Battery cell voltage determination method, battery management system and energy storage system

Abstract

The present application relates to the field of power management technology, and specifically to a method for determining a battery cell voltage, a battery management system, and an energy storage system. The method for determining a battery cell voltage proposed in the present application makes full use of the characteristic of the stepwise recursive update of the recursive least squares method, and adjusts the regression coefficient of the linear regression model according to the current battery data and the compensation result in each iteration. As the regression coefficient is continuously updated, the linear regression model can continuously correct previous errors and avoid long-term deviations caused by initial errors. This enables more accurate voltage compensation to be obtained during the battery balancing process, reducing errors caused by changes in battery parameters or measurement noise. The battery cell voltage measurement value is compensated by calculating the sampling line resistance and the balancing resistance, and the measurement error problem caused by voltage fluctuations during the balancing process is solved by a software algorithm, thereby achieving high-precision battery voltage measurement.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of power management technology, and specifically to a method for determining battery cell voltage, a battery management system, and an energy storage system. Background Art

[0002] The battery management system (BMS) is a key component in modern battery technology. Its role is to ensure that the battery pack operates in a safe, efficient and optimal performance state. Through a series of complex control and monitoring mechanisms, the BMS provides an intelligent management method for the battery pack, thereby significantly improving the service life and reliability of the battery pack.

[0003] A battery pack includes multiple battery cells. Due to certain inconsistencies between the battery cells, the battery pack will produce voltage differences during the charging and discharging process. In order to extend the service life of the battery pack and ensure its safety, it is usually necessary to perform balancing management on the battery pack. In the process of balancing management of the battery pack, the battery management system needs to accurately determine the voltage value of each battery cell. The applicant has found in the research that when the battery management system performs voltage detection on the battery cells in the battery pack, the existence of balancing current and sampling line resistance will cause large errors in the voltage values ​​obtained by directly sampling the battery cells, thereby affecting the balancing effect of the battery management system on the battery pack. Summary of the invention

[0004] In view of the above problems, the embodiments of the present application provide a method for determining battery cell voltage, a battery management system and an energy storage system, which are used to solve the above technical problems existing in the prior art.

[0005] In one aspect of an embodiment of the present application, a method for determining a battery cell voltage is provided, the method being applied to a battery management system, the battery management system being used to manage a plurality of battery cells connected in series; the battery management system comprising a plurality of voltage sampling circuits, the voltage sampling circuit comprising a balancing switch, a balancing resistor and a voltmeter, the balancing switch being connected in series with the balancing resistor and then being connected in parallel with the voltmeter; each of the voltage sampling circuits being respectively connected to two ends of each of the battery cells, for sampling the voltage of each of the battery cells, and adjacent voltage sampling circuits sharing a sampling line;

[0006] The method comprises:

[0007] S1: Obtain the first line resistance value of the voltage sampling circuit corresponding to the battery cell to be tested , Second line resistance and balancing resistor value ;

[0008] S2: Obtaining the first balanced voltage , the second balanced voltage , the third balance voltage , wherein the first equalization voltage The voltage value sampled by the voltmeter of the first voltage sampling circuit corresponding to the first battery cell adjacent to the battery cell to be tested when the balancing switch is closed is the voltage value sampled by the second balancing voltage sampling circuit corresponding to the first battery cell adjacent to the battery cell to be tested. is a voltage meter of a voltage sampling circuit corresponding to the battery cell to be tested, and the voltage value sampled when the balancing switch is closed, the third balancing voltage A voltage value sampled by a voltmeter of a third voltage sampling circuit corresponding to a third battery cell adjacent to the battery cell to be tested when the balancing switch is closed;

[0009] S3: According to the first line resistance , the first balanced voltage , Second line resistance , the second balanced voltage , the third balance voltage and balancing resistor value Determine a linear regression model, wherein the first line resistance , Second line resistance and the measured voltage value of the battery cell to be tested The linear regression coefficient matrix that constitutes the linear regression model ;

[0010] S4: Initialize the linear regression coefficient matrix and the covariance matrix , wherein the measured voltage value of the battery cell to be tested is The initial value of is the voltage value sampled by the voltmeter when the equalizing switch of the voltage sampling circuit corresponding to the battery cell to be tested and the equalizing switch of the voltage sampling circuit corresponding to the battery cell adjacent to the battery cell to be tested are both turned on;

[0011] S5: According to the first equalization voltage , the second balanced voltage and the third balancing voltage Determine the balanced current matrix ;

[0012] S6: According to the balanced current value matrix and the linear regression coefficient matrix Determine the predicted values ​​of the linear regression model ;

[0013] S7: According to the covariance matrix and the balanced current value matrix Determining the Error Gain ;

[0014] S8: Obtain the first balanced voltage at the current moment , the second balanced voltage , the third balance voltage and the actual output value of the linear regression model ;

[0015] S9: Based on the first balanced voltage at the current moment , the second balanced voltage , the third balance voltage , the predicted value of the linear regression model , the actual output value of the linear regression model , the error gain and the linear regression coefficient matrix , update the linear regression coefficient matrix at the current moment and the covariance matrix ;

[0016] S10: According to the linear regression coefficient matrix at the current moment Determine the actual voltage value of the battery cell to be tested ;

[0017] S11: Jump to step S5 until the equalization switch of the voltage sampling circuit adjacent to the battery cell to be tested is turned on.

[0018] Preferably, in some embodiments, the first line resistance , the first balanced voltage , Second line resistance , the second balanced voltage , the third balance voltage and balancing resistor value Determine the linear regression model, including:

[0019] The linear regression model is: ;

[0020] in, , , , ; ; .

[0021] Preferably, in some embodiments, the covariance matrix after initialization is , where M is the preset initialization factor, is the identity matrix.

[0022] Preferably, in some embodiments, the balanced current value matrix and the linear regression coefficient matrix Determine the predicted values ​​of the linear regression model ,include:

[0023] The predicted value of the linear regression model is determined by the following formula:

[0024] ;

[0025] in ; , is the regression coefficient matrix at time t-1; is the regression coefficient at time t-1;

[0026] .

[0027] Preferably, in some embodiments, the covariance matrix and the balanced current value matrix Determining the Error Gain ,include:

[0028] The error gain is determined by the following formula :

[0029] ;

[0030] Among them, the is the covariance matrix at time t-1, For the forgetting factor.

[0031] Preferably, in some embodiments, the predicted value according to the linear regression model is , the actual output value of the linear regression model , the error gain and the linear regression coefficient matrix , update the linear regression coefficient matrix at the current moment ,include:

[0032] Update the linear regression coefficient matrix at the current moment according to the following formula :

[0033] ;

[0034] in, is the linear regression coefficient matrix at time t-1.

[0035] Preferably, in some embodiments, the predicted value according to the linear regression model is , the actual output value of the linear regression model , the error gain and the linear regression coefficient matrix , update the covariance matrix at the current moment ,include:

[0036] Update the covariance matrix at the current moment according to the following formula :

[0037] .

[0038] Another aspect of the embodiments of the present application provides a battery management system for measuring the voltage of a battery cell in a battery pack;

[0039] The battery management system includes a controller and a plurality of voltage sampling circuits;

[0040] The voltage sampling circuit comprises a balancing switch, a balancing resistor and a voltmeter; the balancing switch is connected in series with the balancing resistor and then connected in parallel with the voltmeter to form a voltage sampling circuit;

[0041] Each of the voltage sampling circuits is connected to two ends of each of the battery cells respectively, and is used to sample the voltage of each of the battery cells, and adjacent voltage sampling circuits share a sampling line;

[0042] The controller is connected to each of the voltage meters and is used to execute any one of the above-mentioned methods for determining the battery cell voltage.

[0043] According to a third aspect of the embodiments of the present application, an energy storage system is provided, which includes a battery pack and the battery management system described in the above embodiments;

[0044] The battery pack includes a plurality of battery cells, each of which is connected in series with each other;

[0045] The battery management system is used to manage the battery pack.

[0046] According to a fourth aspect of the embodiments of the present application, a computer-readable storage medium is provided, wherein at least one executable instruction is stored in the storage medium. When the executable instruction is executed on a battery management system, the battery management system executes the operation of the battery cell voltage determination method described in any one of the above embodiments.

[0047] In summary, the battery cell voltage determination method proposed in the embodiment of the present application makes full use of the characteristic of the recursive least squares method of gradual recursive update. In each iteration, the linear regression model regression coefficient is adjusted according to the current battery data (such as the measured voltage value of the battery cell to be measured) and the compensation result (such as the balancing current or voltage). As the regression coefficient is continuously updated, the linear regression model can continuously correct previous errors and avoid long-term deviations caused by initial errors. This enables more accurate voltage compensation to be obtained during the battery balancing process, reducing errors caused by changes in battery parameters or measurement noise. The battery cell voltage measurement value is compensated by calculating the sampling line resistance and the balancing resistance, and the measurement error problem caused by voltage fluctuations during the balancing process is solved by a software algorithm, thereby achieving high-precision battery voltage measurement.

[0048] The above description is only an overview of the technical solution of the embodiment of the present application. In order to more clearly understand the technical means of the embodiment of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the embodiment of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The accompanying drawings are only used to illustrate the embodiments and are not to be considered as limiting the present application. In addition, the same reference symbols are used to represent the same components throughout the accompanying drawings. In the accompanying drawings:

[0050] Figure 1 A schematic diagram of the battery management system structure provided in an embodiment of the present application;

[0051] Figure 2 A flow chart of a method for determining battery cell voltage provided in an embodiment of the present application;

[0052] Figure 3 A schematic diagram of the operating results of the battery cell voltage determination method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0053] The exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein.

[0054] A battery pack is composed of multiple battery cells. Due to limitations of manufacturing processes, usage conditions and other factors, there are differences in performance parameters such as capacity and internal resistance of battery cells. This inconsistency may cause some battery cells to be overcharged or undercharged, resulting in a decrease in the overall performance of the battery pack and even safety issues. Balancing management in battery packs is an important part of the battery management system (BMS). Its main purpose is to reduce the inconsistency between battery cells and improve the overall performance and safety of the battery pack. The voltage detection of battery cells plays a vital role in balancing management. The battery management system needs to monitor the voltage of each battery cell in real time to ensure the safety and performance of the battery pack.

[0055] The applicant has found in research that traditional equalization management methods usually rely on detecting the real-time voltage of battery cells to determine whether equalization is needed. However, due to the existence of equalization current, the detected voltage of battery cells often deviates from the actual open-circuit voltage, resulting in errors in equalization judgment. This error may cause over-equalization or under-equalization of the battery pack, thereby affecting the life and safety of the battery.

[0056] In view of this, the embodiments of the present application propose a battery cell voltage determination method, a battery management system, and an energy storage system for improving the accuracy of battery cell voltage detection. When performing voltage detection on a battery cell, the embodiments of the present application share the same sampling line for adjacent voltage sampling circuits, and when determining the voltage of a battery cell, fully consider the line resistance of the battery cell to be tested and the line resistance of the voltage sampling circuit adjacent to the battery cell to be tested, as well as the influence of the equalization voltage of the battery cell to be tested and the equalization voltage of the battery cell adjacent to the battery cell to be tested on the actual voltage value of the battery cell to be tested, and determine the actual voltage value of the battery cell to be tested by the recursive least squares method. In the process of determining the actual voltage of the battery cell to be tested, the line resistance value of the voltage sampling circuit corresponding to the battery cell to be tested, the line resistance value of the voltage sampling circuit corresponding to the battery cell to be tested, and the measured voltage value of the battery cell to be tested are used as the linear regression coefficient and covariance matrix of the linear regression model, and the balanced voltage of the battery cell to be tested and the balanced voltage of the battery cell adjacent to the battery cell to be tested are used as the balanced current matrix to generate a predicted value, and then the predicted value and the actual value are compared according to the average actual output value obtained at the current moment, and the linear regression coefficient and the covariance matrix are updated according to the comparison result and the error gain, so as to determine the actual voltage value of the battery cell to be tested according to the updated linear regression coefficient. Due to the step-by-step recursive update characteristics of the recursive least squares method, the linear regression model regression coefficient is adjusted according to the current battery data (such as the measured voltage value of the battery cell to be tested) and the compensation result (such as the balanced current or voltage) in each iteration. With the continuous update of the regression coefficient, the linear regression model can continuously correct the previous error and avoid long-term deviation caused by the initial error. This enables more accurate voltage compensation during cell balancing, reducing errors caused by cell parameter variations or measurement noise.

[0057] like Figure 1 As shown in FIG. 1 , it is a schematic diagram of the structure of the battery management system proposed in the embodiment of the present application. The battery cell voltage determination method proposed in the embodiment of the present application can be executed by the battery management system. Figure 1 As shown, the battery pack includes N battery cells, and the N battery cells are connected in series. Figure 1 As shown, batn-1, batn and batn+1 are three adjacent battery cells, and Vbatn-1, Vbatn and Vbatn+1 represent the voltage values ​​of the battery cells respectively.

[0058] The battery management system is used to manage the battery pack and each battery cell in the battery pack and measure the voltage. The battery management system includes multiple voltage sampling circuits, each voltage sampling circuit corresponds to each battery cell, and the two ends of the voltage sampling circuit are respectively connected to the positive and negative electrodes of a battery cell, so as to measure the voltage of the battery cell.

[0059] Each voltage sampling circuit includes a balancing switch, a balancing resistor and a voltmeter. The balancing switch is connected in series with the balancing resistor and then connected in parallel with the voltmeter to form a parallel circuit. Each voltage sampling circuit is connected to both ends of each battery cell to sample the voltage of each battery cell, that is, the parallel circuit is connected to the positive and negative electrodes of the battery cell. Adjacent voltage sampling circuits share a sampling line. Figure 1 As shown, corresponding to the battery cell batn, the corresponding voltage sampling circuit includes a balancing switch Swn, a balancing resistor Rp and a voltmeter, wherein the balancing switch, balancing resistor and voltmeter of each voltage sampling circuit are the same, for example, the balancing resistors have the same resistance Rp. For adjacent voltage sampling circuits, they share a sampling line, such as Figure 1 In the example, the voltage sampling circuit corresponding to the battery cell batn+1 and the voltage sampling circuit corresponding to the battery cell batn share a sampling line with a line resistance of Rsn; the voltage sampling circuit corresponding to the battery cell batn and the voltage sampling circuit corresponding to the battery cell batn-1 share a sampling line with a line resistance of Rsn-1. Figure 1 It can be seen that, except for the first battery cell bat1 and the last battery cell batN, the sampling lines of other battery cells are shared with the adjacent battery cells.

[0060] During the operation of the battery pack and battery management system, when determining the actual voltage of the battery cell, it is necessary to obtain multiple circuit parameters in advance, such as: for each voltage sampling circuit, its line resistance is a determined, balanced resistor The voltage value of the battery cell to be tested can be obtained in real time through the voltmeter. When the measured voltage value and the equalizing voltage value are determined, the equalizing current value In flowing through the equalizing resistor can be determined.

[0061] Continue to refer Figure 1 The present application embodiment is described by taking the actual voltage value of the battery cell batn as an example. The battery cells batn-1 and batn+1 are adjacent battery cells to the battery cell batn. When the balancing switches Swn-1, Swn and Swn+1 are all closed, the first line resistance value corresponding to the battery cell batn-1 is The second line resistance of the battery cell batn is The third line resistance corresponding to the battery cell batn+1 is , these line resistance values ​​can be determined according to the characteristics of the sampling line. At the same time, the first equalization voltage corresponding to the battery cell batn-1 can also be obtained through the voltmeter , the second equalization voltage corresponding to the battery cell batn , the third equalization voltage corresponding to the battery cell batn+1 .

[0062] After determining the above-mentioned balanced voltage value and line resistance value, due to the existence of the line resistance and balanced current of the sampling line, the second balanced voltage value obtained by measurement is directly used. As the actual voltage value of the battery cell batn will have a large error, in view of this, an embodiment of the present application proposes a battery cell voltage determination method, which runs in the above-mentioned battery management system to more accurately determine the actual voltage value of the battery cell.

[0063] like Figure 2 FIG. 1 is a flow chart of a method for determining a battery cell voltage according to an embodiment of the present application, including:

[0064] S1: Obtain the first line resistance value of the voltage sampling circuit corresponding to the battery cell to be tested , Second line resistance and balancing resistor value .

[0065] Depend on Figure 1 It can be seen that the battery cells adjacent to the battery cell batn are batn-1 and batn+1, and the first line resistance is is the line resistance value of a sampling line shared by the voltage sampling circuit corresponding to the battery cell batn-1 and the voltage sampling circuit corresponding to batn; the second line resistance value is the line resistance value of a sampling line shared by the voltage sampling circuit corresponding to the battery cell batn and the voltage sampling circuit corresponding to batn+1. , Second line resistance and balancing resistor value All of these can be predetermined by the battery management system.

[0066] S2: Obtaining the first balanced voltage , the second balanced voltage , the third balance voltage , wherein the first equalization voltage The voltage value sampled by the voltmeter of the first voltage sampling circuit corresponding to the first battery cell adjacent to the battery cell to be tested when the balancing switch is closed is the voltage value sampled by the second balancing voltage sampling circuit corresponding to the first battery cell adjacent to the battery cell to be tested. is a voltage meter of a voltage sampling circuit corresponding to the battery cell to be tested, and the voltage value sampled when the balancing switch is closed, the third balancing voltage The voltage value obtained by sampling when the balancing switch is closed is a voltage meter of a third voltage sampling circuit corresponding to a third battery cell adjacent to the battery cell to be tested.

[0067] When the battery management system samples the voltage of a battery cell, the following situations often occur:

[0068] 1. When the balancing switch of the battery cell batn is closed, and the balancing switches of the adjacent battery cells batn-1 and batn+1 are opened:

[0069] = =0;

[0070] = / ;

[0071] ;

[0072] ;

[0073] ;

[0074] Combining the above formulas, we can know that:

[0075] ;

[0076] ;

[0077] ;

[0078] It can be seen from the above formula that when there are adjacent battery cells with balancing switches closed, their own balancing currents will affect the actual voltages of the adjacent battery cells. When determining the actual voltage of a battery cell, the influence of the adjacent battery cells needs to be considered.

[0079] 2. When the balancing switches of battery cells batn-1, batn and batn+1 are all closed:

[0080] ;

[0081] ;

[0082] ;

[0083] ;

[0084] ;

[0085] ;

[0086] It can be seen from the above formula that when there are adjacent battery cells with balancing switches closed, their own balancing currents will affect the actual voltages of the adjacent battery cells. When determining the actual voltage of a battery cell, the influence of the adjacent battery cells needs to be considered.

[0087] Combining the above two situations, we can conclude that:

[0088] ;

[0089] Therefore, when determining the voltage of a battery cell by the battery cell voltage determination method proposed in the embodiment of the present application, in addition to considering the equalization voltage of the battery cell to be measured, it is also necessary to obtain the equalization voltage of the battery cells adjacent to it.

[0090] S3: According to the first line resistance , the first balanced voltage , Second line resistance , the second balanced voltage , the third balance voltage and balancing resistor value Determine a linear regression model, wherein the first line resistance , Second line resistance and the measured voltage value of the battery cell to be tested The linear regression coefficient matrix that constitutes the linear regression model ;

[0091] Recursive Least Squares (RLS) is an adaptive filtering algorithm that is based on the principle of least squares and recursively updates the filter coefficients to minimize the mean square error of the prediction error to optimize the filtering effect. The RLS algorithm uses existing observation data to estimate the required filter coefficients, and its core goal is to minimize the mean square error of the prediction error. The recursive least squares method not only relies on the current input samples and errors, but also takes into account the entire historical data, so that the filter coefficients can be adjusted more quickly and accurately. In the embodiment of the present application, the principle of recursive least squares is used to classify and summarize the above equations as a linear regression problem, that is, .

[0092] According to the above formula , we can get:

[0093] ;

[0094] The above equations can be summarized as linear regression problems, forming the following linear regression model:

[0095] ;

[0096] in, , , , , .

[0097] That is, the above formula Perform recursive least squares operation, the linear regression coefficient matrix of the linear regression model is = = .

[0098] S4: Initialize the linear regression coefficient matrix and the covariance matrix , wherein the measured voltage value of the battery cell to be tested is The initial value of is the voltage value sampled by the voltmeter when the equalizing switch of the voltage sampling circuit corresponding to the battery cell to be tested and the equalizing switch of the voltage sampling circuit corresponding to the battery cell adjacent to the battery cell to be tested are both turned on;

[0099] Initialize the linear regression coefficient matrix = , and According to the line resistance initially detected by the system, that is: and , Detection voltage before equalization starts , The initial value of is the voltage value sampled by the voltmeter when the balancing switch of the voltage sampling circuit corresponding to the battery cell to be tested and the balancing switch of the voltage sampling circuit corresponding to the battery cell adjacent to the battery cell to be tested are both turned on, that is, .

[0100] The covariance matrix After being initialized, , M is the preset initialization factor, which can take a larger value such as 1000, which represents the uncertainty of the regression results; is the identity matrix, .

[0101] S5: According to the first equalization voltage , the second balanced voltage and the third balancing voltage Determine the balanced current matrix ;

[0102] in, ,because , ,therefore, ;

[0103] is the balanced voltage value sampled by the voltage meter of the voltage detection circuit corresponding to the battery cell batn+1 at time t; is the balanced voltage value sampled by the voltmeter of the voltage detection circuit corresponding to the battery cell batn at time t; It is the balanced voltage value sampled by the voltmeter of the voltage detection circuit corresponding to the battery cell batn+1 at time t.

[0104] S6: According to the balanced current value matrix and the linear regression coefficient matrix Determine the predicted values ​​of the linear regression model ;

[0105] The predicted value of the linear regression model is determined according to the following formula :

[0106] ;

[0107] in ; , is the regression coefficient at time t-1;

[0108] Thus we get:

[0109] ;

[0110] is the voltage value corresponding to the battery cell to be tested at time t, which is predicted based on the parameter value at time t-1.

[0111] S7: According to the covariance matrix and the balanced current value matrix Determining the Error Gain ;

[0112] The error gain is determined by the following formula :

[0113] ;

[0114] Among them, the is the covariance matrix at time t-1.

[0115] S8: Obtain the first balanced voltage at the current moment , the second balanced voltage , the third balance voltage and the actual output value of the linear regression model ;

[0116] The current equalization voltage value is obtained through the voltage meter of the voltage sampling circuit of the battery cell to be tested and the battery cell adjacent to it, including the first equalization voltage , the second balanced voltage , the third balance voltage and the actual output value of the linear regression model , where the actual output value of the linear regression model is The balanced voltage is obtained by collecting the voltage meter of the voltage sampling circuit corresponding to the battery cell to be tested. .

[0117] S9: Based on the first balanced voltage at the current moment , the second balanced voltage , the third balance voltage , the predicted value of the linear regression model , the actual output value of the linear regression model , the error gain and the linear regression coefficient matrix , update the linear regression coefficient matrix at the current moment and the covariance matrix ;

[0118] Among them, the actual output value of the linear regression model for The actual output value is the current balanced voltage value obtained by collecting the voltage meter of the voltage sampling circuit corresponding to the battery cell to be tested.

[0119] Update the linear regression coefficient matrix at the current moment according to the following formula :

[0120] ;

[0121] in, is the linear regression coefficient matrix at time t-1, is the error gain.

[0122] The updated linear regression parameter matrix is

[0123] = .

[0124] At the same time, the covariance matrix at the current moment is updated according to the following formula :

[0125] ;

[0126] in For the forgetting factor.

[0127] S10: According to the linear regression coefficient matrix at the current moment Determine the actual voltage value of the battery cell to be tested ;

[0128] The updated linear regression parameter matrix = Converted to the actual target value, ; ; , That is the actual voltage value of the battery cell to be tested.

[0129] S11: Jump to step S5 until the battery cell to be tested and the balancing switch of the voltage sampling circuit adjacent to the battery cell to be tested are turned on.

[0130] In the above-mentioned cycle process of step S5 to step S10, the equalization voltage corresponding to the battery cell to be tested is periodically collected, and the actual voltage value of the battery cell to be tested can be continuously determined according to the latest obtained equalization voltage. Since the actual voltage value of the battery cell to be tested needs to be continuously obtained during the battery pack equalization process, the cycle process can be executed until the equalization switch of the battery cell to be tested and the voltage sampling circuit adjacent to the battery cell to be tested is turned on.

[0131] When the balancing switch of the battery cell to be tested and the voltage sampling circuit adjacent to the battery cell to be tested is turned on, the current flowing through the sampling line is 0. , can be obtained by direct measurement.

[0132] The actual voltage value determined by the battery cell voltage determination method disclosed in the above embodiment is verified by taking the following Table 1 as an example.

[0133] Table 1

[0134]

[0135] Table 1 includes exemplary input values, including x1, x2, and y values, which are input into the linear regression model:

[0136] ;

[0137] For the linear regression model, the default initialization factor N is 1000 and the forgetting factor is After iterating the input data in Table 1 through the above linear regression model, the output is Figure 3 The iterative results are shown in . Figure 3It can be seen that after iterative calculation, the balanced voltage value =y=3.281, predicted value =3.2812218175132735, parameter value c=3.3011483824149517, which is the actual voltage value of the battery cell to be tested =3.3011. This actual voltage value fully considers the influence of the sampling line resistance, the balancing resistance and the adjacent sampling circuit. Compared with the balancing voltage value obtained by direct measurement, it has higher accuracy.

[0138] In summary, the battery cell voltage determination method proposed in the embodiment of the present application makes full use of the characteristic of the recursive least squares method of gradual recursive update. In each iteration, the linear regression model regression coefficient is adjusted according to the current battery data (such as the measured voltage value of the battery cell to be measured) and the compensation result (such as the balancing current or voltage). As the regression coefficient is continuously updated, the linear regression model can continuously correct previous errors and avoid long-term deviations caused by initial errors. This enables more accurate voltage compensation to be obtained during the battery balancing process, reducing errors caused by changes in battery parameters or measurement noise. The battery cell voltage measurement value is compensated by calculating the sampling line resistance and the balancing resistance, and the measurement error problem caused by voltage fluctuations during the balancing process is solved by a software algorithm, thereby achieving high-precision battery voltage measurement.

[0139] The present application also proposes an energy storage system, including a battery pack and the battery management system described in the above embodiment; the battery pack includes a plurality of battery cells, each of which is connected in series; the battery management system is used to manage the battery pack. The relevant implementation methods of the battery management system are described in detail in the above embodiment and will not be repeated here.

[0140] The embodiment of the present application also provides a computer-readable storage medium, wherein at least one executable instruction is stored in the storage medium, and when the executable instruction is executed on the battery management system, the battery management system executes the operation of any one of the above-mentioned methods for determining the battery cell voltage. The relevant implementations of the method for determining the battery cell voltage are described in detail in the above-mentioned embodiments, and will not be repeated here.

[0141] The algorithm or display provided here are not inherently related to any specific computer, virtual system or other equipment. Various general systems can also be used together with the teaching based on this. According to the above description, it is obvious to construct the structure required for this type of system. In addition, the present application embodiment is not directed to any specific programming language yet. It should be understood that various programming languages ​​can be utilized to realize the content of the present application described here, and the above description of specific languages ​​is to disclose the best mode of implementation of the present application.

[0142] In the description provided herein, a large number of specific details are described. However, it is understood that the embodiments of the present application can be practiced without these specific details. In some instances, well-known methods, structures and techniques are not shown in detail so as not to obscure the understanding of this description.

[0143] Similarly, it should be understood that in order to streamline the present application and help understand one or more of the various aspects of the invention, in the above description of exemplary embodiments of the present application, the various features of the embodiments of the present application are sometimes grouped together into a single embodiment, figure, or description thereof.

[0144] Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and may be divided into a plurality of submodules or subunits or subcomponents. Except that at least some of such features and / or processes or units are mutually exclusive, all features disclosed in this specification (including the accompanying abstract and drawings) and all processes or units of any method or device disclosed in this manner may be combined in any combination. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying abstract and drawings) may be replaced by an alternative feature providing the same, equivalent or similar purpose.

[0145] It should be noted that the above embodiments illustrate the present application rather than limit the present application, and those skilled in the art may design alternative embodiments without departing from the scope. The steps in the above embodiments, unless otherwise specified, should not be understood as limiting the execution order.

Claims

1. A method for determining battery cell voltage, characterized in that: The method is applied to a battery management system, which is used to manage multiple battery cells connected in series; the battery management system includes multiple voltage sampling circuits, the voltage sampling circuit includes a balancing switch, a balancing resistor and a voltmeter, the balancing switch is connected in series with the balancing resistor and then connected in parallel with the voltmeter; each of the voltage sampling circuits is respectively connected to two ends of each of the battery cells, and is used to sample the voltage of each of the battery cells, and adjacent voltage sampling circuits share a sampling line; The method comprises: S1: Obtain the first line resistance value of the voltage sampling circuit corresponding to the battery cell to be tested , Second line resistance and balancing resistor value ; S2: Obtaining the first balanced voltage , the second balanced voltage , the third balance voltage , wherein the first equalization voltage The voltage value sampled by the voltmeter of the first voltage sampling circuit corresponding to the first battery cell adjacent to the battery cell to be tested when the balancing switch is closed is the voltage value sampled by the second balancing voltage sampling circuit corresponding to the first battery cell adjacent to the battery cell to be tested. is a voltage meter of a voltage sampling circuit corresponding to the battery cell to be tested, and the voltage value sampled when the balancing switch is closed, the third balancing voltage A voltage value sampled by a voltmeter of a third voltage sampling circuit corresponding to a third battery cell adjacent to the battery cell to be tested when the balancing switch is closed; S3: According to the first line resistance , the first balanced voltage , Second line resistance , the second balanced voltage , the third balance voltage and balancing resistor value Determine a linear regression model, wherein the first line resistance , Second line resistance and the measured voltage value of the battery cell to be tested The linear regression coefficient matrix that constitutes the linear regression model ; S4: Initialize the linear regression coefficient matrix and the covariance matrix , wherein the measured voltage value of the battery cell to be tested is The initial value of is the voltage value sampled by the voltmeter when the equalizing switch of the voltage sampling circuit corresponding to the battery cell to be tested and the equalizing switch of the voltage sampling circuit corresponding to the battery cell adjacent to the battery cell to be tested are both turned on; S5: According to the first equalization voltage , the second balanced voltage and the third balancing voltage Determine the balanced current matrix ; S6: According to the balanced current value matrix and the linear regression coefficient matrix Determine the predicted values ​​of the linear regression model ; S7: According to the covariance matrix and the balanced current value matrix Determining the Error Gain ; S8: Obtain the first balanced voltage at the current moment , the second balanced voltage , the third balance voltage and the actual output value of the linear regression model ; S9: Based on the first balanced voltage at the current moment , the second balanced voltage , the third balance voltage , the predicted value of the linear regression model , the actual output value of the linear regression model , the error gain and the linear regression coefficient matrix , update the linear regression coefficient matrix at the current moment and the covariance matrix ; S10: According to the linear regression coefficient matrix at the current moment Determine the actual voltage value of the battery cell to be tested ; S11: Jump to step S5 until the equalization switch of the voltage sampling circuit adjacent to the battery cell to be tested is turned on.

2. The method for determining battery cell voltage according to claim 1, characterized in that: According to the first line resistance , the first balanced voltage , Second line resistance , the second balanced voltage , the third balance voltage and balancing resistor value Determine the linear regression model, including: The linear regression model is: ; in, , , , ; ; .

3. The method for determining battery cell voltage according to claim 1, characterized in that: The covariance matrix after initialization , where M is the preset initialization factor, is the identity matrix.

4. The method for determining battery cell voltage according to claim 3, characterized in that: The balanced current value matrix and the linear regression coefficient matrix Determine the predicted values ​​of the linear regression model ,include: The predicted value of the linear regression model is determined by the following formula: ； in ; , is the regression coefficient matrix at time t-1; is the regression coefficient at time t-1; 。 5. The method for determining battery cell voltage according to claim 4, characterized in that: The covariance matrix and the balanced current value matrix Determining the Error Gain ,include: The error gain is determined by the following formula : ； Among them, the is the covariance matrix at time t-1, For the forgetting factor.

6. The method for determining battery cell voltage according to claim 5, characterized in that: The predicted value according to the linear regression model , the actual output value of the linear regression model , the error gain and the linear regression coefficient matrix , update the linear regression coefficient matrix at the current moment ,include: Update the linear regression coefficient matrix at the current moment according to the following formula : ； in, is the linear regression coefficient matrix at time t-1.

7. The method for determining battery cell voltage according to claim 5, characterized in that: The predicted value according to the linear regression model , the actual output value of the linear regression model , the error gain and the linear regression coefficient matrix , update the covariance matrix at the current moment ,include: Update the covariance matrix at the current moment according to the following formula : 。 8. A battery management system, characterized in that: Used to measure the voltage of battery cells in the battery pack; The battery management system includes a controller and a plurality of voltage sampling circuits; The voltage sampling circuit comprises a balancing switch, a balancing resistor and a voltmeter; the balancing switch is connected in series with the balancing resistor and then connected in parallel with the voltmeter to form a voltage sampling circuit; Each of the voltage sampling circuits is connected to two ends of each of the battery cells respectively, and is used to sample the voltage of each of the battery cells, and adjacent voltage sampling circuits share a sampling line; The controller is connected to each of the voltmeters and is used to execute the battery cell voltage determination method as described in any one of claims 1-7.

9. An energy storage system, characterized in that: comprising a battery pack and a battery management system as claimed in claim 8; The battery pack includes a plurality of battery cells, each of which is connected in series with each other; The battery management system is used to manage the battery pack.

10. A computer-readable storage medium, characterized in that: The storage medium stores at least one executable instruction. When the executable instruction is executed on the battery management system, the battery management system executes the operation of the battery cell voltage determination method according to any one of claims 1 to 7.

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