Large cylindrical battery health monitoring method and system

Abstract

The invention discloses a large cylindrical battery health monitoring method and system, and relates to the field of battery health monitoring. The large cylindrical battery health monitoring method comprises the following steps: when a large cylindrical battery is in a running state, continuously acquiring historical battery running state data of a plurality of historical monitoring time periods and current battery running data of a current time period, and preprocessing the historical battery running state data and the current battery running data; analyzing the historical battery operation state data and the current battery operation data of each historical monitoring time period to obtain a historical battery health assessment value and a current battery health assessment value of each historical monitoring time period, and performing analysis again to obtain a current battery health change value; according to the method, the current battery health change value and the preset battery health change range are judged and analyzed, and corresponding measures are taken based on the analysis result, so that the long-term health state of the battery is accurately reflected, potential trends and problems are timely identified, and a stable evaluation result is kept when monitoring is performed in a changing environment.

Description

Technical Field

[0001] The present invention relates to the field of battery health monitoring, and in particular to a large cylindrical battery health monitoring method and system. Background Art

[0002] With the rapid development of renewable energy and electric vehicles, large cylindrical batteries, as the main energy storage devices, play an increasingly important role in various applications. Large cylindrical batteries have high energy density, long cycle life and low production cost. They are widely used in electric vehicles, energy storage systems and portable electronic devices. However, batteries are affected by many factors during use, such as temperature changes, charge and discharge frequency, etc., which cause the battery health to gradually decline, thereby affecting its performance and safety.

[0003] Prior art, such as the invention patent application with announcement number: CN117517980B, discloses a real-time monitoring method and system for the health status of a lithium battery, which belongs to the field of lithium battery monitoring technology. First, a lithium battery equivalent circuit model is established, and the lithium battery equivalent circuit model is converted into a state equation. Then, a variable coefficient is obtained by Pull-type transformation and setting the lithium battery ohmic internal resistance adjustment factor. The parameters of the lithium battery equivalent circuit model are calculated according to the variable coefficient. Finally, the lithium battery health status index is calculated based on the parameters of the lithium battery equivalent circuit model. Through the above method steps, on the one hand, the lithium battery equivalent circuit model is simplified and the model complexity is reduced; on the other hand, the lithium battery ohmic internal resistance adjustment factor is used to characterize the change of the lithium battery internal resistance in the above monitoring process, avoiding complex model construction and training evaluation, and meeting the requirements of real-time monitoring accuracy and model complexity of the lithium battery health status.

[0004] Based on the above solution, it is found that the limitations of the existing technology include at least the following problems. First, the existing technology relies on real-time data and lacks comprehensive analysis of historical data, making it difficult to accurately reflect the long-term health status of the battery, resulting in misjudgment due to instantaneous data fluctuations. Second, the existing technology only uses a single health status indicator for evaluation, which makes the health assessment results not comprehensive and scientific enough, ignores multiple performance parameters of the battery, limits the deep understanding of the overall health status of the battery, and increases the decision-making risk of the battery during maintenance and replacement. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a large cylindrical battery health monitoring method and system, which solves the problem that the prior art relies on real-time data, lacks comprehensive analysis of historical data, and is difficult to accurately reflect the long-term health status of the battery, thus leading to misjudgment due to instantaneous data fluctuations. Secondly, the prior art only uses a single health status indicator for evaluation, which makes the health assessment results not comprehensive and scientific enough, ignores multiple performance parameters of the battery, limits the deep understanding of the overall health status of the battery, and increases the decision-making risk of the battery during maintenance and replacement.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a large cylindrical battery health monitoring method, comprising the following steps: when the large cylindrical battery is in operation, continuously obtaining historical battery operation status data of several historical monitoring time periods and current battery operation data of the current time period, and preprocessing; performing data analysis on the historical battery operation status data of each historical monitoring time period after preprocessing and the current battery operation status data of the current monitoring time period, respectively, to obtain the historical battery attenuation index, historical battery conductivity performance index of each historical monitoring time period and the current battery attenuation index, current battery conductivity performance index of the current monitoring time period, and performing comprehensive analysis respectively, to obtain the historical battery health assessment value of each historical monitoring time period and the current battery health assessment value of the current time period; analyzing the historical battery health assessment values ​​of several historical monitoring time periods and the current battery health assessment value of the current monitoring time period, to obtain the current battery health change value of the current monitoring segment; judging and analyzing the current battery health change value of the current monitoring segment with the preset battery health change range, performing monitoring and evaluation based on the judgment and analysis results, and taking corresponding measures.

[0007] Furthermore, the historical battery operating status data specifically includes historical battery voltage values, historical battery current values, historical battery ambient temperature values, historical battery internal resistance values, historical battery capacity values, historical electrolyte concentration values, historical electrode specific surface area values, and historical battery porosity values; and the current battery operating status data specifically includes current battery voltage value, current battery current value, current battery ambient temperature value, current battery internal resistance value, current battery capacity value, current electrolyte concentration value, current electrode specific surface area value, and current battery porosity value.

[0008] Furthermore, the specific formula for calculating the battery health assessment value for each historical monitoring period is as follows: Among them, JkZ t is the historical battery health assessment value of the tth historical monitoring period, DcS t is the historical battery attenuation index of the tth historical monitoring period, α 1 is the attenuation coefficient stored in the database, DxN tis the historical battery conductivity performance index of the tth historical monitoring period, α 2 is the conductivity coefficient stored in the database, DjK is the current battery health assessment value of the current monitoring period, DsJ is the current battery attenuation index of the current monitoring period, λ 1 is the current attenuation coefficient stored in the database, DaN is the current battery conductivity performance index during the current monitoring period, and λ 2 is the current conductivity coefficient stored in the database, α 1 +α 2 =1,λ 1 +λ 2 =1,t=1,2,3,…,t 0 , t 0 is the number of historical monitoring periods, and e is a natural constant.

[0009] Furthermore, the specific steps for obtaining the historical battery attenuation index of each historical monitoring period and the current battery attenuation index of the current monitoring period are as follows: read the historical battery voltage value, historical battery current value, historical battery ambient temperature value, and historical battery capacity value in the battery operating status data of each historical monitoring period; and obtain the operating status current baseline value and operating status ambient temperature baseline value of the large cylindrical battery in the operating state; analyze the operating status current baseline value and operating status ambient temperature baseline value of the large cylindrical battery in the operating state and the historical battery current value and historical battery ambient temperature value of each historical monitoring period in combination with the multi-dimensional Euclidean distance method to obtain the historical battery loss index of each historical monitoring period; analyze the historical battery voltage value and historical battery capacity value of each historical monitoring period to obtain the historical battery output power of each historical monitoring period; standardize the historical battery loss index and historical battery output power of each historical monitoring period, and comprehensively analyze the standardized historical battery loss index and historical battery output power of each historical monitoring period to obtain the historical battery attenuation index of each historical monitoring period.

[0010] Furthermore, the specific formula for calculating the historical battery loss index, historical battery output power, and historical battery attenuation index for each historical monitoring period is as follows:

[0011] Where D s,t is the historical battery loss index of the tth historical monitoring period, GzD t is the historical battery current value of the tth historical monitoring period, JzD is the operating current reference value of the large cylindrical battery in the operating state, GzW t is the historical battery ambient temperature value in the tth historical monitoring period, JzW is the operating ambient temperature reference value of the large cylindrical battery in the operating state, DnH tis the historical battery output power in the tth historical monitoring period, GzY t is the historical battery voltage value in the tth historical monitoring period, DcR t is the historical battery capacity value of the tth historical monitoring period, DcS t is the historical battery attenuation index of the tth historical monitoring period, DsJ′ t is the historical battery loss index of the tth historical monitoring period after standardization, β 1 is the loss coefficient stored in the database, DnH′ is the historical battery output power of the tth historical monitoring period after normalization, β 2 is the output coefficient stored in the database, and β 1 +β 2 =1,t=1,2,3,…,t 0 , t 0 is the number of historical monitoring periods, and e is a natural constant.

[0012] Furthermore, the specific steps for obtaining the historical battery conductivity performance index of each historical monitoring period and the current battery conductivity performance index of the current monitoring period are as follows: read the battery internal resistance value, electrolyte concentration value, electrode specific surface area value, and battery porosity value in the battery operation status data of each historical monitoring period; analyze the electrode specific surface area value and battery porosity value of each historical monitoring period to obtain the electrode effective specific surface area value of each historical monitoring period; normalize the electrode effective specific surface area value, battery internal resistance value, and electrolyte concentration value of each historical monitoring period, and perform weighted analysis on the normalized electrode effective specific surface area value, battery internal resistance value, and electrolyte concentration value of each historical monitoring period to obtain the battery conductivity performance index of each historical monitoring period.

[0013] Furthermore, the specific calculation formula for calculating the electrode effective specific surface area value and battery conductivity performance index in each historical monitoring period is as follows: Where, YxBt is the historical electrode effective specific surface area value in the tth historical monitoring period, DbJ t is the historical electrode specific surface area value of the tth historical monitoring period, DkX t is the historical battery porosity value in the tth historical monitoring period, DxN t is the historical battery conductivity performance index of the tth historical monitoring period, YxB′ t is the historical electrode effective specific surface area value of the tth historical monitoring period after normalization, φ 1 is the area coefficient stored in the database, DnZ′ t is the historical battery internal resistance value of the tth historical monitoring period after normalization, φ 2is the internal resistance coefficient stored in the database, DjY′ t is the historical electrolyte concentration value of the tth historical monitoring period after normalization, φ 3 is the concentration coefficient stored in the database, and φ 1 +φ 2 +φ 3 =1,t=1,2,3,…,t 0 , t 0 is the number of historical monitoring periods, and e is a natural constant.

[0014] Furthermore, the specific steps for obtaining the current health change rate of the current period are as follows: the historical battery health assessment value of each historical monitoring period and the current battery health assessment value of the current monitoring period are analyzed by combining the moving exponential average method to obtain the historical battery health smoothing value of each historical monitoring period and the current battery health smoothing value of the current monitoring period; and the historical battery health smoothing value of each historical monitoring period and the current battery health smoothing value of the current monitoring period are analyzed by combining the mean method and the difference method to obtain the current battery health change value of the current monitoring period; wherein, the specific calculation formula for calculating the historical battery health smoothing value of each historical monitoring period and the current battery health smoothing value of the current monitoring period and the current battery health change value is as follows: Among them, JkP t is the historical battery health smoothing value of the tth historical monitoring period, JkZ t is the battery health assessment value of the tth historical monitoring period, JkP t-1 is the historical battery health smoothing value of the t-1th historical monitoring period, DjP is the current battery health smoothing value of the current monitoring period, DJk is the current battery health assessment value of the current monitoring period, For the tth 0 The historical battery health smoothing value of the historical monitoring period, DjC, the current battery health change value of the current monitoring period, JkP t+1 is the historical battery health smoothing value of the t+1th historical monitoring period, t=1, 2, 3, ..., t 0 , t 0 is the number of historical monitoring periods.

[0015] Furthermore, corresponding measures are taken based on the judgment and analysis results: if the current battery health change value of the current monitoring segment is within the preset battery health change range, monitoring continues; if the current battery health change value of the current monitoring segment is outside the preset battery health change range, an alarm is triggered.

[0016] A large cylindrical battery health monitoring system comprises: a data acquisition module, a comprehensive analysis module, an evaluation and analysis module, and a monitoring management module; the data acquisition module is used to continuously acquire historical battery operation status data of several historical monitoring periods and current battery operation data of the current period when the large cylindrical battery is in operation, and perform preprocessing; the comprehensive analysis module is used to respectively perform data analysis on the historical battery operation status data of each historical monitoring period after preprocessing and the current battery operation status data of the current monitoring period, obtain the historical battery attenuation index and the historical battery conductivity index of each historical monitoring period, and the current battery attenuation index and the current battery conductivity index of the current monitoring period, and respectively perform comprehensive analysis to obtain the historical battery health evaluation value of each historical monitoring period and the current battery health evaluation value of the current period; the evaluation and analysis module is used to analyze the historical battery health evaluation values ​​of several historical monitoring periods and the current battery health evaluation value of the current monitoring period, and obtain the current battery health change value of the current monitoring section; the monitoring management module is used to perform judgment analysis on the current battery health change value of the current monitoring section and the preset battery health change range, perform monitoring and evaluation based on the judgment and analysis results, and take corresponding measures.

[0017] The present invention has the following beneficial effects:

[0018] (1) This large cylindrical battery health monitoring method can more accurately reflect the long-term health status of the battery and identify potential trends and problems in a timely manner through systematic analysis of historical data and current data, thereby maintaining stable evaluation results when monitoring in a changing environment, greatly reducing decision-making risks caused by instantaneous fluctuations, and continuously adjusting according to new data to ensure that the monitoring results always reflect the true health status of the battery, thereby maximizing the battery life and reducing maintenance costs.

[0019] (2) The large cylindrical battery health monitoring method adopts a multi-index evaluation system, which can provide a deeper understanding of the overall health of the battery and identify possible risks and problems. For example, when the temperature is abnormal, the corresponding current and voltage data are automatically retrieved for analysis to understand whether the battery is within the safe use range, thereby improving the safety and efficiency of the battery. In addition, regular multi-index evaluations can also provide a reference for the subsequent use of the battery, ensuring that the battery operates in the best condition and thus extending its service life.

[0020] (3) This large cylindrical battery health monitoring method, by introducing the monitoring of the internal state of the battery, can more comprehensively evaluate the health of the battery and identify the root causes of battery performance degradation. That is, it collects electrolyte concentration and porosity data in real time and combines them with external performance indicators for analysis, so as to see the specific causes of battery performance degradation in the overall evaluation. At the same time, through a comprehensive analysis mechanism, it effectively responds to the problem of battery performance degradation, which not only improves the accuracy of monitoring, but also provides an important basis for the optimal design and use management of batteries.

[0021] (4) The large cylindrical battery health monitoring system continuously acquires historical data and current data through the data acquisition module to provide high-frequency data sampling, thereby ensuring the accuracy and completeness of the data. The comprehensive analysis module and the evaluation analysis module systematically evaluate the health status of the battery, combining multiple indicators to provide users with a comprehensive health score, and obtain the battery health change value based on historical data and current data analysis, thereby identifying the battery's health status, performance trends and potential problems. Finally, the monitoring management module stores and manages all monitoring data in a centralized manner. By viewing the current status and historical data of the battery, the long-term performance and health changes of the battery can be evaluated.

[0022] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is a flow chart of a large cylindrical battery health monitoring method of the present invention.

[0024] Figure 2 This is a block diagram of a large cylindrical battery health monitoring system of the present invention. DETAILED DESCRIPTION

[0025] The embodiment of the present application solves the problem that the prior art relies on real-time data, lacks comprehensive analysis of historical data, and is difficult to accurately reflect the long-term health status of the battery, thereby causing misjudgment due to instantaneous data fluctuations. Secondly, the prior art only uses a single health status indicator for evaluation, which makes the health assessment results not comprehensive and scientific enough, ignores multiple performance parameters of the battery, limits the deep understanding of the overall health status of the battery, and increases the decision-making risk of the battery during maintenance and replacement.

[0026] The overall idea of ​​the problem in the embodiment of this application is as follows:

[0027] First, when the large cylindrical battery is in a continuous discharge state, the battery operation status data of several historical monitoring periods and the data of the current period are continuously obtained and preprocessed. Secondly, the preprocessed historical and current battery operation status data are analyzed, and the battery attenuation index and conductive performance index of the historical monitoring period and the corresponding index of the current monitoring period are calculated. Based on these indicators, a comprehensive analysis is performed to obtain the battery health assessment value of each monitoring period. In addition, the battery health assessment values ​​of multiple historical monitoring periods and the assessment values ​​of the current period are analyzed to obtain the health change value of the current monitoring period. Finally, the health change value of the current monitoring period is judged and analyzed with the preset health change range, and corresponding measures are taken according to the judgment and analysis results.

[0028] See also Figure 1 The embodiment of the present invention provides a technical solution: a large cylindrical battery health monitoring method, comprising the following steps: when the large cylindrical battery is in an operating state (i.e., in a continuous discharge state), continuously obtaining historical battery operating state data of several historical monitoring time periods (for example: 10 minutes) and current battery operating state data of the current time period, and performing preprocessing; performing data analysis on the historical battery operating state data of each historical monitoring time period after preprocessing and the current battery operating state data of the current monitoring time period, respectively, to obtain the historical battery attenuation index, the historical battery conductivity performance index of each historical monitoring time period, and the current battery attenuation index, the current battery conductivity performance index of the current monitoring time period, and performing comprehensive analysis respectively, to obtain the historical battery health assessment value of each historical monitoring time period and the current battery health assessment value of the current time period; analyzing the historical battery health assessment values ​​of several historical monitoring time periods and the current battery health assessment value of the current monitoring time period, to obtain the current battery health change value of the current monitoring section; performing judgment and analysis on the current battery health change value of the current monitoring section and the preset battery health change range, performing monitoring and evaluation based on the judgment and analysis results, and taking corresponding measures.

[0029] The historical battery operating status data specifically include the historical battery voltage value, the historical battery current value, the historical battery ambient temperature value, the historical battery internal resistance value, the historical battery capacity value, the historical electrolyte concentration value, the historical electrode specific surface area value, and the historical battery porosity value. The current battery operating status data specifically include the current battery voltage value, the current battery current value, the current battery ambient temperature value, the current battery internal resistance value, the current battery capacity value, the current electrolyte concentration value, the current electrode specific surface area value, and the current battery porosity value.

[0030] Among them, the historical electrolyte concentration value is the sum of the concentrations of active substances in the electrolyte inside the battery (i.e., ions participating in the battery reaction, such as lithium ions, sodium ions, etc.). By using a specific ion selective electrode, the concentration of a certain ion in the electrolyte can be directly measured, and the measured concentrations of ions participating in the battery reaction are summed to obtain the electrolyte concentration value.

[0031] The specific surface area of ​​the electrode is the surface area per unit volume of the electrode material. The specific surface area is calculated by the BET method (i.e., by nitrogen adsorption isotherm experiment, the adsorption amount of the electrode under different pressures is measured and the specific surface area is calculated. The specific surface area of ​​the electrode = [monolayer adsorption amount * Avogadro constant * cross-sectional area of ​​nitrogen molecules (usually about 16.2A 2 )] / molecular weight of electrode material)} is obtained.

[0032] The historical battery porosity value refers to the ratio of the volume of pores (voids) in a material (such as activated carbon, metal oxides, etc.) to the total volume, which is obtained by the mercury intrusion method [i.e., using the intrusiveness of mercury in the material to measure the volume and distribution of the pores, and thus calculate the porosity = (pore volume (total volume of pores in the material) / total volume of the material (including the solid portion and pores)]

[0033] The current electrolyte concentration value is the sum of the concentrations of active substances (i.e., ions participating in the battery reaction, such as lithium ions, sodium ions, etc.) in the electrolyte inside the battery. By using a specific ion selective electrode, the concentration of a certain ion in the electrolyte can be directly measured, and the measured concentrations of ions participating in the battery reaction are summed to obtain the electrolyte concentration value.

[0034] The current electrode specific surface area value is the surface area of ​​the electrode material per unit volume. The specific surface area is calculated by the BET method {i.e., by nitrogen adsorption isotherm experiment, the adsorption amount of the electrode under different pressures is measured and the specific surface area is calculated. The electrode specific surface area value = [monolayer adsorption amount * Avogadro constant * cross-sectional area of ​​nitrogen molecules (usually about 16.2A 2 )] / molecular weight of electrode material)} is obtained.

[0035] The current battery porosity value refers to the ratio of the volume of pores (voids) in a material (such as activated carbon, metal oxides, etc.) to the total volume, which is obtained by the mercury intrusion method [i.e., using the intrusiveness of mercury in the material to measure the volume and distribution of the pores, and thus calculate the porosity = (pore volume (total volume of pores in the material) / total volume of the material (including the solid part and pores)]

[0036] Specifically, the specific formula for calculating the battery health assessment value for each historical monitoring period is as follows: Among them, JkZ t is the historical battery health assessment value of the tth historical monitoring period, DcSt is the historical battery attenuation index of the tth historical monitoring period, α 1 is the attenuation coefficient stored in the database, DxN t is the historical battery conductivity performance index of the tth historical monitoring period, α 2 is the conductivity coefficient stored in the database, DjK is the current battery health assessment value of the current monitoring period, DsJ is the current battery attenuation index of the current monitoring period, λ 1 is the current attenuation coefficient stored in the database, DaN is the current battery conductivity performance index during the current monitoring period, and λ 2 is the current conductivity coefficient stored in the database, α 1 +α 2 =1,λ 1 +λ 2 =1,t=1,2,3,…,t 0 , t 0 is the number of historical monitoring periods, and e is a natural constant, usually 2.71.

[0037] It needs to be explained that α 1 , α 2 The specific acquisition process is: obtain the battery attenuation benchmark index and battery conductivity performance benchmark index of the large cylindrical battery in the operating state, and perform sum analysis to obtain the battery health and value, and perform proportion analysis on the battery attenuation benchmark index and battery conductivity performance benchmark index of the battery in the operating state with the battery health and value respectively, and the proportion analysis result is the corresponding coefficient.

[0038] The battery attenuation benchmark index is obtained in the following way: the historical battery voltage value, historical battery current value, historical battery ambient temperature value, historical battery capacity value and the operating ambient temperature benchmark value and operating current benchmark value of the large cylindrical battery in the operating state are obtained from the battery operating status data of each historical monitoring period, and a comprehensive analysis is performed to obtain the historical battery attenuation index of each historical monitoring period. The comprehensive analysis process is consistent with the historical battery attenuation index of each historical monitoring period. The historical battery attenuation index of each historical monitoring period is analyzed in combination with the mean method to obtain the battery attenuation index mean, which is regarded as the battery attenuation benchmark index.

[0039] The battery conductivity performance benchmark index is obtained by obtaining the historical battery internal resistance value, historical electrolyte concentration value, historical electrode specific surface area value, and historical battery porosity value of each historical monitoring period, and performing a comprehensive analysis to obtain the historical battery conductivity performance index of each historical monitoring period. The comprehensive analysis process is consistent with the historical battery conductivity performance index of each historical monitoring period, and the historical battery conductivity performance index of each historical monitoring period is analyzed in combination with the mean method to obtain the battery conductivity performance index mean, which is regarded as the battery conductivity performance benchmark index.

[0040] λ 1 , 2 The specific acquisition process is: obtain the current battery attenuation index and the current battery conductivity performance index of the large cylindrical battery in the current monitoring period, and perform sum analysis to obtain the current battery health and value of the current period, and perform proportion analysis on the current battery attenuation index and the current battery conductivity performance index of the large cylindrical battery in the current monitoring period with the current battery health and value, and the proportion analysis result is the corresponding coefficient.

[0041] In this implementation, by introducing benchmark indicators of battery attenuation and conductivity, the health status of the battery can be evaluated more comprehensively, and this step takes into account multiple key parameters, making the health assessment more accurate. Secondly, analysis based on real-time monitoring data can timely reflect the true performance of the battery under operating conditions, rather than relying solely on static measurements, thereby better capturing changes in battery performance. At the same time, by introducing coefficients for proportion analysis, data from different monitoring periods can be standardized, making the evaluation results comparable and better able to identify trends and anomalies. Finally, the mean method is used to calculate benchmark indicators, which provides a reference standard for battery health assessment, thereby identifying potential problems in advance and reducing the risk of equipment failures and safety hazards. Moreover, the comprehensive analysis of battery attenuation and conductivity performance indicators not only improves the accuracy of the evaluation, but also provides data support for subsequent optimization and maintenance, making battery management more scientific.

[0042] Specifically, the specific steps for obtaining the historical battery attenuation index of each historical monitoring period and the current battery attenuation index of the current monitoring period are as follows: read the historical battery voltage value, historical battery current value, historical battery ambient temperature value, and historical battery capacity value in the battery operating status data of each historical monitoring period; and obtain the operating status current baseline value and operating status ambient temperature baseline value of the large cylindrical battery in the operating state; combine the multi-dimensional Euclidean distance method to analyze the operating status current baseline value, operating status ambient temperature baseline value of the large cylindrical battery in the operating state and the historical battery current value and historical battery ambient temperature value of each historical monitoring period to obtain the historical battery loss index (i.e., the degree of battery performance attenuation) of each historical monitoring period; analyze the historical battery voltage value and historical battery capacity value of each historical monitoring period to obtain the historical battery output power of each historical monitoring period; standardize the historical battery loss index and historical battery output power of each historical monitoring period, and comprehensively analyze the historical battery loss index and historical battery output power of each historical monitoring period after standardization to obtain the historical battery attenuation index of each historical monitoring period.

[0043] Among them, the current battery attenuation index of the current monitoring period is consistent with the acquisition steps of the historical battery attenuation index of each historical monitoring period, and the calculation formula is also consistent.

[0044] The operating state current reference value of the large cylindrical battery in the operating state is obtained by obtaining the rated current from the technical specifications of the battery provided by the manufacturer, and the rated current is regarded as the operating state current reference value. Here, 3.5A is taken as the operating state current reference value.

[0045] The operating environment temperature reference value of large cylindrical batteries in operation can be obtained by consulting the technical documents or product manuals provided by the battery manufacturer, which will list the recommended operating temperature range of the battery (such as 0°C to 40°C). Here, the median value of the operating temperature range, 20°C, is taken as the operating environment temperature reference value.

[0046] The multi-dimensional Euclidean distance method measures the straight-line distance between two points in space. It is used here to measure the spatial distance between the monitoring point (historical battery current value, historical battery ambient temperature value) and the reference point (operating state current reference value, operating state ambient temperature reference value).

[0047] In this implementation scheme, by reading historical battery voltage, battery current, battery ambient temperature, battery capacity and other data, the battery attenuation can be analyzed in detail, which helps to accurately identify the health status and performance changes of the battery, and provide data support for subsequent maintenance and management. Secondly, by determining the current and ambient temperature reference values ​​of the operating state, the consistency of the analysis is ensured, and the reference values ​​are provided by the manufacturer, which is authoritative and helps to improve the accuracy and reliability of the analysis. At the same time, combined with the multi-dimensional Euclidean distance method, the differences between the historical monitoring data and the current detection data and the reference values ​​can be comprehensively considered, so that the degree of battery performance attenuation can be evaluated more scientifically and accurately, and the performance of the battery under specific environmental conditions can be revealed. The combined analysis of output power and attenuation acceleration index makes it possible to comprehensively evaluate the health status of the battery. In addition, the historical monitoring data is standardized so that the data of different monitoring periods are comparable, which is convenient for analyzing and understanding the changing trend of battery performance. Finally, through the analysis of historical and current monitoring data, potential battery problems can be discovered in time, helping managers to formulate scientific maintenance plans, optimize battery use, and extend their service life.

[0048] Specifically, the specific formula for calculating the historical battery loss index, historical battery output power, and historical battery attenuation index for each historical monitoring period is as follows: Where D s,t is the historical battery loss index of the tth historical monitoring period, GzD t is the historical battery current value of the tth historical monitoring period, JZD is the operating current reference value of the large cylindrical battery in the operating state, GZW t is the historical battery ambient temperature value in the tth historical monitoring period, JZW is the operating ambient temperature reference value of the large cylindrical battery in the operating state, DnH t is the historical battery output power in the tth historical monitoring period, GzY t is the historical battery voltage value in the tth historical monitoring period, DcR t is the historical battery capacity value of the tth historical monitoring period, DcS t is the historical battery attenuation index of the tth historical monitoring period, DsJ′ t is the historical battery loss index of the tth historical monitoring period after standardization, β 1 is the loss coefficient stored in the database, DnH′ is the historical battery output power of the tth historical monitoring period after normalization, β 2 is the output coefficient stored in the database, and β 1 +β 2 =1,t=1,2,3,…,t 0 , t 0 is the number of historical monitoring periods, and e is a natural constant, usually 2.71.

[0049] It needs to be explained that β 1 , β 2 The specific acquisition process is: read the historical battery loss index and historical battery output power of each historical monitoring period after standardization, and perform mean analysis respectively to obtain the historical battery loss index mean and the historical battery output power mean, sum and analyze the historical battery loss index mean and the historical battery output power mean to obtain the historical battery attenuation sum value of each historical monitoring period, and perform proportion analysis on the historical battery loss index mean and the historical battery output power mean and the historical battery attenuation sum value, and the proportion analysis result is the corresponding coefficient.

[0050] Among them, the calculation data of historical battery attenuation index in the tth historical monitoring period is shown in the following table:

[0051] Table 1 Example of historical battery attenuation index calculation data for the tth historical monitoring period (here, the battery model commonly used in electric vehicles is a large cylindrical battery of 18650)

[0052] 1 2 3 4 5 <![CDATA[GzD t ]]> 2.50 2.80 3.20 4.20 2.30 JbXj 3.00 3.00 3.00 3.00 3.00 <![CDATA[GzW t ]]> 25.00 21.00 24.00 15.00 28.00 JZQ 20.00 20.00 20.00 20.00 20.00 <![CDATA[DsJ t ]]> 3.14 0.69 2.45 5.38 4.99 <![CDATA[GzY t ]]> 3.70 4.00 3.80 3.75 3.65 <![CDATA[DcR t ]]> 2.50 1.50 3.00 3.50 2.20 <![CDATA[DnH t ]]> 2.33 1.95 2.52 2.65 2.20 <![CDATA[DsJ′ t ]]> 0.32 0.11 0.29 0.81 0.77 DnH′ 0.47 0.21 0.64 0.73 0.25 <![CDATA[β 1 ]]> 0.48 0.48 0.48 0.48 0.48 <![CDATA[β 2 ]]> 0.42 0.42 0.42 0.42 0.42 <![CDATA[DcS t ]]> 0.51 0.46 0.49 0.59 0.65

[0053] In the table, GzD t is the historical battery current value of the tth historical monitoring period, in amperes; JzD is the operating current reference value of the large cylindrical battery in the operating state, in amperes; GzW t is the historical battery ambient temperature value of the tth historical monitoring period, in degrees Celsius; JzW is the operating ambient temperature reference value of the large cylindrical battery in the operating state, in degrees Celsius; DsJ t is the historical battery loss index of the tth historical monitoring period, GzY t DcR is the historical battery voltage value of the tth historical monitoring period, in volts; t The historical battery capacity value of the tth historical monitoring period, in ampere-hours; DnH t DsJ′ is the historical battery output power in the tth historical monitoring period, in watts; t is the historical battery loss index of the tth historical monitoring period after standardization, DnH′ is the historical battery output power of the tth historical monitoring period after standardization, β 1 is the loss coefficient stored in the database, β 2 is the output coefficient stored in the database, DcS t is the historical battery attenuation index of the tth historical monitoring period.

[0054] The first set of data: the historical battery current value of the first historical monitoring period is: 2.50; the operating current baseline value of the large cylindrical battery in the operating state is: 3.00; the historical battery ambient temperature value of the first historical monitoring period is: 25.00; the operating ambient temperature baseline value of the large cylindrical battery in the operating state is: 20.00; the historical battery loss index of the first historical monitoring period is approximately: 3.14; the historical battery voltage value of the first historical monitoring period is: 3.70; the historical battery capacity value of the first historical monitoring period is: 2.50; the historical battery output power of the first historical monitoring period is approximately: 2.33; the historical battery loss index of the first historical monitoring period after standardization is approximately: 0.32; the historical battery output power of the first historical monitoring period after standardization is approximately: 0.47; the loss coefficient stored in the database is approximately: 0.48; the output coefficient stored in the database is approximately: 0.42; the historical battery attenuation index of the first historical monitoring period is approximately: 0.51.

[0055] The second set of data: the historical battery current value of the first historical monitoring period is: 2.80; the operating current baseline value of the large cylindrical battery in the operating state is: 3.00; the historical battery ambient temperature value of the first historical monitoring period is: 21.00; the operating ambient temperature baseline value of the large cylindrical battery in the operating state is: 20.00; the historical battery loss index of the first historical monitoring period is approximately: 0.69; the historical battery voltage value of the first historical monitoring period is: 4.00; the historical battery capacity value of the first historical monitoring period is: 1.50; the historical battery output power of the first historical monitoring period is approximately: 1.95; the historical battery loss index of the first historical monitoring period after standardization is approximately: 0.11; the historical battery output power of the first historical monitoring period after standardization is approximately: 0.21; the loss coefficient stored in the database is approximately: 0.48; the output coefficient stored in the database is approximately: 0.42; the battery attenuation index of the first historical monitoring period is approximately: 0.46.

[0056] The third set of data: the historical battery current value of the first historical monitoring period is: 3.20; the operating current baseline value of the large cylindrical battery in the operating state is: 3.00; the historical battery ambient temperature value of the first historical monitoring period is: 24.00; the operating ambient temperature baseline value of the large cylindrical battery in the operating state is: 20.00; the historical battery loss index of the first historical monitoring period is approximately: 2.45; the historical battery voltage value of the first historical monitoring period is: 3.80; the historical battery capacity value of the first historical monitoring period is: 3.00; the historical battery output power of the first historical monitoring period is approximately: 2.52; the historical battery loss index of the first historical monitoring period after standardization is approximately: 0.29; the historical battery output power of the first historical monitoring period after standardization is approximately: 0.64; the loss coefficient stored in the database is approximately: 0.48; the output coefficient stored in the database is approximately: 0.42; the battery attenuation index of the first historical monitoring period is approximately: 0.49.

[0057] The fourth set of data: the historical battery current value of the first historical monitoring period is: 4.20; the operating current baseline value of the large cylindrical battery in the operating state is: 3.00; the historical battery ambient temperature value of the first historical monitoring period is: 15.00; the operating ambient temperature baseline value of the large cylindrical battery in the operating state is: 20.00; the historical battery loss index of the first historical monitoring period is approximately: 5.38; the historical battery voltage value of the first historical monitoring period is: 3.75; the historical battery capacity value of the first historical monitoring period is: 3.50; the historical battery output power of the first historical monitoring period is approximately: 2.65; the historical battery loss index of the first historical monitoring period after standardization is approximately: 0.81; the historical battery output power of the first historical monitoring period after standardization is approximately: 0.73; the loss coefficient stored in the database is approximately: 0.48; the output coefficient stored in the database is approximately: 0.42; the battery attenuation index of the first historical monitoring period is approximately: 0.59.

[0058] The fifth set of data: the historical battery current value of the first historical monitoring period is: 2.30; the operating current baseline value of the large cylindrical battery in the operating state is: 3.00; the historical battery ambient temperature value of the first historical monitoring period is: 28.00; the operating ambient temperature baseline value of the large cylindrical battery in the operating state is: 20.00; the historical battery loss index of the first historical monitoring period is approximately: 4.99; the historical battery voltage value of the first historical monitoring period is: 3.65; the historical battery capacity value of the first historical monitoring period is: 2.20; the historical battery output power of the first historical monitoring period is approximately: 2.20; the historical battery loss index of the first historical monitoring period after standardization is approximately: 0.77; the historical battery output power of the first historical monitoring period after standardization is approximately: 0.25; the loss coefficient stored in the database is approximately: 0.48; the output coefficient stored in the database is approximately: 0.42; the battery attenuation index of the first historical monitoring period is approximately: 0.65.

[0059] In this implementation scheme, a clear formula is established to evaluate the health status of the battery, so that the analysis results are more credible and can provide a scientific basis for battery performance management. The standardized data is used for calculation, so that the data of different monitoring periods are comparable, so that the battery loss index, output power and overall health indicators can be directly quantified through data, which is convenient for monitoring and analysis. Secondly, through the gradual accumulation and analysis of historical monitoring data, the changing trend of battery performance can be identified, and potential problems can be discovered in time, so as to take measures before the problem worsens to improve the efficiency and safety of battery use. The calculation of the loss coefficient and output coefficient involved in the formula ensures that the decision is based on the results of historical data analysis, not empirical judgment, which helps to improve the scientificity and effectiveness of management. Finally, by summing and analyzing the battery loss index and output power of each historical monitoring period, the overall performance of the battery under different conditions can be fully understood. At the same time, by regularly calculating the attenuation acceleration index and output power, preventive maintenance can be performed before the battery reaches a critical attenuation level, thereby reducing unexpected failures and downtime and improving the reliability and stability of the system.

[0060] Specifically, the specific steps for obtaining the historical battery conductivity performance index of each historical monitoring period and the current battery conductivity performance index of the current monitoring period are as follows: read the battery internal resistance value, electrolyte concentration value, electrode specific surface area value, and battery porosity value in the battery operation status data of each historical monitoring period; analyze the electrode specific surface area value and battery porosity value of each historical monitoring period to obtain the electrode effective specific surface area value (i.e., the surface area of ​​the electrode material actually participating in the electrochemical reaction) of each historical monitoring period; normalize the electrode effective specific surface area value, battery internal resistance value, and electrolyte concentration value of each historical monitoring period, and perform weighted analysis on the normalized electrode effective specific surface area value, battery internal resistance value, and electrolyte concentration value of each historical monitoring period to obtain the battery conductivity performance index of each historical monitoring period.

[0061] The current battery conductivity performance index of the current monitoring period is obtained in accordance with the same steps as the historical battery conductivity performance index of each historical monitoring period, and the calculation formula is also the same.

[0062] In this embodiment, by reading the battery internal resistance value, electrolyte concentration value, electrode specific surface area value and battery porosity value, the battery's conductive performance can be comprehensively evaluated, and the key indicators of the battery's conductive ability in actual operation are provided, which helps to identify potential performance problems. In addition, by analyzing the electrode specific surface area and porosity, the electrode effective specific surface area value is obtained, which helps to understand the surface area actually involved in the electrochemical reaction, thereby revealing the performance of battery materials under different working conditions and optimizing battery design and material selection. Secondly, by normalizing the historical monitoring data, the influence caused by different dimensions can be eliminated, making the data of different monitoring periods more comparable, ensuring that the data under different states can be directly compared and analyzed. In addition, the steps for obtaining the conductive performance index of the current monitoring period are consistent with the historical monitoring period, which makes the data analysis and comparison coherent, and helps to track the changes in the battery's conductive performance and provide reliable data support. Finally, through the analysis of the conductive performance index, managers can promptly identify the performance degradation of the battery, thereby performing necessary maintenance and adjustments, thereby improving the efficiency and accuracy of battery management.

[0063] Specifically, the specific calculation formula for calculating the electrode effective specific surface area value and battery conductivity performance index in each historical monitoring period is as follows: Where, YxBt is the historical electrode effective specific surface area value in the tth historical monitoring period, DbJ t is the historical electrode specific surface area value of the tth historical monitoring period, DkX t is the historical battery porosity value in the tth historical monitoring period, DxN t is the historical battery conductivity performance index of the tth historical monitoring period, YxB′t is the historical electrode effective specific surface area value of the tth historical monitoring period after normalization, φ 1 is the area coefficient stored in the database, DnZ′ t is the historical battery internal resistance value of the tth historical monitoring period after normalization, φ 2 is the internal resistance coefficient stored in the database, DjY′ t is the historical electrolyte concentration value of the tth historical monitoring period after normalization, φ 3 is the concentration coefficient stored in the database, and φ 1 +φ 2 +φ 3 =1,t=1,2.3,…,t 0 , t 0 is the number of historical monitoring periods, and e is a natural constant, usually 2.71.

[0064] It needs to be explained that φ 1 ,φ 2 ,φ 3 The specific acquisition process of is: read the historical electrode effective specific surface area value, historical battery internal resistance value, and historical electrolyte concentration value of each historical monitoring period after normalization, perform mean analysis respectively, and obtain the historical electrode effective specific surface area mean value, historical battery internal resistance mean value, and historical electrolyte concentration mean value after normalization, and perform sum analysis to obtain the historical battery conductivity sum value, and perform proportion analysis on the historical electrode effective specific surface area mean value, historical battery internal resistance mean value, and historical electrolyte concentration mean value after normalization and the historical battery conductivity sum value, and the proportion analysis result is the corresponding coefficient.

[0065] In this embodiment, by normalizing the electrode effective specific surface area, internal resistance and electrolyte concentration values, the influence of different dimensions can be eliminated, which helps to track the changing trend of battery performance, and combines multiple important parameters (such as electrode effective specific surface area, internal resistance and electrolyte concentration) in the calculation process, so that the evaluation of conductivity is more comprehensive, and at the same time, the specific impact of each factor on battery performance is revealed, which helps to optimize battery design and use. Secondly, the coefficient obtained by proportion analysis can provide important information for further analysis of battery performance, so that managers can quickly identify performance advantages and disadvantages and formulate corresponding maintenance and management strategies. Regular calculation of conductivity performance indicators can reflect the status changes of the battery in real time, which helps to detect battery problems in time, reduce the risk of failure, and extend battery life. Finally, the natural constants and coefficient settings in the formula make the formula flexible and can be adjusted and optimized according to different application scenarios and battery characteristics, providing broad space for future research and application.

[0066] Specifically, the specific steps for obtaining the current health change rate in the current period are as follows:

[0067] Combined with the moving exponential average method, the historical battery health assessment value of each historical monitoring period and the current battery health assessment value of the current monitoring period are analyzed to obtain the historical battery health smoothing value of each historical monitoring period and the current battery health smoothing value of the current monitoring period;

[0068] The mean method and the difference method are combined to analyze the changes of the historical battery health smoothed value of each historical monitoring period and the current battery health smoothed value of the current monitoring period to obtain the current battery health change value of the current monitoring period;

[0069] The specific calculation formulas for calculating the historical battery health smoothing value of each historical monitoring period and the current battery health smoothing value and current battery health change value of the current monitoring period are as follows: Among them, JkP t is the historical battery health smoothing value of the tth historical monitoring period, JkZ t is the battery health assessment value of the tth historical monitoring period, JkP t-1 is the historical battery health smoothing value of the t-1th historical monitoring period, DjP is the current battery health smoothing value of the current monitoring period, DJk is the current battery health assessment value of the current monitoring period, For the tth 0 The historical battery health smoothing value of the historical monitoring period, DjC, the current battery health change value of the current monitoring period, JkP t+1 is the historical battery health smoothing value of the t+1th historical monitoring period, t=1, 2, 3, ..., t 0 , t 0 is the number of historical monitoring periods.

[0070] In this implementation scheme, by reading the battery operating status data of each historical and current monitoring period, combined with core parameters such as voltage, capacity, and internal resistance, the health status of the battery can be monitored in real time. The monitoring process not only collects data, but also analyzes the long-term change trend of battery performance by calculating indicators such as smoothing values ​​and change values. Secondly, calculating the health smoothing value is a method to eliminate noise and short-term fluctuations in monitoring data. The smoothing value can be obtained from data of multiple historical periods, which provides a stable basis for evaluating the long-term health status of the battery, thereby enhancing the accuracy of real-time data and providing a more coherent trend analysis. In addition, the calculation of the current battery health change value helps to identify sudden changes or gradual declines in battery performance, and by continuously monitoring and calculating the health change value in real time, it can be warned before serious problems occur in the battery, so that maintenance measures can be taken in the early stage of the problem to avoid battery failure or short life. Finally, the monitoring of historical battery attenuation indicators helps to evaluate the performance degradation rate of the battery in long-term use, especially under different ambient temperature and current reference conditions. The multi-dimensional Euclidean distance method is used to compare and quantify the performance attenuation of the battery. At the same time, by monitoring the attenuation acceleration index of different historical periods, the change law of battery performance over time can be discovered, and the future battery attenuation can be predicted.

[0071] Specifically, corresponding measures are taken based on the judgment and analysis results: if the current battery health change value of the current monitoring segment is within the preset battery health change range, monitoring will continue, and based on the monitoring results, all monitoring data will be recorded for subsequent analysis and trend identification to ensure timely response to future changes; if the current battery health change value of the current monitoring segment is outside the preset battery health change range, an alarm will be triggered to notify relevant personnel to conduct emergency inspections to ensure safety, and at the same time a monitoring abnormality report will be sent to relevant personnel, recording the abnormal situation and measures taken in detail, conducting cause analysis, and formulating corresponding improvement plans to avoid similar problems from happening again.

[0072] In this implementation, by determining in real time whether the battery health change value is within a preset range, the battery health status can be accurately grasped. If the battery status is normal, daily monitoring and adjustment will continue. This dynamic monitoring and management method can optimize the battery use strategy, reasonably allocate the battery load, and thus extend the battery life. When the monitoring results show that the battery health change value deviates from the preset range, an alarm is immediately triggered and the relevant personnel are notified, thereby ensuring that the problem is discovered at an early stage, thereby preventing more serious failures or accidents from occurring. Through timely response, unnecessary downtime and high maintenance costs can be avoided. Secondly, according to the monitoring results, the battery load and strategy can be adjusted to avoid battery overload operation or over-limit use, thereby extending the battery life. All monitoring data are recorded, trend analysis and abnormal situation reports are conducted, which can provide long-term data support for battery management. These data can be used for historical review, pattern recognition and future trend prediction, helping to improve management strategies, thereby further optimizing battery use and maintenance. Finally, by triggering alarms and conducting emergency inspections, safety risks caused by excessive battery degradation or damage can be effectively prevented, abnormal situations can be handled in a timely manner, the safety of batteries and related equipment can be ensured, and serious accidents such as system crashes or fires caused by battery failures can be avoided. At the same time, through the automated monitoring system, when there is a problem with the battery health status, a quick response can be made, reducing manual intervention and reaction time, and improving the efficiency and accuracy of monitoring.

[0073] See also Figure 2 The embodiment of the present invention provides a technical solution: a large cylindrical battery health monitoring system, comprising: a data acquisition module, a comprehensive analysis module, an evaluation and analysis module, and a monitoring management module; the data acquisition module is used to continuously acquire the historical battery operation status data of several historical monitoring periods and the current battery operation data of the current period when the large cylindrical battery is in operation, and perform preprocessing; the comprehensive analysis module is used to perform data analysis on the historical battery operation status data of each historical monitoring period after preprocessing and the current battery operation status data of the current monitoring period, respectively, to obtain the historical battery attenuation index, the historical battery conductivity index of each historical monitoring period, and the current battery attenuation index and the current battery conductivity index of the current monitoring period, and perform comprehensive analysis respectively to obtain the historical battery health evaluation value of each historical monitoring period and the current battery health evaluation value of the current period; the evaluation and analysis module is used to analyze the historical battery health evaluation values ​​of several historical monitoring periods and the current battery health evaluation value of the current monitoring period, and obtain the current battery health change value of the current monitoring section; the monitoring management module is used to judge and analyze the current battery health change value of the current monitoring section with the preset battery health change range, perform monitoring and evaluation based on the judgment and analysis results, and take corresponding measures.

[0074] In summary, this application has at least the following effects:

[0075] Through systematic analysis of historical and current data, the long-term health status of the battery can be more accurately reflected, and potential trends and problems can be identified in a timely manner, so that stable evaluation results can be maintained when monitoring in a changing environment, and the decision-making risks caused by instantaneous fluctuations can be greatly reduced. Continuous adjustments based on new data ensure that the monitoring results always reflect the true health status of the battery, thereby maximizing the battery life and reducing maintenance costs.

[0076] By adopting a multi-indicator evaluation system, we can gain a deeper understanding of the overall health of the battery and identify possible risks and problems. For example, when the temperature is abnormal, the corresponding current and voltage data are automatically retrieved for analysis to understand whether the battery is within the safe use range, thereby improving the safety and efficiency of the battery. In addition, regular multi-indicator evaluations can also provide a reference for the subsequent use of the battery, ensuring that the battery operates in the best condition and thus extending its service life.

[0077] By introducing the monitoring of the internal state of the battery, it is possible to more comprehensively evaluate the health of the battery and identify the root causes of battery performance degradation. That is, the electrolyte concentration and porosity data are collected in real time and combined with external performance indicators for analysis, so that the specific reasons for the battery performance degradation can be seen in the overall evaluation. At the same time, through a comprehensive analysis mechanism, the problem of battery performance degradation can be effectively addressed, which not only improves the accuracy of monitoring, but also provides an important basis for the optimal design and use management of batteries.

[0078] The data acquisition module continuously acquires historical data and current data to provide high-frequency data sampling, thereby ensuring the accuracy and completeness of the data. The comprehensive analysis module and the evaluation analysis module systematically evaluate the health status of the battery, combining multiple indicators to provide users with a comprehensive health score, and obtain the battery health change value based on historical data and current data analysis, thereby identifying the battery's health status, performance trends and potential problems. Finally, the monitoring management module stores and manages all monitoring data in a centralized manner. By viewing the current status and historical data of the battery, the long-term performance and health changes of the battery can be evaluated.

[0079] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0080] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for monitoring the health of large cylindrical batteries. It is characterized in that The following steps are involved: When the large cylindrical battery is in operation, the historical battery operation status data of several historical monitoring periods and the current battery operation data of the current period are continuously acquired and pre-processed; Perform data analysis on the historical battery operation status data of each historical monitoring period after preprocessing and the current battery operation status data of the current monitoring period, respectively, to obtain the historical battery attenuation index and the historical battery conductivity performance index of each historical monitoring period and the current battery attenuation index and the current battery conductivity performance index of the current monitoring period, and perform comprehensive analysis to obtain the historical battery health assessment value of each historical monitoring period and the current battery health assessment value of the current period; Analyze the historical battery health assessment values ​​of several historical monitoring periods and the current battery health assessment value of the current monitoring period to obtain the current battery health change value of the current monitoring period; The current battery health change value of the current monitoring segment is compared with the preset battery health change range, and monitoring and evaluation are performed based on the judgment and analysis results, and corresponding measures are taken.

2. The large cylindrical battery health monitoring method according to claim 1, It is characterized in that The historical battery operating status data specifically includes historical battery voltage values, historical battery current values, historical battery ambient temperature values, historical battery internal resistance values, historical battery capacity values, historical electrolyte concentration values, historical electrode specific surface area values, and historical battery porosity values; the current battery operating status data specifically includes current battery voltage value, current battery current value, current battery ambient temperature value, current battery internal resistance value, current battery capacity value, current electrolyte concentration value, current electrode specific surface area value, and current battery porosity value.

3. The large cylindrical battery health monitoring method according to claim 1, It is characterized in that The specific formula for calculating the battery health assessment value for each historical monitoring period is as follows: Among them, JkZ t is the historical battery health assessment value of the tth historical monitoring period, DcS t is the historical battery attenuation index of the tth historical monitoring period, α 1 is the attenuation coefficient stored in the database, DxN t is the historical battery conductivity performance index of the tth historical monitoring period, α 2 is the conductivity coefficient stored in the database, DjK is the current battery health assessment value of the current monitoring period, DsJ is the current battery attenuation index of the current monitoring period, λ 1 is the current attenuation coefficient stored in the database, DaN is the current battery conductivity performance index during the current monitoring period, and λ 2 is the current conductivity coefficient stored in the database, α 1 +α 2 =1,λ 1 +λ 2 =1,t=1,2,3,…,t 0 , t 0 is the number of historical monitoring periods, and e is a natural constant.

4. The large cylindrical battery health monitoring method according to claim 2, It is characterized in that The specific steps for obtaining the historical battery attenuation index of each historical monitoring period and the current battery attenuation index of the current monitoring period are as follows: Read the historical battery voltage value, historical battery current value, historical battery ambient temperature value, and historical battery capacity value in the battery operating status data of each historical monitoring period; And obtain the operating state current reference value and operating state ambient temperature reference value of the large cylindrical battery in the operating state; Combined with the multi-dimensional Euclidean distance method, the operating state current baseline value, operating state ambient temperature baseline value, and the historical battery current value and historical battery ambient temperature value of each historical monitoring period of the large cylindrical battery under the operating state are analyzed to obtain the historical battery loss index of each historical monitoring period; Analyze the historical battery voltage value and the historical battery capacity value of each historical monitoring period to obtain the historical battery output power of each historical monitoring period; The historical battery loss index and the historical battery output power of each historical monitoring period are standardized, and the standardized historical battery loss index and the historical battery output power of each historical monitoring period are comprehensively analyzed to obtain the historical battery attenuation index of each historical monitoring period.

5. The large cylindrical battery health monitoring method according to claim 4, It is characterized in that The specific formula for calculating the historical battery loss index, historical battery output power, and historical battery attenuation index for each historical monitoring period is as follows: Among them, DsJ t is the historical battery loss index of the tth historical monitoring period, G Z D t is the historical battery current value of the tth historical monitoring period, J Z D is the operating current reference value of the large cylindrical battery in the operating state, G Z W t is the historical battery ambient temperature value in the tth historical monitoring period, J Z W is the operating ambient temperature reference value of the large cylindrical battery in operation, DnH t is the historical battery output power in the tth historical monitoring period, G Z Y t is the historical battery voltage value in the tth historical monitoring period, DcR t is the historical battery capacity value of the tth historical monitoring period, DcS t is the historical battery attenuation index of the tth historical monitoring period, DsJ′ t is the historical battery loss index of the tth historical monitoring period after standardization, β 1 is the loss coefficient stored in the database, DnH′ is the historical battery output power of the tth historical monitoring period after normalization, β 2 is the output coefficient stored in the database, and β 1 +β 2 =1,t=1.2.3,…,t 0 , t 0 is the number of historical monitoring periods, and e is a natural constant.

6. The large cylindrical battery health monitoring method according to claim 2, It is characterized in that The specific steps for obtaining the historical battery conductivity performance index of each historical monitoring period and the current battery conductivity performance index of the current monitoring period are as follows: Read the battery internal resistance value, electrolyte concentration value, electrode specific surface area value, and battery porosity value in the battery operation status data of each historical monitoring period; The electrode specific surface area value and battery porosity value of each historical monitoring period are analyzed to obtain the electrode effective specific surface area value of each historical monitoring period; The electrode effective specific surface area value, battery internal resistance value, and electrolyte concentration value of each historical monitoring period are normalized, and the normalized electrode effective specific surface area value, battery internal resistance value, and electrolyte concentration value of each historical monitoring period are weighted analyzed to obtain the battery conductivity performance index of each historical monitoring period.

7. The large cylindrical battery health monitoring method according to claim 6, It is characterized in that The specific calculation formula for calculating the electrode effective specific surface area value and battery conductivity performance index for each historical monitoring period is as follows: Among them, YxB t is the historical electrode effective specific surface area value in the tth historical monitoring period, DbJ t is the historical electrode specific surface area value of the tth historical monitoring period, DkX t is the historical battery porosity value in the tth historical monitoring period, DxN t is the historical battery conductivity performance index of the tth historical monitoring period, YxB′ t is the historical electrode effective specific surface area value of the tth historical monitoring period after normalization, φ 1 is the area coefficient stored in the database, DnZ′ t is the historical battery internal resistance value of the tth historical monitoring period after normalization, φ 2 is the internal resistance coefficient stored in the database, DjY′ t is the historical electrolyte concentration value of the tth historical monitoring period after normalization, φ 3 is the concentration coefficient stored in the database, and φ 1 +φ 2 +φ 3 =1, t=1, 2.3…, t 0 , t 0 is the number of historical monitoring periods, and e is a natural constant.

8. The large cylindrical battery health monitoring method according to claim 1, It is characterized in that The specific steps to obtain the current health change rate of the current period are as follows: Combined with the moving exponential average method, the historical battery health assessment value of each historical monitoring period and the current battery health assessment value of the current monitoring period are analyzed to obtain the historical battery health smoothing value of each historical monitoring period and the current battery health smoothing value of the current monitoring period; The mean method and the difference method are combined to analyze the changes of the historical battery health smoothed value of each historical monitoring period and the current battery health smoothed value of the current monitoring period to obtain the current battery health change value of the current monitoring period; The specific calculation formulas for calculating the historical battery health smoothing value of each historical monitoring period and the current battery health smoothing value and current battery health change value of the current monitoring period are as follows: Among them, JkP t is the historical battery health smoothing value of the tth historical monitoring period, JkZ t is the battery health assessment value of the tth historical monitoring period, JkP t-1 is the historical battery health smoothing value of the t-1th historical monitoring period, DjP is the current battery health smoothing value of the current monitoring period, DJk is the current battery health assessment value of the current monitoring period, For the tth 0 The historical battery health smoothing value of the historical monitoring period, DjC, the current battery health change value of the current monitoring period, JkP t+1 is the historical battery health smoothing value of the t+1th historical monitoring period, t=1, 2, 3, ..., t 0 , t 0 is the number of historical monitoring periods.

9. The large cylindrical battery health monitoring method according to claim 1, It is characterized in that Take corresponding measures based on the judgment and analysis results: If the current battery health change value of the current monitoring segment is within the preset battery health change range, continue monitoring; If the current battery health change value of the current monitoring segment is outside the preset battery health change range, an alarm is triggered.

10. A large cylindrical battery health monitoring system, using the large cylindrical battery health monitoring method according to any one of claims 1 to 9, It is characterized in that include: Data acquisition module, comprehensive analysis module, evaluation and analysis module, monitoring and management module; The data acquisition module is used to continuously acquire historical battery operation status data of several historical monitoring periods and current battery operation data of the current period when the large cylindrical battery is in operation, and perform preprocessing; The comprehensive analysis module is used to perform data analysis on the historical battery operation status data of each historical monitoring period after preprocessing and the current battery operation status data of the current monitoring period, respectively, to obtain the historical battery attenuation index and the historical battery conductivity performance index of each historical monitoring period and the current battery attenuation index and the current battery conductivity performance index of the current monitoring period, and to perform comprehensive analysis respectively to obtain the historical battery health assessment value of each historical monitoring period and the current battery health assessment value of the current period; The evaluation and analysis module is used to analyze the historical battery health evaluation values ​​of several historical monitoring periods and the current battery health evaluation value of the current monitoring period to obtain the current battery health change value of the current monitoring period; The monitoring management module is used to judge and analyze the current battery health change value of the current monitoring section and the preset battery health change range, perform monitoring and evaluation based on the judgment and analysis results, and take corresponding measures.

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