks.

[0036] The ranking unit 140 may also assign rank C (rank C1), which is the next highest rank after rank B, to battery cells whose estimated quick charge time is equal to or greater than a threshold ThAb and whose estimated number of quick charges is greater than a threshold ThBa. The ranking unit 140 may also assign rank C (rank C2) to battery cells whose estimated quick charge time is equal to or greater than a threshold ThAa and shorter than a threshold ThAb and whose estimated number of quick charges is equal to or less than a threshold ThBa and greater than a threshold ThBb. The ranking unit 140 may also assign rank C (rank C3) to battery cells whose estimated quick charge time is shorter than a threshold ThAa and whose estimated number of quick charges is less than a threshold ThBb. The ranks C1, C2, and C3 may be the same rank or different ranks.

[0037] The ranking unit 140 may also assign rank D (rank D1), which is the next highest rank after rank C, to battery cells whose estimated quick charge time is equal to or greater than a threshold ThAb, and whose estimated number of quick charges is equal to or less than a threshold ThBa and is greater than a threshold ThBb. The ranking unit 140 may also assign rank D (rank D2) to battery cells whose estimated quick charge time is equal to or greater than a threshold ThAa and is shorter than the threshold ThAb, and whose estimated number of quick charges is equal to or less than a threshold ThBb. The ranks D1 and D2 may be the same rank or different ranks. The ranking unit 140 may also assign rank E, which is the lowest rank, to battery cells whose estimated quick charge time is equal to or greater than a threshold ThAb, and whose estimated number of quick charges is equal to or less than a threshold ThBb.

[0038] FIG. 5 is a diagram illustrating rank information according to the first embodiment. The rank information associates, for each battery cell, the identification information of the battery cell, manufacturing data related to the battery cell, and a rank assigned to the battery cell. The rank information illustrated in FIG. 5 is generated by the ranking method indicated by the arrow RaC in FIG. 4. In the rank information illustrated in FIG. 5, for example, the battery cell #1, the manufacturing data #1, and "rank: A (rapid charging time: short, number of rapid charging operations: many)" are associated with each other. Also, for example, the battery cell #2, the manufacturing data #2, and "rank: B2 (rapid charging time: short, number of rapid charging operations: medium)" are associated with each other. Also, for example, the battery cell #3, the manufacturing data #3, and "rank: B1 (rapid charging time: medium, number of rapid charging operations: many)" are associated with each other. Also, for example, the battery cell #4, the manufacturing data #4, and "rank: E (rapid charging time: long, number of rapid charging operations: few)" are associated with each other.

[0039] Here, the price of the battery cell may correspond to the rank of the battery cell. In other words, the higher the rank of the battery cell, the higher the price may be set. In other words, the better the quick charging performance of the battery cell, the higher the price may be set. Note that the correspondence between the rank of the battery cell and the price of the battery cell may be appropriately set by the user according to the market situation.

[0040] The management system 100 selects battery cells according to the customer's request (step S150). Specifically, the rank display unit 144 performs processing for displaying the above-mentioned rank information. For example, the rank display unit 144 causes the interface unit 108 to display the rank information. The request acquisition unit 150 also acquires the customer's request for the battery cell. Specifically, the request acquisition unit 150 acquires a request regarding the performance of the battery cell. In other words, the request acquisition unit 150 acquires a request regarding the rank of the battery cell. For example, the request acquisition unit 150 may acquire a request that the customer desires a battery cell with a short quick charge time and a large number of quick charge cycles. For example, the request acquisition unit 150 may acquire a request that the customer desires a battery cell with a short quick charge time and a medium number of quick charge cycles. For example, the request acquisition unit 150 may acquire a request that the customer desires a battery cell with no particular preference for quick charge performance and a low price. The request acquiring unit 150 may acquire the request of the customer by, for example, a user operating the interface unit 108 .

[0041] The selection unit 160 performs a process for selecting a battery cell of a rank according to the customer's request. When the customer's request indicates a battery cell with good quick charging performance, the selection unit 160 selects a battery cell of a high rank (for example, battery cell #1 in FIG. 5). On the other hand, when the customer's request indicates a battery cell with a low price, the selection unit 160 selects a battery cell of a low rank (for example, battery cell #4 in FIG. 5). Also, for example, when the customer's request indicates a battery cell with a short quick charging time regardless of the number of times it is charged, the selection unit 160 may select rank A, rank B2, or rank C3 as exemplified by the arrow RaC in FIG. 4 according to the customer's budget, etc. Also, for example, when the customer's request indicates a battery cell with a large number of times it is charged regardless of the quick charging time, the selection unit 160 may select rank A, rank B1, or rank C1 as exemplified by the arrow RaC in FIG. 4 according to the customer's budget, etc. The selection unit 160 may cause the interface unit 108 to display a screen for the user to select a battery cell. The user may check the rank information and the customer's request and operate the interface unit 108 to select the battery cells.

[0042] The management system 100 according to the first embodiment is configured to estimate the quick charge performance of each battery cell based on the manufacturing data, and to rank each battery cell based on the estimated quick charge performance. Therefore, the management system 100 according to the first embodiment can evaluate the battery cells according to the rank. In other words, the quick charge performance of the battery cells (secondary batteries) can be appropriately evaluated in accordance with the customer's request. For example, if a customer desires a battery cell with good quick charge performance, a high-ranked battery cell can be provided to the customer. Also, if a customer desires a cheap battery cell, a low-ranked battery cell can be provided to the customer.

[0043] In addition, the quick charge performance of the battery cell may be determined according to the physical property values ​​determined for each material of the battery cell, such as the physical property values ​​of the active material and the physical property values ​​of the electrodes, and the physical property values ​​determined in the manufacturing process of the battery cell. However, there is a variation in the physical property values ​​determined for each material of the battery cell and the physical property values ​​determined in the manufacturing process of the battery cell. Therefore, it is difficult to appropriately set the quick charge performance of the battery cell. Therefore, the quick charge performance of the battery cell at the time of shipment may be set lower than that determined from the above physical property values. As a result, depending on the usage situation of the battery cell, the quick charge performance that can actually be exhibited may not be exhibited. In contrast, the management system 100 according to the first embodiment is configured to estimate the quick charge performance using manufacturing data related to the manufacturing process of the battery cell, and to rank each battery cell based on the estimated quick charge performance. Therefore, ranking can be performed for each battery cell according to the quick charge performance that is estimated to be actually exhibited. In other words, a different rank can be given to each battery cell according to the estimated quick charge performance. This increases the likelihood that the battery cell will exhibit its actual rapid charging performance when it is used.

[0044] The management system 100 according to the first embodiment may select battery cells of a rank according to a customer's request, thereby making it possible to select battery cells with rapid charging performance that meets the customer's request.

[0045] Moreover, the management system 100 according to the first embodiment is configured to estimate at least one of the quick charge time and the high rate resistance of each battery cell as the quick charge performance. Then, the management system 100 according to the first embodiment is configured to rank each battery cell based on the estimated quick charge time when the quick charge time is estimated. Also, the management system 100 according to the first embodiment is configured to rank each battery cell based on the estimated high rate resistance when the high rate resistance is estimated. Therefore, it is possible to assign different ranks to each battery cell according to the quick charge time and the high rate resistance.

[0046] In addition, in the first embodiment, the estimation model used to estimate the quick charging performance is a multiple regression equation generated by multiple regression analysis with multiple factors that are indicated in the manufacturing data and that affect the quick charging performance as explanatory variables and the quick charging performance as a response variable. With such a configuration, the user can easily recognize what factors affect the quick charging performance. In other words, the multiple regression equation can clarify the factors that affect the quick charging performance. Furthermore, the coefficient of each term in the multiple regression equation can clarify the degree of influence of each factor that affects the quick charging performance.

[0047] (Modification) The present invention is not limited to the above-described embodiment, and can be modified as appropriate without departing from the spirit of the present invention. For example, the estimation model is not limited to a multiple regression equation. The estimation model may be generated by a machine learning algorithm such as a neural network. Specifically, the estimation model may be generated by machine learning so as to input manufacturing data and output quick charging performance. In addition, the estimation model generated by the machine learning algorithm may not clearly indicate factors that affect quick charging performance. Therefore, if it is desired to clearly indicate factors that affect quick charging performance, it is better to generate the estimation model by multiple regression analysis.

[0048] In the above embodiment, the ranking unit 140 ranks the quick charging time into three stages, but the present invention is not limited to this configuration. Any number of stages may be assigned to the rank. Furthermore, it is not necessary to perform the ranking discretely as described in the above embodiment. The assigned rank may be expressed by a continuous numerical value. The same applies to the high-rate resistance.

[0049] Furthermore, when ranking is performed based on both the rapid charge time and the high-rate resistance, the ranking is not limited to the example shown by the arrow RaC in Fig. 4. For example, rank B1 when the rapid charge time is "medium" and the number of rapid charge times is "high" and rank B2 when the rapid charge time is "short" and the number of rapid charge times is "medium" do not have to be the same as each other. These ranks may be different depending on which is given more importance, the rapid charge time or the number of rapid charge times (high-rate resistance). The same applies to the cases of other rapid charge times and other numbers of rapid charge times.

[0050] Furthermore, in the case where the rapid charge time is more important than the number of rapid charge times (high rate resistance), the ranking may be performed as follows. As in the above-described embodiment, in the following ranking example, the later the alphabet, the lower the rank. The rank may be A when the rapid charge time is "short" and the number of rapid charge times is "high", the rank may be B when the rapid charge time is "short" and the number of rapid charge times is "medium", and the rank may be C when the rapid charge time is "short" and the number of rapid charge times is "low". The rank may be D when the rapid charge time is "medium" and the number of rapid charge times is "high", the rank may be E when the rapid charge time is "medium" and the number of rapid charge times is "medium", and the rank may be F when the rapid charge time is "medium" and the number of rapid charge times is "low". In addition, a rank may be G when the quick charge time is "long" and the number of quick charges is "high," a rank may be H when the quick charge time is "long" and the number of quick charges is "medium," and a rank may be I when the quick charge time is "long" and the number of quick charges is "low."

[0051] The above-mentioned program includes a set of instructions (or software code) for making the computer perform one or more functions described in the embodiments when the program is loaded into the computer. The program may be stored in a non-transitory computer-readable medium or a tangible storage medium. By way of example and not limitation, the computer-readable medium or the tangible storage medium includes random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drive (SSD) or other memory technology, CD-ROM, digital versatile disk (DVD), Blu-ray® disk or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device. The program may be transmitted on a transitory computer-readable medium or a communication medium. By way of example and not limitation, the transitory computer-readable medium or the communication medium includes electrical, optical, acoustic, or other forms of propagating signals. [Explanation of symbols]

[0052] 100 management system, 112 estimated model generation unit, 114 estimated model storage unit, 120 manufacturing data acquisition unit, 122 manufacturing data storage unit, 130 estimation unit, 140 ranking unit, 142 rank storage unit, 144 rank display unit, 150 request acquisition unit, 160 selection unit

Claims

1. A management system for managing a secondary battery, an estimation unit that estimates a quick-charging performance of each battery cell using an estimation model that is generated in advance based on manufacturing data related to a manufacturing process of each battery cell that is a secondary battery; a ranking unit that ranks each of the battery cells based on the estimated quick charging performance; A management system having:

2. A selection unit that performs processing to select the battery cells of a rank according to customer requirements; The management system of claim 1 further comprising:

3. the estimation unit estimates at least one of a quick-charge time and a high-rate resistance of each of the battery cells as the quick-charge performance; The ranking unit is When the quick charge time is estimated, ranking each of the battery cells based on the estimated quick charge time; When the high-rate resistance is estimated, ranking is performed for each of the battery cells based on the estimated high-rate resistance. The management system according to claim 1 .

4. The estimation model is a multiple regression equation generated by multiple regression analysis using a plurality of factors that are indicated in the manufacturing data and that affect the quick charging performance as explanatory variables and the quick charging performance as a response variable. The management system according to claim 1 .

5. A method for managing a secondary battery, comprising: estimating a quick-charging performance of each battery cell using an estimation model generated in advance based on manufacturing data relating to a manufacturing process of each battery cell that is a secondary battery; ranking each of the battery cells based on the estimated quick charging performance; Management method.

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