Battery cell standby power capability evaluation method and device, electronic equipment and storage medium

Abstract

The invention discloses a battery cell standby power capability evaluation method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring a battery cell discharge curve of a to-be-tested battery cell; according to the cell discharge curve, an initial standby power capability evaluation model corresponding to a preset discharge scene is constructed, and the preset discharge scene comprises a discharge rate and an environment temperature; correcting the initial standby power capability evaluation model through the target correction coefficient to obtain a target standby power capability evaluation model; wherein the target correction coefficient is determined by a correction coefficient obtained by carrying out discharge tests of a plurality of discharge test scenes on a plurality of test cells under different health conditions; and according to the target standby power capability evaluation model, performing standby power capability evaluation on the to-be-tested cell to obtain a standby power capability evaluation result. By considering the discharge capability of the battery cells with different discharge rates, different environment temperatures and different health conditions, the accuracy of predicting the standby power capability of the BBU can be effectively improved, and meanwhile, the safety of data storage and the reliability of power supply are also improved.

Description

Technical Field

[0001] The present application relates to the field of battery cell backup power technology, and in particular to a battery cell backup power capability evaluation method, device, electronic device, and storage medium. Background Art

[0002] Unified storage systems can currently be applied to a variety of scenarios. To ensure the security of unified storage data, data backup using the backup battery unit (BBU) becomes a key step. Therefore, accurate prediction of the BBU backup capacity is necessary. Currently, BBU backup capacity management typically predicts the backup capacity based on the remaining power. However, in actual applications, the BBU backup capacity may be affected by factors such as discharge rate and temperature. Therefore, improving the accuracy of BBU backup capacity prediction has become an urgent issue that needs to be addressed. Summary of the Invention

[0003] The present application provides a method, device, electronic device and storage medium for evaluating the backup power capacity of a battery cell, in order to at least solve the problem of how to improve the accuracy of BBU backup power capacity prediction.

[0004] This application provides a method for evaluating the backup power capacity of a battery cell, including: Obtain the battery cell discharge curve of the battery cell to be tested; Based on the cell discharge curve, an initial backup capacity assessment model corresponding to a preset discharge scenario is constructed. The preset discharge scenario includes: discharge rate and ambient temperature; The initial backup power capacity assessment model is corrected using a target correction coefficient to obtain a target backup power capacity assessment model; wherein the target correction coefficient is determined by performing discharge tests on multiple test cells in different health conditions under multiple discharge test scenarios; According to the target backup power capability evaluation model, the backup power capability of the battery cell to be tested is evaluated to obtain the backup power capability evaluation result.

[0005] The present application also provides a battery cell backup capacity evaluation device, comprising: An acquisition module is used to obtain a cell discharge curve of the cell to be tested; A processing module is used to construct an initial backup power capacity evaluation model corresponding to a preset discharge scenario based on the battery cell discharge curve. The preset discharge scenario includes: discharge rate and ambient temperature; The processing module is further configured to correct the initial backup power capability assessment model using a target correction coefficient to obtain a target backup power capability assessment model; wherein the target correction coefficient is determined by performing discharge tests on multiple test cells in different health conditions in multiple discharge test scenarios; The processing module is further used to evaluate the backup power capability of the battery cell to be tested according to the target backup power capability evaluation model to obtain a backup power capability evaluation result.

[0006] The present application also provides an electronic device, comprising: a memory for storing a computer program; and a processor for implementing the steps of any of the above-mentioned methods for evaluating the backup power capacity of a battery cell when executing the computer program.

[0007] The present application also provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above-mentioned battery cell backup capacity evaluation methods are implemented.

[0008] The present application also provides a computer program product, including a computer program, which implements the steps of any of the above-mentioned battery cell backup capacity evaluation methods when executed by a processor.

[0009] Through this application, the battery cell discharge curve of the battery cell to be tested is obtained; based on the battery cell discharge curve, an initial backup power capacity evaluation model corresponding to a preset discharge scenario is constructed, and the preset discharge scenario includes: discharge rate and ambient temperature; the initial backup power capacity evaluation model is corrected by the target correction coefficient to obtain a target backup power capacity evaluation model; wherein, the target correction coefficient is determined by the correction coefficient obtained by performing discharge tests of multiple discharge test scenarios on multiple test batteries with different health conditions; according to the target backup power capacity evaluation model, the backup power capacity of the battery cell to be tested is evaluated to obtain a backup power capacity evaluation result. In this solution, through discharge tests under multiple conditions, the discharge capacity of batteries with different discharge rates, different ambient temperatures and different health conditions is taken into account, which can effectively improve the accuracy of the BBU backup power capacity prediction, while also improving the security of data storage and the reliability of power supply. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0011] Figure 1 A process for evaluating the backup power capacity of a battery cell provided in an embodiment of the present application Figure 1 ; Figure 2 A process for evaluating the backup power capacity of a battery cell provided in an embodiment of the present application Figure 2 ; Figure 3 A schematic diagram of a discharge curve of a battery cell provided in an embodiment of the present application; Figure 4 A schematic diagram of the OCV-SOC corresponding curve provided in an embodiment of the present application; Figure 5 A schematic diagram of an initial backup power capacity evaluation model provided in an embodiment of the present application; Figure 6 A structural diagram of a battery cell backup capacity evaluation device provided in an embodiment of the present application; Figure 7 A structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0012] The following will be combined with the accompanying drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0013] It should be noted that, in the description of this application, the terms "comprises," "includes," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. The terms "first," "second," etc., in this application are used to distinguish similar objects, and are not used to describe a particular order or sequence.

[0014] It should be noted that in the embodiments of this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of this application should not be interpreted as being more preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0015] In the context of digital transformation, massive amounts of data are constantly growing, and unified storage systems have become widely used. At the same time, unified storage systems can be applied in a variety of scenarios. Driven by commercial models, the requirements for unified storage data security are increasing, and higher requirements are being placed on BBU security and power supply reliability.

[0016] Data backup is a key technology in unified storage systems. Common data backup solutions include BBU-powered data backup, non-volatile dual in-line memory module (NVDIMM)-powered data backup, and configurable battery upgrade (CBU)-powered data backup. Considering cost-effectiveness and power density, BBU-powered data backup is the most widely used technology. Key parameters for data backup security include the accuracy of BBU backup power prediction.

[0017] Existing BBU management technologies only predict BBU health and reserve capacity based on the remaining power (mAh or mWh) read from the metering chip. This technology takes into account the cumulative impact of metering chip sampling errors and performs corrections every six months to eliminate these accumulated errors. This technology does not consider the impact of different discharge rates, ambient temperatures, and BBU State of Health (SOH) on BBU reserve capacity accuracy. While sufficient design margin is required to ensure storage data security, this does not meet the high energy density requirements of storage products. Therefore, improving the accuracy of BBU reserve capacity predictions has become an urgent issue.

[0018] In order to enable those skilled in the art to better understand the present application, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0019] like Figure 1 As shown, Figure 1 A flowchart of a method for evaluating the backup power capacity of a battery cell provided in an embodiment of the present application, the method may include the following steps: 101. Obtain a cell discharge curve of the cell to be tested.

[0020] In an embodiment of the present application, the cell discharge curve of the cell to be tested can be used to describe the correlated changes in parameters such as charge and voltage of the cell to be tested during discharge. The cell discharge curve can be a curve obtained by fitting based on statistics of data collected in real time.

[0021] 102. Based on the battery cell discharge curve, construct an initial backup power capacity assessment model corresponding to the preset discharge scenario.

[0022] In an embodiment of the present application, since different discharge rates will cause changes in different cell-related parameters during the discharge process of the battery cell to be tested, when constructing a backup power capacity evaluation model, a preset discharge scenario commonly used by users can be selected. The preset discharge scenario can specifically include: discharge rate and ambient temperature. The ambient temperature can be set to room temperature (for example: 25°C, 20°C, etc.), and the discharge rate can be set to a discharge rate commonly used by users (for example: 1C, 20A, etc.).

[0023] It should be noted that the backup power capacity of the battery cell can be calculated by integrating the product of the BBU discharge current and discharge voltage over time, and the integral value of the discharge current over the discharge time can be understood as the amount of power consumed. Therefore, the value corresponding to the preset discharge scenario can be directly read through the relationship between the various parameters in the battery cell discharge curve, thereby constructing an initial backup power capacity evaluation model under the preset discharge scenario.

[0024] 103. The initial backup power capacity assessment model is corrected by the target correction coefficient to obtain the target backup power capacity assessment model.

[0025] In the embodiment of the present application, the internal resistance of the battery cell will change during the continuous charging and discharging process, and the error will gradually increase. At the same time, when sampling the state of charge (SOC) in the battery management system (BMS), the open circuit voltage of the battery may be affected by factors such as temperature and aging, resulting in an offset of the open circuit voltage (OCV) curve, and the estimation error will increase. In addition, the cumulative superposition of sampling errors, the difference in discharge capacity of battery cells at different discharge rates, the impact of changes in internal resistance of battery cells during the product cycle on discharge capacity, and the impact of ambient temperature on BBU discharge capacity will also be taken into account. These may lead to certain errors in the backup power capacity evaluation. Therefore, the initial backup power capacity evaluation model needs to be corrected to obtain a target backup power capacity evaluation model. The target backup power capacity evaluation model can be considered to be an accurate backup power capacity evaluation model after correction and taking into account various actual factors.

[0026] It should be noted that, through the above-mentioned possible causes of error, it can be seen that different cell internal resistance, different discharge rates, different ambient temperatures, etc. may affect the backup capacity. Different models of BBU cells will have different backup capacities; the same model of BBU cells will have different backup capacities at different discharge rates; changes in parameters such as operating temperature and cell internal resistance during the product cycle will affect the BBU backup capacity. Therefore, cells with different internal resistances can be placed in scenarios corresponding to multiple discharge rates and multiple ambient temperatures for testing, and the different internal resistances of the cells can be reflected in the health status SOH. In other words, discharge tests can be performed on test cells with different health states under multiple discharge rates and multiple ambient temperatures, and corrections can be made based on the results of the discharge tests. Specifically, a correction coefficient can be obtained based on the discharge test, and the initial backup capacity assessment model can be corrected using the correction coefficient. In other words, the target correction coefficient is determined by the correction coefficient obtained by performing discharge tests on test cells with multiple health states in multiple discharge test scenarios.

[0027] In some embodiments, the target correction coefficient and the initial backup power capability assessment model may be multiplied together to correct the initial backup power capability assessment model and obtain the target backup power capability assessment model.

[0028] It's important to note that the State of Health (SOH) is a core indicator for measuring the degree of degradation in battery cell performance. It indicates the degree of degradation in the current performance of a battery cell compared to its brand-new state, usually expressed as a percentage. When a battery cell is newly manufactured and in brand-new condition, its SOH is 100%. Over time, the SOH value decreases, and the corresponding maximum capacity also decreases, while the internal resistance of the battery increases, affecting both performance and backup capacity.

[0029] 104. According to the target backup power capability evaluation model, the backup power capability of the battery cell to be tested is evaluated to obtain a backup power capability evaluation result.

[0030] In an embodiment of the present application, after obtaining the target backup power capacity evaluation model, the backup power capacity of the battery cell to be tested can be evaluated using the target backup power capacity evaluation model, thereby obtaining the backup power capacity evaluation result of the battery cell to be tested. The backup power capacity evaluation result can be understood as a prediction result of the backup power capacity based on the current actual parameters of the battery cell to be tested, that is, a prediction of how long the battery cell to be tested can currently maintain backup power.

[0031] In an embodiment of the present application, a cell discharge curve of a cell to be tested is obtained; based on the cell discharge curve, an initial backup power capacity assessment model corresponding to a preset discharge scenario is constructed, and the preset discharge scenario includes: discharge rate and ambient temperature; the initial backup power capacity assessment model is corrected by a target correction coefficient to obtain a target backup power capacity assessment model; wherein the target correction coefficient is determined by a correction coefficient obtained by performing discharge tests on multiple test cells in different health conditions in multiple discharge test scenarios; based on the target backup power capacity assessment model, the backup power capacity of the cell to be tested is assessed to obtain a backup power capacity assessment result. In this solution, through discharge tests under multiple conditions, the discharge capacity of cells with different discharge rates, different ambient temperatures, and different health conditions is taken into account, which can effectively improve the accuracy of the BBU backup power capacity prediction, while also improving the security of data storage and the reliability of power supply.

[0032] like Figure 2 As shown, Figure 2 Another flow chart of a method for evaluating the backup power capacity of a battery cell provided in an embodiment of the present application, the method may include the following steps: 201. The battery cells to be tested are discharged at different rates, and the power, voltage and battery cell temperature are recorded in real time.

[0033] In the embodiment of the present application, during the discharge process of the battery cell to be tested, the power, voltage and battery cell temperature values ​​will change at any time, and when the battery cell to be tested is discharged at different rates, the speed of change of the power, voltage and battery cell temperature values ​​is different. Therefore, in order to obtain a more comprehensive battery cell discharge curve, the battery cell to be tested can be discharged at different rates, and then the power, voltage and battery cell temperature values ​​corresponding to each moment can be collected.

[0034] It should be noted that when the battery cell to be tested is discharged at each rate, real-time power, voltage and cell temperature values ​​are collected. That is to say, for each rate, power, voltage and cell temperature values ​​at multiple moments are obtained.

[0035] 202. Construct a cell discharge curve of the cell to be tested based on the corresponding collected power, voltage, and cell temperature values ​​at each moment.

[0036] In an embodiment of the present application, after collecting the power, voltage and cell temperature values ​​at various moments within a period of time, a cell discharge curve can be constructed. Specifically, when the cell to be tested is discharged at various rates, multiple groups of power, voltage and cell temperature values ​​are obtained, and the power and voltage values ​​may be correlated, and the power and cell temperature values ​​may be correlated. Therefore, a curve of the relationship between the power and voltage values, as well as a curve of the relationship between the power and cell temperature values, can be constructed for each rate.

[0037] For example, in Figure 3 The cell discharge curves shown here show five discharge rates: 0.2C, 1C, 10A, 20A, and 30A. The horizontal axis shows capacity (mAh), the vertical axis on the left shows voltage (V), and the vertical axis on the right shows cell temperature (°C). Figure 3 The charge and voltage value curves corresponding to 5 different rates, as well as the charge and cell temperature value curves corresponding to 5 different rates are given respectively, thereby forming the cell discharge curve of the cell to be tested.

[0038] In some embodiments, considering factors such as BMS SOC sampling deviation and cumulative superposition of sampling errors, the accuracy deviation of SOC sampling is about 8%, while the accuracy deviation of voltage sampling can be only about 1%. It can be seen that the SOC sampling accuracy is far inferior to the voltage sampling accuracy. Therefore, the evaluation algorithm is optimized, and the OCV-SOC corresponding curve of the BBU battery cell is constructed through multiple sets of sampling data corresponding to OCV and SOC, as shown in FIG. Figure 4 As shown in the figure, the vertical axis is the voltage value OCV, and the horizontal axis is the state of charge SOC. In this way, the OCV sampling value in the standby state can be used as a reference for the OCV-SOC corresponding curve. By querying the corresponding parameters of the curve, the SOC value corresponding to the OCV sampling value can be obtained for evaluation, thereby improving the estimation accuracy of the BBU backup power capacity.

[0039] 203. Determine the empty discharge equivalent voltage corresponding to the discharge rate and the ambient temperature and the discharge equivalent voltage corresponding to the multiple charge states according to the battery cell discharge curve.

[0040] In the embodiment of the present application, the empty equivalent voltage can be understood as the voltage value when the power is zero, which can be read through the battery cell discharge curve; the state of charge can correspond to the power, that is, the percentage corresponding to the remaining power, and the discharge equivalent voltages corresponding to multiple states of charge can also be directly obtained through the battery cell discharge curve.

[0041] 204. Construct an initial backup power capacity evaluation model corresponding to a preset discharge scenario based on the emptying equivalent voltage and the discharge equivalent voltages corresponding to multiple charge states.

[0042] In the embodiment of the present application, the product of the BBU discharge current and the discharge voltage integrated over time is the BBU backup capacity. The discharge voltage gradually decreases during the BBU discharge process. Therefore, the BBU backup capacity is estimated by multiplying the discharge current integrated over the discharge time (remaining power) by the average discharge voltage. Therefore, an initial backup capacity evaluation model can be constructed based on the empty equivalent voltage and the discharge equivalent voltages corresponding to multiple charge states, such as Figure 5 As shown, Figure 5The shaded trapezoidal area in the figure is the initial backup power capacity assessment model. The lower base of the initial backup power capacity assessment model is the empty equivalent voltage, and the upper base is the discharge equivalent voltage corresponding to the BBU remaining power. The trapezoidal area formed can be considered as the BBU backup power capacity.

[0043] It should be noted that the area of ​​the trapezoid can be expressed as the sum of the upper and lower bases, multiplied by the height, and then divided by 2. The sum of the upper and lower bases divided by 2 can be understood as the average discharge voltage. Therefore, according to Figure 5 The following formula can be obtained:

[0044]

[0045]

[0046] Among them, the empty equivalent voltage is the voltage when the power is zero, the fully charged equivalent voltage is the voltage when the power is 100%, X is the discharge rate, SOC is the state of charge (which can be understood as the percentage of power), and the discharge start voltage is the voltage corresponding to the current power of the battery cell to be tested.

[0047] In some embodiments, the accuracy of the remaining power will be affected by the cumulative sampling error of the BMS. In order to eliminate the influence of the cumulative sampling error on the prediction accuracy of the BBU backup power capacity, the BBU can be shallowly discharged according to a certain period (for example, 3 months, 4 months, etc.). The discharge depth is to ensure that the BBU discharge capacity meets the requirements of one backup power, which can ensure the chemical capacity Q of the battery cell in the BMS. max 、Battery cell internal resistance R a Update in a timely manner.

[0048] 205. Perform discharge tests of multiple discharge test scenarios on the first test cell to determine a first correction coefficient.

[0049] 206. Perform discharge tests of multiple discharge test scenarios on the second test cell to determine a second correction coefficient.

[0050] In the embodiment of the present application, since the target correction coefficient is determined by performing discharge tests on multiple test cells with different health conditions in multiple discharge test scenarios, at least two test cells with different health conditions can be selected for testing. The test cells selected in this solution may include a first test cell and a second test cell. The health conditions of the first test cell and the second test cell are different. Of course, in order to obtain discharge data closer to the standard, a test cell that has just been shipped from the factory, that is, a test cell with a health status of 100%, can be selected; the first test cell and the second test cell are respectively subjected to discharge tests to obtain the first correction coefficient and the second correction coefficient. Of course, more test cells can also be subjected to discharge tests to obtain more correction coefficients, which is not specifically limited in the embodiment of the present application.

[0051] In some embodiments, a discharge test is performed on the first test cell in multiple discharge test scenarios to determine a first correction coefficient, which may specifically include: when the first test cell is in each discharge test scenario, counting the discharge amount of the first test cell when it is discharged according to a preset discharge rate; and determining the first correction coefficient based on the difference between the discharge amount of the first test cell and the standard discharge amount corresponding to the first test cell.

[0052] It should be noted that the test scenario may include multiple different SOC values, such as: 100%, 61%, 31%, and the test scenario may also include multiple different ambient temperature values, such as: 0°C, 25°C, 55°C; that is, by combining different SOC values ​​and different ambient temperature values, a variety of test scenarios can be obtained, such as: 100%, 0°C; 100%, 25°C; 100%, 55°C; 61%, 0°C; 61%, 25°C; 61%, 55°C; 31%, 0°C; 31%, 25°C; 31%, 55°C; and then the first test cell is tested in each test scenario to obtain the discharge amount of the first test cell in each test scenario.

[0053] It should be noted that the standard discharge capacity corresponding to the first test cell can be the Wh number calculated by discharging the first test cell at 0.1C. Therefore, the discharge capacity of the first test cell in each test scenario and the standard discharge capacity corresponding to the first test cell are subtracted, and the difference is linearly fitted. The slope of the fitted straight line is then determined as the first correction coefficient.

[0054] In some embodiments, the second test cell is subjected to discharge tests in multiple discharge test scenarios, and the steps for determining the second correction coefficient are the same as the steps for determining the first correction coefficient, which may specifically include: when the second test cell is in each discharge test scenario, counting the discharge amount of the second test cell when discharged at a preset discharge rate; determining the second correction coefficient based on the difference between the discharge amount of the second test cell and the standard discharge amount corresponding to the second test cell.

[0055] It should be noted that the test scenario may include multiple different SOC values, such as: 100%, 61%, 31%, and the test scenario may also include multiple different ambient temperature values, such as: 0°C, 25°C, 55°C; that is, by combining different SOC values ​​and different ambient temperature values, a variety of test scenarios can be obtained, such as: 100%, 0°C; 100%, 25°C; 100%, 55°C; 61%, 0°C; 61%, 25°C; 61%, 55°C; 31%, 0°C; 31%, 25°C; 31%, 55°C; and then the second test cell is tested in each test scenario to obtain the discharge amount of the second test cell in each test scenario.

[0056] It should be noted that the standard discharge capacity corresponding to the second test cell can be the Wh number calculated by discharging the second test cell at 0.1C. Therefore, the discharge capacity of the second test cell in each test scenario is subtracted from the standard discharge capacity corresponding to the second test cell, and the difference is linearly fitted. The slope of the fitted straight line is then determined as the second correction coefficient.

[0057] 207. Determine a target correction coefficient based on the first correction coefficient and the second correction coefficient.

[0058] In the embodiment of the present application, the target correction coefficient can be determined by combining the first correction coefficient and the second correction coefficient obtained respectively for battery cells with different health conditions.

[0059] In some embodiments, determining the target correction coefficient based on the first correction coefficient and the second correction coefficient may specifically include: determining the target correction coefficient based on the first correction coefficient, the health status of the first test cell, the second correction coefficient, and the health status of the second test cell.

[0060] It should be noted that the target correction coefficient can be determined by the following formula:

[0061] Among them, K is the target correction coefficient, is the first correction coefficient, is the second correction coefficient, It can be expressed as an average health status (ie, the average of the health status of the first test cell and the health status of the second test cell).

[0062] In some embodiments, considering the impact of different discharge rates, ambient temperatures, and changes in the internal resistance of the battery cells during the product cycle (changes in health status) on the BBU backup power capacity, the test battery cells are discharged in multiple scenarios to obtain correction coefficients, and the backup power capacity evaluation model is corrected by the correction coefficients, which can effectively improve the prediction accuracy of the BBU backup power capacity.

[0063] 208. The initial backup power capacity assessment model is corrected using the target correction coefficient to obtain a target backup power capacity assessment model.

[0064] In the embodiment of the present application, for the description of step 208, please refer to the detailed description of step 103 in the above embodiment, and the embodiment of the present application will not be repeated.

[0065] 209. Obtain the current remaining capacity, empty equivalent voltage, and fully charged equivalent voltage of the battery cell to be tested.

[0066] 210. Substitute the current remaining power, empty equivalent voltage, and fully charged equivalent voltage into the target backup power capacity evaluation model to obtain a backup power capacity evaluation result.

[0067] In an embodiment of the present application, after obtaining the target backup power capacity evaluation model, the backup power capacity of the battery cell to be tested can be evaluated through the target backup power capacity evaluation model. Specifically, the empty equivalent voltage and the fully charged equivalent voltage can be fixed values ​​that will not change and can be directly obtained. The current remaining power can be obtained through the current battery status. Then, the current remaining power, the empty equivalent voltage and the fully charged equivalent voltage are substituted into the formula corresponding to the target backup power capacity evaluation model to obtain the backup power capacity evaluation result.

[0068] In some embodiments, in addition to correcting the backup power capacity of the battery cell to be tested through the target correction coefficient during the application process, the backup power capacity can also be corrected before the battery cell to be tested leaves the factory. Specifically, the BBU backup power capacity evaluation model of different battery cells will be different. The BBU development process requires verification of key battery cell parameters, and the BBU backup power capacity evaluation model and correction coefficient are corrected according to the verification results. The verification process can include: OCV-SOC curve verification, equivalent voltage verification, correction coefficient verification, etc.

[0069] In some embodiments, the OCV-SOC curve verification can specifically include: obtaining the open circuit voltages corresponding to the battery cell to be tested at multiple charge states, and establishing a corresponding relationship curve between the charge state and the open circuit voltage; and correcting the open circuit voltage of the battery cell to be tested based on the corresponding relationship curve and the theoretical relationship curve.

[0070] It should be noted that the established correspondence curve between the state of charge and the open circuit voltage can be considered to reflect the current open circuit voltage change of the battery cell to be tested, and the theoretical relationship curve can be considered to be the standard curve of the battery cell, that is, the most ideal open circuit voltage change curve of the battery cell without any error and not affected by any factors. Therefore, the error of the current open circuit voltage can be determined by comparing the real-time established correspondence curve with the theoretical relationship curve, so as to correct the open circuit voltage of the battery cell to be tested.

[0071] In some embodiments, the equivalent voltage verification may specifically include: obtaining the empty equivalent voltage and fully charged equivalent voltage corresponding to the battery cell to be tested when discharged at a preset discharge rate, as well as the voltage values ​​corresponding to different charge states; and correcting the empty equivalent voltage and fully charged equivalent voltage based on the difference between the voltage value and the theoretical voltage value.

[0072] Since the empty equivalent voltage and fully charged equivalent voltage need to be brought into the calculation when evaluating the backup capacity of the battery cell to be tested, the empty equivalent voltage and the fully charged equivalent voltage need to be corrected to improve the accuracy of the backup capacity evaluation. Specifically, the OCV can be verified after the battery cell is discharged, and then the voltage value can be verified at each charge state (for example: 100%, 80%, 70%, 60%, 50%, etc.). The theoretical voltage value can be the voltage value of the most ideal battery cell at different charge states without any error and not affected by any factors. According to the difference between the actual voltage value and the theoretical voltage value of the battery cell to be tested, the empty equivalent voltage and the fully charged equivalent voltage are corrected.

[0073] In some embodiments, since the correction coefficient is related to the ambient temperature, discharge rate, and health status (internal resistance of the battery cell) during the determination process, the verification of the correction coefficient can be understood as the verification of the impact of the ambient temperature, the verification of the impact of the health status (internal resistance of the battery cell), and the verification of the impact of different rates.

[0074] Specifically, the verification of the impact of different rates can be carried out by discharging at multiple rates such as 2C, 5C, and 10C, and collecting the discharge capacity at each state of charge (100% SOC, 70% SOC, 60% SOC, 50% SOC, etc.); the verification of the impact of ambient temperature can be carried out by placing the battery cell in multiple temperature scenes (100°C, 80°C, 50°C, 35°C, 25°C, 20°C, 0°C, etc.) for discharge, and collecting the discharge data at each state of charge. The discharge capacity can be verified by selecting cells with different health conditions (100% SOC, 95% SOC, 90% SOH, 85% SOH, 80% SOH, etc.) for discharge and collecting data at each state of charge (100% SOC, 70% SOC, 60% SOC, 50% SOC, etc.) to verify the discharge capacity. The influence of health status (cell internal resistance) can be verified by selecting cells with different health conditions (100% SOC, 95% SOH, 90% SOH, 85% SOH, 80% SOH, etc.) for discharge and collecting data at each state of charge (100% SOC, 70% SOC, 60% SOC, 50% SOC, etc.) to verify the discharge capacity.

[0075] In some embodiments, the BBU backup power capacity evaluation models of different battery cells may be different. The BBU development process can verify the relevant parameters of the battery cell during discharge, and correct the BBU backup power capacity evaluation model and correction coefficient based on the verification results, so that the relevant parameters of the battery cell are verified during the development process, which improves the power supply stability of the battery cell, eliminates the risk of data loss to a large extent, and improves the security of stored data.

[0076] In some embodiments, considering that the BBU design is compatible with historical versions and future versions, the battery cell model may change during the product cycle. The BBU design needs to configure the key parameters of the battery cell and store the key parameters in the FLASH space inside the BBU. In order to prevent the key parameters of the BBU battery cell from being tampered with, a write protection password can also be designed. The key parameters can only be edited after the password verification is passed.

[0077] In some embodiments, standard parameters of the battery cell are obtained, and the standard parameters of the battery cell include at least: charging parameters, evaluation parameters, alarm thresholds, and correction coefficients; and the battery cell to be tested is factory configured according to the standard parameters of the battery cell.

[0078] It should be noted that the charging parameters may include at least the charging voltage and charging current; the evaluation parameters may include at least the open-circuit voltage evaluation parameter and the charge voltage slope evaluation parameter; the alarm thresholds may include at least the charging current cutoff threshold and the temperature threshold; and the correction factors may include at least the environmental compensation correction factor, the cell health correction factor, and the discharge rate difference correction factor. The above parameters are used to configure the battery cell to be tested at the factory.

[0079] In some embodiments, the battery cell to be tested is factory configured according to the standard parameters of the battery cell, which may specifically include: performing a safety check on the standard parameters of the battery cell to obtain a check result; if the check result indicates that the standard parameters of the battery cell are valid, the battery cell to be tested is factory configured according to the standard parameters of the battery cell.

[0080] It should be noted that to ensure the safety of battery cells, safety design of battery cell standard parameters is required, including frame header design, frame trailer design, and mirror design. Frame header design includes defining the frame header, length, and version number, while frame trailer design includes defining the frame trailer and CRC16 IBM. Mirror design includes storing the battery cell standard parameters in the lower 128 bytes and the mirror data in the upper 128 bytes.

[0081] It should be noted that when the storage product is powered on or the BBU is plugged in or unplugged, the standard parameters of the battery cell are read. After reading, the frame header, frame tail, and length are first judged. After the judgment is passed, the checksum is calculated according to the CRC16 IPM and compared with the read checksum. After the comparison is passed, the mirror data is finally read and compared with the standard parameters of the battery cell. After the comparison is passed, it can be considered that the standard parameters of the battery cell are accurate and valid, and the factory configuration of the battery cell to be tested is performed according to the standard parameters of the battery cell. If any parameter fails the comparison, it is considered that the standard parameters of the battery cell may be incorrect, and an alarm information can be output for processing.

[0082] In some embodiments, during the battery cell development process, by configuring the battery cell standard parameters and performing safety design, the incompatibility problem between the same model battery cells and the system software control parameters is solved, the storage data security and power supply reliability are improved, and the purpose of intelligent and digital control is achieved.

[0083] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus the necessary general hardware platform, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method.

[0084] like Figure 6 As shown, an embodiment of the present application further provides a battery cell backup capacity evaluation device, which may include: An acquisition module 601 is used to obtain a discharge curve of a battery cell to be tested; Processing module 602 is used to construct an initial backup power capacity evaluation model corresponding to a preset discharge scenario based on the battery cell discharge curve, where the preset discharge scenario includes: discharge rate and ambient temperature; The processing module 602 is further configured to modify the initial backup power capability assessment model using a target correction coefficient to obtain a target backup power capability assessment model; wherein the target correction coefficient is determined by performing discharge tests on multiple test cells in different health conditions under multiple discharge test scenarios; The processing module 602 is further configured to perform a backup power capability evaluation on the battery cell to be tested according to the target backup power capability evaluation model to obtain a backup power capability evaluation result.

[0085] In some embodiments, the processing module 602 is specifically configured to discharge the battery cell to be tested at different rates and record the power, voltage, and battery cell temperature in real time; The processing module 602 is specifically configured to construct a cell discharge curve of the cell to be tested according to the corresponding collected power, voltage and cell temperature values ​​at each moment.

[0086] In some embodiments, the processing module 602 is specifically configured to determine, based on the cell discharge curve, an empty discharge equivalent voltage corresponding to the discharge rate and the ambient temperature and a discharge equivalent voltage corresponding to each of the multiple states of charge; The processing module 602 is specifically configured to construct an initial backup power capability evaluation model corresponding to a preset discharge scenario according to the empty equivalent voltage and the discharge equivalent voltages corresponding to multiple states of charge.

[0087] In some embodiments, the processing module 602 is further configured to perform a discharge test of a plurality of discharge test scenarios on the first test cell to determine a first correction coefficient; The processing module 602 is further configured to perform a discharge test of a plurality of discharge test scenarios on the second test cell to determine a second correction coefficient; The processing module 602 is further configured to determine a target correction coefficient based on the first correction coefficient and the second correction coefficient; The health conditions of the first test cell and the second test cell are different.

[0088] In some embodiments, the acquisition module 601 is specifically configured to count the discharge amount of the first test cell when the first test cell is discharged according to a preset discharge rate when the first test cell is in each discharge test scenario; The processing module 602 is specifically configured to determine a first correction coefficient according to a difference between the discharge capacity of the first test cell and a standard discharge capacity corresponding to the first test cell.

[0089] In some embodiments, the acquisition module 601 is specifically configured to count the discharge amount of the second test cell when the second test cell is discharged according to a preset discharge rate when the second test cell is in each discharge test scenario; The processing module 602 is specifically configured to determine a first correction coefficient according to a difference between the discharge capacity of the second test cell and a standard discharge capacity corresponding to the second test cell.

[0090] In some embodiments, the processing module 602 is specifically configured to determine a target correction coefficient according to the first correction coefficient, the health status of the first test cell, the second correction coefficient, and the health status of the second test cell.

[0091] In some embodiments, the acquisition module 601 is specifically configured to acquire the current remaining capacity, the empty equivalent voltage, and the fully charged equivalent voltage of the battery cell to be tested; The processing module 602 is specifically used to bring the current remaining power, the empty equivalent voltage and the fully charged equivalent voltage into the target backup power capacity evaluation model to obtain a backup power capacity evaluation result.

[0092] In some embodiments, the acquisition module 601 is further configured to obtain the open circuit voltages corresponding to the battery cell under test at multiple states of charge, and to establish a corresponding relationship curve between the states of charge and the open circuit voltages; According to the corresponding relationship curve and the theoretical relationship curve, the open circuit voltage of the battery cell to be tested is corrected.

[0093] In some embodiments, the acquisition module 601 is further configured to obtain the empty equivalent voltage and fully charged equivalent voltage corresponding to the battery cell to be tested when discharged at a preset discharge rate, as well as voltage values ​​corresponding to different states of charge; The processing module 602 is further configured to correct the empty-discharge equivalent voltage and the fully-charged equivalent voltage according to the difference between the voltage value and the theoretical voltage value.

[0094] In some embodiments, the acquisition module 601 is further configured to acquire standard parameters of the battery cell, which include at least: charging parameters, evaluation parameters, alarm thresholds, and correction coefficients; The processing module 602 is further configured to perform factory configuration on the battery cell to be tested according to the standard parameters of the battery cell.

[0095] In some embodiments, the processing module 602 is further configured to perform safety verification on the standard parameters of the battery cell to obtain a verification result; The processing module 602 is further configured to perform factory configuration on the battery cell to be tested according to the battery cell standard parameters if the verification result indicates that the battery cell standard parameters are valid.

[0096] In the embodiments of the present application, the description of the features in the embodiments corresponding to the battery cell backup capacity evaluation device can refer to the relevant description of the embodiments corresponding to the battery cell backup capacity evaluation method, and will not be repeated here.

[0097] like Figure 7As shown, an embodiment of the present application also provides an electronic device, including a memory 701 and a processor 702, wherein the memory 701 stores a computer program, and the processor 702 is configured to run the computer program to execute the steps in any of the above-mentioned battery cell backup capacity evaluation method embodiments.

[0098] An embodiment of the present application further provides a computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to execute the steps of any of the above-mentioned battery cell backup capacity evaluation method embodiments when running.

[0099] In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to, various media that can store computer programs, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk, or an optical disk.

[0100] An embodiment of the present application further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the steps in any of the above-mentioned battery cell backup capacity evaluation method embodiments are implemented.

[0101] An embodiment of the present application also provides another computer program product, including a non-volatile computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the steps in any of the above-mentioned battery cell backup capacity evaluation method embodiments.

[0102] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the components and steps of each example according to their functions. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0103] The above is a detailed introduction to the process monitoring of a storage system provided by this application. Specific examples are used herein to illustrate the principles and implementation methods of this application. The description of the above embodiments is only intended to help understand the method and core ideas of this application. It should be pointed out that, for those skilled in the art, without departing from the principles of this application, several improvements and modifications can be made to this application, and these improvements and modifications also fall within the scope of protection of the claims of this application.

Claims

1. A method for evaluating the backup power capacity of a battery cell, characterized in that: The method comprises: Obtain the battery cell discharge curve of the battery cell to be tested; According to the battery cell discharge curve, an initial backup power capacity evaluation model corresponding to a preset discharge scenario is constructed, wherein the preset discharge scenario includes: discharge rate and ambient temperature; The initial backup power capacity assessment model is corrected by a target correction coefficient to obtain a target backup power capacity assessment model; wherein the target correction coefficient is determined by performing discharge tests on multiple test cells in different health conditions in multiple discharge test scenarios; The backup power capability of the battery cell to be tested is evaluated according to the target backup power capability evaluation model to obtain a backup power capability evaluation result.

2. The method according to claim 1, characterized in that The obtaining of the battery cell discharge curve of the battery cell to be tested includes: Discharging the battery cell at different rates and recording the battery capacity, voltage and temperature in real time; The cell discharge curve of the cell to be tested is constructed according to the corresponding collected power, voltage and cell temperature values ​​at each moment.

3. The method according to claim 1, characterized in that The constructing of an initial backup power capacity evaluation model corresponding to a preset discharge scenario according to the battery cell discharge curve includes: Determining, based on the cell discharge curve, an empty discharge equivalent voltage corresponding to the discharge rate and the ambient temperature and a discharge equivalent voltage corresponding to each of a plurality of states of charge; The initial backup power capability evaluation model corresponding to the preset discharge scenario is constructed according to the emptying equivalent voltage and the discharge equivalent voltages corresponding to the multiple states of charge.

4. The method according to claim 1, wherein Before correcting the initial backup power capability evaluation model by using the target correction coefficient to obtain the target backup power capability evaluation model, the method further includes: Performing a discharge test of a plurality of discharge test scenarios on the first test cell to determine a first correction coefficient; Performing discharge tests on the second test cell in multiple discharge test scenarios to determine a second correction coefficient; determining the target correction coefficient according to the first correction coefficient and the second correction coefficient; The health conditions of the first test cell and the second test cell are different.

5. The method according to claim 4, characterized in that The step of performing a discharge test on the first test cell in a plurality of discharge test scenarios to determine the first correction coefficient includes: When the first test cell is in each discharge test scenario, the discharge amount of the first test cell when discharged according to a preset discharge rate is counted; The first correction coefficient is determined according to a difference between the discharge capacity of the first test cell and a standard discharge capacity corresponding to the first test cell.

6. The method according to claim 4, characterized in that The performing a discharge test of a plurality of discharge test scenarios on the second test cell to determine the second correction coefficient includes: When the second test cell is in each discharge test scenario, the discharge amount of the second test cell when discharged according to the preset discharge rate is counted; The first correction coefficient is determined according to a difference between the discharge capacity of the second test cell and a standard discharge capacity corresponding to the second test cell.

7. The method according to claim 4, characterized in that The determining the target correction coefficient according to the first correction coefficient and the second correction coefficient includes: The target correction coefficient is determined according to the first correction coefficient, the health status of the first test cell, the second correction coefficient, and the health status of the second test cell.

8. The method according to claim 1, characterized in that The step of evaluating the backup power capability of the battery cell to be tested according to the target backup power capability evaluation model to obtain a backup power capability evaluation result includes: Obtain the current remaining capacity, empty equivalent voltage, and fully charged equivalent voltage of the battery cell to be tested; The current remaining power, the empty-discharge equivalent voltage, and the fully-charged equivalent voltage are brought into the target backup power capability evaluation model to obtain the backup power capability evaluation result.

9. The method according to claim 1, characterized in that The method further comprises: Obtaining the open circuit voltages corresponding to the battery cell to be tested at multiple states of charge, and establishing a corresponding relationship curve between the state of charge and the open circuit voltage; According to the corresponding relationship curve and the theoretical relationship curve, the open circuit voltage of the battery cell to be tested is corrected.

10. The method according to claim 1, characterized in that The method further comprises: Obtaining the empty equivalent voltage and fully charged equivalent voltage corresponding to the battery cell to be tested when discharged at a preset discharge rate, as well as the voltage values ​​corresponding to different states of charge; The empty-discharge equivalent voltage and the fully-charged equivalent voltage are corrected according to the difference between the voltage value and the theoretical voltage value.

11. The method according to claim 1, characterized in that The method further comprises: Obtaining standard parameters of the battery cell, wherein the standard parameters of the battery cell include at least: charging parameters, evaluation parameters, alarm thresholds, and correction coefficients; The battery cell to be tested is factory configured according to the standard parameters of the battery cell.

12. The method according to claim 11, characterized in that The factory configuration of the battery cell to be tested according to the standard parameters of the battery cell includes: Performing a safety check on the standard parameters of the battery cell to obtain a check result; If the verification result indicates that the battery cell standard parameters are valid, the battery cell to be tested is factory configured according to the battery cell standard parameters.

13. A battery cell backup capacity evaluation device, characterized in that: The device comprises: An acquisition module is used to obtain a cell discharge curve of the cell to be tested; a processing module, configured to construct an initial backup power capacity evaluation model corresponding to a preset discharge scenario based on the battery cell discharge curve, wherein the preset discharge scenario includes: a discharge rate and an ambient temperature; The processing module is further configured to correct the initial backup power capability assessment model using a target correction coefficient to obtain a target backup power capability assessment model; wherein the target correction coefficient is determined by performing discharge tests on multiple test cells in different health conditions in multiple discharge test scenarios; The processing module is further configured to perform a backup power capability evaluation on the battery cell to be tested according to the target backup power capability evaluation model to obtain a backup power capability evaluation result.

14. An electronic device, characterized in that: include: Memory for storing computer programs; A processor, configured to implement the steps of the method for evaluating the backup power capability of a battery cell as claimed in any one of claims 1 to 12 when executing the computer program.

15. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the steps of the method for evaluating the backup power capability of a battery cell according to any one of claims 1 to 12 are implemented.

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