A method and system for monitoring the failure of an energy storage battery pack

Abstract

The application discloses a kind of fault monitoring method and system of energy storage battery pack, it is related to energy storage system operation monitoring technical field, solve the problem that existing method is difficult to accurately monitor identification when early capacity attenuation fault is generated in energy storage battery pack, method is: according to real-time operation data, whether the abnormal state of battery cell in the energy storage battery pack to be measured exists is judged, and then the monitoring state data when battery cell is constructed to carry out charge-discharge cycle;Whether the fault exists in battery cell is judged by monitoring charge value and monitoring voltage value;The releasable capacity of battery cell is calculated based on monitoring state data, and then whether the capacity attenuation fault exists in the energy storage battery pack to be measured is analyzed and judged in combination with historical operation data, and the application realizes the accurate monitoring identification of capacity attenuation fault of energy storage battery pack.

Description

Technical Field

[0001] This invention belongs to the field of energy storage system operation monitoring technology, specifically a fault monitoring method and system for energy storage battery packs. Background Technology

[0002] An energy storage battery pack is a battery system used to store and release electrical energy. It is usually composed of multiple battery modules, each of which is formed by multiple battery cells connected in a certain series and parallel manner. The energy storage battery pack uses a battery management system to collect and manage the operating parameters of each battery cell, such as voltage, current, state of charge, and temperature, to achieve the storage, conversion, and stable output of electrical energy. Depending on the application scenario, energy storage battery packs can be used in fields such as grid peak shaving, renewable energy consumption, backup power, and industrial energy storage. Its performance and safety are affected by the consistency of battery cells, capacity decay status, and abnormal conditions during operation.

[0003] In the existing technology, when analyzing whether there are abnormalities in the capacity state of energy storage battery packs, the existing methods usually only rely on the difference between the current capacity value and the rated capacity value of the energy storage battery pack. It is difficult to fully consider the capacity decay law of the energy storage battery pack during long-term charge and discharge cycles and the correlation changes between the state of charge and the individual cell voltage during discharge. The accuracy of capacity decay fault identification of energy storage battery packs is low, and it is easy to misjudge or miss faults. Therefore, this invention proposes a fault monitoring method and system for energy storage battery packs. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the present invention aims to provide a fault monitoring method and system for energy storage battery packs.

[0005] The technical problem to be solved by this invention is: How to accurately monitor and identify capacity degradation faults in energy storage battery packs.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: A fault monitoring method for an energy storage battery pack, the method comprising: Step S1: Based on real-time operating data, determine whether there is an abnormal state of the battery cells in the energy storage battery pack under test, and then construct monitoring status data of the battery cells during charge and discharge cycles. Step S2: Determine whether there is a fault in the battery cell by monitoring the charge value and the voltage value; Step S3: Calculate the release capacity of the battery cell based on the monitoring status data, and then analyze and determine whether there is a capacity decay fault in the energy storage battery pack under test by combining historical operating data.

[0007] Preferably, the real-time operating data includes the real-time voltage, real-time current, and real-time temperature values ​​of all battery cells in the energy storage battery pack under test. The monitoring status data includes the monitored charge value, monitored voltage value, and cumulative discharge capacity of the battery cell at all time points during the discharge period.

[0008] Preferably, step S1 includes the following sub-steps: Step S11: Number the energy storage battery pack under test, all battery modules, and all battery cells respectively. Step S12: Obtain the real-time voltage, real-time current and real-time temperature values ​​of all battery cells, and compare the real-time voltage value with the safe voltage range, the real-time current value with the safe current range, and the real-time temperature value with the safe temperature range respectively. If the real-time voltage value, real-time current value, or real-time temperature value of any battery cell is not within the safe voltage range, is not within the safe current range, or is not within the safe temperature range, then the corresponding battery cell is determined to be in an abnormal state, the circuit of the corresponding battery cell is disconnected, and no further fault monitoring is performed. If the real-time voltage value of all battery cells is within the safe voltage value range, the real-time current value is within the safe current value range, and the real-time temperature value is within the safe temperature value range, then proceed to step S13. Step S13: Obtain the monitoring charge value of all battery cells in the energy storage battery pack under test, discharge all battery cells until the monitoring charge value of the battery cell is less than or equal to the preset charge threshold, then stop discharging, and then perform a charge-discharge cycle on any battery cell, obtain the discharge time point of the corresponding battery cell, and record the time point after the discharge time point when the monitoring charge value is less than or equal to the preset charge threshold as the end time point. Step S14: The time period consisting of the discharge time point and the end time point is taken as the discharge period.

[0009] Preferably, step S1 further includes the following sub-steps: Step S15: The monitored charge value, monitored voltage value and cumulative discharge capacity of the battery cell at all time points during the discharge period are summarized into the monitoring set of the battery cell. The monitoring set obtained after a fixed number of charge and discharge cycles is merged and summarized into the monitoring status data of the battery cell. Step S16: Repeat step S15 to obtain the monitoring status data of all battery cells in the energy storage battery pack under test, and construct a mapping relationship between the battery cells and the monitoring status data based on the battery cell number. Step S17: Denoise the monitoring status data of the battery cells.

[0010] Preferably, the construction process is as follows: The battery cell numbered Aij is associated with the corresponding monitoring status data and stored to form a structured data table; where i represents the i-th battery module, 1≤i≤n, and j represents the j-th battery cell in the battery module, 1≤j≤m; The structured data table contains the following fields: battery cell number, battery module number to which the battery cell belongs, battery storage group number to which the battery module belongs, monitored charge value during charge-discharge cycles, monitored voltage value, and cumulative discharge capacity; the structured data table uses timestamps as indexes.

[0011] Preferably, step S2 includes the following sub-steps: Step S21: Obtain the monitored charge value and monitored voltage value of the battery cell at all time points, subtract the monitored charge value of the previous time point from the monitored charge value of the next time point, and calculate the charge difference between adjacent time points. At the same time, subtract the monitored voltage value of the previous time point from the monitored voltage value of the next time point, and calculate the voltage difference between adjacent time points. Step S22: When the charge difference between adjacent time points is greater than or equal to zero, obtain the voltage difference between the corresponding adjacent time points; If the voltage difference is greater than or equal to zero, the adjacent time point is determined to be a candidate anomaly point, and the process proceeds to step S23. If the voltage difference is less than zero, the battery cell is determined to be faulty, and subsequent monitoring is stopped. When the charge difference between adjacent time points is less than zero, it is determined that the battery cell has no abnormality at the corresponding adjacent time point; Step S23: Obtain the charge difference and voltage difference corresponding to a fixed number of consecutive time points after the candidate anomaly point; Step S24: Count the suspected abnormal time points where the charge difference is greater than or equal to zero or the voltage difference is greater than or equal to zero, and determine whether the suspected abnormal time points are continuous. If the suspected abnormal time points are consecutive, proceed to step S25; If the suspected abnormal time points are not continuous, the corresponding suspected abnormal time points are determined to be instantaneous fluctuations of the battery cells, and no fault determination is required. Then proceed to step S3. Step S25: Count the number of abnormal time points corresponding to consecutive suspected abnormal time points, and compare the number of abnormal time points with the number threshold. When the number of abnormal time points is greater than or equal to the number threshold, it is determined that there is an abnormal voltage rebound in the battery cell, and subsequent monitoring is stopped; When the number of abnormal time points is less than the number threshold, the corresponding suspected abnormal time point is determined to be an instantaneous fluctuation of the battery cell, and no fault determination is required. Then proceed to step S3.

[0012] Preferably, the historical operating data includes the normal release capacity of all battery cells in the normal energy storage battery pack after each charge-discharge cycle under normal operating conditions, as well as the total release capacity of the normal energy storage battery pack.

[0013] Preferably, step S3 includes the following sub-steps: Step S31: Obtain the cumulative discharge capacity and monitoring voltage value of the battery cell at all time points in any charge-discharge cycle. Subtract the cumulative discharge capacity of the previous time point from the cumulative discharge capacity of the next time point one by one to calculate the discharge capacity increment between adjacent time points until the monitoring voltage value of the battery cell is equal to the minimum voltage and the calculation stops. Specifically, the time point corresponding to the monitoring voltage value being equal to the minimum voltage is earlier than the end time point; since the battery cells during the discharge period are analyzed, the cumulative discharge capacity shows a monotonically increasing trend, and the corresponding discharge capacity increment is greater than or equal to zero. Step S32: Sum the discharge capacity increments of all battery cells to calculate the release capacity of the corresponding battery cell. Step S33: Repeat steps S31 and S32 to calculate the release capacity of all battery cells in all charge-discharge cycles. Step S34: Analyze and determine whether the energy storage battery pack under test has a capacity decay fault.

[0014] Preferably, the analysis process in step S34 is as follows: Step S3401: Obtain the normal release capacity of any battery cell in the normal energy storage battery pack after each charge-discharge cycle. Subtract the normal release capacity of the previous charge-discharge cycle from the normal release capacity of the next charge-discharge cycle. Then divide the calculated result by the normal release capacity of the previous charge-discharge cycle and take the absolute value to calculate the capacity decay rate between adjacent charge-discharge cycles. Step S3402: Repeat step S3401 to obtain the standard capacity decay rate between adjacent charge and discharge cycles of all battery cells in the normal energy storage battery pack after a fixed number of charge and discharge cycles. Iterate through all capacity decay rates to obtain the maximum capacity decay rate of all battery cells in the normal energy storage battery pack. Step S3403: Obtain the release capacity of the battery cells in the energy storage battery pack under test in all charge and discharge cycles. Repeat step S3401 to calculate the test capacity decay rate of all battery cells in the energy storage battery pack under test. Step S3404: Compare the test capacity decay rate of any battery cell in the energy storage battery pack under test with the maximum capacity decay rate. If all tested capacity decay rates are less than or equal to the maximum capacity decay rate, it is determined that there is no aging fault in any of the battery cells in the energy storage battery pack under test. If any test capacity decay rate is greater than the maximum capacity decay rate, proceed to step S3405; Step S3405: ​​Sum the release capacity of all battery cells in the energy storage battery pack under test to obtain the total release capacity of the corresponding energy storage battery pack under test in the current charge-discharge cycle, and divide the total release capacity by the total release capacity of normal energy storage battery packs in historical operating data to calculate the capacity retention rate of the energy storage battery pack under test. Step S3406: If the capacity retention rate is less than or equal to the health threshold, it is determined that the corresponding energy storage battery pack under test has a capacity decay fault, and a fault alarm signal is generated. If the capacity retention rate is greater than the health threshold, the corresponding energy storage battery pack under test is determined to be in normal operating condition.

[0015] The present invention also provides a fault monitoring system for energy storage battery packs, including a data acquisition module, a status monitoring module, a data construction module, an anomaly determination module, a capacity detection module, and a database module; The data acquisition module is used to collect real-time operating data from the energy storage battery pack under test and send the real-time operating data to the status monitoring module. The database module is used to store the safe voltage range, safe current range, and safe temperature range of the energy storage battery pack, as well as the historical operating data of the normal energy storage battery pack. It also sends the safe voltage range, safe current range, and safe temperature range to the status monitoring module, and sends the historical operating data to the capacity detection module. The status monitoring module is used to monitor whether there is an abnormal state in all battery cells in the energy storage battery pack under test based on real-time operating data. When there is no abnormal state, a no-abnormal signal is generated and sent to the data construction module. The data acquisition module is also used to acquire safe voltage range, safe current range, and safe temperature range, and send the safe voltage range, safe current range, and safe temperature range to the data construction module; The data construction module is used to merge and summarize the safe voltage range, safe current range, and safe temperature range into the monitoring status data of the battery cell when no abnormal signal is received, and send the monitoring status data to the abnormality judgment module and the capacity detection module. The anomaly detection module is used to determine whether there is a fault in the battery cell by monitoring the charge value and the voltage value. The capacity detection module is used to calculate the release capacity of the battery cell based on the monitoring status data, and then analyze and determine whether there is a capacity decay fault in the energy storage battery pack under test by combining historical operating data.

[0016] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention first determines whether there is an abnormal state in the battery cells of the energy storage battery pack under test based on real-time operating data, and then constructs monitoring status data of the battery cells during charge and discharge cycles to realize dynamic monitoring of the capacity decay trend of the energy storage battery pack, more accurately identify capacity decay faults, avoid the problem of misjudgment and omission caused by relying solely on rated capacity comparison, and improve the accuracy of fault identification of energy storage battery packs.

[0017] 2. This invention determines whether there is a fault in the battery cell by monitoring the charge value and voltage value, then calculates the release capacity of the battery cell based on the monitoring status data, and finally analyzes and determines whether there is a capacity decay fault in the energy storage battery pack under test by combining historical operating data, thereby achieving accurate early warning of capacity decay faults in the energy storage battery pack and enhancing the operational stability and safety of the energy storage battery pack. Attached Figure Description

[0018] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0019] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a structural example diagram of the energy storage battery pack in this invention; Figure 3 This is a flowchart for determining whether a battery pack under test has a capacity decay fault in this invention; Figure 4 This is an overall system block diagram of the present invention. Detailed Implementation

[0020] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Example 1, please refer to Figures 1-3As shown, the technical solution provided by this invention is: a fault monitoring method for energy storage battery packs. This method first makes a preliminary judgment on whether a fault exists in the energy storage battery pack under test in its current operating state based on real-time operating data. Then, it performs charge-discharge cycles on the energy storage battery pack under test, identifies the discharge period during the charge-discharge cycle, constructs monitoring status data of the battery cells during the discharge period when the energy storage battery pack under test is performing charge-discharge cycles, and performs noise reduction processing on the detected status data to obtain noise-reduced monitoring status data. The method calculates the charge difference and voltage difference between adjacent time points by monitoring the charge value and the voltage value, and then uses the charge difference and voltage difference as the basis for further analysis. The difference is used to analyze and determine whether there is a fault in the battery cell. When there is no fault, the discharge capacity increment of the battery cell between adjacent time points is calculated based on the cumulative discharge capacity and the monitored voltage value. The release capacity of the corresponding battery cell is obtained by summing the discharge capacity increments. The maximum capacity decay rate of all battery cells in the normal energy storage battery pack is calculated based on the normal release capacity of any battery cell after each charge-discharge cycle. At the same time, the test capacity decay rate of all battery cells in the energy storage battery pack under test is calculated. The presence of a fault in the energy storage battery pack under test is determined by the maximum capacity decay rate and the test capacity decay rate.

[0022] In this embodiment, the fault monitoring method includes the following steps: Step S1: Based on real-time operating data, determine whether there is an abnormal state of the battery cells in the energy storage battery pack under test, and then construct monitoring status data of the battery cells during charge and discharge cycles. In this embodiment, the energy storage battery pack under test consists of multiple battery modules, and each battery module consists of multiple battery cells. Multiple battery cells are connected in a preset manner to form corresponding battery modules, and multiple battery modules form the energy storage battery pack. The battery cells can be one of lithium iron phosphate batteries, ternary lithium batteries, sodium-ion batteries, or lead-acid batteries. The real-time operating data specifically includes the real-time voltage, real-time current, and real-time temperature values ​​of all battery cells in the energy storage battery pack under test. Real-time voltage values ​​can be collected using a voltage sensor, real-time current values ​​using a current sensor, and real-time temperature values ​​using a temperature sensor. The monitoring status data specifically includes the monitored charge value, monitored voltage value, and cumulative discharge capacity of the battery cells at all time points during the discharge period. In this embodiment, step S1 includes the following sub-steps: Step S11: Number the energy storage battery pack under test, all battery modules, and all battery cells respectively. For example, the battery pack under test can be numbered A, B, C or D, etc., and the corresponding battery modules in the battery pack can be numbered A-1, A-2, ..., An. The battery cells in each battery module can be numbered A-1-1, A-1-2, ..., A-1-m; n is the maximum number of battery modules in the battery pack under test, and m is the maximum number of battery cells in the battery module. Step S12: Obtain the real-time voltage, real-time current and real-time temperature values ​​of all battery cells, and compare the real-time voltage value with the safe voltage range, the real-time current value with the safe current range, and the real-time temperature value with the safe temperature range respectively. If the real-time voltage value, real-time current value, or real-time temperature value of any battery cell is not within the safe voltage range, is not within the safe current range, or is not within the safe temperature range, then the corresponding battery cell is determined to be in an abnormal state, the circuit of the corresponding battery cell is disconnected, and no further fault monitoring is performed. If the real-time voltage value of all battery cells is within the safe voltage value range, the real-time current value is within the safe current value range, and the real-time temperature value is within the safe temperature value range, then proceed to step S13. Among them, the safe voltage range, safe current range, and safe temperature range can be preset according to industry standards; Step S13: Obtain the monitoring charge value of all battery cells in the energy storage battery pack under test, discharge all battery cells until the monitoring charge value of the battery cell is less than or equal to the preset charge threshold, then stop discharging, and then perform a charge-discharge cycle on any battery cell, obtain the discharge time point of the corresponding battery cell, and record the time point after the discharge time point when the monitoring charge value is less than or equal to the preset charge threshold as the end time point. In practice, the monitored charge value is specifically the ratio of the battery cell's current remaining capacity to its rated capacity when fully charged. This is typically estimated using the ampere-hour integration method combined with open-circuit voltage correction, which will not be elaborated here. The charge-discharge cycle is specifically the process of charging the battery cell to full capacity, letting it rest for a fixed period of time, and then discharging the battery cell to its minimum voltage. The minimum voltage is specifically the lower limit of the battery cell's voltage. When the battery cell's voltage is lower than the minimum voltage, the battery cell will stop discharging to avoid over-discharge damage. The preset charge threshold is calculated numerically based on the battery type and usage scenario. Step S14: The time period consisting of the discharge time point and the end time point is taken as the discharge period. Step S15: The monitored charge value, monitored voltage value and cumulative discharge capacity of the battery cell at all time points during the discharge period are summarized into the monitoring set of the battery cell. The monitoring set obtained after a fixed number of charge and discharge cycles is merged and summarized into the monitoring status data of the battery cell. Step S16: Repeat step S15 to obtain the monitoring status data of all battery cells in the energy storage battery pack under test, and construct a mapping relationship between the battery cells and the monitoring status data based on the battery cell number. The specific construction process is as follows: The battery cell numbered Aij is associated with its corresponding monitoring status data and stored to form a structured data table. Here, i represents the i-th battery module (1≤i≤n), and j represents the j-th battery cell within the battery module (1≤j≤m). The structured data table includes the following fields: battery cell number, battery module number to which the battery cell belongs, battery group number to which the battery module belongs, monitored charge value during charge / discharge cycles, monitored voltage value, and cumulative discharge capacity. The structured data table uses a timestamp as its index. The associated storage involves writing the monitoring status data into a database or storage unit in chronological order. Step S17: Denoise the monitoring status data of the battery cells. The denoising process is as follows: A fixed-size sliding window is constructed, and then any sequence of monitoring status data is selected as input. The sliding window slides sequentially along the time axis, and median filtering is performed on the data within the window to obtain the denoised monitoring status data.

[0023] Step S2: Determine whether there is a fault in the battery cell by monitoring the charge value and the voltage value; In this embodiment, step S2 includes the following sub-steps: Step S21: Obtain the monitored charge value and monitored voltage value of the battery cell at all time points, subtract the monitored charge value of the previous time point from the monitored charge value of the next time point, and calculate the charge difference between adjacent time points. At the same time, subtract the monitored voltage value of the previous time point from the monitored voltage value of the next time point, and calculate the voltage difference between adjacent time points. It should be noted that during the discharge process of the battery cell, the monitored charge value of the battery cell shows a decreasing trend, and the monitored voltage value also shows a decreasing trend. Therefore, the abnormality of the battery cell can be determined by the difference in charge and voltage. Step S22: When the charge difference between adjacent time points is greater than or equal to zero, obtain the voltage difference between the corresponding adjacent time points; If the voltage difference is greater than or equal to zero, the adjacent time point is determined to be a candidate anomaly point, and the process proceeds to step S23. If the voltage difference is less than zero, the battery cell is determined to be faulty, and subsequent monitoring is stopped. When the charge difference between adjacent time points is less than zero, it is determined that the battery cell has no abnormality at the corresponding adjacent time point; Step S23: Obtain the charge difference and voltage difference corresponding to a fixed number of consecutive time points after the candidate anomaly point; Step S24: Count the suspected abnormal time points where the charge difference is greater than or equal to zero or the voltage difference is greater than or equal to zero, and determine whether the suspected abnormal time points are continuous. If the suspected abnormal time points are consecutive, proceed to step S25; If the suspected abnormal time points are not continuous, the corresponding suspected abnormal time points are determined to be instantaneous fluctuations of the battery cells, and no fault determination is required. Then proceed to step S3. Step S25: Count the number of abnormal time points corresponding to consecutive suspected abnormal time points, and compare the number of abnormal time points with the number threshold. When the number of abnormal time points is greater than or equal to the number threshold, it is determined that there is an abnormal voltage rebound in the battery cell, and subsequent monitoring is stopped; When the number of abnormal time points is less than the number threshold, the corresponding suspected abnormal time point is determined to be an instantaneous fluctuation of the battery cell, and no fault determination is required. Then proceed to step S3.

[0024] Step S3: Calculate the release capacity of the battery cell based on the monitoring status data, and then analyze and determine whether there is a capacity decay fault in the energy storage battery pack under test by combining historical operating data. In practice, historical operating data specifically refers to the normal release capacity of all battery cells in a normal energy storage battery pack after each charge-discharge cycle under normal operating conditions, as well as the total release capacity of the normal energy storage battery pack. In this embodiment, step S3 includes the following sub-steps: Step S31: Obtain the cumulative discharge capacity and monitoring voltage value of the battery cell at all time points in any charge-discharge cycle. Subtract the cumulative discharge capacity of the previous time point from the cumulative discharge capacity of the next time point one by one to calculate the discharge capacity increment between adjacent time points until the monitoring voltage value of the battery cell is equal to the minimum voltage and the calculation stops. Specifically, the time point corresponding to the monitoring voltage value being equal to the minimum voltage is earlier than the end time point; since the battery cells during the discharge period are analyzed, the cumulative discharge capacity shows a monotonically increasing trend, and the corresponding discharge capacity increment is greater than or equal to zero. Step S32: Sum the discharge capacity increments of all battery cells to calculate the release capacity of the corresponding battery cell. Step S33: Repeat steps S31 and S32 to calculate the release capacity of all battery cells in all charge-discharge cycles. Step S34: Analyze and determine whether the energy storage battery pack under test has a capacity degradation fault. The specific analysis process is as follows: Step S3401: Obtain the normal release capacity of any battery cell in the normal energy storage battery pack after each charge-discharge cycle. Subtract the normal release capacity of the previous charge-discharge cycle from the normal release capacity of the next charge-discharge cycle. Then divide the calculated result by the normal release capacity of the previous charge-discharge cycle and take the absolute value to calculate the capacity decay rate between adjacent charge-discharge cycles. Step S3402: Repeat step S3401 to obtain the standard capacity decay rate between adjacent charge and discharge cycles of all battery cells in the normal energy storage battery pack after a fixed number of charge and discharge cycles. Iterate through all capacity decay rates to obtain the maximum capacity decay rate of all battery cells in the normal energy storage battery pack. Step S3403: Obtain the release capacity of the battery cells in the energy storage battery pack under test in all charge and discharge cycles. Repeat step S3401 to calculate the test capacity decay rate of all battery cells in the energy storage battery pack under test. Step S3404: Compare the test capacity decay rate of any battery cell in the energy storage battery pack under test with the maximum capacity decay rate. If all tested capacity decay rates are less than or equal to the maximum capacity decay rate, it is determined that there is no aging fault in any of the battery cells in the energy storage battery pack under test. If any test capacity decay rate is greater than the maximum capacity decay rate, proceed to step S3405; Step S3405: ​​Sum the release capacity of all battery cells in the energy storage battery pack under test to obtain the total release capacity of the corresponding energy storage battery pack under test in the current charge-discharge cycle, and divide the total release capacity by the total release capacity of normal energy storage battery packs in historical operating data to calculate the capacity retention rate of the energy storage battery pack under test. In practice, the total release capacity C of the energy storage battery pack under test within the current charge-discharge cycle can be calculated using the serial number of the battery pack under test, the serial numbers of all battery modules within the battery pack, and the serial numbers of all battery cells within each battery module. A The calculation process is as follows: The release capacity of all battery cells numbered Aij (1≤i≤n, 1≤j≤m) in the current charge-discharge cycle is accumulated using the following formula: , where C A，i，j Specifically, the release capacity corresponds to the battery cell numbered Aij; Step S3406: If the capacity retention rate is less than or equal to the health threshold, it is determined that the corresponding energy storage battery pack under test has a capacity decay fault, and a fault alarm signal is generated. If the capacity retention rate is greater than the health threshold, the corresponding energy storage battery pack under test is determined to be in normal operating condition.

[0025] Example 2, please refer to Figure 4 As shown, based on another concept of the same invention, a fault monitoring system for energy storage battery packs is proposed, including a data acquisition module, a status monitoring module, a data construction module, an anomaly determination module, a capacity detection module, and a database module; The data acquisition module is used to collect real-time operating data from the energy storage battery pack under test and send the real-time operating data to the status monitoring module. The database module is used to store the safe voltage range, safe current range, and safe temperature range of the energy storage battery pack, as well as the historical operating data of the normal energy storage battery pack. It also sends the safe voltage range, safe current range, and safe temperature range to the status monitoring module, and sends the historical operating data to the capacity detection module. The status monitoring module is used to monitor whether there is an abnormal state in all battery cells in the energy storage battery pack under test based on real-time operating data. When there is no abnormal state, a no-abnormal signal is generated and sent to the data construction module. The data acquisition module is also used to acquire safe voltage range, safe current range, and safe temperature range, and send the safe voltage range, safe current range, and safe temperature range to the data construction module; The data construction module is used to merge and summarize the safe voltage range, safe current range, and safe temperature range into the monitoring status data of the battery cell when no abnormal signal is received, and send the monitoring status data to the abnormality judgment module and the capacity detection module. The anomaly detection module is used to determine whether there is a fault in the battery cell by monitoring the charge value and the voltage value. The capacity detection module is used to calculate the release capacity of the battery cell based on the monitoring status data, and then analyze and determine whether there is a capacity decay fault in the energy storage battery pack under test by combining historical operating data.

[0026] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A fault monitoring method for an energy storage battery pack, characterized in that, The methods include: Step S1: Based on real-time operating data, determine whether there is an abnormal state of the battery cells in the energy storage battery pack under test, and then construct monitoring status data of the battery cells during charge and discharge cycles. Step S2: Determine whether there is a fault in the battery cell by monitoring the charge value and the voltage value; Step S3: Calculate the release capacity of the battery cell based on the monitoring status data, and then analyze and determine whether there is a capacity decay fault in the energy storage battery pack under test by combining historical operating data.

2. The fault monitoring method for an energy storage battery pack according to claim 1, characterized in that, The real-time operating data includes the real-time voltage, real-time current, and real-time temperature values ​​of all battery cells in the energy storage battery pack under test. The monitoring status data includes the monitored charge value, monitored voltage value, and cumulative discharge capacity of the battery cell at all time points during the discharge period.

3. The fault monitoring method for an energy storage battery pack according to claim 2, characterized in that, Step S1 includes the following sub-steps: Step S11: Number the energy storage battery pack under test, all battery modules, and all battery cells respectively. Step S12: Obtain the real-time voltage, real-time current and real-time temperature values ​​of all battery cells, and compare the real-time voltage value with the safe voltage range, the real-time current value with the safe current range, and the real-time temperature value with the safe temperature range respectively. If the real-time voltage value, real-time current value, or real-time temperature value of any battery cell is not within the safe voltage range, is not within the safe current range, or is not within the safe temperature range, then the corresponding battery cell is determined to be in an abnormal state, the circuit of the corresponding battery cell is disconnected, and no further fault monitoring is performed. If the real-time voltage value of all battery cells is within the safe voltage value range, the real-time current value is within the safe current value range, and the real-time temperature value is within the safe temperature value range, then proceed to step S13. Step S13: Obtain the monitoring charge value of all battery cells in the energy storage battery pack under test, discharge all battery cells until the monitoring charge value of the battery cell is less than or equal to the preset charge threshold, then stop discharging, and then perform a charge-discharge cycle on any battery cell, obtain the discharge time point of the corresponding battery cell, and record the time point after the discharge time point when the monitoring charge value is less than or equal to the preset charge threshold as the end time point. Step S14: The time period consisting of the discharge time point and the end time point is taken as the discharge period.

4. The fault monitoring method for an energy storage battery pack according to claim 3, characterized in that, Step S1 further includes the following sub-steps: Step S15: The monitored charge value, monitored voltage value and cumulative discharge capacity of the battery cell at all time points during the discharge period are summarized into the monitoring set of the battery cell. The monitoring set obtained after a fixed number of charge and discharge cycles is merged and summarized into the monitoring status data of the battery cell. Step S16: Repeat step S15 to obtain the monitoring status data of all battery cells in the energy storage battery pack under test, and construct a mapping relationship between the battery cells and the monitoring status data based on the battery cell number. Step S17: Denoise the monitoring status data of the battery cells.

5. The fault monitoring method for an energy storage battery pack according to claim 4, characterized in that, The specific construction process is as follows: The battery cell numbered Aij is associated with the corresponding monitoring status data and stored to form a structured data table; where i represents the i-th battery module, 1≤i≤n, and j represents the j-th battery cell in the battery module, 1≤j≤m; The structured data table contains the following fields: battery cell number, battery module number to which the battery cell belongs, battery storage group number to which the battery module belongs, monitored charge value during charge-discharge cycles, monitored voltage value, and cumulative discharge capacity. Structured data tables use timestamps as indexes.

6. The fault monitoring method for an energy storage battery pack according to claim 1, characterized in that, Step S2 includes the following sub-steps: Step S21: Obtain the monitored charge value and monitored voltage value of the battery cell at all time points, subtract the monitored charge value of the previous time point from the monitored charge value of the next time point, and calculate the charge difference between adjacent time points. At the same time, subtract the monitored voltage value of the previous time point from the monitored voltage value of the next time point, and calculate the voltage difference between adjacent time points. Step S22: When the charge difference between adjacent time points is greater than or equal to zero, obtain the voltage difference between the corresponding adjacent time points; If the voltage difference is greater than or equal to zero, the adjacent time point is determined to be a candidate anomaly point, and the process proceeds to step S23. If the voltage difference is less than zero, the battery cell is determined to be faulty, and subsequent monitoring is stopped. When the charge difference between adjacent time points is less than zero, it is determined that the battery cell has no abnormality at the corresponding adjacent time point; Step S23: Obtain the charge difference and voltage difference corresponding to a fixed number of consecutive time points after the candidate anomaly point; Step S24: Count the suspected abnormal time points where the charge difference is greater than or equal to zero or the voltage difference is greater than or equal to zero, and determine whether the suspected abnormal time points are continuous. If the suspected abnormal time points are consecutive, proceed to step S25; If the suspected abnormal time points are not continuous, the corresponding suspected abnormal time points are determined to be instantaneous fluctuations of the battery cells, and no fault determination is required. Then proceed to step S3. Step S25: Count the number of abnormal time points corresponding to consecutive suspected abnormal time points, and compare the number of abnormal time points with the number threshold. When the number of abnormal time points is greater than or equal to the number threshold, it is determined that there is an abnormal voltage rebound in the battery cell, and subsequent monitoring is stopped; When the number of abnormal time points is less than the number threshold, the corresponding suspected abnormal time point is determined to be an instantaneous fluctuation of the battery cell, and no fault determination is required. Then proceed to step S3.

7. The fault monitoring method for an energy storage battery pack according to claim 1, characterized in that, Historical operating data represents the normal release capacity of all battery cells in a normal energy storage battery pack after each charge-discharge cycle under normal operating conditions, as well as the total release capacity of the normal energy storage battery pack.

8. The fault monitoring method for an energy storage battery pack according to claim 7, characterized in that, Step S3 includes the following sub-steps: Step S31: Obtain the cumulative discharge capacity and monitoring voltage value of the battery cell at all time points in any charge-discharge cycle. Subtract the cumulative discharge capacity of the previous time point from the cumulative discharge capacity of the next time point one by one to calculate the discharge capacity increment between adjacent time points until the monitoring voltage value of the battery cell is equal to the minimum voltage and the calculation stops. Specifically, the time point corresponding to the monitoring voltage value being equal to the minimum voltage is earlier than the end time point; since the battery cells during the discharge period are analyzed, the cumulative discharge capacity shows a monotonically increasing trend, and the corresponding discharge capacity increment is greater than or equal to zero. Step S32: Sum the discharge capacity increments of all battery cells to calculate the release capacity of the corresponding battery cell. Step S33: Repeat steps S31 and S32 to calculate the release capacity of all battery cells in all charge-discharge cycles. Step S34: Analyze and determine whether the energy storage battery pack under test has a capacity decay fault.

9. A fault monitoring method for an energy storage battery pack according to claim 8, characterized in that, The analysis process in step S34 is as follows: Step S3401: Obtain the normal release capacity of any battery cell in the normal energy storage battery pack after each charge-discharge cycle. Subtract the normal release capacity of the previous charge-discharge cycle from the normal release capacity of the next charge-discharge cycle. Then divide the calculated result by the normal release capacity of the previous charge-discharge cycle and take the absolute value to calculate the capacity decay rate between adjacent charge-discharge cycles. Step S3402: Repeat step S3401 to obtain the standard capacity decay rate between adjacent charge and discharge cycles of all battery cells in the normal energy storage battery pack after a fixed number of charge and discharge cycles. Iterate through all capacity decay rates to obtain the maximum capacity decay rate of all battery cells in the normal energy storage battery pack. Step S3403: Obtain the release capacity of the battery cells in the energy storage battery pack under test in all charge and discharge cycles. Repeat step S3401 to calculate the test capacity decay rate of all battery cells in the energy storage battery pack under test. Step S3404: Compare the test capacity decay rate of any battery cell in the energy storage battery pack under test with the maximum capacity decay rate. If all tested capacity decay rates are less than or equal to the maximum capacity decay rate, it is determined that there is no aging fault in any of the battery cells in the energy storage battery pack under test. If any test capacity decay rate is greater than the maximum capacity decay rate, proceed to step S3405; Step S3405: ​​Sum the release capacity of all battery cells in the energy storage battery pack under test to obtain the total release capacity of the corresponding energy storage battery pack under test in the current charge-discharge cycle, and divide the total release capacity by the total release capacity of normal energy storage battery packs in historical operating data to calculate the capacity retention rate of the energy storage battery pack under test. Step S3406: If the capacity retention rate is less than or equal to the health threshold, it is determined that the corresponding energy storage battery pack under test has a capacity decay fault, and a fault alarm signal is generated. If the capacity retention rate is greater than the health threshold, the corresponding energy storage battery pack under test is determined to be in normal operating condition.

10. A fault monitoring system for an energy storage battery pack, characterized in that, A fault monitoring method for an energy storage battery pack according to any one of claims 1-9 includes a data acquisition module, a status monitoring module, a data construction module, an anomaly determination module, a capacity detection module, and a database module. The data acquisition module is used to collect real-time operating data from the energy storage battery pack under test and send the real-time operating data to the status monitoring module. The database module is used to store the safe voltage range, safe current range, and safe temperature range of the energy storage battery pack, as well as the historical operating data of the normal energy storage battery pack. It also sends the safe voltage range, safe current range, and safe temperature range to the status monitoring module, and sends the historical operating data to the capacity detection module. The status monitoring module is used to monitor whether there is an abnormal state in all battery cells in the energy storage battery pack under test based on real-time operating data. When there is no abnormal state, a no-abnormal signal is generated and sent to the data construction module. The data acquisition module is also used to acquire safe voltage range, safe current range, and safe temperature range, and send the safe voltage range, safe current range, and safe temperature range to the data construction module; The data construction module is used to merge and summarize the safe voltage range, safe current range, and safe temperature range into the monitoring status data of the battery cell when no abnormal signal is received, and send the monitoring status data to the abnormality judgment module and the capacity detection module. The anomaly detection module is used to determine whether there is a fault in the battery cell by monitoring the charge value and the voltage value. The capacity detection module is used to calculate the release capacity of the battery cell based on the monitoring status data, and then analyze and determine whether there is a capacity decay fault in the energy storage battery pack under test by combining historical operating data.

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