CN115372850A - Method, device, equipment and medium for generating and determining battery material aging data - Google Patents
Method, device, equipment and medium for generating and determining battery material aging data Download PDFInfo
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Abstract
The embodiment of the application provides a method, a device, equipment and a medium for generating and determining battery material aging data. The method comprises the following steps: determining N OCV intervals of the battery, wherein the N OCV intervals are formed by dividing the value range of the OCV of the battery; when the battery is in the target aging degree, determining battery material aging parameters corresponding to the N OCV intervals respectively; and generating battery material aging data corresponding to the target aging degree by using the battery material aging parameters corresponding to the N OCV intervals. According to the embodiment of the application, the material aging characteristic of the mixed material battery can be accurately reflected through the material aging data.
Description
Technical Field
The application belongs to the technical field of batteries, and particularly relates to a method, a device, equipment and a medium for generating and determining battery material aging data.
Background
With the development of new energy, new energy is adopted as power in more and more fields. Because of the advantages of high energy density, cyclic charging, safety, environmental protection and the like, the battery is widely applied to the fields of electric devices such as ships and the like, consumer electronics, energy storage systems and the like. During the life cycle of a battery, the battery may gradually age due to various factors, such as the aging of materials. Since the aging of the material causes the change of various properties of the battery, the aging characteristics of the material of the battery need to be measured.
However, the material aging characteristics of a hybrid battery in which a plurality of materials are mixed in a positive electrode are complicated. Therefore, a technical scheme capable of accurately reflecting the material aging characteristics of the compound battery is lacked.
Disclosure of Invention
The embodiment of the application provides a method, a device, equipment and a medium for generating and determining battery material aging data, and the material aging characteristics of a mixed material battery can be accurately reflected through the material aging data.
In a first aspect, an embodiment of the present application provides a method for generating aging data of a battery material, where a positive electrode of a battery is formed by mixing at least two materials, and the method includes:
determining N open-circuit voltage OCV intervals formed by dividing the OCV value range of the battery, wherein N is an integer greater than or equal to 2;
when the battery is in the target aging degree, determining battery material aging parameters corresponding to the N OCV intervals respectively;
and generating battery material aging data corresponding to the target aging degree by using the battery material aging parameters corresponding to the N OCV intervals.
According to the method for generating the battery material aging data, for the mixed battery with the positive electrode formed by mixing at least two materials, when the battery is in the target aging degree, due to the fact that the aging characteristic of the positive electrode material is not uniform in the whole OCV value range, a plurality of OCV intervals divided by the OCV value range can be determined firstly, and then the battery material aging parameters corresponding to the N OCV intervals are determined. Due to the fact that the aging characteristic of the battery material in each COV interval can be accurately reflected by the aging parameter of the battery material in each COV interval, the aging characteristic of the material of the mixed material battery under the target aging degree can be accurately reflected by battery material aging data generated based on the battery material aging parameters corresponding to the N OCV intervals.
In an alternative embodiment, determining N open circuit voltage OCV intervals for a battery includes:
and dividing the value range of the OCV according to the material characteristic parameters of the battery or the variation trend of the OCV of the battery along with the battery capacity to obtain N OCV intervals.
According to the embodiment, different battery materials have different influences on the aging characteristics of the battery materials in different OCV intervals, and the OCV of the battery has different variation trends along with the battery capacity due to different aging characteristics of the battery materials, so that the OCV value range can be accurately divided into a plurality of OCV intervals representing different aging characteristics of the materials according to the material characteristic parameters or the variation trend of the OCV of the battery along with the battery capacity. Furthermore, because each section represents different material aging characteristics, the battery material aging data generated based on the battery material aging parameters corresponding to the N OCV sections can accurately reflect the material aging characteristics of the mixed material battery under the target aging degree.
In an optional embodiment, battery material aging data of a battery under M aging degrees are obtained, wherein the M aging degrees comprise target aging degrees, and M is a positive integer;
and generating a corresponding relation between the aging degrees and the battery material aging data based on the battery material aging data under the M aging degrees.
Through the embodiment, M aging degrees of the battery in the whole life cycle can be selected, and the corresponding relation between the aging degrees and the battery material aging data is generated according to the battery material aging data under the M aging degrees. Therefore, the material aging degree in the whole life cycle of the battery can be accurately reflected by utilizing the corresponding relation between the aging degree and the battery material aging data.
In an alternative embodiment, determining the battery material aging parameter at the target aging degree corresponding to each of the N OCV intervals specifically includes:
for each of the N OCV intervals, the following operations are performed:
acquiring first data and second data, wherein the first data represents the corresponding relation between the OCV in each OCV interval and the battery capacity parameter in the initial life period, and the second data represents the corresponding relation between the OCV in each OCV interval and the battery capacity parameter under the target aging degree;
and determining the battery material aging parameter under the target aging degree corresponding to each OCV interval according to the first data and the second data.
In the present embodiment, the correspondence relationship between the OCV of the battery in each OCV section and the battery capacity parameter in the collected BOL period and the correspondence relationship between the OCV of the battery in each OCV section and the battery capacity parameter in the collected target degree of aging may be used. Since the battery material aging causes a change in the correspondence relationship between the OCV and the battery capacity parameter in each OCV interval, the battery material aging parameter of the battery in each OCV interval can be accurately determined by the difference between the correspondence relationship between the OCV and the battery capacity parameter in each OCV interval at different times.
In an alternative embodiment, the second data is collected for the battery at a target age;
according to the first data and the second data, determining battery material aging parameters under the target aging degree corresponding to each OCV interval, specifically comprising the following steps:
estimating to obtain third data by using the first data, wherein the third data is used for representing the corresponding relation between the OCV in each OCV interval and the battery capacity parameter under the target aging degree;
and determining the battery material aging parameter under the target aging degree corresponding to each OCV interval according to the second data and the third data.
In the present embodiment, the third relationship of the correspondence between the OCV in each OCV interval and the battery capacity parameter at the target degree of aging can be estimated using the first data with the battery material aging parameter as an unknown amount. And then, through the third data obtained by estimation and the second data obtained by collection, the battery material aging parameter under the target aging degree corresponding to each OCV interval can be accurately calculated.
In an alternative embodiment, the first data comprises: the battery pack comprises positive electrode potentials corresponding to L battery capacity parameters in an initial life period and negative electrode potentials corresponding to the L battery capacity parameters in the initial life period, wherein the difference value between the positive electrode potential corresponding to each of the L battery capacity parameters in the initial life period and the negative electrode potential corresponding to the positive electrode potential is within each OCV interval, and L is an integer greater than or equal to 2.
Estimating to obtain third data by using the first data, wherein the method specifically comprises the following steps:
for each capacity parameter, the following operations are performed:
correcting the anode potential corresponding to each capacity parameter by using a first relational expression, wherein the relational coefficient of the first relational expression is related to the aging parameters of the anode material;
correcting the negative electrode potential corresponding to each capacity parameter by using a second relational expression, wherein the relational coefficient of the second relational expression is related to the aging parameter of the negative electrode material and the aging parameter of the active ions;
determining the difference value of the corrected anode potential and the corrected cathode potential as the corrected OCV;
third data is estimated based on the corrected OCV corresponding to each of the L battery capacity parameters in the initial life period.
In the present embodiment, since the correspondence relationship between the positive electrode potential and the capacity parameter of the battery changes as the positive electrode material ages, and the correspondence relationship between the negative electrode potential and the capacity parameter of the battery changes as the negative electrode material ages, the positive electrode potential is corrected by the first relational expression relating to the positive electrode material aging parameter, and the negative electrode potential is corrected by the negative electrode material aging parameter and the active ion aging parameter. Then, the corrected OCV is related to the aging parameter of the positive electrode material, the aging parameter of the negative electrode material and the aging parameter of the active ions, based on the corresponding relationship between the corrected OCV and the capacity parameter at the same aging degree and the corresponding relationship between the acquired OCV and the capacity parameter, the correlation between the aging parameter of the positive electrode material, the aging parameter of the negative electrode material and the aging parameter of the active ions can be accurately solved, and based on the corrected OCV and the capacity parameter at the same aging degree, the calculation accuracy and the comprehensiveness of the aging parameters of the materials are improved.
In an alternative embodiment, the battery material aging parameters include: at least one of the aging parameters of the positive electrode material, the aging parameters of the negative electrode material and the aging parameters of the active ions.
In the embodiment, the material aging degree of the positive electrode material, the negative electrode material and the active ions can be determined, and the material aging characteristics of the mixed material battery can be comprehensively and accurately reflected.
In a second aspect, an embodiment of the present application provides a method for determining aging data of a battery material, where a positive electrode of the battery is formed by mixing multiple materials, and the method includes:
acquiring a target aging degree of the battery, wherein the target aging parameter is the aging degree of the battery at a target moment;
determining target material aging data corresponding to the target aging degree in a preset corresponding relation between the aging degree and battery material aging data, wherein the target material aging data comprises: and the N OCV intervals are formed by dividing the OCV value range of the battery.
In the method for determining aging data of a battery material according to the embodiment of the present application, for a mixed material battery in which a positive electrode is formed by mixing at least two materials, when the battery is in a target aging degree, since the aging characteristic of the positive electrode material is not uniform in the whole OCV value range, the target aging data of the battery material in each aging degree in the embodiment of the present application may include battery material aging parameters corresponding to N OCV intervals. Due to the fact that the aging parameters of the battery materials in the COV sections can accurately reflect the aging characteristics of the sections, the aging data of the battery materials generated based on the aging parameters of the battery materials corresponding to the N OCV sections can accurately reflect the material aging characteristics of the mixed material battery under the target aging degree.
In an optional embodiment, before determining the battery material aging data corresponding to the target aging degree, the method further includes:
acquiring the aging degree of the battery at the previous moment of the target moment;
determining the difference value between the aging degree of the previous moment and the target aging degree;
determining target material aging data corresponding to the target aging degree specifically comprises the following steps:
and determining battery material aging data corresponding to the target aging degree under the condition that the difference value is larger than a preset parameter threshold value.
Through the embodiment, the material aging data of the battery can be updated in time according to the aging degree of the battery in the use process of the battery. In addition, because the current material aging data of the battery is updated only when the difference value between the target aging degree and the aging degree at the previous moment is large enough, namely larger than the preset parameter threshold, on the premise of ensuring the accuracy of the current material aging data, the data processing pressure caused by frequent updating is avoided, and the updating efficiency is ensured.
In an optional embodiment, after determining target material aging data corresponding to the target aging degree, the method further includes:
and determining the corresponding relation between the OCV and the battery capacity parameter in the value range of the OCV of the battery based on the target material aging data corresponding to the target aging degree.
According to the embodiment, the established corresponding relation between the OCV in the OCV value range and the battery capacity parameter can accurately represent the relation between the OCV and the Q of the battery with the target aging degree, so that the battery capacity parameter corresponding to the OCV value can be accurately inquired after the OCV value is obtained in real time.
In an alternative embodiment, the correspondence between OCV and battery capacity parameter includes: a curve representing the variation trend of the OCV in the value range of the OCV along with the battery capacity parameter;
determining the corresponding relation between the OCV in the value range of the OCV of the battery and the battery capacity parameter based on the target material aging data corresponding to the target aging degree, and specifically comprising the following steps:
determining a curve segment representing the change of the OCV of each OCV interval along with the battery capacity parameter based on the battery material aging parameter corresponding to each OCV interval;
and splicing the curve sections corresponding to the N OCV intervals to obtain a curve. Through the embodiment, the characteristic curve which accurately reflects the change relation of the OCV of the battery along with the battery capacity parameter can be obtained, and a user can conveniently and quickly and accurately inquire the battery capacity corresponding to each OCV value in real time through the characteristic curve.
In a third aspect, an embodiment of the present application provides an apparatus for generating aging data of a battery material, where a positive electrode of the battery is formed by mixing at least two materials, and the apparatus includes:
the OCV interval determination module is used for determining N OCV intervals formed by dividing the OCV value range of the battery;
the aging parameter determining module is used for determining battery material aging parameters corresponding to the N OCV intervals when the battery is in the target aging degree;
and the aging data determining module is used for generating battery material aging data corresponding to the target aging degree by using the battery material aging parameters corresponding to the N OCV intervals.
According to the generation device of the battery material aging data, for the mixed battery with the positive electrode formed by mixing at least two materials, when the battery is in the target aging degree, due to the fact that the aging characteristic of the positive electrode material is not uniform in the whole OCV value range, a plurality of OCV intervals divided by the OCV value range can be determined firstly, and then the battery material aging parameters corresponding to the N OCV intervals are determined. Due to the fact that the aging characteristic of the battery material in each COV interval can be accurately reflected by the aging parameter of the battery material in each COV interval, the aging characteristic of the material of the mixed material battery under the target aging degree can be accurately reflected by battery material aging data generated based on the battery material aging parameters corresponding to the N OCV intervals.
In a fourth aspect, an embodiment of the present application provides an apparatus for determining aging data of a battery material, where a positive electrode of the battery is formed by mixing multiple materials, and the apparatus includes:
the aging degree acquisition module is used for acquiring a target aging degree of the battery, wherein the target aging parameter is the aging degree of the battery at a target moment;
the aging data determining module is used for determining target material aging data corresponding to the target aging degree in a preset corresponding relation between the aging degree and the battery material aging data, wherein the target material aging data comprises: and the N OCV intervals are formed by dividing the OCV value range of the battery.
In the apparatus for determining aging data of a battery material according to the embodiment of the present application, for a mixed battery in which a positive electrode is formed by mixing at least two materials, when the battery is in a target aging degree, since the aging characteristic of the positive electrode material is not uniform in the whole OCV value range, the target aging data of the battery material in each aging degree according to the embodiment of the present application may include battery material aging parameters corresponding to N OCV intervals. Due to the fact that the aging characteristic of the battery material in each COV interval can be accurately reflected by the aging parameter of the battery material in each COV interval, the aging characteristic of the material of the mixed material battery under the target aging degree can be accurately reflected by battery material aging data generated based on the battery material aging parameters corresponding to the N OCV intervals.
In a fifth aspect, there is provided a device for generating battery material aging data, including:
a processor and a memory storing computer program instructions;
the processor reads and executes the computer program instructions to implement the method for generating battery material aging data provided by the first aspect or any optional implementation manner of the first aspect.
According to the generation equipment of the battery material aging data, for the mixed battery with the positive electrode formed by mixing at least two materials, when the battery is in the target aging degree, due to the fact that the aging characteristic of the positive electrode material is not uniform in the whole OCV value range, a plurality of OCV intervals divided by the OCV value range can be determined firstly, and then the battery material aging parameters corresponding to the N OCV intervals are determined. Due to the fact that the aging characteristic of the battery material in each COV interval can be accurately reflected by the aging parameter of the battery material in each COV interval, the aging characteristic of the material of the mixed material battery under the target aging degree can be accurately reflected by battery material aging data generated based on the battery material aging parameters corresponding to the N OCV intervals.
In a sixth aspect, there is provided an apparatus for determining aging data of a battery material, comprising:
a processor and a memory storing computer program instructions;
the processor reads and executes the computer program instructions to implement the method for generating battery material aging data provided by the first aspect or any optional implementation manner of the first aspect.
According to the device for determining the aging data of the battery material, for the mixed battery with the positive electrode formed by mixing at least two materials, when the battery is in the target aging degree, because the aging characteristic of the positive electrode material is not uniform in the whole OCV value range, the target material aging data under each aging degree in the embodiment of the application can comprise the battery material aging parameters corresponding to the N OCV intervals. Due to the fact that the aging parameters of the battery materials in the COV sections can accurately reflect the aging characteristics of the sections, the aging data of the battery materials generated based on the aging parameters of the battery materials corresponding to the N OCV sections can accurately reflect the material aging characteristics of the mixed material battery under the target aging degree.
In a seventh aspect, a computer storage medium is provided, on which computer program instructions are stored, which when executed by a processor implement the method for generating battery material aging data provided in the first aspect or any of the optional embodiments of the first aspect, or the method for determining battery material aging data provided in the second aspect or any of the optional embodiments of the second aspect.
According to the computer storage medium of the embodiment of the application, for a mixed battery with a positive electrode formed by mixing at least two materials, when the battery is in a target aging degree, because the aging characteristics of the positive electrode material are not uniform in the whole OCV value range, a plurality of OCV intervals divided by the OCV value range can be determined firstly, and then battery material aging parameters corresponding to the N OCV intervals are determined. Due to the fact that the aging characteristic of the battery material in each COV interval can be accurately reflected by the aging parameter of the battery material in each COV interval, the aging characteristic of the material of the mixed material battery under the target aging degree can be accurately reflected by battery material aging data generated based on the battery material aging parameters corresponding to the N OCV intervals.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly described below, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic illustration of an exemplary OCV-Q curve provided by an embodiment of the present application;
fig. 2 is a schematic flow chart of a method for generating battery material aging data according to an embodiment of the present disclosure;
fig. 3 is a schematic flow chart of another method for generating battery material aging data according to an embodiment of the present disclosure;
fig. 4 is a schematic flowchart of a method for determining aging data of a battery material according to an embodiment of the present disclosure;
fig. 5 is a schematic flowchart of another method for determining aging data of a battery material according to an embodiment of the present disclosure;
fig. 6 is a schematic flowchart of another method for determining aging data of a battery material according to an embodiment of the present disclosure;
fig. 7 is a schematic flowchart of a method for determining aging data of a battery material according to an embodiment of the present disclosure;
fig. 8 is a schematic structural diagram of a device for generating battery material aging data according to an embodiment of the present application;
fig. 9 is a schematic structural diagram of an apparatus for determining battery material aging data according to an embodiment of the present application;
fig. 10 is a schematic diagram illustrating a hardware structure of a device for generating battery material aging data according to an embodiment of the present application;
fig. 11 is a schematic diagram illustrating a hardware configuration of a device for determining battery material aging data according to an embodiment of the present application.
Detailed Description
Features and exemplary embodiments of various aspects of the present application will be described in detail below, and in order to make objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are intended to be illustrative only and are not intended to be limiting. It will be apparent to one skilled in the art that the present application may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the present application by illustrating examples thereof.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of another identical element in a process, method, article, or apparatus that comprises the element.
Throughout the life of the battery, the active materials of the battery gradually age. Therefore, how to evaluate the aging performance of the active material of the battery becomes a problem to be solved urgently.
In a related art, an Open Circuit Voltage (OCV) variation interval Of a positive electrode Of a battery in a Middle Of Life (MOL) and a negative OCV variation interval Of a MOL period may be determined, and then a State Of Charge-Open Circuit Voltage (SOC-OCV) curve Of a positive electrode half cell in an initial Life period (Beginning Of Life, BOL) and a negative electrode half cell SOC-COV curve Of the BOL period may be shifted left or right, respectively, to obtain a positive electrode half cell SOC-OCV curve Of the MOL period and a negative electrode half cell SOC-OCV curve Of the MOL period, and further obtain a full cell SOC-OCV curve Of the MOL period.
In another related art, information indicating the state of aging of a battery pack may be acquired. And then obtaining the current aging characteristic parameters of the battery pack according to the current OCV-SOC curve and information of the battery pack. And updating the OCV-SOC curve of the battery pack according to the current aging characteristic parameters of the battery pack and the current OCV-SOC curve.
However, both of the above-described related arts are directed to a battery of a single positive electrode material, and it is necessary to establish the premise that the material aging characteristics of the battery are uniform over the entire OCV value range. Therefore, the above two related techniques cannot accurately reflect the material aging characteristics of the hybrid battery.
Therefore, a technical scheme capable of accurately reflecting the material aging characteristics of the mixed material battery under the target aging degree is needed.
Based on the method, the device, the equipment and the medium for generating and determining the battery material aging data are provided by the embodiment of the application.
The generation scheme of the battery material aging data can be applied to an application scene for evaluating the material aging characteristics of the battery. The method can be specifically applied to a specific application scenario in which the material aging characteristic of the battery under a target aging degree is estimated before the battery leaves a factory, or a specific application scenario in which the material aging data of the sample battery is used as the material aging data of the material mixing battery of the class to which the sample battery belongs.
The determination scheme of the battery material aging data can be applied to a use scene or an acquisition scene of the battery material aging characteristics. For example, the present invention can be applied to a specific application scenario in which material aging data of a battery is determined during actual use of the battery, or can be applied to an SOC-OCV curve or a Q-OCV curve at a target aging degree, which is obtained by acquiring the material aging data and generating the material aging data.
Compared with the related art, the embodiment of the application can determine a plurality of OCV intervals divided by the OCV value range, and then determine the battery material aging parameters corresponding to the N OCV intervals. Due to the fact that the aging characteristic of the battery material in each COV interval can be accurately reflected by the aging parameter of the battery material in each COV interval, the aging characteristic of the material of the mixed material battery under the target aging degree can be accurately reflected by battery material aging data generated based on the battery material aging parameters corresponding to the N OCV intervals.
Next, the following sections of the embodiments of the present application will explain in detail the determination scheme of the battery material aging data and the generation scheme of the battery material aging data in order.
First, for better understanding of the present application, the present embodiment specifically explains concepts of a battery, OCV, battery aging degree, battery material aging parameter, and the like.
(1) A battery.
In terms of scale, the battery in the embodiment of the present application may be a single battery cell, or may be a battery module or a battery pack, which is not limited herein.
From the aspect of application, the battery in the embodiment of the present application may be applied to a power device such as an automobile or a ship. For example, the power supply device can be applied to an electric automobile to supply power to a motor of the electric automobile and serve as a power source of the electric automobile. The battery can also supply power for other electric appliances in the electric automobile, such as an air conditioner, a vehicle-mounted player, a computer and the like in the automobile.
The battery in the embodiment of the present application may also be referred to as a hybrid battery, which refers to a battery in which a positive electrode is formed by mixing at least two materials, or may refer to a battery in which a positive electrode material is formed by mixing at least two systems of materials. Illustratively, the positive electrode of the battery may be a mixture of a positive electrode material of a ternary system battery and a positive electrode material of a lithium iron system. It should be noted that the positive electrode of the battery may also be formed by mixing materials of other systems, such as at least two of a lithium cobaltate system, a lithium iron system, a ternary system, or a lithium manganate system, which is not specifically limited in this application.
In some embodiments, the negative electrode material of the battery may include carbon or silicon, or the like. The negative electrode material of the battery may be of other types, which is not limited in the examples of the present application.
In other embodiments, the active ions of the battery may be active ions in the electrolyte, such as lithium ions and the like. It should be noted that the negative electrode material of the battery may be of other types, and the specific type of the active ion of the battery is not particularly limited in the embodiments of the present application.
(2)OCV。
Open Circuit Voltage (OCV) refers to the potential difference collected across a battery when the battery meets a resting condition or a quasi-resting condition. Wherein, the standing condition can comprise: the battery is in an open circuit state, and the open circuit duration is greater than or equal to a first preset duration. The quasi-static conditions may include: the time length of the battery which is charged with the charging current less than the preset charging current is greater than or equal to a second preset time length.
Second, there is a linear relationship between the OCV of the battery and the capacity parameter of the battery. For a certain battery, any OCV value corresponds to a capacity parameter. The capacity parameter of the battery is used to measure the real-time capacity of the battery, for example, the capacity Q or the state of charge SOC may be used, which is not specifically limited in the embodiment of the present application.
In a specific application scenario, after a certain OCV sampling value of a battery is obtained, a Q value or an SOC value corresponding to the OCV sampling value can be obtained by querying an OCV-Q relation table or an OCV-SOC relation table.
Next, the value of OCV of the battery is within a certain range, and this range can be regarded as the value range of OCV of the battery. In one example, the OCV range of values for a battery may be expressed as OCV a ，OCV b ]Wherein OCV a May correspond to the OCV of the battery in a fully discharged state, such as the OCV of the battery at SOC =0%, OCV b May correspond to the OCV of the battery in a fully charged state, such as the OCV of the battery at SOC = 100%.
(3) The degree of battery aging.
In the embodiment of the application, the aging degree of the battery is used for measuring the service life of the battery in each period.
Before the battery is put into service, i.e., when the battery is in the BOL period, the battery is in an initial Life period (Beginning of Life, BOL). In one example, a battery in the BOL period may be referred to as a fresh battery.
In the using process of the battery, the aging degree of the battery is gradually deepened, and the residual service life is also gradually reduced along with the aging degree.
In one embodiment, the State of Health (SOH) of the battery may be used to indicate the degree of battery aging. Wherein the smaller the SOH, the higher the degree of battery aging. For example, SOH =100% indicates the degree of battery aging before or at the time of shipment, that is, during the BOL period of the battery. SOH =0% indicates that the battery is in a state of scrap. In one particular example, the SOH of the battery at the target time may be represented by a ratio of a full charge capacity of the battery at the target time to a rated capacity. In another specific example, the SOH of the battery at the target time may be a ratio of a remaining number of cycles of the battery at the target time to a total number of cycles of the battery. It should be noted that SOH may also be represented by other manners, such as maximum discharge capacity and internal resistance, which are not specifically limited in this embodiment of the present application.
In another embodiment, the aging degree of the battery may be expressed by parameters affected by the aging of the battery, such as the remaining cycle number, the maximum discharge capacity, and the internal resistance of the battery, which are not specifically limited in this embodiment.
(4) And (3) aging parameters of the battery material.
The battery material aging parameter is used to indicate the degree of aging of the battery material. Wherein the battery material aging parameter is influenced by the battery aging degree.
In some examples, the battery materials may include a positive electrode material, a negative electrode material, and active ions of the battery. Accordingly, the aging parameter W of the positive electrode material such as a battery can be used p Aging parameter W of the negative electrode material n And active ionRepresents the material aging characteristics of the battery.
Wherein the aging parameter W for the cathode material p Aging parameter W of the cathode Material p For characterizing the aging of the positive electrode material within the cell. In one example, the aging parameter W of the positive electrode material p Can be less than or equal to 1 and greater than 0. Aging parameter W of the positive electrode material when the battery is in the BOL period p Can be 1, the aging parameter W of the positive electrode material increases with the aging degree of the battery p And may be reduced accordingly.
Wherein the aging parameter W for the anode material n In one example, the aging parameter W of the anode material n Can be less than or equal to 1 and greater than 0. Aging parameter W of the positive electrode material when the battery is in the BOL period p Can be 1, the aging parameter W of the positive electrode material increases with the aging degree of the battery p And may be reduced accordingly.
Wherein, as for the aging parameter K of the active ions, the aging parameter K of the active ions is used for representing the aging degree of the active ions in the battery. If the battery is a lithium battery, for example, the aging parameter K of the active ions may be related to the loss of active lithium in the battery. In one example, the aging parameter K of the active ions is positively correlated with the aging parameter K of the active ions, that is, the aging parameter K of the active ions increases as the aging degree of the active ions increases.
After the above-described concept is introduced, the following sections of the examples of the present application will make a preliminary explanation of the aging parameters of the battery materials in conjunction with the OCV-Q curve of the battery for the convenience of understanding. Fig. 1 is a schematic diagram of an exemplary OCV-Q curve provided in an embodiment of the present application. In fig. 1, the abscissa represents the capacity Q and the ordinate represents the open circuit voltage OCV.
As shown in FIG. 1, a first solid line L1 indicates the positive electrode potential OCV of the battery in the BOL period pos The first dotted line L2 represents the positive electrode potential OCV of the aged battery in relation to Q pos With respect to Q, the second solid line L3 represents the power during BOLNegative potential OCV of the cell neg The second dotted line L4 represents the negative electrode potential OCV of the aged battery neg Curve with Q. In FIG. 1, the positive electrode potential OCV pos And negative electrode potential OCV neg May be measured for a full cell. Specifically, the positive electrode potential OCV pos Is a voltage measured between the positive terminal of the full cell and the reference potential terminal. Cathode potential OCV neg Is a voltage measured between the negative terminal and the reference potential terminal of the full cell.
First, as can be seen from fig. 1, the first broken line L2 can be regarded as being scaled in the horizontal axis direction with respect to the first solid line L1. Wherein the aging parameter W of the positive electrode material p For reflecting the amount of scaling of the first broken line L2 in the horizontal axis direction with respect to the first solid line L1.
The second dotted line L4 can be regarded as a result of scaling and translation in the direction of the horizontal axis for the second solid line L3. Wherein the aging parameter W of the anode material n For reflecting the amount of scaling of the second broken line L4 in the direction of the abscissa with respect to the second solid line L3, and the aging parameter K of the active ions is for the amount of translation of the second broken line L4 in the direction of the abscissa with respect to the second solid line L3.
Due to the fact that the material aging characteristics of the mixed material battery in different OCV intervals are different, correspondingly, the material aging parameters of the mixed material battery in different OCV intervals are different. Therefore, as can be seen from fig. 1, the scaling amount and the translation amount of the battery are different in different OCV intervals. For example, if the vertical line corresponds to a capacity of Q 1 Then Q can be given 1 And dividing the value range of the OCV of the battery into 2 sections by taking the OCV value as a demarcation point.
Next, for better understanding of the present application, a method, an apparatus, a device, and a medium for generating and determining aging data of a battery material according to embodiments of the present application will be described in detail below with reference to the accompanying drawings, and it should be noted that these embodiments are not intended to limit the scope of the present disclosure.
Fig. 2 is a schematic flow chart of a method for generating battery material aging data according to an embodiment of the present application. As shown in fig. 2, the generation method of the battery material aging data may include S210 to S230. In some embodiments, the execution subject of each step of the method for generating battery material aging data provided in the embodiment of the present application may be a device with a data processing function, such as a computer, a processor, a battery management system, and the like, which is not particularly limited in this embodiment of the present application.
S210, determining N OCV intervals of the battery, wherein N is an integer greater than or equal to 2.
First, for the battery in S210, it may be referred to as a hybrid battery, and specific contents thereof may be referred to in the description of the above part of the embodiment of the present application, and are not described herein again.
Next, for N OCV intervals in S210, the OCV value range of the battery may be divided into the N OCV intervals. Wherein, the OCV value range of the battery can be expressed as [ OCV a ，OCV b ]For reference, the related contents in the above-mentioned part of the embodiments of the present application may be referred to, and are not described herein again.
In one example, the OCV range may be divided into N OCV intervals, such as a first OCV interval, a second OCV interval, … …, and an nth OCV interval. If the OCV value range can be expressed as [ OCV ] a ，OCV b ]Then N OCV intervals can be respectively expressed as [ OCV a ，OCV 1 )、…、[OCV N-1 ，OCV b ]For example, N may be equal to 2 or equal to 3.
Next, a specific embodiment of S210 will be specifically described below.
In one embodiment, the OCV value range may be divided according to the material characteristic parameters of the battery, so as to obtain N OCV intervals. The material characteristic parameter is used to indicate a parameter that affects the material aging characteristics of the battery.
In one example, the aging characteristics of the materials of the batteries with different mixed materials and the batteries with different mixed material ratios of the same mixed material are different, so the material characteristic parameters can be the types of the positive electrode materials of the batteries, the material mixing ratios and other parameters.
Accordingly, in S210, the number of segments and the positions of the segments of the OCV range may be determined according to the material characteristic parameters, such as the kind of the positive electrode material and/or the material mixing ratio of the battery, and then the OCV interval may be divided into N OCV intervals according to the number of segments and the positions of the segments.
In another example, the material characteristic parameter may be an empirical value of the number of divisions of the section and an empirical value of the division position.
According to the embodiment, different battery materials have different influences on the aging characteristics of the battery materials in different OCV intervals, so that the OCV value range can be accurately divided into a plurality of OCV intervals representing the aging characteristics of different materials according to the material characteristic parameters. Furthermore, because each section represents different material aging characteristics, the battery material aging data generated based on the battery material aging parameters corresponding to the N OCV sections can accurately reflect the material aging characteristics of the mixed material battery under the target aging degree.
In another embodiment, the OCV value range may be divided according to a variation trend of the OCV of the battery along with the battery capacity, so as to obtain N OCV intervals.
The battery capacity may be a parameter that can represent the battery capacity, such as a capacity Q or a state of charge SOC, and is not limited thereto.
In one example, the dividing parameters such as the number of segments and/or the positions of the segments of the OCV value range may be determined according to the variation trend of the OCV of the battery in the BOL period along with the battery capacity, and then the OCV value range may be divided into N OCV intervals according to the dividing parameters.
In another example, the segmentation parameters such as the segmentation number and the segmentation position of the OCV value range can be determined according to the variation trend of the OCV of the sample battery or the experimental battery along with the battery capacity, and then the OCV value range is divided into N OCV intervals according to the segmentation parameters. In a specific example, the variation tendency of the OCV of the battery with the battery capacity may be determined according to an OCV-battery capacity variation curve or an OCV-battery capacity correspondence of the battery.
It should be noted that the OCV value range may also be divided according to other manners, for example, the OCV interval is divided into N OCV intervals in an equal division manner or an unequal division manner, and the specific division manner may be set according to a specific scene and an actual requirement, which is not limited in this embodiment of the application.
According to the embodiment, the variation trend of the OCV of the battery along with the battery capacity is different due to different material aging characteristics of the battery, so that the OCV value range can be accurately divided into a plurality of OCV intervals representing different material aging characteristics according to the variation trend of the OCV of the battery along with the battery capacity. Furthermore, since each section represents different material aging characteristics, the battery material aging data generated based on the battery material aging parameters corresponding to the N OCV sections can accurately reflect the material aging characteristics of the hybrid battery at the target aging degree.
And S220, determining battery material aging parameters corresponding to the N OCV intervals when the battery is in the target aging degree.
First, for a target age level. The target age may be the age of the battery at a selected point in the life cycle.
Second, for battery material aging parameters. Specifically, the aging parameter W of the positive electrode material of the battery p Aging parameter W of the negative electrode material n And aging parameter K of active ions. For other details of the aging parameter of the battery material, reference may be made to the related description in the above section of the embodiment of the present application, and details are not repeated here.
Next, the aging parameters of the battery material corresponding to each of the N OCV intervals are determined. For convenience of understanding, taking the example that the OCV value range can be divided into N OCV intervals, the battery material aging parameter of the ith OCV interval of the N OCV intervals can be represented as the aging parameter W of the positive electrode material of the battery pi Aging parameter W of the negative electrode material Ni And aging parameter K of active ion i . Wherein i is a positive integer less than or equal to N.
Then, in order to accurately obtain the battery material aging parameter, the battery material aging parameter may be determined for each OCV interval, respectively, in S220. Specifically, for each OCV interval, the battery material aging parameter of the battery in each OCV interval may be determined according to the correspondence between the OCV of the battery in each OCV interval and the battery capacity parameter in the collected BOL period and the correspondence between the OCV of the battery in each OCV interval and the battery capacity parameter in the collected target aging degree. The following describes a specific embodiment of S220.
In some embodiments, S220 may specifically include: step A1 and step A2 are performed for each of the N OCV intervals, and next, the following section of the embodiment of the present application will specifically describe step A1 and step A2 by taking the ith OCV interval as an example.
And A1, acquiring first data of an ith OCV interval and second data of the ith OCV interval.
First, for the first data, it may represent the correspondence of the OCV in each OCV section with the battery capacity parameter at the initial life period.
In one embodiment, the first data of the ith OCV interval may be implemented as an OCV composed of a plurality of data pairs 0i -Q i And (4) sequencing. Wherein one data pair comprises: an OCV value in the ith OCV interval, and a capacity Q of the battery at a BOL period corresponding to the OCV value i . Accordingly, the data pair may be expressed as an OCV 0i -Q i 。
Second, for the second data. The second data may represent a correspondence of the OCV in each OCV interval to a battery capacity parameter at a target aging degree.
In one embodiment, the second data may be implemented as an OCV composed of a plurality of data pairs 1i -Q i And (4) sequencing. Accordingly, the OCV 1i The specific content of the-Q sequence can be referred to the related description of the first data, and is not described herein again.
In addition, the first data and the second data may also be implemented in other forms, for example, the first data and the second data may be implemented as an OCV-Q curve. The embodiment of the present application does not limit the specific form of the first data and the second data.
In some embodiments, to improve accuracy, the first data and the second data may be collected when the battery meets a resting condition or a quasi-resting condition.
And step A2, determining battery material aging parameters under the target aging degree corresponding to each OCV interval according to the first data and the second data.
The battery material aging parameter may be determined in a variety of ways in step A2.
In this embodiment, the correspondence relationship between the OCV of the battery in each OCV interval and the battery capacity parameter in the collected BOL period and the correspondence relationship between the OCV of the battery in each OCV interval and the battery capacity parameter in the collected target aging degree may be used. Since the battery material aging causes a change in the correspondence relationship between the OCV and the battery capacity parameter in each OCV interval, the battery material aging parameter of the battery in each OCV interval can be accurately determined by the difference between the correspondence relationship between the OCV and the battery capacity parameter in each OCV interval at different times.
In one embodiment, if the second data is collected for the battery at the target aging degree, the step A2 may specifically include the step a21 and the step a22.
And step A21, estimating to obtain third data by using the first data.
First, for the third data in step a 21. The third data is used to represent the correspondence between the OCV in each OCV interval and the battery capacity parameter at the target degree of aging. In one example, the third data may be implemented as an OCV-Q sequence composed of a plurality of data pairs. Accordingly, the specific content of the OCV-Q sequence can be referred to the related description of the first data, and is not described herein again.
Next, in one example, if the first data in step a21 includes: positive electrode potential OCV corresponding to each of L battery capacity parameters in BOL period p0i And the cathode potential OCV corresponding to each of the L battery capacity parameters in the BOL period n0i . Wherein, the difference between the anode potential corresponding to each of the L battery capacity parameters in the initial life period and the cathode potential corresponding to the anode potentialThe values are within each OCV interval. Wherein L is an integer greater than or equal to 2. Illustratively, the first data may include an OCV p0i -Q i Sequence and OCV n0i -Q i And (4) sequencing.
Accordingly, step a21 may specifically include step a211 and step a212.
Step a211, for each capacity parameter, performs step a2111 to step a2113.
Step A2111, correcting the anode potential corresponding to each capacity parameter by using a first relational expression, wherein the relational coefficient of the first relational expression and the aging parameter W of the anode material pi And (4) correlating.
In one example, the coefficient of relationship in the first relational expression is an aging parameter W of the positive electrode material pi . Illustratively, the first relation may be represented as W pi *OCV p0i ＝OCV p1i . In the first relational expression, W is pi Is an unknown quantity.
Accordingly, if for each capacity parameter Q i Corresponding positive electrode potential OCV p0i OCV corrected by the first relational expression p1i Can be represented as W pi *OCV p0i . Accordingly, OCV p0i -Q i The sequence after being modified in step A211 can be represented as W pi *OCV p0i -Q i And (4) sequencing.
Step A2112, correcting the cathode potential corresponding to each capacity parameter by using a second relational expression, wherein the relational coefficient of the second relational expression is related to the aging parameter of the cathode material and the aging parameter of the active ions.
In one example, the coefficient of relationship in the second relationship includes an aging parameter W of the anode material ni And K i . Illustratively, the second relation may be represented as W ni *OCV n0i +K i ＝OCV n1i . In addition, W in the second relational expression ni And K i Is an unknown quantity.
Accordingly, if for each capacity parameter Q i Corresponding negative electrode potential OCV n0i OCV corrected by the first relational expression p1i Can be represented as W pi *OCV p0i . Accordingly, OCV p0i -Q i The sequence modified by step A212 may be denoted as W ni *OCV n0i +K i -Q i And (4) sequencing.
Step a2113, the difference between the corrected positive electrode potential and the corrected negative electrode potential is determined as the corrected OCV.
In one embodiment, for each Q value in the first data, it may be set at W pi *OCV p0i -Q i The OCV value corresponding to the sequence is determined as the corrected positive electrode potential corresponding to the Q value, and is set at W ni *OCV n0i +K i -Q i The OCV value corresponding to the sequence is determined as the corrected negative electrode potential corresponding to the Q value. Then, the difference between the corrected positive electrode potential corresponding to the Q value and the corrected negative electrode potential corresponding to the Q value is determined as the corrected OCV corresponding to the Q value. For the sake of convenience of distinction, the following sections of the embodiments of the present application represent the corrected OCV determined by step a2113 as the OCV
In the present embodiment, since the correspondence relationship between the positive electrode potential and the capacity parameter of the battery changes as the positive electrode material ages, and the correspondence relationship between the negative electrode potential and the capacity parameter of the battery changes as the negative electrode material ages, the positive electrode potential is corrected by the first relational expression relating to the positive electrode material aging parameter, and the negative electrode potential is corrected by the negative electrode material aging parameter and the active ion aging parameter. Then, the corrected OCV is related to the anode material aging parameter, the cathode material aging parameter and the active ion aging parameter, based on the corresponding relation between the corrected OCV and the capacity parameter under the same aging degree and the corresponding relation between the acquired OCV and the capacity parameter, the correlation among the anode material aging parameter, the cathode material aging parameter and the active ion aging parameter can be accurately solved, and based on the corrected OCV and the capacity parameter under the same aging degree, the calculation accuracy and the comprehensiveness of the material aging parameter are improved.
Step a212, third data is estimated based on the corrected OCVs corresponding to the L battery capacity parameters in the BOL period.
In one example, through steps A2111 to A2113, the Q value for each BOL period can be determined
Then, each Q value and the corresponding Q value
Form a data pair, and then generate a data pair based on multiple Q values
And (4) sequencing.
And step A22, determining battery material aging parameters under the target aging degree corresponding to each OCV interval according to the second data and the third data.
In the present embodiment, the third relationship of the correspondence between the OCV in each OCV interval and the battery capacity parameter at the target degree of aging can be estimated using the first data with the battery material aging parameter as an unknown amount. And then, through the third data obtained by estimation and the second data obtained by collection, the battery material aging parameter under the target aging degree corresponding to each OCV interval can be accurately calculated.
In one example, the second data OCV is acquired through the above-described steps a2111 to a2113 and step a214 1i -Q i Sequence and third data
And (4) sequencing. Since the second data is the acquired sequence and the third data is the estimated sequence and in the sequence
Containing an unknown quantity W pi 、W ni And K i Thus according to OCV 1i -Q i Sequence and
the sequence can be calculated to obtain W pi 、W ni And K i I.e., the aging parameter W of the battery material at the target aging degree corresponding to the i-th OCV interval pi 、W ni And K i . In a specific example, the battery material aging parameter W can be identified by polynomial fitting, least square method and the like pi 、W ni And K i . It should be noted that the battery material aging parameter can also be obtained by using other methods according to the actual scene and the specific requirements, which is not described in detail in the embodiments of the present application.
In addition, in some examples, in order to prevent the Q values of the adjacent OCV sections from being hopped, the maximum Q value of the smaller one of the adjacent OCV sections and the minimum Q value of the larger one of the adjacent OCV sections may be set to the same value. For example, the maximum Q value of the smaller OCV section may be forcibly set to the minimum Q value of the larger OCV section. The OCV values in the large OCV intervals are all larger than the OCV values in the small OCV intervals. Alternatively, both the maximum Q value of the smaller OCV interval and the minimum Q value of the larger OCV interval may be adjusted to be the average of the maximum Q value of the smaller OCV interval and the minimum Q value of the larger OCV interval, or the maximum Q value of the OCV interval and the minimum Q value of the larger OCV interval may be adjusted to be the same value according to actual situations and specific scenarios, which is not limited in this embodiment of the present application.
In addition, it should be noted that in the embodiment of the present application, the battery material aging parameter can also be obtained through calculation according to the correspondence between the OCV and the SOC, and the calculation manner is similar to the manner of obtaining the single cell material aging parameter through calculation according to the correspondence between the OCV and the Q, which is not described in detail in the embodiment of the present application again.
In another embodiment, if the first data and the second data are the curves shown in fig. 1, the amount of scaling of the first broken line L2 with respect to the first solid line L1 may be determined by image processing and determined as the aging parameter W of the cathode material p . Similarly, the amount of scaling and the amount of translation of the second dotted line L4 with respect to the second solid line L3 may be respectivelyDetermining an aging parameter W of the anode material n And the aging parameter K of the active ions.
In another embodiment, after the first data and the second data are acquired, the aging parameter W of the positive electrode material can be obtained by fitting through a data fitting algorithm p Aging parameter W of the cathode Material n And the aging parameter K of the active ions.
It should be noted that, in the embodiment of the present application, other manners may also be adopted to obtain the battery material aging parameter of each OCV interval, and this is not particularly limited in the embodiment of the present application.
And S230, generating battery material aging data corresponding to the target aging degree by using the battery material aging parameters corresponding to the N OCV intervals.
In some embodiments, the battery material aging data corresponding to the target degree of aging may be implemented in the form of a list. For example, the battery material aging data corresponding to the target aging degree may be recorded in the same row of the list.
According to the method for generating the battery material aging data, for the mixed battery with the positive electrode formed by mixing at least two materials, when the battery is in a target aging degree, due to the fact that the aging characteristics of the positive electrode material are not uniform in the whole OCV value range, a plurality of OCV intervals divided by the OCV value range can be determined firstly, and then battery material aging parameters corresponding to the N OCV intervals are determined. Due to the fact that the aging characteristic of the battery material in each COV interval can be accurately reflected by the aging parameter of the battery material in each COV interval, the aging characteristic of the material of the mixed material battery under the target aging degree can be accurately reflected by battery material aging data generated based on the battery material aging parameters corresponding to the N OCV intervals.
In some embodiments, fig. 3 is a schematic flow chart of another method for generating battery material aging data provided in the embodiments of the present application. Fig. 3 is different from fig. 2 in that the method for generating battery material aging data illustrated in fig. 3 further includes S240 and S250.
And S240, acquiring battery material aging data of the battery under M aging degrees. Wherein the M aging degrees include a target aging degree, M being an integer greater than or equal to 2.
First, for M aging levels. Which may reflect the degree of aging at various stages of the life cycle of the battery. In one example, in order to generate the material aging characteristics capable of accurately representing the whole life cycle of the compound material battery, M aging degrees in an aging degree value range corresponding to the life cycle may be determined. Illustratively, if the aging degree range corresponding to the life cycle of the battery is 0% to 100%, one aging degree may be selected every 1%, and correspondingly, the obtained M aging degrees may be 100%, 99%, … …, 75%, … …, 1%, 0%. It should be noted that, in the embodiment of the present application, M aging degrees may also be selected from the aging degree value range according to a specific scenario and an actual requirement in other manners, which is not limited in the embodiment of the present application.
Next, for the specific implementation of S240, in the present embodiment, M aging degrees may be sequentially used as target aging degrees, and then the battery material aging data of each aging degree is determined through the above-mentioned S210 to S230.
And S250, generating a corresponding relation between the aging degrees and the battery material aging data based on the battery material aging data under the M aging degrees.
Secondly, for the correspondence, it may directly include the battery material aging data at M aging levels.
In some embodiments, the correspondence may be implemented as a list of correspondences. Illustratively, table 1 is an exemplary correspondence table between the aging degree and the battery material aging data provided in the embodiments of the present application.
TABLE 1
As shown in table 1, for example, each row corresponds to a battery material aging data for a certain degree of aging. Then for each OCV interval, its multiple battery material aging parameters may be recorded in multiple columns of the same row. For example, if the first OCV interval includes 3 material aging parameters, the three aging parameters may be recorded in three consecutive columns, i.e., columns 2-4 of Table 1, respectively.
It should be noted that table 1 shows an example that the OCV value range is divided into 2 OCV intervals, and in an actual application process, the OCV value range may be divided into 3 or more OCV intervals, and a specific form of the OCV value range is similar to that in table 1, and details of the OCV value range are not described herein again in this embodiment of the present application.
In the embodiment of the present application, the method for generating the battery material aging data is described in detail through the above. In addition, after the battery material aging data is generated, the use process of the battery material aging data is involved in the subsequent process. Based on the method, the embodiment of the application also provides a method for determining the aging data of the battery material. The details of the method are described below.
Through the embodiment, M aging degrees of the battery in the whole life cycle can be selected, and the corresponding relation between the aging degrees and the battery material aging data is generated according to the battery material aging data under the M aging degrees. Therefore, the material aging degree in the whole life cycle of the battery can be accurately reflected by utilizing the corresponding relation between the aging degree and the battery material aging data.
Fig. 4 is a schematic flowchart of a method for determining battery material aging data according to an embodiment of the present disclosure. As shown in fig. 4, the determination method of the battery material aging data may include S410 and S420. In some embodiments, the execution subject of each step of the method for determining battery material aging data provided in the embodiment of the present application may be a device having a data processing function, such as a module or a component having a battery management function, such as a battery management system, and the like, which is not specifically limited in this embodiment of the present application.
And S410, acquiring the target aging degree of the battery. Wherein the target aging parameter is the aging degree of the battery at the target moment
In some embodiments, the target aging degree of the battery may refer to the related description in the above section of the embodiments of the present application, and details of the embodiments of the present application are not repeated herein.
In some specific scenarios, the present material aging data of the battery can be determined in real time during the use of the battery. Accordingly, the target aging degree in S410 may be the current aging degree of the battery. For example, the full charge capacity of the battery may be collected, and then the ratio of the collected full charge capacity to the rated capacity of the battery may be used as the current aging degree of the battery. The present example may refer to an acquisition time at which a full charge capacity is acquired.
And S420, determining target material aging data corresponding to the target aging degree in the preset corresponding relation between the aging degree and the battery material aging data.
Wherein the target material aging data comprises: and the N OCV intervals respectively correspond to battery material aging parameters.
In addition, the corresponding relationship between the preset aging degree and the battery material aging data in S420 may refer to the relevant contents in the above-mentioned part of the embodiment of the present application, and is not described herein again. As an example, continuing with the above table 1 as an example, if the target degree of aging is SOH =96%, the target material aging data may be determined from the battery material aging data corresponding to 96% of one row in table 1. Specifically, the target material aging data may include W corresponding to the first OCV interval p1 、W n1 And K 1 And W corresponding to the second OCV section p2 、W n2 And, K 2 。
In the method for determining aging data of a battery material according to the embodiment of the present application, for a mixed material battery in which a positive electrode is formed by mixing at least two materials, when the battery is in a target aging degree, since the aging characteristic of the positive electrode material is not uniform in the whole OCV value range, the target aging data of the battery material in each aging degree in the embodiment of the present application may include battery material aging parameters corresponding to N OCV intervals. Due to the fact that the aging characteristic of the battery material in each COV interval can be accurately reflected by the aging parameter of the battery material in each COV interval, the aging characteristic of the material of the mixed material battery under the target aging degree can be accurately reflected by battery material aging data generated based on the battery material aging parameters corresponding to the N OCV intervals.
In some embodiments, fig. 5 is a schematic flow chart of another method for determining battery material aging data provided in the embodiments of the present application.
Fig. 5 is different from fig. 4 in that the determination method of battery material aging data shown in fig. 5 further includes S430 and S440.
And S430, acquiring the aging degree of the battery at the moment before the target moment.
In some embodiments, the real-time aging degree of the battery may be acquired every preset time period. For a specific calculation manner of the real-time aging degree, reference may be made to the related description in the foregoing section of the embodiment of the present application, and details of the embodiment of the present application are not repeated herein.
And S440, determining the difference value between the aging degree of the previous moment and the target aging degree.
In addition, fig. 5 is different from fig. 4 in that S420 may specifically include: and under the condition that the difference value between the aging degree at the previous moment and the target aging degree is greater than a preset parameter threshold, determining battery material aging data corresponding to the target aging degree.
First, as for the preset parameter threshold, the preset parameter threshold may be set according to an actual scene and specific requirements, for example, the preset parameter threshold may be set to be 3% or 1%, which is not specifically limited in this application.
Second, for the specific implementation of S420, in some embodiments, the battery material aging data corresponding to the target aging degree may be updated to the current material aging data of the battery. For example, if the current material degradation data of the battery is the battery material degradation data at the previous time of the target time before performing S420. If the difference between the aging degree at the previous moment and the target aging degree is larger than the preset parameter threshold, the current material aging data of the battery can be updated to the battery material aging data of the target aging degree from the original battery material aging data at the previous moment.
In some embodiments, if the difference is smaller than or equal to the preset parameter threshold, the aging degree at the next time of the target time may be continuously obtained as a new target aging degree, then the battery material aging data corresponding to the new target aging degree is calculated, and then it is continuously determined whether the current material aging data of the battery needs to be updated by using S440 and S420.
Through the embodiment, the material aging data of the battery can be updated in time according to the aging degree of the battery in the using process of the battery. In addition, because the current material aging data of the battery is updated only when the difference value between the target aging degree and the aging degree at the previous moment is large enough, namely, is larger than the preset parameter threshold, on the premise of ensuring the accuracy of the current material aging data, the data processing pressure caused by frequent updating is avoided, and the updating efficiency is ensured.
In some embodiments, when the battery is in the target aging degree, in order to facilitate querying a battery capacity parameter corresponding to the real-time sampled OCV value according to the OCV sampled in real time by the battery during the use of the battery, a corresponding relationship between the OCV within the OCV value range and the battery capacity parameter may be generated in advance according to the target material aging data.
Correspondingly, fig. 6 is a schematic flowchart of a method for determining battery material aging data according to an embodiment of the present application. Fig. 6 is different from fig. 4 in that the determination method of battery material aging data shown in fig. 6 further includes S450.
And S450, determining the corresponding relation between the OCV in the value range of the battery OCV and the battery capacity parameter based on the target material aging data corresponding to the target aging degree.
Specifically, the target material aging data corresponding to the target aging degree includes: and aging parameters of the battery material under the target aging degree corresponding to the N OCV intervals. Accordingly, for each of the N OCV intervals, the correspondence between the OCV of the OCV interval and the battery capacity parameter may be determined according to the battery material aging parameter of the OCV interval. And then, generating the corresponding relation between the OCV and the battery capacity parameter in the OCV value range of the battery according to the corresponding relation between the OCV of each of the N OCV intervals and the battery capacity parameter.
According to the embodiment, the established corresponding relation between the OCV in the OCV value range and the battery capacity parameter can accurately represent the relation between the OCV and the Q of the battery with the target aging degree, so that after the OCV value is obtained in real time, the battery capacity parameter corresponding to the OCV value can be accurately inquired.
In one embodiment, the determined correspondence may be a correspondence of OCV to capacity, or may be a correspondence of OCV to SOC. Accordingly, if the correspondence relationship is a functional relationship, it may be an OCV-Q relationship or an OCV-SOC relationship. The correspondence curve may be an OCV-Q curve or an OCV-SOC curve. Illustratively, the OCV-Q curve and the OCV-SOC curve are similar to the curves shown in fig. 1, and the description thereof is omitted in this embodiment of the present application.
In some embodiments, if the OCV corresponds to the battery capacity parameter, the method comprises: and (3) a curve representing the change of the OCV along with the battery capacity parameter in the OCV value range.
Correspondingly, fig. 7 is a schematic flowchart of a method for determining battery material aging data according to another embodiment of the present application. Fig. 7 differs from fig. 6 in that S450 may specifically include S451 and S452.
S451, a curve segment representing the OCV of each OCV section as a function of the battery capacity parameter is determined based on the battery material aging parameter corresponding to each OCV section.
In one embodiment, after determining the battery material aging parameter for each OCV interval, an OCV-battery capacity parameter curve for the OCV interval at the target degree of aging may be determined based on a curve segment of OCV of the OCV interval over the BOL period as a function of the battery capacity parameter.
For example, the aging parameter W of the positive electrode material corresponding to the OCV interval may be set p And as a scaling coefficient, scaling the first curve segment of the battery in the BOL period in the OCV interval to obtain a second curve segment of the battery in the OCV interval under the target aging degree. Wherein, the first curve section and the second curve section both represent the positive electrode potential OCV corresponding to the OCV interval pos And the variation of the battery capacity parameter. As a specific example, both the first and second curve segments may be OCV-Q curve segments, or OCV-SOC curve segmentsAnd (6) line segments.
For another example, the aging parameter W of the negative electrode material corresponding to the OCV interval may be set n And as a scaling coefficient, and scaling and translating the third curve segment of the battery in the BOL period in the OCV interval by taking the aging parameter K of the active ions corresponding to the OCV interval as a translation coefficient, so as to obtain a fourth curve segment of the battery in the OCV interval under the target aging degree. Wherein, the third curve segment and the fourth curve segment both represent the negative electrode potential OCV corresponding to the OCV interval neg And the variation of the battery capacity parameter. As a specific example, the third and fourth curve segments may each be an OCV-Q curve segment, or an OCV-SOC curve segment.
And S452, splicing the corresponding curve sections of the N OCV intervals to obtain a curve.
In one embodiment, if the second curve segment and the fourth curve segment of each OCV interval can be obtained through S451, the second curve segments of the N OCV intervals can be spliced in S452 to obtain the positive electrode potential OCV of the battery under the target aging degree pos And a variation curve of a battery capacity parameter. And splicing the fourth curve segments of the N OCV intervals to obtain the negative electrode potential OCV of the battery under the target aging degree neg And a variation curve of a battery capacity parameter.
In another embodiment, if the second curve segment and the fourth curve segment of each OCV interval can be obtained at S451, the difference between the second curve segment and the fourth curve segment is calculated to obtain the curve segment of the OCV in the OCV interval along with the battery capacity parameter. Then in S452, the curve segments of the N OCV intervals are spliced to obtain a variation curve of the open-circuit voltage OCV and the battery capacity parameter of the battery under the target aging degree.
In one embodiment, since a proportional relationship exists between Q and SOC, after the OCV-Q curve is obtained through S451 and S452, the abscissa values of the points on the curve may be converted into a percentage form to obtain the OCV-SOC curve. Alternatively, the specific manner of conversion to percentage may be to divide the abscissa value of each point by the full-charge battery capacity at the target aging level, or alternatively, may be to divide the abscissa value of each point by the maximum Q value on the curve. The conversion form of the percentage is not particularly limited in the embodiment of the present application.
Alternatively, after obtaining the OCV-SOC curve in S451 and S452, the OCV-Q curve may be obtained by multiplying the abscissa value of each point on the curve by the full charge battery capacity at the target aging degree.
Through the embodiment, the characteristic curve which accurately reflects the change relation of the OCV of the battery along with the battery capacity parameter can be obtained, and a user can conveniently and quickly and accurately inquire the battery capacity corresponding to each OCV value in real time through the characteristic curve.
Based on the same application concept, the embodiment of the application provides a generation device of battery material aging data corresponding to the generation device, besides the generation method of the battery material aging data.
The following describes in detail a device for generating battery material aging data according to an embodiment of the present application, with reference to the accompanying drawings.
Fig. 8 is a schematic structural diagram of an apparatus for generating battery material aging data according to an embodiment of the present application. As shown in fig. 8, the generation apparatus 800 of the battery material aging data includes an OCV interval determination module 810, an aging parameter determination module 820, and an aging data determination module 830.
The OCV interval determination module 810 is configured to determine a plurality of open circuit voltage OCV intervals of the battery, where the N OCV intervals are divided by an OCV value range of the battery.
And an aging parameter determining module 820, configured to determine a battery material aging parameter corresponding to each of the N OCV intervals when the battery is at the target aging degree.
And the aging data determining module 830 is configured to generate battery material aging data corresponding to the target aging degree by using the battery material aging parameters corresponding to the N OCV intervals.
In some embodiments, the OCV interval determination module 810 is specifically configured to: and dividing the value range of the OCV according to the material characteristic parameters of the battery or the variation trend of the OCV of the battery along with the battery capacity to obtain N OCV intervals.
In some embodiments, the apparatus 800 for generating battery material aging data further includes an aging data acquisition module and a correspondence generation module.
The aging data acquisition module is used for acquiring battery material aging data of the battery under M aging degrees, wherein the M aging degrees comprise target aging degrees;
and the corresponding relation generating module is used for generating the corresponding relation between the aging degree and the battery material aging data based on the battery material aging data under the M aging degrees.
In some embodiments, the aging parameter determination module 820 specifically includes a data module unit and an aging parameter determination unit.
A data module unit, configured to obtain first data and second data for each of the N OCV intervals, where the first data represents a correspondence relationship between the OCV in each OCV interval and a battery capacity parameter at an initial life period, and the second data represents a correspondence relationship between the OCV in each OCV interval and a battery capacity parameter at a target aging degree;
and the aging parameter determining unit is used for determining the aging parameter of the battery material under the target aging degree corresponding to each OCV interval according to the first data and the second data aiming at each OCV interval in the N OCV intervals.
In some embodiments, the second data is collected for the battery at a target age.
Correspondingly, the aging parameter determining unit specifically includes: an evaluation subunit and an aging parameter determination subunit.
The estimation operator unit is used for estimating third data by utilizing the first data, and the third data is used for representing the corresponding relation between the OCV in each OCV interval and the battery capacity parameter under the target aging degree;
and the aging parameter determining subunit is used for determining the aging parameter of the battery material under the target aging degree corresponding to each OCV interval according to the second data and the third data.
In some embodiments, the first data comprises: the battery pack comprises a positive electrode potential corresponding to each of L battery capacity parameters in an initial life period, and a negative electrode potential corresponding to each of the L battery capacity parameters in the initial life period, wherein the difference value between the positive electrode potential corresponding to each of the L battery capacity parameters in the initial life period and the negative electrode potential corresponding to the positive electrode potential is within each OCV interval.
Accordingly, the evaluation subunit is specifically configured to:
for each capacity parameter, the following operations are performed: correcting the anode potential corresponding to each capacity parameter by using a first relational expression, wherein the relational coefficient of the first relational expression is related to the aging parameter of the anode material; correcting the negative electrode potential corresponding to each capacity parameter by using a second relational expression, wherein the relational coefficient of the second relational expression is related to the aging parameter of the negative electrode material and the aging parameter of the active ions; determining the difference value of the corrected anode potential and the corrected cathode potential as the corrected OCV;
and estimating to obtain third data based on the corrected OCV corresponding to each of the L battery capacity parameters in the initial life period.
In some embodiments, the battery material aging parameters include: at least one of the aging parameters of the positive electrode material, the aging parameters of the negative electrode material and the aging parameters of the active ions.
According to the generation device of the battery material aging data, for the mixed battery with the positive electrode formed by mixing at least two materials, when the battery is in the target aging degree, due to the fact that the aging characteristic of the positive electrode material is not uniform in the whole OCV value range, a plurality of OCV intervals divided by the OCV value range can be determined firstly, and then the battery material aging parameters corresponding to the N OCV intervals are determined. Due to the fact that the aging characteristic of the battery material in each COV interval can be accurately reflected by the aging parameter of the battery material in each COV interval, the aging characteristic of the material of the mixed material battery under the target aging degree can be accurately reflected by battery material aging data generated based on the battery material aging parameters corresponding to the N OCV intervals.
Other details of the apparatus for generating battery material aging data according to the embodiment of the present application are similar to the method for generating battery material aging data described above with reference to the examples shown in fig. 2 and fig. 3, and can achieve the corresponding technical effects, and are not described herein again for brevity.
Based on the same application concept, the embodiment of the application provides a determination device of battery material aging data corresponding to the determination method of battery material aging data.
The following describes a determination device for battery material aging data according to an embodiment of the present application in detail with reference to the accompanying drawings.
Fig. 9 is a schematic structural diagram of a device for determining battery material aging data according to an embodiment of the present application. As shown in fig. 9, the apparatus 900 for determining aging data of battery material includes an aging degree acquisition module 910 and an aging data determination module 920.
The aging degree obtaining module 910 is configured to obtain a target aging degree of the battery, where the target aging parameter is an aging degree of the battery at a target time.
An aging data determining module 920, configured to determine target material aging data corresponding to the target aging degree in a preset correspondence between the aging degree and the battery material aging data, where the target material aging data includes: and the N OCV intervals are formed by dividing the OCV value range of the battery.
In some embodiments, the aging degree acquiring module 910 is further configured to acquire the aging degree of the battery at a time previous to the target time.
The apparatus 900 for determining battery material aging data further comprises a difference calculation module. The difference value calculating module is used for determining the difference value between the aging degree of the previous moment and the target aging degree.
Accordingly, the aging data determining module 920 is specifically configured to: and determining battery material aging data corresponding to the target aging degree under the condition that the difference value is greater than a preset parameter threshold value.
In some embodiments, the apparatus 900 for determining battery material aging data further comprises a correspondence determining module.
The corresponding relation determining module is used for determining the corresponding relation between the OCV and the battery capacity parameter in the OCV value range of the battery based on the target material aging data corresponding to the target aging degree.
In some embodiments, the correspondence of OCV to battery capacity parameter includes: and (3) a curve representing the variation trend of the OCV along with the battery capacity parameter in the OCV value range.
The corresponding relation determining module specifically comprises a curve section determining unit and a curve splicing unit.
A curve segment determination unit for determining a curve segment representing variation of the OCV of each OCV section with the battery capacity parameter, based on the battery material aging parameter corresponding to each OCV section;
and the curve splicing unit is used for splicing the curve sections corresponding to the N OCV intervals to obtain a curve.
According to the device for determining the aging data of the battery material, for the mixed battery with the positive electrode formed by mixing at least two materials, when the battery is in the target aging degree, because the aging characteristic of the positive electrode material is not uniform in the whole OCV value range, the target material aging data under each aging degree in the embodiment of the application can comprise the battery material aging parameters corresponding to the N OCV intervals. Due to the fact that the aging characteristic of the battery material in each COV interval can be accurately reflected by the aging parameter of the battery material in each COV interval, the aging characteristic of the material of the mixed material battery under the target aging degree can be accurately reflected by battery material aging data generated based on the battery material aging parameters corresponding to the N OCV intervals.
Other details of the device for determining battery material aging data according to the embodiment of the present application are similar to the method for determining battery material aging data described above with reference to the examples shown in fig. 4 to 7, and can achieve corresponding technical effects, and are not described herein again for brevity.
Fig. 10 shows a hardware configuration diagram of a device for generating battery material aging data according to an embodiment of the present application.
The apparatus for generating battery material aging data may comprise a processor 1001 and a memory 1002 in which computer program instructions are stored.
Specifically, the processor 1001 may include a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement the embodiments of the present Application.
In some examples, the Memory 1002 may be a Read Only Memory (ROM). In one example, the ROM can be mask-programmed ROM, programmable ROM (PROM), erasable PROM (EPROM), electrically Erasable PROM (EEPROM), electrically Alterable ROM (EAROM), or flash memory, or a combination of two or more of these.
The processor 1001 reads and executes the computer program instructions stored in the memory 1002 to implement the method for generating battery material aging data in the embodiment shown in fig. 2 and 3, and achieve the corresponding technical effects achieved by the embodiment shown in fig. 2 and 3 executing the method for generating battery material aging data, which are not described herein again for brevity.
In one example, the generation device of battery material aging data may also include a communication interface 1003 and a bus 1010. As shown in fig. 10, the processor 1001, the memory 1002, and the communication interface 1003 are connected to each other via a bus 1010 to complete communication therebetween.
The communication interface 1003 is mainly used for implementing communication between modules, apparatuses, units and/or devices in this embodiment.
The generation device of the battery material aging data may perform the generation method of the battery material aging data in the embodiment of the present application, thereby implementing the generation method of the battery material aging data described in conjunction with fig. 2 and 3 and the generation apparatus of the battery material aging data described in conjunction with fig. 8.
In addition, in combination with the method for generating battery material aging data in the foregoing embodiments, the embodiments of the present application may be implemented by providing a computer storage medium. The computer storage medium having computer program instructions stored thereon; the computer program instructions, when executed by a processor, implement the method of generating battery material aging data of any of the above embodiments.
Fig. 11 is a schematic diagram illustrating a hardware configuration of a device for determining battery material aging data according to an embodiment of the present application.
The determination device of battery material aging data may comprise a processor 1101 and a memory 1102 in which computer program instructions are stored.
Specifically, the processor 1101 may include a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement the embodiments of the present Application.
In some examples, memory 1102 may be a Read Only Memory (ROM). In one example, the ROM can be mask-programmed ROM, programmable ROM (PROM), erasable PROM (EPROM), electrically Erasable PROM (EEPROM), electrically rewritable ROM (EAROM), or flash memory, or a combination of two or more of these.
The processor 1101 reads and executes the computer program instructions stored in the memory 1102 to implement the method for determining the battery material aging data in the embodiment shown in fig. 4 to 7, and achieve the corresponding technical effects achieved by the method/step for determining the battery material aging data executed in the example shown in fig. 4 to 7, which are not described herein again for brevity.
In one example, the device for determining battery material aging data may also include a communication interface 1103 and a bus 1110. As shown in fig. 11, the processor 1101, the memory 1102, and the communication interface 1103 are connected via a bus 1110 to complete communication therebetween.
The communication interface 1103 is mainly used for implementing communication between modules, apparatuses, units and/or devices in this embodiment of the present application.
The determination device of battery material aging data may execute the determination method of battery material aging data in the embodiment of the present application, thereby implementing the determination method of battery material aging data described in conjunction with fig. 4 to 7 and the determination apparatus of battery material aging data described in conjunction with fig. 9.
In addition, in combination with the method for determining the battery material aging data in the foregoing embodiments, the embodiments of the present application may be implemented by providing a computer storage medium. The computer storage medium having computer program instructions stored thereon; the computer program instructions, when executed by a processor, implement the method of determining battery material aging data of any of the above embodiments.
It is to be understood that the present application is not limited to the particular arrangements and instrumentality described above and shown in the attached drawings. A detailed description of known methods is omitted herein for the sake of brevity. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present application are not limited to the specific steps described and illustrated, and those skilled in the art can make various changes, modifications, and additions or change the order between the steps after comprehending the spirit of the present application.
The functional blocks shown in the above-described structural block diagrams may be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic Circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, plug-in, function card, or the like. When implemented in software, the elements of the present application are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine-readable medium or transmitted by a data signal carried in a carrier wave over a transmission medium or a communication link. A "machine-readable medium" may include any medium that can store or transfer information. Examples of a machine-readable medium include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio Frequency (RF) links, and so forth. The code segments may be downloaded via computer networks such as the internet, intranets, etc.
It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, the present application is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, may be performed in an order different from the order in the embodiments, or may be performed simultaneously.
Aspects of the present disclosure are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus, devices and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions/acts specified in the flowchart and/or block diagram block or blocks. Such a processor may be, but is not limited to, a general purpose processor, a special purpose processor, an application specific processor, or a field programmable logic circuit. It will also be understood that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware for performing the specified functions or acts, or combinations of special purpose hardware and computer instructions.
As described above, only the specific embodiments of the present application are provided, and it can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the system, the module and the unit described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again. It should be understood that the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive various equivalent modifications or substitutions within the technical scope of the present application, and these modifications or substitutions should be covered within the scope of the present application.
Claims (16)
1. A method for generating battery material aging data, wherein a positive electrode of a battery is formed by mixing at least two materials, the method comprising:
determining N OCV intervals formed by dividing the value range of the open-circuit voltage OCV of the battery, wherein N is an integer greater than or equal to 2;
determining battery material aging parameters corresponding to the N OCV intervals when the battery is in a target aging degree;
and generating battery material aging data corresponding to the target aging degree by using the battery material aging parameters corresponding to the N OCV intervals respectively.
2. The method of claim 1,
confirm the OCV interval that forms by the open circuit voltage OCV value range division of battery, include:
and dividing the OCV value range according to the material characteristic parameters of the battery or the variation trend of the OCV of the battery along with the battery capacity to obtain the N OCV intervals.
3. The method of claim 1, further comprising:
acquiring battery material aging data of the battery under M aging degrees, wherein the M aging degrees comprise the target aging degree, and M is a positive integer;
and generating a corresponding relation between the aging degrees and the battery material aging data based on the battery material aging data under the M aging degrees.
4. The method according to claim 1, wherein said determining a battery material aging parameter at a target aging level for each of said N OCV intervals comprises:
for each of the N OCV intervals, performing the following operations:
acquiring first data and second data, wherein the first data represents the corresponding relation between the OCV in each OCV interval and the battery capacity parameter in the initial life period, and the second data represents the corresponding relation between the OCV in each OCV interval and the battery capacity parameter under the target aging degree;
and determining the battery material aging parameters under the target aging degree corresponding to each OCV interval according to the first data and the second data.
5. The method of claim 4, wherein the second data is collected for the battery at the target age;
the determining, according to the first data and the second data, a battery material aging parameter under a target aging degree corresponding to each OCV interval specifically includes:
estimating third data by using the first data, wherein the third data is used for representing the corresponding relation between the OCV in each OCV interval and the battery capacity parameter under the target aging degree;
and determining a battery material aging parameter corresponding to each OCV interval under the target aging degree according to the second data and the third data.
6. The method of claim 5, wherein the first data comprises: the method comprises the steps that positive electrode potentials corresponding to L battery capacity parameters in an initial life period respectively and negative electrode potentials corresponding to the L battery capacity parameters in the initial life period respectively, wherein the difference value between the positive electrode potential corresponding to each of the L battery capacity parameters in the initial life period and the negative electrode potential corresponding to the positive electrode potential is in each OCV interval, and L is an integer greater than or equal to 2;
the estimating to obtain third data by using the first data specifically includes:
for each capacity parameter, the following operations are performed:
correcting the anode potential corresponding to each capacity parameter by using a first relational expression, wherein the relational coefficient of the first relational expression is related to the aging parameter of the anode material;
correcting the cathode potential corresponding to each capacity parameter by using a second relational expression, wherein the relational coefficient of the second relational expression is related to the cathode material aging parameter and the active ion aging parameter;
determining the difference value of the corrected positive electrode potential and the corrected negative electrode potential as a corrected OCV;
and estimating to obtain third data based on the corrected OCV corresponding to each of the L battery capacity parameters in the initial life period.
7. The method according to any one of claims 1 to 6,
the battery material aging parameters include: at least one of the aging parameters of the positive electrode material, the aging parameters of the negative electrode material and the aging parameters of the active ions.
8. A method for determining aging data of a battery material, wherein a positive electrode of the battery is formed by mixing a plurality of materials, is characterized by comprising the following steps:
acquiring a target aging degree of a battery, wherein the target aging parameter is the aging degree of the battery at a target moment;
determining target material aging data corresponding to the target aging degree in a preset corresponding relation between the aging degree and battery material aging data, wherein the target material aging data comprises: the battery material aging parameters corresponding to the N OCV intervals respectively are divided into the N OCV intervals, and N is an integer greater than or equal to 2.
9. The method of claim 8,
before determining the battery material aging data corresponding to the target aging degree, the method further comprises the following steps:
acquiring the aging degree of the battery at the moment before the target moment;
determining a difference between the aging degree of the previous moment and the target aging degree;
the determining of the target material aging data corresponding to the target aging degree specifically includes:
and determining battery material aging data corresponding to the target aging degree under the condition that the difference is larger than a preset parameter threshold.
10. The method of claim 8, wherein after determining target material aging data corresponding to the target aging level, the method further comprises:
and determining the corresponding relation between the OCV in the value range of the OCV of the battery and the battery capacity parameter based on the target material aging data corresponding to the target aging degree.
11. The method of claim 10,
the correspondence relationship between the OCV and the battery capacity parameter includes: a curve representing the variation trend of the OCV in the OCV value range along with the battery capacity parameter;
the determining, based on the target material aging data corresponding to the target aging degree, a corresponding relationship between the OCV and the battery capacity parameter within the OCV value range of the battery specifically includes:
determining a curve segment representing the variation of the OCV of each OCV interval along with the battery capacity parameter on the basis of the battery material aging parameter corresponding to each OCV interval;
and splicing the curve sections corresponding to the N OCV intervals to obtain the curve.
12. An apparatus for generating aging data of a battery material, wherein a positive electrode of the battery is formed by mixing at least two materials, the apparatus comprising:
the OCV interval determination module is used for determining N open-circuit voltage OCV intervals formed by dividing the value range of the open-circuit voltage OCV of the battery, wherein N is an integer greater than or equal to 2;
the aging parameter determining module is used for determining battery material aging parameters corresponding to the N OCV intervals when the battery is in a target aging degree;
and the aging data determining module is used for generating battery material aging data corresponding to the target aging degree by using the battery material aging parameters corresponding to the N OCV intervals respectively.
13. An apparatus for determining aging data of a battery material, a positive electrode of the battery being formed by mixing a plurality of materials, the apparatus comprising:
the aging degree acquiring module is used for acquiring a target aging degree of the battery, wherein the target aging parameter is the aging degree of the battery at a target moment;
the aging data determining module is used for determining target material aging data corresponding to the target aging degree in a preset corresponding relation between the aging degree and battery material aging data, wherein the target material aging data comprises: the battery material aging parameters corresponding to the N OCV intervals respectively are divided into the N OCV intervals, and N is an integer greater than or equal to 2.
14. An apparatus for generating data on the aging of a battery material, the apparatus comprising: a processor and a memory storing computer program instructions;
the processor reads and executes the computer program instructions to implement the method of generating battery material aging data according to any of claims 1-7.
15. An apparatus for determining aging data of a battery material, the apparatus comprising: a processor and a memory storing computer program instructions;
the processor reads and executes the computer program instructions to implement the method of determining battery material aging data according to any of claims 8-11.
16. A computer storage medium having stored thereon computer program instructions which, when executed by a processor, implement a method of generating battery material aging data according to any of claims 1 to 7, or a method of determining battery material aging data according to any of claims 8 to 11.
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