Battery health state determination method and device, battery management system and storage medium

Abstract

The embodiment of the invention provides a battery health state determination method and device, a battery management system and a storage medium, and relates to the field of battery health state calculation. Obtaining the current charging and discharging times of the to-be-tested battery pack; based on the current charging and discharging times and a pre-stored fitting model, determining the charging and discharging platform duration of the to-be-tested battery pack under the current charging and discharging times; wherein the fitting model represents a mapping relation between the number of times of charging and discharging and the duration of the charging and discharging platform; and determining the battery health state of the to-be-tested battery pack according to the ratio of the charging and discharging platform duration of the to-be-tested battery pack under the current charging and discharging times to the initial charging and discharging platform duration. Therefore, the battery health state of the to-be-tested battery pack can be determined by focusing on the key voltage platform area which is most sensitive to the change of the battery health state, so that the evaluation accuracy of the battery health state can be improved.

Description

Technical Field

[0001] The present application relates to the field of battery health status calculation, and specifically to a battery health status determination method, device, battery management system and storage medium. Background Art

[0002] With the continuous growth of energy demand and the rapid development of renewable energy, energy storage batteries, as an important energy storage technology, have been widely used in electric vehicles, renewable energy systems, and grid energy storage. However, energy storage batteries still face some limitations. Specifically, batteries will degrade with the passage of charge and discharge cycles and time. Therefore, it is necessary to accurately assess the battery's state of health (SOH) to ensure the safe, efficient, and reliable operation of the battery system.

[0003] Currently, when evaluating the health status of batteries in related technologies, there is often a problem of low evaluation accuracy. Summary of the Invention

[0004] In view of this, the purpose of this application is to provide a battery health status determination method, device, battery management system and storage medium to improve the accuracy of battery health status assessment.

[0005] In order to achieve the above objectives, the technical solutions adopted in the embodiments of the present application are as follows: In a first aspect, the present application provides a method for determining a battery health status, the method comprising: Get the current charge and discharge times of the battery pack under test; Determine the charge and discharge platform duration of the battery pack under test under the current charge and discharge times based on the current charge and discharge times and a pre-stored fitting model; wherein the fitting model represents a mapping relationship between the charge and discharge times and the charge and discharge platform duration; The battery health status mapping relationship of the battery pack to be tested is determined according to the ratio of the charge and discharge platform time length under the current charge and discharge times of the battery pack to be tested to the initial charge and discharge platform time length.

[0006] In an optional embodiment, the battery pack to be tested includes a plurality of battery cells to be tested; the fitting model includes an overall fitting model of the battery pack to be tested and / or an independent fitting model of each battery cell to be tested; The step of determining the charge and discharge platform duration of the battery pack under test under the current charge and discharge times based on the current charge and discharge times and a pre-stored fitting model includes: Determining a charge and discharge platform duration of the entire battery pack based on the current charge and discharge times and the overall fitting model of the battery pack, and / or determining a charge and discharge platform duration of each battery cell to be tested based on the current charge and discharge times and each of the independent fitting models; The step of determining the battery health status of the battery pack to be tested based on the ratio of the charge and discharge platform duration of the battery pack to be tested under the current charge and discharge times to the initial charge and discharge platform duration includes: The overall health status of the battery pack is determined based on the overall charge and discharge platform time and the initial charge and discharge platform time of the battery pack to be tested, and / or the health status of each battery cell to be tested is determined based on the charge and discharge platform time of each battery cell to be tested.

[0007] In an optional embodiment, the fitting model is obtained by the following steps: Performing multiple full charge and discharge operations on the battery pack to be tested, and collecting voltage sequences corresponding to each charge and discharge operation; extracting a charge and discharge platform duration from the voltage sequence based on a preset state of charge range; A mapping relationship between the number of charge and discharge times and the duration of the charge and discharge platform is fitted, and the mapping relationship is iteratively optimized to generate the fitting model.

[0008] In an optional embodiment, the fitting model includes at least one of an exponential model, a polynomial model, and a power function model.

[0009] In an optional embodiment, the method further comprises: The exponential model is obtained by dynamically fitting a preset number of exponential terms and a numerical stabilization function; The polynomial model is obtained by fitting the polynomial model based on the least square method by presetting the polynomial degree; The power function model is obtained by fitting a preset number of power function terms. In an optional embodiment, the step of determining the charge and discharge plateau duration of the battery pack under test under the current charge and discharge times based on the current charge and discharge times and a pre-stored fitting model includes: When there are multiple fitting models, calculating the evaluation parameters of each fitting model; screening a target fitting model based on the evaluation parameters; The charge and discharge platform duration is determined based on the current charge and discharge times and the target fitting model.

[0010] In an optional embodiment, the evaluation parameters include Akaike's information criterion and a coefficient of determination.

[0011] In a second aspect, the present application provides a battery health status determination device integrated into a battery pack, the device comprising: processor and memory; The memory is used to store computer programs; The method according to any one of the aforementioned implementations is performed when the processor is configured to execute the computer program.

[0012] In a third aspect, the present application provides a battery management system integrated into a battery pack, comprising: Voltage monitoring module, used to monitor the battery pack voltage in real time; Compute module, which performs the following operations: Get the current charge and discharge times of the battery pack; Determining a charge and discharge plateau duration based on the current charge and discharge times and a pre-stored fitting model; The battery health state is determined based on the ratio of the charge and discharge plateau duration to the initial charge and discharge plateau duration.

[0013] In a fourth aspect, the present application provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in any one of the aforementioned embodiments.

[0014] The battery health status determination method, device, battery management system, and storage medium provided in the embodiments of the present application can determine the charge and discharge plateau duration under the current charge and discharge times of the battery pack under test based on the current charge and discharge times of the battery pack under test and a pre-stored fitting model, thereby determining the battery health status of the battery pack under test based on the charge and discharge plateau duration and the initial charge and discharge duration. In this way, the battery health status of the battery pack under test can be determined by focusing on the key voltage platform area where the battery health status changes most sensitively, thereby improving the accuracy of battery health status assessment.

[0015] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 A block diagram of a device for determining a battery health status provided by an embodiment of the present application is shown; Figure 2 A schematic diagram showing a flow chart of a method for determining a battery health status provided in an embodiment of the present application is shown; Figure 3Another flowchart of the method for determining the battery health status provided in an embodiment of the present application is shown; Figure 4 A block diagram of a battery management system provided in an embodiment of the present application is shown.

[0018] Icon: 100 - memory; 110 - processor; 200 - voltage monitoring module; 210 - computing module. DETAILED DESCRIPTION

[0019] The following will be combined with the accompanying drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Generally, the components of the embodiments of the present application described and shown in the drawings herein can be arranged and designed in various different configurations.

[0020] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application for protection, but merely represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present application.

[0021] It should be noted that relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0022] With the continuous growth of energy demand and the rapid development of renewable energy, energy storage technology has gradually become a key area to solve the instability of energy storage and supply. As an important energy storage technology, energy storage batteries have been widely used in electric vehicles, renewable energy systems and grid energy storage due to their advantages such as high energy density, long life and environmental friendliness.

[0023] Although battery technology has been widely used and plays a key role in modern society, it still faces some significant drawbacks, mainly related to the degradation of batteries over time as charge and discharge cycles proceed. Therefore, it is necessary to accurately assess the battery SOH to ensure the safe, efficient and reliable operation of the battery system, so that users can promptly notice whether the battery needs to be replaced to avoid unexpected capacity degradation. In addition, battery health assessment is crucial to expanding the recycling industry, allowing manufacturers to decide whether to recycle batteries as scrap metal or use them for less challenging secondary uses.

[0024] Currently, related technologies often use two approaches to assess battery health status: model-driven and data-driven. The model-driven approach involves building a battery reaction model to simulate the battery and estimate the battery health status. The data-driven approach uses big data to analyze data from the battery's operating process to estimate the battery health status.

[0025] However, both approaches have certain limitations. The model-driven approach often relies on complex physical models because it requires modeling the battery to simulate the battery status. The accuracy of the modeling often affects the accuracy of the battery health status. The data-driven approach requires a large amount of data during the battery operation process. Its accuracy depends on the data quality and data volume, and has high requirements for data.

[0026] Obviously, current methods for evaluating battery health status often have problems such as complexity and poor accuracy. Based on this, embodiments of the present application provide a battery health status determination method, device, battery management system, and storage medium to solve the above problems.

[0027] First, an embodiment of the present application provides a battery health status determination device, which is integrated into a battery pack. In this embodiment, the battery health status determination device can be a battery management chip.

[0028] Specifically, Figure 1 A block diagram of a device for determining the battery health status provided in an embodiment of the present application is shown in FIG. Figure 1The electronic device includes a memory 100 and a processor 110. The components of the memory 100 and the processor 110 are electrically connected to each other directly or indirectly to achieve data transmission or interaction. For example, these components can be electrically connected to each other via one or more communication buses or signal lines. The memory 100 is used to store computer programs. The memory 100 can be, but is not limited to, a random access memory (RAM), a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), etc.

[0029] The processor 110 is used to read / write data or computer programs stored in the memory and execute the computer program to implement the battery health status determination method provided in the embodiment of the present application.

[0030] Optionally, the battery health state determination device may further include a communication module, and the communication module may be used to establish a communication connection between the battery health state determination device and other communication terminals through a network, and to send and receive data through the network.

[0031] It should be understood that Figure 1 The structure shown is only a schematic diagram of the structure of the battery health status determination device. The battery health status determination device may also include a comparison Figure 1 More or fewer components than shown, or with Figure 1 Different configurations shown. Figure 1 Each component shown in the figure can be implemented by hardware, software or a combination thereof.

[0032] Next, the above Figure 1 The battery health status determination device in the embodiment is the execution body, and the battery health status determination method provided in the embodiment of the present application is exemplarily introduced in combination with the flow chart.

[0033] Specifically, Figure 2 A flow chart of a method for determining the battery health status provided in an embodiment of the present application is provided in Figure 2 , the method comprising: Step S20: obtaining the current charge and discharge times of the battery pack to be tested.

[0034] Optionally, the battery pack to be tested may be fully charged and discharged first, and when any cell to be tested is fully charged or fully discharged, the current charge and discharge times of the battery pack to be tested may be obtained.

[0035] Optionally, full charging refers to charging the battery cell to a preset full-charge voltage, and full discharging refers to discharging the battery cell to a preset full-discharge voltage, and the full-charge voltage and full-discharge voltage are determined according to the actual conditions of the battery cell.

[0036] In this embodiment, full charge and full discharge refer to constant power charge and discharge.

[0037] Optionally, the current charge and discharge count refers to the number of full charge and discharge cycles of the battery pack under test. It is understood that for the battery pack under test, full charge and discharge cycles exist, so one full charge and discharge cycle counts as one complete charge and discharge cycle. For example, if the battery pack under test is currently fully charged, and the battery pack under test has previously experienced 10 full charge and discharge cycles, the current charge and discharge count should be the 11th.

[0038] In one possible implementation, the battery pack to be tested may be any type of battery having clear voltage platform characteristics during the charge and discharge process, such as a lithium iron phosphate battery.

[0039] Step S21 : determining the charge and discharge platform duration of the battery pack to be tested under the current charge and discharge times based on the current charge and discharge times and a pre-stored fitting model.

[0040] Among them, the fitting model represents the mapping relationship between the number of charge and discharge times and the duration of the charge and discharge platform.

[0041] Optionally, the charge and discharge platform refers to a region where the voltage of the battery remains relatively stable during constant power charge and discharge.

[0042] Step S22 , determining the battery health status of the battery pack to be tested based on the ratio of the charge and discharge platform duration under the current charge and discharge times to the initial charge and discharge platform duration of the battery pack to be tested.

[0043] Optionally, the initial charge and discharge platform duration refers to the platform duration when the battery pack to be tested is fully charged or fully discharged for the first time.

[0044] In this embodiment, the battery health status can be the quotient of the charge and discharge platform time under the current charge and discharge times and the initial charge and discharge platform time, which can be represented by the following formula: SOH=Δt(n) / Δt(0), where Δt(n) represents the charge and discharge platform time under the current charge and discharge times, and Δt(0) represents the initial charge and discharge platform time.

[0045] It is understandable that since the health of the battery is closely related to its internal chemical reactions, as the battery ages, its internal active materials will gradually degrade, resulting in changes in the characteristics of the voltage platform. That is, the battery performance of a new battery is better and the chemical reaction is more stable, so the platform time is longer, while the battery performance of an old battery decreases and the chemical reaction weakens, so the platform time will be shorter. Based on this, the battery health status can be accurately evaluated by the changes in the battery's charge and discharge platform time.

[0046] The battery health status determination method, device, battery management system, and storage medium provided in the embodiments of the present application can determine the charge and discharge plateau duration under the current charge and discharge times of the battery pack under test based on the current charge and discharge times of the battery pack under test and a pre-stored fitting model, thereby determining the battery health status of the battery pack under test based on the charge and discharge plateau duration and the initial charge and discharge duration. In this way, the battery health status of the battery pack under test can be determined by focusing on the key voltage platform area where the battery health status changes most sensitively, thereby improving the accuracy of battery health status assessment.

[0047] In addition, this method only requires fitting a fitting model that can characterize the mapping relationship between the number of charge and discharge times and the charge and discharge platform time. In actual application, the battery health status can be calculated through the fitting model, the current number of charge and discharge times, and the initial charge and discharge platform time. Therefore, it can also improve the assessment accuracy of the battery health status while simplifying the assessment method of the battery health status.

[0048] Considering that in actual applications, the battery pack to be tested often contains multiple cells to be tested, and these cells to be tested are combined in series or parallel to meet specific voltage and capacity requirements. However, in related technologies, whether model-driven or data-driven, the battery pack to be tested is usually treated as a whole, and the battery health status is evaluated based on parameters such as the voltage, current, and temperature of the entire battery pack to be tested. Although this evaluation method can provide the overall health status of the battery pack to be tested, it cannot effectively distinguish the specific health status of each cell to be tested within it.

[0049] For example, suppose a battery pack under test consists of 10 test cells connected in series. During discharge, the overall voltage of the battery pack is the sum of the voltages of these 10 test cells. If the performance of a test cell degrades due to aging or failure, this degradation may only manifest as a slight change in the overall voltage, making it difficult to accurately identify the specific cell with the problem from the overall data. Similarly, when connected in parallel, the currents of multiple cells will be superimposed on each other, further increasing the difficulty of accurately assessing the SOH of a single cell.

[0050] In order to further overcome the above-mentioned defects, the battery health status determination method provided in the embodiment of the present application can also determine the health status of each battery cell to be tested.

[0051] Specifically, the fitting model may include the overall fitting model of the battery pack to be tested and / or the independent fitting model of each battery cell to be tested. Based on this, it can be understood that the battery health status of the battery pack to be tested may include the battery health status of the overall battery pack to be tested and / or the battery health status of each battery cell to be tested in the battery pack to be tested.

[0052] Specifically, the battery health status determination device can determine the overall charge and discharge platform time of the battery pack based on the current charge and discharge times and the overall fitting model of the battery pack, and / or determine the charge and discharge platform time of each battery cell to be tested based on the current charge and discharge times and each independent fitting model; determine the overall health status of the battery pack according to the overall charge and discharge platform time of the battery pack to be tested and the initial charge and discharge platform time, and / or determine the health status of each battery cell to be tested according to the charge and discharge platform time of each battery cell to be tested.

[0053] It is understandable that since different battery cells to be tested may have certain differences, their corresponding battery cell fitting models and initial charge and discharge times may also have certain differences.

[0054] In this embodiment, the user can determine according to actual needs whether to obtain only the battery health status of the entire battery pack to be tested, or only the battery health status of each battery cell to be tested, or to obtain both the battery health status of the entire battery pack to be tested and the battery health status of each battery cell to be tested.

[0055] In this way, the battery health status of each single cell to be tested can be evaluated, so that the specific aging cell can be directly located to achieve an accurate assessment of the battery health status of the battery pack to be tested.

[0056] Optionally, for ease of application, a fitting model needs to be generated and stored in advance. Next, a possible implementation method for obtaining the fitting model is provided.

[0057] Specifically, in Figure 2 On the basis of Figure 3 For another flow chart of the method for determining the battery health status provided in the embodiment of the present application, please refer to Figure 3 , the method further comprises: Step S10 , performing multiple full charge and discharge operations on the battery pack to be tested, and collecting the voltage sequence corresponding to each charge and discharge operation.

[0058] It can be understood that each charge and discharge corresponds to a voltage sequence, which includes multiple voltage values of the battery pack to be tested during the current charge and discharge process.

[0059] Optionally, the full charge and discharge refers to full charge and full discharge. It should be noted that the full charge and discharge of the battery pack to be tested refers to the full charge and discharge of any of the cells to be tested.

[0060] Optionally, since full charging and full discharging refer to constant power charging and discharging, when any cell in the battery pack to be tested is fully charged or fully discharged, not only the capacity, voltage, energy and other parameters of the battery pack to be tested can be obtained, but also the voltage value of each cell to be tested in the battery pack to be tested can be obtained.

[0061] Optionally, in order to facilitate analysis of the charge and discharge platform duration, multiple voltage values corresponding to the battery pack to be tested may be recorded once every preset duration during the charge and discharge process.

[0062] Optionally, the preset duration can be set according to actual application conditions, for example, 3s.

[0063] Optionally, in order to facilitate generation of a fitting model corresponding to the battery pack to be tested and a fitting model for each battery cell to be tested, multiple voltage values corresponding to the battery pack to be tested and multiple voltage values corresponding to each battery cell to be tested may be recorded simultaneously.

[0064] Optionally, outliers among the multiple voltage values may be eliminated, and missing data may be interpolated to ensure the accuracy and continuity of the data.

[0065] It is understandable that, since the voltage value changes according to a certain rule during the charging and discharging process, if a certain voltage value shows an abnormal value, it can be eliminated. In addition, if a certain voltage value is not collected successfully, the voltage value can also be interpolated according to the change rule.

[0066] Step S11 : extracting the charge and discharge platform duration from the voltage sequence based on a preset state of charge range.

[0067] Optionally, the SOC range is used to select the duration of the charge / discharge plateau. In this embodiment, the larger the SOC range and the longer the charge / discharge plateau duration, the higher the accuracy of the generated fitting model and the higher the accuracy of the battery health calculation.

[0068] Optionally, the battery health status determination device can determine the voltages at both ends of the platform area based on the state of charge range. Since each voltage value corresponds to a timestamp of a charging and discharging process, the timestamps corresponding to the two ends of the platform area can be determined based on the voltages at both ends, thereby determining the duration of the charging and discharging platform.

[0069] In one example, if the state of charge range is 95%~10%, the corresponding voltage value range is 3.29V~3.10V, and the points can be taken accurately to the percentile. The battery health status determination device can calculate the charging and discharging platform time based on the timestamp corresponding to 3.29V and the timestamp corresponding to 3.10V.

[0070] Step S12: fitting a mapping relationship between the number of charge and discharge times and the charge and discharge platform duration, and iteratively optimizing the mapping relationship to generate a fitting model.

[0071] Optionally, the battery health status determination device may use the charge and discharge platform duration as the dependent variable y and the number of charge and discharge times as the independent variable x to perform model fitting.

[0072] In this embodiment, before model fitting is performed, data type standardization processing needs to be performed on the dependent variable and the independent variable, such as normalization, type conversion (floating point number conversion to integer), etc.

[0073] Optionally, iterative optimization refers to performing parameter optimization on model parameters of the model and iteratively training the model.

[0074] In this embodiment, the battery health status determination device can first perform model fitting based on the number of charge and discharge times and the corresponding charge and discharge platform duration, and optimize the model parameters of the fitted model through an optimization algorithm to obtain the initial fitting model corresponding to the battery pack to be tested, and determine whether the model fitting is completed according to the preset fitting iteration conditions.

[0075] Optionally, the fitting iteration condition may include the extreme point convergence of the initial fitting model, the function value convergence, the parameter stability, and the number of fitting times reaching a preset number of fitting times.

[0076] In this embodiment, if the initial fitting model meets any one of the conditions of extreme point convergence, function value convergence, parameter stability, and the number of fitting times reaching a preset number of fitting times, it can be determined whether the initial fitting model meets the fitting iteration condition.

[0077] Optionally, the battery health status determination device may first determine whether the initial fitting model has converged to the extreme point, then determine whether the function value has converged, then determine whether the parameters are stable, and finally determine whether the number of fitting times has reached a preset number of fitting times.

[0078] In one possible implementation, the gradient tolerance can be set according to the preset Determine whether the extreme point converges. That is, if the absolute value of the maximum component of the gradient vector satisfies When , it can be determined that the extreme point converges. Characterizes the component of the gradient in the i-th direction.

[0079] In another possible implementation, the target function tolerance can be set according to the preset target function tolerance. Determine whether the function value converges. That is, when the relative change of the objective function value in two consecutive iterations satisfies When , it can be determined that the function value converges. Characterizes the i-th charge and discharge.

[0080] In another possible implementation, whether the parameters are stable can be determined based on a preset parameter tolerance. That is, when the relative change of the parameter vector satisfies When , it can be determined that the parameters are stable. Characterizes the i-th charge and discharge.

[0081] In this embodiment, the battery health status determination device may repeatedly perform model fitting according to the number of charge and discharge times and the charge and discharge platform duration corresponding to each charge and discharge process when the initial fitting model does not meet the fitting iteration conditions, and optimize the model parameters of the fitted model through the optimization algorithm to obtain the steps of the initial fitting model until the initial fitting model meets the fitting iteration conditions, and when the initial fitting model meets the fitting iteration conditions, determine that the fitting is completed, and determine the initial fitting model as the fitting model.

[0082] Optionally, the optimization algorithm may be a trust-region-reflective algorithm with bounded constraints. In this embodiment, the battery health status determination device may perform model fitting based on the number of charge and discharge cycles and the charge and discharge platform duration corresponding to each charge and discharge process, and optimize the model parameters in the fitted model using the trust-region-reflective algorithm with bounded constraints to obtain an initial fitting model.

[0083] Optionally, model parameters refer to unknown quantities in the model. For example, if the exponential model to be fitted is y=a bx , then the model parameters refer to a and b.

[0084] In this embodiment, the model parameters may include multiple, characterized by and ,in, , , where i represents the i-th parameter, Represents the maximum range of y values ( ), where N represents the number of model items configured by the user.

[0085] In this embodiment, the parameter boundary constraint is characterized as ,in, and are the maximum and minimum durations of the charge and discharge platform, respectively. It is understandable that this boundary constraint not only ensures the numerical rationality of the model parameters, but also effectively avoids the numerical instability that may occur during the model fitting process.

[0086] Optionally, the fitting model may include at least one of an exponential model, a polynomial model, and a power function model.

[0087] In this embodiment, only one of the exponential model, the polynomial model, and the power function model may be fitted, or multiple models may be fitted.

[0088] In this embodiment, the battery health status determination device can obtain the exponential model by dynamically fitting a preset number of exponential terms and a numerical stabilization function.

[0089] Optionally, the number of exponential terms can be set by the user according to actual application conditions and requirements for the exponential model, and the battery health status determination device can dynamically generate a mathematical model with multiple adjustable parameters based on the number of exponential terms.

[0090] In one possible implementation, if the number of exponential terms configured by the user is N, the battery health status determination device may dynamically generate a mathematical model including 2N adjustable parameters, which is represented as follows:

[0091] in, and Characterize the model parameters, Characterize the independent variable, characterizes the numerical stabilization function, and .

[0092] In this embodiment, the battery health status determination device can obtain model parameters according to the mathematical model, and optimize and iteratively process the model parameters to finally obtain the exponential model.

[0093] In this embodiment, the battery health status determination device can obtain the polynomial model based on least squares fitting by presetting the polynomial degree.

[0094] Optionally, the battery health status determination device can be based on the charge and discharge number sequence , the duration of the charge and discharge platform corresponding to the number of charge and discharge times And the preset polynomial degree (1≤degree≤n-1), the coefficient matrix C is fitted based on the principle of least squares method, and then the coefficient inversion operation is used to achieve standardized sorting from low-order terms to high-order terms to obtain the model coefficients, and the model parameters are optimized and iteratively processed to finally obtain the polynomial model.

[0095] In this embodiment, the battery health status determination device can obtain the power function model by fitting a preset number of power function terms.

[0096] Optionally, the number of power function terms can be set by the user according to actual application conditions and requirements for the power function model.

[0097] Optionally, the battery health status determining apparatus may generate a mathematical model based on the number of power function terms N input by the user: , where i represents the i-th parameter, and represents the model parameters, and x represents the independent variable.

[0098] In one possible implementation, if N = 1, then the power function model is a monomial, so log-linear regression can be used. , and obtain the initial model parameters a and b by the least squares method. If the least squares method cannot obtain the values of a and b due to data anomalies, the initial value of a should be set to y max -y min , the initial value of b is set to 1.

[0099] In another possible implementation, if N>1, the coefficients With index Initialized to ; Based on this, the sequence .

[0100] In this embodiment, the battery health status determination device may optimize and iteratively process the obtained model parameters to ultimately obtain a power function model.

[0101] Optionally, when there are multiple fitting models, the battery health status determination device may select the optimal fitting model from the multiple fitting models for use.

[0102] In this embodiment, the battery health status determination device can calculate the evaluation parameters of each fitting model when there are multiple fitting models, screen the target fitting model based on the evaluation parameters, and determine the charging and discharging platform time based on the current charge and discharge times and the target fitting model.

[0103] In one example, if the fitting model corresponding to the battery pack to be tested includes an exponential model, a polynomial model, and a power function model, the evaluation parameters of the exponential model, the polynomial model, and the power function model can be calculated respectively, and based on the evaluation parameters, a target fitting model can be selected from the exponential model, the polynomial model, and the power function model, such as the exponential model, and the charging and discharging platform time can be calculated based on the exponential model.

[0104] In one possible implementation, after generating multiple fitting models, a target fitting model can be directly screened out from them, and the target fitting model can be directly stored. When the battery health status needs to be calculated, the target fitting model can be directly called.

[0105] In another possible implementation method, multiple fitting models can be directly stored. When the battery health status needs to be calculated, a target fitting model is first selected from the multiple fitting models, and the charge and discharge platform time is calculated based on the target fitting model.

[0106] In this embodiment, the evaluation parameters may include the Akaike information criterion and the determination coefficient. The battery health status determination device may calculate the Akaike information criterion and the determination coefficient respectively based on the model parameters of each fitting model, the number of charge and discharge times, and the average value of the duration of multiple charge and discharge platforms.

[0107] Optionally, the number of charge and discharge times and the duration of multiple charge and discharge platform times refer to the number of charge and discharge times and the duration of charge and discharge platform times used when fitting the fitting model.

[0108] In this embodiment, the Akaike information criterion AIC and the determination coefficient corresponding to the fitting model can be calculated by the following formula: :

[0109]

[0110] Among them, n represents the number of charge and discharge times, Characterizes the duration of the charge and discharge platform corresponding to the i-th charge and discharge, Characterizes the duration of the charge and discharge platform corresponding to the i-th charge and discharge of the model fitting, Characterizes the number of model parameters, Characterizes the average value of the charge and discharge platform duration.

[0111] Optionally, the battery health state determination device may determine a fitting model with the largest Akaike information criterion and the largest coefficient of determination as the target fitting model.

[0112] Alternatively, if one of the Akaike information criterion and the coefficient of determination is larger and the other is smaller, the target fitting model can be determined by combining experimental tests.

[0113] Optionally, in order to achieve visual analysis of the fitting model, the battery health status determination device can also generate a visual chart including a fitting curve and residual analysis based on the target fitting model for user viewing.

[0114] The present application also provides a battery management system integrated into a battery pack. Specifically, Figure 4 A block diagram of a battery management system provided in an embodiment of the present application is shown in FIG. Figure 4The battery management system includes a voltage monitoring module 200 and a calculation module 210, wherein the voltage monitoring module is used to monitor the battery pack voltage in real time, and the calculation module is used to obtain the current charge and discharge times of the battery pack; based on the current charge and discharge times and a pre-stored fitting model, the charge and discharge platform duration is determined; and the battery health status is determined based on the ratio of the charge and discharge platform duration to the initial charge and discharge platform duration.

[0115] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the battery health status determination method provided in the embodiment of the present application can be implemented.

[0116] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions, and operations of the devices, methods, and computer program products according to the multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment, or a portion of code, and the module, program segment, or a portion of code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the boxes can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or can be implemented using a combination of dedicated hardware and computer instructions.

[0117] In addition, the functional modules in each embodiment of the present application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0118] If the function is implemented in the form of a software function module 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 the present application, or the part that contributes to the existing technology, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program code.

[0119] The above are merely preferred embodiments of the present application and are not intended to limit the present application. Those skilled in the art will readily appreciate that various modifications and variations are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present application shall be included within the scope of protection of the present application.

Claims

1. A method for determining a battery health state, characterized in that: The method comprises: Get the current charge and discharge times of the battery pack under test; Determine the charge and discharge platform duration of the battery pack under test under the current charge and discharge times based on the current charge and discharge times and a pre-stored fitting model; wherein the fitting model represents a mapping relationship between the charge and discharge times and the charge and discharge platform duration; The battery health state of the battery pack to be tested is determined according to the ratio of the charge and discharge platform time length under the current charge and discharge times of the battery pack to be tested to the initial charge and discharge platform time length.

2. The method according to claim 1, characterized in that The battery pack to be tested includes a plurality of battery cells to be tested; the fitting model includes an overall fitting model of the battery pack to be tested and / or an independent fitting model of each battery cell to be tested; The step of determining the charge and discharge platform duration of the battery pack under test under the current charge and discharge times based on the current charge and discharge times and a pre-stored fitting model includes: Determining a charge and discharge platform duration of the entire battery pack based on the current charge and discharge times and the overall fitting model of the battery pack, and / or determining a charge and discharge platform duration of each battery cell to be tested based on the current charge and discharge times and each of the independent fitting models; The step of determining the battery health status of the battery pack to be tested based on the ratio of the charge and discharge platform duration of the battery pack to be tested under the current charge and discharge times to the initial charge and discharge platform duration includes: The overall health status of the battery pack is determined based on the overall charge and discharge platform time and the initial charge and discharge platform time of the battery pack to be tested, and / or the health status of each battery cell to be tested is determined based on the charge and discharge platform time of each battery cell to be tested.

3. The method according to claim 1, characterized in that The fitting model is obtained by the following steps: Performing multiple full charge and discharge operations on the battery pack to be tested, and collecting voltage sequences corresponding to each charge and discharge operation; extracting a charge and discharge platform duration from the voltage sequence based on a preset state of charge range; A mapping relationship between the number of charge and discharge times and the duration of the charge and discharge platform is fitted, and the mapping relationship is iteratively optimized to generate the fitting model.

4. The method according to claim 1, wherein The fitting model includes at least one of an exponential model, a polynomial model and a power function model.

5. The method according to claim 4, characterized in that The method further comprises: The exponential model is obtained by dynamically fitting a preset number of exponential terms and a numerical stabilization function; The polynomial model is obtained by fitting the polynomial model based on the least square method by presetting the polynomial degree; The power function model is obtained by fitting a preset number of power function terms.

6. The method according to claim 1, characterized in that The step of determining the charge and discharge platform duration of the battery pack under test under the current charge and discharge times based on the current charge and discharge times and a pre-stored fitting model includes: When there are multiple fitting models, calculating the evaluation parameters of each fitting model; screening a target fitting model based on the evaluation parameters; The charge and discharge platform duration is determined based on the current charge and discharge times and the target fitting model.

7. The method according to claim 6, characterized in that The evaluation parameters include Akaike's information criterion and the coefficient of determination.

8. A device for determining battery health status, characterized in that: Integrated into a battery pack, the device includes: processor and memory; The memory is used to store computer programs; The processor is configured to implement the method according to any one of claims 1 to 7 when executing the computer program.

9. A battery management system, characterized in that: Integrated into the battery pack, including: Voltage monitoring module, used to monitor the battery pack voltage in real time; Compute module, which performs the following operations: Get the current charge and discharge times of the battery pack; Determining a charge and discharge plateau duration based on the current charge and discharge times and a pre-stored fitting model; The battery health state is determined based on the ratio of the charge and discharge plateau duration to the initial charge and discharge plateau duration.

10. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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