Calculation method and device for relative self-discharge rate of battery, controller and electric equipment

Abstract

The invention relates to a calculation method and device for the relative self-discharge rate of a battery, a controller and electric equipment, and the calculation method comprises the steps: determining a first relative self-discharge SOC of a battery cell based on a state parameter of the battery, and then determining a second relative self-discharge SOC of a battery pack; and determining a first relative self-discharge rate of the battery cell according to the first relative self-discharge SOC, and determining a second relative self-discharge rate of the battery pack according to the second relative self-discharge SOC. On the basis, the self-discharge difference of the battery cell and the battery can be distinguished, the abnormal battery cell can be positioned, and whether self-discharge is deteriorated can be judged, so that the troubleshooting efficiency can be improved, the maintenance cost can be reduced, and the safety risk can be avoided.

Description

Technical Field

[0001] This application relates to the field of battery management technology, and in particular to a method, apparatus, controller and electrical equipment for calculating the relative self-discharge rate of a battery. Background Technology

[0002] With the rise and popularization of electric vehicles, lithium battery packs have become a core component of vehicle power systems, among which lithium iron phosphate batteries are widely used in battery production due to their excellent safety performance. However, due to the electrochemical characteristics of lithium iron phosphate batteries, it is difficult to accurately quantify the state of charge (SOC) of a single cell, posing a challenge to the evaluation of cell-level self-discharge performance.

[0003] Traditional battery self-discharge assessment methods only evaluate the overall self-discharge level of the battery pack, ignoring the differences in self-discharge between different cells and failing to determine whether the self-discharge problem is worsening based on overall data. In practical applications, the self-discharge performance of a battery pack is dominated by the "worst cell"—if a cell experiences abnormal self-discharge due to micro-short circuits, aging, or other reasons, an overall assessment alone cannot identify the specific faulty cell or detect the accelerating state of self-discharge deterioration. This directly leads to low troubleshooting efficiency, high maintenance costs, and potential safety risks due to the failure to intervene in a timely manner. Summary of the Invention

[0004] This application provides a method, apparatus, controller, and electrical equipment for calculating the relative self-discharge rate of a battery, which can solve at least one problem in the prior art.

[0005] This application provides a method for calculating the relative self-discharge rate of a battery. The calculation method includes: determining a first relative self-discharge SOC of a battery cell based on the battery's state parameters, and then determining a second relative self-discharge SOC of the battery pack; determining a first relative self-discharge rate of the battery cell based on the first relative self-discharge SOC, and determining a second relative self-discharge rate of the battery pack based on the second relative self-discharge SOC.

[0006] In one embodiment of this application, the state parameters include at least the measured inflection point capacity and cumulative equalization time of the battery cell. The step of determining the first relative self-discharge SOC of the battery cell based on the battery state parameters, and then determining the second relative self-discharge SOC of the battery pack, includes: preprocessing the measured inflection point capacity and the cumulative equalization time according to preset conditions to obtain the effective measured inflection point capacity and effective cumulative equalization time of each battery cell; determining the first relative self-discharge SOC based on the effective measured inflection point capacity and the effective cumulative equalization time; and determining the second relative self-discharge SOC based on the first relative self-discharge SOC.

[0007] In one embodiment of this application, the preset conditions are that the measurement inflection point capacity is greater than 0 and the cumulative equalization time is greater than or equal to 0.

[0008] In one embodiment of this application, determining the first relative self-discharge SOC based on the effective measurement inflection point and the effective cumulative equalization time includes: obtaining the equalization current of each cell; determining the correction inflection point capacity of each cell according to the correlation between the effective measurement inflection point capacity, the effective cumulative equalization time, and the equalization current; and determining the first relative self-discharge SOC based on the correction inflection point capacity, the nominal capacity of the battery, and the minimum correction inflection point capacity of each cell.

[0009] In one embodiment of this application, determining the second relative self-discharge SOC based on the first relative self-discharge SOC includes: the second relative self-discharge SOC of the battery pack is the maximum value of the first relative self-discharge SOC among all the cells.

[0010] In one embodiment of this application, determining the first relative self-discharge rate of the battery cell based on the first relative self-discharge SOC includes: segmenting the self-discharge time of the battery cell according to a first preset time interval; calculating a first characteristic value of the first relative self-discharge SOC of the battery cell within each segment interval; and determining the first relative self-discharge rate of the battery cell based on the difference between the first characteristic values ​​of adjacent segment intervals and the first preset time interval.

[0011] In one embodiment of this application, the calculation of the first characteristic value of the first relative self-discharge SOC of the battery cell within each segment interval includes: if the first characteristic value of any segment interval is missing, interpolation calculation is performed based on the first characteristic values ​​of adjacent intervals to obtain the first characteristic value of the segment interval.

[0012] In one embodiment of this application, the step of determining the first relative self-discharge rate of the battery cell based on the first relative self-discharge SOC includes: determining the first relative self-discharge rate change rate of the battery cell based on the difference in the first relative self-discharge rates of the battery cells in the adjacent segment intervals and the first preset time interval.

[0013] In one embodiment of this application, determining the second relative self-discharge rate of the battery pack based on the second relative self-discharge SOC includes: segmenting the self-discharge time of the battery pack according to a second preset time interval; calculating a second characteristic value of the second relative self-discharge SOC of the battery pack within each segment interval; and determining the second relative self-discharge rate of the battery pack based on the difference between the second characteristic values ​​of adjacent segment intervals and the second preset time interval.

[0014] In one embodiment of this application, the calculation of the second characteristic value of the second relative self-discharge SOC of the battery pack in each segment interval includes: if the second characteristic value of any segment interval is missing, interpolation calculation is performed based on the second characteristic values ​​of adjacent intervals to obtain the second characteristic value of the segment interval.

[0015] In one embodiment of this application, the step of determining the second relative self-discharge rate of the battery pack based on the second relative self-discharge SOC includes: determining the change rate of the second relative self-discharge rate of the battery pack based on the difference between the second relative self-discharge rates of the battery pack in the adjacent segment intervals and the second preset time interval.

[0016] In one embodiment of this application, the process of determining the first relative self-discharge SOC of the battery cell and the second relative self-discharge SOC of the battery pack based on the battery's state parameters includes: filtering and smoothing the first relative self-discharge SOC of each battery cell and the second relative self-discharge SOC of the battery pack, respectively.

[0017] Accordingly, this application provides a battery pack relative self-discharge rate calculation device, the calculation device comprising: a first determining module, which determines a first relative self-discharge SOC of a cell based on the state parameters of the battery, and then determines a second relative self-discharge SOC of the battery pack; and a second determining module, which determines a first relative self-discharge rate of the cell based on the first relative self-discharge SOC, and determines a second relative self-discharge rate of the battery pack based on the second relative self-discharge SOC.

[0018] Accordingly, this application provides a controller, including: a memory and a processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory, causing the processor to execute the battery relative self-discharge rate calculation method as described in any of the preceding claims.

[0019] Accordingly, this application provides an electrical device, including: a battery pack and a controller, wherein the battery pack includes a plurality of individual battery cells; the controller is used to execute the battery relative self-discharge rate calculation method described in any of the above claims.

[0020] Accordingly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method for calculating the relative self-discharge rate of a battery as described in any of the preceding claims.

[0021] Accordingly, this application provides a computer program product, characterized in that it includes a computer program, which, when executed by a processor, implements the method for calculating the relative self-discharge rate of a battery as described in any of the above claims.

[0022] This application provides a method, apparatus, controller, and electrical equipment for calculating the relative self-discharge rate of a battery. By determining the relative self-discharge SOC and relative self-discharge rate of a cell and a battery pack, it can distinguish the differences in self-discharge characteristics between individual cells and the battery pack, making up for the shortcomings of traditional methods that ignore individual cell differences. It can also locate cells with abnormal self-discharge by comparison, improving fault diagnosis efficiency and reducing maintenance costs. Furthermore, it can capture the self-discharge deterioration state through dynamic monitoring, providing a basis for judging deterioration, avoiding safety risks, and providing strong support for efficient battery pack maintenance and performance optimization. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a flowchart illustrating one embodiment of the method for calculating the relative self-discharge rate of the battery in this application;

[0025] Figure 2 This application Figure 1 A flowchart illustrating an implementation method for step S100;

[0026] Figure 3 This application Figure 2 A flowchart illustrating an embodiment of step S120;

[0027] Figure 4 This application Figure 1 A flowchart illustrating an implementation method for step S200;

[0028] Figure 5 This application Figure 1 A flowchart illustrating another embodiment of step S200;

[0029] Figure 6 This is a flowchart illustrating another embodiment of the method for calculating the relative self-discharge rate of the battery in this application;

[0030] Figure 7 This is a flowchart illustrating another implementation of the method for calculating the relative self-discharge rate of the battery in this application.

[0031] Figure 8 This is a schematic diagram of one embodiment of the battery relative self-discharge rate calculation device of this application;

[0032] Figure 9 This is a schematic diagram of the controller provided in this application. Detailed Implementation

[0033] The present application will now be described in further detail with reference to the accompanying drawings and embodiments. It should be noted that the following embodiments are for illustrative purposes only and do not limit the scope of the application. Similarly, the following embodiments are only some, not all, embodiments of the present application, and all other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of this application.

[0034] In the description of this application, it should be understood that the terms "upper," "lower," "left," "right," "front," "rear," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or relative positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this application and for simplification, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application. Unless otherwise specified, the above-mentioned orientational descriptions can be flexibly set in practical applications, provided that the relative positional relationships shown in the accompanying drawings are satisfied.

[0035] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0036] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," "linking," and "communication" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection. They can refer to a direct connection or an indirect connection through an intermediate medium, or a connection within two components. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0037] In embodiments of this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, article, or apparatus that includes that element.

[0038] 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 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.

[0039] The following section introduces the relevant concepts of this application:

[0040] Inflection point capacity: refers to the actual capacity of a battery cell at the SOC corresponding to the inflection point of the SOC-OCV curve.

[0041] Cumulative equalization time: This refers to the total time that the BMS performs "equalization operation" on a particular cell. The purpose of equalization is to eliminate the SOC difference between cells. A longer cumulative equalization time indicates that the SOC deviation between this cell and other cells is more frequent or more severe, requiring more frequent intervention from the BMS.

[0042] Relative self-discharge rate of a battery: This refers to the difference in self-discharge rate between different cells within the same battery pack (rather than the absolute self-discharge rate of a single cell). Specifically, the self-discharge rate refers to the natural loss of electrical charge that a cell undergoes when it is at rest (not being charged or discharged) due to internal chemical reactions (such as electrolyte decomposition, side reactions of electrode materials) or physical leakage. This phenomenon is called "self-discharge." The self-discharge rate is usually expressed as the "proportion of electrical charge loss per unit time" (e.g., a loss of 0.5% capacity per day).

[0043] The following details the calculation method for the relative self-discharge rate of the battery in this application.

[0044] Please see Figure 1 , Figure 1 This is a flowchart illustrating one embodiment of the battery relative self-discharge rate calculation method of this application, as shown below. Figure 1 The method for calculating the relative self-discharge rate of the battery in this application includes the following steps:

[0045] S100 determines the first relative self-discharge SOC of the cell based on the state parameters of the battery, and then determines the second relative self-discharge SOC of the battery pack.

[0046] In this embodiment, the battery state parameters include at least the measured inflection point capacity and cumulative equalization time for each cell. The measured inflection point capacity is the capacity corresponding to the voltage "inflection point" (such as a critical point of rapid voltage rise / fall) during the charging and discharging process, and is a key indicator reflecting the cell's health status. The cumulative equalization time is the total time spent by the equalization circuit during cell use to "balance" (adjust the voltage / capacity of each cell). The equalization operation affects the actual capacity measurement of the cell.

[0047] Furthermore, the state parameters of the battery pack in this application may also include, but are not limited to, vehicle state data, the rated capacity of the vehicle battery, and the vehicle's hardware configuration. Vehicle state data, such as whether the vehicle is currently moving, stationary, charging, or discharging, affects the battery's operating environment, thereby indirectly affecting cell performance. The rated capacity of the vehicle battery is the standard capacity designed in the battery, serving as a benchmark for assessing whether the current cell capacity is normal. The vehicle's hardware configuration, such as the battery structure (series / parallel connection) and the type of balancing circuit, determines how the data is interpreted.

[0048] By comprehensively collecting the current state parameters of the battery, complete data raw materials can be provided for subsequent steps such as screening effective data and calculating relative self-discharge SOC, ensuring that the analysis covers key dimensions such as battery operating conditions, hardware, and core performance parameters.

[0049] Furthermore, based on the aforementioned battery state parameters, the first relative self-discharge SOC of the cell and the second relative self-discharge SOC of the battery pack are determined, and then the relative self-discharge rates of the two are calculated accordingly. In this embodiment, the battery state parameters first determine the first relative self-discharge SOC of the cell, and then the first relative self-discharge SOC of the cell determines the final second relative self-discharge SOC of the battery pack. The specific calculation process is described in detail below.

[0050] This application calculates the first relative self-discharge SOC of the battery cell and the second relative self-discharge SOC of the battery pack respectively, decomposing the self-discharge characteristics of the battery system into two dimensions: "microscopic individual" and "macroscopic whole". This can identify abnormal aging of individual cells (such as a sudden increase in self-discharge rate caused by micro-short circuit) and evaluate the performance bottleneck of the entire battery pack (constrained by the worst cell).

[0051] S200, determine the first relative self-discharge rate of the cell based on the first relative self-discharge SOC, and determine the second relative self-discharge rate of the battery pack based on the second relative self-discharge SOC.

[0052] The self-discharge rate is determined by calculating the relative self-discharge SOC of each cell and battery pack. By calculating the changes in their respective self-discharge rates, early warnings of accelerated battery aging or potential faults (such as sudden changes in self-discharge rate) can be provided, achieving an upgrade from "post-event detection" to "pre-event prediction." Compared to existing technologies that directly calculate the self-discharge rate based on "capacity decay," which ignores the influence of battery state parameters (such as temperature and cycle count) on the SOC during self-discharge, this application integrates the influence of multiple state parameters in calculating the first relative self-discharge SOC of the cell and the second relative self-discharge SOC of the battery pack. Therefore, the obtained self-discharge rate is closer to the actual self-discharge process of the battery, avoiding the bias caused by a single parameter (such as capacity).

[0053] The above implementation method, by determining the first relative self-discharge SOC of the cell and the second relative self-discharge SOC of the battery pack respectively, and then calculating the corresponding self-discharge rate layered design, separates and evaluates the self-discharge characteristics of the individual cell and the battery pack as a whole, realizes the accurate location of the faulty cell, and provides a reliable technology for battery health monitoring, fault early warning and full life cycle management.

[0054] The above-described implementation method, by determining the first relative self-discharge SOC of the battery cell and the second relative self-discharge SOC of the battery pack respectively, and further calculating the relative self-discharge rate of the two, can effectively distinguish the differences in self-discharge characteristics between a single battery cell and the battery pack. This overcomes the shortcomings of traditional methods that only evaluate the overall self-discharge of the battery pack and ignore the individual differences of the battery cells. Furthermore, by comparing the relative self-discharge rates of the battery cell and the battery pack, it is possible to accurately locate the battery cell with abnormal self-discharge, solving the problem that traditional overall evaluation cannot identify specific faulty battery cells. This helps to improve fault diagnosis efficiency and reduce maintenance costs.

[0055] Furthermore, by dynamically monitoring the relative self-discharge rate, the accelerated state of self-discharge deterioration can be captured in a timely manner, providing a reliable basis for judging whether the battery self-discharge has deteriorated, avoiding safety risks caused by failure to intervene in time, and providing strong support for the efficient maintenance and performance optimization of the battery pack.

[0056] Please refer to further information. Figure 2 , Figure 2 This application Figure 1 A flowchart illustrating an implementation method for step S100 is shown below. Figure 2 Step S100 further includes the following sub-steps:

[0057] S110: Preprocess the measured inflection point capacity and cumulative equalization time according to preset conditions to obtain the effective measured inflection point capacity and effective cumulative equalization time of each cell.

[0058] It is understandable that battery packs are composed of multiple cells connected in series and parallel, but slight differences in the cell manufacturing process (such as material uniformity and internal resistance variation) will lead to natural differences in their self-discharge rates. By calculating the first relative self-discharge SOC of each cell, these individual differences can be accurately captured, providing basic data for subsequent analysis.

[0059] In the specific embodiments of this application, the state parameters referenced for the relative self-discharge rate of the battery are the measured inflection point capacity and cumulative equalization time of each cell. The preprocessing preconditions are that the measured inflection point capacity of the cell is greater than 0, and the cumulative equalization time of the cell must also be greater than or equal to 0. In practical applications, the inflection point capacity cannot be negative; if it is negative, it is usually due to measurement errors or equipment malfunctions. Positive data is retained to ensure the authenticity of the "effective inflection point." Furthermore, the cumulative equalization time is a time indicator and cannot be negative (negative values ​​may indicate recording errors). Non-negative data is retained to ensure the rationality of the "effective equalization time." Thus, after preprocessing, the effective measured inflection point capacity and effective cumulative equalization time of each cell can be obtained.

[0060] The above implementation method, by preprocessing the battery status information, can ensure the validity and reliability of the data used in subsequent calculations and eliminate the interference of abnormal or invalid data on the results.

[0061] S120, the first relative self-discharge SOC is determined based on the effective measurement inflection point capacity and the effective cumulative equalization time.

[0062] Please combine further Figure 3 , Figure 3 This application Figure 2 A flowchart illustrating an implementation method for step S120 is shown below. Figure 3 Step S120 includes the following sub-steps:

[0063] S121 obtains the balanced current of each cell.

[0064] S122, based on the correlation between effective measured inflection point capacity, effective cumulative balancing time and balancing current, determine the correction inflection point capacity of each cell.

[0065] Based on the correlation between effective measurement inflection point capacity, effective cumulative equalization time, and equalization current of each cell, the correction inflection point capacity of each cell is determined using the following formula:

[0066] Qcorrected,i =Qmeasured,i -Ibal ·tbal,i (1)

[0067] Where Qcorrected,i is the "true inflection point capacity" of the i-th cell after excluding the effect of equalization, that is, the corrected inflection point capacity, which can reflect the characteristics of the cell itself.

[0068] Qmeasured,i represents the measured inflection point capacity of the i-th cell, which includes interference from the equalization operation.

[0069] Ibal is the balancing current, which is the current flowing through the cell when the BMS performs balancing, and tbal,i is the effective cumulative balancing time of the i-th cell.

[0070] It is understandable that during battery use, the balancing circuit will adjust the cells through the balancing current (Ibal) (such as charging cells with low capacity or discharging cells with high capacity). Within the cumulative balancing time (tbal,i), the balancing current will cause the measured inflection point capacity (Qmeasured,i) of the cell to include the effect of the balancing operation, that is, not the actual capacity of the cell itself.

[0071] In this embodiment of the application, "Ibal·tbal,i" (current × time = capacity) is the "capacity deviation" caused by the equalization current within the effective cumulative time. Subtracting this deviation from the effective measured inflection point capacity, the resulting "Qcorrected,i" is the true inflection point capacity of the cell itself after eliminating equalization interference, i.e., the corrected inflection point capacity.

[0072] The above implementation method can eliminate the interference of equalization operation on the measurement value, so that the corrected inflection point capacity (Qcorrected,i) only reflects the inherent characteristics of the cell itself, such as actual capacity and aging degree, thereby more accurately judging the true consistency difference between cells.

[0073] S123, the first relative self-discharge SOC of each cell is determined based on the correction inflection point capacity, the nominal capacity of the battery, and the minimum correction inflection point capacity.

[0074] Furthermore, the first relative self-discharge SOC of each cell is determined based on the corrected inflection point capacity, the battery's nominal capacity, and the minimum corrected inflection point capacity, using the following formula:

[0075] SOCrel,i = (Qcorrected,-Qmin ) / Qnom·100 (2)

[0076] Wherein, SOCrel,i: the first relative self-discharge SOC of the i-th cell, representing the degree of difference in self-discharge between this cell and the worst cell in the battery pack.

[0077] Qcorrected,i: The corrected inflection point capacity of the i-th cell after excluding the influence of the equalization current.

[0078] Qmin: The minimum corrected inflection point capacity among all cells, representing the inflection point capacity of the worst-performing cell in the battery pack.

[0079] Qnom: The nominal capacity of the battery, that is, the total capacity of the battery as specified in the design.

[0080] This application compares the difference between the corrected inflection point capacity (Qcorrected,i) of each cell and the minimum corrected inflection point capacity (Qmin) in the battery pack, and converts the difference into the first relative self-discharge SOC value (SOCrel,i) of the cell, which can intuitively reflect the degree of self-discharge of each cell relative to the worst performing cell.

[0081] Furthermore, this application indirectly assesses the differences in self-discharge performance of battery cells by comparing the relative differences in the correction inflection point capacity of the cells, converting the capacity difference into an intuitive SOC percentage. Moreover, this application excludes the influence of equalization current, which can more accurately reflect the true performance differences of the cells and provide a reliable basis for battery management and maintenance.

[0082] S130, determine the second relative self-discharge SOC of the battery pack based on the first relative self-discharge SOC of each cell.

[0083] In practical applications, battery packs consist of multiple cells (usually connected in series or parallel). Their overall performance (including self-discharge characteristics) is limited by the cell with the worst performance. In self-discharge scenarios, if a cell has the highest relative self-discharge state of charge (SOC), meaning its self-discharge is the most significant, that cell will be the first to cause a decrease in the battery pack's usable capacity and accelerate SOC decay, thus affecting the overall battery pack's range and performance.

[0084] Therefore, in this embodiment of the application, the "maximum value of the first relative self-discharge SOC among all cells" is used as the second relative self-discharge SOC of the battery pack, which can accurately reflect the actual self-discharge level of the battery pack.

[0085] In the above embodiments, by quantifying the first relative self-discharge SOC of each cell in layers and determining the second relative self-discharge SOC of the battery pack based on the first relative self-discharge SOC of the cells, the system achieves accurate location of cells with abnormal self-discharge, objectively correlates the individual characteristics of cells with the overall state of the battery pack, and thus provides more comprehensive state information for the overall evaluation of the battery.

[0086] It is understandable that, after determining the first relative self-discharge SOC of the battery cell and the second relative self-discharge SOC of the battery pack, and before calculating their respective relative self-discharge rates, the process also includes: filtering and smoothing the first relative self-discharge SOC of each battery cell and the second relative self-discharge SOC of the battery pack.

[0087] Optionally, in this embodiment of the application, by filtering the first relative self-discharge SOC of each cell and the second relative self-discharge SOC of the battery pack, the true self-discharge trend can be extracted from the noisy raw data, providing a reliable basis for subsequent analysis. The raw noise may originate from sensor measurement errors, environmental interference, and internal electrochemical fluctuations of the battery.

[0088] In a specific implementation, Kalman filtering is used to filter and smooth the relative self-discharge data of cells and battery packs. This effectively eliminates noise interference introduced during data acquisition due to sensor errors, environmental interference, and random system fluctuations, purifying the original data and making it closer to the actual self-discharge variation. Furthermore, the smoothed data exhibits reduced fluctuations and clearer trends, providing stable and reliable foundational data for subsequent calculations of the median by time window segmentation, linear interpolation to fill missing values, and fitting of the self-discharge rate. This avoids outliers caused by noise interfering with the analysis results, thereby improving the accuracy of self-discharge rate calculation and the reliability of time series trend judgment.

[0089] This application evaluates the relative self-discharge rates of individual cells and the battery pack, enabling a comprehensive diagnosis of the battery system. Specifically, at the cell level, the self-discharge rate of a single cell reflects its individual health status (such as the presence of internal short circuits, accelerated aging, or other abnormalities). Due to differences in manufacturing processes and uneven aging during use, the self-discharge rates between cells may vary significantly (for example, the self-discharge rate of one cell may be three times that of other cells). Analyzing only the overall self-discharge rate of the battery pack can mask the abnormal risks of individual cells, leading to a failure to provide early warnings for localized problems (such as thermal runaway in a single cell).

[0090] Furthermore, at the battery pack level: the overall self-discharge rate of the battery pack reflects its performance as a complete system and is limited by the cell with the highest self-discharge rate. For example, even if most cells are in good condition, if even one cell has an excessively high self-discharge rate, the overall range and lifespan of the battery pack will still decrease significantly. Therefore, analyzing the battery pack's self-discharge rate can directly assess its actual usability and provide a basis for system-level decisions (such as whether the battery pack needs to be replaced). The following details the calculation process for the relative self-discharge rates of the cells and the battery pack in this application.

[0091] Please refer to further information. Figure 4 , Figure 4 This application Figure 1 A flowchart illustrating step S200 of an implementation method is provided. This embodiment describes the calculation process of the first relative self-discharge rate of the battery cell. Figure 4 Step S200 further includes the following sub-steps:

[0092] S210, the self-discharge time of the battery cell is segmented according to the first preset time interval.

[0093] In this embodiment, the self-discharge time of the battery cell needs to be segmented according to a first preset time interval. Specifically, a fixed time length can be set as an analysis window based on the battery's self-discharge characteristics, such as self-discharge rate and data acquisition frequency. In this application, the preset time interval can be, for example, 5 minutes, 1 hour, or 1 day. The preset time interval serves as the benchmark for subsequent data segmentation and must reflect the time-varying trend of self-discharge. In practical applications, a time interval that is too short may be affected by noise interference, while a time interval that is too long may lose details or smooth out key changes. Therefore, a suitable time interval needs to be selected based on the actual situation; no specific limitation is made here.

[0094] Furthermore, the time difference window is segmented according to a preset time interval. The time difference refers to the total duration from the start time to the end time of a data record, or the time span between any two adjacent data points. The total time difference is divided into multiple consecutive and equally long time intervals, or intervals, according to the aforementioned preset time intervals. For example, if the total duration is 6 hours and the preset time interval is 2 hours, it can be divided into three intervals: "0-2h", "2-4h", and "4-6h", each with a duration of 2 hours.

[0095] It is understood that, in the embodiments of this application, by segmenting, the originally potentially randomly distributed discrete data is incorporated into a unified time frame to ensure that the self-discharge amount in different intervals is comparable in time.

[0096] S220, calculate the first characteristic value of the first relative self-discharge SOC of the cell in each segment interval.

[0097] In a specific embodiment of this application, each segment interval may contain multiple raw data points for relative self-discharge. For example, if the preset time interval is 1 hour and data is recorded every 10 minutes, then there are 6 raw data points in this interval. By calculating the first characteristic value—which this application uses is the median—the raw data within the segment interval is statistically smoothed. Its function is to sort all the data within the segment interval by size and take the value at the middle position (median) as the representative value of that interval. This allows us to obtain the first characteristic value (median) of the first relative self-discharge SOC for all cells within each segment interval.

[0098] In the above embodiments, since the median is not sensitive to extreme data caused by factors such as sensors, choosing the median as the representative value of the segmented interval can more robustly reflect the true level of self-discharge in that interval and reduce noise interference.

[0099] Furthermore, if the first feature value of any segmented interval is missing, interpolation is performed based on the first feature values ​​of adjacent intervals to obtain the first feature value of that segmented interval.

[0100] In specific application scenarios, during actual data acquisition, sensor malfunctions, data transmission interruptions, or other reasons may result in a lack of original data within a certain segment interval, meaning the first feature value of that interval is missing (median is missing). In such cases, linear interpolation is needed to fill in the missing value. Specifically, interpolation calculations are performed based on the first feature values ​​of adjacent intervals to obtain the missing first feature value.

[0101] Taking the median as an example, after identifying a segmented interval with a missing first median, linear interpolation is needed to fill in the missing first median. Specifically, this can be achieved by using the first median of the preceding and following valid segments as benchmarks, assuming the self-discharge rate between the two segments changes linearly with time, and calculating the first median of the missing interval based on the time ratio. For example, if the first median of the preceding segment (2-4h) is 5%, the first median of the following segment (6-8h) is 9%, and the 5-6h segment is missing, then the first median of the missing interval can be estimated as 7% based on a linear relationship.

[0102] The above implementation method can eliminate the impact of missing data on the continuity of time series and ensure that all intervals have valid data available when calculating the difference in self-discharge between adjacent segment intervals.

[0103] S230, the first relative self-discharge rate of the battery cell is determined based on the difference of the first characteristic value of adjacent segment intervals and the first preset time interval.

[0104] Specifically, after obtaining the first characteristic value (first median) of the battery cell, the first relative self-discharge rate needs to be calculated separately. Specifically, the first relative self-discharge rate of the battery cell is determined by the difference between the first medians of adjacent segment intervals and the preset time interval.

[0105] The calculation of the first relative self-discharge rate for a battery cell is based on the difference between the first medians of adjacent segment intervals and a preset time interval. The formula is as follows:

[0106] RSDR=ΔRSDQ / Δt1 (3)

[0107] Wherein, ΔRSDQ represents the change in self-discharge between adjacent segments, that is, the difference between the first median of the adjacent segments (such as the difference between the first median of the first relative self-discharge SOC of the cell in the (n-1)th segment and the nth segment), and Δt1 is the preset time interval.

[0108] The above formula (3) can be used to calculate the rate of change of the first relative self-discharge SOC of the cell per unit time. Essentially, it uses first-order linear fitting (i.e., the slope of adjacent segment intervals) to characterize the first relative self-discharge rate of the cell in that interval.

[0109] Please refer to further information. Figure 5 , Figure 5 This application Figure 1 A flowchart illustrating another embodiment of step S200 is shown. This embodiment describes the calculation process of the second relative self-discharge rate of the battery pack. Figure 5 Step S200 further includes the following sub-steps:

[0110] S240, the self-discharge time of the battery pack is segmented according to the second preset time interval.

[0111] Similar to the processing direction of the battery cells, this embodiment requires segmenting the self-discharge time of the battery pack according to a second preset time interval. Specifically, a fixed time length can be set as an analysis window based on the battery's self-discharge characteristics, such as self-discharge rate and data acquisition frequency. In this application, the preset time interval can be, for example, 5 minutes, 1 hour, or 1 day. The preset time interval serves as the benchmark for subsequent data segmentation and must reflect the time-varying trend of self-discharge. In practical applications, a time interval that is too short may be affected by noise interference, while a time interval that is too long may lose details or smooth out key changes. Therefore, a suitable time interval needs to be selected based on the actual situation; no specific limitation is made here.

[0112] Furthermore, the time difference window is segmented according to a preset time interval, where the time difference refers to the total duration from the start time to the end time of the data record, or the time span between any two adjacent data points.

[0113] The total time difference is divided into multiple consecutive and equally long time intervals, or intervals, according to the aforementioned preset time intervals. For example, if the total duration is 6 hours and the preset time interval is 2 hours, it can be divided into three intervals: "0-2h", "2-4h", and "4-6h", with each interval lasting 2 hours. It is understood that, in this embodiment, by segmenting, potentially randomly distributed discrete data is incorporated into a unified time frame, ensuring that the self-discharge amounts in different intervals are comparable in time.

[0114] Furthermore, in this embodiment, the first preset time interval and the second preset time interval are the same, which can ensure that the self-discharge rate and change rate of the two are consistent in units in the time dimension, the horizontal comparability of the self-discharge rate, eliminate interference in the time dimension, strengthen the causal relationship between the cell and the battery pack, and improve the efficiency of problem location.

[0115] Understandably, this application enables a comprehensive diagnosis of the battery system by analyzing the self-discharge rate of the cells and the battery pack separately.

[0116] S250, calculate the second characteristic value of the second relative self-discharge SOC of the battery pack in each segment interval.

[0117] In this embodiment, the calculation of the second characteristic value of the battery pack is similar to the calculation of the first characteristic value of the battery cell, as described in detail below:

[0118] In a specific embodiment of this application, each segment interval may contain multiple raw data points for relative self-discharge. For example, if the preset time interval is 1 hour and data is recorded every 10 minutes, then there are 6 raw data points in that interval. Calculating the second characteristic value of the battery pack—the median—is a statistical smoothing process performed on the raw data within the segment interval. Its function is to sort all the data within the segment interval by size and take the value at the middle position (the median) as the representative value of that interval. This yields the second characteristic value (median) of the second relative self-discharge SOC of the battery pack within each segment interval.

[0119] In the above embodiments, since the median is not sensitive to extreme data caused by factors such as sensors, choosing the median as the representative value of the segmented interval can more robustly reflect the true level of self-discharge in that interval and reduce noise interference.

[0120] Furthermore, if the second feature value of any segmented interval is missing, interpolation is performed based on the second feature values ​​of adjacent intervals to obtain the second feature value of that segmented interval.

[0121] In specific application scenarios, during actual data acquisition, sensor malfunctions, data transmission interruptions, or other reasons may result in a lack of original data within a certain segment interval, meaning the second feature value of that interval is missing (median is missing). In such cases, linear interpolation is needed to fill in the missing value. Specifically, interpolation calculations are performed based on the second feature values ​​of adjacent intervals to obtain the missing second feature value.

[0122] Taking the median as an example, we will explain in detail that, based on the second median of the previous valid segment interval and the second median of the next valid interval, we assume that the self-discharge between the two segment intervals changes linearly with time, and calculate the second median of the missing interval by means of the time ratio.

[0123] The above implementation method can eliminate the impact of missing data on the continuity of time series and ensure that all intervals have valid data available when calculating the difference in self-discharge between adjacent segment intervals.

[0124] S260, the second relative self-discharge rate of the battery pack is determined based on the difference of the second characteristic value of adjacent segment intervals and the second preset time interval.

[0125] Similar to the calculation of the first relative self-discharge rate of a battery cell, the second relative self-discharge rate of a battery pack is also calculated as: the ratio of the difference between the second median of the second relative self-discharge SOC of adjacent segment intervals to the second preset time interval. Essentially, it also uses a first-order linear fit (i.e., the slope of adjacent segment intervals) to characterize the second relative self-discharge rate of the battery pack in that interval.

[0126] The above implementation converts the relative self-discharge of cells / battery packs into relative self-discharge rates, quantifying the degree of self-discharge of cells / battery packs per unit time and enabling a direct comparison of the "speed" of self-discharge. Furthermore, through a combination of fixed-time-interval segmentation, median smoothing, and linear interpolation completion, the original, discrete, potentially noisy or missing relative self-discharge rates (SOC) of cells and battery packs are transformed into continuous, uniform, and interference-resistant time-series data. This processing allows the differences in self-discharge rates between adjacent segments to more accurately reflect the true temporal variation, providing a reliable data foundation for subsequent calculations of the "interval relative self-discharge rate."

[0127] Please combine further Figure 6 , Figure 6 This is a flowchart illustrating another embodiment of the method for calculating the relative self-discharge rate of the battery in this application, as shown below. Figure 6 It includes the following steps:

[0128] S300, the first relative self-discharge rate change rate of the battery cell is determined based on the difference in the first relative self-discharge rate of adjacent segmented battery cells and the first preset time interval.

[0129] Specifically, for a battery cell, the calculation of the first relative self-discharge rate change rate is based on the difference between the first self-discharge rate change rates RSDR of adjacent intervals obtained in the above steps. For example, the first self-discharge rate change rate RSDRn-1 of the (n-1)th interval and the first self-discharge rate change rate RSDRn of the nth interval are calculated. The difference between the two is then combined with a preset time interval to obtain the first self-discharge rate change rate of the battery cell, as expressed below:

[0130] The first relative self-discharge rate change rate of the battery cell = (RSDRn-1-RSDRn) / Δt1.

[0131] In the above embodiments, the first relative self-discharge rate change rate of the battery cell can detect the abnormal increase trend of self-discharge rate in the power battery system safety early warning, identify the hidden fault inside the battery cell in advance, and issue an early warning several hours to several days before the risk of thermal runaway occurs, significantly reducing safety accidents such as vehicle fire and battery failure.

[0132] Please combine further Figure 7 , Figure 7 This is a flowchart illustrating another implementation of the method for calculating the relative self-discharge rate of the battery in this application, as shown below. Figure 7 It includes the following steps:

[0133] S400, the second relative self-discharge rate change rate of the battery pack is determined based on the difference in the second relative self-discharge rate of the battery pack in adjacent segment intervals and the second preset time interval.

[0134] For the battery pack, the calculation of its second relative self-discharge rate change rate is the same as that of the battery cell. That is, the second relative self-discharge rate change rate of the battery pack is obtained by the ratio of the difference of the second self-discharge rate change rate RSDR between adjacent intervals and the second preset time interval.

[0135] Understandably, the relative self-discharge rate change rate of a cell / pack is used to further analyze the trend of self-discharge rate itself. Specifically, a positive change rate indicates that the self-discharge rate is accelerating (the battery condition may be deteriorating), while a negative change rate indicates that the self-discharge rate is slowing down (possibly due to environmental improvements or balancing strategies). The relative self-discharge rate change rate of a cell / pack dynamically reflects the stability of the cell / pack's self-discharge characteristics, providing a crucial basis for judging the battery's health status.

[0136] The above implementation method, which measures the change rate of the battery's relative self-discharge rate, overcomes the limitation of only evaluating the absolute value of the battery's relative self-discharge rate. It upgrades the analysis from "static value" to "dynamic trend" analysis, providing more critical and timely decision support for the monitoring of the battery's status throughout its entire life cycle, anomaly warning, and refined management.

[0137] Please see Figure 8 , Figure 8 This is a schematic diagram of one embodiment of the battery relative self-discharge rate calculation device of this application, as shown below. Figure 8 The battery relative self-discharge rate calculation device 100 provided in this application includes:

[0138] The first determining module 101 determines the first relative self-discharge SOC of the battery cell based on the battery's state parameters, and then determines the second relative self-discharge SOC of the battery pack.

[0139] The second determining module 102 determines the first relative self-discharge rate of the cell based on the first relative self-discharge SOC, and determines the second relative self-discharge rate of the battery pack based on the second relative self-discharge SOC.

[0140] It should be noted that the specific details of each module unit in the battery relative self-discharge rate calculation device 100 have been described in detail in the embodiments of the battery relative self-discharge rate calculation method, and will not be repeated here.

[0141] In this embodiment, by determining the first relative self-discharge SOC of the cell and the second relative self-discharge SOC of the battery pack respectively, and further calculating their relative self-discharge rates, the differences in self-discharge characteristics between a single cell and the battery pack can be effectively distinguished. This overcomes the shortcomings of traditional methods that only evaluate the overall self-discharge of the battery pack while ignoring the individual differences of the cells. Furthermore, by comparing the relative self-discharge rates of the cell and the battery pack, cells with abnormal self-discharge can be accurately located, solving the problem that traditional overall assessment cannot identify specific faulty cells. This helps to improve fault diagnosis efficiency and reduce maintenance costs.

[0142] Furthermore, by dynamically monitoring the relative self-discharge rate, the accelerated state of self-discharge deterioration can be captured in a timely manner, providing a reliable basis for judging whether the battery self-discharge has deteriorated, avoiding safety risks caused by failure to intervene in time, and providing strong support for the efficient maintenance and performance optimization of the battery pack.

[0143] In this application embodiment, the terms "module" or "unit" refer to a computer program or part of a computer program that has a predetermined function and works with other related parts to achieve a predetermined goal, and can be implemented wholly or partially using software, hardware (such as processing circuitry or memory), or a combination thereof. Similarly, a processor (or multiple processors or memory) can be used to implement one or more modules or units. Furthermore, each module or unit can be part of an overall module or unit that includes the functionality of that module or unit.

[0144] Figure 9 This is a schematic diagram of the controller provided in this application. Figure 9 As shown, the controller 50 provided in this embodiment includes at least one processor 501 and a memory 502.

[0145] Optionally, the controller 50 also includes a communication component 503. The processor 501, memory 502, and communication component 503 are connected via a bus.

[0146] In the specific implementation process, at least one processor 501 executes computer execution instructions stored in memory 502, causing at least one processor 501 to execute the above-mentioned battery relative self-discharge rate calculation method.

[0147] The specific implementation process of processor 501 can be found in the above embodiment of the battery relative self-discharge rate calculation method. Its implementation principle and technical effect are similar, and will not be repeated here.

[0148] When a battery pack is used in a vehicle, the controller can be a battery management system (BMS) or a vehicle controller.

[0149] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0150] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0151] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0152] This application also provides an electrical device, including: a battery pack and a controller, wherein the battery pack includes multiple individual battery cells; the controller is used to execute the battery relative self-discharge rate calculation method of the above method embodiments.

[0153] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method for calculating the relative self-discharge rate of a battery.

[0154] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method for calculating the relative self-discharge rate of a battery.

[0155] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0156] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0157] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0158] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0159] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0160] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0161] Those skilled in the art will appreciate that all or part of the steps in the above-described method embodiments can be implemented using hardware associated with program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0162] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be performed by a computer program, or by a computer program controlling related hardware. The computer program can be stored in a storage medium and loaded and executed by a processor.

[0163] The foregoing has provided a detailed description of a method, apparatus, controller, and electrical device for calculating the relative self-discharge rate of a battery, as provided in the embodiments of this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

[0164] Although embodiments of this application have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of this application, the scope of which is defined by the claims and their equivalents.

Claims

1. A method for calculating the relative self-discharge rate of a battery, characterized in that, The calculation method includes: The first relative self-discharge SOC of the cell is determined based on the state parameters of the battery, and then the second relative self-discharge SOC of the battery pack is determined. The first relative self-discharge rate of the cell is determined based on the first relative self-discharge SOC, and the second relative self-discharge rate of the battery pack is determined based on the second relative self-discharge SOC.

2. The method for calculating the relative self-discharge rate of a battery according to claim 1, characterized in that, The state parameters include at least the measured inflection point capacity and cumulative equalization time of the battery cell. Determining the first relative self-discharge SOC of the battery cell based on the battery state parameters, and then determining the second relative self-discharge SOC of the battery pack, includes: The measured inflection point capacity and the cumulative equalization time are preprocessed according to preset conditions to obtain the effective measured inflection point capacity and effective cumulative equalization time of each cell. The first relative self-discharge SOC is determined based on the effective measured inflection point capacity and the effective cumulative equalization time. The second relative self-discharge SOC is determined based on the first relative self-discharge SOC.

3. The method for calculating the relative self-discharge rate of a battery according to claim 2, characterized in that, The preset conditions are that the measurement inflection point capacity is greater than 0 and the cumulative equalization time is greater than or equal to 0.

4. The method for calculating the relative self-discharge rate of a battery according to claim 2, characterized in that, The determination of the first relative self-discharge SOC based on the effective measurement inflection point and the effective cumulative equalization time includes: Obtain the balanced current of each battery cell; Based on the correlation between the effective measured inflection point capacity, the effective cumulative equalization time, and the equalization current, the correction inflection point capacity of each cell is determined. The first relative self-discharge state of charge (SOC) is determined based on the correction inflection point capacity, the nominal capacity of the battery, and the minimum correction inflection point capacity of each cell.

5. The method for calculating the relative self-discharge rate of a battery according to claim 2, characterized in that, Determining the second relative self-discharge SOC based on the first relative self-discharge SOC includes: The second relative self-discharge SOC of the battery pack is the maximum value of the first relative self-discharge SOC among all the cells.

6. The method for calculating the relative self-discharge rate of a battery according to claim 1, characterized in that, Determining the first relative self-discharge rate of the cell based on the first relative self-discharge SOC includes: The self-discharge time of the battery cell is segmented according to a first preset time interval; Calculate the first characteristic value of the first relative self-discharge SOC of the battery cell within each segment interval; The first relative self-discharge rate of the battery cell is determined based on the difference between the first feature values ​​of adjacent segment intervals and the first preset time interval.

7. The method for calculating the relative self-discharge rate of a battery according to claim 6, characterized in that, The calculation of the first characteristic value of the first relative self-discharge SOC of the battery cell within each segment interval includes: If the first feature value of any segmented interval is missing, interpolation is performed based on the first feature values ​​of adjacent intervals to obtain the first feature value of the segmented interval.

8. The method for calculating the relative self-discharge rate of a battery according to claim 6, characterized in that, After determining the first relative self-discharge rate of the cell based on the first relative self-discharge SOC, the process includes: determining the first relative self-discharge rate change rate of the cell based on the difference in the first relative self-discharge rates of the cell between adjacent segment intervals and the first preset time interval.

9. The method for calculating the relative self-discharge rate of a battery according to claim 1, characterized in that, Determining the second relative self-discharge rate of the battery pack based on the second relative self-discharge SOC includes: The self-discharge time of the battery pack is segmented according to a second preset time interval; Calculate the second characteristic value of the second relative self-discharge SOC of the battery pack within each segment interval; The second relative self-discharge rate of the battery pack is determined based on the difference between the second feature values ​​of the adjacent segment intervals and the second preset time interval.

10. The method for calculating the relative self-discharge rate of a battery according to claim 9, characterized in that, The calculation of the second characteristic value of the second relative self-discharge SOC of the battery pack within each segment interval includes: If the second feature value of any segmented interval is missing, interpolation is performed based on the second feature values ​​of adjacent intervals to obtain the second feature value of the segmented interval.

11. The method for calculating the relative self-discharge rate of a battery according to claim 9, characterized in that, The step of determining the second relative self-discharge rate of the battery pack based on the second relative self-discharge SOC then includes: The second relative self-discharge rate change rate of the battery pack is determined based on the difference in the second relative self-discharge rate of the battery pack between the adjacent segment intervals and the second preset time interval.

12. The method for calculating the relative self-discharge rate of a battery according to claim 1, characterized in that, After determining the first relative self-discharge SOC of the cell and the second relative self-discharge SOC of the battery pack based on the battery's state parameters, the process includes: The first relative self-discharge SOC of each cell and the second relative self-discharge SOC of the battery pack are filtered and smoothed respectively.

13. A device for calculating the relative self-discharge rate of a battery, characterized in that, The computing device includes: The first determining module determines the first relative self-discharge SOC of the battery cell based on the battery's state parameters, and then determines the second relative self-discharge SOC of the battery pack. The second determining module determines the first relative self-discharge rate of the cell based on the first relative self-discharge SOC, and determines the second relative self-discharge rate of the battery pack based on the second relative self-discharge SOC.

14. A controller, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method for calculating the relative self-discharge rate of the battery as described in any one of claims 1-12.

15. An electrical appliance, characterized in that, include: A battery pack and a controller, wherein the battery pack comprises multiple individual battery cells; The controller is used to execute the method for calculating the relative self-discharge rate of the battery as described in any one of claims 1-12.

16. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method for calculating the relative self-discharge rate of a battery as described in any one of claims 1-12.

17. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method for calculating the relative self-discharge rate of a battery as described in any one of claims 1-12.

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