Charging control method and related equipment

Abstract

The invention discloses a charging control method and related equipment, and relates to the field of charging control, and the method comprises the steps: inputting a to-be-analyzed current waveform into a simulation model to obtain simulation data information of the to-be-analyzed current waveform, the simulation model being a lithium dendrite-based phase field model and a battery network model, establishing a constraint condition information and secondary current distribution module; determining a target charging current based on the simulation data information of the current waveform to be analyzed; and controlling the battery to perform charging operation through the target charging current.

Description

Technical Field

[0001] The present invention relates to the field of charging control, and more specifically, to a charging control method and related equipment. Background Art

[0002] With the rapid popularization of electric vehicles, charging technology has become one of the key factors restricting its further development. At present, most electric vehicles adopt a constant current constant voltage (CC-CV) charging strategy. Although this strategy is mature and widely used, it still has many shortcomings in charging efficiency, charging time and temperature control.

[0003] Lithium dendrites generated during charging can have a serious impact on the safety and life of the battery, and may even cause safety accidents such as short circuits and fires. In order to at least solve some of the above problems, it is urgent to provide a building extraction method and related equipment with better cross-domain extraction capabilities. Summary of the invention

[0004] A series of simplified concepts are introduced in the Summary of the Invention section, which will be further described in detail in the Detailed Description of the Invention section. The Summary of the Invention section of this application does not mean to attempt to define the key features and essential technical features of the claimed technical solution, nor does it mean to attempt to determine the scope of protection of the claimed technical solution.

[0005] In a first aspect, the present application proposes a charging control method, comprising:

[0006] Inputting the current waveform to be analyzed into the simulation model to obtain simulation data information of the current waveform to be analyzed, wherein the simulation model is established based on the phase field model of lithium dendrites, the battery network model, constraint information and the secondary current distribution module;

[0007] Determine the target charging current based on the simulation data information of the current waveform to be analyzed;

[0008] The battery charging operation is controlled by the above target charging current.

[0009] In a feasible implementation manner, the phase field model of the lithium dendrites is constructed based on the order parameter equation, the lithium ion diffusion equation and the charge conservation equation.

[0010] In a feasible implementation, the above order parameter equation is a nonlinear model of changes in time and space combined with the order parameter equation of Butler-Volmer dynamics;

[0011] The above lithium ion diffusion equation is the Nernst-Planck equation;

[0012] The above charge conservation equation is the current density conservation equation described by Poisson's equation.

[0013] In a feasible implementation, the battery grid model is a phase field simulation model of the lithium plating morphology in a two-dimensional half-cell electrodeposition system, and the battery network model is discretized using quadrilateral grids and an adaptive grid technology.

[0014] In a feasible implementation manner, the constraint condition information includes boundary condition information, lithium ion concentration information, and upper and lower boundary potential information.

[0015] In a feasible implementation, the secondary current distribution module is used to describe the relationship between electrode kinetics and impedance.

[0016] In a feasible implementation manner, the above-mentioned simulation data information includes space utilization and aspect ratio;

[0017] The above-mentioned current waveform to be analyzed is generated based on a sine wave.

[0018] In a second aspect, the present application proposes a charging control device, comprising:

[0019] An acquisition unit, used for inputting the current waveform to be analyzed into a simulation model to obtain simulation data information of the current waveform to be analyzed, wherein the simulation model is established based on a phase field model of lithium dendrites, a battery network model, constraint information and a secondary current distribution module;

[0020] A determination unit, configured to determine a target charging current based on the simulation data information of the current waveform to be analyzed;

[0021] The control unit is used to control the battery to perform a charging operation according to the target charging current.

[0022] In a third aspect, an electronic device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor is configured to implement the steps of the charging control method of any one of the first aspects described above when executing the computer program stored in the memory.

[0023] In a fourth aspect, the present application further proposes a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the charging control method of any one of the first aspects is implemented.

[0024] In summary, the charging control method proposed in the embodiment of the present application includes: inputting the current waveform to be analyzed into the simulation model to obtain the simulation data information of the current waveform to be analyzed, wherein the above-mentioned simulation model is established based on the phase field model of lithium dendrites, the battery network model, the constraint information and the secondary current distribution module; determining the target charging current based on the simulation data information of the above-mentioned current waveform to be analyzed; and controlling the battery to perform charging operation through the above-mentioned target charging current. The method proposed in the present application, by inputting the designed current waveform into the simulation system based on the lithium dendrite phase field model for simulation, this scheme can accurately analyze the influence of different current waveforms on the growth of lithium dendrites, and finally determine the target charging current that can significantly inhibit the growth of lithium dendrites. This method effectively reduces the safety risk of the battery during the charging process and improves the service life of the battery. Compared with the traditional constant current and constant voltage charging method, the sinusoidal charging current accurately designed and simulated and analyzed in the present application can improve the charging efficiency while shortening the charging time. This is of great significance to improving the popularity and user experience of electric vehicles. This application can effectively design a charging current waveform with a lower temperature rise by simulating and analyzing the effect of the current waveform on the temperature change inside the battery, avoiding battery damage or performance degradation caused by excessively high temperatures, thereby further improving the safety and stability of the battery. This application provides solid theoretical support and practical guidance for the application of sinusoidal charging current in electric vehicle charging through the construction of a simulation model and the optimization design of the current waveform, filling the gap in current research and having important innovation and practicality. In summary, this application not only proposes a new electric vehicle charging strategy, but also significantly improves the safety, efficiency and temperature control during the charging process through in-depth simulation analysis and optimization design, providing a better solution for the rapid charging of electric vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present specification. Also, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0026] Figure 1 A schematic diagram of a charging control method provided in an embodiment of the present application;

[0027] Figure 2 A schematic diagram of a phase field sequence variable change provided in an embodiment of the present application;

[0028] Figure 3 A schematic diagram of a typical CC mode fast charging current curve of a lithium-ion battery provided in an embodiment of the present application;

[0029] Figure 4A schematic diagram of an SRC1 curve provided in an embodiment of the present application;

[0030] Figure 5 A schematic diagram of an SRC2 curve provided in an embodiment of the present application;

[0031] Figure 6 A schematic diagram of an aspect ratio provided in an embodiment of the present application;

[0032] Figure 7 A schematic diagram of the effect of different sinusoidal current cycles on the growth of lithium dendrites provided in an embodiment of the present application;

[0033] Figure 8 A schematic diagram of a curve showing a change in lithium dendrite space utilization rate under different sinusoidal current cycle conditions provided in an embodiment of the present application;

[0034] Fig. 9 A schematic diagram of the effect of different charging rates on the growth of lithium dendrites provided in an embodiment of the present application;

[0035] Fig.10 A schematic diagram of a lithium dendrite space utilization rate change curve under different sinusoidal current charging rate conditions provided in an embodiment of the present application;

[0036] Fig.11 A schematic diagram of the effect of an SRC2 charging method with different duty cycles on lithium dendrites provided in an embodiment of the present application;

[0037] Fig.12 A schematic diagram of a lithium dendrite space utilization rate change curve under different sinusoidal current duty cycle conditions provided in an embodiment of the present application;

[0038] Fig.13 Schematic diagram of a lithium dendrite height-to-width ratio change curve under different sinusoidal current duty cycles provided in an embodiment of the present application

[0039] Fig.14 A schematic diagram of the structure of a charging control device provided in an embodiment of the present application;

[0040] Fig.15 A schematic diagram of the structure of an electronic device for a charging control method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0041] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices. The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments.

[0042] Unlike the traditional mesoscale method that regards the interface as a zero-dimensional sharp interface, the phase field method characterizes the interface between different phases with phase field variables. In order to avoid the problems encountered by the previous sharp model in solving the problem, the phase field method introduces a continuous state variable that can smoothly transition the phase transformation in the calculation, namely the order parameter or phase field parameter. Figure 2 As shown, ξ is introduced as the phase field order variable. When lithium ions gain electrons to become lithium atoms, they are deposited on the electrode surface to form a solid phase, that is, ξ = 1. When lithium ions are far away from the electrode and no redox reaction occurs, ξ = 0.

[0043] See also Figure 1 , is a schematic diagram of a charging control method provided in an embodiment of the present application, which may specifically include:

[0044] S110, inputting the current waveform to be analyzed into a simulation model to obtain simulation data information of the current waveform to be analyzed, wherein the simulation model is established based on a phase field model of lithium dendrites, a battery network model, constraint information and a secondary current distribution module;

[0045] Exemplarily, the current waveform to be analyzed is input into a simulation model to obtain simulation data information of the current waveform. The simulation model is established based on the phase field model of lithium dendrites, the battery network model, constraint information and the secondary current distribution module. Phase field model of lithium dendrites: This model is used to simulate the growth process of lithium dendrites. The phase field method can accurately describe the migration and deposition behavior of lithium ions in the electrode, which is crucial to understanding the lithium dendrites that may appear during the charging process.

[0046] Battery network model: used to simulate the current distribution inside the battery and analyze how the current flows inside the battery in combination with the electrochemical reaction kinetics, which is very important for evaluating the behavior of the battery under different current waveforms.

[0047] Constraint information: refers to the boundary conditions and initial conditions imposed during the simulation process, such as temperature, pressure, etc. These conditions affect the overall reaction process of the battery.

[0048] Secondary current distribution module: This module is used to simulate the local changes and distribution of current to ensure that the current distribution during the simulation process is consistent with the actual situation.

[0049] By inputting the current waveform to be analyzed into the simulation model, the system can obtain the electrochemical reaction characteristics that may be caused by the current waveform during actual use, and these characteristics form the basis of the simulation data information.

[0050] S120, determining a target charging current based on the simulation data information of the current waveform to be analyzed;

[0051] Exemplarily, the target charging current is determined based on the simulation data information obtained from the simulation model. Specifically, by analyzing the indicators related to lithium dendrite growth, temperature rise control, and battery safety performance in the simulation data information, the system can identify a charging current waveform that can effectively inhibit lithium dendrite growth, optimize charging efficiency, and reduce safety risks. This charging current waveform is the target charging current. The target charging current is the optimal charging current obtained by accurately adjusting the charging strategy while meeting the battery safety and performance requirements.

[0052] S130, controlling the battery to perform charging operation according to the target charging current.

[0053] Exemplarily, the battery is charged by a target charging current. The charging operation is intended to apply the previously determined target charging current to ensure that the battery can effectively suppress the growth of lithium dendrites during the charging process, optimize the charging efficiency, and reduce temperature rise and other potential safety risks. Through this charging process, the overall performance of the battery can be improved, the battery life can be extended, and the incidence of battery accidents can be reduced.

[0054] In summary, the method proposed in this application, by inputting the designed current waveform into the simulation system based on the lithium dendrite phase field model for simulation, this scheme can accurately analyze the influence of different current waveforms on the growth of lithium dendrites, and finally determine the target charging current that can significantly inhibit the growth of lithium dendrites. This method effectively reduces the safety risk of the battery during the charging process and improves the service life of the battery. Compared with the traditional constant current and constant voltage charging method, the sinusoidal charging current accurately designed and simulated and analyzed in this application can improve the charging efficiency while shortening the charging time. This is of great significance for improving the popularity and user experience of electric vehicles. This application can effectively design a charging current waveform with lower temperature rise by simulating and analyzing the influence of the current waveform on the internal temperature change of the battery, avoiding battery damage or performance degradation caused by excessive temperature, thereby further improving the safety and stability of the battery. Through the construction of the simulation model and the optimization design of the current waveform, this application provides solid theoretical support and practical guidance for the application of sinusoidal charging current in electric vehicle charging, fills the gap in current research, and has important innovation and practicality. In summary, this application not only proposes a new electric vehicle charging strategy, but also significantly improves the safety, efficiency and temperature control during the charging process through in-depth simulation analysis and optimization design, providing a better solution for the fast charging of electric vehicles.

[0055] In some examples, the phase field model of lithium dendrites is constructed based on the order parameter equation, the lithium ion diffusion equation and the charge conservation equation.

[0056] Exemplarily, the order parameter equation is used to describe the behavior of phase transition during the growth of lithium dendrites. In the phase field model, the order parameter is used to distinguish materials of different phases. In the simulation of lithium dendrite growth, the order parameter can describe the interface evolution process between lithium dendrites and electrolytes. The introduction of the order parameter equation enables the model to capture the kinetic characteristics of the formation and growth of lithium dendrites, thus providing a basis for the morphological prediction of lithium dendrites.

[0057] The lithium ion diffusion equation is used to describe the diffusion behavior of lithium ions in electrode materials. The diffusion of lithium ions is one of the important factors affecting the growth of lithium dendrites. This equation simulates the migration of lithium ions during charging by describing the spatial distribution and time evolution of lithium ions. The diffusion equation provides the model with key information about how lithium ions move inside the electrode and how they affect dendrite growth.

[0058] The charge conservation equation ensures the conservation of charge in the entire electrochemical system. During the battery charging process, charge conservation is one of the basic physical principles. The charge conservation equation can simulate the changes in current distribution and potential difference at different locations. The introduction of this equation enables the model to more accurately reflect the actual situation of the electrochemical reaction, especially the impact on current and potential during the growth of lithium dendrites.

[0059] The above-mentioned lithium dendrite phase field model combines the order parameter equation, lithium ion diffusion equation and charge conservation equation to construct a comprehensive simulation framework for analyzing and predicting the growth behavior of lithium dendrites. In specific applications, the model simulates the evolution of lithium dendrites during the charging process by inputting different charging current waveforms, and evaluates the inhibitory effect of different current waveforms on dendrite growth.

[0060] Through this simulation model, the charging current waveform that has a significant inhibitory effect on the growth of lithium dendrites can be identified, and the target charging current is determined based on the simulation results. Ultimately, this target charging current is used in actual battery charging operations to reduce the growth of lithium dendrites and improve battery safety and charging efficiency.

[0061] In some examples, the order parameter equation is an order parameter equation of a nonlinear model that varies in time and space combined with Butler-Volmer dynamics;

[0062] The above lithium ion diffusion equation is the Nernst-Planck equation;

[0063] The above charge conservation equation is the current density conservation equation described by Poisson's equation.

[0064] For example, considering that dendrite growth in solid electrolyte is affected by stress, elastic energy density is introduced. The overall method is based on free energy. The total Gibbs free energy during lithium dendrite growth is composed of Möllnholz free energy density, gradient energy density, electrostatic energy density, and elastic energy density, which can be expressed as:

[0065]

[0066] Where f ch represents the Möllnholtz free energy density, f grad represents the gradient energy density, f else represents the electrostatic energy density, f σ represents the elastic energy density, which is related to the stress state of each phase during the deposition of metallic lithium. c represents the concentration distribution of lithium in the electrolyte, and φ represents the distribution of electric potential.

[0067] f ch (ξ)=Wξ 2 (1-ξ) 2 (2)

[0068] In the formula, Wξ 2 (1-ξ) 2 is a basic double-well function, describing the two equilibrium states at the electrode interface and in the electrolyte respectively. W represents the barrier height.

[0069] Since the driving force of the electrode reaction associated with the overpotential is much greater than the driving force associated with the thermodynamic interface energy, the rate of change of the phase interface is linearly related to the decrease in the interface free energy and exponentially related to the driving force of the electrode reaction. The nonlinear model describing the change of the order parameter in time and space combined with the Butler-Volmer kinetics can be expressed as:

[0070]

[0071] Where c + Lithium ion concentration, L σ is the interface mobility, L η is the reaction-related constant, h(ξ) is the interpolation function, h'(ξ) is the first-order derivative of the interpolation function, F is the Faraday constant, R is the gas constant, and T is the temperature. It can be seen that the driving force of interface migration is mainly provided by interface free energy and motor reaction.

[0072] The Nernst-Planck equation is used to describe the diffusion transport of lithium ions. In the electrodeposition process, it is assumed that the solid lithium is immobile and does not diffuse, the effect of electron transport is ignored, and the material consumption at the interface is considered.

[0073] Ignoring the migration of anions, the partial differential equation describing the evolution of lithium ion concentration over time is expressed as:

[0074]

[0075] Where D eff is the diffusion coefficient, c s is the site density of metallic lithium, c 0 is the standard volume concentration of the electrolyte solution. Diffusion coefficient D eff Determined by the interpolation function.

[0076] Assuming that the system is electrically neutral, the Poisson equation can be used to describe the conservation of current density as follows:

[0077]

[0078] Where σ eff is the conductivity.

[0079] In some examples, the battery grid model is a phase field simulation model of the lithium plating morphology in a two-dimensional half-cell electrodeposition system, and the battery network model is discretized using a quadrilateral grid and an adaptive grid technology.

[0080] Exemplarily, the battery grid model is used to simulate the phase field simulation model of the lithium plating morphology, which is constructed based on a two-dimensional half-cell electrodeposition system. In this model, the plating growth process of the lithium-ion battery is simulated as an evolution process in a two-dimensional space. The core of the model is to discretize the simulation area using quadrilateral grid discretization technology to ensure the accuracy of the simulation results and the controllability of the calculation. In order to further improve the calculation efficiency and accuracy, the adaptive grid technology is used, and the density of the grid can be dynamically adjusted as needed to better capture the subtle changes in the growth process of lithium dendrites.

[0081] In some examples, the constraint condition information includes boundary condition information, lithium ion concentration information, and upper and lower boundary potential information.

[0082] For example, boundary condition information is used to define the boundary behavior of the simulation area, which determines the flow and potential distribution of lithium ions at the electrode boundary. Lithium ion concentration information describes the distribution state of lithium ions inside the battery. The change in lithium ion concentration is an important factor in determining the battery reaction rate and dendrite growth. The upper and lower boundary potential information refers to the potential difference between the upper and lower boundaries of the battery during the simulation process. These potential information have an important influence on simulating the electric field distribution and electrochemical reactions during the actual charging process.

[0083] In some examples, the secondary current distribution module described above is used to describe the relationship between electrode kinetics and impedance.

[0084] For example, the secondary current distribution module is used to describe the relationship between electrode dynamics and impedance. By simulating the current distribution of electrode materials during the charge and discharge process, the dynamic response behavior of the electrode and the influence of electrode impedance on the current distribution are evaluated. This module can help understand the flow of current inside the electrode under different charging current conditions, thereby predicting the possible lithium dendrite formation area and morphology.

[0085] Specifically, COMSOL Multiphysics software can be used to perform the simulation using the finite element method. A phase field simulation of the lithium plating morphology was performed in a two-dimensional half-cell electrodeposition system with a size of 6×6μm2. The simulation domain was discretized using a quadrilateral grid with a minimum size of 0.005μm and a maximum size of 0.05μm. Adaptive grid refinement was used to improve the convergence and accuracy of the simulation. Adiabatic boundary conditions were used for the four boundaries of the phase field variables and the left and right boundaries of the concentration and potential. The upper and lower boundaries of the lithium ion concentration were set to 1M and 0M, respectively, and the upper and lower boundary potentials were set to 0.1V and 0V, respectively. A "secondary current distribution" module was added to simulate the electrochemical reaction at the interface between the electrolyte and the electrode. The growth of lithium dendrites can be obtained by solving the control equations (3)(4)(5).

[0086] In some examples, the simulation data information includes space utilization and aspect ratio;

[0087] The above-mentioned current waveform to be analyzed is generated based on a sine wave.

[0088] For example, a typical CC mode fast charge current curve for a standard lithium-ion battery is as follows: Figure 3 As shown. In the CC charging stage, the battery cell maintains I MAX The stable current flows until the battery cell reaches its maximum terminal voltage level V MAX This simulation designs a battery cell with a 1C charging rate constant current as I MAX , the charging time is T under the secondary current charging condition, which is used as the control group.

[0089] In the SRC1 charging mode, I MAX As the basic value, the upper peak current is C1 rate, and the lower peak current is C2 rate, ensuring that the charging capacity in one cycle is the same as that of the control group. Multiple cycles are set within the entire charging time T. Figure 4 As shown, Figure 4 It is the SRC1 curve.

[0090] In the SRC2 charging mode, I MAX As the base value. Figure 5 As shown, Figure 5 It is the SRC2 curve.

[0091] Sets a sinusoidal half-wave trend with a specific duty cycle in one cycle. on Indicates the time of a half-sine wave in one cycle, t off Indicates the remaining time in the cycle. Set multiple cycles within the entire charging time T. The peak value of the half-sine wave is calculated by the following formula:

[0092] Assuming a cycle time of t, a half-sine wave peak value of A, and a half-sine wave frequency with a duty cycle of z, it is:

[0093]

[0094] Based on the same charging capacity in one cycle:

[0095]

[0096] The calculation results are:

[0097]

[0098] This time, the control group, SRC1 charging mode with different cycles and rates, and SRC2 charging mode with different duty cycles were selected for simulation. The specific parameters are shown in Table 1, Table 2 and Table 3.

[0099] Experimental groups cycle C1 C2 Control group T 0 1C SRC1-1 0.5 2C 1C SRC1-2 0.8 2C 1C SRC1-3 1 2C 1C SRC1-4 2 2C 1C SRC1-5 4 2C 1C

[0100] Table 1 Charging current waveform design 1

[0101]

[0102]

[0103] Table 2 Charging current waveform design 2

[0104] Experimental groups cycle Duty Cycle Peak size SRC2-1 2 100％ <![CDATA[1.57I MAX ]]> SRC2-2 2 80％ <![CDATA[1.96I MAX ]]> SRC2-3 2 66.7％ <![CDATA[2.36I MAX ]]> SRC2-4 2 50％ <![CDATA[3.14I MAX ]]> SRC2-5 2 25％ <![CDATA[6.28I MAX ]]>

[0105] Table 3 Charging current waveform design 3

[0106] The phase field method is used to simulate the growth of lithium dendrites. One advantage of the phase field method is that it is intuitive, and the simulation results can directly represent the growth of lithium dendrites. By comparing the calculation results of the order parameter over time, the simulation results of the control group and the experimental group can be roughly observed. In addition to direct observation, two quantitative analysis data indicators are also given here, one is the space utilization rate, and the other is the aspect ratio.

[0107] The spatial utilization rate is the ratio of the lithium dendrite area to the area of ​​the calculation domain. The larger the value, the larger the area occupied by the lithium dendrite and the larger the shape. The aspect ratio is the ratio of the height B and width A of the lithium dendrite, such as Figure 6 The aspect ratio represents the sharpness of the lithium dendrite morphology, and the larger the value, the sharper the lithium dendrite.

[0108] In some examples, the effects of different cycles on the morphology of lithium dendrites are simulated according to the data in Table 1. The results of the morphology of lithium dendrites are as follows: Figure 7 shown. Figure 8 The curve of lithium dendrite space utilization under the above simulation conditions is shown. Figure 7Compared with the control group, the experimental group has a significant inhibitory effect, and as the cycle continues to decrease, the number of sinusoidal current cycles increases during the entire charging time, the lithium dendrite morphology is smaller, and the inhibitory effect is better. Figure 8 The same results can be seen in the line graph shown. SRC1-1 has the best inhibition effect, with smaller lithium dendrite height and lateral length, and smoother side branches.

[0109] In some examples, Figure 4 Based on the SCR1 curve shown in Figure 2, the morphological growth of lithium dendrites is simulated by changing the charge rate C1. The parameter settings are shown in Table 2. Fig. 9 The simulation results are shown. The five charging rates shown in the figure all have a significant inhibitory effect on the growth of lithium dendrites. Among them, the charging rate in the SRC1-7 to SRC1-10 modes is greater than 1C, that is, there is a reverse current in each cycle, which is the discharge current. Fig.10 The data shows that under SRC1-7 conditions, the proportion of reverse current to the total current is very small, and the space utilization rate does not change much compared with SCR1-6 conditions, and the suppression effect is not obvious. However, as the proportion of reverse current increases, the space utilization rate decreases significantly, the lithium dendrite morphology is greatly reduced, and the suppression effect is most obvious under SCR1-10 conditions. Increasing the charging current rate increases the suppression effect.

[0110] In some examples, in the SRC2 charging mode, the effects of sine half-wave modes with duty cycles of 100%, 80%, 66.7%, 50% and 25% on the growth of lithium dendrites are simulated. The simulation results are shown in Fig.11 The simulation results show that the SCR2 charging current has a significant inhibitory effect on the growth of lithium dendrites. The growth morphology of lithium dendrites under different duty cycles is not significantly different.

[0111] Fig.12 and Fig.13 The spatial utilization and aspect ratio data of lithium dendrite morphology under different duty cycle conditions are shown respectively. As the duty cycle increases, the spatial utilization shows an upward trend, which means that the lithium dendrite morphology is larger, and the overall change range is around 0.2%. Compared with the first two working conditions, the change is not obvious, and the overall space occupancy is also larger. As the duty cycle increases, the aspect ratio shows a downward trend, and the overall change trend is not obvious.

[0112] In summary, the two sinusoidal function trend charging currents designed in this application have an inhibitory effect on the growth of lithium dendrites. Under the condition of the first curve SCR1, as the function period becomes smaller and the charging rate increases, the inhibitory effect on the lithium dendrite morphology is more obvious. Under the condition of the second curve SCR2, as the duty cycle changes, the inhibitory effect on the lithium dendrite morphology does not change significantly. According to the above description, the SCR1 curve is selected, and the sinusoidal charging current with a period of 0.5 and a charging rate C1 of 2C is charged, and the inhibitory effect on lithium dendrites is most obvious.

[0113] like Fig.14 As shown, the present application proposes a charging control device, comprising:

[0114] An acquisition unit 21 is used to input the current waveform to be analyzed into a simulation model to obtain simulation data information of the current waveform to be analyzed, wherein the simulation model is established based on a phase field model of lithium dendrites, a battery network model, constraint information and a secondary current distribution module;

[0115] A determination unit 22, configured to determine a target charging current based on the simulation data information of the current waveform to be analyzed;

[0116] The control unit 23 is used to control the battery to perform a charging operation according to the target charging current.

[0117] In some examples, the phase field model of lithium dendrites is constructed based on the order parameter equation, the lithium ion diffusion equation and the charge conservation equation.

[0118] In some examples, the order parameter equation is an order parameter equation of a nonlinear model that varies in time and space combined with Butler-Volmer dynamics;

[0119] The above lithium ion diffusion equation is the Nernst-Planck equation;

[0120] The above charge conservation equation is the current density conservation equation described by Poisson's equation.

[0121] In some examples, the battery grid model is a phase field simulation model of the lithium plating morphology in a two-dimensional half-cell electrodeposition system, and the battery network model is discretized using a quadrilateral grid and an adaptive grid technology.

[0122] In some examples, the constraint condition information includes boundary condition information, lithium ion concentration information, and upper and lower boundary potential information.

[0123] In some examples, the secondary current distribution module described above is used to describe the relationship between electrode kinetics and impedance.

[0124] In some examples, the simulation data information includes space utilization and aspect ratio;

[0125] The above-mentioned current waveform to be analyzed is generated based on a sine wave.

[0126] like Fig.15 As shown, an embodiment of the present application also provides an electronic device 300, including a memory 310, a processor 320, and a computer program 311 stored in the memory 310 and executable on the processor, and when the processor 320 executes the computer program 311, the steps of any one of the above-mentioned charging control methods are implemented.

[0127] Since the electronic device introduced in this embodiment is a device used to implement a charging control device in the embodiment of the present application, based on the method introduced in the embodiment of the present application, the technical personnel in this field can understand the specific implementation method of the electronic device of this embodiment and its various variations. Therefore, how the electronic device implements the method in the embodiment of the present application is not introduced in detail here. As long as the equipment used by the technical personnel in this field to implement the method in the embodiment of the present application is within the scope of protection of this application.

[0128] In the specific implementation process, when the computer program 311 is executed by the processor, it can achieve Figure 1 Any implementation manner in the corresponding embodiments.

[0129] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0130] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0131] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0132] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0133] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0134] An embodiment of the present application further provides a computer program product, which includes computer software instructions. When the computer software instructions are executed on a processing device, the processing device executes the process of the charging control method in the corresponding embodiment.

[0135] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can store or a data storage device such as a server or a data center that includes one or more available media integration. The available medium can be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state drive (SSD)), etc.

[0136] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0137] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0138] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0139] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0140] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program codes.

[0141] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A charging control method, characterized in that: include: Inputting the current waveform to be analyzed into a simulation model to obtain simulation data information of the current waveform to be analyzed, wherein the simulation model is established based on a phase field model of lithium dendrites, a battery network model, constraint information and a secondary current distribution module; Determine a target charging current based on the simulation data information of the current waveform to be analyzed; The battery is charged by controlling the target charging current.

2. The charging control method according to claim 1, characterized in that: The phase field model of lithium dendrites is constructed based on the order parameter equation, the lithium ion diffusion equation and the charge conservation equation.

3. The charging control method according to claim 2, characterized in that: The order parameter equation is a nonlinear model of changes in time and space combined with the order parameter equation of Butler-Volmer dynamics; The lithium ion diffusion equation is the Nernst-Planck equation; The charge conservation equation is a current density conservation equation described by Poisson's equation.

4. The charging control method according to claim 1, characterized in that: The battery grid model is a phase field simulation model of the lithium plating morphology in a two-dimensional half-cell electrodeposition system. The battery network model is discretized using quadrilateral grids and an adaptive grid technology.

5. The charging control method according to claim 1, characterized in that: The constraint condition information includes boundary condition information, lithium ion concentration information, and upper and lower boundary potential information.

6. The charging control method according to claim 1, characterized in that: The secondary current distribution module is used to describe the relationship between electrode kinetics and impedance.

7. The charging control method according to claim 1, characterized in that: The simulation data information includes space utilization and aspect ratio; The current waveform to be analyzed is generated based on a sine wave.

8. A charging control device, characterized in that: include: An acquisition unit, used for inputting the current waveform to be analyzed into a simulation model to obtain simulation data information of the current waveform to be analyzed, wherein the simulation model is established based on a phase field model of lithium dendrites, a battery network model, constraint information and a secondary current distribution module; A determination unit, configured to determine a target charging current based on the simulation data information of the current waveform to be analyzed; The control unit is used to control the battery to perform a charging operation according to the target charging current.

9. An electronic device, comprising: A memory and a processor, wherein the processor is used to implement the steps of the charging control method according to any one of claims 1 to 7 when executing a computer program stored in the memory.

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

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