CN113420475A - Prediction method, device, equipment and medium for lithium deposition of three-electrode lithium ion battery - Google Patents

Prediction method, device, equipment and medium for lithium deposition of three-electrode lithium ion battery Download PDF

Info

Publication number
CN113420475A
CN113420475A CN202110676168.4A CN202110676168A CN113420475A CN 113420475 A CN113420475 A CN 113420475A CN 202110676168 A CN202110676168 A CN 202110676168A CN 113420475 A CN113420475 A CN 113420475A
Authority
CN
China
Prior art keywords
electrode
ion battery
lithium ion
value
electrochemical
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202110676168.4A
Other languages
Chinese (zh)
Other versions
CN113420475B (en
Inventor
陈思
何见超
杜建平
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Svolt Energy Technology Co Ltd
Original Assignee
Svolt Energy Technology Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Svolt Energy Technology Co Ltd filed Critical Svolt Energy Technology Co Ltd
Priority to CN202110676168.4A priority Critical patent/CN113420475B/en
Publication of CN113420475A publication Critical patent/CN113420475A/en
Priority to PCT/CN2022/096012 priority patent/WO2022262566A1/en
Application granted granted Critical
Publication of CN113420475B publication Critical patent/CN113420475B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2113/00—Details relating to the application field
    • G06F2113/08—Fluids
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/08—Thermal analysis or thermal optimisation
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02E60/10—Energy storage using batteries

Abstract

The invention discloses a prediction method, a device, equipment and a medium for lithium deposition of a three-electrode lithium ion battery, wherein the prediction method comprises the following steps: establishing an electrochemical-thermal coupling model of the three-electrode lithium ion battery; calibrating an electrochemical-thermal coupling model according to actually measured charging data of the three-electrode lithium ion battery at different multiplying powers; acquiring a first charging current value meeting a first boundary condition and a first value of an actually-measured decision point according to an electrochemical-thermal coupling model; actually measuring the voltage of the negative electrode and the reference electrode at a decision point; the first boundary condition comprises that the charging voltage is an upper limit cut-off voltage and the value of the simulation decision point is a first threshold; the simulation decision point is the difference value of the solid-phase potential and the liquid-phase potential at the interface of the cathode and the diaphragm; taking the first value of the actually measured decision point as a new first threshold value for simulation again; and if the value of the actually measured prejudgment point of the electrochemical-thermal coupling model is smaller than the new first threshold, the lithium deposition phenomenon exists. The scheme of the invention is convenient for accurately predicting the lithium deposition of the lithium ion battery.

Description

Prediction method, device, equipment and medium for lithium deposition of three-electrode lithium ion battery
Technical Field
The invention relates to the technical field of batteries, in particular to a method, a device, equipment and a medium for predicting lithium deposition of a three-electrode lithium ion battery.
Background
Lithium ion batteries are widely used in electronic products such as watches, mobile phones, and computers due to their excellent properties, such as high power and energy density. The current application of lithium ion batteries has been gradually expanded to electric vehicles. The lithium ion battery charging technology is one of the key points of the application and is also a hot spot of the research nowadays. In order to reduce the charging time of the power battery, large-current charging is often adopted, and the large-current charging of the power lithium ion battery can result in sudden temperature rise, capacity attenuation, service life reduction and the like of the battery. Through the research on the internal mechanism of the battery, the fact that lithium deposition in the battery is easy to occur under the condition of large-current charging is found, side reaction is caused in the battery, and further the battery is invalid. Therefore, the internal mechanism of the lithium ion battery is fully known, and the evaluation and detection of lithium deposition of the lithium ion battery are one of measures for ensuring the safe and reliable operation of the lithium ion battery.
Current methods for detecting lithium deposition include: the three-electrode testing method is a novel testing method, can distinguish interaction and contribution between an anode and a cathode and a whole battery system, and accurately inserts a reference electrode into the centers of the cathode and a diaphragm in the production process, and additionally adds two layers of diaphragms to play a role in protection. After the battery is manufactured, monitoring the reference potential of the negative electrode, and determining that lithium deposition exists once the potential is lower than 0V; or, the battery is disassembled, and then whether lithium is deposited on the negative plate is observed by using a representation means or directly, because the internal state of the battery is difficult to know in the using process of the battery, and the real condition of the battery is difficult to reflect only through parameters such as voltage, current, temperature and the like.
The battery disassembling method needs to disassemble a large number of batteries to form test data, and has higher test cost; the battery required by the three-electrode testing method needs to be manually placed with a reference electrode, the process is complex, the production period is long, in the later testing process, more testing channels are occupied, one or two layers of diaphragms are added at the position where the reference electrode is placed, the reference electrode is prevented from being in direct contact with a negative electrode material, when the three-electrode testing is used for detecting the actual working condition of the battery, the movement displacement inside lithium ions can be increased due to the increase of the diaphragms, the liquid phase potential distribution is influenced, the negative electrode can not truly reflect the lithium deposition state inside the battery to the reference potential, and the accuracy is low.
Disclosure of Invention
The embodiment of the invention provides a method, a device, equipment and a medium for predicting lithium deposition of a three-electrode lithium ion battery, so that the lithium deposition of the lithium ion battery can be predicted accurately, and the test cost is effectively saved.
In a first aspect, an embodiment of the present invention provides a method for predicting lithium deposition of a three-electrode lithium ion battery, including:
establishing an electrochemical-thermal coupling model of the three-electrode lithium ion battery based on an internal real structure of the three-electrode lithium ion battery;
calibrating the electrochemical-thermal coupling model according to the actually measured charging data of the three-electrode lithium ion battery with different multiplying powers;
acquiring a first charging current value meeting a first boundary condition and a first value of an actually-measured decision point according to the electrochemical-thermal coupling model; the actual measurement judgment point is the voltage difference between the negative porous electrode and the reference electrode of the lithium ion battery; the first boundary condition comprises that the charging voltage is an upper limit cut-off voltage and the value of the simulation decision point is a first threshold; the simulation decision point is the difference value of solid-phase potential and liquid-phase potential at the interface of a negative porous electrode and a diaphragm of the lithium ion battery;
taking the first value of the actually measured decision point as a new first threshold value for simulation; and when the simulation is carried out again, if the value of the actually measured decision point of the electrochemical-thermal coupling model is smaller than the new first threshold value, the lithium deposition phenomenon exists.
In a second aspect, an embodiment of the present invention further provides a device for predicting lithium deposition of a three-electrode lithium ion battery, including:
the coupling model establishing unit is used for establishing an electrochemical-thermal coupling model of the three-electrode lithium ion battery based on an internal real structure of the three-electrode lithium ion battery;
the model calibration unit is used for calibrating the electrochemical-thermal coupling model according to the actually measured charging data of the three-electrode lithium ion battery with different multiplying powers;
the threshold correction unit is used for acquiring a first charging current value meeting a first boundary condition and a first value of an actually-measured decision point according to the electrochemical-thermal coupling model; the actual measurement judgment point is the voltage difference between the negative porous electrode and the reference electrode of the lithium ion battery; the first boundary condition comprises that the charging voltage is an upper limit cut-off voltage and the value of the simulation decision point is a first threshold; the simulation decision point is the difference value of solid-phase potential and liquid-phase potential at the interface of a negative porous electrode and a diaphragm of the lithium ion battery;
the simulation prediction unit is used for taking the first value of the actually measured judgment point as a new first threshold value for simulation; and when the simulation is carried out again, if the value of the actually measured decision point of the electrochemical-thermal coupling model is smaller than the new first threshold value, the lithium deposition phenomenon exists.
In a third aspect, an embodiment of the present invention further provides a device for predicting lithium deposition of a three-electrode lithium ion battery, including:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement a method for predicting lithium deposition in a three-electrode lithium-ion battery according to any embodiment of the invention.
In a fourth aspect, embodiments of the present invention also provide a medium containing computer-executable instructions, which when executed by a computer processor, are configured to perform the method for predicting lithium deposition in a three-electrode lithium ion battery according to any of the embodiments of the present invention.
In the invention, an electrochemical-thermal coupling model is established based on an internal real structure of the three-electrode lithium ion battery, the electrochemical-thermal coupling model is calibrated through actually-measured charging data with different multiplying powers, and a first charging current value meeting a first boundary condition and a first value of an actually-measured decision point are obtained according to the electrochemical-thermal coupling model; the first boundary condition is that the charging voltage is the upper limit cut-off voltage and the value of the simulation decision point is the first threshold, the simulation decision point is the difference value between the solid phase potential and the liquid phase potential at the interface of the negative porous electrode and the diaphragm, the actual measurement decision point is the voltage difference between the negative porous electrode and the reference electrode of the lithium ion battery, and the first threshold is reconstructed according to the difference between the value of the simulation decision point and the value of the actual measurement decision point in the electrochemical-thermal coupling model, so that the lithium deposition is accurately simulated, a user can conveniently judge the lithium deposition phenomenon according to the reconstructed first threshold, the occurrence of the lithium deposition is effectively avoided, the charging capacity and the charging effect of the lithium ion battery are increased, and the safety of the battery is effectively improved.
Drawings
Fig. 1 is a schematic flowchart of a method for predicting lithium deposition of a three-electrode lithium ion battery according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of another method for predicting lithium deposition in a three-electrode lithium ion battery according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a one-dimensional electrochemical field according to an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of a three-dimensional thermal model provided by an embodiment of the present invention;
FIG. 5 is a schematic diagram of a coupling relationship between an electrochemical model and a solid thermal field provided by an embodiment of the present invention;
FIG. 6 is a schematic flow chart of another method for predicting lithium deposition in a three-electrode lithium ion battery according to an embodiment of the present invention;
fig. 7 is a comparison graph of a charging voltage-time simulation curve with different multiplying powers at a set external temperature and an actual measurement curve according to an embodiment of the present invention;
fig. 8 is a comparison graph of a simulation decision curve and an actual measurement decision curve when an actual measurement decision point is equal to a first threshold value according to an embodiment of the present invention;
FIG. 9 is an enlarged partial schematic view of region A of FIG. 8;
fig. 10 is a comparison graph of a simulation decision curve and an actual measurement decision curve when the simulation decision point is equal to the first threshold value according to the embodiment of the present invention;
FIG. 11 is a schematic partial discharge view of region B of FIG. 10;
fig. 12 is a schematic structural diagram of a prediction apparatus for lithium deposition of a three-electrode lithium ion battery according to an embodiment of the present invention;
fig. 13 is a schematic structural diagram of a prediction apparatus for lithium deposition of a three-electrode lithium ion battery according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
In the process of testing the three-electrode lithium ion battery, once the potential of the negative electrode to the reference electrode is found, namely, the voltage difference between the negative porous electrode and the reference electrode is less than 0V, the test is usually stopped. The tested three-electrode lithium ion battery is disassembled later, and the phenomenon of lithium precipitation does not occur on the contact interface of the negative electrode and the diaphragm, so that the phenomenon of lithium deposition cannot be accurately predicted by the three-electrode lithium ion battery. The invention provides a simulation method for predicting lithium deposition of a three-electrode lithium ion battery. The internal state of the three-electrode lithium ion battery is simulated, the influence of the diaphragm on the liquid phase potential distribution is fully considered, and the reference potential of the negative electrode of the three-electrode lithium ion battery is accurately monitored, so that the purposes of no lithium deposition and increased charging capacity are achieved.
The embodiment of the invention provides a method for predicting lithium deposition of a three-electrode lithium ion battery, as shown in fig. 1, fig. 1 is a flow diagram of the method for predicting lithium deposition of the three-electrode lithium ion battery provided by the embodiment of the invention, and the method comprises the following specific steps:
s110, establishing an electrochemical-thermal coupling model of the three-electrode lithium ion battery based on the internal real structure of the three-electrode lithium ion battery.
The three-electrode lithium ion battery comprises a positive electrode, a diaphragm, a reference electrode and a negative electrode, wherein the reference electrode can be a copper wire by way of example. A reference electrode is generally placed between the negative electrode and the separator side, and the potential of the negative electrode to the reference electrode can be monitored. In the process of designing the battery quick-charging strategy, a designer usually sets that the potential difference between the negative electrode of the three electrodes and the reference potential is higher than a threshold value of 0V so as to play a role in fully protecting the battery. In the actual process of manufacturing the three-electrode, one or two layers of diaphragms are added between the reference electrode and the negative electrode so as to prevent the reference electrode from directly contacting with the negative electrode material to cause internal short circuit and further influence the safety performance of the battery.
And S120, calibrating the electrochemical-thermal coupling model according to actually measured charging data of the three-electrode lithium ion battery with different multiplying powers.
S130, acquiring a first charging current value meeting a first boundary condition and a first value of an actually-measured decision point according to an electrochemical-thermal coupling model; the actually measured decision point is the voltage difference between the negative porous electrode and the reference electrode of the lithium ion battery; the first boundary condition comprises that the charging voltage is an upper limit cut-off voltage and the value of the simulation decision point is a first threshold; the simulation decision point is the difference between the solid-phase potential and the liquid-phase potential at the interface of the negative porous electrode and the diaphragm of the lithium ion battery.
Optionally, the first threshold may be zero. It should be noted that in this embodiment, both the measured decision point and the simulated decision point are parameters defined in this embodiment. The actual measurement decision point refers to the voltage difference between the negative porous electrode and the reference electrode of the lithium ion battery, the simulation decision point refers to the difference value between the solid-phase potential and the liquid-phase potential at the interface of the negative porous electrode and the diaphragm of the lithium ion battery, the actual measurement decision point has different values under the simulation of different charging states, and the simulation decision point also has different values. In the embodiment, the state that the charging voltage is the upper limit cut-off voltage and the value of the simulation decision point is the first threshold is simultaneously met through the simulation of the electrochemical-thermal coupling model, and the first value of the actual measurement decision point in the state is obtained, wherein the first value is different from the first threshold. Theoretically, it is considered that deposition occurs if the value of the simulation decision point is smaller than the first threshold, and for convenience of measurement, deposition occurs if the value of the actual measurement decision point is smaller than the first threshold, but the solid-phase potential is affected due to the existence of isolation, a certain error may exist between the actual measurement decision point and the simulation decision point, that is, when the value of the actual measurement decision point is smaller than the first threshold, deposition does not necessarily occur, so that a new first threshold needs to be selected for the actual measurement decision point to compensate for the error.
S140, taking the first value of the actually measured decision point as a new first threshold value for simulation; and if the value of the actually measured decision point of the electrochemical-thermal coupling model is smaller than the new first threshold value during the re-simulation, the lithium deposition phenomenon exists.
And compensating and correcting the first threshold of the simulation decision point through an electrochemical-thermal coupling model to obtain a new first threshold, wherein the new first threshold can avoid the influence of a diaphragm on the liquid phase potential distribution and accurately monitor the reference potential of the negative electrode of the three-electrode lithium ion battery. Then, in the simulation process of the electrochemical-thermal coupling model, if the value of the actually measured decision point of the electrochemical-thermal coupling model is smaller than the new first threshold, the lithium deposition phenomenon exists, and the voltage difference between the negative porous electrode and the reference electrode of the lithium ion battery can be controlled to be larger than the new first threshold as much as possible, so that the purposes of no lithium deposition and charging capacity increase are achieved.
In the invention, an electrochemical-thermal coupling model is established based on an internal real structure of the three-electrode lithium ion battery, the electrochemical-thermal coupling model is calibrated through actually-measured charging data with different multiplying powers, and a first charging current value meeting a first boundary condition and a first value of an actually-measured decision point are obtained according to the electrochemical-thermal coupling model; the first boundary condition is that the charging voltage is the upper limit cut-off voltage and the value of the simulation decision point is the first threshold, the simulation decision point is the difference value between the solid phase potential and the liquid phase potential at the interface of the negative porous electrode and the diaphragm, the actual measurement decision point is the voltage difference between the negative porous electrode and the reference electrode of the lithium ion battery, and the first threshold is reconstructed according to the difference between the value of the simulation decision point and the value of the actual measurement decision point in the electrochemical-thermal coupling model, so that the lithium deposition is accurately simulated, a user can conveniently judge the lithium deposition phenomenon according to the reconstructed first threshold, the occurrence of the lithium deposition is effectively avoided, the charging capacity and the charging effect of the lithium ion battery are increased, and the safety of the battery is effectively improved.
The above is the core idea of the present invention, and the technical solution in the embodiment of the present invention will be clearly and completely described below with reference to the drawings in the embodiment of the present invention. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present invention without any creative work belong to the protection scope of the present invention.
The embodiment of the invention discloses a simulation method for predicting lithium deposition of a three-electrode lithium ion battery, which mainly simulates the internal state of the three-electrode lithium ion battery through simulation, analyzes the difference between theoretical lithium deposition and actual three-electrode test, and finds a boundary threshold value of the lithium deposition through the difference to play a guiding role in optimizing a charging strategy for the three-electrode test. The boundary threshold is a boundary condition set for preventing lithium deposition from the negative electrode to the reference electrode during the three-electrode test, and is usually a first threshold, which may be 0V for example, and is often set to a value greater than 0V during the full life cycle. In theory, for the description of lithium deposition, the judgment condition generally adopted in the industry is that the difference between the solid-phase potential and the liquid-phase potential at the interface between the negative electrode and the diaphragm of the lithium ion battery is less than 0V, and then the lithium deposition phenomenon is considered to occur, so that 0V is used as the critical potential of the lithium deposition reaction. In the actual preparation process of the three-electrode lithium ion battery, the reference electrode is placed in the interface of the negative electrode and the diaphragm, and one or two more layers of diaphragms are generally added between the negative electrode and the reference electrode, so that the influence on the battery caused by internal short circuit caused by direct contact of the reference electrode and a negative electrode material is prevented. In the process of testing the three-electrode lithium ion battery, whether lithium is deposited is generally determined according to a negative electrode-to-reference potential of actually measured three-electrode data, specifically, if a difference between a potential at a negative current collector and a reference electrode potential is less than 0V, it is determined that a lithium deposition phenomenon occurs, and if the difference is 0V, the difference is used as a lithium deposition reaction critical potential. Designers usually judge the lithium deposition phenomenon based on an actually measured judgment point, and a certain difference exists between the method and a theoretical judgment method, so that negative effects are caused on the performance of the lithium ion battery.
In the embodiment, the first threshold of the actually measured judgment point is reset instead of being simply set to be zero, and the new first threshold can counteract the influence of the diaphragm on the liquid phase potential distribution, so that the abnormality existing between the actually measured judgment method and the theoretical judgment method can be counteracted.
Optionally, the invention can adopt a positive ternary material plus negative graphite system and a square laminated lithium ion battery with the nominal capacity of 104 Ah. According to the real internal state of the three-electrode lithium ion battery, assuming that when a reference electrode copper wire is placed, two layers of diaphragms are additionally arranged to cover the reference electrode, so that the three-electrode lithium ion battery is obtained. The invention provides a prediction method for lithium deposition of a three-electrode lithium ion battery, which deeply analyzes and simulates the real situation of the three-electrode lithium ion battery, and achieves the purposes of accurately designing a quick charging strategy of the battery and fully reducing the charging time.
On the basis of the foregoing embodiment, the electrochemical-thermal coupling model may include an electrochemical model and a three-dimensional thermal model coupled to each other, as shown in fig. 2, fig. 2 is a schematic flowchart of another prediction method for lithium deposition of a three-electrode lithium ion battery provided in an embodiment of the present invention, and specifically, the process of establishing the electrochemical-thermal coupling model of the battery cell may include the following steps:
s210, establishing a material domain of a one-dimensional electrochemical model; the material domain comprises a negative current collector, a negative porous electrode, a diaphragm, a reference electrode, a diaphragm, a positive porous electrode and a positive current collector which are arranged in sequence.
As shown in fig. 3, fig. 3 is a schematic structural diagram of a one-dimensional electrochemical field according to an embodiment of the present invention, where the embodiment establishes a one-dimensional finite element electrochemical geometric model of a multilayer structure, and the electrochemical model includes a negative electrode current collector, a negative electrode porous electrode, a diaphragm, a reference electrode, a diaphragm, a positive electrode porous electrode, and a positive electrode current collector, which are sequentially arranged in a one-dimensional manner. The reference electrode and the negative electrode porous electrode need to be separated by the diaphragm, the arrangement of the diaphragm can prevent short circuit between the negative electrode porous electrode and the reference electrode, and the three-electrode lithium ion battery at least comprises two layers of diaphragms, and exemplarily, the three-electrode lithium ion battery may comprise three layers of diaphragms: a first diaphragm, a second diaphragm, and a third diaphragm; the three-electrode lithium ion battery comprises a negative current collector, a negative porous electrode, a first diaphragm, a reference electrode, a second diaphragm, a third diaphragm, a positive porous electrode and a positive current collector which are sequentially arranged. It should be noted that the reference electrode may be disposed between the first separator and the second separator, or between the second separator and the third separator, which is not particularly limited in this embodiment, and preferably, the reference electrode may be disposed between the second separator and the third separator, and then two layers of separators are disposed between the negative porous electrode and the reference electrode, so as to further prevent the internal short circuit of the battery and improve the reliability of the lithium ion battery.
S220, defining material basic parameters of each material domain of the electrochemical model; the electric connection position is set as the left end point of a negative current collector, the electrode current density acquisition position is set as the right end point of a positive current collector, and initial battery charge distribution is defined; and customizing variables in the electrochemical model; variables in the electrochemical model include at least cell voltage, negative electrode material state of charge, positive electrode material state of charge, and temperature.
The material properties in the material domains may be defined before the parameters of the respective material domains of the electrochemical model are defined. Firstly, defining positive and negative electrode active material properties, and positive and negative electrode active material property bagComprises the following steps: the intrinsic open circuit voltage OCV of the positive and negative electrode materials, the solid phase diffusion coefficient Ds and the solid phase conductivity of the positive and negative electrode materials. For the intrinsic open-circuit voltage of the positive and negative electrode materials, testing the button half cells of the corresponding positive and negative electrode materials by using 0.01C-0.05C constant current charge and discharge, calculating the OCV of the positive and negative electrode materials through software, performing voltage reconstruction to obtain the OCV of the positive and negative electrode materials, and inserting the OCV curve of the positive and negative electrode materials into the material attribute; as for the solid phase diffusion coefficient, in reality, the shapes of graphite material particles are various, and even graphitized mesophase carbon spheres (MCMB) do not have perfect spherical shapes. The lithium ion diffusion coefficient is generally calculated using the specific surface area measured by the BET specific surface area test method, taking into consideration the actual shape of the particles. The true specific surface area S (cm) of the material is measured by an electrochemical method2/g) calculating the lithium ion diffusion coefficient, a more reliable value can be obtained, which is calculated by the following formula:
Figure BDA0003121213410000071
where ρ is the density (g/cm)3) Δ Q is the amount of electricity (mAh) flowing in the step interval, and m is the corresponding current i and t-1/2Slope of straight line relation (mA s)1/2) (ii) a t is time(s); the solid-phase conductivity of the anode and cathode materials is the default property in the material library.
Next, electrolyte properties and electrode properties are defined. The electrolyte properties can comprise liquid phase diffusion coefficient, liquid phase lithium ion conductivity, lithium ion migration number, thermodynamic relative activity coefficient of the electrolyte and the like, which are respectively measured by experiments, and literature values and material library default values; the electrode properties include electrical conductivity.
The defining of the material basis parameters of the respective material domains of the electrochemical model may specifically comprise: defining positive/negative porous electrode domains: the domain material is linked to the property of the positive/negative electrode active substance, and the particle size of the positive/negative electrode active particles, the exchange current density in the electrochemical reaction, the volume fraction of the positive/negative electrode active material, and the diffusion coefficient and the ionic conductivity of the electrolyte in the porous electrode are set; defining the membrane domain: the domain material is linked to the electrolyte material properties and sets the electrolyte conductivity and diffusion coefficient in the separator domain; defining positive/negative foil domains: the domain material links to the copper/aluminum foil material properties of the electrode properties.
Optionally, defining the initial battery charge distribution may include at least: initial voltage, battery capacity, battery cyclable material loss fraction and negative servo capacity excess fraction. Initial battery charge distribution needs to set initial voltage (or initial battery charge point state) and battery capacity, a recyclable substance loss fraction after battery assembly is set according to the actual design of a battery cell, the recyclable substance loss fraction can be 0-0.1, and a negative servo capacity surplus fraction, namely an NP ratio (ratio of negative capacity to positive capacity) in the battery cell design, is set, wherein the NP ratio can be 1-1.2.
S230, establishing a three-dimensional thermal model; the three-dimensional thermal model is a three-dimensional geometric model with the size consistent with that of the battery cell.
As shown in fig. 4, fig. 4 is a schematic structural diagram of a three-dimensional thermal model provided in an embodiment of the present invention, and the three-dimensional thermal model is maximally simplified into a rectangular parallelepiped with dimensions and directions consistent with the cell according to convergence of the three-dimensional thermal model and a calculated time cost.
S240, defining thermal parameters of the three-dimensional thermal model; the thermal parameters comprise the equivalent specific heat capacity, the expansion heat conductivity coefficient and the radial heat conductivity coefficient of the battery core; defining a heat source of the three-dimensional thermal model as an average heat generation power variable of an electrochemical body in the electrochemical model; setting convection heat fluxes and initial outside temperatures of six boundary surfaces of the three-dimensional thermal model; the temperatures of the cells in the three-dimensional thermal model are assigned to the various material domains of the electrochemical model.
Defining thermal parameters of a three-dimensional thermal model, namely defining the material attribute of a geometric domain, and giving the equivalent specific heat capacity, the equivalent expansion heat conduction coefficient and the radial heat conduction coefficient of an actual cell of the geometric domain of the extremely simple cell; the calculation of the equivalent specific heat capacity, the equivalent expansion heat conductivity and the radial heat conductivity is defined by the following formulas: radial equivalent thermal conductivity kz：
Figure BDA0003121213410000081
Spanwise equivalent thermal conductivity kr：kr∑idi＝∑ikidi。diIs the thickness of each layer of material; k is a radical ofiThermal conductivity of each layer of material.
Defining a heat source: the structure of the battery core is a good conductor, the heat generation is small and neglected, and the heat generation of the battery core mainly comes from the electrochemical heat generation in the charging and discharging processes of the battery, so that the heat generation power variable Qh (W/m3) calculated in the electrochemical model is filled. Defining the boundary heat flux: selecting all 6 boundary surfaces of the extremely-simple geometric model of the battery cell in the figure 4, and setting the convection heat flux to be 10-20 (W/m)2K) The external temperature is set to the initial external temperature. Further, the variables of the three-dimensional thermal model include heat generation power variables; the heat generation power variable is derived from the electrochemical model.
In summary, fig. 5 is a schematic diagram of a coupling relationship between an electrochemical model and a solid heat-generating field according to an embodiment of the present invention, and it can be seen that the coupling relationship between the one-dimensional electrochemical model and the three-dimensional thermal model is as shown in fig. 5, heat-generating power of the electrochemical model acts on a battery cell (the three-dimensional thermal model) to enable the battery cell to have temperature distribution, and a change in battery temperature affects battery performance, that is, the electrochemical model and the three-dimensional thermal model are in a bidirectional coupling manner.
In another example of the embodiment of the present invention, as shown in fig. 6, fig. 6 is a schematic flowchart of another method for predicting lithium deposition of a three-electrode lithium ion battery provided in the embodiment of the present invention, which details an obtaining process of a first threshold, where the method for predicting lithium deposition of a three-electrode lithium ion battery includes the following steps:
s310, establishing an electrochemical-thermal coupling model of the three-electrode lithium ion battery based on the internal real structure of the three-electrode lithium ion battery.
And S320, charging the manufactured three-electrode lithium ion battery with different multiplying powers, and recording the actually measured voltage value of the three-electrode lithium ion battery and the actually measured voltage difference between the negative porous electrode and the reference electrode.
S330, adjusting parameters of the electrochemical-thermal coupling model according to the actually measured voltage value and the actually measured voltage difference between the negative porous electrode and the reference electrode, so that the charging voltage-time simulation curve with different multiplying powers at the set temperature and the voltage difference-time simulation curve between the negative porous electrode and the reference electrode are matched with the actually measured curve.
The steps S320 to S330 are the process of calibrating the electrochemical-thermal coupling model according to the actually measured charging data of the three-electrode lithium ion battery with different multiplying powers. In this embodiment, the measured values, such as the measured voltage, the measured voltage difference between the negative porous electrode and the reference electrode, during the charging process of the battery are compared with the simulation data of the electrochemical-thermal coupling model, and the simulation data of the electrochemical-thermal coupling model is the same as or close to the data of the battery during the actual operation by continuously adjusting various parameters in the electrochemical-thermal coupling model. For example, as shown in fig. 7, fig. 7 is a comparison graph of charging voltage-time simulation curves and actual measurement curves with different magnifications under the set external temperature, which is provided by the embodiment of the present invention, in which the charging voltage-time simulation curves and the charging voltage-time simulation curves with different magnifications, such as 0.33C, 0.5C, 1C, 1.5C, 2C, and the like, under the same external temperature are respectively corrected by the present embodiment, so that the simulation curves are matched with the actual measurement curves, the normal temperature of 25 ℃ can be selected for the same external temperature, and it can be seen from fig. 7 that the simulation curves and the actual measurement curves tend to be consistent, and the calibration effect of the electrochemical-thermal coupling model is good.
S340, acquiring a first charging current value meeting a first boundary condition and a first value of an actually-measured decision point according to an electrochemical-thermal coupling model; the actually measured decision point is the voltage difference between the negative porous electrode and the reference electrode of the lithium ion battery; the first boundary condition comprises that the charging voltage is an upper limit cut-off voltage and the value of the simulation decision point is a first threshold; the simulation decision point is the difference between the solid-phase potential and the liquid-phase potential at the interface of the negative porous electrode and the diaphragm of the lithium ion battery.
S350, acquiring a second charging current value meeting a second boundary condition and a second value of the simulation decision point according to the electrochemical-thermal coupling model; the second boundary condition comprises that the charging voltage is an upper limit cut-off voltage and the value of the actually measured decision point is a first threshold value.
S360, comparing the first charging current value with the second charging current value; and comparing the difference between the first value of the actually measured decision point and the first threshold with the difference between the second value of the simulated decision point and the first threshold.
In the embodiment, the state that the charging voltage is the upper limit cut-off voltage and the value of the actual measurement judgment point is the first threshold is simultaneously met through the electrochemical-thermal coupling model simulation, and the second value of the simulation judgment point in the state is obtained, wherein the second value is different from the first threshold. Therefore, the deviation between the actual measurement judgment point and the simulation judgment point caused by the existence of the diaphragm is further verified. And the first charging current value and the second charging current value are compared, the difference value of the first value deviating from the first threshold value and the difference value of the second value deviating from the first threshold value are compared, and the deviation between the actual measurement judgment point and the simulation judgment point is observed and analyzed through specific data, for example, the influence of different diaphragms on the first threshold value of the actual measurement judgment point can be analyzed.
S370, taking the first value of the actually measured judgment point as a new first threshold value; and if the value of the actually measured prejudgment point of the electrochemical-thermal coupling model is smaller than the new first threshold, the lithium deposition phenomenon exists.
In the electrochemical-thermal coupling model, a certain temperature T0 is set, and by optimizing the current, a current value I1 is found that simultaneously satisfies a first boundary condition: first, the charging voltage is an upper cut-off voltage; second, the simulated decision point is equal to the first threshold V0, which may be 0V, and the measured decision point at this time, V1, is recorded.
In the electrochemical-thermal coupling model, a certain temperature T0 is set, and by optimizing the current, a current value I2 is found which simultaneously satisfies a second boundary condition: first, the charging voltage is an upper cut-off voltage; second, the measured decision point is equal to the first threshold V0, recording the simulated decision point V2 at that time.
Comparing a first current value I1 and a second current value I2 which meet the conditions, and a difference value | V1-V0| between an actually measured judgment point and a first threshold value, and a difference value | V2-V0| between a simulation judgment point and the first threshold value, comparing the two difference values, and obtaining the actually measured judgment point V1 when the simulation judgment point reaches the first threshold value V0 so as to reconstruct a new first threshold value V1.
In the embodiment, the actual measurement judgment point when the simulation judgment point reaches the first threshold value V0 is obtained, the simulation judgment point when the actual measurement judgment point reaches the first threshold value V0 is obtained, the difference between the actual measurement judgment point and the simulation judgment point is judged, and the actual measurement judgment point when the simulation judgment point reaches the first threshold value V0 is taken as the new first threshold value V0 to simulate the lithium deposition of the three-electrode lithium ion battery, so that the lithium deposition of the lithium ion battery can be accurately predicted, the test cost is effectively saved, and the charging capacity of the lithium ion battery is improved.
On the basis of the above embodiment, the prediction method of lithium deposition of the three-electrode lithium ion battery is described in detail by way of specific example:
acquiring parameters: a ternary NCM (lithium-ion battery) with 104Ah capacity laminated lithium-ion battery is adopted, the ternary NCM is used as a positive electrode, and graphite is used as a negative electrode. The basic physical parameters and electrochemical parameters of the battery with the model are obtained by methods such as experimental tests, literature query and the like, and are shown in table 1, wherein the table 1 is a battery parameter table of an electrochemical-thermal coupling model.
Table 1: battery parameter table of electrochemical-thermal coupling model
Figure BDA0003121213410000101
Figure BDA0003121213410000111
A one-dimensional electrochemical model and a three-dimensional thermal model are established according to the modeling process described above. And inputting the relevant parameters into the electrochemical-thermal coupling model to complete the preliminary modeling of the electrochemical-thermal coupling model.
The manufactured three-electrode lithium ion battery is charged at different multiplying powers (0.1C, 0.33C, 0.5C, 1C and 2C) at the normal temperature of 25 ℃, and the voltage of the three-electrode lithium ion battery, the potential of a negative electrode to a reference electrode and other data which change along with time are recorded.
And optimizing parameters in the electrochemical-thermal coupling model through the recorded measured data of the three-electrode lithium ion battery, returning and inputting the parameters into the model to obtain the optimized electrochemical-thermal coupling model, and finishing the final setting of the electrochemical-thermal coupling model.
Set at 25 ℃, using an electrochemical-thermal coupling model, given initial currents I0, I1, I2, … Ii, (Ii > I0) at an initial state of 0% SOC, a series of calculations were performed to reach a condition of satisfying (1. upper cutoff voltage 4.2V; 2. simulated decision point equal to first threshold V0 ═ 0V), and the first current value I1 ═ 240.24A (2.31C) and the voltage value V2 at the actually measured decision point were recorded as-0.0092V.
Set at 25 ℃, using an electrochemical-thermal coupling model, given initial currents I0, I1, I2, … Ii, (Ii > I0) at an initial state of 0% SOC, a series of calculations were performed to reach a condition of satisfying (1. upper cutoff voltage 4.2V; 2. measured decision point equal to first threshold V0 ═ 0V), and second current value I2 ═ 193.44A (1.86C) and voltage value V2 ═ 0.0076V at the simulated decision point were recorded at that time.
Fig. 8 is a comparison diagram of a simulation decision curve and an actual measurement decision curve when an actual measurement decision point is equal to a first threshold value, and fig. 9 is a partially enlarged schematic diagram of a region a in fig. 8. Fig. 10 is a comparison graph of a simulation decision curve and an actual measurement decision curve when a simulation decision point is equal to a first threshold value, and fig. 11 is a schematic partial discharge diagram of a region B in fig. 10. As can be seen from the above curves, the potential at the simulated decision point is slightly higher than the potential at the actually measured decision point, and based on the above results, I2< I1 was found by comparing the first current value I1 with 240.24a and the second current value I2 with 193.44a, which satisfy the conditions; comparing the difference value | V1-V0| -0.0076V, | V2-V0| -0.0092V between the actual measurement judgment point and the simulation judgment point, the current is found to be large, and the difference value is larger. And when the simulation judgment point reaches a preset threshold value V0 which is 0V, an actual measurement judgment point V2 which is-0.0092V is obtained, and a new threshold value V2 which is-0.0092V is reconstructed.
Based on the same idea, the embodiment of the invention also provides a prediction device for lithium deposition of the three-electrode lithium ion battery. The prediction device for lithium deposition of a three-electrode lithium ion battery provided by the embodiment is suitable for predicting the lithium deposition of the three-electrode lithium ion battery. Fig. 12 is a schematic structural diagram of a device for predicting lithium deposition of a three-electrode lithium ion battery according to an embodiment of the present invention, and as shown in fig. 12, the device for predicting lithium deposition of a three-electrode lithium ion battery includes:
the coupling model establishing unit 51 is used for establishing an electrochemical-thermal coupling model of the three-electrode lithium ion battery based on the internal real structure of the three-electrode lithium ion battery;
the model calibration unit 52 is used for calibrating the electrochemical-thermal coupling model according to the actually measured charging data of the three-electrode lithium ion battery with different multiplying powers;
the threshold correction unit 53 acquires a first charging current value meeting a first boundary condition and a first value of an actually measured decision point according to the electrochemical-thermal coupling model; the actually measured decision point is the voltage difference between the negative porous electrode and the reference electrode of the lithium ion battery; the first boundary condition comprises that the charging voltage is an upper limit cut-off voltage and the value of the simulation decision point is a first threshold; the simulation decision point is the difference value of solid-phase potential and liquid-phase potential at the interface of a negative porous electrode and a diaphragm of the lithium ion battery;
the simulation prediction unit 54 takes the first value of the actually measured decision point as a new first threshold; and if the value of the actually measured prejudgment point of the electrochemical-thermal coupling model is smaller than the new first threshold, the lithium deposition phenomenon exists.
The device for predicting the lithium deposition of the three-electrode lithium ion battery provided by the embodiment of the disclosure can execute the method for predicting the lithium deposition of the three-electrode lithium ion battery provided by any embodiment of the disclosure, and has corresponding functional modules and beneficial effects of the execution method.
It should be noted that, the units and modules included in the apparatus are merely divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be implemented; in addition, specific names of the functional units are only used for distinguishing one functional unit from another, and are not used for limiting the protection scope of the embodiments of the present disclosure.
Referring now to fig. 13, which illustrates a prediction apparatus 600 for lithium deposition of a three-electrode lithium-ion battery suitable for implementing embodiments of the present disclosure, the prediction apparatus 600 for lithium deposition of a three-electrode lithium-ion battery in fig. 13 may be a terminal device or a server. The terminal device in the embodiments of the present disclosure may include, but is not limited to, a mobile terminal such as a mobile phone, a notebook computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet computer), a PMP (portable multimedia player), a vehicle terminal (e.g., a car navigation terminal), and the like, and a stationary terminal such as a digital TV, a desktop computer, and the like. The device shown in fig. 13 is only an example, and should not bring any limitation to the function and the scope of use of the embodiments of the present disclosure.
As shown in fig. 13, the prediction apparatus 600 for lithium deposition of a three-electrode lithium ion battery may include a processing device 601 (e.g., a central processing unit, a graphic processing unit, etc.) which may perform various appropriate actions and processes according to a program stored in a Read-Only Memory (ROM) 602 or a program loaded from a storage device 608 into a Random Access Memory (RAM) 603. In the RAM603, various programs and data necessary for the operation of the prediction apparatus 600 for lithium deposition of a three-electrode lithium ion battery are also stored. The processing device 601, the ROM602, and the RAM603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
Generally, the following devices may be connected to the I/O interface 605: input devices 606 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 607 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 608 including, for example, tape, hard disk, etc.; and a communication device 609. The communication means 609 may allow the prediction device 600 of lithium deposition of a three-electrode lithium ion battery to communicate with other devices wirelessly or by wire to exchange data. While fig. 13 illustrates a predictive apparatus 600 for lithium deposition in a three electrode lithium ion battery having various devices, it is to be understood that not all of the illustrated devices are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a non-transitory computer readable medium, the computer program containing program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication means 609, or may be installed from the storage means 608, or may be installed from the ROM 602. The computer program, when executed by the processing device 601, performs the above-described functions defined in the generation method of video data of the embodiment of the present disclosure.
The apparatus provided by the embodiment of the present disclosure and the method for predicting lithium deposition of a three-electrode lithium ion battery provided by the above embodiment belong to the same disclosure concept, and technical details that are not described in detail in the present embodiment may be referred to the above embodiment, and the present embodiment has the same beneficial effects as the above embodiment.
The disclosed embodiments provide a computer storage medium having a computer program stored thereon, which when executed by a processor implements the method for predicting lithium deposition in a three-electrode lithium ion battery provided by the above embodiments.
It should be noted that the computer readable medium in the present disclosure can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a Read-Only Memory (ROM), an Erasable Programmable Read-Only Memory (EPROM) or FLASH Memory (FLASH), an optical fiber, a portable compact disc Read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer readable signal medium may comprise a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (Hyper Text Transfer Protocol), and may interconnect with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the apparatus; or may be separate and not incorporated into the device.
The computer readable medium carries one or more programs which, when executed by the apparatus, cause the apparatus to:
establishing an electrochemical-thermal coupling model of the three-electrode lithium ion battery based on an internal real structure of the three-electrode lithium ion battery;
calibrating the electrochemical-thermal coupling model according to the actually measured charging data of the three-electrode lithium ion battery with different multiplying powers;
acquiring a first charging current value meeting a first boundary condition and a first value of an actually-measured decision point according to the electrochemical-thermal coupling model; the actual measurement judgment point is the voltage difference between the negative porous electrode and the reference electrode of the lithium ion battery; the first boundary condition comprises that the charging voltage is an upper limit cut-off voltage and the value of the simulation decision point is a first threshold; the simulation decision point is the difference value of solid-phase potential and liquid-phase potential at the interface of a negative porous electrode and a diaphragm of the lithium ion battery;
taking the first value of the actually measured judgment point as a new first threshold value; and if the value of the actually measured prejudgment point of the electrochemical-thermal coupling model is smaller than the new first threshold, the lithium deposition phenomenon exists.
Computer program code for carrying out operations for the present disclosure may be written in any combination of one or more programming languages, including but not limited to an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted 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-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present disclosure may be implemented by software or hardware. The names of the units and modules do not limit the units and modules in some cases, and for example, the data generation module may be described as a "video data generation module".
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Part (ASSP), a System On Chip (SOC), a Complex Programmable Logic Device (CPLD), and the like.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments illustrated herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims (10)

1. A method for predicting lithium deposition of a three-electrode lithium ion battery is characterized by comprising the following steps:
establishing an electrochemical-thermal coupling model of the three-electrode lithium ion battery based on an internal real structure of the three-electrode lithium ion battery;
calibrating the electrochemical-thermal coupling model according to the actually measured charging data of the three-electrode lithium ion battery with different multiplying powers;
acquiring a first charging current value meeting a first boundary condition and a first value of an actually-measured decision point according to the electrochemical-thermal coupling model; the actual measurement judgment point is the voltage difference between the negative porous electrode and the reference electrode of the lithium ion battery; the first boundary condition comprises that the charging voltage is an upper limit cut-off voltage and the value of the simulation decision point is a first threshold; the simulation decision point is the difference value of solid-phase potential and liquid-phase potential at the interface of a negative porous electrode and a diaphragm of the lithium ion battery;
taking the first value of the actually measured decision point as a new first threshold value for simulation; and when the simulation is carried out again, if the value of the actually measured decision point of the electrochemical-thermal coupling model is smaller than the new first threshold value, the lithium deposition phenomenon exists.
2. The method for predicting lithium deposition in a three-electrode lithium ion battery according to claim 1, wherein before the first value of the actually measured decision point is used as the new first threshold, the method further comprises:
acquiring a second charging current value meeting a second boundary condition and a second value of the simulation decision point according to the electrochemical-thermal coupling model; the second boundary condition comprises that the charging voltage is an upper limit cut-off voltage and the value of the actually measured decision point is a first threshold value.
3. The method of predicting lithium deposition for a three-electrode lithium ion battery of claim 2, further comprising:
comparing the first charging current value and the second charging current value; and comparing the difference between the first value of the actual measurement judgment point and the first threshold with the difference between the second value of the simulation judgment point and the first threshold.
4. The method of claim 1, wherein establishing an electrochemical-thermal coupling model of the three-electrode lithium ion battery comprises:
establishing a material domain of a one-dimensional electrochemical model; the material domain comprises a negative current collector, a negative porous electrode, a diaphragm, a reference electrode, a diaphragm, a positive porous electrode and a positive current collector which are arranged in sequence;
defining material basis parameters for each material domain of the electrochemical model; the electric connection position is set as the left end point of a negative current collector, the electrode current density acquisition position is set as the right end point of a positive current collector, and initial battery charge distribution is defined; and customizing variables in the electrochemical model; variables in the electrochemical model at least comprise battery voltage, negative electrode material state of charge, positive electrode material state of charge and temperature;
establishing a three-dimensional thermal model; the three-dimensional thermal model is a three-dimensional geometric model with the size consistent with that of the battery cell;
defining thermal parameters of a three-dimensional thermal model; the thermal parameters comprise the equivalent specific heat capacity, the expansion heat conduction coefficient and the radial heat conduction coefficient of the battery cell; defining a heat source of the three-dimensional thermal model as an average heat generation power variable of an electrochemical body in the electrochemical model; setting convection heat fluxes and initial outside temperatures of six boundary surfaces of the three-dimensional thermal model; assigning the temperature of the cells in the three-dimensional thermal model to respective material domains of the electrochemical model.
5. The method of predicting lithium deposition for a three-electrode lithium ion battery of claim 4, wherein the initial battery charge profile comprises:
initial voltage, battery capacity, battery cyclable material loss fraction and negative servo capacity excess fraction.
6. The method for predicting lithium deposition in a three-electrode lithium ion battery according to claim 1, wherein calibrating the electrochemical-thermal coupling model according to the measured charging data of the three-electrode lithium ion battery at different multiplying powers comprises:
charging the manufactured three-electrode lithium ion battery with different multiplying powers, and recording an actually measured voltage value of the three-electrode lithium ion battery and an actually measured voltage difference between the negative porous electrode and the reference electrode;
and adjusting parameters of the electrochemical-thermal coupling model according to the actually measured voltage value and the actually measured voltage difference between the negative porous electrode and the reference electrode, so that the charging voltage-time simulation curve with different multiplying powers at the set temperature and the voltage difference-time simulation curve between the negative porous electrode and the reference electrode are matched with the actually measured curves.
7. The method of predicting lithium deposition for a three-electrode lithium ion battery of claim 1, wherein the three-electrode lithium ion battery comprises three layers of separator: a first diaphragm, a second diaphragm, and a third diaphragm;
the three-electrode lithium ion battery comprises a negative current collector, a negative porous electrode, a first diaphragm, a second diaphragm, a reference electrode, a third diaphragm, a positive porous electrode and a positive current collector which are sequentially arranged.
8. An apparatus for predicting lithium deposition in a three-electrode lithium ion battery, comprising:
the coupling model establishing unit is used for establishing an electrochemical-thermal coupling model of the three-electrode lithium ion battery based on an internal real structure of the three-electrode lithium ion battery;
the model calibration unit is used for calibrating the electrochemical-thermal coupling model according to the actually measured charging data of the three-electrode lithium ion battery with different multiplying powers;
the threshold correction unit is used for acquiring a first charging current value meeting a first boundary condition and a first value of an actually-measured decision point according to the electrochemical-thermal coupling model; the actual measurement judgment point is the voltage difference between the negative porous electrode and the reference electrode of the lithium ion battery; the first boundary condition comprises that the charging voltage is an upper limit cut-off voltage and the value of the simulation decision point is a first threshold; the simulation decision point is the difference value of solid-phase potential and liquid-phase potential at the interface of a negative porous electrode and a diaphragm of the lithium ion battery;
the simulation prediction unit is used for taking the first value of the actually measured judgment point as a new first threshold value for simulation; and when the simulation is carried out again, if the value of the actually measured decision point of the electrochemical-thermal coupling model is smaller than the new first threshold value, the lithium deposition phenomenon exists.
9. An apparatus for predicting lithium deposition in a three-electrode lithium ion battery, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of predicting lithium deposition for a three electrode lithium ion battery of any of claims 1-7.
10. A medium containing computer executable instructions for performing the method of predicting lithium deposition for a three electrode lithium ion battery of any one of claims 1-7 when executed by a computer processor.
CN202110676168.4A 2021-06-18 2021-06-18 Prediction method, device, equipment and medium for lithium deposition of three-electrode lithium ion battery Active CN113420475B (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN202110676168.4A CN113420475B (en) 2021-06-18 2021-06-18 Prediction method, device, equipment and medium for lithium deposition of three-electrode lithium ion battery
PCT/CN2022/096012 WO2022262566A1 (en) 2021-06-18 2022-05-30 Prediction method and apparatus for lithium deposition of three-electrode lithium ion battery, and device and medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110676168.4A CN113420475B (en) 2021-06-18 2021-06-18 Prediction method, device, equipment and medium for lithium deposition of three-electrode lithium ion battery

Publications (2)

Publication Number Publication Date
CN113420475A true CN113420475A (en) 2021-09-21
CN113420475B CN113420475B (en) 2023-01-24

Family

ID=77788983

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110676168.4A Active CN113420475B (en) 2021-06-18 2021-06-18 Prediction method, device, equipment and medium for lithium deposition of three-electrode lithium ion battery

Country Status (2)

Country Link
CN (1) CN113420475B (en)
WO (1) WO2022262566A1 (en)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113937340A (en) * 2021-12-17 2022-01-14 中创新航科技股份有限公司 Battery cell, battery and charging method
CN114459963A (en) * 2022-03-25 2022-05-10 蜂巢能源科技股份有限公司 Method for evaluating lithium ion diffusion capacity in positive electrode material
CN114839251A (en) * 2022-03-18 2022-08-02 清华大学 Defect identification method, defect identification device, potential sensor, battery, medium and product
CN115424671A (en) * 2022-08-26 2022-12-02 上海玫克生储能科技有限公司 Lithium ion battery performance analysis and prediction method, storage medium and electronic equipment
WO2022262566A1 (en) * 2021-06-18 2022-12-22 蜂巢能源科技股份有限公司 Prediction method and apparatus for lithium deposition of three-electrode lithium ion battery, and device and medium

Families Citing this family (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116050106A (en) * 2022-12-26 2023-05-02 蜂巢能源科技(马鞍山)有限公司 Simulation method and system for thick electrode through hole design
CN116680938B (en) * 2023-08-04 2023-10-20 通达电磁能股份有限公司 Modeling method and system for lithium battery electric heating coupling model
CN117233617B (en) * 2023-11-14 2024-02-13 苏州易来科得科技有限公司 Lithium ion battery aging test method, storage medium and equipment under circulation working condition
CN117289683A (en) * 2023-11-21 2023-12-26 晶科储能科技有限公司 Energy storage battery management system testing method and system, electronic equipment and storage medium
CN117542431B (en) * 2024-01-10 2024-03-19 清华四川能源互联网研究院 Electrochemical simulation parameter determination method and device for lithium ion battery electrolyte

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2015228324A (en) * 2014-05-31 2015-12-17 トヨタ自動車株式会社 Battery system
CN107516750A (en) * 2017-08-03 2017-12-26 国联汽车动力电池研究院有限责任公司 A kind of method and device for determining lithium ion battery safe charging condition
CN108427077A (en) * 2018-02-27 2018-08-21 山西长征动力科技有限公司 A kind of experimental method for analysing lithium using reference electrode monitoring cathode
CN109872002A (en) * 2019-03-04 2019-06-11 汤依伟 Prediction technique, device and the electronic equipment of lithium metal deposition
CN110165314A (en) * 2019-04-30 2019-08-23 蜂巢能源科技有限公司 Battery battery core performance parameter acquisition methods and acquisition device

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113420475B (en) * 2021-06-18 2023-01-24 蜂巢能源科技有限公司 Prediction method, device, equipment and medium for lithium deposition of three-electrode lithium ion battery

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2015228324A (en) * 2014-05-31 2015-12-17 トヨタ自動車株式会社 Battery system
CN107516750A (en) * 2017-08-03 2017-12-26 国联汽车动力电池研究院有限责任公司 A kind of method and device for determining lithium ion battery safe charging condition
CN108427077A (en) * 2018-02-27 2018-08-21 山西长征动力科技有限公司 A kind of experimental method for analysing lithium using reference electrode monitoring cathode
CN109872002A (en) * 2019-03-04 2019-06-11 汤依伟 Prediction technique, device and the electronic equipment of lithium metal deposition
CN110165314A (en) * 2019-04-30 2019-08-23 蜂巢能源科技有限公司 Battery battery core performance parameter acquisition methods and acquisition device

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2022262566A1 (en) * 2021-06-18 2022-12-22 蜂巢能源科技股份有限公司 Prediction method and apparatus for lithium deposition of three-electrode lithium ion battery, and device and medium
CN113937340A (en) * 2021-12-17 2022-01-14 中创新航科技股份有限公司 Battery cell, battery and charging method
CN113937340B (en) * 2021-12-17 2022-03-08 中创新航科技股份有限公司 Battery cell, battery and charging method
CN114839251A (en) * 2022-03-18 2022-08-02 清华大学 Defect identification method, defect identification device, potential sensor, battery, medium and product
CN114459963A (en) * 2022-03-25 2022-05-10 蜂巢能源科技股份有限公司 Method for evaluating lithium ion diffusion capacity in positive electrode material
CN114459963B (en) * 2022-03-25 2024-04-02 蜂巢能源科技股份有限公司 Evaluation method for lithium ion diffusion capacity in positive electrode material
CN115424671A (en) * 2022-08-26 2022-12-02 上海玫克生储能科技有限公司 Lithium ion battery performance analysis and prediction method, storage medium and electronic equipment

Also Published As

Publication number Publication date
CN113420475B (en) 2023-01-24
WO2022262566A1 (en) 2022-12-22

Similar Documents

Publication Publication Date Title
CN113420475B (en) Prediction method, device, equipment and medium for lithium deposition of three-electrode lithium ion battery
WO2020135481A1 (en) Battery charging method and device
Mastali et al. Electrochemical-thermal modeling and experimental validation of commercial graphite/LiFePO4 pouch lithium-ion batteries
CN104991980B (en) The electrochemical mechanism modeling method of lithium ion battery
CN112949101B (en) Method, device, equipment and medium for acquiring pulse charging and discharging maximum current of battery
Chaturvedi et al. Modeling, estimation, and control challenges for lithium-ion batteries
US10539621B2 (en) Method and apparatus for identifying a battery model
CN108169683B (en) Simulation analysis method for internal distribution characteristics of lithium ion battery with multilayer laminated structure
JP5815134B2 (en) Li-ion battery life prediction method and system
CN111062137B (en) Lithium ion battery performance prediction model, construction method and application thereof
CN113051852B (en) Method, device and equipment for acquiring contact resistance of battery cell structural member and storage medium
CN109738806B (en) Method, device and medium for simulating heat generation rate of battery
CN112180278B (en) Electric vehicle power battery performance nondestructive testing method considering voltage hysteresis characteristic
CN113253131B (en) Method and device for determining charging and discharging performance of battery core, storage medium and electronic equipment
Lin et al. Simplification and efficient simulation of electrochemical model for Li-ion battery in EVs
Zhang et al. Numerical investigation on the thermal behavior of cylindrical lithium-ion batteries based on the electrochemical-thermal coupling model
Jin et al. Comparison of Li-ion battery degradation models for system design and control algorithm development
CN115453377B (en) Battery pack life prediction method based on electrochemistry-thermal-aging and three-dimensional order reduction
Muñoz et al. Parameter optimization of an electrochemical and thermal model for a lithium-ion commercial battery
CN114280480A (en) Method for decomposing direct current internal resistance of lithium ion battery based on numerical model
Song et al. Anomalous diffusion models in frequency-domain characterization of lithium-ion capacitors
Garrick et al. Modeling electrochemical transport within a three-electrode system
Inui et al. Detailed estimation method of heat generation during charge/discharge in lithium‐ion battery using equivalent circuit
Su et al. Modeling the effects of state of charge and temperature on calendar capacity loss of nickel-manganese-cobalt lithium-ion batteries
CN114547903A (en) Method for predicting cycle life of lithium battery based on electrochemical-thermal coupling model

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant