Battery detection management method and system

Abstract

A battery detection management method includes: detecting a target battery at a first time point to generate health degree detection data; uploading the health degree detection data to a cloud database; the classification state of the target battery is judged according to the health degree detection data and a preset health degree range, a label is generated to be attached to the target battery, and the label presents the classification state and is used for being linked to the health degree detection data of the target battery in a cloud database; and detecting the target battery at a second time point later than the first time point to update the health degree detection data of the target battery in the cloud database. A battery detection management system comprises a detection device, an arithmetic device and a labeling machine, and the arithmetic device is connected with the detection device and the labeling machine.

Description

Technical Field

[0001] The present invention relates to a battery management method and system, and particularly to a battery detection management method and system. Background Art

[0002] Battery recycling currently mainly focuses on the extraction and reuse of valuable metals (such as cobalt, nickel, lithium, copper, etc.) in batteries. Traditional methods include pyrometallurgy and hydrometallurgy. The former separates metals by high-temperature heating, and the latter uses acid leaching to dissolve the metals in the battery for extraction and regeneration. These technologies can effectively recycle metal resources, but have problems such as high energy consumption and pollution emissions. In recent years, with the improvement of environmental protection requirements, technological progress has begun to focus on new recycling methods with low energy consumption and low pollution, or classifying battery recycling before reuse to improve efficiency and reduce environmental impact.

[0003] However, there are some problems with battery detection management methods in the prior art. Since traditional detection methods require a large amount of time and resources, the data analysis function of the battery management system has limited efficiency in processing a large amount of data, and cannot quickly provide classification or perform accurate health status assessment, which is a challenge for application scenarios that require high precision and high reliability. Summary of the Invention

[0004] In view of the above, the present invention provides a battery detection management method and system.

[0005] According to an embodiment of the present invention, a battery detection management system includes a detection device, an arithmetic device, and a label printer, wherein the arithmetic device is connected to the detection device and the label printer. The detection device is used to detect a target battery to generate health degree detection data; the arithmetic device is used to upload the health degree detection data to a cloud database and determine the classification status of the target battery according to the health degree detection data and a preset health degree range; the label printer is used to generate a label for pasting on the target battery, wherein the label presents the classification status and is used to link to the health degree detection data of the target battery in the cloud database.

[0006] According to an embodiment of the present invention, a battery detection management method includes: detecting a target battery at a first time point to generate health degree detection data; uploading the health degree detection data to a cloud database; determining the classification status of the target battery according to the health degree detection data and a preset health degree range, and generating a label for pasting on the target battery, wherein the label presents the classification status and is used to link to the health degree detection data of the target battery in the cloud database; and detecting the target battery at a second time point later than the first time point to update the health degree detection data of the target battery in the cloud database.

[0007] With the above structure, the battery detection and management method and system disclosed by the present invention can screen and classify and label the recycled batteries, and perform reuse after classified recycling, so as to improve efficiency and reduce the impact on the environment.

[0008] The above description of the content of the present invention and the following description of the embodiments are used to demonstrate and explain the spirit and principle of the present invention, and provide a further explanation for the protection scope of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 It is a block diagram of a battery detection and management system according to an embodiment of the present invention.

[0010] Figure 2 It is a block diagram of a battery detection and management system according to another embodiment of the present invention.

[0011] Figure 3 It is a flowchart of a battery detection and management method according to an embodiment of the present invention.

[0012] Figure 4 It is a flowchart of determining the classification status of a battery according to an embodiment of the present invention.

[0013] Figure 5 It is a flowchart of determining the classification status of a battery according to another embodiment of the present invention.

[0014] Figure 6 It is a flowchart of detecting a battery according to an embodiment of the present invention.

[0015] Figure 7 It is a flowchart of detecting a battery according to another embodiment of the present invention.

[0016] Figure 8 It is a flowchart of a battery detection and management method according to another embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] The following details the features and advantages of the present invention in the embodiments. The content is sufficient for those skilled in the art to understand the technical content of the present invention and implement it accordingly. According to the content, protection scope and drawings disclosed in this specification, those skilled in the art can easily understand the related purposes and advantages of the present invention. The following embodiments further illustrate the viewpoints of the present invention, but do not limit the scope of the present invention in any way.

[0018] Please refer to Figure 1 , Figure 1 which is a block diagram of a battery detection and management system according to an embodiment of the present invention. As Figure 1As shown, the battery detection and management system 1 includes a detection device 11, an arithmetic device 12, a label printer 13, and a cloud database 14. The arithmetic device 12 is connected to the detection device 11, the label printer 13, and the cloud database 14 by wired or wireless means, where the cloud database 14 can be regarded as an internal database of the battery detection and management system 1, or can be an external database of the battery detection and management system 1.

[0019] The detection device 11 is used to detect the target battery to generate health detection data. For example, the detection device 11 may include an internal resistance tester, a capacity tester, a charge and discharge cycle life tester, a voltage detector, a temperature monitoring system, a battery management system (BMS) test device, a BMS data collector, or a combination of one or more of the above devices. For example, the target battery may be a lithium-ion battery, a nickel-metal hydride battery, a lead-acid battery, a lithium polymer battery, etc. For example, the health detection data may include the state of health (SOH) of the battery, the current voltage, the charging impedance, the voltage drop rate, the voltage rise rate, the discharge impedance, the remaining available capacity, and / or the classification level, etc.

[0020] In one embodiment, the detection device 11 can be used to establish a simulation test program according to the characteristic specifications of the target battery, and execute the simulation test program to generate the health detection data of the battery. For example, the characteristic specifications of the battery can be the battery characteristic specification provided by the client or the battery specification data to be tested. The simulation test program can be determined by the battery management system protocol (BMS protocol) and 30 standard samples (Golden samples 30ea). The health detection data of the battery can be a battery detection evaluation report, the SOH status of the battery detection, and / or the battery detection classification.

[0021] The arithmetic device 12 is used to upload the health detection data to the cloud database and determine the classification status of the target battery according to the health detection data and the preset health range. In one embodiment, the arithmetic device 12 can be a server, a personal computer, a laptop computer, a smart phone, an industrial computer, a tablet computer, or a quantum computer, etc., which can upload the detection data to the cloud database 14 and can determine whether the classification status of the battery conforms to the preset health range according to the detection data. In addition, the arithmetic device 12 can include one or more processors, such as a central processing unit, a graphics processing unit, a microcontroller, a programmable logic controller, or other processors with signal processing functions. In another embodiment, the arithmetic device 12 can be an embedded system or a sensor, etc., which can upload the detection data to the cloud database, and one or a combination of arithmetic devices such as a BMS test diagnosis device, an edge computing device, a battery health monitoring system, and a cloud analysis platform, which can determine whether the classification status of the battery conforms to the preset health range according to the detection data.

[0022] In one embodiment, the preset health range indicates that the health of the battery is greater than 20%. When the health detection data conforms to the preset health range, the classification status indicates reuse, and when the health detection data does not conform to the preset health range, the classification status indicates scrap processing. For example, the battery may be recycled when it reaches less than 80%. Therefore, when the classification status indicates reuse, the health of the battery can be between 20% and 80%, and it can be downgraded and reused in energy storage cabinets, roadside equipment, and uninterruptible power systems (UPS).

[0023] In one embodiment, when the difference between the health detection data of the target battery and multiple pre-used batteries of the uninterruptible power system is less than a preset value, the arithmetic device 12 marks the target battery as suitable for the uninterruptible power system. For example, the health of multiple pre-used batteries of the uninterruptible power system is 60%, and when the detection device 11 detects that the health detection data of the target battery indicates a health of 60%, the arithmetic device 12 determines that the difference between the health detection data of the target battery and multiple pre-used batteries of the uninterruptible power system is less than the preset value, and marks the target battery as suitable for the uninterruptible power system. The preset value can be set according to the actual situation, and the present invention is not limited thereto.

[0024] The label printer 13 is used to generate labels for pasting on target batteries, where the labels are in a classified state and are used to link to the health detection data of the target batteries in the cloud database 14. The generation can be printing, and the labels can be two-dimensional barcodes, three-dimensional barcodes, Quick Response (QR) barcodes, antennas, Radiofrequency Identification (RFID) tags, and / or encrypted electronic protection cards, etc., and can have different colors or patterns to represent different classified states of the batteries. For example, the labels generated by the label printer 13 with two-dimensional codes and / or antennas can be scanned to link to the health detection data of the batteries in the cloud database. When the classified state of the battery is for reuse, the generated labels can be green or contain patterns indicating reuse. When the classified state of the battery is for scrap disposal, the generated labels can be red or contain patterns indicating scrap disposal.

[0025] The cloud database 14 is used to receive the health detection data uploaded by the computing device 12, and the health detection data can be connected through the labels generated by the label printer 13. For example, the cloud database 14 can include a relational database, a document database, and / or an automated database. The form of linking the health detection data of the batteries in the cloud database 14 through the labels can be a table, a graphic file, or a text file. Specifically, the cloud database 14 can be a database of Global Standards One (GS1).

[0026] Please refer to Figure 2 , Figure 2 , which is a block diagram of a battery detection and management system according to another embodiment of the present invention. As Figure 2 shown, the battery detection and management system 1' includes a detection device 11, a computing device 12, a label printer 13, a cloud database 14, a switching hub 15, a communication adapter 16, a reliability test device 17, a temperature collector 18, and a voltage collector 19. Among them, the implementation devices, functions, and connection relationships of the detection device 11, the computing device 12, the label printer 13, and the cloud database 14 are the same as Figure 1The battery detection and management system 1 will not be elaborated here. In this embodiment, the detection device 11 of the battery detection and management system 1' may include a test device 111 and a BMS data collector 112. Among them, the test device 111 is connected to the computing device 12 via a switching hub 15 and a communication adapter box 16, and the BMS data collector 112 is connected to the computing device 12. In addition, the computing device 12 is further connected to the switching hub 15, the communication adapter box 16, a reliability test device 17, a temperature collector 18, and a voltage collector 19. In one embodiment, the BMS data collector 112, the reliability test device 17, the temperature collector 18, and the voltage collector 19 may be connected to the computing device 12 by wired or wireless means. In another embodiment, other communication adapter boxes 16 may be further provided between the BMS data collector 112, the reliability test device 17, the temperature collector 18, the voltage collector 19 and the computing device 12, and are connected to the computing device 12 through the other communication adapter boxes 16. The battery 2 is connected to the battery detection and management system 1' of the present invention through the test device 111 for testing. The battery 2 may be a storage battery for a storage cabinet or a power battery for a locomotive, an automobile, or a bus. The communication adapter box 16 may be implemented in a connection manner of RS-485 or Ethernet. The number of the communication adapter boxes 16 and the batteries 2 is Figure 2 schematically shown as two in the figure. However, the present disclosure is not limited to the figure shown and may be one or more than two. For example, there may be 8 communication adapter boxes 16, each connected to a test device 111. For example, the number of batteries that can be simultaneously tested by one test device 111 is 64.

[0027] The test device 111 is used to detect the battery and generate battery health data. For example, the test device 111 may be a rapid test equipment and / or a battery quick screening detection system, and may include a golden sampling modeling, a battery aging model, and a state of charge (SOC) distribution model, and rapidly detect the battery health status through intelligent calculation. The BMS data collector 112 is used to collect the battery health data. For example, the BMS data collector 112 may be an intelligent battery management module, a battery monitoring system, a multi-channel data collector, a mobile detection device, etc.

[0028] In this embodiment, the switching hub 15 can be used to connect the computing device 12 to a plurality of communication adapters 16. The communication adapters 16 can be used to connect each device to the computing device 12. The reliability test equipment 17 can be an environmental test chamber, an electrical durability test equipment, a thermal cycle test equipment, etc. The temperature collector 18 can be a thermocouple, a thermistor, an infrared temperature sensor, etc. The voltage collector 19 can be a multimeter, a voltage divider, a wireless voltage sensor, etc. Among them, the switching hub 15, the communication adapters 16, the reliability test equipment 17, the temperature collector 18, and / or the voltage collector 19 are selectively provided components.

[0029] Please refer to Figure 3 , Figure 3 FIG. is a flowchart of a battery detection and management method according to an embodiment of the present invention. As Figure 3 shown, the battery detection and management method includes steps S11: detecting a target battery at a first time point to generate health detection data; step S13: uploading the health detection data to a cloud database; step S15: determining a classification status of the target battery according to the health detection data and a preset health range, and generating a label for pasting on the target battery; and step S17: detecting the target battery at a second time point later than the first time point to update the health detection data of the target battery in the cloud database, wherein the execution order of step S13 and step S15 does not have a certain sequential relationship, that is, step S15 can be executed first and then step S13 can be continued, or they can be executed simultaneously, and the present disclosure does not limit this. The battery detection and management method can be applied to Figure 1 the battery detection and management system 1 shown in Figure 2 and the battery detection and management system 1' shown in Figure 1 The battery detection and management system 1 shown in Figure 3 is used to illustrate the battery detection and management method shown in

[0030] In step S11, the detection device 11 detects the target battery at the first time point and generates health detection data. Specifically, the first time point can be the time when the recycled battery enters the factory, or the time when the battery is received. The battery can be a storage battery applicable to a storage cabinet or a power battery for locomotives, automobiles, and buses. The health detection data can include the state of health (SOH) of the battery, the current voltage, the charging impedance, the voltage drop rate, the voltage rise rate, the discharge impedance, the remaining available capacity, and the classification level, etc.

[0031] In step S13, the computing device 12 uploads the health detection data of the target battery to the cloud database 14. Specifically, the form of uploading to the cloud database 14 can be a table, a graph file, or a text file. The health detection data can include the battery serial number. The health detection data is uploaded through the computing device 12 to establish a lookup table in the cloud database 14 for the battery serial number corresponding to the detection value.

[0032] In step S15, the computing device 12 determines the classification status of the target battery according to the health detection data and the preset health range, and generates a label through the label printer 13 for pasting on the target battery. Specifically, the preset health range can be that the health of the battery is greater than 20%. The classification status of the battery can indicate reuse or scrapping. The label can be a two-dimensional barcode, a three-dimensional barcode, a Quick Response (QR) barcode, an antenna, a Radiofrequency Identification (RFID) tag, and / or an encrypted electronic protection card, etc., and can have different colors or patterns to present different classification statuses of the battery.

[0033] In step S17, the detection device 11 detects the target battery at a second time point later than the first time point to update the health detection data of the target battery in the cloud database. Specifically, the second time point can be the time point after the battery is degraded and reused in an energy storage cabinet, a roadside device, or an uninterruptible power supply system. Updating the health detection data of the battery in the cloud database can be uploading the battery health data to the Global Standards One (GS1) database. In addition, in another embodiment, when detecting the battery at the second time point, the classification status of the battery can also be determined again according to the health detection data at the second time point and the preset health range. For example, when the health detection data of the battery detected at the second time point meets the preset health range, the classification status indicates reuse, and when the health detection data does not meet the preset health range, the classification status indicates scrapping.

[0034] Please combine Figure 3 with Figure 4 which Figure 4 is a flowchart showing the determination of the classification status of the battery according to an embodiment of the present invention. As Figure 4 shown, Figure 3Step S15 may include step S151: determining whether the health detection data meets a preset health range; when the determination result of step S151 is "no", that is, when the health detection data meets the preset health range, execute step S153: the classification status indicates scrapping; and when the determination result of step S151 is "yes", that is, when the health detection data does not meet the preset health range, execute step S155: the classification status indicates reuse. Determining the classification status of the battery is applicable to Figure 1 the battery detection management system 1 shown in Figure 2 and the battery detection management system 1' shown in Figure 1 The battery detection management system 1 shown in is used for illustration Figure 4 the determination of the classification status of the battery shown in

[0035] In step S151, the computing device 12 determines whether the health detection data meets the preset health range. Specifically, the preset health range may indicate that the health of the battery is greater than 20%. When the health detection data meets the preset health range, that is, the health of the battery is greater than 20%, and when the health detection data does not meet the preset health range, that is, the health of the battery is less than or equal to 20%.

[0036] In step S153, the label printer 13 generates a label with the classification status indicating scrapping. Specifically, the label generated by the label printer 13 can be a two-dimensional code and can be scanned to link to the health detection data of the battery in the cloud database. When the classification status of the battery is scrapping, the generated label can be red or include a pattern indicating scrapping.

[0037] In step S155, the label printer 13 generates a label with the classification status indicating reuse. Specifically, the label generated by the label printer 13 can be a two-dimensional code and can be scanned to link to the health detection data of the battery in the cloud database. When the classification status of the battery is reuse, the generated label can be green or include a pattern indicating reuse.

[0038] Please refer to Figure 5 wherein Figure 5 is a flowchart of determining the classification status of the battery according to another embodiment of the present invention. As shown in Figure 5As shown, step S15’ may include step S151: determining whether the health detection data meets the preset health range; when the judgment result of step S151 is "no", that is, when the health detection data meets the preset health range, execute step S153: classifying the status indication for scrapping; when the judgment result of step S151 is "yes", that is, when the health detection data does not meet the preset health range, execute step S152: determining whether the difference between the health detection data of the target battery and multiple pre-used batteries of the uninterruptible power supply system is less than a preset value; when the judgment result of step S152 is "yes", that is, when the difference between the health detection data of the target battery and multiple pre-used batteries of the uninterruptible power supply system is less than the preset value, execute step S154: classifying the status indication for reuse and being applicable to the uninterruptible power system; and when the judgment result of step S152 is "no", that is, when the difference between the health detection data of the target battery and multiple pre-used batteries of the uninterruptible power supply system is not less than the preset value, execute step S156: classifying the status indication for reuse, where the execution methods of step S151 and step S153 are the same as Figure 4 , so they will not be elaborated here. Among them, judging the classification status of the battery can be applicable to Figure 1 the battery detection management system 1 shown in Figure 2 and the battery detection management system 1' shown in Figure 1 . Hereinafter, the battery detection management system 1 shown in Figure 5 will be used as an example to illustrate the judgment of the classification status of the battery.

[0039] In step S152, the arithmetic device 12 determines whether the difference between the health detection data of the target battery and multiple pre-used batteries of the uninterruptible power supply system is less than a preset value. Specifically, for example, the health of multiple pre-used batteries of the uninterruptible power supply system can be 60%, and when the detection device 11 detects that the health detection data of the target battery indicates a health of 60%, the arithmetic device 12 determines that the difference between the health detection data of the target battery and multiple pre-used batteries of the uninterruptible power supply system is less than the preset value.

[0040] In step S154, the label printer 13 generates a label with a classification status indication for reuse and is applicable to the uninterruptible power system. Specifically, for example, the health of multiple pre-used batteries of the uninterruptible power supply system can be 60%, and when the detection device 11 detects that the health detection data of the target battery indicates a health of 60%, the arithmetic device 12 determines that the difference between the health detection data of the target battery and multiple pre-used batteries of the uninterruptible power supply system is less than the preset value, and the label printer 13 generates a label with a classification status indication for reuse and is applicable to the uninterruptible power system.

[0041] In step S156, the label printer 13 generates a classification status indication for the label for reuse. Specifically, for example, the health of multiple standby batteries of the uninterruptible power supply system can be 60%, and when the health detection data of the target battery detected by the detection device 11 indicates that the health is 30%, the arithmetic device 12 determines that the difference between the health detection data of the target battery and the multiple standby batteries of the uninterruptible power supply system is greater than the preset value, and the label printer 13 generates a classification status indication for the label for reuse.

[0042] Please refer to Figure 6 , where Figure 6 is a flowchart for detecting a battery according to an embodiment of the present invention. As Figure 6 shown, step S11 may include step S111: establishing a simulation test program according to the characteristic specifications of the target battery; and step S113: executing the simulation test program to generate health detection data of the target battery. The battery detection can be applicable to Figure 1 the battery detection management system 1 shown in Figure 2 and the battery detection management system 1' shown in Figure 1 The following exemplarily uses the battery detection management system 1 shown in Figure 6 to illustrate the process of detecting a battery shown in

[0043] In step S111, the arithmetic device 12 establishes a simulation test program according to the characteristic specifications of the target battery. Specifically, the characteristic specifications of the battery can be the battery characteristic specification sheet provided by the client or the battery specification data to be measured, and the simulation test program can be determined by the battery management system protocol and 30 standard samples.

[0044] In step S113, the detection device 11 executes the simulation test program to generate health detection data of the target battery. Specifically, the health detection data of the battery can be a battery detection evaluation report, the SOH status of the battery detection, and / or the battery detection classification.

[0045] Please refer to Figure 7 , where Figure 7 is a flowchart for detecting a battery according to another embodiment of the present invention. As Figure 7 shown, step S11' may include step S112: obtaining a battery characteristic specification sheet; step S114: planning a simulation test program according to the battery characteristic specifications; step S116: receiving basic data of the executor and the unit and basic data of the battery product specifications; step S118: the charge and discharge machine equipment performs batch operations to generate a test report; step S120: performing artificial intelligence batch automatic calculation and filing, and establishing a total measurement index table according to the database; step S122: performing database management with a web query management total table; and step S124: generating a battery quick screening evaluation report.

[0046] In this embodiment, the battery characteristic specifications obtained in step S112 can be used to plan a process simulation curve graph. In step S114, the simulation test curve can be predicted and protection points can be set for the battery. In step S116, basic test data is filled in. And in step S118, when the charge and discharge machine equipment performs batch operations, a real-time display panel is provided for each test channel to display the status information of the battery under test. The test and the unfinished process can be interrupted at any time. After interruption, the scheduling test can continue on other channels. At the same time, a test curve graph and a text report can be generated to provide data for interactive reference. In step S120, artificial intelligence (AI) operations are performed and a database file is established. And in step S122, the database is managed by querying the management summary table. The battery quick screening and evaluation report generated in step S124 can include the state of health (SOH) of the battery, the current voltage, the charging impedance, the voltage drop rate, the voltage rise rate, the discharge impedance, the remaining available capacity, and the classification level, etc.

[0047] Please refer to Figure 8 , in which Figure 8 is a flowchart of a battery detection management method illustrated according to another embodiment of the present invention. As Figure 8 shown, the battery detection management method may include step S201: receiving a used target battery recycled from a recycling plant; step S203: detecting the target battery to generate health degree detection data; step S205: uploading the health degree detection data to a cloud database; step S207: judging whether the target battery meets a preset health degree range based on the health degree detection data; step S209: generating a label presenting a classification status indication for reuse by a label printer; step S211: reusing the target battery after downgrading; step S213: generating a label presenting a classification status indication for scrapping by a label printer; step S215: scrapping the target battery; step S217: canceling the processing of the target battery; step S219: quickly discharging the target battery; and step S221: physically crushing and hydrometallurgically treating the target battery. The battery detection management method is applicable to Figure 1 the battery detection management system 1 shown in Figure 2 and Figure 1 the battery detection management system 1' shown in Figure 8 The battery detection management method will be described below by taking the battery detection management system 1 shown in

[0048] In this embodiment, the used battery is recycled from the recycling plant in step S201. The battery is detected by the detection device 11 in step S203 to generate health detection data. In step S205, the computing device 12 uploads the health detection data to the cloud database 14. In step 207, the computing device 12 determines whether the battery meets the preset health range according to the health detection data. When the judgment result is "yes", step S209 is executed, and the label printer 13 generates a label presenting the classification status indicating reuse, and step S211 is executed to reuse the battery after degradation. The degradation reuse can be, for example, for energy storage cabinets, roadside equipment, and uninterruptible power systems, and after reuse, steps S203 and the processes corresponding to after step S203 can be executed again; when in step 207, the computing device 12 determines that the battery does not meet the preset health range according to the health detection data, that is, when the judgment result is "no", step S213 is executed, and the label printer 13 generates a label presenting the classification status indicating scrapping, and then steps S215 for scrapping the battery, S217 for canceling the battery, S219 for quickly discharging the battery, and S221 for physically crushing and hydrometallurgical treatment of the battery are carried out. The quick discharge of the battery can be achieved by using high-frequency pulse width modulation charge and discharge control (Pulse width modulation, PWM) or direct current internal resistance (Direct Current Internal Resistance, DCIR).

[0049] With the above structure, the battery detection and management method and system disclosed in the present invention can screen and classify and label the recycled batteries, and perform reuse after classification and recycling to improve efficiency and reduce environmental impact. In addition, through the quick screening equipment and the battery classification method, the battery detection and management method and system disclosed in the present invention can save a large amount of time and resources, enabling the data analysis of the battery management system to efficiently provide classification and perform accurate health status assessment when dealing with a large amount of data.

[0050]

Explanation of Reference Numerals

[0051] 1, 1’: Battery detection and management system

[0052] 11: Detection device

[0053] 12: Computing device

[0054] 13: Label printer

[0055] 14: Cloud database

[0056] 15: Switching hub

[0057] 16: Communication adapter box

[0058] 17: Reliability test equipment

[0059] 18: Temperature collector

[0060] 19: Voltage collector

[0061] 111: Test equipment

[0062] 112: BMS data collector

[0063] 2: Battery

[0064] S11, S13, S15, S17, S11’, S15’, S151, S153, S155, S152, S154, S156, S111, S113, S112, S114, S116, S118, S120, S122, S124, S201, S203, S205, S207, S209, S211, S213, S215, S217, S219, S221: Steps

Claims

1. A battery detection management method, characterized in that: Include: Detecting a target battery at a first time point to generate health detection data; Uploading the health test data to a cloud database; Determine a classification state of the target battery according to the health detection data and a preset health range, and generate a label to be attached to the target battery, wherein the label presents the classification state and is used to link to the health detection data of the target battery in the cloud database; and The target battery is detected at a second time point later than the first time point to update the health detection data of the target battery in the cloud database.

2. The battery detection management method according to claim 1, characterized in that: The preset health range indicates that the health of the target battery is greater than 20%. When the health detection data meets the preset health range, the classification status indicates reuse, and when the health detection data does not meet the preset health range, the classification status indicates scrapping.

3. The battery detection management method according to claim 1, characterized in that: Testing the target battery to generate the health test data report includes: Establishing a simulation test program according to the characteristic specifications of the target battery; and The simulation test program is executed to generate the health detection data of the target battery.

4. The battery detection management method according to claim 1, characterized in that: Also includes: When the difference between the health detection data of the target battery and a plurality of pre-used batteries of an uninterruptible power supply system is less than a preset value, the target battery is marked as being suitable for the uninterruptible power supply system.

5. The battery detection management method according to claim 1, characterized in that: The label presents different classification states with different colors or patterns.

6. A battery detection management system, characterized in that: Include: A detection device for detecting a target battery to generate health detection data; a computing device connected to the detection device, for uploading the health detection data to a cloud database and determining a classification state of the target battery according to the health detection data and a preset health range; and A labeling machine is connected to the computing device and is used to generate a label to be attached to the target battery, wherein the label presents the classification status and is used to link to the health detection data of the target battery in the cloud database.

7. The battery detection management system according to claim 6, characterized in that: The preset health range indicates that the health of the target battery is greater than 20%. When the health detection data meets the preset health range, the classification status indicates reuse, and when the health detection data does not meet the preset health range, the classification status indicates scrapping.

8. The battery detection management system according to claim 6, characterized in that: The detection device is used to establish a simulation test program according to the characteristic specification of the target battery and execute the simulation test program to generate the health detection data of the target battery.

9. The battery detection management system according to claim 6, characterized in that: The computing device is further used to mark the target battery as being suitable for the uninterruptible power supply system when the difference between the health detection data of the target battery and a plurality of pre-used batteries of an uninterruptible power supply system is less than a preset value.

10. The battery detection management system according to claim 6, characterized in that: The label presents different classification states with different colors or patterns.

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