Diagnostic program, diagnostic device, diagnostic system

Abstract

A diagnosis program (P) that diagnoses a battery pack (2) including a plurality of battery modules (2a) causes a processor (10) to acquire module identification information (B), module configuration information (C), and usage history information (D) of the plurality of battery modules (2a) included in the battery pack (2), diagnose the plurality of battery modules (2a) on the basis of the usage history information (D), and associate a diagnosis result obtained by the diagnosis with the module identification information (B) on the basis of the module configuration information (C).

Description

[0001] Cross-referencing of related applications

[0002] This application is based on Japanese Patent Application No. 2024-53162, filed on March 28, 2024, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This disclosure relates to techniques for diagnosing batteries. Background Technology

[0004] Previously, when reusing used battery packs, a method was known to involve disassembling the recycled battery pack and individually measuring the battery characteristics of each battery module by wiring them. This method increases the time required for wiring and other operations. Therefore, Patent Document 1 proposes a method for comprehensively measuring the battery characteristics of multiple battery modules before disassembling the battery pack. This reduces the time required for wiring and other operations.

[0005] Patent Document 1: Japanese Patent Application Publication No. 2022-11803 Summary of the Invention

[0006] In the case of the method in Patent Document 1, it is necessary to record the correspondence between the identification information of each battery module and the battery characteristics while disassembling the battery pack. If the association between each battery module and the battery characteristics is misunderstood in this process, it is difficult to accurately determine the battery characteristics of each battery module.

[0007] This disclosure aims to provide a technique that is effective in accurately determining the battery characteristics of the battery modules contained in a battery pack while minimizing operating time.

[0008] One aspect of this disclosure is a diagnostic procedure for diagnosing a battery pack comprising multiple battery modules, wherein the processor:

[0009] Obtain module identification information, module configuration information, and usage history information of the multiple battery modules contained in the aforementioned battery pack;

[0010] Based on the aforementioned historical usage information, diagnose multiple of the aforementioned battery modules; and

[0011] Based on the module configuration information above, the diagnostic results obtained through this diagnosis will be associated with the module identification information above.

[0012] Another aspect of this disclosure is a diagnostic device for diagnosing a battery pack comprising multiple battery modules, wherein it includes:

[0013] The information acquisition unit acquires module identification information, module configuration information, and usage history information of the multiple battery modules contained in the battery pack.

[0014] The diagnostic department diagnoses multiple of the aforementioned battery modules based on the above-mentioned usage history information; and

[0015] The association unit associates the diagnostic results obtained by the diagnostic unit with the identification information of the module based on the module configuration information.

[0016] Based on the methods described above, the battery characteristics of the multiple battery modules contained in the battery pack can be accurately determined while minimizing operating time.

[0017] Furthermore, the reference numerals in parentheses in the claims indicate the correspondence with the specific units described in the embodiments described later, and do not limit the technical scope of this disclosure. Attached Figure Description

[0018] The above-described objects, as well as other objects, features, and advantages of this disclosure, will become more apparent from the following detailed description with reference to the accompanying drawings. The accompanying drawings are:

[0019] Figure 1 This is a block diagram showing the structure of the diagnostic system according to the first embodiment.

[0020] Figure 2 This is a flowchart of the diagnostic process of the diagnostic system in the first embodiment.

[0021] Figure 3 It is used for explanation Figure 2 A diagram of the battery diagnostic model used in the diagnostic process.

[0022] Figure 4 This is a block diagram showing the structure of the diagnostic system according to the second embodiment.

[0023] Figure 5 This is a block diagram showing the structure of the diagnostic system according to the third embodiment.

[0024] Figure 6 This is a block diagram showing the structure of the diagnostic system according to the fourth embodiment.

[0025] Figure 7 This is a block diagram showing the structure of the diagnostic system according to the fifth embodiment.

[0026] Figure 8 This is a flowchart of the diagnostic processing of the diagnostic system according to the fifth embodiment.

[0027] Figure 9 It is used for explanation Figure 8 The diagram shows a specific example of a simplified diagnosis.

[0028] Figure 10 This is a block diagram showing the structure of the diagnostic system according to the sixth embodiment.

[0029] Figure 11 This is a flowchart of the diagnostic process of the diagnostic system according to the sixth embodiment. Detailed Implementation

[0030] The battery diagnostic techniques described above will now be explained in detail with reference to the accompanying drawings.

[0031] (First Implementation)

[0032] Figure 1 The diagram shows a diagnostic system 101 according to a first embodiment. This diagnostic system 101 is used to diagnose the battery pack 2 installed in a vehicle 1, such as an electric vehicle or a hybrid vehicle. For example, the vehicle 1 equipped with the battery pack 2 is sent by a user U to a dealer V. The battery pack 2 is then sent from the dealer V to a repair shop 20, where diagnostics of the battery pack 2 are performed.

[0033] At repair shop 20, based on the receipt of battery pack 2, the remanufactured product is sent to distributor V. The remanufactured product can be a repaired battery pack 2 sent from distributor V, or it can be an item different from the battery pack 2 sent from distributor V.

[0034] The functions of the diagnostic system 101 are performed by the processor 10. The term "processor 10" here broadly encompasses any processing unit in a computer's architecture that performs data processing and conversion, executes programs, and controls other devices. The processor 10 may be a CPU (Central Processing Unit) that manages the overall control of the computer, or an MPU (Micro Processing Unit) that integrates some of the functions of a CPU.

[0035] 1. Structure of Battery Pack 2

[0036] like Figure 1 As shown, the battery pack 2 includes multiple battery modules 2a and a main battery management unit 3 (hereinafter referred to as "main BMU3"). Each of the multiple battery modules 2a includes a combined battery consisting of multiple battery cells and a satellite battery management unit 4 (hereinafter referred to as "satellite BMU4"). The battery cells are rechargeable secondary batteries.

[0037] The diagnostic system 101 includes a battery information acquisition device 21, a maintenance terminal 24, a diagnostic device 40, a battery information management database 50, and a manufacturing information management database 61. The battery information acquisition device 21 and the maintenance terminal 24 are located at the repair shop 20. The diagnostic device 40 and the battery information management database 50 are located in the cloud 30 or on a data server 31. The manufacturing information management database 61 is located at the battery manufacturer 60.

[0038] 2. Structure of the battery information acquisition device 21

[0039] The battery information acquisition device 21 acquires battery information about the battery pack 2 and sends the battery information to the diagnostic device 40. The battery information includes pack identification information A, usage history information D, battery characteristics E, etc.

[0040] Pack identification information A is information that can identify battery pack 2. This pack identification information A is registered in the main BMU3 of battery pack 2 and stored in the battery information storage unit 55 of the battery information management database 50, and in the manufacturing information storage unit 63 of the manufacturing information management database 61. Furthermore, pack identification information A is registered during the manufacturing of the main BMU3. Pack identification information A can also be affixed to or printed on the packaging surface of battery pack 2 in the form of a symbol, QR code (registered trademark), RFID, etc.

[0041] Usage history information D represents the usage history of each of the multiple battery modules 2a, and is information obtained when measuring battery characteristic E. Examples of usage history information D include, for instance, the history of cumulative charge, cumulative discharge, temperature frequency distribution, SOC (State of Charge) frequency distribution, SOC fluctuation frequency, current frequency, current duration frequency, and multi-dimensional frequencies of various characteristic quantities (e.g., two-dimensional frequencies of SOC and temperature) generated based on sensing data such as usage period, vehicle 1 driving distance, vehicle 1 start-up frequency, current, voltage, and temperature. This usage history information D is registered in the main BMU3 of the battery pack 2 and stored in the battery information storage unit 55 of the battery information management database 50. Usage history information D is continuously generated by the BMU3 from the time the battery pack 2 is manufactured until the time of measurement of battery characteristic E.

[0042] Battery characteristic E refers to information representing the characteristics of each of the multiple battery modules 2a. Examples of battery characteristic E include, for instance, the resistance and range capacity of the battery module 2a. Battery characteristic E is stored in the battery information storage unit 55 of the battery information management database 50. Furthermore, when acquiring battery characteristic E, the battery is charged and discharged using a charging and discharging device, and battery characteristic E can be measured based on sensing data such as current, voltage, and temperature. Battery characteristic E includes at least one of a charging voltage characteristic based on the voltage shift when the battery module 2a is charged to a predetermined charging target voltage and the voltage shift after the battery module 2a has been charged to the aforementioned charging target value and charging has stopped, and at least one of a discharging voltage characteristic based on the voltage shift when the battery is discharged to a predetermined discharging target voltage and the voltage shift after the secondary battery has been discharged to the aforementioned discharging target voltage and discharging has stopped. Other examples of battery characteristic E include the ratio of the voltage change of the secondary battery to the capacity change of the secondary battery within the voltage range, the ratio of the voltage change of the secondary battery to the elapsed time within the voltage range, and the capacity ratio of the range capacity of the voltage range to the sum of the range capacities.

[0043] The battery information acquisition device 21 includes a battery information acquisition unit 22 and a battery characteristic acquisition unit 23 as its structural elements. The functions of these structural elements are executed by the processor 10A. The processor 10A, together with the processors 10B, 10C, 10D, and 10E described later, is included in the processor 10.

[0044] The battery information acquisition unit 22 acquires battery information about the battery pack 2 from the main BMU3 and sends the battery information to the diagnostic device 40. The battery characteristic acquisition unit 23 has the function of acquiring the battery characteristics of the battery pack 2 and sending the battery characteristics to the diagnostic device 40.

[0045] 3. Structure of Maintenance Operation Terminal 24

[0046] The maintenance terminal 24 is a terminal used for maintenance work on the battery module 2a included in the battery pack 2. The maintenance terminal 24 has a module ID reading unit 25, a diagnostic result request unit 26, a diagnostic result receiving unit 27, and a diagnostic result display unit 28 as its structural elements. The functions of these structural elements are executed by the processor 10B. The maintenance terminal 24 is typically composed of a desktop or laptop personal computer (PC), a tablet terminal, a mobile terminal, etc.

[0047] The module ID reading unit 25 reads the ID (e.g., identification number) of the battery module 2a and sends the ID to the diagnostic result request unit 26. Based on the ID sent from the module ID reading unit 25, the diagnostic result request unit 26 requests the diagnostic result of the battery module 2a corresponding to that ID from the battery information storage unit 55 of the battery information management database 50. The diagnostic result receiving unit 27 receives the diagnostic result of the battery module 2a from the battery information storage unit 55 of the battery information management database 50 and sends the diagnostic result to the diagnostic result display unit 28. The diagnostic result display unit 28 displays and outputs the diagnostic result sent from the diagnostic result receiving unit 27.

[0048] 4. Structure of the diagnostic device 40

[0049] The diagnostic device 40 has the function of diagnosing the battery pack 2. The diagnostic device 40 includes a module information acquisition unit 41, a usage history information acquisition unit 42, a battery characteristic acquisition unit 43, a diagnostic unit 44, and a correlation unit 45 as its structural elements. The functions of these structural elements are executed by the processor 10C.

[0050] The module information acquisition unit 41 acquires the pack identification information A of the battery pack 2 from the battery information acquisition unit 22 of the battery information acquisition device 21, and outputs an information request signal for requesting module information corresponding to the pack identification information A to the information request receiving unit 51 of the battery information management database 50. Based on the request signal, the module information acquisition unit 41 acquires the module information sent from the response information sending unit 54 of the battery information management database 50. The module information consists of module identification information B and module configuration information C for the multiple battery modules 2a included in the battery pack 2. The module information acquisition unit 41 can acquire the module identification information B and module configuration information C online at any time from the cloud 30 or data server 31 that centrally manages the pack identification information A of the battery pack 2.

[0051] Module identification information B is identification information that can identify each of the multiple battery modules 2a. Module configuration information C is information indicating the configuration of each of the multiple battery modules 2a in the battery pack 2. This module identification information B and module configuration information C are stored in the battery information storage unit 55 of the battery information management database 50 and in the manufacturing information storage unit 63 of the manufacturing information management database 61.

[0052] The historical information acquisition unit 42 acquires usage history information D from the battery information acquisition unit 22 of the battery information acquisition device 21. The battery characteristic acquisition unit 43 acquires battery characteristic E from the battery characteristic acquisition unit 23 of the battery information acquisition device 21. The diagnostic unit 44 diagnoses multiple battery modules 2a based on the usage history information D acquired from the battery information acquisition unit 22 and the battery characteristic E acquired from the battery characteristic acquisition unit 23. The association unit 45 associates the diagnostic results obtained by the diagnostic unit 44 with the module identification information B based on the module configuration information C. The diagnostic results obtained by the diagnostic unit 44 and the association results obtained by the association unit 45 are stored in the battery information storage unit 55 of the battery information management database 50.

[0053] 5. Structure of Battery Information Management Database 50

[0054] The battery information management database 50 is a database used to manage battery information related to the battery pack 2. The battery information management database 50 has an information request receiving unit 51, an information request sending unit 52, a response information receiving unit 53, a response information sending unit 54, and a battery information storage unit 55 as its structural elements. The functions of these structural elements are executed by the processor 10D.

[0055] The information request receiving unit 51 receives an information request signal from the module information acquisition unit 41 of the diagnostic device 40 and sends the information request signal to the information request sending unit 52. The information request sending unit 52 sends the information request signal sent from the information request receiving unit 51 to the information request receiving unit 62 of the manufacturing information management database 61. The response information receiving unit 53 receives response information (module identification information B and module configuration information C) from the response information sending unit 64 of the manufacturing information management database 61. The response information sending unit 54 sends the response information received by the response information receiving unit 53 to the module information acquisition unit 41 of the diagnostic device 40.

[0056] 6. Structure of Manufacturing Information Management Database 61

[0057] The manufacturing information management database 61 is a database used to manage the manufacturing information of the battery pack 2. The manufacturing information management database 61 has an information request receiving unit 62, a manufacturing information storage unit 63, and a response information sending unit 64 as its structural elements. The information request receiving unit 62 receives information request signals from the information request sending unit 52 of the battery information management database 50. The manufacturing information storage unit 63 pre-stores manufacturing information of multiple battery packs 2. The response information sending unit 64 reads the module identification information B and module configuration information C of the multiple battery modules 2a contained in the battery pack 2 corresponding to the information request signal received by the information request receiving unit 62 from the manufacturing information storage unit 63, and sends them to the response information receiving unit 53 of the battery information management database 50.

[0058] The functions of each structural element of the aforementioned diagnostic system 101 are realized by having the processor 10 execute the diagnostic program P for diagnosing the battery pack 2. Therefore, the diagnostic program P is a program used to enable the processor 10 to perform the functions of each structural element. The processor 10 consists of all or part of the aforementioned processors 10A, 10B, 10C, 10D, and 10E. The diagnostic program P is stored in a non-volatile storage medium 11. The non-volatile storage medium 11 is shown separately in the accompanying drawings to avoid excessive detail. However, the non-volatile storage medium 11 is included in the vehicle 1, the battery information acquisition device 21, the maintenance terminal 24, the diagnostic device 40, the battery information management database 50, and the manufacturing information management database 61. At least a portion of the diagnostic program P is stored in the non-volatile storage medium 11 included in each of these structural elements. Various media such as memory type, disk type, and magnetic tape type can be used as the non-volatile storage medium 11. Alternatively, the diagnostic program P can also be stored in the cloud 30 or the data server 31. Alternatively, at least a portion of the diagnostic procedure P can be downloaded from the cloud 30 or data server 31 to the vehicle 1, battery information acquisition device 21, maintenance operation terminal 24, diagnostic device 40, battery information management database 50, and manufacturing information management database 61.

[0059] Furthermore, the allocation of the various structural elements (functional elements) of the aforementioned diagnostic system 101 to the repair shop 20, the cloud 30 or data server 31, and the battery manufacturer 60 is not limited to... Figure 1 The division can be appropriately changed as needed. In addition, other machines or equipment can be used as the destination for the allocation of each structural element (functional element).

[0060] 7. Diagnostic processing performed by diagnostic system 101

[0061] Reference Figures 1-3 The diagnostic processing performed by the diagnostic system 101 is described. This diagnostic processing follows... Figure 2 Steps S101 to S108 in the flowchart shown are executed sequentially. Additionally, one or more steps may be added as needed, or multiple steps may be appropriately integrated.

[0062] In step S101, the battery pack 2 is confirmed to be in stock at the repair shop 20. Step S102 is to obtain the module identification information B and module configuration information C of the multiple battery modules 2a contained in the battery pack 2 that was in stock in step S101. In step S102, the battery pack identification information A of the battery pack 2 is sent from the battery information acquisition unit 22 of the battery information acquisition device 21 to the information request receiving unit 62 of the manufacturing information management database 61 via the module information acquisition unit 41 of the diagnostic device 40 and the information request receiving unit 51 of the battery information management database 50. As a result, the module identification information B and module configuration information C, which are stored in the manufacturing information storage unit 63 in advance corresponding to the pack identification information A, are sent from the response information sending unit 64 to the module information acquisition unit 41 of the diagnostic device 40 via the response information receiving unit 53 and the response information sending unit 54 of the battery information management database 50.

[0063] Step S103 is the step of acquiring the usage history information D of the battery pack 2. In this step S103, the usage history information acquisition unit 42 of the diagnostic device 40 acquires the usage history information D from the battery information acquisition unit 22 of the battery information acquisition device 21. Step S104 is the step of evaluating the overall module characteristic E1 under the pack state of the battery pack 2 (keeping the multiple battery modules 2a connected unchanged). The overall module characteristic E1 is information that comprehensively represents the battery characteristics E of the multiple battery modules 2a. In step S104, the battery characteristic acquisition unit 23 of the battery information acquisition device 21 can acquire the sampling results (overall module characteristic E1) of the battery characteristics E of each of the multiple battery modules 2a under the pack state of the battery pack 2 from the main BMU3 of the battery pack 2. When acquiring the overall module characteristic E1, a charging and discharging device is connected to the battery pack 2. By charging and discharging the battery through the charging and discharging device, the overall module characteristic E1 can be measured based on sensing data such as current, voltage, and temperature. As another variation, the main BMU3 can also acquire sensing data. Furthermore, the battery characteristic E can also be calculated by the battery information acquisition device 21 or the diagnostic device 40 based on the sensing data.

[0064] Step S105 is the step by which the diagnostic unit 44 diagnoses the plurality of battery modules 2a included in the battery pack 2. In this step S105, as... Figure 3As shown, a pre-built battery diagnostic model M is used. This battery diagnostic model M is constructed using theoretical models or machine learning models, etc. In this battery diagnostic model M, the usage history information D obtained in step S103 and the battery characteristics E obtained in step S104 are used as input information, and the diagnostic results R of battery module 2a (e.g., capacity, capacity degradation, SOH (State of Health) as a degradation degree, and SOH change per unit period) are used as output information. In the battery diagnostic model M, for example, the battery degradation model formula Ma expressed by the following equation (1) is used.

[0065] Y = a1×X1 + a2×X2 + ... + a n ×X n + intercept…(1)

[0066] The battery degradation model formula Ma is derived through linear regression analysis using battery characteristic E (as characteristic data of battery module 2a) as the target variable X, and the usage history information D of battery module 2a and the power of D as the explanatory variables Y. This battery degradation model formula Ma is a modeled expression where the coefficients of each term in the explanatory variable Y are predefined as positive or negative. The formula Ma includes a term using the usage history information D and a term using the power of D (a non-linear term). Linear regression analysis can use appropriate algorithms such as Lasso regression, Ridge regression, or ElasticNet.

[0067] Furthermore, the battery degradation model formula Ma can be stored in the cloud 30 or data server 31, or it can be stored in the battery information acquisition device 21 or maintenance operation terminal 24 of the repair shop 20. In addition, the battery degradation model formula Ma can also be updated appropriately.

[0068] The diagnostic model used in step S105 is not limited to the battery diagnostic model M. Instead of the battery diagnostic model M, a battery diagnostic model that uses either historical information D or battery characteristics E as input information can be used. Alternatively, a measured determination based on actual values ​​can be used instead of a presumed determination based on the battery diagnostic model M. Furthermore, a step to determine whether battery module 2a can be diagnosed can be set before step S105, if necessary.

[0069] Step S106 is the step of associating the diagnostic result R obtained in step S105 with the module identification information B based on the module configuration information C. According to step S106, while maintaining the pack state of the battery pack 2, the module identification information B of each of the multiple battery modules 2a can be automatically associated with the diagnostic result R. Therefore, the battery characteristics of the multiple battery modules 2a can be determined with good accuracy. In step S107, the operator actually disassembles the battery pack 2.

[0070] 8. Effects

[0071] According to Embodiment 1, since the diagnostic result R is automatically associated with each of the multiple battery modules 2a in step S106, the operator does not need to record the wiring sequence, identification information, and configuration information of each battery module 2a while disassembling the battery pack 2 in step S107. Therefore, by shortening the operation time, operation hours can be reduced. In addition, even if the multiple battery modules 2a are scattered, their diagnostic results R can be obtained by reading the module identification information B of any battery module 2a, eliminating human error by the operator. Then, in step S108, after disassembling the battery pack 2, the multiple battery modules 2a are classified according to their diagnostic results R.

[0072] Therefore, the battery characteristics of the multiple battery modules 2a contained in the battery pack 2 can be accurately determined while suppressing the working time.

[0073] Hereinafter, other embodiments related to the first embodiment described above will be described with reference to the accompanying drawings. In these other embodiments, elements identical to those in the first embodiment described above will be labeled with the same reference numerals, and descriptions of these identical elements will be omitted.

[0074] (Second Implementation)

[0075] Figure 4 The diagram illustrates a diagnostic system 102 according to a second embodiment. The structure of this diagnostic system 102 regarding the battery information management database 50 and the manufacturing information management database 61 differs from that of the diagnostic system 101 in the first embodiment. Other structures and diagnostic processes are the same as in the first embodiment.

[0076] In the diagnostic system 102, the battery information management database 50 includes an information request receiving unit 51, a response information sending unit 54, a battery information storage unit 55, and a manufacturing information storage unit 56. Additionally, in the diagnostic system 102, the manufacturing information management database 61 includes a manufacturing information storage unit 63 and a response information sending unit 64.

[0077] The manufacturing information storage unit 56 acquires and stores response information from the response information sending unit 64. The response information sending unit 54 reads the response information (module identification information B and module configuration information C) from the manufacturing information storage unit 56 based on the information request signal sent from the information request receiving unit 51, and sends it to the module information acquisition unit 41 of the diagnostic device 40.

[0078] According to the second embodiment, similar to the first embodiment, the battery characteristics of the multiple battery modules 2a included in the battery pack 2 can be accurately determined while suppressing working hours.

[0079] Furthermore, it achieves the same effects as the first embodiment.

[0080] (Third implementation method)

[0081] Figure 5 The diagram shows a diagnostic system 103 according to a third embodiment. The structure of this diagnostic system 103 regarding the battery information management database 50 and the manufacturing information management database 61 differs from that of the diagnostic system 101 in the first embodiment. Other structures and diagnostic processes are the same as in the first embodiment.

[0082] In the diagnostic system 103, the battery information acquisition unit 22 of the battery information acquisition device 21 is characterized in that it acquires from the main BMU3 the pack identification information A, module identification information B, and module configuration information C, which are written to the main BMU3 of the battery pack 2 through the manufacturing information management database 61. Correspondingly, the battery information management database 50 only has a battery information storage unit 55.

[0083] The manufacturing information management database 61 includes a manufacturing information storage unit 63, an information registration unit 65, and an information writing unit 66. The information registration unit 65 stores the manufacturing information of the battery pack 2 read from the manufacturing information storage unit 63 (pack identification information A of the battery pack 2, module identification information B of the multiple battery modules 2a contained in the battery pack 2, and module configuration information C). The information writing unit 66 writes the manufacturing information registered in the information registration unit 65 to the main BMU3 of the battery pack 2.

[0084] According to the third embodiment, since the manufacturing information of the battery pack 2 is obtained from the main BMU3 attached to the battery pack 2, accurate manufacturing information can be obtained. Furthermore, the manufacturing information of the battery pack 2 can be obtained even when offline and not connected to the cloud 30 or data server 31. Additionally, by adopting a structure that allows the main BMU3 to store the manufacturing information of the battery pack 2, the load on the battery information management database 50 can be reduced.

[0085] Furthermore, it achieves the same effects as the first embodiment.

[0086] (Fourth Implementation)

[0087] Figure 6 The diagram shows a diagnostic system 104 according to the fourth embodiment. The structure of this diagnostic system 104 regarding the battery information management database 50 differs from that of the diagnostic system 103 according to the third embodiment. Other structures and diagnostic processes are the same as in the third embodiment.

[0088] In the diagnostic system 104, the characteristic is that the main BMU3 of the battery pack 2 is equipped with a Figure 5 The diagnostic device 40 in the cloud is functional. Correspondingly, only the battery information management database 50 is provided in the cloud 30 or data server 31.

[0089] The main BMU3 has a battery information storage unit 3a. In the battery information storage unit 3a, the manufacturing information of the battery pack 2 (pack identification information A of the battery pack 2, module identification information B of the multiple battery modules 2a contained in the battery pack 2, and module configuration information C) is written by the information writing unit 66 of the manufacturing information management database 61.

[0090] According to the fourth embodiment, by employing a configuration that includes two functions—the function of assigning manufacturing information to the main BMU3 and the function of diagnosing the battery pack 2—the load on the battery information management database 50 can be reduced.

[0091] Furthermore, it achieves the same effect as the third embodiment.

[0092] (Fifth implementation method)

[0093] Figure 7 The diagram shows a diagnostic system 105 according to a fifth embodiment. This diagnostic system 105 differs from the diagnostic system 101 of the first embodiment in the structure of the diagnostic device 40. Other structural features are the same as in the first embodiment.

[0094] In the diagnostic system 105, the diagnostic device 40 also includes a design information acquisition unit 46 and a usage history information production unit 47. Additionally, the diagnostic device 40 includes a simplified diagnostic unit 44a and a high-precision diagnostic unit 44b, both equivalent to the diagnostic unit 44.

[0095] The design information acquisition unit 46 acquires design information F of the usage environment of the multiple battery modules 2a included in the battery pack 2 from the battery information storage unit 55 of the battery information management database 50. The usage history information creation unit 47 creates usage history information D for each of the multiple battery modules 2a based on the design information F acquired by the design information acquisition unit 46. The usage history information creation unit 47 is an information acquisition unit that acquires the usage history information D. At this time, the design information F is individual information corresponding to each of the multiple battery modules 2a. Therefore, individual usage history information D is created.

[0096] The simplified diagnostic unit 44a uses usage history information D generated by the usage history information generation unit 47 to diagnose each of the multiple battery modules 2a. In contrast, the high-precision diagnostic unit 44b diagnoses the multiple battery modules 2a based on the usage history information D generated by the usage history information generation unit 47 and the battery characteristics E obtained from the battery characteristic acquisition unit 23. Because the high-precision diagnostic unit 44b uses battery characteristics E in addition to usage history information D, it can perform more accurate diagnoses compared to the simplified diagnostic unit 44a. The diagnostic results of both the simplified diagnostic unit 44a and the high-precision diagnostic unit 44b are displayed and output to the diagnostic result display unit 28 of the maintenance terminal 24.

[0097] Next, refer to Figures 7-9 The diagnostic processing performed by the diagnostic system 105 is described. This diagnostic processing follows... Figure 8 Steps S201 to S212 in the flowchart shown are executed sequentially. Additionally, one or more steps may be added as needed, or multiple steps may be appropriately integrated.

[0098] Steps S201 to S203 are the same as steps S101 to S103 in the first embodiment. Step S204 is the step of obtaining design information F of the usage environment of the plurality of battery modules 2a included in the battery pack 2. In step S204, the design information F pre-accumulated in the battery information storage unit 55 of the battery information management database 50 is sent to the design information acquisition unit 46. For example, the design temperature can be cited as the design information F.

[0099] Step S205 is a step in which the simplified diagnostic unit 44a performs a simplified diagnostic on the multiple battery modules 2a included in the battery pack 2. In this S205, a simplified diagnostic is performed using only the usage history information D, which is created based on the design information F obtained in step S204. Thus, each of the multiple battery modules 2a can be diagnosed based on the individual usage history information D.

[0100] Here, a specific example of the diagnostic process in step S205 will be explained.

[0101] like Figure 9 As shown, as an example, let N be the number of battery modules 2a contained in battery pack 2, and let F be the design temperature T of battery module 2a. In this case, the design temperature of the first battery module 2a_1 is T_1, the design temperature of the second battery module 2a_2 is T_2, and the design temperature of the Nth battery module 2a_N is T_N, with each design temperature varying depending on the configuration. On the other hand, the representative temperature Tr of battery pack 2 is sensed by a temperature sensor (not shown), but the representative temperature Tr is common to all N battery modules 2a. As a result, if usage history information is generated based on the design temperature and the representative temperature Tr, the usage history information D_1 of battery module 2a_1, the usage history information D_2 of battery module 2a_2, and the usage history information D_N of battery module 2a_N all become different. Furthermore, in this diagnostic process, each battery module 2a is determined to be either qualified or unqualified based on its usage history information D_1, D_2, and D_N respectively. Therefore, according to step S205, a highly accurate diagnosis based on the configuration differences of battery module 2a can be performed.

[0102] Step S206 is the step of determining whether battery pack 2 is a discarded item. If battery pack 2 is not a discarded item (step S206 is "Yes"), proceed to step S207; otherwise (step S206 is "No"), proceed to the discarding of battery pack 2. The determination in step S206 can be based on the proportion of battery modules 2a that were determined to be unqualified in the simplified diagnosis in step S205. If, for example, the proportion of battery modules 2a that were determined to be unqualified is 90% or more, battery pack 2 itself can be determined to be a discarded item. By removing the discarded battery pack 2 according to step S206, the subsequent processes can be simplified.

[0103] Step S207 is the same as step S104 in the first embodiment. Step S208 is a step to determine whether battery module 2a is a discarded item. This determination is based on the diagnostic result of step S205. For example, battery module 2a with a SOH (state of decay) below a threshold can be determined as a discarded item. For battery module 2a that is not a discarded item, proceed to step S209; for battery module 2a that is a discarded item, proceed to the discard step without proceeding to the diagnosis in step S209.

[0104] Step S209 is a step in which the high-precision diagnostic unit 44b performs a re-diagnosis on the battery module 2a that was excluded from the discard list in step S208, i.e., the battery module 2a whose diagnostic result in step S205 was determined to be qualified. In this step S209, the battery diagnostic model M (refer to...) is used in the same way as in step S105 of Embodiment 1. Figure 3 In the battery diagnostic model M, the usage history information D obtained in step S203 and the summary module characteristics E1 obtained in step S207 are used as input information, and the result R of the re-diagnosis of battery module 2a is used as output information.

[0105] Step S210 is the step of associating the result R of the re-diagnosis obtained in step S209 with the module identification information B based on the module configuration information C. Steps S211 and S212 are the same as steps S107 and S108 in the first embodiment.

[0106] According to the fifth embodiment, by using design information F, accurate diagnosis of battery module 2a can be performed. Furthermore, since only the necessary battery modules 2a among the multiple battery modules 2a included in the battery pack 2 can be diagnosed, the computational load involved in the diagnosis can be reduced.

[0107] Furthermore, it achieves the same effects as the first embodiment.

[0108] (Sixth Implementation Method)

[0109] Figure 10 The diagram shows a diagnostic system 106 according to a sixth embodiment. This diagnostic system 106 differs from the diagnostic system 105 of the fifth embodiment in its diagnostic processing within the diagnostic device 40. Otherwise, it is the same as the fifth embodiment.

[0110] The diagnostic processing performed by the diagnostic system 106 is in accordance with Figure 11 Steps S301 to S312 in the flowchart shown are executed sequentially. Additionally, one or more steps may be added as needed, or multiple steps may be appropriately integrated.

[0111] Steps S301 to S306 are the same as steps S201 to S206 in the fifth embodiment. Step S307 is the step of associating the simplified diagnostic result R obtained in step S305 with the module identification information B based on the module configuration information C. Step S308 is the same as step S211 in the fifth embodiment. Step S309 is the same as step S208 in the fifth embodiment.

[0112] Step S310 is a step of evaluating the individual module characteristics E2 in the disassembled state of the battery pack 2. Individual module characteristics E2 are information that individually represents the battery characteristics E of the multiple battery modules 2a. In step S310, the battery information acquisition device 21 can acquire the sampling results (individual module characteristics E2) of the battery characteristics E of each of the multiple battery modules 2a. When acquiring individual module characteristics E2, a charging / discharging device is connected to the battery pack 2. By charging and discharging the battery through this device, the individual module characteristics E2 can be measured based on sensing data such as current, voltage, and temperature. As another variation, the battery information acquisition device 21 can also acquire sensing data. Furthermore, the battery characteristics E can be calculated by the battery information acquisition device 21 or the diagnostic device 40 based on this sensing data.

[0113] Step S311 is a step in which the high-precision diagnostic unit 44b performs a re-diagnosis on the battery module 2a that was excluded from the discard list in step S309, i.e., the battery module 2a whose diagnostic result in step S305 was determined to be qualified. In this step S311, the battery diagnostic model M (refer to...) is used in the same way as in step S105 of Embodiment 1. Figure 3 However, in the battery diagnostic model M, the usage history information D obtained in step S303 and the individual module characteristic E2 obtained in step S310 are used as input information, and the result R of the re-diagnosis of battery module 2a is used as output information. Step S312 is the same as step S212 in the fifth embodiment.

[0114] According to the sixth embodiment, similar to the fifth embodiment, accurate diagnosis of the battery module 2a can be performed by using design information F. Furthermore, since only the necessary battery modules 2a among the multiple battery modules 2a included in the battery pack 2 can be diagnosed, the computational load involved in the diagnosis can be reduced. Moreover, only the individual module characteristics E2 of the necessary battery modules 2a among the multiple battery modules 2a included in the battery pack 2 can be evaluated. Therefore, the computational load involved in evaluating the individual module characteristics E2 can be reduced.

[0115] Furthermore, it has the same effect as the fifth embodiment.

[0116] This disclosure has been described based on the above-described embodiments, but it should be understood that this disclosure is not limited to these embodiments or constructions. This disclosure also includes various modifications or variations within the same range. Furthermore, various combinations or methods, even those containing only one element, or other combinations or methods above or below, also fall within the scope or spirit of this disclosure. For example, the following methods applying the above-described methods may also be implemented.

[0117] In the above-described manner, a case where the battery pack 2 mounted on the vehicle 1 is diagnosed is exemplified, but the diagnosis technique can be applied to diagnose the battery pack 2 mounted on a civil device or an industrial device other than the vehicle 1.

Claims

1. A diagnostic procedure (P) for diagnosing a battery pack (2) comprising multiple battery modules (2a), wherein, Enable processor (10): Obtain module identification information (B), module configuration information (C), and usage history information (D) of the multiple battery modules contained in the battery pack; Diagnose multiple battery modules based on the aforementioned usage history information; and Based on the module configuration information, the diagnostic results obtained through this diagnosis are associated with the module identification information.

2. The diagnostic procedure according to claim 1, wherein, Enable processor (10): The module identification information and the module configuration information are obtained from the cloud (30) or data server (31) that manages the pack identification information (A) of the battery pack.

3. The diagnostic procedure according to claim 1, wherein, Enable processor (10): The module identification information and module configuration information are obtained from the main battery management unit (3) that manages the battery pack.

4. The diagnostic procedure according to any one of claims 1 to 3, wherein, Enable processor (10): The usage history information and summary module characteristics (E1) are used to diagnose multiple battery modules, the summary module characteristics representing the battery characteristics (E) of multiple battery modules in a summary manner in the pack state of the battery pack.

5. The diagnostic procedure according to claim 4, wherein, Enable processor (10): The usage history information is obtained based on the design information (F) of the usage environment of the multiple battery modules; The historical usage information is used to diagnose multiple battery modules; The battery module was re-diagnosed using the usage history information and the overall module characteristics; and The results of the re-diagnosis are associated with the module identification information.

6. The diagnostic procedure according to claim 5, wherein, Enable processor (10): The battery module was deemed qualified after a second diagnostic using the diagnostic results from the usage history information.

7. The diagnostic procedure according to any one of claims 1 to 3, wherein, Enable processor (10): The usage history information is obtained based on the design information (F) of the usage environment of the multiple battery modules; The usage history information is used to diagnose multiple battery modules; The diagnostic results obtained through this diagnosis are associated with the module identification information; Obtain individual module characteristics (E2), which individually represent the battery characteristics (E) of multiple battery modules in the pack disassembly state where the battery pack is disassembled; and The battery module was re-diagnosed using the usage history information and the individual module characteristics.

8. The diagnostic procedure according to claim 7, wherein, Enable processor (10): The battery module was deemed qualified after a second diagnostic using the diagnostic results from the usage history information.

9. A diagnostic device (40) for diagnosing a battery pack (2) comprising multiple battery modules (2a), wherein, have: The information acquisition unit (41, 42, 47) acquires module identification information (B), module configuration information (C), and usage history information (D) of the multiple battery modules contained in the battery pack. Diagnostic units (44, 44a, 44b) diagnose multiple battery modules based on the historical usage information; and The association unit (45) associates the diagnostic results obtained by the diagnostic unit with the module identification information based on the module configuration information.

10. The diagnostic device according to claim 9, wherein, The information acquisition unit obtains the module identification information and the module configuration information from the cloud (30) or data server (31) that manages the pack identification information (A) of the battery pack.

11. The diagnostic device according to claim 9, wherein, The information acquisition unit obtains the module identification information and the module configuration information from the main battery management unit (3) that manages the battery pack.

12. The diagnostic device according to any one of claims 9 to 11, wherein, The diagnostic unit uses the usage history information and the summary module characteristics (E1) to diagnose multiple battery modules, the summary module characteristics representing the battery characteristics (E) of multiple battery modules in a summary manner in the pack state of the battery pack.

13. The diagnostic device according to claim 12, wherein, The information acquisition unit acquires the usage history information based on the design information (F) of the usage environment of the multiple battery modules. The diagnostic unit uses the usage history information to diagnose multiple battery modules, and uses the usage history information and the overall module characteristics to diagnose the battery modules again. The association unit associates the results of the re-diagnosis obtained by the diagnosis unit with the module identification information.

14. The diagnostic device according to claim 13, wherein, The diagnostic department re-diagnoses the battery module that was deemed qualified based on the diagnostic results obtained from the usage history information.

15. The diagnostic device according to any one of claims 9 to 11, wherein, The information acquisition unit acquires the usage history information based on the design information (F) of the usage environment of the multiple battery modules. The diagnostic unit uses the usage history information to diagnose multiple battery modules. The association unit associates the diagnostic results obtained by the diagnostic unit with the module identification information. The information acquisition unit acquires individual module characteristics (E2), which individually represent the battery characteristics (E) of multiple battery modules in the battery pack decomposition state. The diagnostic unit uses the usage history information and the individual module characteristics to re-diagnose the battery module.

16. The diagnostic device according to claim 15, wherein, The diagnostic department re-diagnoses the battery module that was deemed qualified based on the diagnostic results obtained from the usage history information.

17. A diagnostic system (101, 102, 103, 104, 105, 106), wherein, have: The diagnostic device according to any one of claims 9 to 11; Battery information acquisition device (21) acquires battery information about the battery pack and sends it to the diagnostic device; as well as Battery information management database (50) manages the battery information.

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