Energy storage system battery cell failure identification method and energy storage system

Abstract

The application provides a kind of energy storage system battery cell fault identification method and energy storage system.The energy storage system battery cell fault identification method includes: setting cell voltage offset threshold upper limit;The cell voltage V_n_i of each battery cell is obtained, wherein n is the number of battery modules, and i is the battery cell number in a battery module;Carry out horizontal comparison to battery cell, obtain the deviation AV_n_i of the cell voltage in the same battery module relative to the average value of the cell voltage in the same battery module;Carry out vertical comparison to battery cell, calculate the difference between the deviation of the battery cell with the same number in each battery module and the median of the deviation of the battery cell with the same number, if the difference is greater than the cell voltage offset threshold upper limit, then judge the battery cell corresponding to the difference is faulty.The energy storage system battery cell fault identification method of the application can accurately identify the voltage offset of battery cell, timely find the battery cell fault in energy storage system, and improve system safety.

Description

Technical Field

[0001] This invention relates to the field of battery technology, and more specifically, to a method for identifying faults in individual battery cells of an energy storage system and an energy storage system. Background Technology

[0002] An energy storage system includes at least multiple battery modules. Each battery module is composed of numerous battery cells connected in series or in parallel. Each battery module is equipped with a battery management system, which is used to collect battery module voltage, current and temperature information, estimate the battery's state of charge (SOC) and state of health (SOH), and identify and diagnose cell faults.

[0003] A related technology discloses a method for assessing the consistency safety status of power batteries. This method involves acquiring a large amount of historical operating data from the vehicle being evaluated, calculating the standard deviation and variance entropy consistency characteristics of the individual cell voltages for each charging data segment to obtain feature values, acquiring the number of charge / discharge cycles, and then constructing a feature matrix from these feature values. The feature matrix is ​​then subjected to unsupervised training using a pre-defined algorithm to obtain a confusion matrix. Based on the confusion matrix, a quantitative calculation model for the consistency safety status of the power battery is constructed. By quantitatively assessing the consistency safety status of the power battery, risk factors can be more intuitively identified from a large amount of historical operating data. However, this method requires dynamically identifying and assessing the internal consistency of the vehicle after a period of operation, and necessitates the optimization of the model using a large amount of historical data. Furthermore, the commonly used BMS (Battery Management System) methods for diagnosing battery cell faults in the industry currently rely on setting upper limits for the voltage of individual cells and the average voltage. When a cell's voltage exceeds the average voltage by a significant margin, it is considered a fault. While this method is simple, it is prone to numerous misjudgments and missed diagnoses. The main reason for this is that after the battery modules are assembled, the differences in the external circuitry of the individual cells (including electrical connector circuitry and sampling line circuitry) mean that even if all individual cells are in the same factory condition, there will still be inconsistencies in the individual cell data collected by the BMS after they are assembled into a battery module. Therefore, if a cell with an initial voltage that is too high or too low malfunctions, and its voltage drops or rises, its individual cell voltage will not deviate from the upper limit of the average voltage. The BMS system cannot identify the fault in time, posing a significant safety hazard. Summary of the Invention

[0004] The main objective of this invention is to provide a method for identifying battery cell faults in an energy storage system and an energy storage system that can accurately identify the voltage deviation of battery cells, promptly detect battery cell faults within the energy storage system, and improve system safety.

[0005] To achieve the above objectives, according to one aspect of the present invention, a method for identifying faults in a battery cell of an energy storage system is provided, comprising:

[0006] Set the upper limit of the individual cell voltage offset threshold;

[0007] Obtain the individual cell voltage V_n_i of each battery cell, where n is the number of battery modules and i is the cell number within a battery module.

[0008] By comparing individual battery cells laterally, the deviation ΔV_n_i of the individual cell voltage within the same battery module relative to the average individual cell voltage within the same battery module is obtained.

[0009] A longitudinal comparison of individual battery cells is performed. The difference between the deviation of individual battery cells with the same number within each battery module and the median deviation of individual battery cells with the same number is calculated. If the difference is greater than the upper limit of the individual cell voltage offset threshold, the battery cell corresponding to that difference is determined to be faulty.

[0010] Furthermore, the step of performing a horizontal comparison of individual battery cells to obtain the deviation ΔV_n_i of the individual cell voltage relative to the average individual cell voltage within the same battery module includes:

[0011] To obtain the average single-cell voltage within the nth battery module: ave_v_n = (v_1 + v_2 + ... + v_i) / i;

[0012] Calculate the deviation of the individual cell voltage V_n_i from the average individual cell voltage within the same battery module, where ΔV_n_i = V_n_i - ave_v_n.

[0013] Furthermore, a longitudinal comparison is performed on individual battery cells. The difference between the deviation of battery cells with the same number within each battery module and the median deviation of battery cells with the same number is calculated. If the difference is greater than the upper limit of the individual cell voltage offset threshold, the steps to determine the battery cell corresponding to this difference as faulty include:

[0014] Arrange the deviations ΔV_n_i of the same numbered battery cells in all battery modules in ascending order, and obtain the median H_n_imid, maximum value H_n_imax and minimum value H_n_imin of the deviations ΔV_n_i of the same numbered battery cells;

[0015] Calculate the maximum voltage offset of individual cells with the same serial number relative to the median:

[0016] MAX=max[(H_n_imax-H_n_imid),(H_n_imid-H_n_imin)].

[0017] Furthermore, a longitudinal comparison of individual battery cells is performed, and the difference between the deviation of battery cells with the same number within each battery module and the median deviation of battery cells with the same number is calculated. If the difference is greater than the upper limit of the individual cell voltage offset threshold, the step of determining the battery cell corresponding to the difference as faulty further includes:

[0018] Identify the cell numbers of those whose voltage difference exceeds the upper limit of the cell voltage offset threshold;

[0019] The BMS for uploading data is determined based on the cell number;

[0020] The BMS determines the corresponding battery module based on the uploaded data.

[0021] Furthermore, each battery module includes a BMS, through which individual battery cells within the battery module upload data to the microgrid controller.

[0022] Furthermore, the method for identifying individual battery cell faults in energy storage systems also includes:

[0023] When a fault is detected in a single battery cell, charging and discharging of the battery module containing that battery cell is stopped.

[0024] Furthermore, the upper limit of the individual cell voltage offset threshold is obtained through experiments or empirical formulas.

[0025] According to another aspect of the present invention, an energy storage system is provided, which applies the above-described energy storage system battery cell fault identification method. The energy storage system includes:

[0026] n battery modules are connected in parallel. Each battery module includes a BMS and multiple battery cells, which are connected in series and / or in parallel.

[0027] The microgrid controller communicates with each BMS to obtain battery module parameters collected by each BMS and processes these parameters.

[0028] Furthermore, the energy storage system also includes an energy storage converter, which is connected to all battery modules and controls the charging and discharging of the battery modules.

[0029] Furthermore, the energy storage converter is electrically connected to the microgrid controller. When the microgrid controller detects a cell fault, it issues a shutdown command to the energy storage converter to stop charging and discharging the battery module.

[0030] The method for identifying battery cell faults in an energy storage system using the technical solution of this invention includes: setting an upper limit for a cell voltage deviation threshold; acquiring the cell voltage V_n_i of each battery cell, where n is the number of battery modules and i is the cell number within a battery module; performing a horizontal comparison of battery cells to obtain the deviation ΔV_n_i of the cell voltage within the same battery module relative to the average cell voltage within the same battery module; performing a vertical comparison of battery cells to calculate the difference between the deviation of cell numbers within each battery module and the median deviation of cell numbers within the same battery module; if the difference is greater than the upper limit for the cell voltage deviation threshold, the battery cell corresponding to the difference is determined to be faulty. This method for identifying battery cell faults in an energy storage system collects cell voltage data from multiple battery modules and sets the average voltage of each battery module as a benchmark, making the voltages of cell numbers or positions within each battery module comparable. Then, the normal voltage of the cell number or position is found by taking the median and set as the benchmark to determine the actual voltage deviation of all cell numbers. This eliminates the influence of the initial consistency of battery modules on the judgment result and avoids misjudgment and missed judgment of faults. Attached Figure Description

[0031] The accompanying drawings, which form part of this application, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0032] Figure 1 A flowchart illustrating a battery cell fault identification method for an energy storage system according to an embodiment of the present invention is shown; and

[0033] Figure 2 A structural diagram of an energy storage system according to an embodiment of the present invention is shown. Detailed Implementation

[0034] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0035] See also Figure 1As shown, this invention provides a method for identifying battery cell faults in an energy storage system, comprising: setting an upper limit for a cell voltage deviation threshold; obtaining the cell voltage V_n_i of each battery cell, where n is the number of battery modules and i is the cell number within a battery module; performing a horizontal comparison of battery cells to obtain the deviation ΔV_n_i of the cell voltage within the same battery module relative to the average cell voltage within the same battery module; performing a vertical comparison of battery cells to calculate the difference between the deviation of the same numbered battery cells within each battery module and the median deviation of the same numbered battery cells; if the difference is greater than the upper limit for the cell voltage deviation threshold, then determining that the battery cell corresponding to the difference is faulty.

[0036] The battery cell fault identification method of this energy storage system collects the individual cell voltage data of multiple battery modules and sets the average voltage of each battery module as a benchmark to make the voltages of battery cells with the same number or position within each battery module comparable. Then, the normal voltage of the battery cell with this number or position is found by taking the median and set as the benchmark to determine the actual voltage deviation of all battery cells with this number. This eliminates the influence of the initial consistency of the battery modules on the judgment result and avoids false faults and missed faults.

[0037] In one embodiment, the step of performing a lateral comparison of individual battery cells to obtain the deviation ΔV_n_i of the individual cell voltage within the same battery module relative to the average individual cell voltage within the same battery module includes:

[0038] To obtain the average single-cell voltage within the nth battery module: ave_v_n = (v_1 + v_2 + ... + v_i) / i;

[0039] Calculate the deviation of the individual cell voltage V_n_i from the average individual cell voltage within the same battery module, where ΔV_n_i = V_n_i - ave_v_n.

[0040] In this embodiment, the energy storage system includes n battery modules, and each battery module includes i battery cells connected in series. Therefore, the voltage of the i-th battery cell in the n-th battery module is V_n_i. In this way, by numbering each battery cell according to different battery modules and different series positions, the faulty battery cell can be quickly identified, the battery module in which the battery cell is located and its position within the battery module can be determined, thereby improving the efficiency and accuracy of battery cell fault diagnosis.

[0041] In this embodiment, each battery module includes a BMS (Battery Management System). Each battery cell in the battery module is connected to the BMS, thereby using the BMS to collect the voltage information of all battery cells in the corresponding battery module and upload it to the microgrid controller in order to accurately determine the voltage of each battery cell.

[0042] After each BMS collects the voltage information of all individual cells in the corresponding battery module and uploads it to the microgrid controller, the average voltage ave_v_n of all individual cells in the battery module corresponding to the nth BMS can be obtained.

[0043] After determining the individual cell voltage of each battery cell, the average individual cell voltage of each battery cell in each battery module can be determined. Since the battery modules are connected in parallel, the current of the individual cells in each battery module is the same. Therefore, the average individual cell voltage of each individual cell in the same battery module is calculated together. Then, the deviation of each individual cell relative to the average individual cell voltage in the same battery module is calculated as ΔV_n_i = V_n_i - ave_v_n.

[0044] By comparing the individual cell voltages of battery cells within the same battery module with the average individual cell voltage, the difference ΔV_n_i between the average voltage of all battery cells within the corresponding BMS and the average voltage can be obtained. In other words, by using the average voltage of all individual cells within the same BMS as a benchmark, the overall individual cell voltages collected by the same BMS are shifted downwards. This method ensures that all individual cell voltage data from all BMSs are based on the average value, making the voltages of battery cells at the same location collected by different BMSs comparable. Because the State of Charge (SOC) of different battery modules varies, the individual cell voltages within different battery modules will also differ. Setting the average voltage as a unified benchmark can eliminate the influence of SOC differences between different battery modules on the individual cell voltages.

[0045] In one embodiment, the step of longitudinally comparing individual battery cells and calculating the difference between the deviation of battery cells with the same number within each battery module and the median deviation of battery cells with the same number, and determining the battery cell fault corresponding to the difference if the difference is greater than the upper limit of the individual cell voltage offset threshold, includes:

[0046] Arrange the deviations ΔV_n_i of the same numbered cells within all battery modules in ascending order, and obtain the median H_n_imid, maximum H_n_imax, and minimum H_n_imin of the deviations ΔV_n_i of the same numbered cells. Under the same operating conditions, the voltage performance of the same numbered cells within different battery modules is the same. Therefore, the median is more representative of the normal voltage level of the cell with this number at this position than the average, making it convenient to calculate the voltage offset based on the median.

[0047] Calculate the maximum voltage offset of individual cells with the same serial number relative to the median:

[0048] MAX=max[(H_n_imax-H_n_imid),(H_n_imid-H_n_imin)].

[0049] Since different battery cells are also affected by their position, they exhibit significant differences. Therefore, in order to reduce these differences, it is necessary to compare the battery cells longitudinally, that is, to compare the offset values ​​obtained by comparing each battery cell laterally, thereby eliminating the influence of the positional differences of battery cells at different locations.

[0050] By comparing individual battery cells laterally to obtain the deviation of each individual battery cell relative to the average voltage of the individual battery cells in its battery module, and then comparing the deviation values ​​of individual battery cells at the same position or with the same number in different battery modules longitudinally, the influence of the external circuit and internal environment of the individual battery cells can be effectively eliminated, thereby effectively improving the accuracy and reliability of battery fault diagnosis.

[0051] If the MAX value corresponding to battery cell i is greater than the upper limit of the cell voltage offset threshold, it means that among all battery modules, the battery cell numbered i in one of the battery modules has failed. Then, the corresponding battery module is found based on the uploaded data of the BMS to determine the failed battery module. Otherwise, it means that all battery cells numbered i are normal.

[0052] In one embodiment, the step of performing a longitudinal comparison of individual battery cells and calculating the difference between the deviation of battery cells with the same number within each battery module and the median deviation of battery cells with the same number, and determining the battery cell corresponding to the difference as faulty if the difference is greater than the upper limit of the individual cell voltage offset threshold, further includes: determining the number of the battery cell whose difference is greater than the upper limit of the individual cell voltage offset threshold; determining the BMS for uploading data based on the number of the battery cell; and determining the corresponding battery module based on the BMS for uploading data.

[0053] In this embodiment, since the individual battery cells in each battery module have been numbered beforehand, each individual battery cell has a unique number. Based on this number, the battery module and location of each individual battery cell can be determined. In this way, when detecting faults in individual battery cells, the problem of number confusion can be avoided, the faulty individual battery cell and its battery module can be accurately identified, and subsequent processing can be carried out in a timely manner.

[0054] In one embodiment, each battery module includes a BMS (Battery Management System), and the individual battery cells within the module upload data to the microgrid controller via the BMS. All individual battery cells within the same module are connected in parallel to the BMS via external circuitry; therefore, the BMS can accurately measure the voltage information of each individual battery cell.

[0055] In one embodiment, the method for identifying battery cell faults in an energy storage system further includes: when a fault is detected in a battery cell, stopping the charging and discharging of the battery module containing that battery cell.

[0056] In one embodiment, the upper limit of the single-cell voltage offset threshold is obtained through experimentation or empirical formula.

[0057] See also Figure 2 As shown in the embodiment of the present invention, the energy storage system applies the above-mentioned energy storage system battery cell fault identification method. The energy storage system includes: n battery modules, which are connected in parallel. Each battery module includes a BMS and multiple battery cells, which are connected in series and / or in parallel; a microgrid controller, which is communicatively connected to each BMS, acquires the battery module parameters collected by each BMS, and processes the battery module parameters.

[0058] In this embodiment, the energy storage system includes n battery modules, each of which consists of i cells connected in series and / or in parallel. Each battery module is equipped with a battery management system (BMS) for collecting cell voltage information. Each BMS is electrically connected to a microgrid controller. The microgrid controller receives the cell voltage information and temperature information of all cells collected by the BMS and processes and analyzes the information. One microgrid controller corresponds to multiple BMS: BMS#1 to BMS#n, and sets an upper limit for the cell internal resistance offset value.

[0059] In one embodiment, the energy storage system further includes an energy storage converter connected to all battery modules and controlling the charging and discharging of the battery modules.

[0060] In one embodiment, all battery modules in the energy storage system are charged and discharged at the same power to ensure that the voltage performance of each battery module is not affected by the discharge rate.

[0061] In one embodiment, the energy storage converter is electrically connected to the microgrid controller. When the microgrid controller detects a cell failure, it issues a shutdown command to the energy storage converter to stop charging and discharging the battery module.

[0062] In one embodiment, all battery modules in the energy storage system are cooled by liquid cooling. In this case, the temperature difference between different modules is smaller. Compared with air cooling systems, liquid cooling is not affected by spatial location and has a better cooling effect, which can more effectively control the battery temperature.

[0063] In one embodiment, the BMS uses an STM32f4 series microcontroller, and the MC uses an ARM-A8 processor.

[0064] The embodiments of the present invention have the following advantages:

[0065] 1) Improved the accuracy of fault diagnosis. By setting the average voltage of individual cells as a unified benchmark for all battery modules, the voltage of individual cells with the same number or position in different battery modules can be compared longitudinally, thereby accurately calculating the magnitude of voltage deviation. When the voltage deviates from the threshold, the microgrid controller can accurately detect the fault at the first time.

[0066] 2) To avoid misjudgment and missed judgment of faults, this invention eliminates the consistency problem caused by initial design and manufacturing. By comparing battery cells with the same number or position, it completely avoids the problem that the voltage of a faulty battery cell may decrease or increase due to the initial voltage being too high or too low, but this is not detected by the system. It also avoids the problem that some cells with high initial voltage may be misjudged as not faulty when the voltage shifts slightly upward, thus improving the accuracy of the system's judgment.

[0067] 3) Improves the overall security of the energy storage system at the system level. When the BMS performs fault protection for the energy storage system, the microgrid controller further utilizes its data breadth advantage to protect the energy storage system at the system level and improves the overall security of the system.

[0068] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0069] It should be noted that the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in sequences other than those illustrated or described herein.

[0070] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for identifying faults in a single battery cell of an energy storage system, characterized in that, include: Each battery cell is numbered according to its different battery module and different series connection position; The voltage of the battery cell at the i-th series connection position of the n-th battery module is V_n_i; Set the upper limit of the individual cell voltage offset threshold; Obtain the individual cell voltage V_n_i of each battery cell, where n is the battery module number and i is the individual cell number within a battery module; By comparing individual battery cells laterally, the deviation ΔV_n_i of the individual cell voltage within the same battery module relative to the average individual cell voltage within the same battery module is obtained. A longitudinal comparison of individual battery cells is performed. The difference between the deviation of individual battery cells with the same number within each battery module and the median deviation of individual battery cells with the same number is calculated. If the difference is greater than the upper limit of the individual cell voltage offset threshold, the battery cell corresponding to that difference is determined to be faulty.

2. The method for identifying battery cell faults in an energy storage system according to claim 1, characterized in that, The steps for comparing individual battery cells laterally to obtain the deviation ΔV_n_i of the individual cell voltage within the same battery module relative to the average individual cell voltage within the same battery module include: To obtain the average single-cell voltage within the nth battery module: ave_v_n = (v_1 + v_2 + ... + v_i) / i; Calculate the deviation of the individual cell voltage V_n_i from the average individual cell voltage within the same battery module, where ΔV_n_i = V_n_i - ave_v_n.

3. The method for identifying battery cell faults in an energy storage system according to claim 1, characterized in that, The step of longitudinally comparing individual battery cells and calculating the difference between the deviation of battery cells with the same number within each battery module and the median deviation of battery cells with the same number, and determining the battery cell fault corresponding to the difference if the difference is greater than the upper limit of the individual cell voltage offset threshold, includes: Arrange the deviations ΔV_n_i of the same numbered battery cells in all battery modules in ascending order, and obtain the median H_n_imid, maximum value H_n_imax and minimum value H_n_imin of the deviations ΔV_n_i of the same numbered battery cells; Calculate the maximum voltage offset of individual cells with the same serial number relative to the median: MAX=max[(H_n_imax-H_n_imid),(H_n_imid-H_n_imin)].

4. The method for identifying battery cell faults in an energy storage system according to claim 3, characterized in that, The step of longitudinally comparing individual battery cells and calculating the difference between the deviation of battery cells with the same number within each battery module and the median deviation of battery cells with the same number, and determining the battery cell fault corresponding to the difference if the difference is greater than the upper limit of the individual cell voltage offset threshold, further includes: Identify the cell numbers of those whose voltage difference exceeds the upper limit of the cell voltage offset threshold; The BMS for uploading data is determined based on the cell number; The BMS determines the corresponding battery module based on the uploaded data.

5. The method for identifying battery cell faults in an energy storage system according to claim 1, characterized in that, Each battery module includes a BMS, and the individual battery cells within the battery module upload data to the microgrid controller via the BMS.

6. The method for identifying battery cell faults in an energy storage system according to claim 1, characterized in that, The method for identifying individual battery cell faults in the energy storage system also includes: When a fault is detected in a single battery cell, charging and discharging of the battery module containing that battery cell is stopped.

7. The method for identifying battery cell faults in an energy storage system according to claim 1, characterized in that, The upper limit of the individual cell voltage offset threshold is obtained through experiments or empirical formulas.

8. An energy storage system, employing the battery cell fault identification method according to any one of claims 1 to 7, characterized in that, The energy storage system includes: n battery modules are connected in parallel, and each battery module includes a BMS and multiple battery cells, with the multiple battery cells connected in series and / or in parallel. The microgrid controller communicates with each of the BMS, acquires the battery module parameters collected by each BMS, and processes the battery module parameters.

9. The energy storage system according to claim 8, characterized in that, The energy storage system also includes an energy storage converter, which is connected to all the battery modules and controls the charging and discharging of the battery modules.

10. The energy storage system according to claim 9, characterized in that, The energy storage converter is electrically connected to the microgrid controller. When the microgrid controller detects a cell failure, it issues a shutdown command to the energy storage converter to stop charging and discharging the battery module.

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