Battery management method and device, computer device, storage medium and program product

Abstract

The application relates to a battery management method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: obtaining a first charge state value, a second charge state value, a first charge state value change amount, a first theoretical ampere-hour change amount, a first actual ampere-hour change amount, and a working condition identifier of a vehicle battery pack. The first charge state value is a charge state value of the battery pack in a first time period, and the first time period is later than a second time period. Based on the first charge state value, the second charge state value, the first charge state value change amount, the first theoretical ampere-hour change amount, the first actual ampere-hour change amount, and the working condition identifier of the vehicle, an abnormality detection result of the battery pack is determined. The abnormality detection result comprises at least one of charge state data abnormality, charge state deviation, and charge state jump. Abnormality detection early warning information is sent based on the abnormality detection result.

Description

Technical Field

[0001] This application relates to the field of new energy vehicle battery technology, and in particular to a battery management method, device, computer equipment, storage medium, and program product. Background Technology

[0002] With the rapid development of new energy vehicles, lithium batteries are being used more and more widely. However, the electrochemical characteristics of lithium batteries are complex and affected by many factors such as temperature and charge / discharge rate. Therefore, the State of Charge (SOC) does not exhibit a simple linear relationship with the actual voltage, increasing the difficulty of accurately estimating SOC. An incorrect SOC may cause the battery management system to fail to accurately detect the battery status, leading to overcharging and over-discharging, or even serious safety hazards such as battery failure and thermal runaway, threatening the lives of people inside the vehicle and in the surrounding area. Therefore, accurately identifying SOC jumps and deviations in lithium batteries is crucial.

[0003] In related technologies, the server obtains vehicle data uploaded by the vehicle terminal, extracts key parameters such as mileage, temperature, time, and SOC value from the vehicle data, calculates the time difference and SOC difference between two adjacent frames of data according to the vehicle's operating conditions, and determines whether an anomaly has occurred by the ratio of the SOC change rate to the time difference.

[0004] However, the above-mentioned methods for identifying SOC anomalies are relatively simple, resulting in low accuracy in judging SOC anomalies and poor battery management performance. Summary of the Invention

[0005] This application provides a battery management method, apparatus, computer device, storage medium, and program product, which can improve battery management performance. The technical solution is as follows:

[0006] On one hand, a battery management method is provided, the method comprising:

[0007] The system acquires the first state of charge (SOC) value, second SOC value, change in the first SOC value, change in the first theoretical ampere-hour (Ah) count, change in the first actual Ah count, and the vehicle's operating condition indicator for the battery pack. The first SOC value is the SOC value of the battery pack within a first time period, the second SOC value is the SOC value of the battery pack within a second time period, the first time period is later than the second time period, the change in the first SOC value is the change in the SOC value of the battery pack within the first time period, the change in the first theoretical Ah count is the change in the theoretical Ah count of the battery pack within the first time period, the change in the first actual Ah count is the change in the actual Ah count of the battery pack within the first time period, and the vehicle's operating condition indicator is used to indicate the operating condition of the vehicle, which includes charging condition and driving condition.

[0008] Based on the first charge state value, the second charge state value, the change in the first charge state value, the change in the first theoretical ampere-hours, the change in the first actual ampere-hours, and the vehicle's operating condition indicator, the abnormal detection result of the battery pack is determined. The abnormal detection result includes at least one of abnormal charge state data, charge state deviation, and charge state jump.

[0009] Anomaly detection warning information is sent based on the anomaly detection results.

[0010] On the other hand, a battery management device is provided, the device comprising:

[0011] The parameter acquisition module is used to acquire the first state of charge value, second state of charge value, change in the first state of charge value, change in the first theoretical ampere-hour (Ah) count, change in the first actual Ah-hour (Ah) count, and the vehicle's operating condition indicator for the vehicle's battery pack. The first state of charge value is the state of charge value of the battery pack in a first time period, the second state of charge value is the state of charge value of the battery pack in a second time period, the first time period is later than the second time period, the change in the first state of charge value is the change in the state of charge value of the battery pack in the first time period, the change in the first theoretical Ah-hour (Ah) count is the change in the theoretical Ah-hour (Ah) count of the battery pack in the first time period, the change in the first actual Ah-hour (Ah) count is the change in the actual Ah-hour (Ah) count of the battery pack in the first time period, and the vehicle's operating condition indicator is used to indicate the operating condition of the vehicle, which includes charging condition and driving condition.

[0012] The detection result determination module is used to determine the abnormal detection result of the battery pack based on the first charge state value, the second charge state value, the change in the first charge state value, the change in the first theoretical ampere-hours, the change in the first actual ampere-hours, and the operating condition indicator of the vehicle. The abnormal detection result includes at least one of charge state data abnormality, charge state deviation, and charge state jump.

[0013] The early warning information sending module is used to send anomaly detection early warning information based on the anomaly detection results.

[0014] In one possible implementation, the detection result determination module is used for,

[0015] When the vehicle's operating condition indicator indicates that the vehicle is in the charging condition, and the first state of charge value is less than the second state of charge value, it is determined that the abnormal detection result of the battery pack includes abnormal state of charge data.

[0016] When the vehicle's operating condition indicator indicates that the vehicle is in the driving condition, and the first charge state value is greater than the second charge state value, it is determined that the abnormal detection result of the battery pack includes abnormal charge state data.

[0017] In one possible implementation, the detection result determination module is used for,

[0018] When the change in the first charge state value is not less than the first charge state value change threshold, and the ratio between the first actual ampere-hour change and the first theoretical ampere-hour change is not less than the proportional threshold, the abnormal detection result of the battery pack is determined to include charge state deviation.

[0019] In one possible implementation, the detection result determination module is used for,

[0020] When the change in the first charge state value is not less than the threshold of the change in the second charge state value, the abnormal detection result of the battery pack is determined to include a charge state jump.

[0021] In one possible implementation, the warning information sending module is used to:

[0022] Obtain the warning level of the anomaly detection results;

[0023] Based on the aforementioned warning level, the anomaly detection warning information is sent.

[0024] In one possible implementation, if the anomaly detection result includes anomalies in the charge state data, the warning level is determined by the difference between the first charge state value and the second charge state value.

[0025] When the abnormal detection result includes the charge state deviation, the warning level is determined by the change in the first charge state value and the ratio between the change in the first actual ampere-hours and the change in the first theoretical ampere-hours.

[0026] If the abnormal detection result includes the charge state jump, the warning level is determined by the amount of change in the first charge state value.

[0027] In another aspect, a computer device is provided, the computer device comprising a processor and a memory, the memory storing at least one instruction, at least one program, code set or instruction set, the at least one instruction, the at least one program, the code set or instruction set being loaded and executed by the processor to implement the battery management method as described above.

[0028] In another aspect, a computer-readable storage medium is provided, wherein at least one instruction, at least one program, code set, or instruction set is stored therein, wherein the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by a processor to implement the battery management method described above.

[0029] In another aspect, a computer program product is provided, comprising a computer program stored in a computer-readable storage medium. A processor of a computer device reads the computer program from the computer-readable storage medium and executes the computer program, causing the computer device to perform the battery management methods provided in the various alternative implementations described above.

[0030] The technical solution provided in this application may include the following beneficial effects:

[0031] The server acquires data on the vehicle's battery pack and vehicle operating conditions. It extracts data from different time periods from this data and combines it with three factors: time information, battery pack data, and vehicle operating conditions. Based on the actual application scenario of the battery pack and its status at different times, the server can more comprehensively determine the results of battery pack anomaly detection, effectively improving the accuracy of anomaly detection and thus improving the overall battery management effect.

[0032] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0033] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0034] Figure 1 This is a system configuration diagram of a battery management method according to one embodiment of this application;

[0035] Figure 2 This is a flowchart of a battery management method provided in one embodiment of this application;

[0036] Figure 3 This is a flowchart of a battery management method provided in one embodiment of this application;

[0037] Figure 4 This is a flowchart of a data processing method provided in one embodiment of this application;

[0038] Figure 5 This is a block diagram of a battery management device provided in an exemplary embodiment of this application;

[0039] Figure 6 This is a schematic diagram of the structure of a computer device provided in an exemplary embodiment of this application. Detailed Implementation

[0040] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0041] Figure 1 This is a system configuration diagram of a battery management method according to one embodiment of this application. Figure 1 As shown, the system includes a vehicle 120 and a cloud server 130 corresponding to the vehicle 120.

[0042] The cloud server 130 corresponding to vehicle 120 can be a single cloud server, or a combination of several cloud servers, or a virtualization platform, or a cloud computing service center.

[0043] The vehicle 120 and the cloud server 130 can be connected via a communication network. Optionally, this communication network can be a wired network or a wireless network.

[0044] Optionally, the aforementioned wireless or wired networks use standard communication technologies and / or protocols. The network is typically the Internet, but can also be any network, including but not limited to Local Area Networks (LANs), Metropolitan Area Networks (MANs), Wide Area Networks (WANs), mobile, wired or wireless networks, private networks, or any combination of virtual private networks. In some embodiments, technologies and / or formats including Hyper Text Markup Language (HTML), Extensible Markup Language (XML), etc., are used to represent data exchanged over the network. Furthermore, conventional encryption technologies such as Secure Socket Layer (SSL), Transport Layer Security (TLS), Virtual Private Networks (VPNs), and Internet Protocol Security (IPsec) can be used to encrypt all or some links. In other embodiments, custom and / or dedicated data communication technologies can be used to replace or supplement the aforementioned data communication technologies.

[0045] exist Figure 1 In the system shown, the vehicle 120 can provide vehicle data for various time periods to the cloud server 130. The cloud server 130 performs anomaly detection on the vehicle 120 based on the received vehicle data, and after determining the anomaly detection result, sends anomaly detection warning information to the vehicle 120 based on the anomaly detection result.

[0046] Specifically, the vehicle 120 collects in real time the battery pack's first state of charge (SOC), second SOC, change in the first SOC, change in the first theoretical ampere-hours (Ah), change in the first actual Ah, and the vehicle's operating condition indicator. The first SOC is the battery pack's SOC within a first time period, the second SOC within a second time period (the first time period is later than the second time period), the change in the first SOC is the change in the battery pack's SOC within the first time period, the change in the first theoretical Ah is the change in the battery pack's theoretical Ah within the first time period, the change in the first actual Ah is the change in the battery pack's actual Ah within the first time period, and the vehicle's operating condition indicator indicates the vehicle's current operating condition. The vehicle's operating conditions include charging and driving conditions, and the collected data is synchronously uploaded to the cloud server 130. After acquiring the first state of charge value, second state of charge value, change in first state of charge value, change in first theoretical ampere-hours, change in first actual ampere-hours, and the vehicle's operating condition identifier, the cloud server 130 determines the abnormal detection results of the battery pack based on the first state of charge value, second state of charge value, change in first state of charge value, change in first theoretical ampere-hours, change in first actual ampere-hours, and the vehicle's operating condition identifier. The abnormal detection results include at least one of abnormal state of charge data, state of charge deviation, and state of charge jump. Based on the abnormal detection results, an abnormal detection warning message is sent to the vehicle 120.

[0047] Figure 2 This is a flowchart of a battery management method provided in one embodiment of this application. The battery management method may include steps 210, 220, and 230. This method can be executed by a server corresponding to the vehicle, and the vehicle may be... Figure 1 Vehicle 120 in the middle, the server can be Figure 1 The specific implementation process of this method is as follows, using server 130 in the example.

[0048] Step 210: Obtain the first state of charge (SOC) value, second SOC value, change in the first SOC value, change in the first theoretical ampere-hour (Ah) count, change in the first actual Ah count, and the vehicle's operating condition indicator for the battery pack. The first SOC value is the SOC value of the battery pack in a first time period, the second SOC value is the SOC value of the battery pack in a second time period, the first time period is later than the second time period, the change in the first SOC value is the change in the SOC value of the battery pack in the first time period, the change in the first theoretical Ah count is the change in the theoretical Ah count of the battery pack in the first time period, the change in the first actual Ah count is the change in the actual Ah count of the battery pack in the first time period, and the vehicle's operating condition indicator is used to indicate the operating condition of the vehicle, which includes charging condition and driving condition.

[0049] The aforementioned change in the first state of charge is the absolute value of the change in the state of charge of the vehicle's battery pack during the first time period.

[0050] The operating condition indicator of the vehicle can be a binary signal bit, that is, the operating condition indicator of the vehicle can be "0" or "1", where "1" indicates that the vehicle is in charging condition and "0" indicates that the vehicle is in driving condition.

[0051] Step 220: Based on the first charge state value, the second charge state value, the change in the first charge state value, the change in the first theoretical ampere-hours, the change in the first actual ampere-hours, and the vehicle's operating condition indicator, determine the abnormal detection results of the battery pack. The abnormal detection results include at least one of abnormal charge state data, charge state deviation, and charge state jump.

[0052] The above-mentioned abnormal charge state data indicates that the charge state value of the battery pack does not conform to the charge state value corresponding to the current operating conditions of the vehicle. For example, the charge state value of the battery pack is too high or too low.

[0053] The aforementioned charge state deviation indicates that the charge state value of the battery pack differs significantly from the common charge state value corresponding to the current operating conditions of the vehicle, exceeding the range corresponding to the common charge state value for the current operating conditions of the vehicle.

[0054] The aforementioned charge state jump indicates that the charge state value of the battery pack fluctuates considerably within a specified time period, such as suddenly becoming very large or very small in a short period of time.

[0055] Step 230: Send an anomaly detection warning message based on the anomaly detection results.

[0056] In this embodiment, after determining the anomaly detection result, the server sends an anomaly detection warning message corresponding to the anomaly detection result to the vehicle.

[0057] In this embodiment, the server obtains relevant data on the vehicle's battery pack and vehicle operating conditions, extracts data from different time periods from the relevant data on the vehicle's battery pack and vehicle operating conditions, and combines three factors: time information, battery pack-related data, and vehicle operating condition data. That is, based on the actual application scenario of the battery pack and the state of the battery pack at different time points, the server can more comprehensively judge the abnormal detection results of the battery pack, effectively improve the accuracy of abnormal detection of the battery pack, and thus improve the overall management effect of the battery.

[0058] Based on the solutions shown in any one or more of the above embodiments, in one possible implementation, step 220 can be implemented as follows: when the vehicle's operating condition indicator indicates that the vehicle is in charging condition and the first charge state value is less than the second charge state value, determine that the abnormal detection result of the battery pack includes abnormal charge state data; when the vehicle's operating condition indicator indicates that the vehicle is in driving condition and the first charge state value is greater than the second charge state value, determine that the abnormal detection result of the battery pack includes abnormal charge state data.

[0059] The aforementioned second state of charge value is the state of charge value of the vehicle's battery pack in a second time period earlier than the first time period.

[0060] In this embodiment, the vehicle's operating condition indicator indicates that the vehicle is in charging condition. The fact that the first state of charge value is less than the second state of charge value means that when the vehicle is in charging condition, the state of charge value of the battery pack in the first time period is less than the second state of charge value. That is, the state of charge value of the battery pack decreases as the charging time increases. Under normal charging conditions, the state of charge value of the battery pack should increase as the charging time increases. The fact that the first state of charge value is less than the second state of charge value indicates that the battery pack may have leakage or charging failure due to its own fault or other reasons.

[0061] In this embodiment, the vehicle's operating condition indicator indicates that the vehicle is in driving condition, and the first state of charge value being greater than the second state of charge value means that when the vehicle is in driving condition, the state of charge value of the battery pack in the first time period is greater than the second state of charge value. That is, the state of charge value of the battery pack increases as the driving time increases, whereas under normal driving conditions, the state of charge value of the battery pack should decrease as the driving time increases. The first state of charge value being greater than the second state of charge value indicates that there may be an abnormality in the battery pack, such as abnormal charging, battery failure, or system error.

[0062] In this embodiment, the server determines whether the battery charge state value is abnormal based on the vehicle's operating conditions and the charge state value of the battery pack at different time periods, effectively improving the accuracy of detecting abnormal charge state data of the battery pack.

[0063] Based on the solutions shown in any one or more of the above embodiments, in one possible implementation, step 220 can be implemented as follows: when the change in the first charge state value is not less than the first charge state value change threshold, and the ratio between the change in the first actual ampere-hours and the change in the first theoretical ampere-hours is not less than the proportional threshold, the abnormal detection result of the battery pack is determined to include charge state deviation.

[0064] The ratio between the first actual ampere-hour change and the first theoretical ampere-hour change is used to quantify the energy utilization rate or efficiency of the battery pack under actual operating conditions.

[0065] The statement that the change in the first state of charge value is not less than the threshold value of the change in the first state of charge value indicates that the change in the state of charge value of the battery pack exceeds the preset threshold value within the first time period, indicating that the state of charge value of the battery pack has changed significantly.

[0066] If the ratio between the first actual change in ampere-hours and the first theoretical change in ampere-hours is not less than the proportional threshold, it indicates that the actual discharge or charging behavior of the battery pack deviates significantly from the theoretical state.

[0067] In this embodiment of the application, the change in the state of charge value within a first time period and the ratio between the change in the first actual ampere-hour count and the change in the first theoretical ampere-hour count are used to determine whether there is a deviation in the state of charge value of the battery pack, which can effectively improve the accuracy of detecting the deviation in the state of charge of the battery.

[0068] Based on the solutions shown in any one or more of the above embodiments, in one possible implementation, step 220 can be implemented as follows: when the change in the first charge state value is not less than the threshold of the change in the second charge state value, the abnormal detection result of the battery pack is determined to include a charge state jump.

[0069] The aforementioned second charge state value change threshold is a large charge state change value, which is greater than the charge state value change threshold used to determine whether the battery pack has any abnormal deviation.

[0070] In this embodiment, the change in the first charge state value not being less than the threshold of the change in the second charge state value indicates that the charge state value has undergone a significant change within the first time period, and the degree of change exceeds the deviation range, reaching the level of a jump.

[0071] In this embodiment of the application, by comparing the change in the first charge state value with the change threshold of the second charge state value, it is possible to quickly determine whether the charge state value of the battery pack has changed drastically in the first time period, effectively improving the accuracy of detecting charge state jumps.

[0072] based on Figure 2 Please refer to the battery management method shown. Figure 3 , Figure 3 This is a flowchart of a battery management method provided in one embodiment of this application. The above step 230 can be implemented as step 230a and step 230b, as detailed below.

[0073] Step 230a: Obtain the warning level of the anomaly detection results.

[0074] In some embodiments, the server stores a first mapping relationship between warning levels and anomaly detection results, wherein different anomaly detection results correspond to different warning levels.

[0075] In other embodiments, the server stores a second mapping relationship between warning levels and anomaly detection results, in which different degrees of anomaly detection results correspond to different warning levels.

[0076] Step 230b: Send anomaly detection warning information based on the warning level.

[0077] The above-mentioned abnormal detection warning information is used to remind the vehicle's battery pack of any abnormalities.

[0078] In some embodiments, different warning levels correspond to different types of anomaly detection warning information.

[0079] Specifically, different warning levels correspond to different methods of sending anomaly detection warning information. The server sends anomaly detection warning information in a manner corresponding to the warning level.

[0080] For example, when the warning level reaches the highest level, it indicates that the current anomaly detection result indicates that the battery pack has a serious anomaly. At this time, the anomaly detection warning information is sent through a combination of audio broadcast and light reminder. When the warning level reaches the medium level, it indicates that the current anomaly detection result indicates that the battery pack has a general anomaly. At this time, the anomaly detection warning information is sent through audio broadcast.

[0081] Specifically, the content of the anomaly detection warning information varies depending on the warning level. The server sends the anomaly detection warning information content corresponding to the warning level.

[0082] For example, when the warning level reaches the highest level, it indicates that the current anomaly detection result indicates that the battery pack has a serious anomaly. At this time, the anomaly detection warning information includes the anomaly detection result and the suggested solution for the anomaly detection result. When the warning level reaches the medium level, it indicates that the current anomaly detection result indicates that the battery pack has a general anomaly. The anomaly detection warning information includes the anomaly detection result.

[0083] In this embodiment, the server sends targeted anomaly detection warning information based on the warning level of the anomaly detection result, making the anomaly detection warning information more targeted and providing a more intuitive warning of the current abnormal situation of the battery pack, thereby effectively improving the warning effect of anomaly detection results for the battery.

[0084] Based on the solutions shown in any one or more of the above-described embodiments, in one possible implementation, when the abnormal detection result includes abnormal charge state data, the warning level is determined by the difference between the first charge state value and the second charge state value; when the abnormal detection result includes charge state deviation, the warning level is determined by the change in the first charge state value and the ratio between the change in the first actual ampere-hours and the change in the first theoretical ampere-hours; when the abnormal detection result includes a charge state jump, the warning level is determined by the change in the first charge state value.

[0085] Specifically, when abnormal detection results include abnormal state of charge (SOC) data, if the vehicle is charging and the first SOC value is less than the second SOC value, the larger the difference between the two values, the more the SOC value decreases during charging, the more severe the SOC data abnormality, and the higher the corresponding warning level. Conversely, if the vehicle is driving and the first SOC value is greater than the second SOC value, the larger the difference between the two values, the more the SOC value increases during discharging, the more severe the SOC data abnormality, and the higher the corresponding warning level.

[0086] Specifically, when abnormal detection results include charge state deviation, the greater the change in the first charge state value and the greater the ratio between the change in the first actual ampere-hours and the change in the first theoretical ampere-hours, the greater the error in estimating the accumulated charge state of the battery pack, and the more severe the deviation between the actual charging and discharging behavior and the theoretical charging and discharging behavior, the higher the corresponding warning level.

[0087] Specifically, when the abnormal detection results include charge state jumps, the greater the change in the first charge state value, the greater the degree of change in the charge state value of the battery pack within the first time period, the more drastic the change, the more severe the charge state jump, and the higher the corresponding warning level.

[0088] In the embodiments of this application, the above-mentioned solution, through a multi-dimensional and scenario-based evaluation method, can more accurately reflect the actual severity of the battery pack's anomalies, avoid false alarms or missed alarms caused by a single criterion, and adopt a differentiated and targeted warning level determination mechanism based on the characteristics of different types of charge state anomalies, effectively improving the accuracy and reliability of the battery management system's warnings.

[0089] For example, based on Figures 2 to 3 For any one or more embodiments, this application proposes a calculation model for identifying SOC jump deviation based on data-driven methods.

[0090] This solution presents an innovative data-driven computational model focused on accurately identifying SOC jumps and deviations. Through efficient data interaction between the vehicle and the cloud, it fully leverages the advantages of massive real-time cloud data to extract voltage, current, and SOC data over specific time spans. Relying on the powerful computing capabilities of the cloud, it can accurately identify SOC jumps and deviations, and promptly collaborate with after-sales departments to conduct investigations, determining the source of the problem as the battery or BMS (Battery Management System), thus minimizing personnel and vehicle losses.

[0091] In actual operation, this model accurately identified and corrected batches of rapid SOC anomalies. It also collaborated with the BMS department to fix vulnerabilities and facilitate OTA (Over-the-Air) upgrades for vehicles, minimizing personnel and vehicle losses. Furthermore, rigorous validation with a large number of negative samples showed an accuracy rate of up to 90%, meaning the model can effectively and accurately identify SOC jumps / deviations, ensuring the stable and safe operation of electric vehicles.

[0092] Please refer to Figure 4 , Figure 4 This is a flowchart of a data processing method provided in one embodiment of this application.

[0093] like Figure 4 As shown, the specific details of this solution are as follows.

[0094] In operation, electric vehicles upload relevant data conforming to the national standard GBT / 32960 to the automaker's cloud server via the T-box gateway. The transmitted fields include key information such as timestamp, total voltage, voltage of each individual cell, temperature at each measuring point, total current, state of charge (SOC), driving status, and charging status. Using the timestamp as a reference, a sliding window of a specific duration is set to obtain real-time SOC status information from a certain time range, providing a data foundation for subsequent analysis.

[0095] Based on fields such as driving status and charging status in the collected data, the data is divided into charging condition dataset and driving condition dataset, denoted as data1 and data2 respectively, to achieve accurate data classification.

[0096] The system calculates the SOC change within a time window, the theoretical Ah (ampere-hour) change, and the actual Ah change, constructing a refined model for comparing these changes. It then compares the current SOC with the SOC state outside the time window to determine if anomalies caused a SOC jump. Furthermore, it categorizes different SOC changes and Ah ratios, and, considering the varying degrees of SOC jumps, activates a corresponding tiered early warning mechanism.

[0097] Taking full account of the impact of temperature on SOC, linear interpolation is performed based on SOC-OCV (Open Circuit Voltage-State of Charge) at different temperatures to accurately calculate the theoretical SOC value under the current operating conditions, which is then compared with the real-time SOC value. Similarly, tiered early warning thresholds are established to address different degrees of deviation between the two values, enabling timely warnings of abnormal SOC deviations.

[0098] Please refer to Figure 5 The diagram illustrates a block diagram of a battery management device provided in an exemplary embodiment of this application. This input battery management device can be implemented as all or part of a computer device through hardware or a combination of hardware and software, to achieve the above-described... Figures 2 to 3 All or part of the steps in the illustrated embodiments. For example... Figure 5 As shown, the battery management device includes:

[0099] The parameter acquisition module 51 is used to acquire the first state of charge value, the second state of charge value, the change in the first state of charge value, the change in the first theoretical ampere-hours, the change in the first actual ampere-hours, and the vehicle's operating condition indicator of the vehicle's battery pack. The first state of charge value is the state of charge value of the battery pack in a first time period, the second state of charge value is the state of charge value of the battery pack in a second time period, the first time period is later than the second time period, the change in the first state of charge value is the change in the state of charge value of the battery pack in the first time period, the change in the first theoretical ampere-hours is the change in the theoretical ampere-hours of the battery pack in the first time period, the change in the first actual ampere-hours is the change in the actual ampere-hours of the battery pack in the first time period, and the vehicle's operating condition indicator is used to indicate the operating condition of the vehicle, which includes charging condition and driving condition.

[0100] The detection result determination module 52 is used to determine the abnormal detection result of the battery pack based on the first charge state value, the second charge state value, the change in the first charge state value, the change in the first theoretical ampere-hours, the change in the first actual ampere-hours, and the vehicle's operating condition indicator. The abnormal detection result includes at least one of the following: abnormal charge state data, charge state deviation, and charge state jump.

[0101] The early warning information sending module 53 is used to send early warning information for abnormal detection based on the abnormal detection results.

[0102] In one possible implementation, the detection result determination module 52 is used for,

[0103] When the vehicle's operating condition indicator shows that the vehicle is in charging condition and the first state of charge value is less than the second state of charge value, the abnormal detection result of the battery pack is determined to include abnormal state of charge data.

[0104] When the vehicle's operating condition indicator shows that the vehicle is in driving condition and the first state of charge value is greater than the second state of charge value, the abnormal detection result of the battery pack is determined to include abnormal state of charge data.

[0105] In one possible implementation, the detection result determination module 52 is used for,

[0106] When the change in the first state of charge value is not less than the threshold value for the change in the first state of charge value, and the ratio between the change in the first actual ampere-hours and the change in the first theoretical ampere-hours is not less than the proportional threshold value, the abnormal detection results of the battery pack are determined to include the state of charge deviation.

[0107] In one possible implementation, the detection result determination module 52 is used for,

[0108] When the change in the first charge state value is not less than the threshold of the change in the second charge state value, the abnormal detection result of the battery pack is determined to include charge state jump.

[0109] In one possible implementation, the warning information sending module 53 is used for,

[0110] Obtain the warning level for abnormal detection results;

[0111] Based on the warning level, send anomaly detection warning information.

[0112] In one possible implementation, when the anomaly detection result includes anomalies in charge state data, the warning level is determined by the difference between the first charge state value and the second charge state value.

[0113] In cases where abnormal detection results include charge state deviation, the warning level is determined by the change in the first charge state value and the ratio between the change in the first actual ampere-hours and the change in the first theoretical ampere-hours.

[0114] When the abnormal detection results include a change in charge state, the warning level is determined by the amount of change in the first charge state value.

[0115] Please refer to Figure 6 , Figure 6This is a schematic diagram of the structure of a computer device provided in an exemplary embodiment of this application. The computer device 600 includes a Central Processing Unit (CPU) 601, a system memory 604 including Random Access Memory (RAM) 602 and Read-Only Memory (ROM) 603, and a system bus 605 connecting the system memory 604 and the CPU 601. The computer device 600 also includes a Basic Input / Output System (I / O System) 606 that facilitates the transfer of information between various devices within the computer, and a mass storage device 607 for storing the operating system 613, application programs 614, and other program modules 615.

[0116] The basic input / output system 606 includes a display 608 for displaying information and an input device 609 for user input, such as a mouse or keyboard. Both the display 608 and the input device 609 are connected to the central processing unit 601 via an input / output controller 610 connected to the system bus 605. The basic input / output system 606 may also include the input / output controller 610 for receiving and processing input from multiple other devices such as a keyboard, mouse, or electronic stylus. Similarly, the input / output controller 610 also provides output to a display screen, printer, or other types of output devices.

[0117] The mass storage device 607 is connected to the central processing unit 601 via a mass storage controller (not shown) connected to the system bus 605. The mass storage device 607 and its associated computer-readable media provide non-volatile storage for the computer device 600. That is, the mass storage device 607 may include computer-readable media (not shown) such as a hard disk or a CD-ROM (Compact Disc Read-Only Memory) drive.

[0118] Without loss of generality, the computer-readable medium may include computer storage media and communication media. Computer storage media include volatile and non-volatile, removable and non-removable media implemented using any method or technology for storing information such as computer-readable instructions, data structures, program modules, or other data. Computer storage media include RAM (Random Access Memory), ROM (Read-Only Memory), EPROM (Erasable Programmable Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), flash memory or other solid-state storage technologies, CD-ROM, DVD (Digital Video Disc) or other optical storage, magnetic tape cassettes, magnetic tape, disk storage, or other magnetic storage devices. Of course, those skilled in the art will recognize that the computer storage media are not limited to the above-mentioned types. The system memory 604 and the mass storage device 607 described above can be collectively referred to as memory.

[0119] Computer device 600 can be connected to the Internet or other network devices via network interface unit 611 connected to the system bus 605.

[0120] The memory also includes one or more programs stored in the memory, and the central processing unit 601 implements these programs by executing them. Figures 2 to 3 All or some of the steps in the method shown.

[0121] In an exemplary embodiment, a chip is also provided, the chip including programmable logic circuitry and / or program instructions, which, when the chip is run on a computer device, are used to implement all or part of the steps of the methods shown in the above embodiments of this application.

[0122] In an exemplary embodiment, a computer program product is also provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions to implement all or part of the steps of the methods shown in the above embodiments of this application.

[0123] In an exemplary embodiment, a computer-readable storage medium is also provided, which stores a computer program that is loaded and executed by a processor to implement all or part of the steps of the methods shown in the above embodiments of this application.

[0124] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0125] Those skilled in the art will recognize that the functions described in the embodiments of this application in one or more of the above examples can be implemented using hardware, software, firmware, or any combination thereof. When implemented using software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any medium that facilitates the transfer of a computer program from one place to another. Storage media can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0126] The above description is merely an optional embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A battery management method, characterized in that, The method includes: Acquire vehicle data; the vehicle data includes the first state of charge value of the vehicle's battery pack in a first time period, the second state of charge value in a second time period earlier than the first time period, the change in the first state of charge value in the first time period, the change in the first theoretical ampere-hours in the first time period, the change in the first actual ampere-hours in the first time period, and the vehicle's operating condition identifier, which is used to indicate the operating condition of the vehicle. Based on the vehicle data, the abnormal detection result of the battery pack is determined, and the abnormal detection result includes at least one of charge state data abnormality, charge state deviation, and charge state jump; when the operating condition indicator indicates that the vehicle is in charging condition and the first charge state value is less than the second charge state value, the abnormal detection result is determined to include charge state data abnormality; when the operating condition indicator indicates that the vehicle is in driving condition and the first charge state value is greater than the second charge state value, the abnormal detection result is determined to include charge state data abnormality; when the change in the first charge state value is not less than a first charge state value change threshold and the ratio between the first actual ampere-hour change and the first theoretical ampere-hour change is not less than a proportional threshold, the abnormal detection result is determined to include charge state deviation. Anomaly detection warning information is sent based on the anomaly detection results.

2. The method according to claim 1, characterized in that, The determination of the abnormal detection result of the battery pack based on the first charge state value, the second charge state value, the change in the first charge state value, the change in the first theoretical ampere-hours, the change in the first actual ampere-hours, the vehicle's charging indicator, and the vehicle's driving indicator includes: When the change in the first charge state value is not less than the threshold of the change in the second charge state value, the abnormal detection result of the battery pack is determined to include a charge state jump.

3. The method according to claim 1 or 2, characterized in that, Sending anomaly detection warning information based on the anomaly detection results includes: Obtain the warning level of the anomaly detection results; Based on the aforementioned warning level, the anomaly detection warning information is sent.

4. The method according to claim 3, characterized in that, If the anomaly detection result includes an anomaly in the charge state data, the warning level is determined by the difference between the first charge state value and the second charge state value; When the abnormal detection result includes the charge state deviation, the warning level is determined by the change in the first charge state value and the ratio between the change in the first actual ampere-hours and the change in the first theoretical ampere-hours. If the abnormal detection result includes the charge state jump, the warning level is determined by the amount of change in the first charge state value.

5. A battery management device, characterized in that, The device includes: The parameter acquisition module is used to acquire vehicle data. The vehicle data includes the first state of charge (SOC) value, second SOC value, change in the first SOC value, change in the first theoretical ampere-hours (Ahs), change in the first actual Ahs, and the vehicle's operating condition indicator. The first SOC value is the SOC value of the battery pack in a first time period, the second SOC value is the SOC value of the battery pack in a second time period earlier than the first time period, the change in the first SOC value is the change in the SOC value of the battery pack in the first time period, the change in the first theoretical Ahs is the change in the theoretical Ahs of the battery pack in the first time period, the change in the first actual Ahs is the change in the actual Ahs of the battery pack in the first time period, and the vehicle's operating condition indicator is used to indicate the operating condition of the vehicle. The detection result determination module is used to determine the abnormal detection result of the battery pack based on vehicle data. The abnormal detection result includes at least one of charge state data abnormality, charge state deviation, and charge state jump. When the operating condition indicator indicates that the vehicle is in charging condition and the first charge state value is less than the second charge state value, the module determines that the abnormal detection result of the battery pack includes charge state data abnormality. When the operating condition indicator indicates that the vehicle is in driving condition and the first charge state value is greater than the second charge state value, the module determines that the abnormal detection result includes charge state data abnormality. When the change in the first charge state value is not less than a first charge state value change threshold and the ratio between the first actual ampere-hour change and the first theoretical ampere-hour change is not less than a proportional threshold, the module determines that the abnormal detection result includes charge state deviation. The early warning information sending module is used to send anomaly detection early warning information based on the anomaly detection results.

6. A computer device, characterized in that, The computer device includes a processor and a memory, the memory storing instructions which are executed by the processor to implement the battery management method as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The storage medium stores instructions that are executed by a processor of a computer device to implement the battery management method as described in any one of claims 1 to 4.

8. A computer program product, characterized in that, The computer program product includes computer instructions stored in a computer-readable storage medium; the computer instructions are read and executed by a processor of a computer device to implement the battery management method as described in any one of claims 1 to 4.

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