A method and device for detecting the health of a battery pack

Abstract

The present application provides a method and device for detecting the health of a battery pack. The method includes: when the battery pack of a target vehicle is being charged and in the battery pack health self-check mode, reading the self-check data of the battery pack of the target vehicle; determining whether the self-check data meets a first preset threshold range; if so, requesting the battery management system of the target vehicle to charge the battery pack according to a preset charging current scheme; when the charging process of the battery pack ends, obtaining the battery pack health data during the charging process; uploading the battery pack health data to a big data center for battery health diagnosis; when receiving the feedback result from the big data center, updating the charging current scheme according to the feedback result. It can be seen that this method can accurately detect the battery health status, is suitable for in-vehicle testing, has a short testing time and high accuracy.

Description

Technical Field

[0001] The present application relates to the technical field of batteries, and more particularly, to a method and device for detecting the health of a battery pack. Background Art

[0002] At present, electric vehicles are gradually becoming popular in the automotive market of our country. At the same time, the safety of the battery pack, especially fast charging safety, has become a restricting factor for further penetration and promotion of its market share. Currently, the battery packs of pure electric vehicles are mostly lithium-ion batteries composed of graphite anodes, nickel cobalt manganese (NCM) ternary cathodes or lithium iron phosphate (LFP) cathodes. From an electrochemical perspective, such batteries are prone to inducing the formation of a solid electrolyte interphase (SEI) on the graphite anode under high-rate charging conditions, which greatly increases the probability of dendrite generation and even causes the risk of battery thermal runaway in severe cases. Existing battery health management methods usually measure the capacity or internal resistance characteristics of the battery directly by testing methods such as constant current charge and discharge, hybrid pulse power characteristics, and electrochemical impedance spectroscopy (EIS), so as to adjust the charging scheme. However, in practice, it is found that the existing methods require the intervention of experimental equipment, are difficult to be applied to real vehicles, have a long testing time, and poor accuracy. Summary of the Invention

[0003] The purpose of the embodiments of the present application is to provide a method and device for detecting the health of a battery pack, which can accurately detect the health status of the battery, is applicable to real vehicle testing, has a short testing time, and high accuracy.

[0004] The first aspect of the embodiments of the present application provides a method for detecting the health of a battery pack, including:

[0005] When the battery pack of the target vehicle is charging and in the battery pack health self-check mode, read the self-check data of the battery pack of the target vehicle;

[0006] Judge whether the self-check data meets the first preset threshold range;

[0007] If so, request the battery management system of the target vehicle to charge the battery pack according to the preset charging current scheme;

[0008] When the charging process of the battery pack ends, obtain the battery pack health data of the charging process;

[0009] Upload the battery pack health data to the big data center for battery health diagnosis;

[0010] When receiving the feedback result from the big data center, update the charging current scheme according to the feedback result.

[0011] In the above implementation process, the method can preferably read the battery self-check data of the target vehicle when the battery pack of the target vehicle is charging and in the battery pack health self-check mode; then judge whether the self-check data meets the first preset threshold range; and when the self-check data meets the first preset threshold range, request the battery management system of the target vehicle to charge the battery pack according to the preset charging current scheme; when the charging process of the battery pack ends, obtain the battery pack health data during the charging process; then upload the battery pack health data to the big data center for battery health diagnosis; finally, when receiving the feedback result from the big data center, update the charging current scheme according to the feedback result. It can be seen that implementing this implementation method can accurately detect the battery health status, is applicable to real vehicle testing, has a short testing time and high accuracy.

[0012] Further, after requesting the battery management system of the target vehicle to charge the battery pack according to the preset charging current scheme, the method further includes:

[0013] Collect the current battery charging voltage of the target vehicle;

[0014] Analyze the battery health status of each cell of the battery pack according to the current battery charging voltage using the point method and the current battery charging voltage;

[0015] Detect whether the current charging voltage of each cell of the battery pack exceeds the second preset threshold range;

[0016] If so, end the charging process of the battery pack and execute the step of obtaining the battery pack health data during the charging process.

[0017] Further, the battery pack self-check data at least includes the battery static time, the state of charge of the battery, the voltage of each cell of the battery pack, and the temperature of the battery pack;

[0018] The first preset threshold range at least includes a static time threshold range, a state of charge threshold range, a cell voltage threshold range, and a temperature threshold range.

[0019] Further, the obtaining of the battery pack health data during the charging process includes:

[0020] Obtain the vehicle information of the target vehicle, the vehicle identification code, and the battery health status of each cell;

[0021] Calculate the battery health status of the entire battery pack according to the battery health status of each cell;

[0022] Summarize the vehicle information, the vehicle identification code, the battery health status of each single cell, and the battery health status of the entire battery pack to obtain the battery pack health data.

[0023] Further, the updating of the charging current scheme according to the feedback result includes:

[0024] Request to determine the optimized charging power, the optimized discharge depth, and the optimized slow charge voltage according to the feedback result;

[0025] Update the charging current scheme according to the charging power, the discharge depth, and the slow charge voltage.

[0026] A second aspect of the embodiments of the present application provides a battery pack health detection device, and the battery pack health detection device includes:

[0027] A reading unit, configured to read the battery pack self-check data of the target vehicle when the battery pack of the target vehicle is charging and in the battery pack health self-check mode;

[0028] A first judgment unit, configured to judge whether the self-check data meets a first preset threshold range;

[0029] A request unit, configured to request the battery management system of the target vehicle to charge the battery pack according to a preset charging current scheme when it is determined that the self-check data meets the first preset threshold range;

[0030] An obtaining unit, configured to obtain the battery pack health data of the charging process after the charging process of the battery pack ends;

[0031] An uploading unit, configured to upload the battery pack health data to a big data center for battery health diagnosis;

[0032] An updating unit, configured to update the charging current scheme according to the feedback result when receiving the feedback result fed back by the big data center.

[0033] In the above implementation process, the device can read the battery pack self-check data of the target vehicle through the reading unit when the battery pack of the target vehicle is charging and in the battery pack health self-check mode; judge whether the self-check data meets the first preset threshold range through the first judgment unit; when it is judged that the self-check data meets the first preset threshold range, request the battery management system of the target vehicle to charge the battery pack according to the preset charging current scheme through the request unit; after the battery pack ends the charging process, obtain the battery pack health data of the charging process through the obtaining unit; upload the battery pack health data to the big data center for battery health diagnosis through the uploading unit; when receiving the feedback result fed back by the big data center, update the charging current scheme according to the feedback result through the updating unit. It can be seen that implementing this implementation method can accurately detect the battery health status, is applicable to real vehicle testing, has a short testing time and high accuracy.

[0034] Further, the battery pack health detection device further includes:

[0035] The acquisition unit is used to acquire the current battery charging voltage of the target vehicle after requesting the battery management system of the target vehicle to charge the battery pack according to the preset charging current scheme;

[0036] The analysis unit is used to analyze the battery health status of each cell of the battery pack according to the current battery charging voltage by using the dot method and the current battery charging voltage;

[0037] The detection unit is used to detect whether the current charging voltage of each cell of the battery pack exceeds the second preset threshold range;

[0038] The ending unit is used to end the charging process of the battery pack when it is judged that the current charging voltage exceeds the second preset threshold range, and trigger the obtaining unit to obtain the battery pack health data of the charging process.

[0039] Further, the battery pack self-check data at least includes the battery static time, the state of charge of the battery, the voltage of each cell of the battery pack, and the temperature of the battery pack;

[0040] The first preset threshold range at least includes a static time threshold range, a charge threshold range, a cell voltage threshold range, and a temperature threshold range.

[0041] Further, the obtaining unit includes:

[0042] The obtaining subunit is used to obtain the vehicle information of the target vehicle, the vehicle identification code, and the battery health status of each cell;

[0043] The calculation subunit is used to calculate the battery health status of the entire battery pack according to the battery health status of each cell;

[0044] A summarizing subunit, configured to summarize the vehicle information, the vehicle identification code, the battery health status of each single cell, and the battery health status of the entire battery pack to obtain battery pack health data.

[0045] Further, the updating unit includes:

[0046] A determining subunit, configured to determine an optimized charging power, an optimized discharge depth, and an optimized slow charging voltage according to the feedback result request;

[0047] An updating subunit, configured to update the charging current scheme according to the charging power, the discharge depth, and the slow charging voltage.

[0048] A third aspect of the embodiments of the present application provides an electronic device, including a memory and a processor, where the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute the battery pack health detection method according to any one of the first aspects of the embodiments of the present application.

[0049] A fourth aspect of the embodiments of the present application provides a computer-readable storage medium, which stores computer program instructions, and when the computer program instructions are read and run by a processor, the battery pack health detection method according to any one of the first aspects of the embodiments of the present application is executed. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required to be used in the embodiments of the present application. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts.

[0051] Figure 1 It is a flowchart of a battery pack health detection method provided by an embodiment of the present application;

[0052] Figure 2 It is a structural schematic diagram of a battery pack health detection device provided by an embodiment of the present application;

[0053] Figure 3 It is a schematic diagram of an example of the structure of a battery pack health detection device provided by an embodiment of the present application;

[0054] Figure 4 It is an ICA curve graph at different aging stages obtained from an actual vehicle provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0055] Next, the technical solutions in the embodiments of the present application will be described with reference to the accompanying drawings in the embodiments of the present application.

[0056] It should be noted that: Similar reference numerals and letters denote similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of the present application, the terms "first", "second", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0057] Embodiment 1

[0058] Please refer to Figure 1 , Figure 1 , which is a schematic flowchart of a battery pack health detection method provided by an embodiment of the present application. Among them, the battery pack health detection method includes:

[0059] S101. When the battery pack of the target vehicle is charging and in the battery pack health self-check mode, read the battery pack self-check data of the target vehicle.

[0060] S102. Determine whether the self-check data meets the first preset threshold range. If so, execute step S103; if not, end this process.

[0061] S103. Request the battery management system of the target vehicle to charge the battery pack according to a preset charging current scheme.

[0062] S104. Collect the current battery charging voltage of the target vehicle.

[0063] S105. Analyze the battery health status of each cell in the battery pack based on the point method and the current battery charging voltage according to the current battery charging voltage.

[0064] S106. Detect whether the current charging voltage of each cell in the battery pack exceeds the second preset threshold range. If so, execute step S107; if not, end this process.

[0065] S107. End the charging process of the battery pack.

[0066] S108. Obtain the vehicle information, vehicle identification code, and battery health status of each cell of the target vehicle.

[0067] S109. Calculate the battery health status of the entire battery pack according to the battery health status of each cell.

[0068] S110. Summarize the vehicle information, vehicle identification code, battery health status of each cell, and battery health status of the entire battery pack to obtain battery pack health data.

[0069] S111. Upload the battery pack health data to the big data center for battery health diagnosis.

[0070] S112. When receiving the feedback result from the big data center, determine the optimized charging power, optimized discharge depth, and optimized slow charge voltage according to the feedback result request.

[0071] S113. Update the charging current scheme according to the charging power, discharge depth, and slow charge voltage.

[0072] In this embodiment, the method provides an estimation method for battery SOH, which is specifically executed in cooperation with the vehicle BMS by the detection device. The method is exemplified as follows:

[0073] ① The detection device reads the vehicle Vin code, temperature, SOC, and the voltage of each cell, etc., and determines whether each parameter is within the pre-set threshold range. If the judgment result is yes, it sends a BMS through the UDS instruction to change the BMS requested current map; if the judgment result is no, it ends the health self-check mode.

[0074] ② In a possible implementation of the first step, the charging voltage of the battery is collected, and according to the voltage data within the threshold range, the formula: ΔQ / ΔV = n*I / (3600*f*ΔV) is used. Where n is the number of data points within the voltage threshold range, I is the charging current value, f is the sampling frequency, and ΔV is the voltage sampling interval.

[0075] ③ When the charging voltage in the second step exceeds the pre-set threshold, the BMS stops charging. The detection device stores the calculated SOH value of each cell, calculates the whole pack SOH = min{SOHCell1, SOHCell2,..., SOHCellmax} and uploads the data to the cloud.

[0076] ④ The big data center judges the rationality of the calculated SOH value and compares whether the SOH value meets the pre-set threshold. If the judgment result is yes, it feeds back to the communication unit, sends a UDS instruction, and writes the optimized charging map, DOD, and full charge voltage; if the judgment result is no, it ends the health self-check.

[0077] In this embodiment, in the above first step, the battery's static time, temperature, cell voltage, and SOC threshold are determined by off-line test calibration. Among them, the battery static time should be greater than t0, and the temperature range is T1~T2 to ensure that the battery polarization effect is small when starting the health self-check; the cell voltage is less than V0, and the SOC range is SOC1~SOC2 to ensure that after the health self-check starts, the ICA method can capture the complete peak curve and the whole self-check time is not too long.

[0078] In this embodiment, in the above-mentioned second step, if the control conditions set in the first step are met, the UDS switched battery request current I = 1 / 5C, the sampling frequency f of the current and voltage, and the number point interval is ΔV.

[0079] In this embodiment, in the above-mentioned third step, when all the cell voltages exceed V1, the charging process ends.

[0080] In this embodiment, in the above-mentioned fourth step, the big data center compares the SOH of the battery. If the SOH is less than the calibrated threshold SOH1, the communication unit switches the battery from BOL Map to MOL Map, reduces the DOD and lowers the full charge voltage; if the SOH is less than the flag threshold SOH2, the communication unit switches the charging Map to EOL Map, further reduces the DOD and lowers the full charge voltage.

[0081] Please refer to Figure 3 , Figure 3 which is a schematic diagram of an embodiment of the present invention. The data acquisition unit is used to acquire the current, cell voltage, temperature, and SOC of the battery and output them to the main control unit. The main control unit can temporarily store the above data in the RAM or EEPROM. The main control unit is used to receive the data output by the data acquisition unit and upload the above data to the cloud big data center through the communication unit. The main control unit is also used to receive and verify the data transmitted by the communication unit and control the entire health self-check process according to the above-designed logic. The data processing unit is used to perform equal voltage interval number points on the charging voltage data and convert it into an SOH value through an algorithm. The data processing unit also interacts with the communication unit and uploads the calculated SOH values of each cell to the big data center. The data communication unit transmits information with the main control unit, the data processing unit, and the big data center, and can also interact with the BMS to control the BMS through UDS.

[0082] In this embodiment, the specific steps for the method to implement battery SOH detection and full life cycle management are as follows:

[0083] ① The detection unit measures the battery Vin code, temperature, each cell voltage, and SOC, and then outputs them to the main control unit and the communication unit;

[0084] ② The control unit determines whether the battery temperature, cell voltage, and SOC are within the threshold range. The battery temperature, cell voltage, and SOC are all calibrated from the pre-offline battery aging test, aiming to minimize the error caused by polarization in the subsequent ICA test and control the total duration of the entire self-check process;

[0085] ③ Under the condition that the temperature, cell voltage, and SOC are all within the threshold range, the main control unit starts the self-check process, outputs an instruction to the BMS through the communication unit, and switches the battery charging map;

[0086] ④The BMS enters the normal charging process. The detection unit collects the voltages of each battery cell at a preset sampling frequency and outputs them to the main control unit and the data processing unit;

[0087] ⑤The data processing unit processes the collected data, performs data points at a preset sampling frequency and voltage interval ΔV, and calculates the peak intensity of the single cell through the formula: ΔQ / ΔV = n*I / (3600*f*ΔV). When all single cells exceed the preset voltage upper limit threshold, the data point ends, and the number of points is looked up in the table to obtain the SOH of the battery. This two-dimensional table of the number of points - SOH is obtained from the offline battery cycle test and will not be elaborated here;

[0088] ⑥The main control unit controls the BMS to end the charging process. The data processing unit feeds back the SOH calculation result to the data unit and uploads it to the big data center;

[0089] ⑦The big data center judges the rationality of the vehicle SOH result and the battery aging state belongs to MOL (Middle of Life), EOL (End of Life), and transmits it back to the data communication unit;

[0090] ⑧The data communication unit outputs the judgment result of the big data center to the main control unit. The main control unit controls the BMS to switch to the preset MOL Map or EOL Map according to the feedback result. At the same time, it limits the DOD and full charge voltage of the battery.

[0091] Please refer to Figure 4 , Figure 4 which shows an ICA curve graph at different aging stages obtained from an actual vehicle. It can be seen that this result can show that the method provided by the present invention can fit the ICA curve in the actual vehicle BMS and further accurately obtain the battery SOH based on this, proving the feasibility of the present invention.

[0092] In this embodiment, the above four steps are all essential, and steps one and four are preferred. Step one ensures the reliability of the battery health self-check result and is used to eliminate the polarization effect in part of the constant current charging curve; step four is used to optimize the battery charging strategy with the obtained SOH value to ensure the charging safety of the battery throughout its life cycle.

[0093] In this embodiment, the execution subject of this method is the detection device.

[0094] In this embodiment, the execution subject of this method can specifically be a computing device such as a computer or a server, and no limitation is made in this embodiment.

[0095] In this embodiment, the execution subject of this method can also be a smart device such as a smart phone or a tablet computer, and no limitation is made in this embodiment.

[0096] It can be seen that implementing the battery pack health detection method described in this embodiment can improve the overall low operation efficiency and avoid the problem of data anomalies (jumping large numbers) that may be caused by differential operations; it can also solve the problem of SOH estimation.

[0097] Embodiment 2

[0098] Please refer to Figure 2 , Figure 2 which is a schematic structural diagram of a battery pack health detection device provided by an embodiment of the present application. As Figure 2 shown, the battery pack health detection device includes:

[0099] A reading unit 210, configured to read the self-check data of the battery pack of the target vehicle when the battery pack of the target vehicle is charging and in the battery pack health self-check mode;

[0100] A first judgment unit 220, configured to judge whether the self-check data meets a first preset threshold range;

[0101] A request unit 230, configured to request the battery management system of the target vehicle to charge the battery pack according to a preset charging current scheme when it is determined that the self-check data meets the first preset threshold range;

[0102] An acquisition unit 240, configured to acquire the battery pack health data during the charging process after the charging process of the battery pack ends;

[0103] An upload unit 250, configured to upload the battery pack health data to a big data center for battery health diagnosis;

[0104] An update unit 260, configured to update the charging current scheme according to the feedback result when receiving the feedback result from the big data center.

[0105] As an optional implementation manner, the battery pack health detection device further includes:

[0106] An acquisition unit 270, configured to acquire the current battery charging voltage of the target vehicle after requesting the battery management system of the target vehicle to charge the battery pack according to a preset charging current scheme;

[0107] An analysis unit 280, configured to analyze the battery health status of each cell of the battery pack according to the current battery charging voltage by using the point method and the current battery charging voltage;

[0108] A detection unit 290, configured to detect whether the current charging voltage of each cell of the battery pack exceeds a second preset threshold range;

[0109] An end unit 300, which is configured to end the charging process of the battery pack when it is determined that the current charging voltage exceeds the second preset threshold range, and trigger the acquisition unit 240 to acquire the battery pack health data during the charging process.

[0110] In this embodiment, the battery pack self-check data at least includes the battery static time, the state of charge of the battery, the voltage of each battery cell in the battery pack, and the temperature of the battery pack.

[0111] The first preset threshold range at least includes a static time threshold range, a state of charge threshold range, a single cell voltage threshold range, and a temperature threshold range.

[0112] As an optional implementation manner, the acquisition unit 240 includes:

[0113] An acquisition subunit 241, which is configured to acquire the vehicle information of the target vehicle, the vehicle identification code, and the battery health status of each single cell.

[0114] A calculation subunit 242, which is configured to calculate the battery health status of the entire battery pack according to the battery health status of each single cell.

[0115] A summary subunit 243, which is configured to summarize the vehicle information, the vehicle identification code, the battery health status of each single cell, and the battery health status of the entire battery pack to obtain the battery pack health data.

[0116] As an optional implementation manner, the update unit 260 includes:

[0117] A determination subunit 261, which is configured to request and determine the optimized charging power, the optimized discharge depth, and the optimized slow charging voltage according to the feedback result.

[0118] An update subunit 262, which is configured to update the charging current scheme according to the charging power, the discharge depth, and the slow charging voltage.

[0119] For example, the device can be a device for vehicle health self-check. In the example, the device can include: a data acquisition unit, which is configured to acquire the measured battery SOC, temperature, current, and the voltage of each single cell; a main control unit, which is configured to determine whether the SOC, temperature, and the voltage of each single cell are within the preset threshold range. If the determination result is yes, switch the charging map of the BMS to 1 / 5C constant current until the SOC or the voltage jumps out of the preset threshold range, otherwise exit the health self-check process; a data processing unit, which is configured to calculate the battery SOH in real time by using the point method according to the acquired 1 / 5C constant current partial charging voltage curve; a data communication unit, which is configured to interact with the cloud big data center and upload the SOH result of this health self-check; and also interact with the BMS, which is configured to control the charging strategy of the BMS and optimize the charging map, the full charge voltage, the discharge depth (DOD), etc. according to different battery aging states.

[0120] In this embodiment, the explanation of the battery pack health detection device can refer to the description in Embodiment 1, and thus will not be elaborated herein.

[0121] It can be seen that implementing the battery pack health detection device described in this embodiment can improve the overall low computing efficiency and avoid the problem of data anomalies (large number jumps) that may be caused by differential operations; it can also solve the problem of SOH estimation.

[0122] An embodiment of the present application provides an electronic device, including a memory and a processor. The memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute the battery pack health detection method in Embodiment 1 of the present application.

[0123] An embodiment of the present application provides a computer-readable storage medium, which stores computer program instructions. When the computer program instructions are read and run by a processor, the battery pack health detection method in Embodiment 1 of the present application is executed.

[0124] In several embodiments provided by the present application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions, and operations of devices, methods, and computer program products according to multiple embodiments of the present application. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, and the module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order from that marked in the accompanying drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0125] In addition, in each embodiment of the present application, the functional modules can be integrated together to form an independent part, or each module can exist alone, or two or more modules can be integrated to form an independent part.

[0126] When the above-mentioned functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The foregoing storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs.

[0127] The above are only the embodiments of this application and are not used to limit the protection scope of this application. For those skilled in the art, this application can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this application shall be included in the protection scope of this application. It should be noted that similar reference numerals and letters indicate similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0128] The above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in this application, and all should be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

[0129] It should be noted that in this text, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or further includes elements inherent to such process, method, article or device. Without further limitations, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including the said element.

Claims

1. A battery pack health detection method, characterized in that, Including: When the battery pack of the target vehicle is being charged and in the battery pack health self-check mode, read the battery pack self-check data of the target vehicle; Judge whether the self-check data meets the first preset threshold range; If so, request the battery management system of the target vehicle to charge the battery pack according to the preset charging current scheme; After the battery pack finishes the charging process, obtain the battery pack health data of the charging process; Upload the battery pack health data to the big data center for battery health diagnosis; When receiving the feedback result from the big data center, update the charging current scheme according to the feedback result; Wherein, the battery pack self-check data at least includes the battery static time, the state of charge of the battery, the single cell voltage of the battery pack, and the battery pack temperature; The first preset threshold range at least includes a static time threshold range, a state of charge threshold range, a single cell voltage threshold range, and a temperature threshold range.

2. The battery pack health detection method according to claim 1, wherein After the request to the battery management system of the target vehicle to charge the battery pack according to the preset charging current scheme, the method further includes: Collect the current battery charging voltage of the target vehicle; Analyze the battery health state of each single cell of the battery pack according to the current battery charging voltage by using the point method and the current battery charging voltage; Detect whether the current charging voltage of each single cell of the battery pack exceeds the second preset threshold range; If so, end the charging process of the battery pack, and execute the obtaining of the battery pack health data of the charging process.

3. The battery pack health detection method according to claim 2, wherein The obtaining of the battery pack health data of the charging process includes: Obtain the vehicle information, vehicle identification code, and battery health state of each single cell of the target vehicle; Calculate the battery health state of the entire battery pack according to the battery health state of each single cell; Summarize the vehicle information, the vehicle identification code, the battery health state of each single cell, and the battery health state of the entire battery pack to obtain the battery pack health data.

4. The battery pack health detection method according to claim 1, wherein The updating of the charging current scheme according to the feedback result includes: Request to determine the optimized charging power, optimized discharge depth, and optimized slow charge voltage according to the feedback result; Update the charging current scheme according to the charging power, the discharge depth, and the slow charge voltage.

5. A battery pack health detection device, characterized in that, The battery pack health detection device includes: A reading unit, configured to read the battery pack self-check data of the target vehicle when the battery pack of the target vehicle is being charged and in the battery pack health self-check mode; A first judgment unit, configured to judge whether the self-check data meets the first preset threshold range; A request unit, configured to request the battery management system of the target vehicle to charge the battery pack according to the preset charging current scheme when it is judged that the self-check data meets the first preset threshold range; An obtaining unit, configured to obtain the battery pack health data of the charging process after the battery pack finishes the charging process; An uploading unit, configured to upload the battery pack health data to the big data center for battery health diagnosis; An update unit, configured to update the charging current scheme according to the feedback result when receiving the feedback result fed back by the big data center; Wherein, the battery pack self-check data at least includes battery static time, state of charge of the battery, single cell voltage of the battery pack, and temperature of the battery pack; The first preset threshold range at least includes a static time threshold range, a charge threshold range, a single cell voltage threshold range, and a temperature threshold range.

6. The battery pack health detection device according to claim 5, characterized in that, The battery pack health detection device further includes: A collection unit, configured to collect the current battery charging voltage of the target vehicle after requesting the battery management system of the target vehicle to charge the battery pack according to a preset charging current scheme; An analysis unit, configured to analyze the battery health status of each single cell of the battery pack according to the current battery charging voltage by using the dot method and the current battery charging voltage; A detection unit, configured to detect whether the current charging voltage of each single cell of the battery pack exceeds a second preset threshold range; An end unit, configured to end the charging process of the battery pack and trigger the acquisition unit to acquire the battery pack health data of the charging process when it is determined that the current charging voltage exceeds the second preset threshold range; 7. The battery pack health detection device according to claim 6, characterized in that, The acquisition unit includes: An acquisition subunit, configured to acquire the vehicle information, vehicle identification code, and battery health status of each single cell of the target vehicle; A calculation subunit, configured to calculate the battery health status of the entire battery pack according to the battery health status of each single cell; A summary subunit, configured to summarize the vehicle information, the vehicle identification code, the battery health status of each single cell, and the battery health status of the entire battery pack to obtain the battery pack health data.

8. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute the battery pack health detection method according to any one of claims 1 to 4.

9. A readable storage medium, characterized in that, Computer program instructions are stored in the readable storage medium, and when the computer program instructions are read and run by a processor, the battery pack health detection method according to any one of claims 1 to 4 is executed.

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