Method, device, electronic device and storage medium for determining battery health status

Abstract

The present application relates to a method, device, electronic device and storage medium for determining the health status of a battery. The method comprises: obtaining the cell voltage of each cell in the target battery pack when the cell is offline, the battery pack is offline, the vehicle is offline and the first charging of the vehicle is completed; obtaining the duration information of the three stages from the cell offline to the battery pack offline, the battery pack offline to the vehicle offline, and the vehicle offline to the first charging of the vehicle; when the target battery pack is in a long-term storage state, determining the voltage change rate of each stage based on multiple cell voltages and multiple duration information; determining the target health status of the target battery pack when the vehicle is offline based on the voltage change rate and the average health status obtained in advance. The use of this method can improve the accuracy of the health status measurement of the battery pack when the battery pack and the vehicle are offline, thereby reducing the cumulative error generated in the subsequent calculation of the state of charge.

Description

Technical Field

[0001] The present application relates to the field of battery technology, and in particular to a method, device, electronic device and storage medium for determining a battery health status. Background Art

[0002] With the rapid development of the new energy vehicle industry, battery technology has become a key factor in improving vehicle performance. From the battery cell off the production line to the battery pack assembly, to the battery pack transportation, vehicle loading and the first charging test, the entire process is closely connected to ensure the high performance and safety of the battery.

[0003] However, when the vehicle rolls off the production line, due to inaccurate measurement of the battery pack's state of health (SOH), the battery management system will produce cumulative errors in the subsequent calculation of the state of charge (SOC), which in turn affects the vehicle's range. Summary of the invention

[0004] Based on the above problems, the present application provides a method, device, electronic device and storage medium for determining the health status of a battery, which can improve the accuracy of measuring the health status of a battery pack when the battery pack is off the production line, thereby reducing the cumulative error generated in the subsequent calculation of the state of charge.

[0005] In a first aspect, the present application provides a method for determining a battery health status, the method comprising: obtaining the cell voltage of each battery cell in a target battery pack when the battery cell is offline, the battery pack is offline, the vehicle is offline, and the first charging of the vehicle is completed; obtaining the duration information of the three stages from the battery cell being offline to the battery pack being offline, from the battery pack being offline to the vehicle being offline, and from the vehicle being offline to the first charging of the vehicle being completed; when the target battery pack is in a long-term storage state, determining the voltage change rate of each stage based on multiple cell voltages and multiple duration information; determining the target health status of the target battery pack when the vehicle is offline based on the voltage change rate and the average health status acquired in advance.

[0006] In the technical solution of the embodiment of the present application, firstly, by collecting the cell voltage at different stages, the complete life cycle of the battery pack from production to vehicle assembly is covered. This full-process monitoring enables the dynamic changes of the cell state to be fully recorded, so that the performance degradation at each stage can be accurately captured. In addition, the step of determining the voltage change rate in combination with the duration information can reveal the performance change trend of the battery pack at different stages. This method not only considers the static parameters of the cell, but also combines its actual performance in storage and use. By calculating the voltage change rate, the degree of aging of the battery pack can be more scientifically reflected, thereby improving the accuracy of the prediction of the health status. Finally, by combining the voltage change rate with the pre-acquired average health status, a comprehensive assessment of the health status of the battery pack when the vehicle is off the assembly line is performed. This method reduces the impact of single data point errors while taking into account the differences between individual cells through multi-stage and multi-dimensional data analysis, thereby significantly improving the measurement accuracy of the health status of the battery pack.

[0007] In some embodiments, the target health state of the target battery pack when the vehicle rolls off the production line is determined based on the voltage change rate and the pre-acquired average health state, including: determining the health state decay rate of the target battery pack based on multiple voltage change rates; determining the target health state of the target battery pack when the vehicle rolls off the production line based on the health state decay rate and the average health state. The technical solution of the embodiment of the present application determines the health state decay rate through multiple voltage change rates, which can more comprehensively reflect the performance changes of the battery pack at different stages. By comprehensively considering multiple voltage change rates rather than relying on a single parameter, the evaluation deviation caused by measurement errors or abnormal data points can be reduced. This multi-dimensional data analysis method improves the stability and reliability of health state assessment.

[0008] In some embodiments, based on the health state decay rate and the average health state, the target health state of the target battery pack when the vehicle rolls off the assembly line is determined, including: when the health state decay rate is not greater than the preset decay rate threshold, the average health state is determined as the target health state of the target battery pack when the vehicle rolls off the assembly line; when the health state decay rate is greater than the preset decay rate threshold, the health state decay rate and the average health state are substituted into a preset relationship for calculation to obtain the target health state of the target battery pack when the vehicle rolls off the assembly line. In the technical solution of the embodiment of the present application, by setting a threshold value for the health state decay rate, it is possible to distinguish the treatment methods of battery packs at different degrees of decay. When the health state decay rate is small, directly using the average health state can reduce the error accumulation caused by the complex calculation process. When the decay rate is large, the target health state adjusted by the relationship can more truly reflect the actual situation of the battery pack and improve the credibility of the evaluation results.

[0009] In some embodiments, based on multiple cell voltages and multiple duration information, the voltage change rate of each stage is determined, including: for each cell, based on the cell voltage when the cell is offline, the cell voltage when the battery pack is offline, and the duration information from the cell offline to the battery pack offline, the voltage change rate from the battery pack offline to the battery pack offline is determined; based on the cell voltage when the battery pack is offline, the cell voltage when the vehicle is offline, and the duration information from the battery pack offline to the vehicle offline, the voltage change rate from the battery pack offline to the vehicle offline is determined; based on the cell voltage when the vehicle is offline, the cell voltage when the vehicle is charged for the first time, and the duration information from the vehicle offline to the vehicle first charging completion stage, the voltage change rate from the vehicle offline to the vehicle first charging stage is determined. In the technical solution of the embodiment of the present application, by respectively calculating the voltage change rate of the cell from offline to battery pack offline, from battery pack offline to vehicle offline, and from vehicle offline to the first charging completion stage, the whole process monitoring of the cell throughout the life cycle is achieved. This staged voltage change rate calculation can fully reflect the performance degradation of the battery cell under different environments and usage conditions.

[0010] In some embodiments, the method further includes: when the target battery pack is in a non-long-term storage state, obtaining the actual cell capacity of each cell in the target battery pack when the whole vehicle is offline; based on the actual cell capacity and the rated capacity and number of cells acquired in advance, determining the target health state when the whole vehicle is offline. In the technical solution of the embodiment of the present application, since the performance degradation of the battery cell in the non-long-term storage state is small, the evaluation result is closer to the actual health state of the battery pack. By comparing the actual capacity with the rated capacity, the current state of the battery cell can be more directly reflected, reducing the impact of uncertainties caused by long-term storage or idleness on the health state assessment.

[0011] In some embodiments, based on the actual cell capacity and the pre-acquired rated capacity and number of cells, the target health state of the vehicle when it rolls off the production line is determined, including: determining the health state decay amount based on the actual cell capacity, the rated capacity and the number of cells; determining the target health state based on the health state decay amount. In the technical solution of the embodiment of the present application, by determining the health state decay amount based on the actual cell capacity, the rated capacity and the number of cells, the actual changes in the performance of the cell during use can be effectively captured.

[0012] In some embodiments, the method further includes: performing correction processing on the target health state to obtain a corrected target health state. In the technical solution of the embodiment of the present application, through correction processing, the target health state value is closer to the actual state of the target battery pack when the vehicle is off the production line, reducing the error accumulation caused by initial setting deviation or external environmental factors.

[0013] In a second aspect, the present application further provides a device for determining a battery health status, the device comprising:

[0014] A cell voltage acquisition module is used to obtain the cell voltage of each cell in the target battery pack when the cell is offline, the battery pack is offline, the vehicle is offline, and the vehicle is charged for the first time;

[0015] The duration information acquisition module is used to respectively acquire the duration information of the three stages from the battery cell off-line to the battery pack off-line, from the battery pack off-line to the vehicle off-line, and from the vehicle off-line to the completion of the first charging of the vehicle;

[0016] A voltage change rate determination module, used to determine the voltage change rate of each stage based on multiple cell voltages and multiple duration information when the target battery pack is in a long-term storage state;

[0017] The first health state determination module is used to determine the target health state of the target battery pack when the vehicle is offline based on the voltage change rate and the pre-acquired average health state.

[0018] In a third aspect, the present application further provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements any one of the methods in the first aspect when executing the computer program.

[0019] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method of any one of the first aspects is implemented.

[0020] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, which implements any one of the methods in the first aspect when executed by a processor. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the optional embodiments below. The accompanying drawings are only used for the purpose of illustrating the optional embodiments and are not to be considered as limiting the present application. Moreover, the same reference numerals are used throughout the drawings to represent the same components. In the drawings:

[0022] Figure 1 is an application environment diagram of a method for determining a battery health status according to an embodiment of the present application;

[0023] Figure 2 is a flowchart of a method for determining a battery health status according to an embodiment of the present application;

[0024] Figure 3 It is a flowchart of the steps of determining the target health state of the target battery pack when the vehicle is off the production line according to one embodiment of the present application;

[0025] Figure 4is a flowchart of a method for determining a battery health status according to an embodiment of the present application;

[0026] Figure 5 It is a flowchart of the steps of determining the target health state of the target battery pack when the vehicle is off the production line according to one embodiment of the present application;

[0027] Figure 6 is a structural block diagram of a device for determining a battery health status according to an embodiment of the present application;

[0028] Figure 7 is a structural block diagram of a device for determining a battery health status according to another embodiment of the present application;

[0029] Figure 8 is a structural block diagram of a device for determining a battery health status according to another embodiment of the present application;

[0030] Fig. 9 It is a diagram of the internal structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0031] The following embodiments of the technical solution of the present application are described in detail in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present application, and are therefore only used as examples, and cannot be used to limit the scope of protection of the present application.

[0032] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by technicians in the technical field to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" in the specification and claims of this application and the above-mentioned figure descriptions and any variations thereof are intended to cover non-exclusive inclusions.

[0033] In the description of the embodiments of the present application, the technical terms "first", "second", etc. are only used to distinguish different objects, and cannot be understood as indicating or implying relative importance or implicitly indicating the number, specific order or primary and secondary relationship of the indicated technical features. In the description of the embodiments of the present application, the meaning of "multiple" is more than two, unless otherwise clearly and specifically defined.

[0034] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0035] In the description of the embodiments of the present application, the term "and / or" is only a description of the association relationship of the associated objects, indicating that there may be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0036] In the description of the embodiments of the present application, the term "multiple" refers to more than two (including two). Similarly, "multiple groups" refers to more than two groups (including two groups), and "multiple pieces" refers to more than two pieces (including two pieces).

[0037] In the description of the embodiments of the present application, unless otherwise clearly specified and limited, technical terms such as "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, and it can be the internal connection of two elements or the interaction relationship between two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the embodiments of the present application can be understood according to the specific circumstances.

[0038] With the rapid development of the new energy vehicle industry, battery technology has become the key to improving vehicle performance. In the entire supply chain, from battery cell production to vehicle assembly, each link directly affects the performance, safety and user experience of the final vehicle.

[0039] First of all, the production of battery cells is the basis of battery performance. Before the battery cells come off the production line, they need to go through a series of quality tests, including the evaluation of multiple key parameters such as electrochemical performance, internal resistance, capacity and safety. After passing all the tests, the battery cells enter the assembly stage, in which multiple battery cells are arranged and integrated into battery modules or battery packs.

[0040] After the battery pack is packaged, it needs to be transported to the vehicle manufacturer through a dedicated logistics channel. After arriving at the vehicle manufacturer, the battery pack enters the vehicle loading stage. During this process, the battery pack must match the electrical system and mechanical structure of the vehicle, and undergo necessary functional tests. Finally, the first charging test will be carried out after the vehicle is assembled.

[0041] However, when the vehicle is off the assembly line, inaccurate measurement of the health status of the battery pack may cause the subsequent battery management system (BMS) to generate cumulative errors when calculating the state of charge, which in turn has an adverse effect on the vehicle's range. SOH is a key indicator to measure the degree of battery performance degradation, which is directly related to the remaining capacity and discharge capacity of the battery. When there is a deviation in the SOH measurement, the BMS estimates the actual capacity of the battery inaccurately, resulting in a shift in the calculation basis of the SOC. Specifically, if the SOH is overestimated, the BMS may mistakenly believe that the available capacity of the battery is large, thereby underestimating the actual discharge of the battery, resulting in an overly high SOC display. This error will gradually accumulate with the increase of charge and discharge cycles, and eventually lead to a deviation in the vehicle's range prediction. The user may be misled into believing that the range is sufficient when the battery is about to run out of power, resulting in a sudden power outage during driving. On the contrary, if the SOH is underestimated, the SOC may be underestimated, causing the vehicle to enter the low-power protection mode prematurely when the actual remaining power is large, limiting the power output or prompting the user to charge, reducing the actual use efficiency of the vehicle. In addition, the accumulation of SOC errors will have a chain reaction on the overall control strategy of the BMS, further affecting the battery's thermal management and energy distribution efficiency, thereby exacerbating the instability of the cruising range.

[0042] In response to the above problems, the embodiment of the present application provides a health status determination scheme, which first obtains the cell voltage of each cell in the target battery pack when the cell is offline, the battery pack is offline, the vehicle is offline, and the first charging of the vehicle is completed; then obtains the duration information of the three stages from the cell offline to the battery pack offline, the battery pack offline to the vehicle offline, and the vehicle offline to the first charging of the vehicle; when the target battery pack is in a long-term storage state, the voltage change rate of each stage is determined based on multiple cell voltages and multiple duration information; based on the voltage change rate and the average health status obtained in advance, the target health status of the target battery pack when the vehicle is offline is determined. The technical solution of the embodiment of the present application first collects the cell voltage at different stages, covering the complete life cycle of the battery pack from production to vehicle assembly. This full-process monitoring enables the dynamic changes of the cell state to be fully recorded, so that the performance degradation of each stage can be accurately captured. In addition, the step of determining the voltage change rate in combination with the duration information can reveal the performance change trend of the battery pack at different stages. This method not only takes into account the static parameters of the cell, but also combines its actual performance in storage and use. By calculating the voltage change rate, the aging degree of the battery pack can be more scientifically reflected, thereby improving the accuracy of the prediction of the health status. Finally, by combining the voltage change rate with the pre-acquired average health status, a comprehensive assessment of the health status of the battery pack when the vehicle rolls off the production line is performed. This method not only takes into account the differences between individual cells, but also reduces the impact of single data point errors through multi-stage and multi-dimensional data analysis, thereby significantly improving the measurement accuracy of the battery pack health status.

[0043] The method for determining the battery health status provided in the embodiment of the present application can be applied to refer to Figure 1 In the application environment shown. The backend system 01 communicates with the battery management system 02. When the battery cell has not yet been integrated into the battery pack, the battery management system 02 cannot directly collect the voltage data of each battery cell. Therefore, when the battery cell is offline and ready for shipment, the barcode is scanned with a barcode scanner, and the actual battery cell capacity, rated capacity, battery cell voltage and number of each battery cell are recorded through the backend system 01. Before shipment, the backend system 01 counts the actual capacity of each battery cell and groups the batteries according to the consistency of the rated capacity or the capacity deviation within the range of +0.x%Ah.

[0044] The backend system 01 calculates the health status of each battery cell based on the actual battery cell capacity collected. If the calculation result is within the predetermined range (such as 100% to 100+x%), the battery pack is assembled. After the battery pack is assembled, the backend system 01 can send the actual battery cell capacity, rated capacity and battery cell voltage collected to the battery management system 02. It should be noted that in the two stages from the battery pack off-line to the vehicle off-line and from the vehicle off-line to the completion of the first charging of the vehicle, data information is obtained through the battery management system 02.

[0045] According to some embodiments of the present application, referring to Figure 2 A method for determining the health status of a battery is provided. Figure 1 The battery management system in the example can be used as an example to illustrate the following steps:

[0046] Step 201, respectively obtain the cell voltage of each cell in the target battery pack when the cell is offline, the battery pack is offline, the vehicle is offline, and the first charging of the vehicle is completed.

[0047] Among them, the cell voltage when the cell is off the line reflects the electrochemical performance of the cell in its initial state. The cell voltage when the battery pack is off the line reflects the voltage change of the cell during assembly and storage. The cell voltage when the vehicle is off the line reflects the impact of the battery pack storage process and the electrical system integration of the battery pack during vehicle loading on the cell voltage. The cell voltage when the vehicle is charged for the first time reflects the information on the changes in the electrochemical characteristics of the battery pack during the storage process and the first charging process.

[0048] After the battery cell production is completed and passed the inspection, the BMS re-obtains the cell voltage of each battery cell when it comes off the line from the background system. When multiple battery cells are integrated into the battery pack and the battery pack comes off the production line, the BMS directly obtains the voltage of each battery cell. When the whole vehicle is assembled and the whole vehicle comes off the line, the BMS further collects the cell voltage of each battery cell. When the first charge of the whole vehicle is completed, the BMS records the cell voltage of each battery cell.

[0049] Step 202, respectively obtain the duration information of the three stages: from the battery cell off the assembly line to the battery pack off the assembly line, from the battery pack off the assembly line to the vehicle off the assembly line, and from the vehicle off the assembly line to the completion of the first charging of the vehicle.

[0050] The time period from when the battery cell rolls off the production line to when the battery pack rolls off the production line reflects the time span of the battery cell during storage and transportation. The time period from when the battery pack rolls off the production line to when the vehicle rolls off the production line covers the time the battery pack spends during the vehicle production process. The time period from when the vehicle rolls off the production line to when the vehicle is charged for the first time reflects the storage and transportation time of the vehicle after assembly.

[0051] After the cell production is completed and passes the quality inspection, the BMS obtains the cell offline time. When the cell is assembled and integrated into a battery pack, the BMS obtains the battery pack offline time. When the battery pack is integrated into the vehicle and the vehicle is assembled and offline, the BMS obtains the vehicle offline time. When the first charge after the vehicle is offline is completed, the BMS obtains the vehicle first charge completion time.

[0052] BMS calculates the time from when the battery cell is offline to when the battery pack is offline by comparing the time when the battery cell is offline and the time when the battery pack is offline. BMS calculates the time from when the battery pack is offline to when the vehicle is offline by comparing the time when the battery pack is offline and the time when the vehicle is offline. BMS calculates the time from when the vehicle is offline to when the first charge is completed by comparing the time when the vehicle is offline and the time when the first charge is completed.

[0053] Step 203 : when the target battery pack is in a long-term storage state, determine the voltage change rate of each stage based on multiple cell voltages and multiple duration information.

[0054] The target battery pack is in a long-term storage state, which means that the target battery pack has not been used or charged or discharged for a long time. This state usually occurs after the battery pack is produced, but the battery pack is not put into use in time due to various reasons during transportation, storage or vehicle assembly. In the long-term storage state, the cells in the battery pack may experience a certain amount of self-discharge or performance changes, resulting in voltage drop or other changes in electrochemical characteristics.

[0055] In the embodiment of the present application, the target battery pack being in a long-term storage state means that the long-term storage time of the target battery pack is greater than or equal to 30 days.

[0056] When the target battery pack is in a long-term storage state, the pre-established cell aging model can be used to predict the voltage change rate of the cell by inputting the cell voltage and duration information of the current stage. The specific process is as follows: First, based on a large amount of historical cell voltage data, an aging model is constructed that can evaluate the voltage change trend of the cell under different storage time and usage conditions, and the relevant parameters are fitted through regression analysis or machine learning. Then, the currently collected cell voltage and the duration information from the cell offline to the current stage are input into the aging model, and the voltage change rate of each stage is determined using the established cell aging model.

[0057] Step 204 , based on the voltage change rate and the pre-acquired average health state, determine the target health state of the target battery pack when the vehicle rolls off the production line.

[0058] When the battery pack is offline, the barcode of the current battery pack is identified by a barcode scanner, and the number of cells that meet the current battery pack assembly requirements is matched from the background system. Subsequently, the background system writes the average health status of the battery pack into the battery management system through the controller area network (CAN) communication interface and the unified diagnostic services (UDS) protocol.

[0059] The battery management system compares the voltage change rate of each cell with the average health state obtained. By comparing the deviation of each cell from the average health state, cells with abnormal health states can be identified. Specifically, the battery management system calculates the voltage change rate of each cell and compares it with the reference value of the average health state. If the voltage change rate of a cell deviates significantly from the average, it indicates that there may be a problem with the health state of the cell.

[0060] Next, the battery management system quantifies the health state deviation based on the difference between the voltage change rate of each battery cell and the average health state. After obtaining the health state deviation of each battery cell, the battery management system integrates these health state deviations to calculate the target health state of the entire battery pack.

[0061] For example, the weighted average method is used for integration. First, the weight of each battery cell is determined according to its importance in the battery pack. The weight can be determined based on the position, performance or other relevant parameters of the battery cell in the battery pack; for example, batteries in the center or key positions may have higher weights because they have a greater impact on the overall performance of the battery pack.

[0062] Next, the health status of each battery cell is multiplied by the corresponding weight to obtain the weighted health status. Then, the weighted health status of all battery cells is added together and divided by the total weight to obtain the weighted average health status of the entire battery pack. The weighted average health status is the target health status of the target battery pack when the vehicle rolls off the production line.

[0063] In some embodiments, the method for obtaining the average health status may include: the BMS divides the cells in the battery pack into different groups according to certain characteristics of the cells (such as position, capacity, etc.). For example, the cells may be divided into "upper layer" and "lower layer" groups according to their physical positions, or the cells may be divided into "high capacity group" and "low capacity group" according to their capacities.

[0064] For each group of cells, calculate the average health status of the group. Integrate the health status of each group according to its importance or quantity to obtain the overall health status of the battery pack. Integration can use weighted average or simple average method. For example, suppose a battery pack is divided into two groups. Group A contains 4 cells with health status of 95%, 94%, 96%, and 93%, respectively. Group B contains 2 cells with health status of 90% and 91%, respectively.

[0065] The average health status of group A is:

[0066] (95+94+96+93) / 4=94.5%(95+94+96+93) / 4=94.5\%(95+94+96+93) / 4=94.5%.

[0067] Average health status of group B:

[0068] (90+91) / 2=90.5%(90+91) / 2=90.5\%(90+91) / 2=90.5%.

[0069] In the above embodiment, the cell voltage of each cell in the target battery pack is first obtained when the cell is offline, the battery pack is offline, the vehicle is offline, and the first charging of the vehicle is completed; then the duration information of the three stages from the cell offline to the battery pack offline, the battery pack offline to the vehicle offline, and the vehicle offline to the first charging of the vehicle is obtained; when the target battery pack is in a long-term storage state, the voltage change rate of each stage is determined based on multiple cell voltages and multiple duration information; based on the voltage change rate and the average health state obtained in advance, the target health state of the target battery pack when the vehicle is offline is determined. The technical solution of the embodiment of the present application first covers the complete life cycle of the battery pack from production to vehicle assembly by collecting cell voltages at different stages. This full-process monitoring enables the dynamic changes of the cell state to be fully recorded, so that the performance degradation of each stage can be accurately captured. In addition, the step of determining the voltage change rate in combination with the duration information can reveal the performance change trend of the battery pack at different stages. This method not only takes into account the static parameters of the cell, but also combines its actual performance in storage and use. By calculating the voltage change rate, the aging degree of the battery pack can be more scientifically reflected, thereby improving the accuracy of the prediction of the health status. Finally, by combining the voltage change rate with the pre-acquired average health status, a comprehensive assessment of the health status of the battery pack when the vehicle rolls off the production line is performed. This method not only takes into account the differences between individual cells, but also reduces the impact of single data point errors through multi-stage and multi-dimensional data analysis, thereby significantly improving the measurement accuracy of the battery pack health status.

[0070] According to some embodiments of the present application, referring to Figure 3In the above embodiment, “determining the target health state of the target battery pack when the vehicle is off the production line based on the voltage change rate and the pre-acquired average health state” may include the following steps:

[0071] Step 301 : determining a health status decay rate of a target battery pack based on a plurality of voltage change rates.

[0072] Among them, the health state decay rate indicates the speed at which the health state of the battery cell decreases.

[0073] In the three stages from the cell off-line to the battery pack off-line, from the battery pack off-line to the vehicle off-line, and from the vehicle off-line to the first charging of the vehicle, the weight proportion of each stage is inconsistent, so the normalization is introduced to eliminate the influence of factors with small weights on the entire nonlinear system. The health state decay rate can be calculated by formula (1).

[0074] (1)

[0075] in, is the health status decay rate, The actual voltage change rate from the cell off-line to the battery pack off-line stage, The actual voltage change rate from the battery pack off-line to the vehicle off-line stage, The actual voltage change rate from the time the vehicle is offline to the time the vehicle is charged for the first time. It is the rated voltage change rate from the cell off-line to the battery pack off-line stage, is the rated voltage change rate from the battery pack off-line to the vehicle off-line stage, It is the rated voltage change rate from the time the vehicle rolls off the production line to the time the vehicle is charged for the first time.

[0076] Step 302, based on the health state decay rate and the average health state, determine the target health state of the target battery pack when the vehicle rolls off the production line.

[0077] Based on the initial average health state, the health state decay rate is first applied to gradually adjust the health state to reflect the performance decay of the battery pack during use and storage. Subsequently, the health state decay effects of each stage are accumulated, and the target health state is continuously updated until the target health state when the vehicle rolls off the assembly line is obtained. Finally, the calculation results are verified and adjusted as needed so that the final target health state can accurately reflect the actual condition of the battery pack.

[0078] For example, assume that the initial average health state of an electric vehicle's battery pack is 95%. During production and transportation, the battery pack undergoes multiple stages of storage and use, and each stage causes a decline in health state. For example, during the storage process after the battery pack is assembled, the health state decays by 1%; during the vehicle production process, due to the aging of the battery cells and other factors, the health state decays by another 2%; during the testing process before the vehicle rolls off the assembly line, the health state decays further by 1%.

[0079] In this case, starting from the initial 95%, the health decay rate of each stage is applied. For example, after the first stage, the health status drops from 95% to 94%, after the second stage, the health status drops further to 92%, and in the final stage, the health status drops to 91%.

[0080] Finally, the health status is verified and necessary adjustments are made based on actual data so that the final target health status can accurately reflect the actual performance of the battery pack when the vehicle rolls off the production line. The final calculated target health status is 91%, which is recorded in the battery management system as a reference for subsequent maintenance and monitoring.

[0081] In the above embodiment, the health state decay rate of the target battery pack is first determined based on multiple voltage change rates; then, based on the health state decay rate and the average health state, the target health state of the target battery pack when the vehicle rolls off the production line is determined. The technical solution of the embodiment of the present application determines the health state decay rate through multiple voltage change rates, which can more comprehensively reflect the performance changes of the battery pack at different stages. By comprehensively considering multiple voltage change rates rather than relying on a single parameter, the evaluation deviation caused by measurement errors or abnormal data points can be reduced. This multi-dimensional data analysis method improves the stability and reliability of health state assessment.

[0082] According to some embodiments of the present application, in the above embodiment, “determining the target health state of the target battery pack when the vehicle is off the production line based on the health state decay rate and the average health state” may include the following situations:

[0083] Case 1: When the health state decay rate is not greater than the preset decay rate threshold, the average health state is determined as the target health state of the target battery pack when the vehicle rolls off the production line.

[0084] The preset attenuation rate threshold may be set to 0.1.

[0085] When the health state decay rate is not greater than the preset decay rate threshold, the average health state is determined as the target health state of the target battery pack when the vehicle is off the production line. The process of calculating the target health state is shown in formula (2).

[0086] (2)

[0087] in, The target health state is Average health status.

[0088] Case 2: When the health state decay rate is greater than the preset decay rate threshold, the health state decay rate and the average health state are substituted into the preset relationship for calculation to obtain the target health state of the target battery pack when the vehicle rolls off the production line.

[0089] When the health state decay rate is greater than the preset decay rate threshold, the health state decay rate and the average health state are substituted into the preset relationship for calculation to obtain the target health state of the target battery pack when the vehicle rolls off the production line. The process of calculating the target health state is shown in formula (3).

[0090] (3)

[0091] in, The target health state is For average health status, is the health status decay rate, The actual health status.

[0092] In the above embodiment, when the health state decay rate is not greater than the preset decay rate threshold, the average health state is determined as the target health state of the target battery pack when the vehicle rolls off the production line; when the health state decay rate is greater than the preset decay rate threshold, the health state decay rate and the average health state are substituted into the preset relationship for calculation to obtain the target health state of the target battery pack when the vehicle rolls off the production line. The technical solution of the embodiment of the present application can distinguish the treatment methods of battery packs at different degrees of decay by setting a threshold for the health state decay rate. When the health state decay rate is small, the average health state is directly used to reduce the error accumulation caused by the complex calculation process. When the decay rate is large, the target health state adjusted by the relationship can more truly reflect the actual situation of the battery pack and improve the credibility of the evaluation results.

[0093] According to some embodiments of the present application, in the above embodiment, “when the target battery pack is in a long-term storage state, based on multiple cell voltages and multiple duration information, determining the voltage change rate in each stage” may include the following situations:

[0094] Case 1: For each battery cell, the voltage change rate from the battery cell offline to the battery pack offline is determined based on the battery cell voltage when the battery cell is offline, the battery cell voltage when the battery pack is offline, and the duration information from the battery cell offline to the battery pack offline.

[0095] For each battery cell, the voltage change rate from the battery cell offline to the battery pack offline is determined based on the battery cell voltage when the battery cell is offline, the battery cell voltage when the battery pack is offline, and the duration information from the battery cell offline to the battery pack offline. The process of determining the voltage change rate from the battery cell offline to the battery pack offline is shown in formula (4).

[0096] (4)

[0097] in, is the voltage change rate from the cell off-line to the battery pack off-line stage, is the cell voltage when the cell is offline, is the cell voltage when the battery pack is offline, It is the duration from the battery cell offline to the battery pack offline, and n is the number of battery cells in the battery pack.

[0098] Case 2: Based on the cell voltage when the battery pack is offline, the cell voltage when the vehicle is offline, and the duration information from the battery pack being offline to the vehicle being offline, determine the voltage change rate from the battery pack being offline to the vehicle being offline.

[0099] Based on the cell voltage when the battery pack is offline, the cell voltage when the vehicle is offline, and the duration from the battery pack offline to the vehicle offline, the voltage change rate from the battery pack offline to the vehicle offline is determined. The process of determining the voltage change rate from the battery pack offline to the vehicle offline is shown in formula (5).

[0100] (5)

[0101] in, is the voltage change rate from the battery pack off-line to the vehicle off-line stage, is the cell voltage when the battery pack is offline, is the cell voltage when the vehicle is off the line, It is the time from when the battery pack is offline to when the vehicle is offline, and n is the number of cells in the battery pack.

[0102] Case three: Based on the cell voltage when the vehicle rolls off the production line, the cell voltage when the vehicle is charged for the first time, and the duration from the time the vehicle rolls off the production line to the completion of the first charging of the vehicle, determine the voltage change rate from the time the vehicle rolls off the production line to the time the vehicle is charged for the first time.

[0103] Based on the cell voltage when the vehicle is offline, the cell voltage when the vehicle is charged for the first time, and the duration from the vehicle being offline to the completion of the first charging of the vehicle, the voltage change rate from the vehicle being offline to the first charging of the vehicle is determined. The process of determining the voltage change rate from the vehicle being offline to the first charging of the vehicle is shown in formula (6).

[0104] (6)

[0105] in, The voltage change rate from the vehicle off the assembly line to the first charging stage of the vehicle, The cell voltage when the vehicle is charged for the first time. is the cell voltage when the vehicle is off the line, It is the time from the vehicle rolling off the production line to the completion of the first charging of the vehicle, and n is the number of cells in the battery pack.

[0106] In the above embodiment, for each battery cell, the voltage change rate from the battery cell offline to the battery pack offline stage is determined based on the battery cell voltage when the battery cell is offline, the battery cell voltage when the battery pack is offline, and the duration information from the battery cell offline to the battery pack offline stage; the voltage change rate from the battery pack offline to the vehicle offline stage is determined based on the battery cell voltage when the battery pack is offline, the battery cell voltage when the vehicle is offline, and the duration information from the battery pack offline to the vehicle offline stage; the voltage change rate from the vehicle offline to the vehicle first charging stage is determined based on the battery cell voltage when the vehicle is offline, the battery cell voltage when the vehicle is first charged, and the duration information from the vehicle offline to the vehicle first charging stage. The technical solution of the embodiment of the present application realizes full monitoring of the battery cell throughout its entire life cycle by respectively calculating the voltage change rate of the battery cell from offline to battery pack offline, from battery pack offline to vehicle offline, and from vehicle offline to the first charging stage. This staged voltage change rate calculation can fully reflect the performance degradation of the battery cell under different environments and usage conditions.

[0107] According to some embodiments of the present application, referring to Figure 4 , the above method may further include the following steps:

[0108] Step 401, when the target battery pack is in a non-long-term storage state, obtain the actual cell capacity of each cell in the target battery pack when the whole vehicle is offline.

[0109] Among them, the target battery pack is in a non-long-term storage state, which means that the battery pack has gone through various production and testing stages in a short period of time and has not been stored or idle for a long time. In other words, the entire process of the battery pack from production and assembly to the end of the vehicle production line is relatively compact, and there is no significant change in the performance of the battery cell due to long-term storage.

[0110] When the target battery pack is in a non-long-term storage state, the BMS obtains the actual cell capacity of each cell in the target battery pack when the vehicle is offline.

[0111] Step 402, based on the actual cell capacity and the pre-acquired rated capacity and number of cells, determine the target health state of the vehicle when it is off the production line.

[0112] The battery management system uses the actual cell capacity of each battery cell, the pre-acquired rated capacity, and the number of cells to determine the target health state of the vehicle when it rolls off the production line.

[0113] For example, assume that the actual cell capacity of the battery cell is 92Ah, the rated capacity is 100Ah, and the total number of battery cells is 100. Next, the BMS compares the actual cell capacity of each battery cell with its rated capacity and calculates the health status of each battery cell. For example, the health status of each battery cell can be expressed as the ratio of the actual capacity to the rated capacity, that is, 92Ah / 100Ah=92%. The BMS then summarizes the health status of all battery cells and uses a weighted average method to consider the different importance of the battery cells in the battery pack. Specifically, the BMS assigns a weight to each battery cell based on factors such as the specific location and performance of the battery cell, and multiplies the health status of each battery cell by its weight to calculate the weighted health status. Finally, by summing all weighted health statuses and dividing them by the total weight, the target health status of the vehicle when it rolls off the assembly line can be obtained.

[0114] In the above embodiment, when the target battery pack is in a non-long-term storage state, the actual cell capacity of each cell in the target battery pack is obtained when the whole vehicle is offline; based on the actual cell capacity and the rated capacity and number of cells acquired in advance, the target health state when the whole vehicle is offline is determined. The technical solution of the embodiment of the present application, due to the small attenuation of cell performance in a non-long-term storage state, the evaluation result is closer to the actual health state of the battery pack. By comparing the actual capacity with the rated capacity, the current state of the cell can be more directly reflected, reducing the impact of uncertainties caused by long-term storage or idleness on the health state assessment.

[0115] According to some embodiments of the present application, referring to Figure 5 In the above embodiment, “determining the target health state of the vehicle when it is off the production line based on the actual cell capacity and the pre-acquired rated capacity and number of cells” may include the following steps:

[0116] Step 501, determining the health state attenuation based on the actual cell capacity, the rated capacity and the number of cells.

[0117] Based on the actual cell capacity, rated capacity and number of cells, the process of determining the health state attenuation is shown in formula (7).

[0118]

[0119] 100%*AHe<=AHn<=(100+x%)*AHe (7)

[0120] in, is the actual cell capacity, is the rated capacity, n and NUM are the number of cells, is the health status decay.

[0121] Step 502: Determine a target health state based on the health state attenuation.

[0122] Based on the health state attenuation, the process of determining the target health state is shown in formula (8).

[0123] (8)

[0124] in, Target health status.

[0125] In the above embodiment, the health state decay amount is determined based on the actual battery cell capacity, the rated capacity and the number of battery cells; and the target health state is determined based on the health state decay amount. The technical solution of the embodiment of the present application can effectively capture the actual changes in the performance of the battery cell during use by determining the health state decay amount based on the actual battery cell capacity, the rated capacity and the number of battery cells.

[0126] According to some embodiments of the present application, the method may further include the following steps:

[0127] The target health state is corrected to obtain a corrected target health state.

[0128] The battery management system analyzes the main factors that affect the health status of the battery cell, including manufacturing differences, aging speed, and storage conditions. Based on these analysis results, the battery management system uses a pre-established correction model to predict the correction value of the target health status. The correction model determines the corresponding correction factor by analyzing the collected data and known influencing factors.

[0129] Next, these correction factors are applied to the target health state to adjust the target health state to obtain a corrected target health state. After the correction is completed, the corrected target health state is verified and calibrated. If deviations are found, the correction model is further optimized.

[0130] For example, when the battery pack is rolled off the assembly line, the BMS detects that a group of cells in the battery pack is aging faster than other cells. By analyzing historical data, the BMS identifies the cause of this problem as being closer to a high temperature source than other cells in the battery pack, which accelerates the degradation of the health of the cells.

[0131] Based on this, the correction model will take this influencing factor into account and generate the corresponding correction factor, adjusting the target health status from 90% to a more accurate 85%. At the same time, the BMS will compare this corrected target health status with the target health status before correction to verify the validity of the correction value.

[0132] In the above embodiment, the target health state is corrected to obtain the corrected target health state. The technical solution of the embodiment of the present application, through correction processing, makes the target health state value closer to the actual state of the target battery pack when the vehicle is off the production line, reducing the error accumulation caused by initial setting deviation or external environmental factors.

[0133] According to some embodiments of the present application, a method for determining a battery health state is provided, wherein the method is applied to Figure 1 The battery management system in the example can be used as an example to illustrate the following steps:

[0134] Step 1, respectively obtain the cell voltage of each cell in the target battery pack when the cell is offline, the battery pack is offline, the vehicle is offline, and the first charging of the vehicle is completed.

[0135] Step 2, respectively obtain the duration information of the three stages: from the battery cell off-line to the battery pack off-line, from the battery pack off-line to the vehicle off-line, and from the vehicle off-line to the completion of the first charging of the vehicle.

[0136] Step 3, when the target battery pack is in a long-term storage state, for each battery cell, based on the cell voltage when the battery cell is offline, the cell voltage when the battery pack is offline, and the duration information from the battery cell offline to the battery pack offline, determine the voltage change rate from the battery pack offline to the vehicle offline stage based on the cell voltage when the battery pack is offline, the cell voltage when the vehicle is offline, and the duration information from the battery pack offline to the vehicle offline stage; based on the cell voltage when the vehicle is offline, the cell voltage when the vehicle is offline, and the duration information from the battery pack offline to the vehicle offline stage, determine the voltage change rate from the vehicle offline to the vehicle offline stage; based on the cell voltage when the vehicle is offline, the cell voltage when the vehicle is charged for the first time, and the duration information from the vehicle offline to the completion of the first charging of the vehicle, determine the voltage change rate from the vehicle offline to the vehicle first charging stage.

[0137] Step 4: determine the health status decay rate of the target battery pack based on multiple voltage change rates.

[0138] Step 5: When the health state decay rate is not greater than the preset decay rate threshold, the average health state is determined as the target health state of the target battery pack when the vehicle rolls off the production line.

[0139] Step 6, when the health state decay rate is greater than the preset decay rate threshold, the health state decay rate and the average health state are substituted into the preset relationship for calculation to obtain the target health state of the target battery pack when the vehicle rolls off the production line.

[0140] Step 7: When the target battery pack is in a non-long-term storage state, obtain the actual cell capacity of each cell in the target battery pack when the vehicle is offline.

[0141] Step 8: Determine the health state attenuation based on the actual cell capacity, rated capacity and number of cells.

[0142] Step 9: Determine the target health state based on the health state attenuation.

[0143] Step 10, correcting the target health state to obtain a corrected target health state.

[0144] It should be noted that in the embodiment of the present application, the execution order of step 1 and step 2 is not limited. In the actual execution process, step 2 can be executed first and then step 1, or step 1 and step 2 can be executed in parallel.

[0145] In addition, in the actual execution process, it is necessary to execute corresponding steps according to the state of the target battery pack. When the target battery pack is in a long-term storage state, execute steps 3 to 6; when the target battery pack is in a non-long-term storage state, execute steps 7 to 9.

[0146] In the above embodiment, the cell voltage of each cell in the target battery pack is first obtained when the cell is offline, the battery pack is offline, the vehicle is offline, and the first charging of the vehicle is completed; then the duration information of the three stages from the cell offline to the battery pack offline, the battery pack offline to the vehicle offline, and the vehicle offline to the first charging of the vehicle is obtained; when the target battery pack is in a long-term storage state, the voltage change rate of each stage is determined based on multiple cell voltages and multiple duration information; based on the voltage change rate and the average health state obtained in advance, the target health state of the target battery pack when the vehicle is offline is determined. The technical solution of the embodiment of the present application first covers the complete life cycle of the battery pack from production to vehicle assembly by collecting cell voltages at different stages. This full-process monitoring enables the dynamic changes of the cell state to be fully recorded, so that the performance degradation of each stage can be accurately captured. In addition, the step of determining the voltage change rate in combination with the duration information can reveal the performance change trend of the battery pack at different stages. This method not only takes into account the static parameters of the cell, but also combines its actual performance in storage and use. By calculating the voltage change rate, the aging degree of the battery pack can be more scientifically reflected, thereby improving the accuracy of the prediction of the health status. Finally, by combining the voltage change rate with the pre-acquired average health status, a comprehensive assessment of the health status of the battery pack when the vehicle rolls off the production line is performed. This method not only takes into account the differences between individual cells, but also reduces the impact of single data point errors through multi-stage and multi-dimensional data analysis, thereby significantly improving the measurement accuracy of the battery pack health status.

[0147] It should be understood that, although the various steps in the above-mentioned flow chart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the above-mentioned flow chart may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0148] Based on the same inventive concept, the embodiment of the present application also provides a device for determining the battery health state for implementing the method for determining the battery health state involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiments of one or more device for determining the battery health state provided below can refer to the limitations of the method for determining the battery health state above, and will not be repeated here.

[0149] According to some embodiments of the present application, referring to Figure 6 , provides a device for determining a battery health state, the device comprising:

[0150] The cell voltage acquisition module 601 is used to respectively acquire the cell voltage of each cell in the target battery pack when the cell is offline, the battery pack is offline, the vehicle is offline, and the first charging of the vehicle is completed.

[0151] The duration information acquisition module 602 is used to respectively acquire the duration information of three stages: from the battery cell off-line to the battery pack off-line, from the battery pack off-line to the vehicle off-line, and from the vehicle off-line to the completion of the first charging of the vehicle.

[0152] The voltage change rate determination module 603 is used to determine the voltage change rate of each stage based on multiple cell voltages and multiple duration information when the target battery pack is in a long-term storage state.

[0153] The first health state determination module 604 is used to determine the target health state of the target battery pack when the vehicle is offline based on the voltage change rate and the pre-acquired average health state.

[0154] In some embodiments, the first health status determination module 604 is specifically used to determine the health status decay rate of the target battery pack based on multiple voltage change rates; based on the health status decay rate and the average health status, determine the target health status of the target battery pack when the vehicle rolls off the production line.

[0155] In some embodiments, the first health status determination module 604 is specifically used to determine the average health status as the target health status of the target battery pack when the vehicle rolls off the production line when the health status decay rate is not greater than a preset decay rate threshold; when the health status decay rate is greater than a preset decay rate threshold, the health status decay rate and the average health status are substituted into a preset relationship for calculation to obtain the target health status of the target battery pack when the vehicle rolls off the production line.

[0156] In some embodiments, the voltage change rate determination module 603 is specifically used to determine, for each battery cell, the voltage change rate from the battery cell off-line to the battery pack off-line stage based on the battery cell voltage when the battery cell is off-line, the battery cell voltage when the battery pack is off-line, and the duration information from the battery cell off-line to the battery pack off-line stage; determine the voltage change rate from the battery pack off-line to the vehicle off-line stage based on the battery cell voltage when the battery pack is off-line, the battery cell voltage when the vehicle is off-line, and the duration information from the battery pack off-line to the vehicle off-line stage; determine the voltage change rate from the vehicle off-line to the first charging stage based on the battery cell voltage when the vehicle is off-line, the battery cell voltage when the vehicle is charged for the first time, and the duration information from the vehicle off-line to the completion of the first charging of the vehicle.

[0157] In some embodiments, Figure 7 As shown, the above device also includes:

[0158] The cell capacity acquisition module 605 is used to acquire the actual cell capacity of each cell in the target battery pack when the vehicle is offline when the target battery pack is in a non-long-term storage state;

[0159] The second health state determination module 606 is used to determine the target health state of the vehicle when it is offline based on the actual cell capacity and the pre-acquired rated capacity and number of cells.

[0160] In some embodiments, the second health status determination module 606 is specifically used to determine the health status attenuation based on the actual battery cell capacity, the rated capacity and the number of battery cells; and determine the target health status based on the health status attenuation.

[0161] Each module in the above-mentioned battery health status determination device can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in an electronic device in the form of hardware, or can be stored in a memory in an electronic device in the form of software, so that the processor can call and execute operations corresponding to each of the above modules.

[0162] In some embodiments, Figure 8 As shown, the above device also includes:

[0163] The correction module 607 is used to correct the target health state to obtain a corrected target health state.

[0164] According to some embodiments of the present application, an electronic device is provided. The electronic device may be a battery management system, and its internal structure diagram may be as follows: Fig. 9 As shown. The electronic device includes a processor, a memory, an input / output interface, and a communication interface. The processor, the memory, and the input / output interface are connected via a system bus, and the communication interface, the display unit, and the input device are connected to the system bus via the input / output interface. The processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the electronic device is used to exchange information between the processor and an external device. The communication interface of the electronic device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a method for determining a battery health state is implemented.

[0165] Those skilled in the art will understand that Fig. 9 The structure shown in the figure is merely a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the electronic device to which the scheme of the present application is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0166] According to some embodiments of the present application, there is also provided a non-transitory computer-readable storage medium including instructions, such as a memory including instructions, and the above instructions can be executed by a processor of an electronic device to complete the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0167] According to some embodiments of the present application, a computer program product is also provided, and when the computer program is executed by a processor, the above method can be implemented. The computer program product includes one or more computer instructions. When these computer instructions are loaded and executed on a computer, part or all of the above method can be implemented in whole or in part according to the process or function described in the embodiment of the present application.

[0168] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0169] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0170] The above-described embodiments only express several implementation methods of the present application, which is convenient for understanding the technical solutions of the present application in detail, but cannot be understood as limiting the scope of protection of the invention patent. It should be pointed out that for ordinary technicians in this field, without departing from the concept of the present application, several modifications and improvements can be made, which all belong to the protection scope of the present application. It should be understood that the technical solutions obtained by those skilled in the art through logical analysis, reasoning or limited experiments on the basis of the technical solutions provided in the present application are all within the protection scope of the attached claims described in the present application. Therefore, the protection scope of the patent of this application shall be based on the contents of the attached claims, and the description and drawings can be used to explain the contents of the claims.

Claims

1. A method for determining a battery health status, characterized in that: The method comprises: Obtain the cell voltage of each cell in the target battery pack when the cell is offline, the battery pack is offline, the vehicle is offline, and the vehicle is charged for the first time; Obtain the duration information of the three stages: from the battery cell off-line to the battery pack off-line, from the battery pack off-line to the vehicle off-line, and from the vehicle off-line to the completion of the first charging of the vehicle; When the target battery pack is in a long-term storage state, determining a voltage change rate in each stage based on a plurality of cell voltages and a plurality of duration information; Determining a target health state of the target battery pack when the vehicle is off the production line based on the voltage change rate and the pre-acquired average health state; The determining, based on the voltage change rate and the pre-acquired average health state, the target health state of the target battery pack when the vehicle is off the production line includes: Determining a health state decay rate of the target battery pack based on a plurality of the voltage change rates; Based on the health state decay rate and the average health state, the target health state of the target battery pack when the vehicle rolls off the production line is determined.

2. The method according to claim 1, characterized in that The determining, based on the health state decay rate and the average health state, the target health state of the target battery pack when the vehicle is off the production line includes: When the health state decay rate is not greater than a preset decay rate threshold, the average health state is determined as the target health state of the target battery pack when the vehicle is offline; When the health state decay rate is greater than the preset decay rate threshold, the health state decay rate and the average health state are substituted into a preset relationship for calculation to obtain the target health state of the target battery pack when the vehicle rolls off the production line.

3. The method according to claim 1, characterized in that: The determining the voltage change rate of each stage based on the plurality of cell voltages and the plurality of duration information includes: For each battery cell, based on the battery cell voltage when the battery cell is offline, the battery cell voltage when the battery pack is offline, and the duration information from the battery cell offline to the battery pack offline, determine the voltage change rate from the battery cell offline to the battery pack offline stage; Determine the voltage change rate from the battery pack offline to the vehicle offline stage based on the cell voltage when the battery pack is offline, the cell voltage when the vehicle is offline, and the duration information from the battery pack offline to the vehicle offline stage; Based on the cell voltage when the vehicle is offline, the cell voltage when the vehicle is charged for the first time, and the duration from the vehicle being offline to the completion of the first charging of the vehicle, the voltage change rate from the vehicle being offline to the first charging of the vehicle is determined.

4. The method according to any one of claims 1 to 3, characterized in that: The method further comprises: When the target battery pack is in a non-long-term storage state, obtaining the actual cell capacity of each cell in the target battery pack when the vehicle is offline; Based on the actual cell capacity and the pre-acquired rated capacity and number of cells, a target health state of the vehicle when it rolls off the production line is determined.

5. The method according to claim 4, characterized in that The determining the target health state of the vehicle when it is off the production line based on the actual cell capacity and the pre-acquired rated capacity and the number of cells includes: Determining a health state decay amount based on the actual battery cell capacity, the rated capacity, and the number of battery cells; The target health state is determined based on the health state decay amount.

6. The method according to claim 1, characterized in that The method further comprises: The target health state is corrected to obtain a corrected target health state.

7. A device for determining a battery health status, characterized in that: The device comprises: A cell voltage acquisition module is used to obtain the cell voltage of each cell in the target battery pack when the cell is offline, the battery pack is offline, the vehicle is offline, and the vehicle is charged for the first time; The duration information acquisition module is used to respectively acquire the duration information of the three stages from the battery cell off-line to the battery pack off-line, from the battery pack off-line to the vehicle off-line, and from the vehicle off-line to the completion of the first charging of the vehicle; A voltage change rate determination module, configured to determine the voltage change rate of each stage based on the plurality of cell voltages and the plurality of duration information when the target battery pack is in a long-term storage state; A first health state determination module, used to determine a target health state of the target battery pack when the vehicle is offline based on the voltage change rate and the pre-acquired average health state; The first health status determination module is specifically used to determine the health status decay rate of the target battery pack based on the multiple voltage change rates; based on the health status decay rate and the average health status, determine the target health status of the target battery pack when the vehicle rolls off the production line.

8. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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