An energy storage monitoring method and system, electronic equipment and storage medium

Abstract

An energy storage monitoring method and system, electronic equipment and storage medium, relate to the technical field of energy storage. The method comprises: acquiring voltage data and temperature data of a plurality of different types of battery units; generating a voltage response curve of the corresponding battery unit based on each voltage data, and generating a temperature response curve of the corresponding battery unit based on each temperature data; dividing each battery unit into a plurality of battery groups with different charge-discharge characteristics according to each voltage response curve and each temperature response curve, and calculating the residual capacity value of each battery unit in each battery group; in each battery group, combining the residual capacity value of each battery unit to determine the capacity difference between each battery unit, and taking each battery unit with a capacity difference greater than a capacity threshold as a target battery pair; concurrently balancing and adjusting the power parameters of each target battery pair until the capacity difference of each target battery pair is less than the capacity threshold. The technical solution provided by the present application can improve the overall energy storage efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of energy storage, in particular to an energy storage monitoring method and system, an electronic device and a storage medium. BACKGROUND

[0002] With the rapid development of new energy technology, energy storage systems play an increasingly important role in power peak shaving, demand side response and other fields. Energy storage systems are usually composed of a large number of battery units, which may come from different batches, different manufacturers, or even use different chemical systems. In order to improve the service life and safety performance of the energy storage system, it is necessary to effectively monitor and manage the battery units in the system.

[0003] At present, the energy storage system usually adopts a unified management strategy to monitor and control all battery units. This method mainly collects voltage data of the battery units and performs charging and discharging control based on preset management parameters. However, in actual application, due to the differences in charging and discharging characteristics of different types of battery units, the unified management strategy often cannot accurately reflect the actual working state of various types of battery units. In this case, some battery units may be in overcharged or overdischarged state, and energy loss cannot be discovered and processed in time, thereby reducing the overall energy storage efficiency. SUMMARY

[0004] The present application provides an energy storage monitoring method, system, electronic device and storage medium, which can improve the overall energy storage efficiency.

[0005] In a first aspect, the present application provides an energy storage monitoring method, comprising:

[0006] obtaining voltage data and temperature data of a plurality of different types of battery units;

[0007] generating voltage response curves of the corresponding battery units based on the voltage data, and generating temperature response curves of the corresponding battery units based on the temperature data;

[0008] dividing the battery units into a plurality of battery groups with different charging and discharging characteristics according to the voltage response curves and the temperature response curves, and calculating the residual capacity value of each battery unit in each battery group;

[0009] In each battery group, the residual capacity value of each battery unit is combined to determine the capacity difference between each battery unit, and each battery unit with a capacity difference greater than a capacity threshold is regarded as a target battery pair;

[0010] Concurrently adjusting the power parameters of each target battery pair until the capacity difference of each target battery pair is less than the capacity threshold.

[0011] By adopting the technical scheme, the voltage data and the temperature data of different types of battery units are acquired, and the voltage response curves and the temperature response curves are respectively generated, so that the working characteristics of each battery unit can be comprehensively reflected; then, the battery units are divided into battery groups with different charging and discharging characteristics based on the response curves, and the residual capacity values of the battery units are calculated, so that the classification management of different types of battery units is realized; then, the power difference between each battery unit in the same battery group is calculated, the target battery pair with the power difference greater than the power threshold is identified, and the power parameters of the target battery pair are concurrently and equally adjusted until the power difference is reduced to below the threshold, so that the charging and discharging balance of each battery unit is ensured, the battery units in overcharging or overdischarging state are avoided, the energy loss is reduced, and the energy storage efficiency of the entire energy storage system is finally improved.

[0012] In a second aspect of the present application, an energy storage monitoring system is provided, the system comprising:

[0013] a data acquisition module configured to acquire voltage data and temperature data of a plurality of battery units of different types;

[0014] a response curve generation module configured to generate a voltage response curve of a corresponding battery unit based on each of the voltage data, and generate a temperature response curve of the corresponding battery unit based on each of the temperature data;

[0015] a residual capacity value calculation module configured to divide each of the battery units into a plurality of battery groups with different charging and discharging characteristics according to each of the voltage response curves and each of the temperature response curves, and calculate a residual capacity value of each battery unit in each of the battery groups;

[0016] a power adjustment module configured to determine a power difference between each of the battery units in each of the battery groups in combination with the residual capacity value of each of the battery units, and identify each battery unit with a power difference greater than a power threshold as a target battery pair; concurrently and equally adjust the power parameters of each of the target battery pair until the power difference of each of the target battery pair is less than the power threshold.

[0017] In a third aspect of the present application, an electronic device is provided, comprising a memory, a processor, and a program stored in the memory and executable on the processor, which can be loaded and executed by the processor to implement an energy storage monitoring method.

[0018] In a fourth aspect of the present application, a computer readable storage medium is provided, which stores a computer program, and the computer program is executed by a processor to implement an energy storage monitoring method.

[0019] In summary, the one or more technical solutions provided by the present application have at least the following technical effects or advantages:

[0020] By adopting the above technical solution, voltage and temperature data of different types of battery cells are acquired, and voltage response curves and temperature response curves are generated respectively, which can comprehensively reflect the working characteristics of each battery cell. Then, based on these response curves, the battery cells are divided into battery packs with different charge and discharge characteristics, and the remaining capacity of each battery cell is calculated, realizing the classified management of different types of battery cells. Then, by calculating the capacity difference between battery cells in the same battery pack, target battery pairs with capacity differences greater than the capacity threshold are identified, and the power parameters of these target battery pairs are concurrently balanced until the capacity difference is reduced to below the threshold. This ensures the charge and discharge balance of each battery cell, avoids battery cells being in an overcharged or over-discharged state, reduces energy loss, and ultimately improves the energy storage efficiency of the entire energy storage system. Attached Figure Description

[0021] Figure 1 This is a schematic flowchart of an energy storage monitoring method provided in an embodiment of this application;

[0022] Figure 2 This is a schematic diagram of the structure of an energy storage monitoring system provided in an embodiment of this application;

[0023] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0024] Explanation of reference numerals in the attached drawings: 300, electronic device; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. Detailed Implementation

[0025] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0026] In the description of the embodiments of this application, the words "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design that is described as "for example" or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design options. Rather, the use of the words "for example" or "for instance" is intended to present the relevant concepts in a specific manner.

[0027] In the description of the embodiments of this application, the term "multiple" means two or more. For example, multiple systems means two or more systems, and multiple screen terminals means two or more screen terminals. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0028] This application provides an energy storage monitoring method. In one embodiment, please refer to... Figure 1 , Figure 1 This is a flowchart illustrating the energy storage monitoring method provided in this application embodiment. This method can be implemented using a computer program, which can be integrated into an application or run as a standalone utility application. The method can also be implemented using a microcontroller and can run on an energy storage monitoring system based on the von Neumann architecture. Specifically, the method may include the following steps:

[0029] Step 101: Obtain voltage and temperature data for multiple different types of battery cells.

[0030] Voltage data refers to the terminal voltage value of the battery cell during actual operation. Specifically, voltage data includes the real-time voltage values ​​of the battery cell under charging and discharging conditions, reflecting the electrochemical characteristics of the battery cell under different operating states.

[0031] Temperature data refers to the surface temperature value of a battery cell during the charging and discharging process. Temperature data includes the real-time temperature changes of the battery cell under charging and discharging conditions.

[0032] Specifically, the first step is to acquire voltage and temperature data from multiple different types of battery cells through the battery management system of the energy storage system. Since the battery cells in the energy storage system may come from different batches, manufacturers, or use different chemical systems, these cells will exhibit different electrochemical characteristics during charging and discharging. Therefore, it is necessary to simultaneously collect these two key parameters, voltage and temperature, to comprehensively reflect the operating status of the battery cells. In practice, a voltage sampling module and a temperature sensor are installed on each battery cell. The voltage sampling module collects the voltage value across the battery cell, and the temperature sensor collects the temperature value on the surface of the battery cell. The sampling frequency of the voltage sampling module can be set to 100ms to ensure that rapid voltage changes during charging and discharging are captured. The sampling frequency of the temperature sensor can be set to 1s, because temperature changes relatively slowly; this sampling frequency ensures data accuracy while reducing the burden of data processing.

[0033] The acquired voltage and temperature data are transmitted to the central controller in real time via a communication interface. In the central controller, the raw data undergoes preprocessing, including outlier removal and data smoothing, to improve the reliability of subsequent analysis. Simultaneously, the processed data is stored according to timestamps, providing a data foundation for the subsequent generation of voltage and temperature response curves. Voltage and temperature data acquired in this way accurately reflect the state changes of each battery cell during actual operation.

[0034] Step 102: Generate the voltage response curve of the corresponding battery cell based on each voltage data, and generate the temperature response curve of the corresponding battery cell based on each temperature data.

[0035] Among them, the voltage response curve refers to the voltage change characteristic curve of the battery cell during the charging and discharging process. It consists of the charging response curve and the discharging response curve. The charging response curve represents the voltage rise characteristic of the battery cell during the charging process, reflecting the voltage change rate and charging acceptance capability of the battery cell during charging. The discharging response curve represents the voltage drop characteristic of the battery cell during the discharging process, reflecting the voltage change rate and discharging capability of the battery cell during discharging.

[0036] The temperature response curve is the curve showing the relationship between the rate of temperature change of a battery cell and its charging and discharging power. This curve characterizes the thermal properties of the battery cell by establishing a mapping relationship between the temperature change trend of the battery cell and its charging and discharging power.

[0037] Specifically, to accurately characterize the operating characteristics of different types of battery cells, voltage response curves and temperature response curves need to be generated based on the collected voltage and temperature data, respectively. Since battery cells exhibit different electrochemical and thermal characteristics during charging and discharging, these characteristics can be characterized by the morphological features of the response curves, thus providing a basis for subsequent battery grouping and equalization control.

[0038] When generating the voltage response curve, voltage data under charging and discharging conditions are first extracted from the voltage data. Then, the voltage data under charging and discharging conditions are sequentially arranged to obtain charging and discharging voltage sequences. Based on these voltage sequences, charging and discharging response curves are generated using data fitting methods. Finally, the charging and discharging response curves are combined to form the voltage response curve of the battery cell. This generated voltage response curve comprehensively reflects the voltage change characteristics of the battery cell during charging and discharging.

[0039] When generating the temperature response curve, the temperature change trends under charging and discharging conditions are first identified. These trends reflect the thermal response characteristics of the battery cell under different power conditions. Then, based on these temperature change trends, a mapping relationship is established between the battery cell's temperature change rate and the charging and discharging power. Finally, the temperature response curve of the battery cell is generated according to this mapping relationship. The temperature response curve generated in this way can reflect the temperature change pattern of the battery cell under different power conditions.

[0040] Based on the above embodiments, as an optional embodiment, step 102, which generates the voltage response curve of the corresponding battery cell based on each voltage data, may further include the following steps:

[0041] Step 201: For each battery cell, extract the voltage data under charging conditions and the voltage data under discharging conditions from the voltage data.

[0042] Specifically, the first step is to distinguish and extract voltage data under charging and discharging conditions from the voltage data. This is because battery cells exhibit different electrochemical characteristics during charging and discharging, requiring separate analysis. In practice, the operating condition is identified by detecting the direction of the current in the battery cell: when a positive current is detected, the battery is in a charging condition, and the recorded voltage data is classified as charging voltage data; when a negative current is detected, the battery is in a discharging condition, and the recorded voltage data is classified as discharging voltage data. This classification and extraction method ensures the accuracy of the charge and discharge characteristics in subsequent analyses.

[0043] Step 202: Arrange the voltage data under charging condition and the voltage data under discharging condition in time sequence to obtain the charging voltage sequence and the discharging voltage sequence.

[0044] Specifically, the extracted voltage data under charging and discharging conditions are time-series arranged to accurately reflect the voltage variation of the battery cell over time during charging and discharging. In practice, the voltage data under charging conditions are first sorted by timestamp in ascending order to form a charging voltage sequence, which reflects the complete voltage change process of the battery cell from the start of charging to the end of charging. Similarly, the voltage data under discharging conditions are sorted by timestamp in ascending order to form a discharging voltage sequence, which reflects the complete voltage change process of the battery cell from the start of discharging to the end of discharging. This time-series arrangement ensures that the subsequently generated response curve accurately reflects the dynamic characteristics of the battery cell.

[0045] Step 203: Generate the charging response curve corresponding to the charging voltage sequence and the discharging response curve corresponding to the discharging voltage sequence; use the charging response curve and the discharging response curve as the voltage response curve corresponding to the battery cell.

[0046] Specifically, based on the pre-arranged charging and discharging voltage sequences, charging and discharging response curves are generated through data fitting. In practice, mathematical methods such as polynomial fitting or spline interpolation are used to convert the discrete voltage sequences into continuous response curves. For the charging voltage sequence, the fitted charging response curve characterizes the voltage rise characteristics of the battery cell during charging; for the discharging voltage sequence, the fitted discharging response curve characterizes the voltage drop characteristics of the battery cell during discharging. Finally, these two curves are combined as the voltage response curve of the battery cell, thus comprehensively reflecting the voltage characteristics of the battery cell under different operating conditions. The voltage response curve generated in this way has continuity and smoothness, facilitating subsequent feature extraction and analysis.

[0047] Based on the above embodiments, as an optional embodiment, step 102, which generates the temperature response curve of the corresponding battery cell based on each temperature data, may further include the following steps:

[0048] Step 204: For each battery cell, identify the temperature change trend of the temperature data under charging conditions and the temperature change trend under discharging conditions.

[0049] Specifically, it is necessary to identify the temperature data trends under charge and discharge conditions, as battery cells exhibit different temperature change characteristics under different power conditions. In practice, the temperature data is first divided into charging and discharging temperature data based on the current direction. Then, the temperature difference between adjacent time points is calculated to obtain a temperature change rate sequence. Statistical analysis of these temperature change rate sequences yields the temperature change trends under different charge and discharge powers. For example, when the charging power is 2kW, the corresponding temperature rise rate is recorded; when the discharging power is 3kW, the corresponding temperature rise rate is recorded. This trend identification method can reflect the thermal characteristics of the battery cell under different operating conditions.

[0050] Step 205: Based on the temperature change trend, establish the mapping relationship between the temperature change rate of the battery cell and the charging power and discharging power.

[0051] Specifically, based on the identified temperature change trend, a mapping relationship is established between the temperature change rate of the battery cell and the charging / discharging power. In practice, firstly, the temperature change rate data at different power levels are organized to obtain separate sets of data for charging power-temperature change rate and discharging power-temperature change rate. Then, mathematical methods such as the least squares method are used to fit these data sets to obtain the functional relationship between the temperature change rate and the charging / discharging power. For example, a quadratic function relationship can be obtained between the temperature change rate and the charging power, as well as a quadratic function relationship between the temperature change rate and the discharging power. This mapping relationship provides the mathematical foundation for the subsequent generation of temperature response curves.

[0052] Step 206: Generate the temperature response curve of the battery cell based on the mapping relationship.

[0053] Specifically, the temperature response curve of the battery cell is generated based on the established mapping relationship. In practice, the range of charge and discharge power is first determined, such as a charging power range of 0-5kW and a discharging power range of 0-5kW. Then, these power values ​​are substituted into the established mapping relationship function to calculate the corresponding temperature change rate. Finally, the power value is plotted on the x-axis and the temperature change rate on the y-axis to obtain a continuous temperature response curve. This curve intuitively reflects the temperature change characteristics of the battery cell under different power conditions and can be used for subsequent battery grouping and power control. The temperature response curve generated in this way has good continuity and predictability, and can effectively guide the thermal management and power regulation of the energy storage system.

[0054] Step 103: Based on the voltage response curves and temperature response curves, divide each battery cell into multiple battery packs with different charge and discharge characteristics, and calculate the remaining capacity of each battery cell in each battery pack.

[0055] A battery pack refers to a collection of battery cells with similar charge-discharge characteristics. This grouping method ensures that the battery cells within the same battery pack have similar electrochemical and thermal characteristics, facilitating the implementation of a unified management strategy.

[0056] The remaining charge value refers to the actual usable charge currently stored in the battery cell. This remaining charge value directly reflects the current energy state of the battery cell and is an important basis for balancing control.

[0057] Specifically, to achieve precise management of different types of battery cells, it is necessary to group the battery cells according to the characteristics of their voltage and temperature response curves and calculate the remaining capacity of each battery cell. This is because battery cells with similar charge-discharge characteristics are suitable for the same management strategy, and accurate calculation of the remaining capacity is crucial for subsequent equalization control. In practice, the slope parameters of each voltage response curve and the curvature parameters of each temperature response curve are first calculated. The slope parameter of the voltage response curve reflects the charge-discharge rate characteristics of the battery cell, while the curvature parameter of the temperature response curve reflects the thermal characteristics of the battery cell. Then, a feature vector is constructed for each battery cell based on these parameters. The feature vector contains key characteristic information of the battery cell. Cluster analysis is performed on the feature vectors of all battery cells, and a hierarchical clustering algorithm is used to calculate the vector distance between the feature vectors. When the vector distance is less than a preset distance threshold, the corresponding battery cell is grouped into a battery group with the same charge-discharge characteristics. This multi-dimensional feature-based grouping method can effectively identify battery cells with similar characteristics.

[0058] After grouping the batteries, it is necessary to calculate the remaining capacity of each battery cell in each group. Specifically, this involves first collecting the charging and discharging cutoff voltages of each battery cell during the charging and discharging process, and calculating the voltage range. Then, the voltage range is compared with a pre-set reference voltage range to obtain the range change. Based on a pre-defined remaining capacity mapping table, the remaining capacity proportion corresponding to the range change is determined. Finally, the remaining capacity proportion is multiplied by the rated capacity of the battery group to obtain the actual remaining capacity of the battery cell.

[0059] This method of battery grouping and remaining capacity calculation enables differentiated management of different types of battery cells. Battery cells with similar characteristics are grouped together, facilitating a unified management strategy; accurate remaining capacity calculation provides a reliable basis for subsequent equalization control. This management approach not only improves the operating efficiency of the energy storage system but also effectively extends the lifespan of battery cells. Simultaneously, the grouping method based on multi-dimensional features improves the accuracy of battery state assessment, helping to promptly identify and address battery cells in abnormal states.

[0060] Based on the above embodiments, as an optional embodiment, in step 103: dividing each battery cell into multiple battery packs with different charge-discharge characteristics according to each voltage response curve and each temperature response curve, this step may further include the following steps:

[0061] Step 301: Calculate the slope parameter of each voltage response curve and the curvature parameter of each temperature response curve.

[0062] Specifically, it is necessary to calculate the slope parameter of the voltage response curve and the curvature parameter of the temperature response curve. These parameters can quantitatively characterize the charge and discharge characteristics of the battery cell. In practice, for the voltage response curve, multiple sampling points are selected on both the charging and discharging response curves, and the voltage change rate between adjacent sampling points is calculated to obtain multiple local slope values. These local slope values ​​are then weighted and averaged to obtain the slope parameter characterizing the charge and discharge rate characteristics. For the temperature response curve, multiple power points are selected on the curve, and the second derivative value at each power point is calculated. These values ​​reflect the sensitivity of the temperature change rate to power change. These second derivative values ​​are then weighted and averaged to obtain the curvature parameter characterizing the thermal characteristics. This parameter calculation method can effectively extract key characteristic information of the battery cell.

[0063] Step 302: Construct the feature vector of the corresponding battery cell based on the slope parameter and curvature parameter of each battery cell.

[0064] Specifically, feature vectors are constructed based on the calculated slope and curvature parameters to uniformly express the multidimensional characteristic information of the battery cell. In practice, the slope parameters of the charging response curve, the slope parameters of the discharging response curve, and the curvature parameters of the temperature response curve are combined according to preset weighting coefficients to form an n-dimensional feature vector. For example, a three-dimensional feature vector can be constructed, where the first dimension represents the charging slope parameter, the second dimension represents the discharging slope parameter, and the third dimension represents the temperature curvature parameter. This method of constructing feature vectors achieves a comprehensive characterization of the charging and discharging characteristics of the battery cell.

[0065] Step 303: Perform cluster analysis on the feature vectors of each battery cell to obtain the vector distance between each feature vector; classify battery cells with vector distance less than the distance threshold into battery packs with the same charge and discharge characteristics.

[0066] Specifically, cluster analysis is performed on the constructed feature vectors, and battery cells with similar characteristics are identified by calculating vector distance. In practice, Euclidean distance or Mahalanobis distance is used to calculate the distance between any two feature vectors. Then, hierarchical clustering or K-means clustering algorithms are used to cluster feature vectors whose vector distance is less than a preset distance threshold into one class. Finally, battery cells whose feature vectors belong to the same class are grouped into battery packs with the same charge / discharge characteristics. For example, when the Euclidean distance between the feature vectors of two battery cells is less than the set threshold of 0.1, these two battery cells will be grouped into the same battery pack. This grouping method based on feature vector distance ensures that battery cells within the same battery pack have similar charge / discharge characteristics, laying the foundation for subsequent group management and equalization control.

[0067] Based on the above embodiments, as an optional embodiment, step 103, calculating the remaining charge value of each battery cell in each battery pack, may further include the following steps:

[0068] Step 304: For each battery pack, collect the charging cut-off voltage and discharging cut-off voltage of each battery cell during the charging and discharging process; calculate the voltage range of each battery cell based on the charging cut-off voltage and discharging cut-off voltage of each battery cell.

[0069] Specifically, it is necessary to collect the charge / discharge cutoff voltages of the battery cells in each battery pack, as the voltage range is an important indicator for assessing the health of the battery cells. In practice, a standard charge / discharge cycle test is performed on each battery cell. When the charging current drops to a preset cutoff current (e.g., 0.05C), the voltage value at this point is recorded as the charging cutoff voltage; when the discharge reaches a preset cutoff voltage (e.g., 2.5V), the voltage value at this point is recorded as the discharging cutoff voltage. Then, the voltage range is calculated by comparing the charging cutoff voltage and the discharging cutoff voltage. The voltage range obtained in this way reflects the degree of capacity degradation of the battery cell.

[0070] Step 305: Calculate the range change of each battery cell's voltage range relative to the reference voltage range, and determine the remaining capacity ratio corresponding to each range change based on the preset remaining capacity mapping table.

[0071] Specifically, calculating the range change based on the voltage range and determining the remaining capacity ratio is a crucial step in accurately assessing the actual usable capacity of a battery cell. In practice, a reference voltage range is first established, typically selected from the voltage range measured under standard conditions for a new battery. The actual voltage range of each battery cell is compared to the reference voltage range to obtain the range change. For example, if a battery cell's voltage range is 3.2V and the reference voltage range is 4.0V, the range change is -0.8V. Then, a pre-established remaining capacity mapping table is consulted, which contains the remaining capacity ratios corresponding to different range changes. The remaining capacity ratio corresponding to this range change is calculated through interpolation. This mapping relationship is usually established based on extensive experimental data and statistical analysis.

[0072] Step 306: The product of the remaining capacity percentage of each battery cell and the rated capacity of the battery pack is taken as the remaining power value of the corresponding battery cell.

[0073] Specifically, the actual remaining capacity of a battery cell is obtained by multiplying the remaining capacity percentage by the rated capacity of the battery pack. This calculation method accurately reflects the current energy state of the battery cell. In practice, the rated capacity of the battery pack is first determined, typically taken from its specifications. Then, the remaining capacity percentage is multiplied by the rated capacity. For example, if the rated capacity of a battery pack containing a certain battery cell is 100Ah, and the remaining capacity percentage of that battery cell is 85%, then its remaining capacity is 85Ah. This calculation method takes into account the rated parameters of the battery pack, making the result more practically meaningful. The remaining capacity value obtained in this way accurately reflects the usable capacity of the battery cell, providing a reliable basis for subsequent equalization control and capacity adjustment, and helping to improve the overall performance and lifespan of the energy storage system.

[0074] Step 104: In each battery pack, based on the remaining charge value of each battery cell, determine the charge difference between each battery cell, and designate each battery cell with a charge difference greater than the charge threshold as the target battery pair.

[0075] Among them, the target battery pair refers to the battery cell pair formed by two battery cells within the same battery pack when the difference in the remaining charge value between the two battery cells exceeds a preset charge threshold.

[0076] Specifically, to achieve charge balance within the battery pack, it is necessary to identify battery cell pairs with significant charge differences within each battery pack. These battery cell pairs will be the target objects for subsequent equalization control. This is because charge imbalance within the same battery pack can lead to overcharging or over-discharging of some battery cells, affecting the performance and lifespan of the entire energy storage system. In practice, the remaining charge values ​​of battery cells within the same battery pack are first compared pairwise to calculate the charge difference between any two battery cells. For example, if the battery pack contains n battery cells, C(n,2) comparisons are needed to obtain C(n,2) charge differences. When calculating the charge difference, the remaining charge value of the battery cell with the larger remaining charge value is subtracted from the remaining charge value of the battery cell with the smaller remaining charge value. Then, the calculated charge difference is compared with a preset charge threshold. When the charge difference between a pair of battery cells is greater than the charge threshold, this pair of battery cells is identified as the target battery pair. For example, if the preset power threshold is 10Ah, when the remaining power of battery cell A is detected to be 85Ah and the remaining power of battery cell B is detected to be 70Ah, the power difference of 15Ah is greater than the power threshold, then battery cell A and battery cell B are identified as a target battery pair.

[0077] Identifying target battery pairs in this way allows for targeted subsequent equalization control. The setting of the charge threshold must ensure timely detection of battery cells requiring equalization while avoiding overly frequent equalization operations. This target battery pair identification method based on charge difference can accurately identify battery cell combinations with significant charge imbalances, laying the foundation for precise equalization control. Furthermore, since the comparison is conducted within the same battery pack, these target battery pairs have similar charge and discharge characteristics, facilitating subsequent equalization operations and improving equalization efficiency.

[0078] Step 105: Perform concurrent equalization adjustment of the power parameters of each target battery pair until the power difference between each target battery pair is less than the power threshold.

[0079] Specifically, to eliminate the capacity differences between target battery pairs, the power parameters of the target battery pairs need to be concurrently balanced. This concurrent adjustment method can process multiple target battery pairs simultaneously, improving balancing efficiency and shortening balancing time. The adjustment of power parameters mainly includes adjusting the charging power and discharging power. By rationally allocating power parameters, energy transfer between battery cells is achieved.

[0080] In practice, the first step is to calculate the energy transfer required between the high-capacity and low-capacity battery cells in each target battery pair. Based on the capacity difference and a preset equalization efficiency, a suitable power regulation strategy is determined. For the high-capacity battery cell, its discharge power is increased or its charging power is decreased; for the low-capacity battery cell, its discharge power is decreased or its charging power is increased. For example, when the capacity difference of a target battery pair is 15Ah, the discharge power of the high-capacity battery cell can be set to 2kW, while the discharge power of the low-capacity battery cell can be set to 1kW. This differentiated power setting gradually brings the remaining capacity of the two battery cells closer together.

[0081] During the equalization process, the charge difference between the target battery pairs is continuously monitored. When the charge difference drops below a threshold, power adjustment for that target battery pair is stopped. For example, when the charge difference of a target battery pair drops to 9Ah (less than the preset charge threshold of 10Ah), the power parameters of that target battery pair are restored to normal operating conditions. This dynamic adjustment method avoids energy waste caused by over-equalization. Furthermore, due to the concurrent adjustment strategy, multiple target battery pairs can be equalized simultaneously, improving equalization efficiency.

[0082] Based on the above embodiments, as an optional embodiment, in step 105: the power parameters of each target battery pair are concurrently balanced until the power difference between each target battery pair is less than the power threshold. This step may further include the following steps:

[0083] Step 401: Identify the charging and discharging units in each target battery pair; obtain the discharge power parameters of each charging unit and the charging power parameters of each discharging unit.

[0084] Specifically, the first step is to determine the role of each battery cell in the target battery pair and obtain its power parameters, which is the foundation for achieving precise equalization control. In practice, for each target battery pair, the battery cells with higher remaining charge values ​​are designated as discharging cells, and those with lower remaining charge values ​​are designated as charging cells. Then, the current charging power parameters of the discharging cells and the current discharging power parameters of the charging cells are collected. These power parameters reflect the real-time operating status of the battery cells, providing a reference for subsequent power adjustment.

[0085] Step 402: Calculate the power regulation coefficient of the corresponding target battery pair based on each discharge power parameter and each charge power parameter.

[0086] Specifically, a power regulation coefficient is calculated based on the acquired power parameters. This coefficient determines the magnitude and rate of power regulation. In practice, the difference in charge level between the charging and discharging units of the target battery is first calculated. This difference is then compared with a preset equalization time to obtain the required energy transfer rate. Next, the power regulation coefficient is calculated by combining the rated power of the battery units and the current power parameters. For example, if the charge difference is 15 Ah and the preset equalization time is 2 hours, the required power regulation coefficient can be calculated to be 0.8. This method of calculating the regulation coefficient based on actual needs ensures the smoothness of the equalization process.

[0087] Based on the above embodiments, as an optional embodiment, step 402: calculating the power regulation coefficient of the corresponding target battery pair based on each discharge power parameter and each charging power parameter, this step may further include the following steps:

[0088] Step 412: Calculate the ratio between the discharge power parameter of each target battery's centering discharge unit and the rated discharge power as the discharge coefficient; calculate the ratio between the charging power parameter of each target battery's centering charging unit and the rated charging power as the charging coefficient.

[0089] Specifically, it is necessary to calculate the discharge coefficient and the charge coefficient, which reflect the current power utilization status of the battery cell. In practice, for a discharge cell, its current discharge power parameter is divided by its rated discharge power to obtain the discharge coefficient. For example, if the current discharge power of a discharge cell is 2kW and its rated discharge power is 5kW, then its discharge coefficient is 0.4. Similarly, for a charge cell, its current charging power parameter is divided by its rated charging power to obtain the charge coefficient. This calculation method, based on the ratio of actual power to rated power, accurately reflects the power utilization level of the battery cell.

[0090] Step 422: Obtain the number of times the charging unit and the number of times the discharging unit of each target battery pair are charged, and determine the charging coefficient weight and the discharging coefficient weight of the corresponding target battery pair charging unit based on the number of times each is charged and each is discharged.

[0091] Specifically, weighting coefficients are determined by statistically analyzing the number of charge-discharge cycles. This is to account for the impact of battery cell usage history on equalization control. In practice, the number of charge cycles for charging cells and the number of discharge cycles for discharging cells are first obtained. Then, based on a preset weighting calculation formula, the number of charge cycles is converted into a charging coefficient weight, and the number of discharge cycles is converted into a discharging coefficient weight. For example, an exponential decay function can be used to calculate the weights, so that battery cells with more charge-discharge cycles receive smaller weighting coefficients, thus facing more restrictions in subsequent power regulation. This weighting allocation method based on usage history helps extend the lifespan of battery cells.

[0092] Step 432: For each target battery pair, the charging coefficient of the charging unit and the discharging coefficient of the discharging unit are weighted and calculated based on the charging coefficient weight and the discharging coefficient weight to obtain the power regulation coefficient of the corresponding target battery pair.

[0093] Specifically, the final power regulation coefficient needs to be calculated using weighted averages, and this coefficient directly determines the magnitude of power regulation. In practice, the charging coefficient of the charging unit is multiplied by its weight to obtain the weighted charging coefficient; the discharging coefficient of the discharging unit is multiplied by its weight to obtain the weighted discharging coefficient. Then, the weighted charging coefficient and the weighted discharging coefficient are arithmetically averaged to obtain the power regulation coefficient for the target battery pair. For example, if the charging coefficient of the charging unit is 0.3 with a weight of 0.8, and the discharging coefficient of the discharging unit is 0.4 with a weight of 0.7, then the calculated power regulation coefficient is 0.25. This comprehensive calculation method, which considers power utilization status and usage history, enables more accurate and reasonable power regulation, ensuring a balanced effect while avoiding excessive wear and tear on the battery units.

[0094] Step 403: Based on each power adjustment coefficient, synchronously adjust the discharge power of the discharge unit and the charging power of the charging unit corresponding to the target battery.

[0095] Specifically, the power parameters of the two battery cells in the target battery pair are synchronously adjusted according to the calculated power regulation coefficient. In practice, for the discharging cell, its discharge power is increased while its charging power is decreased according to the power regulation coefficient; for the charging cell, its charging power is increased while its discharging power is decreased according to the power regulation coefficient. For example, when the power regulation coefficient is 0.8, the discharge power of the discharging cell can be increased to 80% of its rated power, and the charging power of the charging cell can be increased to 80% of its rated power. This synchronous adjustment method enables smooth energy transfer between battery cells.

[0096] Step 404: Detect the charge difference between the charging and discharging units of each target battery pair. When the charge difference is less than the charge threshold, stop power adjustment.

[0097] Specifically, the balancing effect of the target battery pair is continuously monitored, and power regulation is stopped promptly when the balancing target is reached. In practice, the charge difference between the charging and discharging units is detected every preset time interval (e.g., 1 minute). The detected charge difference is compared with a preset charge threshold; when the difference is less than the threshold, it indicates that the target battery pair has reached a balanced state. At this point, the power parameters of the charging and discharging units are restored to normal operating conditions. For example, when the detected charge difference decreases to 9Ah (less than the preset threshold of 10Ah), power regulation is stopped. This real-time monitoring-based control method avoids over-balancing, ensuring balancing effectiveness while improving energy utilization efficiency. Through this series of steps, precise balancing of the charge within the battery pack can be achieved, improving the overall performance and lifespan of the energy storage system.

[0098] Reference Figure 2 This application provides an energy storage monitoring system, which includes: a data acquisition module, a response curve generation module, a remaining energy value calculation module, and a power regulation module, wherein:

[0099] The data acquisition module is used to acquire voltage and temperature data of multiple different types of battery cells;

[0100] The response curve generation module is used to generate the voltage response curve of the corresponding battery cell based on each voltage data, and to generate the temperature response curve of the corresponding battery cell based on each temperature data.

[0101] The remaining power value calculation module is used to divide each battery cell into multiple battery packs with different charge and discharge characteristics based on each voltage response curve and each temperature response curve, and to calculate the remaining power value of each battery cell in each battery pack.

[0102] The power adjustment module is used to determine the power difference between battery cells in each battery pack by combining the remaining power value of each battery cell, and to designate battery cells with power differences greater than the power threshold as target battery pairs; and to perform equalization adjustment on the power parameters of each target battery pair concurrently until the power difference between each target battery pair is less than the power threshold.

[0103] Based on the above embodiments, the response curve generation module is also used to extract voltage data under charging conditions and voltage data under discharging conditions from the voltage data for each battery cell; to arrange the voltage data under charging conditions and voltage data under discharging conditions in time sequence to obtain charging voltage sequence and discharging voltage sequence; to generate charging response curve corresponding to charging voltage sequence and discharging response curve corresponding to discharging voltage sequence; and to use the charging response curve and discharging response curve as the voltage response curve corresponding to the battery cell.

[0104] Based on the above embodiments, the response curve generation module is also used to identify the temperature change trend of temperature data under charging conditions and the temperature change trend under discharging conditions for each battery cell; establish a mapping relationship between the temperature change rate of the battery cell and the charging power and discharging power based on the temperature change trend; and generate the temperature response curve of the battery cell according to the mapping relationship.

[0105] Based on the above embodiments, the remaining power value calculation module is also used to calculate the slope parameter of each voltage response curve and the curvature parameter of each temperature response curve respectively; construct the feature vector of the corresponding battery cell based on the slope parameter and curvature parameter of each battery cell; perform cluster analysis on the feature vector of each battery cell to obtain the vector distance between each feature vector; and classify the battery cells with a vector distance less than the distance threshold into battery packs with the same charge and discharge characteristics.

[0106] Based on the above embodiments, the remaining capacity calculation module is also used to collect the charging cut-off voltage and discharging cut-off voltage of each battery cell during the charging and discharging process for each battery pack; calculate the voltage range of each battery cell based on the charging cut-off voltage and discharging cut-off voltage of each battery cell; calculate the range change of each battery cell's voltage range relative to the reference voltage range, and determine the remaining capacity ratio corresponding to each range change based on a preset remaining capacity mapping table; and use the product between the remaining capacity ratio of each battery cell and the rated capacity of the battery pack as the remaining capacity value of the corresponding battery cell.

[0107] Based on the above embodiments, the power adjustment module is further configured to determine the charging unit and discharging unit in each target battery pair; acquire the discharge power parameters of each charging unit and the charging power parameters of each discharging unit; calculate the power adjustment coefficient of the corresponding target battery pair based on the discharge power parameters and the charging power parameters; synchronously adjust the discharge power of the discharging unit and the charging power of the charging unit in the corresponding target battery pair according to the power adjustment coefficients; detect the charge difference between the charging unit and the discharging unit in each target battery pair, and stop the power adjustment when the charge difference is less than the charge threshold.

[0108] Based on the above embodiments, the power regulation module is further configured to calculate the ratio between the discharge power parameter of the discharge unit in each target battery pair and the rated discharge power as the discharge coefficient; calculate the ratio between the charging power parameter of the charging unit in each target battery pair and the rated charging power as the charging coefficient; obtain the number of charging times of the charging unit and the number of discharging times of the discharge unit in each target battery pair, and determine the charging coefficient weight and the discharge coefficient weight of the corresponding target battery pair charging unit based on the number of charging times and the number of discharging times; for each target battery pair, the charging coefficient of the charging unit and the discharge coefficient of the discharge unit are weighted and calculated based on the charging coefficient weight and the discharge coefficient weight to obtain the power regulation coefficient of the corresponding target battery pair.

[0109] It should be noted that the above embodiments of the apparatus are only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0110] This application also discloses an electronic device. (See reference...) Figure 3 , Figure 3 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application. The electronic device 300 may include: at least one processor 301, at least one network interface 304, a user interface 303, a memory 305, and at least one communication bus 302.

[0111] The communication bus 302 is used to enable communication between these components.

[0112] The user interface 303 may include a display interface and a camera interface. Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0113] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0114] The processor 301 may include one or more processing cores. The processor 301 connects to various parts of the server using various interfaces and lines, and performs various server functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in the memory 305, and by calling data stored in the memory 305. Optionally, the processor 301 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 301 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface graphics, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 301 and may be implemented as a separate chip.

[0115] The memory 305 may include random access memory (RAM) or read-only memory. Optionally, the memory 305 may include a non-transitory computer-readable storage medium. The memory 305 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 305 may also be at least one storage device located remotely from the aforementioned processor 301. (Refer to...) Figure 3 The memory 305, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for an energy storage monitoring method.

[0116] exist Figure 3In the illustrated electronic device 300, the user interface 303 is mainly used to provide an input interface for the user and acquire user input data; while the processor 301 can be used to call an application program storing an energy storage monitoring method in the memory 305. When executed by one or more processors 301, the electronic device 300 performs one or more methods as described in the above embodiments. It should be noted that, for the foregoing method embodiments, for the sake of simplicity, they are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0117] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0118] In the various embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some service interface; the indirect coupling or communication connection between apparatuses or units may be electrical or other forms.

[0119] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0120] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0121] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0122] The above are merely exemplary embodiments of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Other embodiments of this disclosure will be readily apparent to those skilled in the art upon consideration of the specification and practical disclosure.

[0123] This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure. The specification and embodiments are to be considered exemplary only.

Claims

1. An energy storage monitoring method, characterized in that, include: Acquire voltage and temperature data for multiple different types of battery cells; Based on the voltage data, a voltage response curve for the corresponding battery cell is generated, and based on the temperature data, a temperature response curve for the corresponding battery cell is generated. Based on the voltage response curves and temperature response curves, each battery cell is divided into multiple battery packs with different charge and discharge characteristics, and the remaining charge value of each battery cell in each battery pack is calculated. In each of the battery packs, the remaining power value of each battery cell is combined to determine the power difference between each battery cell, and each battery cell with a power difference greater than a power threshold is designated as the target battery pair; The power parameters of each target battery pair are concurrently balanced until the power difference between each target battery pair is less than the power threshold. The step of dividing each battery cell into multiple battery packs with different charge-discharge characteristics based on each voltage response curve and each temperature response curve includes: Calculate the slope parameter of each voltage response curve and the curvature parameter of each temperature response curve respectively; Based on the slope and curvature parameters of each battery cell, a feature vector for the corresponding battery cell is constructed. Cluster analysis is performed on the feature vectors of each battery cell to obtain the vector distance between each feature vector; Battery cells whose vector distance is less than a distance threshold are grouped into battery packs with the same charge / discharge characteristics.

2. The energy storage monitoring method according to claim 1, characterized in that, The generation of the voltage response curve for the corresponding battery cell based on each of the voltage data includes: For each battery cell, voltage data under charging conditions and voltage data under discharging conditions are extracted from the voltage data. The voltage data under the charging condition and the voltage data under the discharging condition are respectively time-sequenced to obtain the charging voltage sequence and the discharging voltage sequence; Generate the charging response curve corresponding to the charging voltage sequence and the discharging response curve corresponding to the discharging voltage sequence; The charging response curve and the discharging response curve are used as the voltage response curves corresponding to the battery cell.

3. The energy storage monitoring method according to claim 1, characterized in that, The step of generating the temperature response curve of the corresponding battery cell based on the temperature data includes: For each of the battery cells, identify the temperature change trend of the temperature data under charging conditions and the temperature change trend under discharging conditions; Based on the temperature change trend, a mapping relationship is established between the temperature change rate of the battery cell and the charging power and discharging power. The temperature response curve of the battery cell is generated based on the mapping relationship.

4. The energy storage monitoring method according to claim 1, characterized in that, The calculation of the remaining charge value of each battery cell in each of the battery packs includes: For each of the battery packs, the charging cut-off voltage and discharging cut-off voltage of each of the battery cells are collected during the charging and discharging process; Calculate the voltage range of each battery cell based on the charging cut-off voltage and discharging cut-off voltage of each battery cell; Calculate the range change of each battery cell's voltage range relative to the reference voltage range, and determine the remaining capacity ratio corresponding to each range change based on a preset remaining capacity mapping table; The product of the remaining capacity percentage of each battery cell and the rated capacity of the battery pack is taken as the remaining power value of the corresponding battery cell.

5. The energy storage monitoring method according to claim 1, characterized in that, The step of concurrently equalizing the power parameters of each target battery pair until the power difference between the target battery pairs is less than the power threshold includes: Identify the charging unit and discharging unit in each of the target battery pairs; Obtain the discharge power parameters of each of the charging units and the charging power parameters of each of the discharge units; Based on the discharge power parameters and the charging power parameters, calculate the power regulation coefficient of the corresponding target battery pair; Based on the power adjustment coefficients described above, the discharge power of the corresponding target battery's discharge unit and the charging power of the charging unit are adjusted synchronously. The power difference between the charging unit and the discharging unit of each target battery pair is detected. When the power difference is less than the power threshold, the power adjustment is stopped.

6. The energy storage monitoring method according to claim 5, characterized in that, The calculation of the power regulation coefficient for the corresponding target battery pair based on each of the discharge power parameters and each of the charging power parameters includes: The ratio between the discharge power parameter of each target battery's centering discharge unit and the rated discharge power is calculated as the discharge coefficient. The ratio between the charging power parameter of each target battery pair's charging unit and the rated charging power is calculated as the charging coefficient. The number of times the charging unit and the number of times the discharging unit of each target battery are charged are obtained, and the charging coefficient weight and the discharging coefficient weight of the corresponding target battery charging unit are determined based on the number of times the charging unit and the number of times the discharging unit are discharged. For each target battery pair, the charging coefficient of the charging unit and the discharging coefficient of the discharging unit are weighted and calculated based on the charging coefficient weight and the discharging coefficient weight to obtain the power regulation coefficient of the corresponding target battery pair.

7. An energy storage monitoring system, characterized in that, The system includes: The data acquisition module is used to acquire voltage and temperature data of multiple different types of battery cells; The response curve generation module is used to generate a voltage response curve for the corresponding battery cell based on the voltage data and to generate a temperature response curve for the corresponding battery cell based on the temperature data. The remaining power value calculation module is used to divide each battery cell into multiple battery packs with different charge and discharge characteristics according to each voltage response curve and each temperature response curve, and to calculate the remaining power value of each battery cell in each battery pack. The power adjustment module is used to determine the power difference between the battery cells in each battery pack by combining the remaining power value of each battery cell, and to designate the battery cells with the power difference greater than the power threshold as target battery pairs; and to perform equalization adjustment on the power parameters of each target battery pair concurrently until the power difference between the target battery pairs is less than the power threshold. The step of dividing each battery cell into multiple battery packs with different charge-discharge characteristics based on each voltage response curve and each temperature response curve includes: Calculate the slope parameter of each voltage response curve and the curvature parameter of each temperature response curve respectively; Based on the slope and curvature parameters of each battery cell, a feature vector for the corresponding battery cell is constructed. Cluster analysis is performed on the feature vectors of each battery cell to obtain the vector distance between each feature vector; Battery cells whose vector distance is less than a distance threshold are grouped into battery packs with the same charge / discharge characteristics.

8. An electronic device, characterized in that, The device includes a processor, a memory, a user interface, and a network interface. The memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory to cause the electronic device to perform the energy storage monitoring method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed, perform the energy storage monitoring method as described in any one of claims 1-6.

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