Battery pack health monitoring method and system for scene

Abstract

The invention provides a battery pack health monitoring method and system for a scene. The battery pack health monitoring method for the scene comprises the following steps: collecting parameter information of a battery pack in different scenes in real time; obtaining the health state of the current battery pack according to the parameter information of the battery pack; and when the health state of the current battery pack is in an abnormal state, judging the degradation state of the current battery pack, and giving an abnormal and degradation state alarm. The system comprises modules corresponding to the steps of the method.

Description

Technical Field

[0001] The present invention provides a battery pack health monitoring method and system for use in a scenario, belonging to the technical field of battery monitoring. Background Art

[0002] With the increasing global emphasis on environmental protection and energy transition, electric vehicles, a key trend in future transportation, are experiencing a significant acceleration in their adoption. As a core component of electric vehicles, the performance and quality of the battery pack directly determine the vehicle's range, safety, and reliability. Therefore, comprehensive and efficient battery pack health monitoring has become a critical component in the development, development, and operation and maintenance of electric vehicles. During actual use, electric vehicle battery packs are subject to a variety of complex and changing conditions, including extreme environments such as high and low temperatures, high humidity, and vibration, as well as frequent charge and discharge cycles. These factors can affect battery pack performance to varying degrees, leading to performance degradation and safety hazards. To ensure the safe operation of electric vehicles and extend the battery pack's lifespan, real-time and accurate battery pack health monitoring is essential.

[0003] Most existing battery pack health monitoring methods rely on fixed detection equipment and complex algorithm models, and have the following shortcomings: First, the monitoring data is single and it is difficult to fully reflect the performance changes of the battery pack in different scenarios; second, the data processing is complex and the real-time performance is poor, which makes it difficult to meet the needs of electric vehicles for rapid response; third, the alarm mechanism is not intelligent enough and often only sounds an alarm when the battery pack has obvious faults, and cannot provide early warning of potential degradation conditions. Summary of the Invention

[0004] The present invention provides a battery pack health monitoring method and system for use in scenarios to solve the technical problems existing in the above-mentioned prior art. The technical solutions adopted are as follows: A battery pack health monitoring method for a scenario, the battery pack health monitoring method for a scenario comprising: Real-time collection of battery pack parameter information in different scenarios; Obtaining a current health status of the battery pack according to the parameter information of the battery pack; When the health status of the current battery pack is in an abnormal state, the degradation state of the current battery pack is determined, and an abnormality and degradation state alarm is issued.

[0005] Furthermore, real-time collection of battery pack parameter information in different scenarios includes: Real-time collection of first parameter information of the battery pack during operation in different scenarios, wherein the first parameter information of the battery pack includes battery capacity and battery internal resistance; The second parameter information of the battery pack during operation is collected in real time, wherein the second parameter information of the battery pack includes voltage data, current data and temperature data.

[0006] Furthermore, obtaining the current health status of the battery pack according to the parameter information of the battery pack includes: The first health state parameter is obtained using the first parameter information corresponding to each unit time of the battery pack operation; wherein the first health state parameter is obtained by the following formula: in, L 01 represents the first health status parameter; C b express n The standard deviation of battery capacity corresponding to unit time; R b express n The standard deviation of the battery internal resistance corresponding to the unit time; n Indicates the number of unit times included in the battery pack operation; C n Indicates the nominal capacity of the battery pack; C ti Indicates the i Battery capacity corresponding to unit time; R n Indicates the initial internal resistance of the battery pack; C ti Indicates the i The internal resistance of the battery corresponding to the unit time; The second health state parameter is obtained using the second parameter information corresponding to each unit time of the battery pack operation; wherein the second health state parameter is obtained by the following formula: in, L 02 represents the first health status parameter; n Indicates the number of unit times included in the battery pack operation; Vn 、 In and Tn Indicates standard values ​​for voltage, current, and temperature; Vti 、 Iti and Tti Indicates the i The data values ​​of voltage, current and temperature corresponding to each unit time; Fymax express Get the maximum allowable floating values ​​of the corresponding voltage, current and temperature; Fymin express Get the maximum allowable floating values ​​of the corresponding voltage, current and temperature; frepresents the adjustment coefficient, and the adjustment coefficient is obtained by the following formula: in, f represents the adjustment coefficient; V b 、 I b and T b Indicates battery pack operation n The standard deviation of voltage, current and temperature corresponding to each unit time; w 01 、 w 02 and w 03 Indicates the weight values ​​corresponding to voltage, current and temperature; The health status evaluation parameter is obtained by using the first health status parameter and the second health status parameter; wherein the health status evaluation parameter is obtained by the following formula: in, L Indicates health status evaluation parameters; L 01 represents the first health status parameter; L 02 represents the first health status parameter; Comparing the health status evaluation parameter with a preset health evaluation status threshold; When the health status evaluation parameter is not lower than a preset health evaluation status threshold, it is determined that the battery pack is in an abnormal health state.

[0007] Furthermore, when the health status of the current battery pack is abnormal, the degradation status of the current battery pack is determined, and an abnormality and degradation status alarm is issued, including: When the current health status of the battery pack is in an abnormal state, extracting a first operating status parameter and a second operating status parameter from historical operating data of the battery pack; Determining the current degradation state of the battery pack using the first operating state parameter and the second operating state parameter to obtain a degradation state determination result; According to the degradation state determination result and the abnormal state, an abnormal and degradation state alarm is issued; Wherein, the degradation state includes a primary degradation state and an advanced degradation state; In addition, the first operating status parameters include open circuit voltage, charging efficiency and discharging efficiency; the second operating status parameters include the internal resistance value of the battery pack corresponding to each charge and discharge, the current actual battery capacity of the battery pack and the number of battery charge and discharge cycles.

[0008] Furthermore, determining the current degradation state of the battery pack using the first operating state parameter and the second operating state parameter includes: extracting a first operating state parameter; The first operating state parameter is used to obtain a first degradation state parameter; wherein the first degradation state parameter is obtained by the following formula: in, E 01 represents the first degenerate state parameter; V kn Indicates the standard value of open circuit voltage; V dn Indicates the current open circuit voltage value; V bk Indicates the standard deviation of the open circuit voltage during battery pack operation; P c and P f Represent the current charging efficiency and discharging efficiency respectively; P cb and P fb Standard values ​​of charging efficiency and discharging efficiency respectively; extracting a second operating state parameter; The second operating state parameter is used to obtain a second degradation state parameter; wherein the second degradation state parameter is obtained by the following formula: in, E 02 represents the second degenerate state parameter; m Indicates the number of battery charge and discharge cycles; R zi and R si Indicates the i The internal resistance of the battery pack at the start and end of the charge and discharge cycle; R n Indicates the initial internal resistance of the battery pack; C n Indicates the nominal capacity of the battery pack; C d Indicates the battery capacity of the battery pack when the health status of the current battery pack is in an abnormal state; comparing the first degradation state parameter with a preset first degradation state threshold; comparing the second degradation state parameter with a preset second degradation state threshold; When the first degradation state parameter and the second degradation state parameter are both lower than their corresponding first degradation state threshold and second degradation state threshold, it is determined that no degradation state occurs; When any one of the first degradation state parameter and the second degradation state parameter is not lower than its corresponding degradation state threshold, it is determined that a degradation state occurs, and the degradation state is a primary degradation state; When both the first degradation state parameter and the second degradation state parameter are not lower than their corresponding first degradation state thresholds and second degradation state thresholds, it is determined that a degradation state occurs, and the degradation state is an advanced degradation state.

[0009] A battery pack health monitoring system for a scenario, the battery pack health monitoring system for the scenario comprising: Real-time acquisition module, used to collect parameter information of battery packs in different scenarios in real time; A health status acquisition module, configured to acquire the current health status of the battery pack based on the parameter information of the battery pack; The degradation judgment and early warning module is used to judge the degradation state of the current battery pack when the health state of the current battery pack is in an abnormal state, and to issue an abnormal and degradation state alarm.

[0010] Furthermore, the real-time acquisition module includes: A first parameter information acquisition module, configured to acquire first parameter information of the battery pack during operation in different scenarios in real time, wherein the first parameter information of the battery pack includes battery capacity and battery internal resistance; The second parameter information acquisition module is used to collect the second parameter information of the battery pack in real time during operation, wherein the second parameter information of the battery pack includes voltage data, current data and temperature data.

[0011] Furthermore, the health status acquisition module includes: The first health state parameter acquisition module is configured to acquire a first health state parameter using first parameter information corresponding to each unit time of battery pack operation; wherein the first health state parameter is acquired using the following formula: in, L 01 represents the first health status parameter; C b express n The standard deviation of battery capacity corresponding to unit time; R b express n The standard deviation of the battery internal resistance corresponding to the unit time; n Indicates the number of unit times included in the battery pack operation; C n Indicates the nominal capacity of the battery pack; C ti Indicates thei Battery capacity corresponding to unit time; R n Indicates the initial internal resistance of the battery pack; C ti Indicates the i The internal resistance of the battery corresponding to the unit time; The second health state parameter acquisition module is used to obtain the second health state parameter using the second parameter information corresponding to each unit time of the battery pack operation; wherein the second health state parameter is obtained by the following formula: in, L 02 represents the first health status parameter; n Indicates the number of unit times included in the battery pack operation; Vn 、 In and Tn Indicates standard values ​​for voltage, current, and temperature; Vti 、 Iti and Tti Indicates the i The data values ​​of voltage, current and temperature corresponding to each unit time; Fymax express Get the maximum allowable floating values ​​of the corresponding voltage, current and temperature; Fymin express Get the maximum allowable floating values ​​of the corresponding voltage, current and temperature; f represents the adjustment coefficient, and the adjustment coefficient is obtained by the following formula: in, f represents the adjustment coefficient; V b 、 I b and T b Indicates battery pack operation n The standard deviation of voltage, current and temperature corresponding to each unit time; w 01 、 w 02 and w 03 Indicates the weight values ​​corresponding to voltage, current and temperature; A health status evaluation parameter acquisition module is used to obtain a health status evaluation parameter using the first health status parameter and the second health status parameter; wherein the health status evaluation parameter is obtained by the following formula: in, L Indicates health status evaluation parameters; L 01represents the first health status parameter; L 02 represents the first health status parameter; A first comparison module, configured to compare the health status evaluation parameter with a preset health evaluation status threshold; The abnormal state judgment module is used to determine that the battery pack is in an abnormal health state when the health state evaluation parameter is not lower than a preset health evaluation state threshold.

[0012] Furthermore, the degradation determination and early warning module includes: an operating state parameter extraction module, configured to extract a first operating state parameter and a second operating state parameter from historical operating data of the battery pack when the health state of the current battery pack is in an abnormal state; a degradation state determination result acquisition module, configured to determine the degradation state of the current battery pack using the first operating state parameter and the second operating state parameter to obtain a degradation state determination result; an alarm execution module, configured to issue an abnormality and degradation state alarm based on the degradation state determination result and the abnormal state; Wherein, the degradation state includes a primary degradation state and an advanced degradation state; In addition, the first operating status parameters include open circuit voltage, charging efficiency and discharging efficiency; the second operating status parameters include the internal resistance value of the battery pack corresponding to each charge and discharge, the current actual battery capacity of the battery pack and the number of battery charge and discharge cycles.

[0013] Furthermore, the degradation state determination result acquisition module includes: A first operating state parameter extraction module, configured to extract a first operating state parameter; The first degradation state parameter acquisition module is configured to acquire a first degradation state parameter using the first operating state parameter; wherein the first degradation state parameter is acquired using the following formula: in, E 01 represents the first degenerate state parameter; V kn Indicates the standard value of open circuit voltage; V dn Indicates the current open circuit voltage value; V bk Indicates the standard deviation of the open circuit voltage during battery pack operation; P c and P f Represent the current charging efficiency and discharging efficiency respectively; P cb and Pfb Standard values ​​of charging efficiency and discharging efficiency respectively; A second operating state parameter extraction module, used to extract the second operating state parameter; The second degradation state parameter acquisition module is used to obtain a second degradation state parameter using the second operating state parameter; wherein the second degradation state parameter is obtained by the following formula: in, E 02 represents the second degenerate state parameter; m Indicates the number of battery charge and discharge cycles; R zi and R si Indicates the i The internal resistance of the battery pack at the start and end of the charge and discharge cycle; R n Indicates the initial internal resistance of the battery pack; C n Indicates the nominal capacity of the battery pack; C d Indicates the battery capacity of the battery pack when the health status of the current battery pack is in an abnormal state; a second comparing module, configured to compare the first degradation state parameter with a preset first degradation state threshold; a third comparing module, configured to compare the second degradation state parameter with a preset second degradation state threshold; a first degradation state judgment module, configured to determine that no degradation state has occurred when both the first degradation state parameter and the second degradation state parameter are lower than their corresponding first degradation state thresholds and second degradation state thresholds; a second degradation state judgment module, configured to determine that a degradation state occurs when any one of the first degradation state parameter and the second degradation state parameter is not lower than its corresponding degradation state threshold, and the degradation state is a primary degradation state; The third degradation state judgment module is configured to determine that a degradation state occurs when both the first degradation state parameter and the second degradation state parameter are not lower than their corresponding first degradation state thresholds and second degradation state thresholds, and the degradation state is an advanced degradation state.

[0014] Beneficial effects of the present invention: The scenario-based battery pack health monitoring method and system proposed in this invention can collect real-time battery pack parameter information under different scenarios, including key parameters such as voltage, current, temperature, and internal resistance, and comprehensively assess the battery pack's health status based on this parameter information. Furthermore, when the battery pack's health status shows an abnormality, the method intelligently determines the battery pack's degradation state and issues timely and accurate abnormality and degradation status alarms, allowing users or maintenance personnel to quickly take measures to ensure the safe operation of the electric vehicle and extend the battery pack's service life. Real-time monitoring of the battery pack's health status can promptly detect and provide early warning of potential safety hazards, such as battery overheating and short circuits, thereby preventing accidents. By assessing the battery pack's degradation state, users can promptly implement maintenance measures or replace the battery pack to extend the overall service life of the electric vehicle. Through intelligent monitoring and alarm mechanisms, users can continuously monitor the battery pack's performance and make adjustments or repairs as needed, thereby improving the driving experience and satisfaction. For electric vehicle operators, this method helps achieve refined battery pack management and optimized operation and maintenance, reducing operating costs and improving operational efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A flow chart of the method of the present invention; Figure 2 This is a system block diagram of the system of the present invention. DETAILED DESCRIPTION

[0016] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0017] The embodiment of the present invention proposes a battery pack health monitoring method for scenarios such as Figure 1 As shown, the battery pack health monitoring method for the scenario includes: S1. Real-time collection of battery pack parameter information in different scenarios; S2. Obtaining the current health status of the battery pack according to the parameter information of the battery pack; S3. When the health status of the current battery pack is in an abnormal state, determine the degradation state of the current battery pack and issue an abnormal and degradation state alarm.

[0018] The working principle of this technical solution is to collect real-time battery pack parameter information through various sensors installed on the battery pack (such as voltage sensors, current sensors, and temperature sensors). These sensors can capture real-time data on the battery pack under different usage scenarios (such as high temperature, low temperature, high humidity, and vibration). The collected data is transmitted to a data processing center or vehicle control system for preliminary cleaning, verification, and storage to ensure data accuracy and integrity.

[0019] Advanced algorithms (such as machine learning and neural networks) analyze collected parameter information to assess the battery pack's health status. These algorithms comprehensively consider the correlations and changing trends between multiple parameters, enabling a more accurate assessment of the battery pack's performance. Based on the results of the algorithmic analysis, a quantitative assessment of the battery pack's health status is performed, such as providing a health score or grading. This assessment results serve as the basis for subsequent decision-making.

[0020] If the current battery pack health status is abnormal, the system determines the current battery pack degradation state and issues an abnormality and degradation alarm. If the battery pack health assessment indicates an abnormality, the system automatically triggers the degradation state assessment mechanism. By further analyzing battery pack parameters (such as capacity decay rate and internal resistance increase), the system determines the extent and cause of battery pack degradation. Once an abnormal or degraded battery pack is confirmed, the system immediately activates an alarm mechanism, alerting the user or maintenance personnel via the vehicle dashboard, mobile app, or remote monitoring system. The alarm information will include the battery pack's current state, degradation level, and recommended corrective measures.

[0021] The benefits of this technical solution are: by monitoring the health of the battery pack in real time, potential safety hazards such as battery overheating and short circuits can be promptly detected and warned, thereby avoiding accidents. By assessing the degradation of the battery pack, users can take timely maintenance measures or replace the battery pack, thereby extending the overall service life of the electric vehicle. Through intelligent monitoring and alarm mechanisms, users can understand the performance status of the battery pack at all times and make adjustments or repairs as needed, thereby improving the driving experience and satisfaction. For electric vehicle operators, this method helps achieve refined battery pack management and operation and maintenance optimization, reducing operating costs and improving operational efficiency.

[0022] In summary, this technical solution achieves comprehensive monitoring and effective management of the health status of battery packs through real-time monitoring, intelligent analysis, and timely alarms. It is of great significance for ensuring the safe operation of electric vehicles, extending their service life, and improving user experience.

[0023] In one embodiment of the present invention, real-time acquisition of parameter information of a battery pack in different scenarios includes: S101, collecting first parameter information of a battery pack during operation in different scenarios in real time, wherein the first parameter information of the battery pack includes battery capacity and battery internal resistance; S102 . Collect second parameter information of the battery pack in real time during operation, wherein the second parameter information of the battery pack includes voltage data, current data, and temperature data.

[0024] The working principle of the above technical solution is as follows: Battery capacity and internal resistance are key parameters during battery pack operation, directly reflecting the battery pack's energy storage capacity and internal state. High-precision sensors or measuring devices are used to monitor changes in battery capacity and internal resistance in real time under different scenarios. These sensors can be integrated into the battery pack to ensure data accuracy and real-time performance. The collected battery capacity and internal resistance data is transmitted to a data processing center or vehicle control system for further analysis and processing. For example, the battery pack's performance degradation can be assessed by comparing historical data or preset thresholds.

[0025] Voltage, current, and temperature data are fundamental parameters during battery pack operation and are crucial for monitoring the pack's operating status and safety. Voltage sensors measure the pack's total voltage and individual cell voltages in real time to understand the battery's state of charge and health. Current sensors monitor the pack's charge and discharge currents in real time, helping to calculate the battery's state of charge (SOC) and state of discharge (SOD) and detect overcurrent conditions. Temperature sensors collect temperature information from multiple points in the battery pack to monitor temperature fluctuations and prevent overheating or cold start issues. These parameter data are transmitted in real time to a data processing system for comprehensive analysis. Based on this data, the system can determine the battery pack's operating status, such as whether it is experiencing abnormal conditions such as overcharge, overdischarge, or overtemperature.

[0026] The above technical solution achieves the following benefits: By collecting multiple parameter information in real time, a more comprehensive understanding of the battery pack's operating status in different scenarios is achieved, improving monitoring precision and accuracy. Abnormal battery pack conditions (such as overcharging, over-discharging, and overheating) can be promptly detected and preventive measures can be taken to avoid safety accidents and enhance the safety of electric vehicles. Based on the collected parameter information, more refined battery pack management can be implemented, such as adjusting charging strategies and optimizing energy distribution, thereby extending the battery pack's service life and improving energy efficiency. By comparing historical data with real-time data, faults or problems in the battery pack can be more easily diagnosed, providing strong support for repair and maintenance. Users can view battery pack parameter information in real time through the vehicle dashboard or mobile app, understanding the battery pack's performance and usage, thereby improving the driving experience and satisfaction.

[0027] In summary, this technical solution achieves comprehensive monitoring and effective management of the battery pack's operating status by real-time collection of various parameter information of the battery pack in different scenarios. It is of great significance for improving the safety of electric vehicles, extending the service life of the battery pack, and enhancing the user experience.

[0028] In one embodiment of the present invention, obtaining the current health status of the battery pack according to the parameter information of the battery pack includes: S201. Obtain a first health status parameter using first parameter information corresponding to each unit time of battery pack operation; wherein the first health status parameter is obtained by the following formula: in, L 01 represents the first health status parameter; C b express n The standard deviation of battery capacity corresponding to unit time; R b express n The standard deviation of the battery internal resistance corresponding to the unit time; n Indicates the number of unit times included in the battery pack operation; C n Indicates the nominal capacity of the battery pack; C ti Indicates the i Battery capacity corresponding to unit time; R n Indicates the initial internal resistance of the battery pack; C ti Indicates the i The internal resistance of the battery corresponding to the unit time; S202: Obtain a second health status parameter using second parameter information corresponding to each unit time of battery pack operation; wherein the second health status parameter is obtained by the following formula: in, L 02 represents the first health status parameter; n Indicates the number of unit times included in the battery pack operation; Vn 、 In and Tn Indicates standard values ​​for voltage, current, and temperature; Vti 、 Iti and Tti Indicates the i The data values ​​of voltage, current and temperature corresponding to each unit time; Fymax express Get the maximum allowable floating values ​​of the corresponding voltage, current and temperature; Fymin express Get the maximum allowable floating values ​​of the corresponding voltage, current and temperature; f represents the adjustment coefficient, and the adjustment coefficient is obtained by the following formula: in, f represents the adjustment coefficient; V b 、 I b and T b Indicates battery pack operation n The standard deviation of voltage, current and temperature corresponding to each unit time; w 01 、 w 02 and w 03 Indicates the weight values ​​corresponding to voltage, current and temperature; S203. Obtain a health status evaluation parameter using the first health status parameter and the second health status parameter; wherein the health status evaluation parameter is obtained by the following formula: in, L Indicates health status evaluation parameters; L 01 represents the first health status parameter; L 02 represents the first health status parameter; S204, comparing the health status evaluation parameter with a preset health evaluation status threshold; S205: When the health status evaluation parameter is not lower than a preset health evaluation status threshold, it is determined that the battery pack is in an abnormal health state.

[0029] The working principle of the above technical solution is to evaluate the performance stability of the battery pack over long-term operation by comparing the standard deviation of battery capacity and internal resistance with the nominal or initial values. First, the standard deviation of battery capacity Cb and the standard deviation of battery internal resistance Rb over n time units are calculated. Then, combined with the battery pack's nominal capacity Cn and initial internal resistance Rn, the above technical solution is used to calculate the first health parameter L01. This parameter reflects the fluctuation of battery capacity and internal resistance. The greater the fluctuation, the more unstable the battery pack performance.

[0030] The battery pack's real-time operating status is assessed by comparing actual voltage, current, and temperature values ​​with their standard values ​​or maximum allowable fluctuations. This technical solution calculates a second health parameter, L02, by calculating the deviations of voltage (Vti), current (Iti), and temperature (Tti) from their respective standard values ​​(Vn, In, and Tn) per unit time, taking into account the maximum allowable fluctuations (Fymax and Fymin), and an adjustment factor (f) calculated based on the standard deviations of voltage, current, and temperature and their respective weights (w01, w02, and w03). This parameter integrates the real-time status of the battery pack in terms of voltage, current, and temperature, reflecting whether the battery pack is within its normal operating range.

[0031] Combining the first and second health parameters yields a comprehensive health evaluation parameter, L, to comprehensively assess the battery pack's health. L01 and L02 are weighted or summed using the aforementioned technical solution to obtain the health evaluation parameter, L. This parameter integrates the battery pack's performance stability and real-time operating status over long periods of operation, providing a basis for subsequent health assessments.

[0032] Determine whether the battery pack's health status is within the normal range. Compare the calculated health status evaluation parameter L with the preset health evaluation threshold. The threshold is set based on factors such as the battery pack's design requirements, usage experience, and safety standards. If L is not lower than the preset threshold, it indicates that the battery pack has experienced performance fluctuations or abnormal conditions during long-term or real-time operation, potentially posing a safety hazard or performance degradation.

[0033] The above technical solution achieves the following benefits: By comprehensively considering multiple parameters such as battery capacity, internal resistance, voltage, current, and temperature, it achieves a comprehensive assessment of the battery pack's health status. By collecting and analyzing battery pack parameters in real time, abnormal battery pack conditions can be promptly detected and appropriate measures taken. Statistical methods and mathematical models, such as standard deviation, bias, and adjustment coefficients, are used for calculation and analysis, improving the accuracy and reliability of the assessment results. When the battery pack is in an abnormal health state, a warning signal is issued, alerting the user or maintenance personnel to conduct inspection and repairs, thereby preventing safety accidents. The assessment results can provide a scientific basis and guidance for routine battery pack maintenance, care, and replacement.

[0034] In one embodiment of the present invention, when the health status of the current battery pack is abnormal, determining the degradation status of the current battery pack and issuing an abnormality and degradation status alarm includes: S301: When the current health status of the battery pack is in an abnormal state, extract a first operating status parameter and a second operating status parameter from historical operating data of the battery pack; S302: Determine the degradation state of the current battery pack using the first operating state parameter and the second operating state parameter to obtain a degradation state determination result; S303, issuing an abnormality and degradation state alarm based on the degradation state determination result and the abnormal state; Wherein, the degradation state includes a primary degradation state and an advanced degradation state; In addition, the first operating status parameters include open circuit voltage, charging efficiency and discharging efficiency; the second operating status parameters include the internal resistance value of the battery pack corresponding to each charge and discharge, the current actual battery capacity of the battery pack and the number of battery charge and discharge cycles.

[0035] The working principle of the above technical solution is: in order to accurately judge the degradation state of the battery pack, it is necessary to extract the key parameters of the battery pack during its historical operation. These parameters can reflect the performance changes and degradation of the battery pack.

[0036] Parameter content: The first operating status parameter includes open circuit voltage, charge efficiency, and discharge efficiency. These parameters are directly related to the electrochemical performance and charge and discharge capacity of the battery pack and are important indicators for evaluating battery pack performance.

[0037] Secondary operating status parameters: These include the internal resistance of the battery pack corresponding to each charge and discharge cycle, the actual battery capacity of the battery pack, and the number of charge and discharge cycles. These parameters reflect the physical changes and performance degradation of the battery pack during long-term use.

[0038] The extracted historical operating data is compared with pre-set degradation criteria or models, and the current battery pack degradation level is calculated using algorithms or data analysis methods. Based on the comparison results, the battery pack degradation state is classified into primary and advanced degradation states. Primary degradation indicates that the battery pack performance has slightly degraded, but still meets normal usage requirements; advanced degradation indicates severe performance degradation, which may affect normal use and even pose a safety hazard.

[0039] When the battery pack's health status is determined to be abnormal and the degradation reaches the preset alarm threshold, an alarm mechanism is triggered. Alarm information can be presented to the user or maintenance personnel via the vehicle's instrument panel, onboard information system, or remote monitoring platform. The alarm information should include a description of the battery pack's abnormal condition, the degradation determination result, and any corresponding treatment recommendations or maintenance instructions.

[0040] The above technical solution achieves the following benefits: Through real-time monitoring and data analysis, abnormal battery pack conditions and degradation can be promptly detected, providing users and maintenance personnel with timely warnings. Degradation status determination is based on multiple operating parameters, improving accuracy and reliability. Based on degradation status determination results and abnormal condition information, users are provided with scientific maintenance recommendations and repair guidance, helping to extend the battery pack's lifespan and improve safety. Timely warnings and scientific maintenance guidance can enhance user trust and satisfaction with electric vehicles, and improve the user experience.

[0041] In summary, this technical solution achieves timely early warning and scientific maintenance guidance for abnormal and degraded states of battery packs by extracting historical operating data of battery packs and conducting analysis and judgment, which has significant technical effects and application value.

[0042] In one embodiment of the present invention, determining the current degradation state of the battery pack using the first operating state parameter and the second operating state parameter includes: S3021. Extracting a first operating state parameter; S3022. Obtain a first degradation state parameter using the first operating state parameter; wherein the first degradation state parameter is obtained using the following formula: in, E 01 represents the first degenerate state parameter; V kn Indicates the standard value of open circuit voltage; V dn Indicates the current open circuit voltage value; V bk Indicates the standard deviation of the open circuit voltage during battery pack operation; P c and P f Represent the current charging efficiency and discharging efficiency respectively; P cb and P fb Standard values ​​of charging efficiency and discharging efficiency respectively; S3023. Extract the second operating state parameter; S3024. Obtain a second degradation state parameter using the second operating state parameter; wherein the second degradation state parameter is obtained by the following formula: in, E 02 represents the second degenerate state parameter; m Indicates the number of battery charge and discharge cycles; R zi andR si Indicates the i The internal resistance of the battery pack at the start and end of the charge and discharge cycle; R n Indicates the initial internal resistance of the battery pack; C n Indicates the nominal capacity of the battery pack; C d Indicates the battery capacity of the battery pack when the health status of the current battery pack is in an abnormal state; S3025. Compare the first degradation state parameter with a preset first degradation state threshold; S3026. Compare the second degradation state parameter with a preset second degradation state threshold; S3027: When the first degradation state parameter and the second degradation state parameter are both lower than their corresponding first degradation state threshold and second degradation state threshold, it is determined that no degradation state has occurred; S3028. When any one of the first degradation state parameter and the second degradation state parameter is not lower than its corresponding degradation state threshold, it is determined that a degradation state occurs, and the degradation state is a primary degradation state. S3029: When both the first degradation state parameter and the second degradation state parameter are not lower than their corresponding first degradation state thresholds and second degradation state thresholds, it is determined that a degradation state occurs, and the degradation state is an advanced degradation state.

[0043] The working principle of the above technical solution is to obtain parameters directly related to the electrochemical performance of the battery pack, such as open-circuit voltage, charge efficiency, and discharge efficiency. These parameters can reflect the performance changes of the battery pack during the charge and discharge process. The first degradation parameter E01 is calculated by comparing the current open-circuit voltage with the standard value, the current charge and discharge efficiency with the standard value, and the fluctuation (standard deviation) of the open-circuit voltage. This parameter combines the stability of the open-circuit voltage and the changes in the charge and discharge efficiency to reflect the degradation of the battery pack's electrochemical performance. Parameters related to the physical performance of the battery pack are obtained, such as the number of battery charge and discharge cycles, the change in internal resistance per cycle, and the current battery capacity. These parameters can reflect the physical changes and performance degradation of the battery pack during long-term use. The second degradation parameter E02 is calculated by calculating the number of battery charge and discharge cycles, the change in internal resistance per cycle (the difference between the internal resistance at the start and end times), the relationship between the current battery capacity and the nominal capacity, and taking into account the initial internal resistance of the battery pack. This parameter combines the internal resistance change, capacity attenuation, and cycle count of the battery pack during the charge and discharge cycle to reflect the degradation of the battery pack's physical properties. It determines whether the degradation of the battery pack's electrochemical performance has reached a preset threshold, and at the same time, determines whether the degradation of the battery pack's physical performance has reached a preset threshold.

[0044] If both degradation state parameters are lower than their corresponding thresholds, it is determined that the battery pack is not in a degradation state.

[0045] If any degradation state parameter is not lower than its corresponding threshold value but does not meet the higher level judgment standard, the battery pack is determined to be in a primary degradation state.

[0046] If both degradation state parameters are not lower than their corresponding thresholds and meet or exceed the judgment criteria of a higher level, the battery pack is determined to be in a high-level degradation state.

[0047] The above technical solution achieves the following: By combining electrochemical and physical performance parameters for comprehensive evaluation, it can more comprehensively and accurately reflect the degradation of the battery pack. By calculating degradation state parameters and comparing them with preset thresholds, the degradation state of the battery pack can be quantitatively determined, improving the accuracy and objectivity of the determination. By setting different judgment criteria and warning levels (non-degradation, primary degradation, and advanced degradation) according to the degree of degradation, users can be provided with more precise maintenance recommendations and repair guidance. By promptly determining the degradation state of the battery pack and issuing a warning signal, users or maintenance personnel can be guided to take appropriate measures to maintain or replace the battery pack, extending the battery pack's service life and improving its safety.

[0048] In summary, this technical solution achieves a comprehensive assessment and quantitative determination of the degradation state of the battery pack by comprehensively considering the electrochemical properties and physical performance parameters of the battery pack, and has significant technical effects and application value.

[0049] The embodiment of the present invention proposes a battery pack health monitoring system for scenarios such as Figure 2 As shown, the battery pack health monitoring system for the scenario includes: Real-time acquisition module, used to collect parameter information of battery packs in different scenarios in real time; A health status acquisition module, configured to acquire the current health status of the battery pack based on the parameter information of the battery pack; The degradation judgment and early warning module is used to judge the degradation state of the current battery pack when the health state of the current battery pack is in an abnormal state, and to issue an abnormal and degradation state alarm.

[0050] The working principle of this technical solution is to collect real-time battery pack parameter information through various sensors installed on the battery pack (such as voltage sensors, current sensors, and temperature sensors). These sensors can capture real-time data on the battery pack under different usage scenarios (such as high temperature, low temperature, high humidity, and vibration). The collected data is transmitted to a data processing center or vehicle control system for preliminary cleaning, verification, and storage to ensure data accuracy and integrity.

[0051] Advanced algorithms (such as machine learning and neural networks) analyze collected parameter information to assess the battery pack's health status. These algorithms comprehensively consider the correlations and changing trends between multiple parameters, enabling a more accurate assessment of the battery pack's performance. Based on the results of the algorithmic analysis, a quantitative assessment of the battery pack's health status is performed, such as providing a health score or grading. This assessment results serve as the basis for subsequent decision-making.

[0052] If the current battery pack health status is abnormal, the system determines the current battery pack degradation state and issues an abnormality and degradation alarm. If the battery pack health assessment indicates an abnormality, the system automatically triggers the degradation state assessment mechanism. By further analyzing battery pack parameters (such as capacity decay rate and internal resistance increase), the system determines the extent and cause of battery pack degradation. Once an abnormal or degraded battery pack is confirmed, the system immediately activates an alarm mechanism, alerting the user or maintenance personnel via the vehicle dashboard, mobile app, or remote monitoring system. The alarm information will include the battery pack's current state, degradation level, and recommended corrective measures.

[0053] The benefits of this technical solution are: by monitoring the health of the battery pack in real time, potential safety hazards such as battery overheating and short circuits can be promptly detected and warned, thereby avoiding accidents. By assessing the degradation of the battery pack, users can take timely maintenance measures or replace the battery pack, thereby extending the overall service life of the electric vehicle. Through intelligent monitoring and alarm mechanisms, users can understand the performance status of the battery pack at all times and make adjustments or repairs as needed, thereby improving the driving experience and satisfaction. For electric vehicle operators, this method helps achieve refined battery pack management and operation and maintenance optimization, reducing operating costs and improving operational efficiency.

[0054] In summary, this technical solution achieves comprehensive monitoring and effective management of the health status of battery packs through real-time monitoring, intelligent analysis, and timely alarms. It is of great significance for ensuring the safe operation of electric vehicles, extending their service life, and improving user experience.

[0055] In one embodiment of the present invention, the real-time acquisition module includes: A first parameter information acquisition module, configured to acquire first parameter information of the battery pack during operation in different scenarios in real time, wherein the first parameter information of the battery pack includes battery capacity and battery internal resistance; The second parameter information acquisition module is used to collect the second parameter information of the battery pack in real time during operation, wherein the second parameter information of the battery pack includes voltage data, current data and temperature data.

[0056] The working principle of the above technical solution is as follows: Battery capacity and internal resistance are key parameters during battery pack operation, directly reflecting the battery pack's energy storage capacity and internal state. High-precision sensors or measuring devices are used to monitor changes in battery capacity and internal resistance in real time under different scenarios. These sensors can be integrated into the battery pack to ensure data accuracy and real-time performance. The collected battery capacity and internal resistance data is transmitted to a data processing center or vehicle control system for further analysis and processing. For example, the battery pack's performance degradation can be assessed by comparing historical data or preset thresholds.

[0057] Voltage, current, and temperature data are fundamental parameters during battery pack operation and are crucial for monitoring the pack's operating status and safety. Voltage sensors measure the pack's total voltage and individual cell voltages in real time to understand the battery's state of charge and health. Current sensors monitor the pack's charge and discharge currents in real time, helping to calculate the battery's state of charge (SOC) and state of discharge (SOD) and detect overcurrent conditions. Temperature sensors collect temperature information from multiple points in the battery pack to monitor temperature fluctuations and prevent overheating or cold start issues. These parameter data are transmitted in real time to a data processing system for comprehensive analysis. Based on this data, the system can determine the battery pack's operating status, such as whether it is experiencing abnormal conditions such as overcharge, overdischarge, or overtemperature.

[0058] The above technical solution achieves the following benefits: By collecting multiple parameter information in real time, a more comprehensive understanding of the battery pack's operating status in different scenarios is achieved, improving monitoring precision and accuracy. Abnormal battery pack conditions (such as overcharging, over-discharging, and overheating) can be promptly detected and preventive measures can be taken to avoid safety accidents and enhance the safety of electric vehicles. Based on the collected parameter information, more refined battery pack management can be implemented, such as adjusting charging strategies and optimizing energy distribution, thereby extending the battery pack's service life and improving energy efficiency. By comparing historical data with real-time data, faults or problems in the battery pack can be more easily diagnosed, providing strong support for repair and maintenance. Users can view battery pack parameter information in real time through the vehicle dashboard or mobile app, understanding the battery pack's performance and usage, thereby improving the driving experience and satisfaction.

[0059] In summary, this technical solution achieves comprehensive monitoring and effective management of the battery pack's operating status by real-time collection of various parameter information of the battery pack in different scenarios. It is of great significance for improving the safety of electric vehicles, extending the service life of the battery pack, and enhancing the user experience.

[0060] In one embodiment of the present invention, the health status acquisition module includes: The first health state parameter acquisition module is configured to acquire a first health state parameter using first parameter information corresponding to each unit time of battery pack operation; wherein the first health state parameter is acquired using the following formula: in, L 01 represents the first health status parameter; C b express n The standard deviation of battery capacity corresponding to unit time; R b express nThe standard deviation of the battery internal resistance corresponding to the unit time; n Indicates the number of unit times included in the battery pack operation; C n Indicates the nominal capacity of the battery pack; C ti Indicates the i Battery capacity corresponding to unit time; R n Indicates the initial internal resistance of the battery pack; C ti Indicates the i The internal resistance of the battery corresponding to the unit time; The second health state parameter acquisition module is used to obtain the second health state parameter using the second parameter information corresponding to each unit time of the battery pack operation; wherein the second health state parameter is obtained by the following formula: in, L 02 represents the first health status parameter; n Indicates the number of unit times included in the battery pack operation; Vn 、 In and Tn Indicates standard values ​​for voltage, current, and temperature; Vti 、 Iti and Tti Indicates the i The data values ​​of voltage, current and temperature corresponding to each unit time; Fymax express Get the maximum allowable floating values ​​of the corresponding voltage, current and temperature; Fymin express Get the maximum allowable floating values ​​of the corresponding voltage, current and temperature; f represents the adjustment coefficient, and the adjustment coefficient is obtained by the following formula: in, f represents the adjustment coefficient; V b 、 I b and T b Indicates battery pack operation n The standard deviation of voltage, current and temperature corresponding to each unit time; w 01 、 w 02 and w 03 Indicates the weight values ​​corresponding to voltage, current and temperature; A health status evaluation parameter acquisition module is used to obtain a health status evaluation parameter using the first health status parameter and the second health status parameter; wherein the health status evaluation parameter is obtained by the following formula: in, L Indicates health status evaluation parameters; L 01 represents the first health status parameter; L 02 represents the first health status parameter; A first comparison module, configured to compare the health status evaluation parameter with a preset health evaluation status threshold; The abnormal state judgment module is used to determine that the battery pack is in an abnormal health state when the health state evaluation parameter is not lower than a preset health evaluation state threshold.

[0061] The working principle of the above technical solution is to evaluate the performance stability of the battery pack over long-term operation by comparing the standard deviation of battery capacity and internal resistance with the nominal or initial values. First, the standard deviation of battery capacity Cb and the standard deviation of battery internal resistance Rb over n time units are calculated. Then, combined with the battery pack's nominal capacity Cn and initial internal resistance Rn, the above technical solution is used to calculate the first health parameter L01. This parameter reflects the fluctuation of battery capacity and internal resistance. The greater the fluctuation, the more unstable the battery pack performance.

[0062] The battery pack's real-time operating status is assessed by comparing actual voltage, current, and temperature values ​​with their standard values ​​or maximum allowable fluctuations. This technical solution calculates a second health parameter, L02, by calculating the deviations of voltage (Vti), current (Iti), and temperature (Tti) from their respective standard values ​​(Vn, In, and Tn) per unit time, taking into account the maximum allowable fluctuations (Fymax and Fymin), and an adjustment factor (f) calculated based on the standard deviations of voltage, current, and temperature and their respective weights (w01, w02, and w03). This parameter integrates the real-time status of the battery pack in terms of voltage, current, and temperature, reflecting whether the battery pack is within its normal operating range.

[0063] Combining the first and second health parameters yields a comprehensive health evaluation parameter, L, to comprehensively assess the battery pack's health. L01 and L02 are weighted or summed using the aforementioned technical solution to obtain the health evaluation parameter, L. This parameter integrates the battery pack's performance stability and real-time operating status over long periods of operation, providing a basis for subsequent health assessments.

[0064] Determine whether the battery pack's health status is within the normal range. Compare the calculated health status evaluation parameter L with the preset health evaluation threshold. The threshold is set based on factors such as the battery pack's design requirements, usage experience, and safety standards. If L is not lower than the preset threshold, it indicates that the battery pack has experienced performance fluctuations or abnormal conditions during long-term or real-time operation, potentially posing a safety hazard or performance degradation.

[0065] The above technical solution achieves the following benefits: By comprehensively considering multiple parameters such as battery capacity, internal resistance, voltage, current, and temperature, it achieves a comprehensive assessment of the battery pack's health status. By collecting and analyzing battery pack parameters in real time, abnormal battery pack conditions can be promptly detected and appropriate measures taken. Statistical methods and mathematical models, such as standard deviation, bias, and adjustment coefficients, are used for calculation and analysis, improving the accuracy and reliability of the assessment results. When the battery pack is in an abnormal health state, a warning signal is issued, alerting the user or maintenance personnel to conduct inspection and repairs, thereby preventing safety accidents. The assessment results can provide a scientific basis and guidance for routine battery pack maintenance, care, and replacement.

[0066] In one embodiment of the present invention, the degradation determination and early warning module includes: an operating state parameter extraction module, configured to extract a first operating state parameter and a second operating state parameter from historical operating data of the battery pack when the health state of the current battery pack is in an abnormal state; a degradation state determination result acquisition module, configured to determine the degradation state of the current battery pack using the first operating state parameter and the second operating state parameter to obtain a degradation state determination result; an alarm execution module, configured to issue an abnormality and degradation state alarm based on the degradation state determination result and the abnormal state; Wherein, the degradation state includes a primary degradation state and an advanced degradation state; In addition, the first operating status parameters include open circuit voltage, charging efficiency and discharging efficiency; the second operating status parameters include the internal resistance value of the battery pack corresponding to each charge and discharge, the current actual battery capacity of the battery pack and the number of battery charge and discharge cycles.

[0067] The working principle of the above technical solution is: in order to accurately judge the degradation state of the battery pack, it is necessary to extract the key parameters of the battery pack during its historical operation. These parameters can reflect the performance changes and degradation of the battery pack.

[0068] Parameter content: The first operating status parameter includes open circuit voltage, charge efficiency, and discharge efficiency. These parameters are directly related to the electrochemical performance and charge and discharge capacity of the battery pack and are important indicators for evaluating battery pack performance.

[0069] Secondary operating status parameters: These include the internal resistance of the battery pack corresponding to each charge and discharge cycle, the actual battery capacity of the battery pack, and the number of charge and discharge cycles. These parameters reflect the physical changes and performance degradation of the battery pack during long-term use.

[0070] The extracted historical operating data is compared with pre-set degradation criteria or models, and the current battery pack degradation level is calculated using algorithms or data analysis methods. Based on the comparison results, the battery pack degradation state is classified into primary and advanced degradation states. Primary degradation indicates that the battery pack performance has slightly degraded, but still meets normal usage requirements; advanced degradation indicates severe performance degradation, which may affect normal use and even pose a safety hazard.

[0071] When the battery pack's health status is determined to be abnormal and the degradation reaches the preset alarm threshold, an alarm mechanism is triggered. Alarm information can be presented to the user or maintenance personnel via the vehicle's instrument panel, onboard information system, or remote monitoring platform. The alarm information should include a description of the battery pack's abnormal condition, the degradation determination result, and any corresponding treatment recommendations or maintenance instructions.

[0072] The above technical solution achieves the following benefits: Through real-time monitoring and data analysis, abnormal battery pack conditions and degradation can be promptly detected, providing users and maintenance personnel with timely warnings. Degradation status determination is based on multiple operating parameters, improving accuracy and reliability. Based on degradation status determination results and abnormal condition information, users are provided with scientific maintenance recommendations and repair guidance, helping to extend the battery pack's lifespan and improve safety. Timely warnings and scientific maintenance guidance can enhance user trust and satisfaction with electric vehicles, and improve the user experience.

[0073] In summary, this technical solution achieves timely early warning and scientific maintenance guidance for abnormal and degraded states of battery packs by extracting historical operating data of battery packs and conducting analysis and judgment, which has significant technical effects and application value.

[0074] In one embodiment of the present invention, the degradation state determination result acquisition module includes: A first operating state parameter extraction module, configured to extract a first operating state parameter; The first degradation state parameter acquisition module is configured to acquire a first degradation state parameter using the first operating state parameter; wherein the first degradation state parameter is acquired using the following formula: in, E 01 represents the first degenerate state parameter; Vkn Indicates the standard value of open circuit voltage; V dn Indicates the current open circuit voltage value; V bk Indicates the standard deviation of the open circuit voltage during battery pack operation; P c and P f Represent the current charging efficiency and discharging efficiency respectively; P cb and P fb Standard values ​​of charging efficiency and discharging efficiency respectively; A second operating state parameter extraction module, used to extract the second operating state parameter; The second degradation state parameter acquisition module is used to obtain a second degradation state parameter using the second operating state parameter; wherein the second degradation state parameter is obtained by the following formula: in, E 02 represents the second degenerate state parameter; m Indicates the number of battery charge and discharge cycles; R zi and R si Indicates the i The internal resistance of the battery pack at the start and end of the charge and discharge cycle; R n Indicates the initial internal resistance of the battery pack; C n Indicates the nominal capacity of the battery pack; C d Indicates the battery capacity of the battery pack when the health status of the current battery pack is in an abnormal state; a second comparing module, configured to compare the first degradation state parameter with a preset first degradation state threshold; a third comparing module, configured to compare the second degradation state parameter with a preset second degradation state threshold; a first degradation state judgment module, configured to determine that no degradation state has occurred when both the first degradation state parameter and the second degradation state parameter are lower than their corresponding first degradation state thresholds and second degradation state thresholds; a second degradation state judgment module, configured to determine that a degradation state occurs when any one of the first degradation state parameter and the second degradation state parameter is not lower than its corresponding degradation state threshold, and the degradation state is a primary degradation state; The third degradation state judgment module is configured to determine that a degradation state occurs when both the first degradation state parameter and the second degradation state parameter are not lower than their corresponding first degradation state thresholds and second degradation state thresholds, and the degradation state is an advanced degradation state.

[0075] The working principle of the above technical solution is to obtain parameters directly related to the electrochemical performance of the battery pack, such as open-circuit voltage, charge efficiency, and discharge efficiency. These parameters can reflect the performance changes of the battery pack during the charge and discharge process. The first degradation parameter E01 is calculated by comparing the current open-circuit voltage with the standard value, the current charge and discharge efficiency with the standard value, and the fluctuation (standard deviation) of the open-circuit voltage. This parameter combines the stability of the open-circuit voltage and the changes in the charge and discharge efficiency to reflect the degradation of the battery pack's electrochemical performance. Parameters related to the physical performance of the battery pack are obtained, such as the number of battery charge and discharge cycles, the change in internal resistance per cycle, and the current battery capacity. These parameters can reflect the physical changes and performance degradation of the battery pack during long-term use. The second degradation parameter E02 is calculated by calculating the number of battery charge and discharge cycles, the change in internal resistance per cycle (the difference between the internal resistance at the start and end times), the relationship between the current battery capacity and the nominal capacity, and taking into account the initial internal resistance of the battery pack. This parameter combines the internal resistance change, capacity attenuation, and cycle count of the battery pack during the charge and discharge cycle to reflect the degradation of the battery pack's physical properties. It determines whether the degradation of the battery pack's electrochemical performance has reached a preset threshold, and at the same time, determines whether the degradation of the battery pack's physical performance has reached a preset threshold.

[0076] If both degradation state parameters are lower than their corresponding thresholds, it is determined that the battery pack is not in a degradation state.

[0077] If any degradation state parameter is not lower than its corresponding threshold value but does not meet the higher level judgment standard, the battery pack is determined to be in a primary degradation state.

[0078] If both degradation state parameters are not lower than their corresponding thresholds and meet or exceed the judgment criteria of a higher level, the battery pack is determined to be in a high-level degradation state.

[0079] The above technical solution achieves the following: By combining electrochemical and physical performance parameters for comprehensive evaluation, it can more comprehensively and accurately reflect the degradation of the battery pack. By calculating degradation state parameters and comparing them with preset thresholds, the degradation state of the battery pack can be quantitatively determined, improving the accuracy and objectivity of the determination. By setting different judgment criteria and warning levels (non-degradation, primary degradation, and advanced degradation) according to the degree of degradation, users can be provided with more precise maintenance recommendations and repair guidance. By promptly determining the degradation state of the battery pack and issuing a warning signal, users or maintenance personnel can be guided to take appropriate measures to maintain or replace the battery pack, extending the battery pack's service life and improving its safety.

[0080] In summary, this technical solution achieves a comprehensive assessment and quantitative determination of the degradation state of the battery pack by comprehensively considering the electrochemical properties and physical performance parameters of the battery pack, and has significant technical effects and application value.

[0081] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A battery pack health monitoring method for a scenario, characterized in that: The battery pack health monitoring method for the scenario includes: Real-time collection of battery pack parameter information in different scenarios; Obtaining a current health status of the battery pack according to the parameter information of the battery pack; When the health status of the current battery pack is in an abnormal state, the degradation state of the current battery pack is determined, and an abnormality and degradation state alarm is issued.

2. The battery pack health monitoring method for a scenario according to claim 1, characterized in that: Real-time collection of battery pack parameter information in different scenarios, including: Real-time collection of first parameter information of the battery pack during operation in different scenarios, wherein the first parameter information of the battery pack includes battery capacity and battery internal resistance; The second parameter information of the battery pack during operation is collected in real time, wherein the second parameter information of the battery pack includes voltage data, current data and temperature data.

3. The battery pack health monitoring method for a scenario according to claim 1, characterized in that: Obtaining the current health status of the battery pack based on the parameter information of the battery pack, including: The first health state parameter is obtained using the first parameter information corresponding to each unit time of the battery pack operation; wherein the first health state parameter is obtained by the following formula: in, L 01 represents the first health status parameter; C b express n The standard deviation of battery capacity corresponding to unit time; R b express n The standard deviation of the battery internal resistance corresponding to the unit time; n Indicates the number of unit times included in the battery pack operation; C n Indicates the nominal capacity of the battery pack; C ti Indicates the i Battery capacity corresponding to unit time; R n Indicates the initial internal resistance of the battery pack; C ti Indicates the i The internal resistance of the battery corresponding to the unit time; The second health state parameter is obtained using the second parameter information corresponding to each unit time of the battery pack operation; wherein the second health state parameter is obtained by the following formula: in, L 02 represents the first health status parameter; n Indicates the number of unit times included in the battery pack operation; Vn 、 In and Tn Indicates standard values ​​for voltage, current, and temperature; Vti 、 Iti and Tti Indicates the i The data values ​​of voltage, current and temperature corresponding to each unit time; Fymax express Get the maximum allowable floating values ​​of the corresponding voltage, current and temperature; Fymin express Get the maximum allowable floating values ​​of the corresponding voltage, current and temperature; f represents the adjustment coefficient, and the adjustment coefficient is obtained by the following formula: in, f represents the adjustment coefficient; V b 、 I b and T b Indicates battery pack operation n The standard deviation of voltage, current and temperature corresponding to each unit time; w 01 、 w 02 and w 03 Indicates the weight values ​​corresponding to voltage, current and temperature; A health status evaluation parameter is obtained using the first health status parameter and the second health status parameter; wherein the health status evaluation parameter is obtained by the following formula: in, L Indicates health status evaluation parameters; L 01 represents the first health status parameter; L 02 represents the first health status parameter; Comparing the health status evaluation parameter with a preset health evaluation status threshold; When the health status evaluation parameter is not lower than a preset health evaluation status threshold, it is determined that the battery pack is in an abnormal health state.

4. The battery pack health monitoring method for a scenario according to claim 1, characterized in that: When the health status of the current battery pack is abnormal, determining the degradation status of the current battery pack and issuing an abnormality and degradation status alarm includes: When the current health status of the battery pack is in an abnormal state, extracting a first operating status parameter and a second operating status parameter from historical operating data of the battery pack; Determining the current degradation state of the battery pack using the first operating state parameter and the second operating state parameter to obtain a degradation state determination result; According to the degradation state determination result and the abnormal state, an abnormal and degradation state alarm is issued; Wherein, the degradation state includes a primary degradation state and an advanced degradation state; In addition, the first operating status parameters include open circuit voltage, charging efficiency and discharging efficiency; the second operating status parameters include the internal resistance value of the battery pack corresponding to each charge and discharge, the current actual battery capacity of the battery pack and the number of battery charge and discharge cycles.

5. The battery pack health monitoring method for a scenario according to claim 4, characterized in that: Determining the current degradation state of the battery pack using the first operating state parameter and the second operating state parameter includes: extracting a first operating state parameter; The first operating state parameter is used to obtain a first degradation state parameter; wherein the first degradation state parameter is obtained by the following formula: in, E 01 represents the first degenerate state parameter; V kn Indicates the standard value of open circuit voltage; V dn Indicates the current open circuit voltage value; V bk Indicates the standard deviation of the open circuit voltage during battery pack operation; P c and P f Represent the current charging efficiency and discharging efficiency respectively; P cb and P fb Standard values ​​of charging efficiency and discharging efficiency respectively; extracting a second operating state parameter; The second operating state parameter is used to obtain a second degradation state parameter; wherein the second degradation state parameter is obtained by the following formula: in, E 02 represents the second degenerate state parameter; m Indicates the number of battery charge and discharge cycles; R zi and R si Indicates the i The internal resistance of the battery pack at the start and end of the charge and discharge cycle; R n Indicates the initial internal resistance of the battery pack; C n Indicates the nominal capacity of the battery pack; C d Indicates the battery capacity of the battery pack when the health status of the current battery pack is in an abnormal state; comparing the first degradation state parameter with a preset first degradation state threshold; comparing the second degradation state parameter with a preset second degradation state threshold; When the first degradation state parameter and the second degradation state parameter are both lower than their corresponding first degradation state threshold and second degradation state threshold, it is determined that no degradation state occurs; When any one of the first degradation state parameter and the second degradation state parameter is not lower than its corresponding degradation state threshold, it is determined that a degradation state occurs, and the degradation state is a primary degradation state; When both the first degradation state parameter and the second degradation state parameter are not lower than their corresponding first degradation state thresholds and second degradation state thresholds, it is determined that a degradation state occurs, and the degradation state is an advanced degradation state.

6. A battery pack health monitoring system for a scenario, characterized in that: The battery pack health monitoring system for the scenario includes: Real-time acquisition module, used to collect parameter information of battery packs in different scenarios in real time; A health status acquisition module, configured to acquire the current health status of the battery pack based on the parameter information of the battery pack; The degradation judgment and early warning module is used to judge the degradation state of the current battery pack when the health state of the current battery pack is in an abnormal state, and to issue an abnormal and degradation state alarm.

7. The battery pack health monitoring system for a scenario according to claim 6, characterized in that: The real-time acquisition module includes: A first parameter information acquisition module, configured to acquire first parameter information of the battery pack during operation in different scenarios in real time, wherein the first parameter information of the battery pack includes battery capacity and battery internal resistance; The second parameter information acquisition module is used to collect the second parameter information of the battery pack in real time during operation, wherein the second parameter information of the battery pack includes voltage data, current data and temperature data.

8. The battery pack health monitoring system for a scenario according to claim 6, characterized in that: The health status acquisition module includes: The first health state parameter acquisition module is configured to acquire a first health state parameter using first parameter information corresponding to each unit time of battery pack operation; wherein the first health state parameter is acquired using the following formula: in, L 01 represents the first health status parameter; C b express n The standard deviation of battery capacity corresponding to unit time; R b express n The standard deviation of the battery internal resistance corresponding to the unit time; n Indicates the number of unit times included in the battery pack operation; C n Indicates the nominal capacity of the battery pack; C ti Indicates the i Battery capacity corresponding to unit time; R n Indicates the initial internal resistance of the battery pack; C ti Indicates the i The internal resistance of the battery corresponding to the unit time; The second health state parameter acquisition module is used to obtain the second health state parameter using the second parameter information corresponding to each unit time of the battery pack operation; wherein the second health state parameter is obtained by the following formula: in, L 02 represents the first health status parameter; n Indicates the number of unit times included in the battery pack operation; Vn 、 In and Tn Indicates standard values ​​for voltage, current, and temperature; Vti 、 Iti and Tti Indicates the i The data values ​​of voltage, current and temperature corresponding to each unit time; Fymax express Get the maximum allowable floating values ​​of the corresponding voltage, current and temperature; Fymin express Get the maximum allowable floating values ​​of the corresponding voltage, current and temperature; f represents the adjustment coefficient, and the adjustment coefficient is obtained by the following formula: in, f represents the adjustment coefficient; V b 、 I b and T b Indicates battery pack operation n The standard deviation of voltage, current and temperature corresponding to each unit time; w 01 、 w 02 and w 03 Indicates the weight values ​​corresponding to voltage, current and temperature; A health status evaluation parameter acquisition module is used to obtain a health status evaluation parameter using the first health status parameter and the second health status parameter; wherein the health status evaluation parameter is obtained by the following formula: in, L Indicates health status evaluation parameters; L 01 represents the first health status parameter; L 02 represents the first health status parameter; A first comparison module, configured to compare the health status evaluation parameter with a preset health evaluation status threshold; The abnormal state judgment module is used to determine that the battery pack is in an abnormal health state when the health state evaluation parameter is not lower than a preset health evaluation state threshold.

9. The battery pack health monitoring system for a scenario according to claim 6, characterized in that: The degradation judgment and early warning module includes: an operating state parameter extraction module, configured to extract a first operating state parameter and a second operating state parameter from historical operating data of the battery pack when the current health state of the battery pack is in an abnormal state; a degradation state determination result acquisition module, configured to determine the degradation state of the current battery pack using the first operating state parameter and the second operating state parameter to obtain a degradation state determination result; an alarm execution module, configured to issue an abnormality and degradation state alarm based on the degradation state determination result and the abnormal state; Wherein, the degradation state includes a primary degradation state and an advanced degradation state; In addition, the first operating status parameters include open circuit voltage, charging efficiency and discharging efficiency; the second operating status parameters include the internal resistance value of the battery pack corresponding to each charge and discharge, the current actual battery capacity of the battery pack and the number of battery charge and discharge cycles.

10. The battery pack health monitoring system for a scenario according to claim 9, characterized in that: The degradation state determination result acquisition module includes: A first operating state parameter extraction module, configured to extract a first operating state parameter; The first degradation state parameter acquisition module is configured to acquire a first degradation state parameter using the first operating state parameter; wherein the first degradation state parameter is acquired using the following formula: in, E 01 represents the first degenerate state parameter; V kn Indicates the standard value of open circuit voltage; V dn Indicates the current open circuit voltage value; V bk Indicates the standard deviation of the open circuit voltage during battery pack operation; P c and P f Represent the current charging efficiency and discharging efficiency respectively; P cb and P fb Standard values ​​of charging efficiency and discharging efficiency respectively; A second operating state parameter extraction module, used to extract the second operating state parameter; The second degradation state parameter acquisition module is used to obtain a second degradation state parameter using the second operating state parameter; wherein the second degradation state parameter is obtained by the following formula: in, E 02 represents the second degenerate state parameter; m Indicates the number of battery charge and discharge cycles; R zi and R si Indicates the i The internal resistance of the battery pack at the start and end of the charge and discharge cycle; R n Indicates the initial internal resistance of the battery pack; C n Indicates the nominal capacity of the battery pack; C d Indicates the battery capacity of the battery pack when the health status of the current battery pack is in an abnormal state; a second comparing module, configured to compare the first degradation state parameter with a preset first degradation state threshold; a third comparing module, configured to compare the second degradation state parameter with a preset second degradation state threshold; a first degradation state judgment module, configured to determine that no degradation state has occurred when both the first degradation state parameter and the second degradation state parameter are lower than their corresponding first degradation state thresholds and second degradation state thresholds; a second degradation state judgment module, configured to determine that a degradation state occurs when any one of the first degradation state parameter and the second degradation state parameter is not lower than its corresponding degradation state threshold, and the degradation state is a primary degradation state; The third degradation state judgment module is configured to determine that a degradation state occurs when both the first degradation state parameter and the second degradation state parameter are not lower than their corresponding first degradation state thresholds and second degradation state thresholds, and the degradation state is an advanced degradation state.

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