Large cylindrical battery capacity estimation method and system

Abstract

The invention discloses a large cylindrical battery capacity estimation method and system, and relates to the technical field of battery capacity estimation. According to the method for estimating the capacity of the large cylindrical battery, the historical operation state data and the current operation state data of the large cylindrical battery are obtained, and comprehensive analysis is carried out to obtain a capacity fading rate index, a battery temperature influence index, a battery passing current influence index and a battery discharge depth influence index; according to the method, the historical and current operation data of the large cylindrical battery, such as charge-discharge cycle times, internal resistance, temperature and current data, are collected and analyzed, the capacity fading rate index and other influence indexes of the battery are calculated by integrating the factors, and the battery capacity estimation value of the large cylindrical battery is analyzed by combining the initial capacity value of the battery. Therefore, the future performance and the attenuation trend of the battery can be accurately predicted, more accurate battery health state evaluation is provided, making of a more effective maintenance strategy is supported, unnecessary battery replacement is avoided, and the service life of the battery is prolonged.

Description

Technical Field

[0001] The present invention relates to the technical field of battery capacity estimation, and in particular to a method and system for estimating the capacity of a large cylindrical battery. Background Art

[0002] In the field of battery technology, especially in the application of large cylindrical batteries, accurate estimation of battery capacity is crucial. Battery capacity estimation is not only related to the effective management and use of batteries, but also directly affects the performance and reliability of battery-powered systems. Battery capacity, that is, the maximum amount of electricity that a battery can store when fully charged, is an important indicator for measuring battery performance.

[0003] With the rapid development of renewable energy technology and electric vehicles, large cylindrical batteries are widely used due to their high energy density and long service life. However, the battery will gradually decay during use, and its capacity will decrease due to many factors, including the number of charge and discharge cycles, battery temperature, current size and discharge depth. Therefore, being able to accurately estimate the current capacity of the battery is crucial for battery maintenance, scheduling and life prediction.

[0004] Prior art, such as the battery capacity estimation method and system disclosed in the invention patent application with publication number: CN113125983B, the method includes, in a computerized processor, monitoring a sensor that is operable to collect data about a battery, determining a voltage-based state of charge of the battery based on data from the sensor, determining a capacity degradation value of the battery based on data from the sensor, determining an integrated current value by coulomb counting based on data from the sensor, determining a predicted battery state of charge of the battery based on the capacity degradation value and the integrated current value, using a Kalman filter to process the voltage-based state of charge and the predicted battery state of charge to generate an updated total battery capacity estimation result, and using the updated total battery capacity estimation result to control battery management.

[0005] Based on the above solution, it is found that the limitations of the existing technology include at least the following problems: the existing battery capacity estimation method usually relies on a single data point or only collects data in a short period of time, and fails to fully utilize the long-term cumulative effect of historical operating data and current operating data, which easily leads to changes in battery performance, especially under extreme or changing conditions of use. It is difficult to accurately reflect the actual capacity, which in turn affects the efficiency and life assessment of the battery, resulting in waste of resources and insufficient energy management. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides a method and system for estimating the capacity of a large cylindrical battery, which solves the problem that the existing battery capacity estimation methods usually rely on a single data point or only collect data in a short period of time, but fail to fully utilize the long-term cumulative effect of historical operating data and current operating data, which easily leads to changes in battery performance, especially in extreme or changing conditions of use. It is difficult to accurately reflect the actual capacity, which in turn affects the efficiency and life evaluation of the battery, resulting in waste of resources and insufficient energy management.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: a large cylindrical battery capacity estimation method, comprising the following steps: obtaining historical operating status data, current operating status data and battery initial capacity value of a large cylindrical battery, the historical operating status data including historical battery attenuation data, historical battery temperature data, historical battery current data and historical battery discharge depth data, the current operating status data including current battery internal resistance value, current battery internal temperature value, current battery current value and current battery discharge depth value; comprehensively analyzing the historical operating status data and current operating status data of the large cylindrical battery to obtain the capacity attenuation rate index, battery temperature influence index, battery current influence index and battery discharge depth influence index of the large cylindrical battery; comprehensively analyzing the battery initial capacity value of the large cylindrical battery with the capacity attenuation rate index, battery temperature influence index, battery current influence index and battery discharge depth influence index to obtain the battery capacity estimation value of the large cylindrical battery.

[0008] Furthermore, the historical battery attenuation data specifically includes the number of historical completed charge and discharge cycles and the historical battery internal resistance value at each historical time point in each historical use; the historical battery temperature data specifically includes the historical battery internal temperature value at each historical time point in each historical use; the historical battery current data specifically includes the historical battery current value at each historical time point in each historical use; and the historical battery discharge depth data specifically includes the historical battery discharge depth value after each historical use.

[0009] Furthermore, the specific formula for calculating the estimated value of the battery capacity of the large cylindrical battery is as follows: RgS=CsR*SjZ*WdZ*TgZ*FsZ; wherein RgS is the estimated value of the battery capacity of the large cylindrical battery, CsR is the initial capacity value of the battery of the large cylindrical battery, SjZ is the capacity attenuation rate index of the large cylindrical battery, WdZ is the battery temperature influence index of the large cylindrical battery, TgZ is the battery through current influence index of the large cylindrical battery, and FsZ is the battery discharge depth influence index of the large cylindrical battery.

[0010] Furthermore, the specific steps for obtaining the capacity decay rate index of the large cylindrical battery are as follows: obtaining a reference value for the number of charge and discharge cycles of the large cylindrical battery; performing a mean analysis on the historical battery internal resistance values ​​at each historical time point in each historical use of the large cylindrical battery to obtain a historical battery internal resistance reference value of the large cylindrical battery; performing a comprehensive analysis on the historical battery internal resistance reference value of the large cylindrical battery, the current battery internal resistance value, the number of historical completed charge and discharge cycles, and the reference value of the number of charge and discharge cycles to obtain the capacity decay rate index of the large cylindrical battery.

[0011] Furthermore, the specific formula for calculating the historical battery internal resistance reference value and capacity decay rate index of large cylindrical batteries is as follows: Among them, LnJ is the historical battery internal resistance reference value of large cylindrical batteries, LnZ iu is the historical battery internal resistance value of the large cylindrical battery at the u-th time point in the historical i-th use, i = 1, 2, 3, ..., i0, i0 is the historical number of uses, u = 1, 2, 3, ..., u0, u0 is the number of historical time points, SjZ is the capacity decay rate index of the large cylindrical battery, e is a natural constant, DqN is the current battery internal resistance value of the large cylindrical battery, α is the internal resistance influence coefficient stored in the database, YfX is the number of historical completed charge and discharge cycles of the large cylindrical battery, FxC is the reference value of the number of charge and discharge cycles of the large cylindrical battery, and β is the charge and discharge cycle number influence coefficient stored in the database.

[0012] Furthermore, the specific steps for obtaining the battery temperature influence index of the large cylindrical battery are as follows: performing a mean analysis on the historical battery internal temperature values ​​at each historical time point in each historical use of the large cylindrical battery to obtain the historical battery internal temperature reference value of the large cylindrical battery; performing a comprehensive analysis on the historical battery internal temperature reference value and the current battery internal temperature value of the large cylindrical battery to obtain the battery temperature influence index of the large cylindrical battery.

[0013] Furthermore, the specific formula for calculating the historical battery internal temperature reference value and battery temperature influence index of the large cylindrical battery is as follows: Where LWJ is the historical battery internal temperature reference value of large cylindrical batteries, LnW iu is the historical battery internal temperature value at the u-th time point in the historical i-th use of the large cylindrical battery, i = 1.2, 3, ..., i0, i0 is the number of historical uses, u = 1, 2, 3, ..., u0, u0 is the number of historical time points, WdZ is the battery temperature influence index of the large cylindrical battery, e is a natural constant, DqW is the current battery internal temperature value of the large cylindrical battery, and δ is the temperature influence coefficient stored in the database.

[0014] Furthermore, the specific steps of obtaining the battery current influence index of the large cylindrical battery are as follows: comparatively analyzing the historical battery current values ​​at each time point in each historical use of the large cylindrical battery to obtain the historical maximum battery current of the large cylindrical battery; comprehensively analyzing the historical maximum battery current of the large cylindrical battery and the current battery current value to obtain the battery current influence index of the large cylindrical battery, and the calculation formula is as follows: Among them, TgZ is the battery current influence index of the large cylindrical battery, DqD is the current battery current value of the large cylindrical battery, LtD Max is the historical maximum value of the battery through-current of the large cylindrical battery, and ω is the through-current influence coefficient stored in the database.

[0015] Furthermore, the specific steps for obtaining the battery discharge depth influence index of the large cylindrical battery are as follows: performing mean analysis on the historical battery discharge depth values ​​after each use of the large cylindrical battery to obtain the historical battery discharge depth reference value of the large cylindrical battery; performing comprehensive analysis on the historical battery discharge depth reference value and the current battery discharge depth value of the large cylindrical battery to obtain the battery discharge depth influence index of the large cylindrical battery; wherein, the specific formula for calculating the historical battery discharge depth reference value and the battery discharge depth influence index of the large cylindrical battery is as follows: Where LfC is the historical battery discharge depth reference value of large cylindrical batteries, LfS i is the historical battery discharge depth value of the large cylindrical battery after the i-th use in history, i = 1.2.3, ..., i0, i0 is the number of historical uses, FsZ is the battery discharge depth influence index of the large cylindrical battery, DqF is the current battery discharge depth value of the large cylindrical battery, and θ is the discharge depth influence coefficient stored in the database.

[0016] A large cylindrical battery capacity estimation system comprises: a data acquisition module, an index analysis module, and a capacity estimation module; the data acquisition module is used to acquire historical operating status data, current operating status data, and initial battery capacity value of the large cylindrical battery, the historical operating status data comprises historical battery attenuation data, historical battery temperature data, historical battery current data, and historical battery discharge depth data, and the current operating status data comprises current battery internal resistance value, current battery internal temperature value, current battery current value, and current battery discharge depth value; the index analysis module is used to comprehensively analyze the historical operating status data and current operating status data of the large cylindrical battery to obtain the capacity attenuation rate index, battery temperature influence index, battery current influence index, and battery discharge depth influence index of the large cylindrical battery; the capacity estimation module is used to comprehensively analyze the initial battery capacity value of the large cylindrical battery with the capacity attenuation rate index, battery temperature influence index, battery current influence index, and battery discharge depth influence index to obtain the battery capacity estimation value of the large cylindrical battery.

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

[0018] (1) This large cylindrical battery capacity estimation method collects and analyzes the historical and current operating data of the large cylindrical battery, such as the number of charge and discharge cycles, internal resistance, temperature, and current data, and combines these factors to calculate the battery's capacity decay rate index and other influencing indexes, thereby helping to accurately predict the battery's future performance and decay trend, and further providing a more accurate battery health status assessment, supporting the formulation of more effective maintenance strategies, avoiding unnecessary battery replacement, and extending battery service life.

[0019] (2) This large cylindrical battery capacity estimation method combines real-time monitoring of the battery's internal temperature and current with historical data analysis to promptly identify trends that may lead to performance degradation or safety risks. For example, by comparing historical and current changes in internal resistance, battery aging or impending failure can be detected early, so that preventive measures can be implemented to prevent the failure from developing to the point where it affects the overall battery system, thereby improving the safety of the battery during use.

[0020] (3) This large cylindrical battery capacity estimation method can accurately calculate and predict the actual capacity and health status of the battery, allowing the energy system to distribute loads more efficiently and reduce energy waste. This is especially true in applications that rely heavily on battery performance, such as electric vehicles and energy storage systems. This method can significantly improve overall energy efficiency.

[0021] (4) The large cylindrical battery capacity estimation system can achieve real-time monitoring and data management of battery performance through the collaborative work of the data acquisition module, index analysis module and capacity estimation module. By automatically collecting historical and current operating status data, it not only improves the efficiency of data processing, but also ensures the integrity and accuracy of the data. Real-time performance monitoring allows the operation and maintenance team to instantly obtain the operating status of the battery, such as increased internal resistance, increased temperature or abnormal current, which are key indicators for predicting battery failure and managing battery health. In addition, this systematic real-time monitoring helps to quickly identify and respond to potential battery problems, thereby reducing downtime and maintenance costs and improving the stability and reliability of the entire energy system.

[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 The present invention is a flow chart of a large cylindrical battery capacity estimation method.

[0024] Figure 2 The present invention is a flowchart of the specific steps for obtaining the capacity decay rate index of a large cylindrical battery in a large cylindrical battery capacity estimation method.

[0025] Figure 3 This is a block diagram of a large cylindrical battery capacity estimation system of the present invention. DETAILED DESCRIPTION

[0026] The embodiments of the present application provide a large cylindrical battery capacity estimation method and system to solve the problem that existing battery capacity estimation methods usually rely on a single data point or only collect data in a short period of time, but fail to fully utilize the long-term cumulative effect of historical operating data and current operating data, which easily leads to changes in battery performance, especially in extreme or changing conditions of use. It is difficult to accurately reflect the actual capacity, which in turn affects the efficiency and life assessment of the battery, resulting in waste of resources and insufficient energy management.

[0027] The overall idea of ​​the problem in the embodiment of this application is as follows:

[0028] At the beginning, the historical operating status data and current operating status data of the large cylindrical battery are collected first, including historical battery attenuation data, battery temperature data, current data, discharge depth data, and current battery internal resistance, internal temperature, current value and discharge depth. Next, the collected historical and current data are comprehensively analyzed. This step aims to extract the capacity attenuation rate index, battery temperature influence index, current influence index and discharge depth influence index from the data to evaluate their specific impact on the battery capacity. Finally, the various influence indices obtained from the analysis are combined with the initial capacity value of the battery to obtain the current capacity estimate of the battery through comprehensive calculation. This value is predicted based on the actual usage status and historical performance of the battery, and can more accurately reflect the current health status and remaining life of the battery.

[0029] See also Figure 1 The embodiment of the present invention provides a technical solution: a method for estimating the capacity of a large cylindrical battery, comprising the following steps: obtaining historical operating status data, current operating status data and initial battery capacity value of a large cylindrical battery, the historical operating status data including historical battery attenuation data, historical battery temperature data, historical battery current data and historical battery discharge depth data, the current operating status data including current battery internal resistance value, current battery internal temperature value, current battery current value and current battery discharge depth value (the discharge depth value of the battery from the beginning of current use to the present); comprehensively analyzing the historical operating status data and current operating status data of the large cylindrical battery to obtain the capacity attenuation rate index, battery temperature influence index, battery current influence index and battery discharge depth influence index of the large cylindrical battery; comprehensively analyzing the initial battery capacity value of the large cylindrical battery with the capacity attenuation rate index, battery temperature influence index, battery current influence index and battery discharge depth influence index to obtain the battery capacity estimation value of the large cylindrical battery.

[0030] The historical battery attenuation data specifically includes the number of historical completed charge and discharge cycles and the historical battery internal resistance value at each historical time point in each historical use; the historical battery temperature data specifically includes the historical battery internal temperature value at each historical time point in each historical use; the historical battery current data specifically includes the historical battery current value at each historical time point in each historical use; the historical battery discharge depth data specifically includes the historical battery discharge depth value after each historical use (i.e., the percentage from full charge to current charge during each discharge).

[0031] Among them, the number of historical completed charge and discharge cycles is obtained through the battery management system (BMS).

[0032] The internal resistance of the battery is obtained by a resistance tester or an impedance meter.

[0033] The internal temperature of the battery is obtained through a thermocouple, thermistor or infrared thermal imager.

[0034] The battery current value is obtained through a Hall effect current sensor or a current transformer.

[0035] The battery discharge depth value is obtained by a fuel gauge or a high-precision voltage measurement device.

[0036] Specifically, the specific formula for calculating the estimated value of the battery capacity of the large cylindrical battery is as follows: RgS=CsR*SjZ*WdZ*TgZ*FsZ; wherein RgS is the estimated value of the battery capacity of the large cylindrical battery, CsR is the initial capacity value of the battery of the large cylindrical battery, SjZ is the capacity attenuation rate index of the large cylindrical battery, WdZ is the battery temperature influence index of the large cylindrical battery, TgZ is the battery through current influence index of the large cylindrical battery, and FSZ is the battery discharge depth influence index of the large cylindrical battery.

[0037] In this embodiment, the formula for calculating the estimated battery capacity of large cylindrical batteries combines the initial battery capacity with multiple key performance indexes (capacity decay rate, temperature effect, current effect, and discharge depth effect), providing a comprehensive perspective to evaluate the actual capacity of the battery. This method enables battery managers to make more accurate usage, maintenance, or replacement decisions based on the current health of the battery. Accurate capacity estimation helps optimize the battery's service life and maintenance plan, ensuring that the battery maximizes its performance under the premise of safety and efficiency. By real-time monitoring and analyzing the impact of battery parameters such as temperature, current, and discharge depth, factors that may cause performance degradation or potential failures can be identified in a timely manner. For example, changes in the temperature impact index may indicate a battery overheating problem, while changes in the current impact index may reflect that the battery's load bearing capacity is decreasing. Timely discovery of these Preventive measures can be taken to avoid battery damage and extend the battery life. Accurate battery capacity estimation can help energy systems optimize their battery charging and discharging strategies to adapt to different operating needs and conditions, thereby improving the energy efficiency of the entire system. For example, by understanding the performance of the battery under different discharge depths and current conditions, the system can adjust its energy allocation strategy to reduce energy waste and improve economic benefits. In addition, this method can also help reduce operational interruptions caused by poor battery performance and ensure business continuity. For sustainable energy systems that rely on batteries (such as electric vehicles and renewable energy storage systems), accurate capacity estimation is the key to ensuring reliable system operation. Through this precise capacity estimation method, it can be ensured that the battery can operate in an optimal state throughout its life cycle, support the widespread application of sustainable energy technologies, and reduce environmental impact.

[0038] Specifically, Figure 2As shown, the specific steps for obtaining the capacity decay rate index of the large cylindrical battery are as follows: obtain the reference value of the number of charge and discharge cycles of the large cylindrical battery, which is directly obtained from the documents provided by the manufacturer; perform mean analysis on the historical battery internal resistance values ​​at each historical time point in each historical use of the large cylindrical battery to obtain the historical battery internal resistance reference value of the large cylindrical battery; perform a comprehensive analysis on the historical battery internal resistance reference value of the large cylindrical battery, the current battery internal resistance value, the historical number of completed charge and discharge cycles, and the reference value of the number of charge and discharge cycles to obtain the capacity decay rate index of the large cylindrical battery.

[0039] The specific formula for calculating the historical battery internal resistance reference value and capacity decay rate index of large cylindrical batteries is as follows: Among them, LnnJ is the historical battery internal resistance reference value of large cylindrical batteries, LnZ iu is the historical battery internal resistance value of the large cylindrical battery at the u-th time point in the historical i-th use, i = 1, 2, 3, ..., i0, i0 is the historical number of uses, u = 1, 2, 3, ..., u0, u0 is the number of historical time points, SjZ is the capacity decay rate index of the large cylindrical battery, e is a natural constant, DqN is the current battery internal resistance value of the large cylindrical battery, α is the internal resistance influence coefficient stored in the database, YfX is the number of historical completed charge and discharge cycles of the large cylindrical battery, FxC is the reference value of the number of charge and discharge cycles of the large cylindrical battery, and β is the charge and discharge cycle number influence coefficient stored in the database.

[0040] It needs to be explained that the specific calculation process of the internal resistance influence coefficient is: (using an internal resistance meter and a battery testing system) periodically measure the internal resistance and remaining capacity of the battery under standard conditions, select a batch of batteries of the same type, regularly record the internal resistance and corresponding capacity of each battery, collect enough data points (for example, measure once every 100 cycles for 1000 cycles), use linear regression to analyze the relationship between the increase in internal resistance and capacity attenuation, determine the slope and intercept of the regression line, and the slope is the internal resistance influence coefficient.

[0041] The specific calculation process of the coefficient of influence of the number of charge and discharge cycles is as follows: charge and discharge the battery, measure its capacity after completing a certain number of cycles, and record the data, for example, measure once every 100 cycles, and use nonlinear regression (which can be an exponential decay model) to analyze the relationship between the number of cycles and the capacity. The attenuation coefficient extracted from the model is the coefficient of influence of the number of charge and discharge cycles.

[0042] In this implementation scheme, by combining comprehensive analysis of historical internal resistance data and charge and discharge cycle numbers, this method can more accurately predict the capacity decay of the battery. By monitoring the changes in internal resistance and the number of charge and discharge cycles, the health status and life of the battery can be accurately evaluated. This evaluation is not only based on a single indicator, but also provides a comprehensive capacity decay perspective through the interaction of multiple influencing factors. The specific formula and calculation process for calculating the historical battery internal resistance reference value and capacity decay rate index of large cylindrical batteries enable the battery maintenance team to develop a more effective preventive maintenance strategy based on the actual use of the battery. By understanding the relationship between the increase in internal resistance and the charge and discharge cycle, it is possible to predict when the battery may need maintenance or replacement, thereby optimizing operating costs and maintenance plans. Planning to prevent battery failure at critical moments. Using this calculation process, the battery management system (BMS) can adjust the monitoring and control strategy of the battery in real time in response to the actual measured changes in internal resistance and charge and discharge efficiency. Such responsiveness ensures that the battery system maintains an optimal balance between efficiency and safety. Especially when the battery is aging or its performance degrades, the system can respond quickly to adjust the charging strategy and load distribution. By accurately calculating the capacity decay rate, the use of the battery can be more in line with its actual performance, avoiding overcharging and discharging and unnecessary energy loss. Accurate capacity estimation allows the energy system to optimize energy distribution according to the actual state of the battery, thereby improving energy efficiency, reducing energy waste caused by battery performance degradation, and reducing overall operating costs.

[0043] Specifically, the specific steps for obtaining the battery temperature impact index of the large cylindrical battery are as follows: perform a mean analysis on the historical battery internal temperature values ​​at each historical time point in each historical use of the large cylindrical battery to obtain the historical battery internal temperature reference value of the large cylindrical battery; perform a comprehensive analysis on the historical battery internal temperature reference value and the current battery internal temperature value of the large cylindrical battery to obtain the battery temperature impact index of the large cylindrical battery.

[0044] The specific formula for calculating the historical battery internal temperature reference value and battery temperature impact index of large cylindrical batteries is as follows: Among them, LwJ is the historical battery internal temperature reference value of large cylindrical batteries, LnW iu is the historical battery internal temperature value at the u-th time point in the historical i-th use of the large cylindrical battery, i = 1, 2, 3, ..., i0, i0 is the historical number of uses, u = 1, 2, 3, ..., u0, u0 is the number of historical time points, WdZ is the battery temperature influence index of the large cylindrical battery, e is a natural constant, DqW is the current battery internal temperature value of the large cylindrical battery, and δ is the temperature influence coefficient stored in the database.

[0045] It needs to be explained that the specific calculation process of the temperature influence coefficient is: measure the battery capacity at different temperatures, for example, measure the battery capacity at multiple temperature points such as 25°C, 35°C, 45°C, collect and record the data, use nonlinear regression to analyze the relationship between temperature and capacity, and extract the influence coefficient, which is the temperature influence coefficient.

[0046] In this embodiment, by analyzing historical and current internal temperature data, the battery temperature impact index obtained can help predict the specific impact of temperature changes on battery performance. This analysis can reveal the actual impact of temperature on battery capacity and life, allowing battery managers to more accurately predict the performance of batteries under different environmental conditions. For example, if it is known that the performance of the battery decreases significantly at high temperatures, measures such as improving the cooling system can be taken to maintain the efficiency and life of the battery. An accurate battery temperature impact index allows battery operators to adjust their usage strategies to adapt to different environmental conditions. For example, when it is predicted that the battery will be more efficient at lower temperatures, the battery can be used preferentially in low temperature environments, or it can be used preferentially in high temperature conditions. Reduce battery load during the period to reduce performance degradation and accelerated aging caused by temperature. By continuously monitoring the battery temperature and analyzing its impact on battery performance, potential safety issues such as overheating can be identified in a timely manner. The real-time update of the battery temperature impact index can help identify the trend of abnormal temperature increase, so as to take preventive measures, such as reducing the charging rate or stopping use, to avoid possible safety accidents such as battery fire or explosion. Understanding the long-term impact of temperature on battery capacity and life helps to optimize the economic use cycle of the battery. The accurate calculation of the temperature impact coefficient makes it possible to scientifically plan the battery replacement cycle and maintenance time, reduce economic losses due to unexpected battery failure, and extend the effective service life of the battery.

[0047] Specifically, the specific steps for obtaining the battery current influence index of the large cylindrical battery are as follows: compare and analyze the historical battery current values ​​at each time point in the history of each use of the large cylindrical battery to obtain the historical maximum battery current of the large cylindrical battery; conduct a comprehensive analysis of the historical maximum battery current and the current battery current value of the large cylindrical battery to obtain the battery current influence index of the large cylindrical battery, and the calculation formula is as follows: Among them, TgZ is the battery current influence index of the large cylindrical battery, DqD is the current battery current value of the large cylindrical battery, LtD Max is the historical maximum value of the battery through-current of the large cylindrical battery, and ω is the through-current influence coefficient stored in the database.

[0048] It needs to be explained that the specific calculation process of the current influence coefficient is: operate the battery under different current loads and record the battery capacity decay. For example, at discharge currents of different multiples such as 1C (the current of the battery's nominal capacity) and 2C, measure the battery capacity and other health indicators, and use linear or nonlinear regression to analyze the relationship between current load and capacity decay. The coefficient of current load extracted from the regression model is the current influence coefficient, which reflects the sensitivity of current changes to capacity decay.

[0049] The specific calculation example is as follows:

[0050] Assume that when the battery is discharged at 1C, the capacity decays from 100% to 90% after a certain period of time; when discharged at 2C, the capacity decays to 85% after the same period of time.

[0051] Regression analysis was performed using the data (1C, 90%), (2C, 85%).

[0052] If the regression line is y=100-ωx, where x is the C rate and y is the remaining capacity percentage, the current influence coefficient ω can be obtained by solving the data points.

[0053] In this embodiment, by understanding the impact of current changes on battery capacity, the battery load conditions can be adjusted more accurately. For example, if the analysis shows that high current discharge significantly accelerates battery capacity decay, the battery usage strategy can be optimized to limit operation to a lower discharge rate, or the current load can be appropriately distributed during high demand periods to extend the battery life and maintain its high efficiency. By calculating the current impact index, the battery management system can monitor the battery's operating status in real time and make timely adjustments when excessive current may cause performance degradation or damage to the battery. This not only helps to maintain the battery in the best working state, but also increases the overall reliability of the system and avoids battery failures due to excessive current. The current impact index allows accurate prediction of battery performance decay and ultimate life under different current conditions. This evaluation is extremely important for battery design improvements, maintenance plan formulation, and keeping the battery in the optimal state at all times, especially in applications where battery demand changes greatly or the usage environment is complex.

[0054] Specifically, the specific steps for obtaining the battery discharge depth influence index of the large cylindrical battery are as follows: performing a mean analysis on the historical battery discharge depth values ​​after each use of the large cylindrical battery to obtain the historical battery discharge depth reference value of the large cylindrical battery; performing a comprehensive analysis on the historical battery discharge depth reference value and the current battery discharge depth value of the large cylindrical battery to obtain the battery discharge depth influence index of the large cylindrical battery.

[0055] Among them, the specific formula for calculating the historical battery discharge depth reference value and battery discharge depth influence index of large cylindrical batteries is as follows: Where LfC is the historical battery discharge depth reference value of large cylindrical batteries, LfS i is the historical battery discharge depth value of the large cylindrical battery after the i-th use in history, i = 1.2.3, ..., i0, i0 is the number of historical uses, FsZ is the battery discharge depth influence index of the large cylindrical battery, DqF is the current battery discharge depth value of the large cylindrical battery, and θ is the discharge depth influence coefficient stored in the database.

[0056] It needs to be explained that the specific calculation process of the discharge depth influence coefficient is: perform periodic tests on the battery at different discharge depths, record the capacity change data, for example, set the battery to operate at 50%, 80% and 100% discharge depths, and measure its capacity, use statistical or regression analysis to establish a model between discharge depth and capacity attenuation, and extract the influence coefficient of discharge depth change from the model as the discharge depth influence coefficient.

[0057] The specific calculation example is as follows:

[0058] Assuming that the battery retains 95% of its capacity at a 50% depth of discharge and drops to 85% at a 100% depth of discharge, use the data (50%, 95%), (100%, 85%) for regression analysis.

[0059] If the model is y=100-θ(x-50), where x is the percentage of discharge depth and y is the percentage of remaining capacity, the discharge depth influence coefficient θ is calculated through the data.

[0060] In this embodiment, by quantitatively analyzing the impact of discharge depth on battery capacity, the battery usage strategy can be designed more accurately to minimize capacity loss. Understanding how different discharge depths affect battery life can help decision makers develop more effective charging and discharging plans, such as selecting a milder discharge depth to extend the total service life of the battery, or maximizing energy output without affecting battery health. Discharge depth is one of the key factors affecting the life of lithium batteries. Through systematic analysis of historical and current discharge depth data, the optimal discharge depth range can be identified to avoid excessive discharge of the battery, reduce battery loss, and extend its service life. This method helps battery users reduce the economic burden caused by battery replacement while maintaining efficient energy utilization. The calculation of the battery discharge depth impact index enables energy managers to better understand the performance and efficiency of the battery at a specific discharge depth, which helps to optimize the performance of the battery in the application system, such as in electric vehicles and renewable energy storage systems, ensuring that the battery maintains efficient and economical operation while providing the necessary power. The specific discharge depth impact analysis enables the battery management system (BMS) to monitor and regulate the status of the battery more accurately. For example, the BMS can adjust the discharge strategy in real time according to the discharge depth impact index to prevent excessive discharge or unnecessary rapid discharge of the battery, thereby improving the reliability and safety of the entire system.

[0061] See also Figure 3 The embodiment of the present invention provides a technical solution: a large cylindrical battery capacity estimation system, including: a data acquisition module, an index analysis module, and a capacity estimation module; the data acquisition module is used to acquire historical operating status data, current operating status data, and battery initial capacity value of the large cylindrical battery, the historical operating status data includes historical battery attenuation data, historical battery temperature data, historical battery current data, and historical battery discharge depth data, and the current operating status data includes current battery internal resistance value, current battery internal temperature value, current battery current value, and current battery discharge depth value (battery discharge depth value from the beginning of current use to the present); the index analysis module is used to comprehensively analyze the historical operating status data and current operating status data of the large cylindrical battery to obtain the capacity attenuation rate index, battery temperature influence index, battery current influence index, and battery discharge depth influence index of the large cylindrical battery; the capacity estimation module is used to comprehensively analyze the battery initial capacity value of the large cylindrical battery with the capacity attenuation rate index, battery temperature influence index, battery current influence index, and battery discharge depth influence index to obtain the battery capacity estimation value of the large cylindrical battery.

[0062] Among them, the specific implementation example of calculating the estimated value of the battery capacity of a large cylindrical battery is as follows, and the following data is available:

[0063] The initial capacity value of the large cylindrical battery is: 3000mAH.

[0064] The historical battery internal resistance reference value for large cylindrical batteries is: 0.2Ω.

[0065] The current battery internal resistance value of the large cylindrical battery is: 0.3Ω.

[0066] The internal resistance influence coefficient stored in the database is: 0.05.

[0067] The large cylindrical battery has completed 800 charge and discharge cycles.

[0068] The reference value for the number of charge and discharge cycles of large cylindrical batteries is: 1000 times.

[0069] The impact coefficient of the number of charge and discharge cycles stored in the database is: 0.08.

[0070] The historical battery internal temperature reference value for large cylindrical batteries is: 28°C.

[0071] The current internal battery temperature value of the large cylindrical battery is: 32°C.

[0072] The temperature influence coefficient stored in the database is: 0.05.

[0073] The current battery flow rate of the large cylindrical battery is: 150A.

[0074] The historical maximum current passing through a large cylindrical battery is: 200A.

[0075] The through current influence coefficient stored in the database is: 0.05.

[0076] The historical battery discharge depth reference value for large cylindrical batteries is: 70%.

[0077] The current battery discharge depth value for the large cylindrical battery is: 80%.

[0078] The discharge depth influence coefficient stored in the database is: 0.02.

[0079] Substituting the above data into the specific formulas for calculating the capacity attenuation rate index, battery temperature influence index, battery current influence index, and battery discharge depth influence index of large cylindrical batteries, we obtain:

[0080] The capacity decay rate index of the large cylindrical battery = exp(-((0.05*(0.3-0.2) / 0.2)+(0.08*(800 / 1000)))) = 0.9148.

[0081] The battery temperature influence index of the large cylindrical battery = exp(-0.05*((32-28) / 28))) = 0.9929.

[0082] The battery current influence index of the large cylindrical battery = 1-(0.05*(150 / 200)) = 0.9625.

[0083] The battery discharge depth influence index of the large cylindrical battery = 1-(0.02*(0.7 / 0.8)) = 0.9825.

[0084] Substitute the capacity decay rate index, battery temperature influence index, battery current influence index, battery discharge depth influence index, and battery initial capacity value of the large cylindrical battery into the specific formula for calculating the estimated battery capacity of the large cylindrical battery, and obtain the estimated battery capacity of the large cylindrical battery = 3000*0.9148*0.9929*0.9625*0.9825=2576.83mAH, that is, the estimated battery capacity of the large cylindrical battery is 2576.83mAH.

[0085] In summary, this application has at least the following effects:

[0086] By collecting and analyzing the historical and current operating data of large cylindrical batteries, such as the number of charge and discharge cycles, internal resistance, temperature, and current data, these factors are combined to calculate the battery's capacity decay rate index and other influencing indexes, which can help accurately predict the battery's future performance and decay trend, and then provide a more accurate battery health status assessment, support the formulation of more effective maintenance strategies, avoid unnecessary battery replacement, and extend battery life.

[0087] By combining real-time monitoring of the battery's internal temperature and current with historical data analysis, trends that may lead to performance degradation or safety risks can be identified in a timely manner. For example, by comparing historical and current changes in internal resistance, battery aging or impending failure can be detected early, so that preventive measures can be implemented to prevent the failure from developing to the point where it affects the battery's overall system, thereby improving the safety of the battery's use process.

[0088] By accurately calculating and predicting the actual capacity and health status of the battery, the energy system can more efficiently distribute loads and reduce energy waste. This approach can significantly improve overall energy efficiency, especially in applications that rely heavily on battery performance, such as electric vehicles and energy storage systems.

[0089] Through the collaborative work of the data acquisition module, index analysis module and capacity estimation module, real-time monitoring and data management of battery performance can be achieved. By automatically collecting historical and current operating status data, not only the efficiency of data processing is improved, but also the integrity and accuracy of the data are guaranteed. Real-time performance monitoring allows the operation and maintenance team to instantly obtain the operating status of the battery, such as increased internal resistance, increased temperature or abnormal current, which are key indicators for predicting battery failure and managing battery health. In addition, this systematic real-time monitoring helps to quickly identify and respond to potential battery problems, thereby reducing downtime and maintenance costs, and improving the stability and reliability of the entire energy system.

[0090] 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.

[0091] 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 estimating the capacity of large cylindrical batteries. It is characterized in that The following steps are involved: Obtain historical operating status data, current operating status data and initial capacity value of the large cylindrical battery, wherein the historical operating status data includes historical battery attenuation data, historical battery temperature data, historical battery current data and historical battery discharge depth data, and the current operating status data includes current battery internal resistance value, current battery internal temperature value, current battery current value and current battery discharge depth value; Comprehensively analyze the historical and current operating status data of large cylindrical batteries to obtain the capacity attenuation rate index, battery temperature influence index, battery current influence index, and battery discharge depth influence index of large cylindrical batteries; The initial capacity value of the large cylindrical battery is comprehensively analyzed with the capacity attenuation rate index, battery temperature influence index, battery current influence index, and battery discharge depth influence index to obtain the estimated value of the battery capacity of the large cylindrical battery.

2. The method for estimating the capacity of a large cylindrical battery according to claim 1, It is characterized in that The historical battery attenuation data specifically includes the number of historical completed charge and discharge cycles and the historical battery internal resistance value at each historical time point in each historical use; the historical battery temperature data specifically includes the historical battery internal temperature value at each historical time point in each historical use; the historical battery current data specifically includes the historical battery current value at each historical time point in each historical use; the historical battery discharge depth data specifically includes the historical battery discharge depth value after each historical use.

3. The method for estimating the capacity of a large cylindrical battery according to claim 1, It is characterized in that The specific formula for calculating the estimated battery capacity of a large cylindrical battery is as follows: RgS=CsR*SjZ*WdZ*TgZ*FsZ; Among them, RgS is the estimated value of the battery capacity of the large cylindrical battery, CsR is the initial capacity value of the battery of the large cylindrical battery, SjZ is the capacity attenuation rate index of the large cylindrical battery, WdZ is the battery temperature influence index of the large cylindrical battery, TgZ is the battery through current influence index of the large cylindrical battery, and FsZ is the battery discharge depth influence index of the large cylindrical battery.

4. The method for estimating the capacity of a large cylindrical battery according to claim 2, It is characterized in that The specific steps to obtain the capacity decay rate index of a large cylindrical battery are as follows: Obtain reference value of charge and discharge cycle number of large cylindrical battery; Perform mean analysis on the historical battery internal resistance values ​​at each time point in the history of each use of the large cylindrical battery to obtain the historical battery internal resistance reference value of the large cylindrical battery; A comprehensive analysis is performed on the historical battery internal resistance reference value, current battery internal resistance value, historical completed charge and discharge cycle number, and charge and discharge cycle number reference value of the large cylindrical battery to obtain the capacity decay rate index of the large cylindrical battery.

5. The method for estimating the capacity of a large cylindrical battery according to claim 4, It is characterized in that The specific formula for calculating the historical battery internal resistance reference value and capacity decay rate index of large cylindrical batteries is as follows: Among them, LnJ is the historical battery internal resistance reference value of large cylindrical batteries, LnZ iu is the historical battery internal resistance value at the uth time point in the history of the i-th use of the large cylindrical battery, i = 1, 2, 3, ..., i 0 ,i 0 is the number of historical usages, u=1, 2, 3, …, u 0 ,u 0 is the number of historical time points, SjZ is the capacity attenuation rate index of the large cylindrical battery, e is a natural constant, DqN is the current battery internal resistance value of the large cylindrical battery, α is the internal resistance influence coefficient stored in the database, YfX is the number of historical completed charge and discharge cycles of the large cylindrical battery, FxC is the reference value of the number of charge and discharge cycles of the large cylindrical battery, and β is the charge and discharge cycle influence coefficient stored in the database.

6. The method for estimating the capacity of a large cylindrical battery according to claim 2, It is characterized in that The specific steps for obtaining the battery temperature impact index of a large cylindrical battery are as follows: Perform mean analysis on the historical battery internal temperature values ​​at each time point in each historical use of the large cylindrical battery to obtain the historical battery internal temperature reference value of the large cylindrical battery; A comprehensive analysis is performed on the historical battery internal temperature reference values ​​and current battery internal temperature values ​​of the large cylindrical battery to obtain the battery temperature influence index of the large cylindrical battery.

7. The method for estimating the capacity of a large cylindrical battery according to claim 6, It is characterized in that The specific formula for calculating the historical battery internal temperature reference value and battery temperature impact index of large cylindrical batteries is as follows: Among them, LwJ is the historical battery internal temperature reference value of large cylindrical batteries, LnW iu is the historical battery internal temperature value at the uth time point in the history of the i-th use of the large cylindrical battery, i = 1, 2, 3, ..., i 0 ,i 0 is the number of historical usages, u=1, 2, 3, …, u 0 ,u 0 is the number of historical time points, WdZ is the battery temperature influence index of the large cylindrical battery, e is a natural constant, DqW is the current battery internal temperature value of the large cylindrical battery, and δ is the temperature influence coefficient stored in the database.

8. The method for estimating the capacity of a large cylindrical battery according to claim 2, It is characterized in that The specific steps to obtain the battery current influence index of a large cylindrical battery are as follows: Compare and analyze the historical battery current values ​​at each time point in the history of each use of the large cylindrical battery to obtain the historical maximum value of the battery current of the large cylindrical battery; A comprehensive analysis is performed on the historical maximum battery current and current battery current of large cylindrical batteries to obtain the battery current influence index of large cylindrical batteries. The calculation formula is as follows: Among them, TgZ is the battery current influence index of the large cylindrical battery, DqD is the current battery current value of the large cylindrical battery, LtD Max is the historical maximum value of the battery through-current of the large cylindrical battery, and ω is the through-current influence coefficient stored in the database.

9. The method for estimating the capacity of a large cylindrical battery according to claim 2, It is characterized in that The specific steps for obtaining the battery discharge depth influence index of a large cylindrical battery are as follows: Perform mean analysis on the historical battery discharge depth values ​​after each use of the large cylindrical battery to obtain a historical battery discharge depth reference value of the large cylindrical battery; A comprehensive analysis is performed on the historical battery discharge depth reference value and the current battery discharge depth value of the large cylindrical battery to obtain the battery discharge depth impact index of the large cylindrical battery; Among them, the specific formula for calculating the historical battery discharge depth reference value and battery discharge depth influence index of large cylindrical batteries is as follows: Where LfC is the historical battery discharge depth reference value of large cylindrical batteries, LfS i is the historical battery discharge depth value after the i-th use of the large cylindrical battery, i = 1, 2, 3, ..., i 0 ,i 0 is the number of historical uses, FsZ is the battery discharge depth influence index of the large cylindrical battery, DqF is the current battery discharge depth value of the large cylindrical battery, and θ is the discharge depth influence coefficient stored in the database.

10. A large cylindrical battery capacity estimation system, using the large cylindrical battery capacity estimation method according to any one of claims 1 to 9, It is characterized in that include: Data acquisition module, index analysis module, capacity estimation module; The data acquisition module is used to acquire the historical operating status data, current operating status data and initial capacity value of the large cylindrical battery, wherein the historical operating status data includes historical battery attenuation data, historical battery temperature data, historical battery current data and historical battery discharge depth data, and the current operating status data includes the current battery internal resistance value, the current battery internal temperature value, the current battery current value and the current battery discharge depth value; The index analysis module is used to comprehensively analyze the historical operating status data and current operating status data of the large cylindrical battery to obtain the capacity decay rate index, battery temperature influence index, battery current influence index, and battery discharge depth influence index of the large cylindrical battery; The capacity estimation module is used to comprehensively analyze the initial capacity value of the large cylindrical battery with the capacity decay rate index, the battery temperature influence index, the battery current influence index, and the battery discharge depth influence index to obtain the battery capacity estimation value of the large cylindrical battery.

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